Proposed Rule2021-17496
Corporate Average Fuel Economy Standards for Model Years 2024-2026 Passenger Cars and Light Trucks
Primary source
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Published
September 3, 2021
Issuing agencies
Transportation DepartmentNational Highway Traffic Safety Administration
Abstract
NHTSA, on behalf of the Department of Transportation, is proposing revised fuel economy standards for passenger cars and light trucks for model years 2024-2026. On January 20, 2021, President Biden signed an Executive order (E.O.) entitled, "Protecting Public Health and the Environment and Restoring Science To Tackle the Climate Crisis." In it, the President directed that "The Safer Affordable Fuel-Efficient (SAFE) Vehicles Rule for Model Years 2021-2026 Passenger Cars and Light Trucks" (hereafter, "the 2020 final rule") be immediately reviewed for consistency with our Nation's abiding commitment to empower our workers and communities; promote and protect our public health and the environment; and conserve our national treasures and monuments, places that secure our national memory. President Biden further directed that the 2020 final rule be reviewed at once and that (in this case) the Secretary of Transportation consider "suspending, revising, or rescinding" it, via a new proposal, by July 2021. Because of the President's direction in the E.O., NHTSA reexamined the 2020 final rule under its authority to set corporate average fuel economy (CAFE) standards. In doing so, NHTSA tentatively concluded that the fuel economy standards set in 2020 should be revised so that they increase at a rate of 8 percent year over year for each model year from 2024 through 2026, for both passenger cars and light trucks. This responds to the agency's statutory mandate to improve energy conservation. This proposal also makes certain minor changes to fuel economy reporting requirements.
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[Federal Register Volume 86, Number 169 (Friday, September 3, 2021)]
[Proposed Rules]
[Pages 49602-49883]
From the Federal Register Online via the Government Publishing Office [<a href="http://www.gpo.gov">www.gpo.gov</a>]
[FR Doc No: 2021-17496]
[[Page 49601]]
Vol. 86
Friday,
No. 169
September 3, 2021
Part II
Department of Transportation
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National Highway Traffic Safety Administration
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49 CFR Parts 531, 533 et al.
Corporate Average Fuel Economy Standards for Model Years 2024-2026
Passenger Cars and Light Trucks; Proposed Rule
Federal Register / Vol. 86, No. 169 / Friday, September 3, 2021 /
Proposed Rules
[[Page 49602]]
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DEPARTMENT OF TRANSPORTATION
National Highway Traffic Safety Administration
49 CFR Parts 531, 533, 536, and 537
[NHTSA-2021-0053]
RIN 2127-AM34
Corporate Average Fuel Economy Standards for Model Years 2024-
2026 Passenger Cars and Light Trucks
AGENCY: National Highway Traffic Safety Administration (NHTSA),
Department of Transportation (DOT).
ACTION: Notice of proposed rulemaking.
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SUMMARY: NHTSA, on behalf of the Department of Transportation, is
proposing revised fuel economy standards for passenger cars and light
trucks for model years 2024-2026. On January 20, 2021, President Biden
signed an Executive order (E.O.) entitled, ``Protecting Public Health
and the Environment and Restoring Science To Tackle the Climate
Crisis.'' In it, the President directed that ``The Safer Affordable
Fuel-Efficient (SAFE) Vehicles Rule for Model Years 2021-2026 Passenger
Cars and Light Trucks'' (hereafter, ``the 2020 final rule'') be
immediately reviewed for consistency with our Nation's abiding
commitment to empower our workers and communities; promote and protect
our public health and the environment; and conserve our national
treasures and monuments, places that secure our national memory.
President Biden further directed that the 2020 final rule be reviewed
at once and that (in this case) the Secretary of Transportation
consider ``suspending, revising, or rescinding'' it, via a new
proposal, by July 2021. Because of the President's direction in the
E.O., NHTSA reexamined the 2020 final rule under its authority to set
corporate average fuel economy (CAFE) standards. In doing so, NHTSA
tentatively concluded that the fuel economy standards set in 2020
should be revised so that they increase at a rate of 8 percent year
over year for each model year from 2024 through 2026, for both
passenger cars and light trucks. This responds to the agency's
statutory mandate to improve energy conservation. This proposal also
makes certain minor changes to fuel economy reporting requirements.
DATES: Comments: Comments are requested on or before October 26, 2021.
In compliance with the Paperwork Reduction Act, NHTSA is also seeking
comment on a revision to an existing information collection. For
additional information, see the Paperwork Reduction Act Section under
Section IX, below. All comments relating to the information collection
requirements should be submitted to NHTSA and to the Office of
Management and Budget (OMB) at the address listed in the ADDRESSES
section on or before October 26, 2021. See the SUPPLEMENTARY
INFORMATION section on ``Public Participation,'' below, for more
information about written comments.
Public Hearings: NHTSA will hold one virtual public hearing during
the public comment period. The agency will announce the specific date
and web address for the hearing in a supplemental Federal Register
notification. The agency will accept oral and written comments on the
rulemaking documents and will also accept comments on the Supplemental
Environmental Impact Statement (SEIS) at this hearing. The hearing will
start at 9 a.m. Eastern standard time and continue until everyone has
had a chance to speak. See the SUPPLEMENTARY INFORMATION section on
``Public Participation,'' below, for more information about the public
hearing.
ADDRESSES: You may send comments, identified by Docket No. NHTSA-2021-
0053, by any of the following methods:
<bullet> Federal eRulemaking Portal: <a href="http://www.regulations.gov">http://www.regulations.gov</a>.
Follow the instructions for submitting comments.
<bullet> Fax: (202) 493-2251.
<bullet> Mail: Docket Management Facility, M-30, U.S. Department of
Transportation, West Building, Ground Floor, Rm. W12-140, 1200 New
Jersey Avenue SE, Washington, DC 20590.
<bullet> Hand Delivery: Docket Management Facility, M-30, U.S.
Department of Transportation, West Building, Ground Floor, Rm. W12-140,
1200 New Jersey Avenue SE, Washington, DC 20590, between 9 a.m. and 4
p.m. Eastern Time, Monday through Friday, except Federal holidays.
Comments on the proposed information collection requirements should
be submitted to: Office of Management and Budget at <a href="http://www.reginfo.gov/public/do/PRAMain">www.reginfo.gov/public/do/PRAMain</a>. To find this particular information collection,
select ``Currently under Review--Open for Public Comment'' or use the
search function. NHTSA requests that comments sent to the OMB also be
sent to the NHTSA rulemaking docket identified in the heading of this
document.
Instructions: All submissions received must include the agency name
and docket number or Regulatory Information Number (RIN) for this
rulemaking. All comments received will be posted without change to
<a href="http://www.regulations.gov">http://www.regulations.gov</a>, including any personal information
provided. For detailed instructions on sending comments and additional
information on the rulemaking process, see the ``Public Participation''
heading of the SUPPLEMENTARY INFORMATION section of this document.
Docket: For access to the dockets or to read background documents
or comments received, please visit <a href="http://www.regulations.gov">http://www.regulations.gov</a>, and/or
Docket Management Facility, M-30, U.S. Department of Transportation,
West Building, Ground Floor, Rm. W12-140, 1200 New Jersey Avenue SE,
Washington, DC 20590. The Docket Management Facility is open between 9
a.m. and 4 p.m. Eastern Time, Monday through Friday, except Federal
holidays.
FOR FURTHER INFORMATION CONTACT: Rebecca Schade, NHTSA Office of Chief
Counsel, National Highway Traffic Safety Administration, 1200 New
Jersey Avenue SE, Washington, DC 20590; email: <a href="/cdn-cgi/l/email-protection#27554245424444460954444f4643426743485309404851"><span class="__cf_email__" data-cfemail="6a180f080f09090b441909020b0e0f2a0e051e440d051c">[email protected]</span></a>.
SUPPLEMENTARY INFORMATION:
Does this action apply to me?
This action affects companies that manufacture or sell new
passenger automobiles (passenger cars) and non-passenger automobiles
(light trucks) as defined under NHTSA's CAFE regulations.\1\ Regulated
categories and entities include:
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\1\ ``Passenger car'' and ``light truck'' are defined in 49 CFR
part 523.
[[Page 49603]]
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NAICS Codes Examples of potentially
Category \A\ regulated entities
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Industry....................... 335111 Motor Vehicle
Manufacturers.
336112
Industry....................... 811111 Commercial Importers of
Vehicles and Vehicle
Components.
811112
811198
423110
Industry....................... 335312 Alternative Fuel
Vehicle Converters.
336312
336399
811198
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\A\ North American Industry Classification System (NAICS).
This list is not intended to be exhaustive, but rather provides a
guide regarding entities likely to be regulated by this action. To
determine whether particular activities may be regulated by this
action, you should carefully examine the regulations. You may direct
questions regarding the applicability of this action to the person
listed in FOR FURTHER INFORMATION CONTACT.
I. Executive Summary
NHTSA, on behalf of the Department of Transportation, is proposing
to amend standards regulating corporate average fuel economy (CAFE) for
passenger cars and light trucks for model years (MYs) 2024-2026. This
proposal responds to NHTSA's statutory obligation to set maximum
feasible CAFE standards to improve energy conservation, and to
President Biden's directive in Executive Order 13990 of January 20,
2021 that ``The Safer Affordable Fuel-Efficient (SAFE) Vehicles Rule
for Model Years 2021-2026 Passenger Cars and Light Trucks'', 2020 final
rule or 2020 CAFE rule (85 FR 24174 (April 30, 2020)), be immediately
reviewed for consistency with our Nation's abiding commitment to
promote and protect our public health and the environment, among other
things. NHTSA undertook that review immediately, and this proposal is
the result of that process.
The proposed amended CAFE standards would increase in stringency
from MY 2023 levels by 8 percent per year, for both passenger cars and
light trucks over MYs 2024-2026. NHTSA tentatively concludes that this
level is maximum feasible for these model years, as discussed in more
detail in Section VI, and seeks comment on that conclusion. The
proposal considers a range of regulatory alternatives, consistent with
NHTSA's obligations under the National Environmental Policy Act (NEPA)
and Executive Order 12866. While E.O. 13990 directed the review of CAFE
standards for MYs 2021-2026, statutory lead time requirements mean that
the soonest model year that can currently be amended in the CAFE
program is MY 2024. The proposed standards would remain vehicle
footprint-based, like the CAFE standards in effect since MY 2011.
Recognizing that many readers think about CAFE standards in terms of
the miles per gallon (mpg) values that the standards are projected to
eventually require, NHTSA currently projects that the proposed
standards would require, on an average industry fleet-wide basis,
roughly 48 mpg in MY 2026. NHTSA notes both that real-world fuel
economy is generally 20-30 percent lower than the estimated required
CAFE level stated above, and also that the actual CAFE standards are
the footprint target curves for passenger cars and light trucks,
meaning that ultimate fleet-wide levels will vary depending on the mix
of vehicles that industry produces for sale in those model years. Table
I-1 shows the incremental differences in stringency levels for
passenger cars and light trucks, by regulatory alternative, in the
model years subject to regulation.
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This proposal is significantly different from the conclusion that
NHTSA reached in the 2020 final rule, but this is because important
facts have changed, and because NHTSA has reconsidered how to balance
the relevant statutory considerations in light of those facts. NHTSA
tentatively concludes that significantly more stringent standards are
maximum feasible. Contrary to the 2020 final rule, NHTSA recognizes
that the need of the United States to conserve energy must include
serious consideration of the energy security risks of continuing to
consume oil, which more stringent fuel economy standards can reduce.
Reducing our Nation's climate impacts can also benefit our national
security. Additionally, at least part of the automobile industry
appears increasingly convinced that improving fuel economy and reducing
greenhouse gas (GHG) emissions is a growth market for them, and that
the market rewards investment in advanced technology. Nearly all auto
manufacturers have announced forthcoming new higher fuel-economy and
electric vehicle models, and five major manufacturers voluntarily bound
themselves to stricter GHG requirements than set forth by NHTSA and the
Environmental Protection Agency (EPA) in 2020 through contractual
agreements with the State of California, which will result in their
achieving fuel economy levels well above the standards set forth in the
2020 final rule. These companies are sophisticated, for-profit
enterprises. If they are taking these steps, NHTSA can be more
confident than the agency was in 2020 that the market is getting ready
to make the leap to significantly higher fuel economy. The California
Framework and the clear planning by industry to migrate toward more
advanced fuel economy technologies are evidence of the practicability
of more stringent standards. Moreover, more stringent CAFE standards
will help to encourage industry to continue improving the fuel economy
of all vehicles, rather than simply producing a few electric vehicles,
such that all Americans can benefit from higher fuel economy and save
money on fuel. NHTSA cannot consider the fuel economy of dedicated
alternative fuel vehicles like battery electric vehicles when
determining maximum feasible standards, but the fact that industry
increasingly appears to believe that there is a market for these
vehicles is broader evidence of market (and consumer) interest in fuel
economy, which is relevant to NHTSA's determination of whether more
stringent standards would be economically practicable. For all of these
reasons, NHTSA tentatively concludes that standards that increase at 8
percent per year are maximum feasible.
This proposal is also different from the 2020 final rule in that it
is issued by NHTSA alone, and EPA has issued a separate proposal. The
primary reason for this is the difference in statutory authority--EPA
does not have the same lead time requirements as NHTSA and is thus able
to amend MY 2023 in addition to MYs 2024-2026. An important consequence
of this is that EPA's proposed rate of stringency increase, after
taking a big leap in MY 2023, looks slower than NHTSA's over the same
time period. NHTSA emphasizes, however, that the proposed standards are
what NHTSA believes best fulfills our statutory directive of energy
conservation, and in the context of the EPA standards, the analysis we
have done is tackling the core question of whether compliance with both
standards should be achievable with the same vehicle fleet, after
manufacturers fully understand the requirements from both proposals.
The differences in what the two agencies' standards require become
smaller each year, until alignment is achieved. While NHTSA recognizes
that the last several CAFE standard rulemakings have been issued
jointly with EPA, and that issuing separate proposals represents a
change in approach, the agencies worked together to avoid
inconsistencies and to create proposals that would continue to allow
manufacturers to build a single fleet of vehicles to meet both
agencies' proposed standards. Additionally, and importantly, NHTSA has
also considered and accounted for California's Zero Emission Vehicle
(ZEV) program (and its adoption by a number of other states) in
developing the baseline for this proposal, and has accounted for the
aforementioned ``Framework Agreements'' between California and BMW,
Ford, Honda, Volkswagen of America (VWA), and Volvo, which are
national-level GHG standards to which these companies committed for
several model years.
A number of other improvements and updates have been made to the
analysis since the 2020 final rule. Table I-2 summarizes these, and
they are discussed in much more detail below and in the documents
accompanying this preamble.
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NHTSA estimates that this proposal could reduce average
undiscounted fuel outlays over the lifetimes of MY 2029 vehicles by
about $1,280, while increasing the average cost of those vehicles by
about $960 over the baseline described above. With the social cost of
carbon (SCC) discounted at 2.5 percent and other benefits and costs
discounted at 3 percent, for the three affected model years NHTSA finds
$65.8 billion in benefits attributable to the proposed standards and
$37.4 billion in proposed costs so that present net benefits could be
$28.4 billion.\2\ Applied to the entire fleet for MYs 1981-2029, NHTSA
estimates $120 billion in costs and $121
[[Page 49606]]
billion in benefits attributable to the proposed standards, such that
the present value of aggregate net benefits to society could be $1
billion. Like any analysis of this magnitude attempting to forecast
future effects of current policies, significant uncertainty exists
about many key inputs. Changes in the price of fuel or in the social
cost of carbon could dramatically change benefits, for example, and
readers should expect that the eventual final rule will reflect any
updates made to those (and many other) values that occur between now
and then. It is also worth stressing that NHTSA's statutory authority
requires that its standards be maximum feasible, taking into account
four statutory factors. While NHTSA's estimates of costs and benefits
are important considerations, it is the maximum feasible analysis that
controls the setting of CAFE standards.
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\2\ As discussed in Section III.G.2.b), NHTSA has discounted the
SCC at 2.5% when other benefits and costs are discounted at 3% but
seeks comment on this approach.
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Like many other types of regulations, CAFE standards apply only to
new vehicles. The costs attributable to new CAFE standards are thus
``front-loaded,'' because they result primarily from the application of
fuel-saving technology to new vehicles. On the other hand, the impact
of new CAFE standards on fuel consumption and greenhouse gases--and the
associated benefits to society--occur over an extended time, as drivers
buy, use, and eventually scrap these new vehicles. By accounting for
many model years and extending well into the future (2050), our
analysis accounts for these differing patterns in impacts, benefits,
and costs. Our analysis also accounts for the potential that, by
changing new vehicle prices and fuel economy levels, CAFE standards
could indirectly impact the operation of vehicles produced before or
after the model years (2024-2026) for which we are proposing new CAFE
standards. This means that some of the proposal's impacts and
corresponding benefits and costs are actually attributable to indirect
impacts on vehicles produced before and after model years 2024-2026.
The bulk of our analysis considers a ``model year'' (MY)
perspective that considers the lifetime impacts attributable to all
vehicles produced prior to model year 2030, accounting for the
operation of these vehicles over their entire useful lives (with some
model year 2029 vehicles estimated to be in service as late as 2068).
This approach emphasizes the role of model years 2024-2026, while
accounting for the potential that it may take manufacturers a few
additional years to produce fleets fully responsive to the proposed MY
2026 standards, and for the potential that the proposal could induce
some changes in the operation of vehicles produced prior to MY 2024.
Our analysis also considers a ``calendar year'' (CY) perspective
that includes the annual impacts attributable to all vehicles estimated
to be in service in each calendar year for which our analysis includes
a representation of the entire registered light-duty fleet. For this
NPRM, this calendar year perspective covers each of calendar years
2021-2050, with differential impacts accruing as early as model year
2023. Compared to the ``model year'' perspective, this calendar year
perspective emphasizes model years of vehicles produced in the longer
term, beyond those model years for which standards are currently being
proposed. Table I-3 summarizes estimates of selected physical impacts
viewed from each of these two perspectives, as well as corresponding
estimates of the present values of cumulative benefits, costs, and net
benefits.
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Finally, for purposes of comparing the benefits and costs of new
CAFE standards to the benefits and costs of other Federal regulations,
policies, and programs, we have computed ``annualized'' benefits and
costs. These are the annual averages of the cumulative benefits and
costs over the covered model or calendar years, after expressing these
in present value terms.
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As discussed in detail below, the monetized estimated costs and
benefits of this proposal are relevant and important to the agency's
tentative conclusion, but they are not the whole of the conclusion.
[[Page 49609]]
Additionally, although NHTSA is prohibited from considering the
availability of certain flexibilities in making our determination about
the levels of CAFE standards that would be maximum feasible,
manufacturers have a variety of flexibilities available to them to
reduce their compliance burden. Table I-10 through Table I-13 below
summarizes available compliance flexibilities. NHTSA seeks comment on
whether to retain non-statutory flexibilities for the final rule.
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BILLING CODE 4910-59-C
NHTSA recognizes that the lead time for this proposal is shorter
than past rulemakings have provided, and that the economy and the
country are in the process of recovering from a global pandemic and the
resulting economic distress. At the same time, NHTSA also recognizes
that at least parts of the industry are nonetheless stepping up their
product offerings and releasing more and more high fuel-economy vehicle
models, and many companies did not deviate significantly from product
plans established in response to the standards set forth in the 2012
final rule (77 FR 62624, Oct. 15, 2012) and confirmed by EPA in its
January 2017 Final Determination. With these considerations in mind,
NHTSA is proposing to amend the CAFE standards for MYs 2024-2026.
NHTSA, like any other Federal agency, is afforded an opportunity to
reconsider prior views and, when warranted, to adopt new positions.
Indeed, as a matter of good governance, agencies should revisit their
positions when appropriate, especially to ensure that their actions and
regulations reflect legally sound interpretations of the agency's
authority and remain consistent with the agency's views and practices.
As a matter of law, ``an Agency is entitled to change its
interpretation of a statute.'' \3\ Nonetheless, ``[w]hen an Agency
adopts a materially changed interpretation of a statute, it must in
addition provide a `reasoned analysis' supporting its decision to
revise its interpretation.'' \4\ The analysis presented in this
preamble and in the accompanying Technical Support Document (TSD),
Preliminary Regulatory Impact Analysis (PRIA), Supplemental
Environmental Impact Statement (SEIS), CAFE Model documentation, and
extensive rulemaking docket fully supports the proposed decision and
revised balancing of the statutory factors for MYs 2024-2026 standards.
NHTSA seeks comment on the entirety of the rulemaking record.
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\3\ Phoenix Hydro Corp. v. FERC, 775 F.2d 1187, 1191 (D.C. Cir.
1985).
\4\ Alabama Educ. Ass'n v. Chao, 455 F.3d 386, 392 (D.C. Cir.
2006) (quoting Motor Vehicle Mfrs. Ass'n of U.S., Inc. v. State Farm
Mut. Auto. Ins. Co., 463 U.S. 29, 57 (1983)); see also Encino
Motorcars, LLC v. Navarro, 136 S.Ct. 2117, 2125 (2016) (``Agencies
are free to change their existing policies as long as they provide a
reasoned explanation for the change.'') (citations omitted).
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II. Introduction
In this notice of proposed rulemaking (NPRM), NHTSA is proposing to
revise CAFE standards for model years (MYs) 2024-2026. On January 20,
2021, the President signed Executive Order (E.O.) 13990, ``Protecting
Public Health and the Environment and Restoring Science To Tackle the
Climate Crisis.'' \5\ In it, the President directed that ``The Safer
Affordable Fuel-Efficient (SAFE) Vehicles Rule for Model Years 2021-
2026 Passenger Cars and Light Trucks'' (hereafter, ``the 2020 final
rule''), 85 FR 24174 (April 30, 2020), must be immediately reviewed for
consistency with our Nation's abiding commitment to empower our workers
and communities; promote and protect our public health and the
environment; and conserve our national treasures and monuments, places
that secure our national memory. E.O. 13990 states expressly that the
Administration prioritizes listening to the science, improving public
health and protecting the environment, reducing greenhouse gas
emissions, and improving environmental justice while creating well-
paying union jobs. The E.O. thus directs that the 2020 final rule be
reviewed at once and that (in this case) the Secretary of
Transportation consider ``suspending, revising, or rescinding'' it, via
an NPRM, by July 2021.\6\
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\5\ 86 FR 7037 (Jan. 25, 2021).
\6\ Id., Sec. 2(a)(ii).
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Section 32902(g)(1) of Title 49, United States Code allows the
Secretary (by delegation to NHTSA) to prescribe regulations amending an
average fuel economy standard prescribed under 49 U.S.C. 32902(a), like
those prescribed in the 2020 final rule, if the amended standard meets
the requirements of 32902(a). The Secretary's authority to set fuel
economy standards is delegated to NHTSA at 49 CFR 1.95(a); therefore,
in this NPRM, NHTSA proposes revised fuel economy standards for MYs
2024-2026. Section 32902(g)(2) states that when the amendment makes an
average fuel economy standard more stringent, it must be prescribed at
least 18 months before the beginning of the model year to which the
amendment applies. NHTSA generally calculates the 18-month lead time
requirement as April of the calendar year prior to the start of the
model year. Thus, 18 months before MY 2023 would be April 2021, because
MY 2023 begins in September 2022. Because of this lead time
requirement, NHTSA is not proposing to amend the CAFE standards for MYs
2021-2023, even though the 2020 final rule also covered those model
years. For purposes of the CAFE program, the 2020 final rule's
standards for MYs 2021-2023 will remain in effect.
For the MYs for which there is statutory lead time to amend the
standards, however, NHTSA is proposing amendments to the currently
applicable fuel economy standards. Although only one year has passed
since the 2020 final rule, the agency believes it is reasonable and
appropriate to revisit the CAFE standards for MYs 2024-2026. In
particular, the agency has further considered the serious adverse
effects on energy conservation that the standards finalized in 2020
would cause
[[Page 49611]]
as compared to the proposed standards. The need of the U.S. to conserve
energy is greater than understood in the 2020 final rule. In addition,
standards that are more stringent than those that were finalized in
2020 appear economically practicable. Nearly all auto manufacturers
have announced forthcoming new advanced technology vehicle models with
higher fuel economy, making strong public commitments that mirror those
of the Administration. Five major manufacturers voluntarily bound
themselves to stricter national-level GHG requirements as part of the
California Framework agreement. Meanwhile, certain facts on the ground
remain similar to what was before NHTSA in the prior analysis--gas
prices still remain relatively low in the U.S., for example, and while
light-duty vehicle sales fell sharply in MY 2020, the vehicles that did
sell tended to be, on average, larger, heavier, and more powerful, all
factors that increase fuel consumption. However, the renewed focus on
addressing energy conservation and the industry's apparent ability to
meet more stringent standards show that a rebalancing of the EPCA
factors, and the proposal of more stringent standards, is appropriate
for model years 2024-2026.
The following sections introduce the proposal in more detail.
A. What is NHTSA proposing?
NHTSA is proposing to set CAFE standards for passenger cars and
light trucks manufactured for sale in the United States in MYs 2024-
2026. Passenger cars are generally sedans, station wagons, and two-
wheel drive crossovers and sport utility vehicles (CUVs and SUVs),
while light trucks are generally four-wheel drive vehicles, larger/
heavier two-wheel drive sport utility vehicles, pickups, minivans, and
passenger/cargo vans.\7\ The proposed standards would increase at 8
percent per year for both cars and trucks, and are represented by
regulatory Alternative 2 in the agency's analysis. The proposed
standards would be defined by a mathematical equation that represents a
constrained linear function relating vehicle footprint to fuel economy
targets for both cars and trucks; vehicle footprint is roughly measured
as the rectangle that is made by the four points where the vehicle's
tires touch the ground. Generally, passenger cars will have more
stringent targets than light trucks regardless of footprint, and
smaller vehicles will have more stringent targets than larger vehicles.
No individual vehicle or vehicle model need meet its target exactly,
but a manufacturer's compliance is determined by how its average fleet
fuel economy compares to the average fuel economy of the targets of the
vehicles it manufactures.
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\7\ ``Passenger car'' and ``light truck'' are defined at 49 CFR
part 523.
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The proposed target curves \8\ for passenger cars and light trucks
are as follows; curves for MYs 2020-2023 are included in Figure II-1
and Figure II-2 for context.
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\8\ NHTSA underscores that the equations and coefficients
defining the curves are what the agency is proposing, and not the
mpg numbers that the agency currently estimates could result from
manufacturers complying with the curves. Because the estimated mpg
numbers are an effect of the proposed curves, they are presented in
the following section.
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BILLING CODE 4910-59-C
NHTSA is also proposing to amend the minimum domestic passenger car
CAFE standards for MYs 2024-2026. The provision at 49 U.S.C.
32902(b)(4) requires NHTSA to project the minimum standard when it
promulgates passenger car standards for a model year, so it is
appropriate to revisit the minimum standards at this time. NHTSA is
proposing to retain the 1.9 percent offset used in the 2020 final rule,
such that the minimum domestic passenger car standard would be as shown
in Table II-1.
[GRAPHIC] [TIFF OMITTED] TP03SE21.015
The next section describes some of the effects that NHTSA estimates
would follow from this proposal, including how the curves shown above
translate to estimated average mile per gallon requirements for the
industry.
B. What does NHTSA estimate the effects of proposing this would be?
As for past CAFE rulemakings, NHTSA has used the CAFE Model to
estimate the effects of proposed CAFE standards, and of other
regulatory alternatives under consideration. Some inputs to the CAFE
Model are derived from other models, such as Argonne National
Laboratory's ``Autonomie'' vehicle simulation tool and Argonne's
Greenhouse gases, Regulated Emissions, and Energy use in Transportation
(GREET) fuel-cycle emissions analysis model, the U.S. Energy
Information Administration's (EIA's) National Energy Modeling System
(NEMS), and EPA's Motor Vehicle Emission Simulator (MOVES) vehicle
emissions model. Especially given the scope of the
[[Page 49614]]
NHTSA's analysis (through model years 2050, with driving of model year
2029 vehicles accounted for through calendar year 2068), these inputs
involve a multitude of uncertainties. For example, a set of inputs with
significant uncertainty could include future population and economic
growth, future gasoline and electricity prices, future petroleum market
characteristics (e.g., imports and exports), future battery costs,
manufacturers' future responses to standards and fuel prices, buyers'
future responses to changes in vehicle prices and fuel economy levels,
and future emission rates for ``upstream'' processes (e.g., refining,
finished fuel transportation, electricity generation). Considering that
all of this is uncertain from a 2021 vantage point, NHTSA underscores
that all results of this analysis are, in turn, uncertain, and simply
represent the agency's best estimates based on the information
currently before us.
NHTSA estimates that this proposal would increase the eventual \9\
average of manufacturers' CAFE requirements to about 48 mpg by 2026
rather than, under the No-Action Alternative (i.e., the baseline
standards issued in 2020), about 40 mpg. For passenger cars, the
average in 2026 is estimated to reach about 58 mpg, and for light
trucks, about 42. This compares with 47 mpg and 34 mpg for cars and
trucks, respectively, under the No-Action Alternative.
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\9\ Here, ``eventual'' means by MY 2029, after most of the fleet
will have been redesigned under the MY 2026 standards. NHTSA allows
the CAFE Model to continue working out compliance solutions for the
regulated model years for three model years after the last regulated
model year, in recognition of the fact that manufacturers do not
comply perfectly with CAFE standards in each model year.
[GRAPHIC] [TIFF OMITTED] TP03SE21.016
Because manufacturers do not comply exactly with each standard in
each model year, but rather focus their compliance efforts when and
where it is most cost-effective to do so, ``estimated achieved'' fuel
economy levels differ somewhat from ``estimated required'' levels for
each fleet, for each year. NHTSA estimates that the industry-wide
average fuel economy achieved in MY 2029 could increase from about 44
mpg under the No-Action Alternative to about 49 mpg under the proposal.
[GRAPHIC] [TIFF OMITTED] TP03SE21.017
As discussed above, NHTSA's analysis--unlike its previous CAFE
analyses--estimates manufacturers' potential responses to the combined
effect of CAFE standards and separate CO<INF>2</INF> standards
(including agreements some manufacturers have reached with California),
ZEV mandates, and fuel prices. Together, the aforementioned regulatory
programs are more binding than any single program considered in
isolation, and this analysis, like past analyses, shows some estimated
overcompliance with the proposed CAFE standards, albeit by much less
than what was shown in the NPRM that preceded the 2020 final rule, and
any overcompliance is highly manufacturer-dependent.
Expressed as equivalent required and achieved average
CO<INF>2</INF> levels (using 8887 grams of CO<INF>2</INF> per gallon of
gasoline vehicle certification fuel), the above CAFE levels appear as
shown in Table II-4 and Table II-5.
[GRAPHIC] [TIFF OMITTED] TP03SE21.018
[[Page 49615]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.019
Average requirements and achieved CAFE levels would ultimately
depend on manufacturers' and consumers' responses to standards,
technology developments, economic conditions, fuel prices, and other
factors.
NHTSA estimates that over the lives of vehicles produced prior to
MY 2030, the proposal would save about 50 billion gallons of gasoline
and increase electricity consumption (as the percentage of electric
vehicles increases over time) by about 275 terawatts (TWh), compared to
levels of gasoline and electricity consumption NHTSA projects would
occur under the baseline standards (i.e., the No-Action Alternative).
[GRAPHIC] [TIFF OMITTED] TP03SE21.020
NHTSA's analysis also estimates total annual consumption of fuel by
the entire on-road fleet from calendar year 2020 through calendar year
2050. On this basis, gasoline and electricity consumption by the U.S.
light-duty vehicle fleet evolves as shown in Figure II-3 and Figure II-
4, each of which shows projections for the No-Action Alternative
(Alternative 0, i.e., the baseline), Alternative 1, Alternative 2 (the
proposal), and Alternative 3.
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[[Page 49616]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.021
[[Page 49617]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.022
Accounting for emissions from both vehicles and upstream energy
sector processes (e.g., petroleum refining and electricity generation),
NHTSA estimates that the proposal would reduce greenhouse gas emissions
by about 465 million metric tons of carbon dioxide (CO<INF>2</INF>),
about 500 thousand metric tons of methane (CH<INF>4</INF>), and about
12 thousand tons of nitrous oxide (N<INF>2</INF>O).
[GRAPHIC] [TIFF OMITTED] TP03SE21.023
As for fuel consumption, NHTSA's analysis also estimates annual
emissions attributable to the entire on-road fleet from calendar year
2020 through calendar year 2050. Also accounting for both vehicles and
upstream processes, NHTSA estimates that CO<INF>2</INF> emissions could
evolve over time as shown in Figure II-5, which accounts for both
emissions from both vehicles and upstream processes.
[[Page 49618]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.024
Estimated emissions of methane and nitrous oxides follow similar
trends. As discussed in the TSD, PRIA, and this NPRM, NHTSA has
performed two types of supporting analysis. This NPRM and PRIA focus on
the ``standard setting'' analysis, which sets aside the potential that
manufacturers could respond to standards by using compliance credits or
introducing new alternative fuel vehicle (including BEVs) models during
the ``decision years'' (for this NPRM, 2024, 2025, and 2026). The
accompanying SEIS focuses on an ``unconstrained'' analysis, which does
not set aside these potential manufacturer actions. The SEIS presents
much more information regarding projected GHG emissions, as well as
model-based estimates of corresponding impacts on several measures of
global climate change.
Also accounting for vehicular and upstream emissions, NHTSA has
estimated annual emissions of most criteria pollutants (i.e.,
pollutants for which EPA has issued National Ambient Air Quality
Standards). NHTSA estimates that under each regulatory alternative,
annual emissions of carbon monoxide (CO), volatile organic compounds
(VOC), nitrogen oxide (NO<INF>X</INF>), and fine particulate matter
(PM<INF>2.5</INF>) attributable to the light-duty on-road fleet will
decline dramatically between 2020 and 2050, and that emissions in any
given year could be very nearly the same under each regulatory
alternative. For example, Figure II-6 shows NHTSA's estimate of future
NO<INF>X</INF> emissions under each alternative.
[[Page 49619]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.025
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On the other hand, as discussed in the PRIA and SEIS, NHTSA
projects that annual SO<INF>2</INF> emissions attributable to the
light-duty on-road fleet could increase modestly under the action
alternatives, because, as discussed above, NHTSA projects that each of
the action alternatives could lead to greater use of electricity (for
PHEVs and BEVs). The adoption of actions--such as actions prompted by
President Biden's Executive order directing agencies to develop a
Federal Clean Electricity and Vehicle Procurement Strategy--to reduce
electricity generation emission rates beyond projections underlying
NHTSA's analysis (discussed in the TSD) could dramatically reduce
SO<INF>2</INF> emissions under all regulatory alternatives considered
here.\10\
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\10\ <a href="https://www.whitehouse.gov/briefing-room/presidential-actions/2021/01/27/executive-order-on-tackling-the-climate-crisis-at-home-and-abroad/">https://www.whitehouse.gov/briefing-room/presidential-actions/2021/01/27/executive-order-on-tackling-the-climate-crisis-at-home-and-abroad/</a>, accessed June 17, 2021.
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For the ``standard setting'' analysis, the PRIA accompanying this
NPRM provides additional detail regarding projected criteria pollutant
emissions and health effects, as well as the inclusion of these impacts
in this benefit-cost analysis. For the ``unconstrained'' or ``EIS''
type of analysis, the SEIS accompanying this NPRM presents much more
information regarding projected criteria pollutant emissions, as well
as model-based estimates of corresponding impacts on several measures
of urban air quality and public health. As mentioned above, these
estimates of criteria pollutant emissions are based on a complex
analysis involving interacting simulation techniques and a myriad of
input estimates and assumptions. Especially extending well past 2040,
the analysis involves a multitude of uncertainties. Therefore, actual
criteria pollutant emissions could ultimately be different from NHTSA's
current estimates.
To illustrate the effectiveness of the technology added in response
to this proposal, Table II-8 presents NHTSA's estimates for increased
vehicle cost and lifetime fuel expenditures if we assumed the
behavioral response to the lower cost of driving were zero.\11\ These
numbers are presented in lieu of NHTSA's primary estimate of lifetime
fuel savings, which would give an incomplete picture of technological
effectiveness because the analysis accounts for consumers' behavioral
response to the lower cost-per-mile of driving a more fuel-efficient
vehicle.
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\11\ While this comparison illustrates the effectiveness of the
technology added in response to this proposal, it does not represent
a full consumer welfare analysis, which would account for drivers'
likely response to the lower cost-per-mile of driving, as well as a
variety of other benefits and costs they will experience. The
agency's complete analysis of the proposal's likely impacts on
passenger car and light truck buyers appears in the PRIA, Appendix
I, Table A-23-1.
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[[Page 49620]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.026
With the SCC discounted at 2.5% and other benefits and costs
discounted at 3%, NHTSA estimates that costs and benefits could be
approximately $120 billion and $121 billion, respectively, such that
the present value of aggregate net benefits to society could be
somewhat less than $1 billion. With the social cost of carbon (SCC)
discounted at 3% and other benefits and costs discounted at 7%, NHTSA
estimates approximately $90 billion in costs and $76 billion in
benefits could be attributable to vehicles produced prior to MY 2030
over the course of their lives, such that the present value of
aggregate net costs to society could be approximately $15 billion.\13\
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\12\ Assumes no rebound effect.
\13\ NHTSA interprets the 2021 IWG draft guidance as indicating
that a 2.5% discount rate for the SCC is consistent with discounting
near-term benefits and costs of the proposal at the OMB-recommended
consumption discount rate of 3%. For the OMB-recommended discount
rate of 7%, NHTSA concluded that a 3% discount rate for the SCC was
reasonable given that the IWG draft guidance suggested that the
appropriate discount rate for the SCC was likely lower than 3%.
NHTSA refers readers specifically to pp. 16-17 of that guidance,
available at <a href="https://www.whitehouse.gov/wp-content/uploads/2021/02/TechnicalSupportDocument_SocialCostofCarbonMethaneNitrousOxide.pdf?source=email">https://www.whitehouse.gov/wp-content/uploads/2021/02/TechnicalSupportDocument_SocialCostofCarbonMethaneNitrousOxide.pdf?source=email</a>.
[GRAPHIC] [TIFF OMITTED] TP03SE21.027
Model results can be viewed many different ways, and NHTSA's
rulemaking considers both ``model year'' and ``calendar year''
perspectives. The ``model year'' perspective, above, considers vehicles
projected to be produced in some range of model years, and accounts for
impacts, benefits, and costs attributable to these vehicles from the
present (from the model year's perspective, 2020) until they are
projected to be scrapped. The bulk of NHTSA's analysis considers
vehicles produced prior to model year 2030, accounting for the
estimated indirect impacts new standards could have on the remaining
operation of vehicles already in service. This perspective emphasizes
impacts on those model years nearest to those (2024-2026) for which
NHTSA is proposing new standards. NHTSA's analysis also presents some
results focused only on model years 2024-2026, setting aside the
estimated indirect impacts on earlier model years, and the impacts
estimated to occur during model years 2027-2029, as some manufacturers
and products ``catch up'' to the standards.
Another way to present the benefits and costs of the proposal is
the ``calendar year'' perspective shown in Table II-10, which is
similar to how EPA presents benefits and costs in its proposal for GHG
standards for MYs 2023-2026. The calendar year perspective considers
all vehicles projected to be in service in each of some range of future
calendar years. NHTSA's presentation of results from this perspective
considers calendar years 2020-2050, because the model's representation
of the full on-road fleet extends through 2050. Unlike the model year
perspective, this perspective includes vehicles projected produced
during model years 2030-2050. This perspective emphasizes longer-term
impacts that could accrue if standards were to continue without change.
Table II-10 shows costs and benefits for MYs 2023-2026 while Table II-9
shows costs and benefits through MY 2029.
[[Page 49621]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.028
Though based on the exact same model results, these two
perspectives provide considerably different views of estimated costs
and benefits. Because technology costs account for a large share of
overall estimated costs, and are also projected to decline over time
(as manufacturers gain more experience with new technologies), costs
tend to be ``front loaded''--occurring early in a vehicle's life and
tending to be higher in earlier model years than in later model years.
Conversely, because social benefits of standards occur as vehicles are
driven, and because both fuel prices and the social cost of
CO<INF>2</INF> emissions are projected to increase in the future,
benefits tend to be ``back loaded.'' As a result, estimates of future
fuel savings, CO<INF>2</INF> reductions, and net social benefits are
higher under the calendar year perspective than under the model year
perspective. On the other hand, with longer-term impacts playing a
greater role, the calendar year perspective is more subject to
uncertainties regarding, for example, future technology costs and fuel
prices.
Even though NHTSA and EPA estimate benefits, costs, and net
benefits using similar methodologies and achieve similar results,
different approaches to accounting may give the false appearance of
significant divergences. Table II-10 above presents NHTSA's results
using comparable accounting to EPA's preamble Table 5. EPA also
presents cost and benefit information in its RIA over calendar years
2021 through 2050. The numbers most comparable to those presented in
EPA's RIA are those NHTSA developed to complete its Supplemental
Environmental Impact Statement (SEIS) using an identical accounting
approach. This is because the statutory limitations constraining
NHTSA's standard setting analysis, such as those in 49 U.S.C. 32902(h)
prohibiting consideration of full vehicle electrification during the
rulemaking timeframe, or consideration of the trading or transferring
of overcompliance credits, do not similarly apply to its EIS
analysis.\14\ NHTSA's EIS analysis estimates $312 billion in costs,
$443 billion in benefits, and $132 billion in net benefits using a 3%
discount rate over calendar years 2021 through 2050.\15\ NHTSA
describes its cost and benefit accounting approach in Section V of this
preamble.
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\14\ As the EIS analysis contains information that NHTSA is
statutorily prevented from considering, the agency does not rely on
this analysis in regulatory decision-making.
\15\ See PRIA Chapter 6.5 for more information regarding NHTSA's
estimates of annual benefits and costs using NHTSA's standard
setting analysis. See Tables B-7-25 through B-7-30 in Appendix II of
the PRIA for a more detailed breakdown of NHTSA's EIS analysis.
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C. Why does NHTSA tentatively believe the proposal would be maximum
feasible, and how and why is this tentative conclusion different from
the 2020 final rule?
NHTSA's tentative conclusion, after consideration of the factors
described below and information in the administrative record for this
action, is that 8 percent increases in stringency for MYs 2024-2026
(Alternative 2 of this analysis) are maximum feasible. The Department
of Transportation is deeply committed to working aggressively to
improve energy conservation and reduce security risks associated with
energy use, and higher standards appear increasingly likely to be
economically practicable given almost-daily announcements by major
automakers about forthcoming new high-fuel-economy vehicle models, as
described in more detail below. Despite only one year having passed
since the 2020 final rule, enough has changed in the U.S. and the world
that revisiting the CAFE standards for MYs 2024-2026, and raising their
stringency considerably, is both appropriate and reasonable.
The 2020 final rule set CAFE standards that increased at 1.5
percent per year for cars and trucks for MYs 2021-2026, in large part
because it prioritized industry concerns and reducing vehicle purchase
costs to consumers and manufacturers. This proposed rule acknowledges
the priority of energy conservation, consistent with NHTSA's statutory
authority. Moreover, NHTSA is also legally required to consider the
environmental implications of this action under NEPA, and while the
2020 final rule did undertake a NEPA analysis, it did not prioritize
the environmental considerations aspects of the statutory need of the
U.S. to conserve energy.
NHTSA recognizes that the amount of lead time available before MY
2024 is less than what was provided in the 2012 rule. As will be
discussed further in Section VI, NHTSA believes that the evidence
suggests that the proposed standards are still economically
practicable.
We note further that while this proposal is different from the 2020
final rule (and also from the 2012 final rule), NHTSA, like any other
Federal agency, is afforded an opportunity to reconsider prior views
and, when warranted, to adopt new positions. Indeed, as a matter of
good governance, agencies should revisit their positions when
appropriate, especially to ensure that their actions and regulations
reflect legally sound interpretations of the agency's authority and
remain consistent with the agency's views and practices. As a matter of
law, ``an Agency is entitled to change its interpretation of a
statute.'' \16\ Nonetheless, ``[w]hen an Agency adopts a materially
changed interpretation of a statute, it must in addition provide a
`reasoned analysis' supporting its decision to revise its
interpretation.'' \17\
[[Page 49622]]
This preamble and the accompanying TSD and PRIA all provide extensive
detail on the agency's updated analysis, and Section VI contains the
agency's explanation of how the agency has considered that analysis and
other relevant information in tentatively determining that the proposed
CAFE standards are maximum feasible for MYs 2024-2026 passenger cars
and light trucks.
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\16\ Phoenix Hydro Corp. v. FERC, 775 F.2d 1187, 1191 (D.C. Cir.
1985).
\17\ Alabama Educ. Ass'n v. Chao, 455 F.3d 386, 392 (D.C. Cir.
2006) (quoting Motor Vehicle Mfrs. Ass'n of U.S., Inc. v. State Farm
Mut. Auto. Ins. Co., 463 U.S. 29, 57 (1983)); see also Encino
Motorcars, LLC v. Navarro, 136 S.Ct. 2117, 2125 (2016) (``Agencies
are free to change their existing policies as long as they provide a
reasoned explanation for the change.'') (citations omitted).
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D. How is this proposal consistent with EPA's proposal and with
California's programs?
The NHTSA and EPA proposals remain coordinated despite being issued
as separate regulatory actions. Because NHTSA and EPA are regulating
the exact same vehicles and manufacturer will use the same technologies
to meet both sets of standards, NHTSA and EPA coordinated during the
development of each agency's independent proposal to revise the
standards set forth in the 2020 final rule. The NHTSA-proposed CAFE and
EPA-proposed CO<INF>2</INF> standards for MY 2026 represent roughly
equivalent levels of stringency and may serve as a coordinated starting
point for subsequent standards. While the proposed CAFE and
CO<INF>2</INF> standards for MYs 2024-2025 are different, this is
largely due to the difference in the ``start year'' for the revised
regulations--EPA is proposing to revise standards for MY 2023, while
EPCA's lead time requirements, which do not apply to EPA, prevent NHTSA
from proposing revised standards until MY 2024. In order to set
standards for MY 2023, EPA intends to issue its final rule by December
31, 2021, whereas NHTSA has until April 2022 to finalize standards for
MY 2024. The difference in timing makes separate rulemaking actions
reasonable and prudent. The specific differences in what the two
agencies' standards require become smaller each year, until alignment
is achieved. The agencies still have coordinated closely to minimize
inconsistency between the programs and will continue to do so through
the final rule stage.
While NHTSA's and EPA's programs differ in certain other respects,
like programmatic flexibilities, those differences are not new in this
proposal. Some parts of the programs are harmonized, and others differ,
often as a result of statute. Since NHTSA and EPA began regulating
together under President Obama, differences in programmatic
flexibilities have meant that manufacturers have had (and will have) to
plan their compliance strategies considering both the CAFE standards
and the GHG standards and assure that they are in compliance with both,
while still building a single fleet of vehicles to accomplish that
goal. NHTSA is proposing CAFE standards that increase at 8 percent per
year over MYs 2024-2026 because that is what NHTSA has tentatively
concluded is maximum feasible in those model years, under the EPCA
factors, and is confident that industry would still be able to build a
single fleet of vehicles to meet both the NHTSA and EPA standards. Auto
manufacturers are extremely sophisticated companies, well-able to
manage complex compliance strategies that account for multiple
regulatory programs concurrently. If different agencies' standards are
more binding for some companies in certain years, this does not mean
that manufacturers must build multiple fleets of vehicles, simply that
they will have to be more strategic about how they build their fleet.
NHTSA has also considered and accounted for California's ZEV
mandate (and its adoption by a number of other states) in developing
the baseline for this proposal, and has also accounted for the
Framework Agreements between California, BMW, Ford, Honda, VWA, and
Volvo. NHTSA believes that it is reasonable to include ZEV in the
baseline for this proposal regardless of whether California receives a
waiver of preemption under the Clean Air Act (CAA) because, according
to California, industry overcompliance with the ZEV mandate has been
extensive, which indicates that whether or not a waiver exists, many
companies intend to produce ZEVs in volumes comparable to what a ZEV
mandate would require. Because no decision has yet been made on a CAA
waiver for California, and because modeling a sub-national fleet is not
currently an analytical option for NHTSA, NHTSA has not expressly
accounted for California GHG standards in the analysis for this
proposal, although we seek comment on whether and how to account for
them in the final rule. Chapter 6 of the accompanying PRIA shows the
estimated effects of all of these programs simultaneously.
III. Technical Foundation for NPRM Analysis
A. Why does NHTSA conduct this analysis?
NHTSA is proposing to establish revised CAFE standards for
passenger cars and light trucks produced for model years (MYs) 2024-
2026. NHTSA's review of the existing standards is consistent with
Executive Order 13990, Protecting Public Health and the Environment and
Restoring Science to Tackle the Climate Crisis, signed on January 20,
2021, directing the review of the 2020 final rule that established CAFE
standards for MYs 2021-2026 and the consideration of whether to
suspend, revise, or rescind that action by July 2021.\18\ NHTSA
establishes CAFE standards under the Energy Policy and Conservation
Act, as amended, and this proposal is undertaken pursuant to that
authority. This proposal would require CAFE stringency for both
passenger cars and light trucks to increase at a rate of 8 percent per
year annually from MY 2024 through MY 2026. NHTSA estimates that over
the useful lives of vehicles produced prior to MY 2030, the proposal
would save about 50 billion gallons of gasoline and increase
electricity consumption by about 275 TWh. Accounting for emissions from
both vehicles and upstream energy sector processes (e.g., petroleum
refining and electricity generation), NHTSA estimates that the proposal
would reduce greenhouse gas emissions by about 465 million metric tons
of carbon dioxide (CO<INF>2</INF>), about 500 thousand tons metric tons
of methane (CH<INF>4</INF>), and about 12 thousand tons of nitrous
oxide (N<INF>2</INF>O).
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\18\ 86 FR 7037 (Jan. 25, 2021).
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When NHTSA promulgates new regulations, it generally presents an
analysis that estimates the impacts of such regulations, and the
impacts of other regulatory alternatives. These analyses derive from
statutes such as the Administrative Procedure Act (APA) and National
Environmental Policy Act (NEPA), from Executive orders (such as
Executive Order 12866 and 13653), and from other administrative
guidance (e.g., Office of Management Budget Circular A-4). For CAFE,
the Energy Policy and Conservation Act (EPCA), as amended by the Energy
Independence and Security Act (EISA), contains a variety of provisions
that require NHTSA to consider certain compliance elements in certain
ways and avoid considering other things, in determining maximum
feasible CAFE standards. Collectively, capturing all of these
requirements and guidance elements analytically means that, at least
for CAFE, NHTSA presents an analysis that spans a meaningful range of
regulatory alternatives, that quantifies a range of technological,
economic, and environmental impacts, and that does so in a manner that
accounts for EPCA's express requirements for the CAFE program
[[Page 49623]]
(e.g., passenger cars and light trucks are regulated separately, and
the standard for each fleet must be set at the maximum feasible level
in each model year).
NHTSA's decision regarding the proposed standards is thus supported
by extensive analysis of potential impacts of the regulatory
alternatives under consideration. Along with this preamble, a Technical
Support Document (TSD), a Preliminary Regulatory Impact Analysis
(PRIA), and a Supplemental Environmental Impact Statement (SEIS),
together provide an extensive and detailed enumeration of related
methods, estimates, assumptions, and results. NHTSA's analysis has been
constructed specifically to reflect various aspects of governing law
applicable to CAFE standards and has been expanded and improved in
response to comments received to the prior rulemaking and based on
additional work conducted over the last year. Further improvements may
be made based on comments received to this proposal, the 2021 NAS
Report,\19\ and other additional work generally previewed in these
rulemaking documents. The analysis for this proposal aided NHTSA in
implementing its statutory obligations, including the weighing of
various considerations, by reasonably informing decision-makers about
the estimated effects of choosing different regulatory alternatives.
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\19\ National Academies of Sciences, Engineering, and Medicine
(NASEM), 2021. Assessment of Technologies for Improving Fuel Economy
of Light-Duty Vehicles--2025-2035, Washington, DC: The National
Academies Press (hereafter, ``2021 NAS Report''). Available at
<a href="https://www.nationalacademies.org/our-work/assessment-of-technologies-for-improving-fuel-economy-of-light-duty-vehicles-phase-3">https://www.nationalacademies.org/our-work/assessment-of-technologies-for-improving-fuel-economy-of-light-duty-vehicles-phase-3</a> and for hard-copy review at DOT headquarters.
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NHTSA's analysis makes use of a range of data (i.e., observations
of things that have occurred), estimates (i.e., things that may occur
in the future), and models (i.e., methods for making estimates). Two
examples of data include (1) records of actual odometer readings used
to estimate annual mileage accumulation at different vehicle ages and
(2) CAFE compliance data used as the foundation for the ``analysis
fleet'' containing, among other things, production volumes and fuel
economy levels of specific configurations of specific vehicle models
produced for sale in the U.S. Two examples of estimates include (1)
forecasts of future GDP growth used, with other estimates, to forecast
future vehicle sales volumes and (2) the ``retail price equivalent''
(RPE) factor used to estimate the ultimate cost to consumers of a given
fuel-saving technology, given accompanying estimates of the
technology's ``direct cost,'' as adjusted to account for estimated
``cost learning effects'' (i.e., the tendency that it will cost a
manufacturer less to apply a technology as the manufacturer gains more
experience doing so).
NHTSA uses the CAFE Compliance and Effects Modeling System (usually
shortened to the ``CAFE Model'') to estimate manufacturers' potential
responses to new CAFE and CO<INF>2</INF> standards and to estimate
various impacts of those responses. DOT's Volpe National Transportation
Systems Center (often simply referred to as the ``Volpe Center'')
develops, maintains, and applies the model for NHTSA. NHTSA has used
the CAFE Model to perform analyses supporting every CAFE rulemaking
since 2001. The 2016 rulemaking regarding heavy-duty pickup and van
fuel consumption and CO<INF>2</INF> emissions also used the CAFE Model
for analysis (81 FR 73478, October 25, 2016).
The basic design of the CAFE Model is as follows: the system first
estimates how vehicle manufacturers might respond to a given regulatory
scenario, and from that potential compliance solution, the system
estimates what impact that response will have on fuel consumption,
emissions, and economic externalities. In a highly-summarized form,
Figure III-1 shows the basic categories of CAFE Model procedures and
the sequential flow between different stages of the modeling. The
diagram does not present specific model inputs or outputs, as well as
many specific procedures and model interactions. The model
documentation accompanying this preamble presents these details, and
Chapter 1 of the TSD contains a more detailed version of this flow
diagram for readers who are interested.
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[[Page 49624]]
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BILLING CODE 4910-59-C
More specifically, the model may be characterized as an integrated
system of models. For example, one model estimates manufacturers'
responses, another estimates resultant changes in total vehicle sales,
and still another estimates resultant changes in fleet turnover (i.e.,
scrappage). Additionally, and importantly, the model does not determine
the form or stringency of the standards. Instead, the model applies
inputs specifying the form and stringency of standards to be analyzed
and produces outputs showing the impacts of manufacturers working to
meet those standards, which become the basis for comparing between
different potential stringencies. A regulatory scenario, meanwhile,
involves specification of the form, or shape, of the standards (e.g.,
flat standards, or linear or logistic attribute-based standards), scope
of passenger car and truck regulatory classes, and stringency of the
CAFE standards for each model year to be analyzed. For example, a
regulatory scenario may define CAFE standards that increase in
stringency by 8 percent per year for 3 consecutive years.
Manufacturer compliance simulation and the ensuing effects
estimation, collectively referred to as compliance modeling, encompass
numerous subsidiary elements. Compliance simulation begins with a
detailed user-provided \20\ initial forecast of the vehicle models
offered for sale during the simulation period. The compliance
simulation then attempts to bring each manufacturer into compliance
with the standards \21\ defined by the regulatory scenario contained
within an input file developed by the user.
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\20\ Because the CAFE Model is publicly available, anyone can
develop their own initial forecast (or other inputs) for the model
to use. The DOT-developed market data file that contains the
forecast used for this proposal is available on NHTSA's website.
\21\ With appropriate inputs, the model can also be used to
estimate impacts of manufacturers' potential responses to new
CO<INF>2</INF> standards and to California's ZEV program.
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Estimating impacts involves calculating resultant changes in new
vehicle costs, estimating a variety of costs (e.g., for fuel) and
effects (e.g., CO<INF>2</INF> emissions from fuel combustion) occurring
as vehicles are driven over their lifetimes before eventually being
[[Page 49625]]
scrapped, and estimating the monetary value of these effects.
Estimating impacts also involves consideration of consumer responses--
e.g., the impact of vehicle fuel economy, operating costs, and vehicle
price on consumer demand for passenger cars and light trucks. Both
basic analytical elements involve the application of many analytical
inputs. Many of these inputs are developed outside of the model and not
by the model. For example, the model applies fuel prices; it does not
estimate fuel prices.
NHTSA also uses EPA's MOVES model to estimate ``tailpipe'' (a.k.a.
``vehicle'' or ``downstream'') emission factors for criteria
pollutants,\22\ and uses four Department of Energy (DOE) and DOE-
sponsored models to develop inputs to the CAFE Model, including three
developed and maintained by DOE's Argonne National Laboratory. The
agency uses the DOE Energy Information Administration's (EIA's)
National Energy Modeling System (NEMS) to estimate fuel prices,\23\ and
uses Argonne's Greenhouse gases, Regulated Emissions, and Energy use in
Transportation (GREET) model to estimate emissions rates from fuel
production and distribution processes.\24\ DOT also sponsored DOE/
Argonne to use Argonne's Autonomie full-vehicle modeling and simulation
system to estimate the fuel economy impacts for roughly a million
combinations of technologies and vehicle types.<SUP>25 26</SUP> The TSD
and PRIA describe details of the agency's use of these models. In
addition, as discussed in the SEIS accompanying this NPRM, DOT relied
on a range of climate models to estimate impacts on climate, air
quality, and public health. The SEIS discusses and describes the use of
these models.
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\22\ See <a href="https://www.epa.gov/moves">https://www.epa.gov/moves</a>. This proposal uses version
MOVES3, available at <a href="https://www.epa.gov/moves/latest-version-motor-vehicle-emission-simulator-moves">https://www.epa.gov/moves/latest-version-motor-vehicle-emission-simulator-moves</a>.
\23\ See <a href="https://www.eia.gov/outlooks/aeo/info_nems_archive.php">https://www.eia.gov/outlooks/aeo/info_nems_archive.php</a>.
This proposal uses fuel prices estimated using the Annual Energy
Outlook (AEO) 2021 version of NEMS (see <a href="https://www.eia.gov/outlooks/aeo/pdf/02%20AEO2021%20Petroleum.pdf">https://www.eia.gov/outlooks/aeo/pdf/02%20AEO2021%20Petroleum.pdf</a>).
\24\ Information regarding GREET is available at <a href="https://greet.es.anl.gov/index.php">https://greet.es.anl.gov/index.php</a>. This NPRM uses the 2020 version of
GREET.
\25\ As part of the Argonne simulation effort, individual
technology combinations simulated in Autonomie were paired with
Argonne's BatPaC model to estimate the battery cost associated with
each technology combination based on characteristics of the
simulated vehicle and its level of electrification. Information
regarding Argonne's BatPaC model is available at <a href="https://www.anl.gov/cse/batpac-model-software">https://www.anl.gov/cse/batpac-model-software</a>.
\26\ In addition, the impact of engine technologies on fuel
consumption, torque, and other metrics was characterized using GT-
POWER simulation modeling in combination with other engine modeling
that was conducted by IAV Automotive Engineering, Inc. (IAV). The
engine characterization ``maps'' resulting from this analysis were
used as inputs for the Autonomie full-vehicle simulation modeling.
Information regarding GT-POWER is available at <a href="https://www.gtisoft.com/gt-suite-applications/propulsion-systems/gt-power-engine-simulation-software">https://www.gtisoft.com/gt-suite-applications/propulsion-systems/gt-power-engine-simulation-software</a>.
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To prepare for analysis supporting this proposal, DOT has refined
and expanded the CAFE Model through ongoing development. Examples of
such changes, some informed by past external comments, made since early
2020 include:
<bullet> Inclusion of 400- and 500-mile BEVs;
<bullet> Inclusion of high compression ratio (HCR) engines with
cylinder deactivation;
<bullet> Accounting for manufacturers' responses to both CAFE and
CO<INF>2</INF> standards jointly (rather than only separately)
<bullet> Accounting for the ZEV mandates applicable in California
and the ``Section 177'' states;
<bullet> Accounting for some vehicle manufacturers' (BMW, Ford,
Honda, VW, and Volvo) voluntary agreement with the State of California
to continued annual national-level reductions of vehicle greenhouse gas
emissions through MY 2026, with greater rates of electrification than
would have been required under the 2020 Federal final rule; \27\
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\27\ For more information on the Framework Agreements for Clean
Cars, including the specific agreements signed by individual
manufacturers, see <a href="https://ww2.arb.ca.gov/news/framework-agreements-clean-cars">https://ww2.arb.ca.gov/news/framework-agreements-clean-cars</a>.
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[cir] Inclusion of CAFE civil penalties in the ``effective cost''
metric used when simulating manufacturers' potential application of
fuel-saving technologies;
[cir] Refined procedures to estimate health effects and
corresponding monetized damages attributable to criteria pollutant
emissions;
[cir] New procedures to estimate the impacts and corresponding
monetized damages of highway vehicle crashes that do not result in
fatalities;
[cir] Procedures to ensure that modeled technology application and
production volumes are the same across all regulatory alternatives in
the earliest model years; and
[cir] Procedures to more precisely focus application of EPCA's
``standard setting constraints'' (i.e., regarding the consideration of
compliance credits and additional dedicated alternative fueled
vehicles) to only those model years for which NHTSA is proposing or
finalizing new standards.
These changes reflect DOT's long-standing commitment to ongoing
refinement of its approach to estimating the potential impacts of new
CAFE standards.
NHTSA underscores that this analysis exercises the CAFE Model in a
manner that explicitly accounts for the fact that in producing a single
fleet of vehicles for sale in the United States, manufacturers face the
combination of CAFE standards, EPA CO<INF>2</INF> standards, and ZEV
mandates, and for five manufacturers, the voluntary agreement with
California to more stringent CO<INF>2</INF> reduction requirements
(also applicable to these manufacturers' total production for the U.S.
market) through model year 2026. These regulations and contracts have
important structural and other differences that affect the strategy a
manufacturer could use to comply with each of the above.
As explained, the analysis is designed to reflect a number of
statutory and regulatory requirements applicable to CAFE and tailpipe
CO<INF>2</INF> standard-setting. EPCA contains a number of requirements
governing the scope and nature of CAFE standard setting. Among these,
some have been in place since EPCA was first signed into law in 1975,
and some were added in 2007, when Congress passed EISA and amended
EPCA. EPCA/EISA requirements regarding the technical characteristics of
CAFE standards and the analysis thereof include, but are not limited
to, the following, and the analysis reflects these requirements as
summarized:
Corporate Average Standards: The provision at 49 U.S.C. 32902
requires standards that apply to the average fuel economy levels
achieved by each corporation's fleets of vehicles produced for sale in
the U.S.\28\ The CAFE Model calculates the CAFE and CO<INF>2</INF>
levels of each manufacturer's fleets based on estimated production
volumes and characteristics, including fuel economy levels, of distinct
vehicle models that could be produced for sale in the U.S.
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\28\ This differs from safety standards and traditional
emissions standards, which apply separately to each vehicle. For
example, every vehicle produced for sale in the U.S. must, on its
own, meet all applicable Federal motor vehicle safety standards
(FMVSS), but no vehicle produced for sale must, on its own, meet
Federal fuel economy standards. Rather, each manufacturer is
required to produce a mix of vehicles that, taken together, achieve
an average fuel economy level no less than the applicable minimum
level.
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Separate Standards for Passenger Cars and Light Trucks: The
provision at 49 U.S.C. 32902 requires the Secretary of Transportation
to set CAFE standards separately for passenger cars and light trucks.
The CAFE Model accounts separately for passenger cars and light trucks
when it analyzes CAFE or CO<INF>2</INF> standards, including
differentiated standards and compliance.
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Attribute-Based Standards: The provision at 49 U.S.C. 32902
requires the Secretary of Transportation to define CAFE standards as
mathematical functions expressed in terms of one or more vehicle
attributes related to fuel economy. This means that for a given
manufacturer's fleet of vehicles produced for sale in the U.S. in a
given regulatory class and model year, the applicable minimum CAFE
requirement (i.e., the numerical value of the requirement) is computed
based on the applicable mathematical function, and the mix and
attributes of vehicles in the manufacturer's fleet. The CAFE Model
accounts for such functions and vehicle attributes explicitly.
Separately Defined Standards for Each Model Year: The provision at
49 U.S.C. 32902 requires the Secretary to set CAFE standards
(separately for passenger cars and light trucks \29\) at the maximum
feasible levels in each model year. The CAFE Model represents each
model year explicitly, and accounts for the production relationships
between model years.\30\
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\29\ 49 U.S.C. chapter 329 uses the term ``non-passenger
automobiles,'' while NHTSA uses the term ``light trucks'' in its
CAFE regulations. The terms' meanings are identical.
\30\ For example, a new engine first applied to given vehicle
model/configuration in model year 2020 will most likely be ``carried
forward'' to model year 2021 of that same vehicle model/
configuration, in order to reflect the fact that manufacturers do
not apply brand-new engines to a given vehicle model every single
year. The CAFE Model is designed to account for these real-world
factors.
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Separate Compliance for Domestic and Imported Passenger Car Fleets:
The provision at 49 U.S.C. 32904 requires the EPA Administrator to
determine CAFE compliance separately for each manufacturers' fleets of
domestic passenger cars and imported passenger cars, which
manufacturers must consider as they decide how to improve the fuel
economy of their passenger car fleets. The CAFE Model accounts
explicitly for this requirement when simulating manufacturers'
potential responses to CAFE standards, and combines any given
manufacturer's domestic and imported cars into a single fleet when
simulating that manufacturer's potential response to CO<INF>2</INF>
standards (because EPA does not have separate standards for domestic
and imported passenger cars).
Minimum CAFE Standards for Domestic Passenger Car Fleets: The
provision at 49 U.S.C. 32902 requires that domestic passenger car
fleets meet a minimum standard, which is calculated as 92 percent of
the industry-wide average level required under the applicable
attribute-based CAFE standard, as projected by the Secretary at the
time the standard is promulgated. The CAFE Model accounts explicitly
for this requirement for CAFE standards and sets this requirement aside
for CO<INF>2</INF> standards.
Civil Penalties for Noncompliance: The provision at 49 U.S.C. 32912
(and implementing regulations) prescribes a rate (in dollars per tenth
of a mpg) at which the Secretary is to levy civil penalties if a
manufacturer fails to comply with a CAFE standard for a given fleet in
a given model year, after considering available credits. Some
manufacturers have historically demonstrated a willingness to pay civil
penalties rather than achieving full numerical compliance across all
fleets. The CAFE Model calculates civil penalties for CAFE shortfalls
and provides means to estimate that a manufacturer might stop adding
fuel-saving technologies once continuing to do so would be effectively
more ``expensive'' (after accounting for fuel prices and buyers'
willingness to pay for fuel economy) than paying civil penalties. The
CAFE Model does not allow civil penalty payment as an option for
CO<INF>2</INF> standards.
Dual-Fueled and Dedicated Alternative Fuel Vehicles: For purposes
of calculating CAFE levels used to determine compliance, 49 U.S.C.
32905 and 32906 specify methods for calculating the fuel economy levels
of vehicles operating on alternative fuels to gasoline or diesel
through MY 2020. After MY 2020, methods for calculating alternative
fuel vehicle (AFV) fuel economy are governed by regulation. The CAFE
Model is able to account for these requirements explicitly for each
vehicle model. However, 49 U.S.C. 32902 prohibits consideration of the
fuel economy of dedicated alternative fuel vehicle (AFV) models when
NHTSA determines what levels of CAFE standards are maximum feasible.
The CAFE Model therefore has an option to be run in a manner that
excludes the additional application of dedicated AFV technologies in
model years for which maximum feasible standards are under
consideration. As allowed under NEPA for analysis appearing in EISs
informing decisions regarding CAFE standards, the CAFE Model can also
be run without this analytical constraint. The CAFE Model does account
for dual- and alternative fuel vehicles when simulating manufacturers'
potential responses to CO<INF>2</INF> standards. For natural gas
vehicles, both dedicated and dual-fueled, EPA has a multiplier of 2.0
for model years 2022-2026.\31\
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\31\ While EPA is proposing changes to this and other
flexibility provisions in its separate NPRM, for purposes of this
NPRM, the CAFE Model only reflects the current EPA regulatory
flexibilities.
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ZEV Mandates: The CAFE Model can simulate manufacturers' compliance
with ZEV mandates applicable in California and ``Section 177'' \32\
states. The approach involves identifying specific vehicle model/
configurations that could be replaced with PHEVs or BEVs, and
immediately making these changes in each model year, before beginning
to consider the potential that other technologies could be applied
toward compliance with CAFE or CO<INF>2</INF> standards.
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\32\ The term ``Section 177'' states refers to states which have
elected to adopt California's standards in lieu of Federal
requirements, as allowed under Section 177 of the CAA.
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Creation and Use of Compliance Credits: The provision at 49 U.S.C.
32903 provides that manufacturers may earn CAFE ``credits'' by
achieving a CAFE level beyond that required of a given fleet in a given
model year, and specifies how these credits may be used to offset the
amount by which a different fleet falls short of its corresponding
requirement. These provisions allow credits to be ``carried forward''
and ``carried back'' between model years, transferred between regulated
classes (domestic passenger cars, imported passenger cars, and light
trucks), and traded between manufacturers. However, credit use is also
subject to specific statutory limits. For example, CAFE compliance
credits can be carried forward a maximum of five model years and
carried back a maximum of three model years. Also, EPCA/EISA caps the
amount of credit that can be transferred between passenger car and
light truck fleets and prohibits manufacturers from applying traded or
transferred credits to offset a failure to achieve the applicable
minimum standard for domestic passenger cars. The CAFE Model explicitly
simulates manufacturers' potential use of credits carried forward from
prior model years or transferred from other fleets.\33\ The provision
at 49
[[Page 49627]]
U.S.C. 32902 prohibits consideration of manufacturers' potential
application of CAFE compliance credits when setting maximum feasible
CAFE standards. The CAFE Model can be operated in a manner that
excludes the application of CAFE credits for a given model year under
consideration for standard setting. For modeling CO<INF>2</INF>
standards, the CAFE Model does not limit transfers. Insofar as the CAFE
Model can be exercised in a manner that simulates trading of
CO<INF>2</INF> compliance credits, such simulations treat trading as
unlimited.\34\
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\33\ The CAFE Model does not explicitly simulate the potential
that manufacturers would carry CAFE or CO<INF>2</INF> credits back
(i.e., borrow) from future model years, or acquire and use CAFE
compliance credits from other manufacturers. At the same time,
because EPA has currently elected not to limit credit trading, the
CAFE Model can be exercised in a manner that simulates unlimited
(a.k.a. ``perfect'') CO<INF>2</INF> compliance credit trading
throughout the industry (or, potentially, within discrete trading
``blocs''). NHTSA believes there is significant uncertainty in how
manufacturers may choose to employ these particular flexibilities in
the future: For example, while it is reasonably foreseeable that a
manufacturer who over-complies in one year may ``coast'' through
several subsequent years relying on those credits rather than
continuing to make technology improvements, it is harder to assume
with confidence that manufacturers will rely on future technology
investments to offset prior-year shortfalls, or whether/how
manufacturers will trade credits with market competitors rather than
making their own technology investments. Historically, carry-back
and trading have been much less utilized than carry-forward, for a
variety of reasons including higher risk and preference not to `pay
competitors to make fuel economy improvements we should be making'
(to paraphrase one manufacturer), although NHTSA recognizes that
carry-back and trading are used more frequently when standards
increase in stringency more rapidly. Given the uncertainty just
discussed, and given also the fact that the agency has yet to
resolve some of the analytical challenges associated with simulating
use of these flexibilities, the agency considers borrowing and
trading to involve sufficient risk that it is prudent to support
this proposal with analysis that sets aside the potential that
manufacturers could come to depend widely on borrowing and trading.
While compliance costs in real life may be somewhat different from
what is modeled today as a result of this analytical decision, that
is broadly true no matter what, and the agency does not believe that
the difference would be so great that it would change the policy
outcome. Furthermore, a manufacturer employing a trading strategy
would presumably do so because it represents a lower-cost compliance
option. Thus, the estimates derived from this modeling approach are
likely to be conservative in this respect, with real-world
compliance costs possibly being lower.
\34\ To avoid making judgments about possible future trading
activity, the model simulates trading by combining all manufacturers
into a single entity, so that the most cost-effective choices are
made for the fleet as a whole.
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Statutory Basis for Stringency: The provision at 49 U.S.C. 32902
requires the Secretary to set CAFE standards at the maximum feasible
levels, considering technological feasibility, economic practicability,
the need of the United States to conserve energy, and the impact of
other motor vehicle standards of the Government. EPCA/EISA authorizes
the Secretary to interpret these factors, and as the Department's
interpretation has evolved, NHTSA has continued to expand and refine
its qualitative and quantitative analysis to account for these
statutory factors. For example, one of the ways that economic
practicability considerations are incorporated into the analysis is
through the technology effectiveness determinations: The Autonomie
simulations reflect the agency's judgment that it would not be
economically practicable for a manufacturer to ``split'' an engine
shared among many vehicle model/configurations into myriad versions
each optimized to a single vehicle model/configuration.
National Environmental Policy Act: In addition, NEPA requires the
Secretary to issue an EIS that documents the estimated impacts of
regulatory alternatives under consideration. The SEIS accompanying this
NPRM documents changes in emission inventories as estimated using the
CAFE Model, but also documents corresponding estimates--based on the
application of other models documented in the SEIS, of impacts on the
global climate, on tropospheric air quality, and on human health.
Other Aspects of Compliance: Beyond these statutory requirements
applicable to DOT and/or EPA are a number of specific technical
characteristics of CAFE and/or CO<INF>2</INF> regulations that are also
relevant to the construction of this analysis. For example, EPA has
defined procedures for calculating average CO<INF>2</INF> levels, and
has revised procedures for calculating CAFE levels, to reflect
manufacturers' application of ``off-cycle'' technologies that increase
fuel economy (and reduce CO<INF>2</INF> emissions). Although too little
information is available to account for these provisions explicitly in
the same way that the agency has accounted for other technologies, the
CAFE Model does include and makes use of inputs reflecting the agency's
expectations regarding the extent to which manufacturers may earn such
credits, along with estimates of corresponding costs. Similarly, the
CAFE Model includes and makes use of inputs regarding credits EPA has
elected to allow manufacturers to earn toward CO<INF>2</INF> levels
(not CAFE) based on the use of air conditioner refrigerants with lower
global warming potential (GWP), or on the application of technologies
to reduce refrigerant leakage. In addition, the CAFE Model accounts for
EPA ``multipliers'' for certain alternative fueled vehicles, based on
current regulatory provisions or on alternative approaches. Although
these are examples of regulatory provisions that arise from the
exercise of discretion rather than specific statutory mandate, they can
materially impact outcomes.
Besides the updates to the model described above, any analysis of
regulatory actions that will be implemented several years in the
future, and whose benefits and costs accrue over decades, requires a
large number of assumptions. Over such time horizons, many, if not
most, of the relevant assumptions in such an analysis are inevitably
uncertain. Each successive CAFE analysis seeks to update assumptions to
reflect better the current state of the world and the best current
estimates of future conditions.
A number of assumptions have been updated since the 2020 final rule
for this proposal. While NHTSA would have made these updates as a
matter of course, we note that that the COVID-19 pandemic has been
profoundly disruptive, including in ways directly material to major
analytical inputs such as fuel prices, gross domestic product (GDP),
vehicle production and sales, and highway travel. As discussed below,
NHTSA has updated its ``analysis fleet'' from a model year 2017
reference to a model year 2020 reference, updated estimates of
manufacturers' compliance credit ``holdings,'' updated fuel price
projections to reflect the U.S. Energy Information Administration's
(EIA's) 2021 Annual Energy Outlook (AEO), updated projections of GDP
and related macroeconomic measures, and updated projections of future
highway travel. In addition, through Executive Order 13990, President
Biden has required the formation of an Interagency Working Group (IWG)
on the Social Cost of Greenhouse Gases and charged this body with
updating estimates of the social costs of carbon, nitrous oxide, and
methane. As discussed in the TSD, NHTSA has applied the IWG's interim
guidance, which contains cost estimates (per ton of emissions)
considerably greater than those applied in the analysis supporting the
2020 SAFE rule. These and other updated analytical inputs are discussed
in detail in the TSD. NHTSA seeks comment on the above discussion.
B. What is NHTSA analyzing?
As in the CAFE and CO<INF>2</INF> rulemakings in 2010, 2012, and
2020, NHTSA is proposing to set attribute-based CAFE standards defined
by a mathematical function of vehicle footprint, which has observable
correlation with fuel economy. EPCA, as amended by EISA, expressly
requires that CAFE standards for passenger cars and light trucks be
based on one or more vehicle attributes related to fuel economy and be
expressed in the form of a mathematical function.\35\ Thus, the
proposed standards (and regulatory alternatives) take the form of fuel
economy targets expressed as functions of vehicle footprint (the
product of vehicle wheelbase and average track width) that are separate
for passenger cars and light trucks. Chapter 1.2.3 of the TSD discusses
in detail NHTSA's continued
[[Page 49628]]
reliance on footprint as the relevant attribute in this proposal.
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\35\ 49 U.S.C. 32902(a)(3)(A).
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Under the footprint-based standards, the function defines a fuel
economy performance target for each unique footprint combination within
a car or truck model type. Using the functions, each manufacturer thus
will have a CAFE average standard for each year that is almost
certainly unique to each of its fleets,\36\ based upon the footprints
and production volumes of the vehicle models produced by that
manufacturer. A manufacturer will have separate footprint-based
standards for cars and for trucks, consistent with 49 U.S.C. 32902(b)'s
direction that NHTSA must set separate standards for cars and for
trucks. The functions are mostly sloped, so that generally, larger
vehicles (i.e., vehicles with larger footprints) will be subject to
lower mpg targets than smaller vehicles. This is because, generally
speaking, smaller vehicles are more capable of achieving higher levels
of fuel economy, mostly because they tend not to have to work as hard
(and therefore require as much energy) to perform their driving task.
Although a manufacturer's fleet average standards could be estimated
throughout the model year based on the projected production volume of
its vehicle fleet (and are estimated as part of EPA's certification
process), the standards with which the manufacturer must comply are
determined by its final model year production figures. A manufacturer's
calculation of its fleet average standards, as well as its fleets'
average performance at the end of the model year, will thus be based on
the production-weighted average target and performance of each model in
its fleet.\37\
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\36\ EPCA/EISA requires NHTSA and EPA to separate passenger cars
into domestic and import passenger car fleets for CAFE compliance
purposes (49 U.S.C. 32904(b)), whereas EPA combines all passenger
cars into one fleet.
\37\ As discussed in prior rulemakings, a manufacturer may have
some vehicle models that exceed their target and some that are below
their target. Compliance with a fleet average standard is determined
by comparing the fleet average standard (based on the production-
weighted average of the target levels for each model) with fleet
average performance (based on the production-weighted average of the
performance of each model).
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For passenger cars, consistent with prior rulemakings, NHTSA is
proposing to define fuel economy targets as shown in Equation III-1.
[GRAPHIC] [TIFF OMITTED] TP03SE21.030
Where:
TARGETFE is the fuel economy target (in mpg) applicable to a
specific vehicle model type with a unique footprint combination,
a is a minimum fuel economy target (in mpg),
b is a maximum fuel economy target (in mpg),
c is the slope (in gallons per mile per square foot, or gpm, per
square foot) of a line relating fuel consumption (the inverse of
fuel economy) to footprint, and
d is an intercept (in gpm) of the same line.
Here, MIN and MAX are functions that take the minimum and maximum
values, respectively, of the set of included values. For example,
MIN[40, 35] = 35 and MAX(40, 25) = 40, such that MIN[MAX(40, 25),
35] = 35.
For the preferred alternative, this equation is represented
graphically as the curves in Figure III-2.
BILLING CODE 4910-59-P
[[Page 49629]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.031
For light trucks, also consistent with prior rulemakings, NHTSA is
proposing to define fuel economy targets as shown in Equation III-2.
[GRAPHIC] [TIFF OMITTED] TP03SE21.032
Where:
TARGETFE is the fuel economy target (in mpg) applicable to a
specific vehicle model type with a unique footprint combination,
a, b, c, and d are as for passenger cars, but taking values specific
to light trucks,
e is a second minimum fuel economy target (in mpg),
f is a second maximum fuel economy target (in mpg),
g is the slope (in gpm per square foot) of a second line relating
fuel consumption (the inverse of fuel economy) to footprint, and
h is an intercept (in gpm) of the same second line.
For the preferred alternative, this equation is represented
graphically as the curves in Figure III-3.
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[GRAPHIC] [TIFF OMITTED] TP03SE21.033
BILLING CODE 4910-59-C
Although the general model of the target function equation is the
same for each vehicle category (passenger cars and light trucks) and
each model year, the parameters of the function equation differ for
cars and trucks. The actual parameters for both the preferred
alternative and the other regulatory alternatives are presented in
Section IV.B of this preamble.
As has been the case since NHTSA began establishing attribute-based
standards, no vehicle need meet the specific applicable fuel economy
target, because compliance with CAFE standards is determined based on
corporate average fuel economy. In this respect, CAFE standards are
unlike, for example, Federal Motor Vehicle Safety Standards (FMVSS) and
certain vehicle criteria pollutant emissions standards where each car
must meet the requirements. CAFE standards apply to the average fuel
economy levels achieved by manufacturers' entire fleets of vehicles
produced for sale in the U.S. Safety standards apply on a vehicle-by-
vehicle basis, such that every single vehicle produced for sale in the
U.S. must, on its own, comply with minimum FMVSS. When first mandating
CAFE standards in the 1970s, Congress specified a more flexible
averaging-based approach that allows some vehicles to ``under comply''
(i.e., fall short of the overall flat standard, or fall short of their
target under attribute-based standards) as long as a manufacturer's
overall fleet is in compliance.
The required CAFE level applicable to a given fleet in a given
model year is determined by calculating the production-weighted
harmonic average of fuel economy targets applicable to specific vehicle
model configurations in the fleet, as shown in Equation III-3.
[[Page 49631]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.034
Where:
CAFErequired is the CAFE level the fleet is required to achieve,
i refers to specific vehicle model/configurations in the fleet,
PRODUCTIONi is the number of model configuration i produced for sale
in the U.S., and
TARGETFE,I is the fuel economy target (as defined above) for model
configuration i.
Chapter 1 of the TSD describes the use of attribute-based
standards, generally, and explains the specific decision, in past rules
and for the current rule, to continue to use vehicle footprint as the
attribute over which to vary stringency. That chapter also discusses
the policy in selecting the specific mathematical function; the
methodologies used to develop the current attribute-based standards;
and methodologies previously used to reconsider the mathematical
function for CAFE standards. NHTSA refers readers to the TSD for a full
discussion of these topics.
While Chapter 1 of the TSD explains why the proposed standards for
MYs 2024-2026 continue to be footprint-based, the question has arisen
periodically of whether NHTSA should instead consider multi-attribute
standards, such as those that also depend on weight, torque, power,
towing capability, and/or off-road capability. To date, every time
NHTSA has considered options for which attribute(s) to select, the
agency has concluded that a properly-designed footprint-based approach
provides the best means of achieving the basic policy goals (i.e., by
increasing the likelihood of improved fuel economy across the entire
fleet of vehicles; by reducing disparities between manufacturers'
compliance burdens; and by reducing incentives for manufacturers to
respond to standards in ways that could compromise overall highway
safety) involved in applying an attribute-based standard. At the same
time, footprint-based standards need also to be structured in a way
that furthers the energy and environmental policy goals of EPCA without
creating inappropriate incentives to increase vehicle size in ways that
could increase fuel consumption or compromise safety. That said, as
NHTSA moves forward with the CAFE program, and continues to refine our
understanding of the light-duty vehicle market and trends in vehicle
and highway safety, NHTSA will also continue to revisit whether other
approaches (or other ways of applying the same basic approaches) could
foreseeably provide better means of achieving policy goals.
For example, in the 2021 NAS Report, the committee recommended that
if Congress does not act to remove the prohibition at 49 U.S.C.
32902(h) on considering the fuel economy of dedicated alternative fuel
vehicles (like BEVs) in determining maximum feasible CAFE standards,
then NHTSA should account for the fuel economy benefits of ZEVs by
``setting the standard as a function of a second attribute in addition
to footprint--for example, the expected market share of ZEVs in the
total U.S. fleet of new light-duty vehicles--such that the standards
increase as the share of ZEVs in the total U.S. fleet increases.'' \38\
DOE seconded this suggestion in its comments during interagency review
of this proposal. Chapter 1 of the TSD contains an examination of this
suggestion, and NHTSA seeks comment on whether and how NHTSA might
consider adding electrification as an attribute on which to base CAFE
standards.
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\38\ National Academies of Sciences, Engineering, and Medicine,
2021. Assessment of Technologies for Improving Fuel Economy of
Light-Duty Vehicles--2025-2035, Washington, DC: The National
Academies Press (hereafter, ``2021 NAS Report''), at Summary
Recommendation 5. Available at <a href="https://www.nationalacademies.org/our-work/assessment-of-technologies-for-improving-fuel-economy-of-light-duty-vehicles-phase-3">https://www.nationalacademies.org/our-work/assessment-of-technologies-for-improving-fuel-economy-of-light-duty-vehicles-phase-3</a> and for hard-copy review at DOT
headquarters.
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Changes in the market that have occurred since NHTSA last examined
the appropriateness of the footprint curves have been, for the most
part, consistent with the trends that the agency identified in 2018.
For the most part, the fleet has continued to grow somewhat in vehicle
size, as vehicle manufacturers have continued over the past several
years to reduce their offerings of smaller footprint vehicles and
increase their sales of larger footprint vehicles and continue to sell
many small to mid-size crossovers and SUVs, some of which are
classified as passenger cars and some of which are light trucks.
Although this trend has had the effect of reducing the achieved fuel
economy of the fleet (and thus increasing its carbon dioxide emissions)
as compared to if vehicles had instead remained the same size or gotten
smaller, NHTSA does not believe that there have been sufficiently major
changes in the relationship between footprint and fuel economy over the
last three years to warrant a detailed re-examination of that
relationship as part of this proposal. Moreover, changes to the
footprint curves can significantly affect manufacturers' ability to
comply. Given the available lead time between now and the beginning of
MY 2024, NHTSA believes it is unlikely any potential benefit of
changing the shape of the footprint curves (when we are already
proposing to change standard stringency) would outweigh the costs of
doing so.
NHTSA seeks comment on the choice of footprint as the attribute on
which the proposed standards are based, and particularly seeks comment
on the 2021 NAS report recommendation described above. If commenters
wish to provide comments on possible changes to the attribute(s) on
which fuel economy standards should be based, including approaches for
considering vehicle electrification in ways that would further a zero
emissions fleet as discussed in Chapter 1 of the TSD, NHTSA would
appreciate commenters including a discussion of the timeframe in which
those changes should be made--for example, whether and how much lead
time would be preferable for making such changes, particularly
recognizing the available lead time for MY 2024. NHTSA also seeks
comment on whether, to the extent that vehicle upsizing trends and fuel
economy curves are causally related instead of correlated, it is the
curve shape versus the choice of footprint that creates this
relationship (or, alternatively, whether the relationship if any
derives from vehicle classification). Again, if commenters wish to
provide comments on possible changes to the curve shapes, NHTSA would
appreciate commenters including a discussion of the timeframe in which
those changes should be made.
NHTSA seeks comment on the discussion above and in the TSD.
[[Page 49632]]
C. What inputs does the compliance analysis require?
The CAFE Model applies various technologies to different vehicle
models in each manufacturer's product line to simulate how each
manufacturer might make progress toward compliance with the specified
standard. Subject to a variety of user-controlled constraints, the
model applies technologies based on their relative cost-effectiveness,
as determined by several input assumptions regarding the cost and
effectiveness of each technology, the cost of compliance (determined by
the change in CAFE or CO<INF>2</INF> credits, CAFE-related civil
penalties, or value of CO<INF>2</INF> credits, depending on the
compliance program being evaluated), and the value of avoided fuel
expenses. For a given manufacturer, the compliance simulation algorithm
applies technologies either until the manufacturer runs out of cost-
effective technologies,\39\ until the manufacturer exhausts all
available technologies, or, if the manufacturer is assumed to be
willing to pay civil penalties or acquire credits from another
manufacturer, until paying civil penalties or purchasing credits
becomes more cost-effective than increasing vehicle fuel economy. At
this stage, the system assigns an incurred technology cost and updated
fuel economy to each vehicle model, as well as any civil penalties
incurred/credits purchased by each manufacturer. This compliance
simulation process is repeated for each model year included in the
study period (through model year 2050 in this analysis).
---------------------------------------------------------------------------
\39\ Generally, the model considers a technology cost-effective
if it pays for itself in fuel savings within 30 months. Depending on
the settings applied, the model can continue to apply technologies
that are not cost-effective rather than choosing other compliance
options; if it does so, it will apply those additional technologies
in order of cost-effectiveness (i.e., most cost-effective first).
---------------------------------------------------------------------------
At the conclusion of the compliance simulation for a given
regulatory scenario the system transitions between compliance
simulation and effects calculations. This is the point where the system
produces a full representation of the registered light-duty vehicle
population in the United States. The CAFE Model then uses this fleet to
generate estimates of the following (for each model year and calendar
year included in the analysis): Lifetime travel, fuel consumption,
carbon dioxide and criteria pollutant emissions, the magnitude of
various economic externalities related to vehicular travel (e.g.,
congestion and noise), and energy consumption (e.g., the economic costs
of short-term increases in petroleum prices, or social damages
associated with GHG emissions). The system then uses these estimates to
measure the benefits and costs associated with each regulatory
alternative (relative to the no-action alternative).
To perform this analysis, the CAFE Model uses millions of data
points contained in several input files that have been populated by
engineers, economists, and safety and environmental program analysts at
both NHTSA and the DOT's Volpe National Transportations Systems Center
(Volpe). In addition, some of the input data comes from modeling and
simulation analysis performed by experts at Argonne National Laboratory
using their Autonomie full vehicle simulation model and BatPaC battery
cost model. Other inputs are derived from other models, such as the
U.S. Energy Information Administration's (EIA's) National Energy
Modeling System (NEMS), Argonne's ``GREET'' fuel-cycle emissions
analysis model, and U.S. EPA's ``MOVES'' vehicle emissions analysis
model. As NHTSA and Volpe are both organizations within DOT, we use DOT
throughout these sections to refer to the collaborative work performed
for this analysis.
This section and Section III.D describe the inputs that the
compliance simulation requires, including an in-depth discussion of the
technologies used in the analysis, how they are defined in the CAFE
Model, how they are characterized on vehicles that already exist in the
market, how they can be applied to realistically simulate
manufacturer's decisions, their effectiveness, and their cost. The
inputs and analyses for the effects calculations, including economic,
safety, and environmental effects, are discussed later in Sections
III.C through III.H. NHTSA seeks comment on the following discussion.
1. Overview of Inputs to the Analysis
As discussed above, the current analysis involves estimating four
major swaths of effects. First, the analysis estimates how the
application of various combinations of technologies could impact
vehicles' costs and fuel economy levels (and CO<INF>2</INF> emission
rates). Second, the analysis estimates how vehicle manufacturers might
respond to standards by adding fuel-saving technologies to new
vehicles. Third, the analysis estimates how changes in new vehicles
might impact vehicle sales and operation. Finally, the analysis
estimates how the combination of these changes might impact national-
scale energy consumption, emissions, highway safety, and public health.
There are several CAFE Model input files important to the
discussion these first two steps, and these input files are discussed
in detail later in this section and in Section III.D. The Market Data
file contains the detailed description of the vehicle models and model
configurations each manufacturer produces for sale in the U.S. The file
also contains a range of other inputs that, though not specific to
individual vehicle models, may be specific to individual manufacturers.
The Technologies file identifies about six dozen technologies to be
included in the analysis, indicates when and how widely each technology
can be applied to specific types of vehicles, provides most of the
inputs involved in estimating what costs will be incurred, and provides
some of the inputs involved in estimating impacts on vehicle fuel
consumption and weight.
The CAFE Model also makes use of databases of estimates of fuel
consumption impacts and, as applicable, battery costs for different
combinations of fuel saving technologies.\40\ These databases are
termed the FE1 and FE2 Adjustments databases (the main database and the
database specific to plug-in hybrid electric vehicles, applicable to
those vehicles' operation on electricity) and the Battery Costs
database. DOT developed these databases using a large set of full
vehicle and accompanying battery cost model simulations developed by
Argonne National Laboratory. The Argonne simulation outputs, battery
costs, and other reference materials are also discussed in the
following sections.\41\
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\40\ To be used as files provided separately from the model and
loaded every time the model is executed, these databases are
prohibitively large, spanning more than a million records and more
than half a gigabyte. To conserve memory and speed model operation,
DOT has integrated the databases into the CAFE Model executable
file. When the model is run, however, the databases are extracted
and placed in an accessible location on the user's disk drive.
\41\ The Argonne workbooks included in the docket for this
proposal include ten databases that contain the outputs of the
Autonomie full vehicle simulations, two summary workbooks of
assumptions used for the full vehicle simulations, a data
dictionary, and the lookup tables for battery costs generated using
the BatPaC battery cost model.
---------------------------------------------------------------------------
The following discussion in this section and in Section III.D
expands on the inputs used in the compliance analysis. Further detail
is included in Chapters 2 and 3 of the TSD accompanying this proposal,
and all input values relevant to the compliance analysis can be seen in
the Market Data, Technologies, fuel consumption and battery cost
database files, and Argonne
[[Page 49633]]
summary files included in the docket for this proposal. As previously
mentioned, other model input files underlie the effects analysis, and
these are discussed in detail in Sections III.C through III.H. NHTSA
seeks comment on the above discussion.
2. The Market Data File
The Market Data file contains the detailed description of the
vehicle models and model configurations each manufacturer produces for
sale in the U.S. This snapshot of the recent light duty vehicle market,
termed the analysis fleet, or baseline fleet, is the starting point for
the evaluation of different stringency levels for future fuel economy
standards. The analysis fleet provides a reference from which to
project how manufacturers could apply additional technologies to
vehicles to cost-effectively improve vehicle fuel economy, in response
to regulatory action and market conditions.\42\ For this analysis, the
MY 2020 light duty fleet was selected as the baseline for further
evaluation of the effects of different fuel economy standards. The
Market Data file also contains a range of other inputs that, though not
specific to individual vehicle models, may be specific to individual
manufacturers.
---------------------------------------------------------------------------
\42\ The CAFE Model does not generate compliance paths a
manufacturer should, must, or will deploy. It is intended as a tool
to demonstrate a compliance pathway a manufacturer could choose. It
is almost certain all manufacturers will make compliance choices
differing from those projected by the CAFE Model.
---------------------------------------------------------------------------
The Market Data file is an Excel spreadsheet that contains five
worksheets. Three worksheets, the Vehicles worksheet, Engines
worksheet, and Transmissions worksheet, characterize the baseline fleet
for this analysis. The three worksheets contain a characterization of
every vehicle sold in MY 2020 and their relevant technology content,
including the engines and transmissions that a manufacturer uses in its
vehicle platforms and how those technologies are shared across
platforms. In addition, the Vehicles worksheet includes baseline
economic and safety inputs linked to each vehicle that allow the CAFE
Model to estimate economic and safety impacts resulting from any
simulated compliance pathway. The remaining two worksheets, the
Manufacturers worksheet and Credits and Adjustments worksheet, include
baseline compliance positions for each manufacturer, including each
manufacturer's starting CAFE credit banks and whether the manufacturer
is willing to pay civil penalties for noncompliance with CAFE
standards, among other inputs.
New inputs have been added for this analysis in the Vehicles
worksheet and Manufacturers worksheet. The new inputs indicate which
vehicles a manufacturer may reasonably be expected to convert to a zero
emissions vehicle (ZEV) at first redesign opportunity, to comply with
several States' ZEV program provisions. The new inputs also indicate if
a manufacturer has entered into an agreement with California to achieve
more stringent CO<INF>2</INF> emissions reductions targets than those
promulgated in the 2020 final rule.
The following sections discuss how we built the Market Data file,
including characterizing vehicles sold in MY 2020 and their technology
content, and baseline safety, economic, and manufacturer compliance
positions. A detailed discussion of the Market Data file development
process is in TSD Chapter 2.2. NHTSA seeks comment on the below
discussion and the agency's approach to developing the Market Data file
for this proposal.
(a) Characterizing Vehicles and Their Technology Content
The Market Data file integrates information from many sources,
including manufacturer compliance submissions, publicly available
information, and confidential business information. At times, DOT must
populate inputs using analyst judgment, either because information is
still incomplete or confidential, or because the information does not
yet exist.\43\ For this analysis DOT uses mid-model year 2020
compliance data as the basis of the analysis fleet. The compliance data
is supplemented for each vehicle nameplate with manufacturer
specification sheets, usually from the manufacturer media website, or
from online marketing brochures.\44\ For additional information about
how specification sheets inform MY 2020 vehicle technology assignments,
see the technology specific assignments sections in Section III.D.
---------------------------------------------------------------------------
\43\ Forward looking refresh/redesign cycles are one example of
when analyst judgement is necessary.
\44\ The catalogue of reference specification sheets (broken
down by manufacturer, by nameplate) used to populate information in
the market data file is available in the docket.
---------------------------------------------------------------------------
DOT uses the mid-model year 2020 compliance data to create a row on
the Vehicles worksheet in the Market Data file for each vehicle (or
vehicle variant \45\) that lists a certification fuel economy, sales
volume, regulatory class, and footprint. DOT identifies which
combination of modeled technologies reasonably represents the fuel
saving technologies already on each vehicle, and assigns those
technologies to each vehicle, either on the Vehicles worksheet, the
Engines worksheet, or the Transmissions worksheet. The fuel saving
technologies considered in this analysis are listed in Table III-1.
---------------------------------------------------------------------------
\45\ The market data file often includes a few rows for vehicles
that may have identical certification fuel economies, regulatory
classes, and footprints (with compliance sales volumes divided out
among rows), because other pieces of information used in the CAFE
Model may be dissimilar. For instance, in the reference materials
used to create the Market Data file, for a nameplate curb weight may
vary by trim level (with premium trim levels often weighing more on
account of additional equipment on the vehicle), or a manufacturer
may provide consumers the option to purchase a larger fuel tank size
for their vehicle. These pieces of information may not impact the
observed compliance position directly, but curb weight (in relation
to other vehicle attributes) is important to assess mass reduction
technology already used on the vehicle, and fuel tank size is
directly relevant to saving time at the gas pump, which the CAFE
Model uses when calculating the value of avoided time spent
refueling.
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BILLING CODE 4910-59-P
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[[Page 49636]]
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BILLING CODE 4910-59-C
For additional information on the characterization of these
technologies (including the cost, prevalence in the 2020 fleet,
effectiveness estimates, and considerations for their adoption) see the
appropriate technology section in Section III.D or TSD Chapter 3.
DOT also assigns each vehicle a technology class. The CAFE Model
uses the technology class (and engine class, discussed below) in the
Market Data file to reference the most relevant technology costs for
each vehicle, and fuel saving technology combinations. We assign each
vehicle in the fleet a technology class using a two-step algorithm that
takes into account key characteristics of vehicles in the fleet
compared to the baseline characteristics of each technology class.\46\
As discussed further in Section III.C.4.b), there are ten technology
classes used in the CAFE analysis that span five vehicle types and two
performance variants. The
[[Page 49637]]
technology class algorithm and assignment process is discussed in more
detail in TSD Chapter 2.4.2.
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\46\ Baseline 0 to 60 mph accelerations times are assumed for
each technology class as part of the Autonomie full vehicle
simulations. DOT calculates class baseline curb weights and
footprints by averaging the curb weights and footprints of vehicles
within each technology class as assigned in previous analyses.
---------------------------------------------------------------------------
We also assign each vehicle an engine technology class so that the
CAFE Model can reference the powertrain costs in the Technologies file
that most reasonably align with the observed vehicle. DOT assigns
engine technology classes for all vehicles, including electric
vehicles. If an electric powertrain replaces and internal combustion
engine, the electric motor specifications may be different (and hence
costs may be different) depending on the capabilities of the internal
combustion engine it is replacing, and the costs in the technologies
file (on the engine tab) account for the power output and capability of
the gasoline or electric drivetrain.
Parts sharing helps manufacturers achieve economies of scale,
deploy capital efficiently, and make the most of shared research and
development expenses, while still presenting a wide array of consumer
choices to the market. The CAFE Model simulates part sharing by
implementing shared engines, shared transmissions, and shared mass
reduction platforms. Vehicles sharing a part (as recognized in the CAFE
Model), will adopt fuel saving technologies affecting that part
together. To account for parts sharing across products, vehicle model/
configurations that share engines are assigned the same engine
code,\47\ vehicle model/configurations that share transmissions have
the same transmission code, and vehicles that adopt mass reduction
technologies together share the same platform. For more information
about engine codes, transmission codes, and mass reduction platforms
see TSD Chapter 3.
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\47\ Engines (or transmissions) may not be exactly identical, as
specifications or vehicle integration features may be different.
However, the architectures are similar enough that it is likely the
powertrain systems share research and development (R&D), tooling,
and production resources in a meaningful way.
---------------------------------------------------------------------------
Manufacturers often introduce fuel saving technologies at a major
redesign of their product or adopt technologies at minor refreshes in
between major product redesigns. To support the CAFE Model accounting
for new fuel saving technology introduction as it relates to product
lifecycle, the Market Data file includes a projection of redesign and
refresh years for each vehicle. DOT projects future redesign years and
refresh years based on the historical cadence of that vehicle's product
lifecycle. For new nameplates, DOT considers the manufacturer's
treatment of product lifecycles for past products in similar market
segments. When considering year-by-year analysis of standards, the
sizing of redesign and refresh intervals will affect projected
compliance pathways and how quickly manufacturers can respond to
standards. TSD Chapter 2.2.1.7 includes additional information about
the product design cycles assumed for this proposal based on historical
manufacturer product design cycles.
The Market Data file also includes information about air
conditioning (A/C) and off-cycle technologies, but the information is
not currently broken out at a row level, vehicle by vehicle.\48\
Instead, historical data (and forecast projections, which are used for
analysis regardless of regulatory scenario) are listed by manufacturer,
by fleet on the Credits and Adjustments worksheet of the Market Data
file. Section III.D.8 shows model inputs specifying estimated
adjustments (all in grams/mile) for improvements to air conditioner
efficiency and other off-cycle energy consumption, and for reduced
leakage of air conditioner refrigerants with high global warming
potential (GWP). DOT estimated future values based on an expectation
that manufacturers already relying heavily on these adjustments would
continue do so, and that other manufacturers would, over time, also
approach the limits on adjustments allowed for such improvements.
---------------------------------------------------------------------------
\48\ Regulatory provisions regarding off-cycle technologies are
new, and manufacturers have only recently begun including related
detailed information in compliance reporting data. For this
analysis, though, such information was not sufficiently complete to
support a detailed representation of the application of off-cycle
technology to specific vehicle model/configurations in the MY 2020
fleet.
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(b) Characterizing Baseline Safety, Economic, and Compliance Positions
In addition to characterizing vehicles and their technology
content, the Market Data file contains a range of other inputs that,
though not specific to individual vehicle models, may be specific to
individual manufacturers, or that characterize baseline safety or
economic information.
First, the CAFE Model considers the potential safety effect of mass
reduction technologies and crash compatibility of different vehicle
types. Mass reduction technologies lower the vehicle's curb weight,
which may improve crash compatibility and safety, or not, depending on
the type of vehicle. DOT assigns each vehicle in the Market Data file a
safety class that best aligns with the mass-size-safety analysis. This
analysis is discussed in more detail in Section III.H of this proposal
and TSD Chapter 7.
The CAFE Model also includes procedures to consider the direct
labor impacts of manufacturer's response to CAFE regulations,
considering the assembly location of vehicles, engines, and
transmissions, the percent U.S. content (that reflects percent U.S. and
Canada content),\49\ and the dealership employment associated with new
vehicle sales. The Market Data file therefore includes baseline labor
information, by vehicle. Sales volumes also influence total estimated
direct labor projections in the analysis.
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\49\ Percent U.S. content was informed by the 2020 Part 583
American Automobile Labeling Act Reports, appearing on NHTSA's
website.
---------------------------------------------------------------------------
We hold the percent U.S. content constant for each vehicle row for
the duration of the analysis. In practice, this may not be the case.
Changes to trade policy and tariff policy may affect percent U.S.
content in the future. Also, some technologies may be more or less
likely to be produced in the U.S., and if that is the case, their
adoption could affect future U.S. content. NHTSA does not have data at
this time to support varying the percent U.S. content.
We also hold the labor hours projected in the Market Data file per
unit transacted at dealerships, per unit produced for final assembly,
per unit produced for engine assembly, and per unit produced for
transmission assembly constant for the duration of the analysis, and
project that the origin of these activities to remain unchanged. In
practice, it is reasonable to expect that plants could move locations,
or engine and transmission technologies are replaced by another fuel
saving technology (like electric motors and fixed gear boxes) that
could require a meaningfully different amount of assembly labor hours.
NHTSA does not have data at this time to support varying labor hours
projected in the Market Data file, but we will continue to explore
methods to estimate the direct labor impacts of manufacturer's
responses to CAFE standards in future analyses.
As observed from Table III-2, manufacturers employ U.S. labor with
varying intensity. In many cases, vehicles certifying in the light
truck (LT) regulatory class have a larger percent U.S. content than
vehicles certifying in the passenger car (PC) regulatory class.
[[Page 49638]]
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Next, manufacturers may over-comply with CAFE standards and bank
so-called over compliance credits. As discussed further in Section
III.C.7, manufacturers may use these credits later, sell them to other
manufacturers, or let them expire. The CAFE Model does not explicitly
trade credits between and among manufacturers, but staff have adjusted
starting credit banks in the Market Data file to reflect trades that
are likely to happen when the simulation begins (in MY 2020).
Considering information manufacturers have reported regarding
compliance credits, and considering recent manufacturers' compliance
positions, DOT estimates manufacturers' potential use of compliance
credits in earlier MYs. This aligns to an extent that represents how
manufacturers could deplete their credit banks rather than producing
high volume vehicles with fuel saving technologies in earlier MYs. This
also avoids the unrealistic application of technologies for
manufacturers in early analysis years that typically rely on credits.
For a complete discussion about how this data is collected and assigned
in the Market Data file, see TSD Chapter 2.2.2.3.
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\50\ Tesla does not have internal combustion engines, or multi-
speed transmissions, even though they are identified as producing
engine and transmission systems in the United States in the Market
Data file.
---------------------------------------------------------------------------
The Market Data file also includes assumptions about a vehicle
manufacturer's preferences towards civil penalty payments. EPCA
requires that if a manufacturer does not achieve compliance with a CAFE
standard in a given model year and cannot apply credits sufficient to
cover the compliance shortfall, the manufacturer must pay civil
penalties (i.e., fines) to the Federal Government. If inputs indicate
that a manufacturer treats civil penalty payment as an economic choice
(i.e., one to be taken if doing so would be economically preferable to
applying further technology toward compliance), the CAFE Model, when
evaluating the manufacturer's response to CAFE standards in a given
model year, will apply fuel-saving technology only up to the point
beyond which doing so would be more expensive (after subtracting the
value of avoided fuel outlays) than paying civil penalties.
For this analysis, DOT exercises the CAFE Model with inputs
treating all manufacturers as treating civil penalty
[[Page 49639]]
payment as an economic choice through model year 2023. While DOT
expects that only manufacturers with some history of paying civil
penalties would actually treat civil penalty payment as an acceptable
option, the CAFE Model does not currently simulate compliance credit
trading between manufacturers, and DOT expects that this treatment of
civil penalty payment will serve as a reasonable proxy for compliance
credit purchases some manufacturers might actually make through model
year 2023. These input assumptions for model years through 2023 reduce
the potential that the model will overestimate technology application
in the model years leading up to those for which the agency is
proposing new standards. As in past CAFE rulemaking analyses (except
that supporting the 2020 final rule), DOT has treated manufacturers
with some history of civil penalty payment (i.e., BMW, Daimler, FCA,
Jaguar-Land Rover, Volvo, and Volkswagen) as continuing to treat civil
penalty payment as an acceptable option beyond model year 2023, but has
treated all other manufacturers as unwilling to do so beyond model year
2023.
Next, the CAFE Model uses an ``effective cost'' metric to evaluate
options to apply specific technologies to specific engines,
transmissions, and vehicle model configurations. Expressed on a $/
gallon basis, the analysis computes this metric by subtracting the
estimated values of avoided fuel outlays and civil penalties from the
corresponding technology costs, and then dividing the result by the
quantity of avoided fuel consumption. The analysis computes the value
of fuel outlays over a ``payback period'' representing the
manufacturer's expectation that the market will be willing to pay for
some portion of fuel savings achieved through higher fuel economy. Once
the model has applied enough technology to a manufacturer's fleet to
achieve compliance with CAFE standards (and CO<INF>2</INF> standards
and ZEV mandates) in a given model year, the model will apply any
further fuel economy improvements estimated to produce a negative
effective cost (i.e., any technology applications for which avoided
fuel outlays during the payback period are larger than the
corresponding technology costs). As discussed above in Section III.A
and below in Section III.C, DOT anticipates that manufacturers are
likely to act as if the market is willing to pay for avoided fuel
outlays expected during the first 30 months of vehicle operation.
We seek comment on whether this expectation is appropriate, or
whether some other amount of time should be used. If commenters believe
a different amount of time should be used for the payback assumption,
it would be most helpful if commenters could define the amount of time,
provide an explanation of why that amount of time is preferable,
provide any data or information on which the amount of time is based,
and provide any discussion of how changing this assumption would
interact with other elements in the analysis.
In addition, the Market Data file includes two new sets of inputs
for this analysis. In 2020, five vehicle manufacturers reached a
voluntary commitment with the state of California to improve the fuel
economy of their future nationwide fleets above levels required by the
2020 final rule. For this analysis, compliance with this agreement is
in the baseline case for designated manufacturers. The Market Data file
contains inputs indicating whether each manufacturer has committed to
exceed Federal requirements per this agreement.
Finally, when considering other standards that may affect fuel
economy compliance pathways, DOT includes projected zero emissions
vehicles (ZEV) that would be required for manufacturers to meet
standards in California and Section 177 States, per the waiver granted
under the Clean Air Act. To support the inclusion of the ZEV program in
the analysis, DOT identifies specific vehicle model/configurations that
could adopt BEV technology in response to the ZEV program, independent
of CAFE standards, at the first redesign opportunity. These ZEVs are
identified in the Market Data file as future BEV200s, BEV300s, or
BEV400s. Not all announced BEV nameplates appear in the MY 2020 Market
Data file; in these cases, in consultation with CARB, DOT used the
volume from a comparable vehicle in the manufacturer's Market Data file
portfolio as a proxy. The Market Data file also includes information
about the portion of each manufacturer's sales that occur in California
and Section 177 states, which is helpful for determining how many ZEV
credits each manufacturer will need to generate in the future to comply
with the ZEV program with their own portfolio in the rulemaking
timeframe. These new procedures are described in detail below and in
TSD Chapter 2.3.
3. Simulating the Zero Emissions Vehicle Program
California's Zero Emissions Vehicle (ZEV) program is one part of a
program of coordinated standards that the California Air Resources
Board (CARB) has enacted to control emissions of criteria pollutants
and greenhouse gas emissions from vehicles. The program began in 1990,
within the low-emission vehicle (LEV) regulation,\51\ and has since
expanded to include eleven other states.\52\ These states may be
referred to as Section 177 states, in reference to Section 177 of the
Clean Air Act's grant of authority to allow these states to adopt
California's air quality standards,\53\ but it is important to note
that not all Section 177 states have adopted the ZEV program
component.\54\ In the following discussion of the incorporation of the
ZEV program into the CAFE Model, any reference to the Section 177
states refers to those states that have adopted California's ZEV
program requirements.
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\51\ California Air Resource Board (CARB), Zero-Emission Vehicle
Program. California Air Resources Board. Accessed April 12, 2021.
<a href="https://ww2.arb.ca.gov/our-work/programs/zero-emission-vehicle-program/about">https://ww2.arb.ca.gov/our-work/programs/zero-emission-vehicle-program/about</a>.
\52\ At the time of writing, the Section 177 states that have
adopted the ZEV program are Colorado, Connecticut, Maine, Maryland,
Massachusetts, New Jersey, New York, Oregon, Rhode Island, Vermont,
and Washington. See Vermont Department of Environmental
Conservation, Zero Emission Vehicles. Accessed April 12, 2021.
https://dec.vermont.gov/air-quality/mobile-sources/
zev#:~:text=To%20date%2C%2012%20states%20have,ZEVs%20over%20the%20nex
t%20decade.
\53\ Section 177 of the Clean Air Act allows other states to
adopt California's air quality standards.
\54\ At the time of writing, Delaware and Pennsylvania are the
two states that have adopted the LEV standards, but not the ZEV
portion.
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To account for the ZEV program, and particularly as other states
have recently adopted California's ZEV standards, DOT includes the main
provisions of the ZEV program in the CAFE Model's analysis of
compliance pathways. As explained below, incorporating the ZEV program
into the model includes converting vehicles that have been identified
as potential ZEV candidates into battery-electric vehicles (BEVs) at
the first redesign opportunity, so that a manufacturer's fleet meets
calculated ZEV credit requirements. Since ZEV program compliance
pathways happen independently from the adoption of fuel saving
technology in response to increasing CAFE standards, the ZEV program is
considered in the baseline of the analysis, and in all other regulatory
alternatives.
Through its ZEV program, California requires that all manufacturers
that sell cars within the state meet ZEV credit standards. The current
credit requirements are calculated based on manufacturers' California
sales volumes. Manufacturers primarily earn ZEV credits through the
production of BEVs, fuel cell vehicles (FCVs), and
[[Page 49640]]
transitional zero-emissions vehicles (TZEVs), which are vehicles with
partial electrification, namely plug-in hybrids (PHEVs). Total credits
are calculated by multiplying the credit value each ZEV receives by the
vehicle's volume.
The ZEV and PHEV/TZEV credit value per vehicle is calculated based
on the vehicle's range; ZEVs may earn up to 4 credits each and PHEVs
with a US06 all-electric range capability of 10 mi or higher receive an
additional 0.2 credits on top of the credits received based on all-
electric range.\55\ The maximum PHEV credit amount available per
vehicle is 1.10.\56\ Note however that CARB only allows intermediate-
volume manufacturers to meet their ZEV credit requirements through PHEV
production.\57\
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\55\ US06 is one of the drive cycles used to test fuel economy
and all-electric range, specifically for the simulation of
aggressive driving. See Dynamometer Drive Schedules [verbar] Vehicle
and Fuel Emissions Testing [verbar] U.S. EPA for more information,
as well as Section III.C.4 and Section III.D.3.d).
\56\ 13 CCR 1962.2(c)(3).
\57\ 13 CCR 1962.2(c)(3).
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DOT's method for simulating the ZEV program involves several steps;
first, DOT calculates an approximate ZEV credit target for each
manufacturer based on the manufacturer's national sales volumes, share
of sales in Section 177 states, and the CARB credit requirements. Next,
DOT identifies a general pathway to compliance that involves accounting
for manufacturers' potential use of ZEV overcompliance credits or other
credit mechanisms, and the likelihood that manufacturers would choose
to comply with the requirements with BEVs rather than PHEVs or other
types of compliant vehicles, in addition to other factors. For this
analysis, as discussed further below, DOT consulted with CARB to
determine reasonable assumptions for this compliance pathway. Finally,
DOT identifies vehicles in the MY 2020 analysis fleet that
manufacturers could reasonably adapt to comply with the ZEV standards
at the first opportunity for vehicle redesign, based on publicly
announced product plans and other information. Each of these steps is
discussed in turn, below, and a more detailed description of DOT's
simulation of the ZEV program is included in TSD Chapter 2.3.
The CAFE Model is designed to present outcomes at a national scale,
so the ZEV analysis considers the Section 177 states as a group as
opposed to estimating each state's ZEV credit requirements
individually. To capture the appropriate volumes subject to the ZEV
requirement, DOT calculates each manufacturer's total market share in
Section 177 states. DOT also calculates the overall market share of
ZEVs in Section 177 states, in order to estimate as closely as possible
the number of predicted ZEVs we expect all manufacturers to sell in
those states. These shares are then used to scale down national-level
information in the CAFE Model to ensure that we represent only Section
177 states in the final calculation of ZEV credits that we project each
manufacturer to earn in future years.
DOT uses model year 2019 National Vehicle Population Profile (NVPP)
from IHS Markit--Polk to calculate these percentages.\58\ These data
include vehicle characteristics such as powertrain, fuel type,
manufacturer, nameplate, and trim level, as well as the state in which
each vehicle is sold, which allows staff to identify the different
types of ZEVs manufacturers sell in the Section 177 state group. DOT
may make use of future Polk data in updating the analysis for the final
rule and may include other states that join the ZEV program after the
publication of this proposal, if necessary.
---------------------------------------------------------------------------
\58\ National Vehicle Population Profile (NVPP) 2020, IHS
Markit--Polk. At the time of the analysis, model year 2019 data from
the NVPP contained the most current estimate of market shares by
manufacturer, and best represented the registered vehicle population
on January 1, 2020.
---------------------------------------------------------------------------
We calculate sales volumes for the ZEV credit requirement based on
each manufacturer's future assumed market share in Section 177 states.
DOT decided to carry each manufacturer's ZEV market shares forward to
future years, after examination of past market share data from model
year 2016, from the 2017 version of the NVPP.\59\ Comparison of these
data to the 2020 version showed that manufacturers' market shares
remain fairly constant in terms of geographic distribution. Therefore,
we determined that it was reasonable to carry forward the recently
calculated market shares to future years.
---------------------------------------------------------------------------
\59\ National Vehicle Population Profile (NVPP) 2017, IHS
Markit--Polk.
---------------------------------------------------------------------------
We calculate total credits required for ZEV compliance by
multiplying the percentages from CARB's ZEV requirement schedule by the
Section 177 state volumes. CARB's credit percentage requirement
schedule for the years covered in this analysis begins at 9.5% in 2020
and ramps up in increments to 22% by 2025.\60\ Note that the
requirements do not currently change after 2025.\61\
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\60\ See 13 CCR 1962.2(b). The percentage credit requirements
are as follows: 9.5% in 2020, 12% in 2021, 14.5% in 2022, 17% in
2023, 19.5% in 2024, and 22% in 2025 and onward.
\61\ 13 CCR 1962.2(b).
---------------------------------------------------------------------------
We generate national sales volume predictions for future years
using the Compliance Report, a CAFE Model output file that includes
simulated sales by manufacturer, fleet, and model year. We use a
Compliance Report that corresponds to the baseline scenario of 1.5% per
year increases in standards for both passenger car and light truck
fleets. The resulting national sales volume predictions by manufacturer
are then multiplied by each manufacturer's total market share in the
Section 177 states to capture the appropriate volumes in the ZEV
credits calculation. Required credits by manufacturer, per year, are
determined by multiplying the Section 177 state volumes by CARB's ZEV
credit percentage requirement. These required credits are subsequently
added to the CAFE Model inputs as targets for manufacturer compliance
with ZEV standards in the CAFE baseline.
The estimated ZEV credit requirements serve as a target for
simulating ZEV compliance in the baseline. To achieve this, DOT
determines a modeling philosophy for ZEV pathways, reviews various
sources for information regarding upcoming ZEV programs, and inserts
those programs into the analysis fleet inputs. As manufacturers can
meet ZEV standards in a variety of different ways, using various
technology combinations, the analysis must include certain simplifying
assumptions in choosing ZEV pathways. We made these assumptions in
conjunction with guidance from CARB staff. The following sections
discuss the approach used to simulate a pathway to ZEV program
compliance in this analysis.
First, DOT targeted 2025 compliance, as opposed to assuming
manufacturers would perfectly comply with their credit requirements in
each year prior to 2025. This simplifying assumption was made upon
review of past history of ZEV credit transfers, existing ZEV credit
banks, and redesign schedules. DOT focused on integrating ZEV
technology throughout that timeline with the target of meeting 2025
obligations; thus, some manufacturers are estimated to over-comply or
under-comply, depending on their individual situations, in the years
2021-2024.
Second, DOT determined that the most reasonable way to model ZEV
compliance would be to allow under-compliance in certain cases and
assume that some manufacturers would not meet their ZEV obligation on
their own in 2025. Instead, these manufacturers were assumed to prefer
to purchase credits from another manufacturer with a credit surplus.
Reviews of past ZEV credit transfers between manufacturers informed the
decision to make this
[[Page 49641]]
simplifying assumption.\62\ CARB advised that for these manufacturers,
the CAFE Model should still project that each manufacturer meet
approximately 80% of their ZEV requirements with technology included in
their own portfolio. Manufacturers that were observed to have generated
many ZEV credits in the past or had announced major upcoming BEV
initiatives were projected to meet 100% of their ZEV requirements on
their own, without purchasing ZEV credits from other manufacturers.\63\
---------------------------------------------------------------------------
\62\ See <a href="https://ww2.arb.ca.gov/our/work/programs/advanced-clean-cars-program/zev-program-zero-emission-vehicle-credit-balances">https://ww2.arb.ca.gov/our/work/programs/advanced-clean-cars-program/zev-program-zero-emission-vehicle-credit-balances</a>
for past credit balances and transfer information.
\63\ The following manufacturers were assumed to meet 100% ZEV
compliance: Ford, General Motors, Hyundai, Kia, Jaguar Land Rover,
and Volkswagen Automotive. Tesla was also assumed to meet 100% of
its required standards, but the analyst team did not need to add
additional ZEV substitutes to the baseline for this manufacturer.
---------------------------------------------------------------------------
Third, DOT agreed that manufacturers would meet their ZEV credit
requirements in 2025 though the production of BEVs. As discussed above,
manufacturers may choose to build PHEVs or FCVs to earn some portion of
their required ZEV credits. However, DOT projected that manufacturers
would rely on BEVs to meet their credit requirements, based on reviews
of press releases and industry news, as well as discussion with CARB.
Since nearly all manufacturers have announced some plans to produce
BEVs at a scale meaningful to future ZEV requirements, DOT agreed that
this was a reasonable assumption.\64\ Furthermore, as CARB only allows
intermediate-volume manufacturers to meet their ZEV credit requirements
through the production of PHEVs, and the volume status of these few
manufacturers could change over the years, assuming BEV production for
ZEV compliance is the most straightforward path.
---------------------------------------------------------------------------
\64\ See TSD Chapter 2.3 for a list of potential BEV programs
recently announced by manufacturers.
---------------------------------------------------------------------------
Fourth, to account for the new BEV programs announced by some
manufacturers, DOT identified vehicles in the 2020 fleet that closely
matched the upcoming BEVs, by regulatory class, market segment, and
redesign schedule. DOT made an effort to distribute ZEV candidate
vehicles by CAFE regulatory class (light truck, passenger car), by
manufacturer, in a manner consistent with the 2020 manufacturer fleet
mix. Since passenger car and light truck mixes by manufacturer could
change in response to the CAFE policy alternative under consideration,
this effort was deemed necessary in order to avoid redistributing the
fleet mix in an unrealistic manner. However, there were some exceptions
to this assumption, as some manufacturers are already closer to meeting
their ZEV obligation through 2025 with BEVs currently produced, and
some manufacturers underperform their compliance targets more so in one
fleet than another. In these cases, DOT deviated from keeping the LT/PC
mix of BEVs evenly distributed across the manufacturer's portfolio.\65\
---------------------------------------------------------------------------
\65\ The GM light truck and passenger car distribution is one
such example.
---------------------------------------------------------------------------
DOT then identified future ZEV programs that could plausibly
contribute towards the ZEV requirements for each manufacturer by 2025.
To obtain this information, DOT examined various sources, including
trade press releases, industry announcements, and investor reports. In
many cases, these BEV programs are in addition to programs already in
production.\66\ Some manufacturers have not yet released details of
future electric vehicle programs at the time of writing, but have
indicated goals of reaching certain percentages of electric vehicles in
their portfolios by a specified year. In these cases, DOT reviewed the
manufacturer's current fleet characteristics as well as the
aspirational information in press releases and other news in order to
make reasonable assumptions about the vehicle segment and range of
those future BEVs. DOT may reassign some manufacturer's ZEV programs in
the analysis fleet for the final rule based on stakeholder comments or
other public information releases that occur in time for the final rule
analysis.
---------------------------------------------------------------------------
\66\ Examples of BEV programs already in production include the
Nissan Leaf and the Chevrolet Bolt.
---------------------------------------------------------------------------
Overall, analysts assumed that manufacturers would lean towards
producing BEV300s rather than BEV200s, based on the information
reviewed and an initial conversation with CARB.\67\ Phase-in caps were
also considered, especially for BEV200, with the understanding that the
CAFE Model will always pick BEV200 before BEV300 or BEV400, until the
quantity of BEV200s is exhausted. See Section III.D.3.c) for details
regarding BEV phase-in caps.
---------------------------------------------------------------------------
\67\ BEV300s are 300-mile range battery-electric vehicles. See
Section III.D.3.b) for further information regarding electrification
fleet assignments.
---------------------------------------------------------------------------
BEVs, especially BEVs with smaller battery packs and less range,
are less likely to meet all the performance needs of traditional pickup
truck owners today. However, new markets for BEVs may emerge,
potentially in the form of electric delivery trucks and some light-duty
electric truck applications in state and local government. The extent
to which BEVs will be used in these and other new markets is difficult
to project. DOT did identify certain trucks as upcoming BEVs for ZEV
compliance, and these BEVs were expected to have higher ranges, due to
the specific performance needs associated with these vehicles. Outside
of the ZEV inputs described here, the CAFE Model does not handle the
application of BEV technology with any special considerations as to
whether the vehicle is a pickup truck or not. Comments from
manufacturers are solicited on this issue.
Finally, in order to simulate manufacturers' compliance with their
particular ZEV credits target, 142 rows in the analysis fleet were
identified as substitutes for future ZEV programs. As discussed above,
the analysis fleet summarizes the roughly 13.6 million light-duty
vehicles produced and sold in the United States in the 2020 model year
with more than 3,500 rows, each reflecting information for one vehicle
type observed. Each row includes the vehicle's nameplate and trim
level, the sales volume, engine, transmission, drive configuration,
regulatory class, projected redesign schedule, and fuel saving
technologies, among other attributes.
As the goal of the ZEV analysis is to simulate compliance with the
ZEV program in the baseline, and the analysis fleet only contains
vehicles produced during model year 2020, DOT identified existing
models in the analysis fleet that shared certain characteristics with
upcoming BEVs. DOT also focused on identifying substitute vehicles with
redesign years similar to the future BEV's introduction year. The sales
volumes of those existing models, as predicted for 2025, were then used
to simulate production of the upcoming BEVs. DOT identified a
combination of rows that would meet the ZEV target, could contribute
productively towards CAFE program obligations (by manufacturer and by
fleet), and would introduce BEVs in each manufacturer's portfolio in a
way that reasonably aligned with projections and announcements. DOT
tagged each of these rows with information in the Market Data file,
instructing the CAFE Model to apply the specified BEV technology to the
row at the first redesign year, regardless of the scenario or type of
CAFE or GHG simulation.
The CAFE Model does not optimize compliance with the ZEV mandate;
it relies upon the inputs described in this section in order to
estimate each
[[Page 49642]]
manufacturer's resulting ZEV credits. The resulting amount of ZEV
credits earned by manufacturer for each model year can be found in the
CAFE Model's Compliance file.
Not all ZEV-qualifying vehicles in the U.S. earn ZEV credits, as
they are not all sold in states that have adopted ZEV regulations. In
order to reflect this in the CAFE Model, which only estimates sales
volumes at the national level, the percentages calculated for each
manufacturer are used to scale down the national-level volumes.
Multiplying national-level ZEV sales volumes by these percentages
ensures that only the ZEVs sold in Section 177 states count towards the
ZEV credit targets of each manufacturer.\68\ See Section 5.8 of the
CAFE Model Documentation for a detailed description of how the model
applied these ZEV technologies and any changes made to the model's
programming for the incorporation of the ZEV program into the baseline.
---------------------------------------------------------------------------
\68\ The single exception to this assumption is Mazda, as Mazda
has not yet produced any ZEV-qualifying vehicles at the time of
writing. Thus, the percentage of ZEVs sold in Section 177 states
cannot be calculated from existing data. However, Mazda has
indicated its intention to produce ZEV-qualifying vehicles in the
future, so DOT assumed that 100% of future ZEVs would be sold in
Section 177 states for the purposes of estimating ZEV credits in the
CAFE Model.
---------------------------------------------------------------------------
As discussed above, DOT made an effort to distribute the newly
identified ZEV candidates between CAFE regulatory classes (light truck
and passenger car) in a manner consistent with the proportions seen in
the 2020 analysis fleet, by manufacturer. As mentioned previously,
there were a few exceptions to this assumption in cases where
manufacturers' regulatory class distribution of current or planned ZEV
programs clearly differed from their regulatory class distribution as a
whole.
In some instances, the regulatory distribution of flagged ZEV
candidates leaned towards a higher portion of PCs. The reasoning behind
this differs in each case, but there is an observed pattern in the 2020
analysis fleet of fewer BEVs being light trucks, especially pickups.
The 2020 analysis fleet contains no BEV pickups in the light truck
segment. The slow emergence of electric pickups could be linked to the
specific performance needs associated with pickup trucks. However, the
market for BEVs may emerge in unexpected ways that are difficult to
project. Examples of this include anticipated electric delivery trucks
and light-duty electric trucks used by state and local governments. Due
to these considerations, DOT tagged some trucks as BEVs for ZEV, and
expected that these would generally be of higher ranges.
TSD Chapter 2.3 includes more information about the process we use
to simulate ZEV program compliance in this analysis.
4. Technology Effectiveness Values
The next input we use to simulate manufacturers' decision-making
processes for the year-by-year application of technologies to specific
vehicles are estimates of how effective each technology would be at
reducing fuel consumption. For this analysis, we use full-vehicle
modeling and simulation to estimate the fuel economy improvements
manufacturers could make to a fleet of vehicles, considering the
vehicles' technical specifications and how combinations of technologies
interact. Full-vehicle modeling and simulation uses physics-based
models to predict how combinations of technologies perform as a full
system under defined conditions. We use full vehicle simulations
performed in Autonomie, a physics-based full-vehicle modeling and
simulation software developed and maintained by the U.S. Department of
Energy's Argonne National Laboratory.\69\
---------------------------------------------------------------------------
\69\ Islam, E. S., A. Moawad, N. Kim, R. Vijayagopal, and A.
Rousseau. A Detailed Vehicle Simulation Process to Support CAFE
Standards for the MY 2024-2026 Analysis. ANL/ESD-21/9 [hereinafter
Autonomie model documentation].
---------------------------------------------------------------------------
A model is a mathematical representation of a system, and
simulation is the behavior of that mathematical representation over
time. In this analysis, the model is a mathematical representation of
an entire vehicle,\70\ including its individual components such as the
engine and transmission, overall vehicle characteristics such as mass
and aerodynamic drag, and the environmental conditions, such as ambient
temperature and barometric pressure. We simulate the model's behavior
over test cycles, including the 2-cycle laboratory compliance tests (or
2-cycle tests),\71\ to determine how the individual components
interact.
---------------------------------------------------------------------------
\70\ Each full vehicle model in this analysis is composed of
sub-models, which is why the full vehicle model could also be
referred to as a full system model, composed of sub-system models.
\71\ EPA's compliance test cycles are used to measure the fuel
economy of a vehicle. For readers unfamiliar with this process, it
is like running a car on a treadmill following a program--or more
specifically, two programs. The ``programs'' are the ``urban
cycle,'' or Federal Test Procedure (abbreviated as ``FTP''), and the
``highway cycle,'' or Highway Fuel Economy Test (abbreviated as
``HFET'' or ``HWFET''), and they have not changed substantively
since 1975. Each cycle is a designated speed trace (of vehicle speed
versus time) that all certified vehicles must follow during testing.
The FTP is meant roughly to simulate stop and go city driving, and
the HFET is meant roughly to simulate steady flowing highway driving
at about 50 mph.
---------------------------------------------------------------------------
Using full-vehicle modeling and simulation to estimate technology
efficiency improvements has two primary advantages over using single or
limited point estimates. An analysis using single or limited point
estimates may assume that, for example, one fuel economy-improving
technology with an effectiveness value of 5 percent by itself and
another technology with an effectiveness value of 10 percent by itself,
when applied together achieve an additive improvement of 15 percent.
Single point estimates generally do not provide accurate effectiveness
values because they do not capture complex relationships among
technologies. Technology effectiveness often differs significantly
depending on the vehicle type (e.g., sedan versus pickup truck) and the
way in which the technology interacts with other technologies on the
vehicle, as different technologies may provide different incremental
levels of fuel economy improvement if implemented alone or in
combination with other technologies. Any oversimplification of these
complex interactions leads to less accurate and often overestimated
effectiveness estimates.
In addition, because manufacturers often implement several fuel-
saving technologies simultaneously when redesigning a vehicle, it is
difficult to isolate the effect of individual technologies using
laboratory measurement of production vehicles alone. Modeling and
simulation offer the opportunity to isolate the effects of individual
technologies by using a single or small number of baseline vehicle
configurations and incrementally adding technologies to those baseline
configurations. This provides a consistent reference point for the
incremental effectiveness estimates for each technology and for
combinations of technologies for each vehicle type. Vehicle modeling
also reduces the potential for overcounting or undercounting technology
effectiveness.
An important feature of this analysis is that the incremental
effectiveness of each technology and combinations of technologies
should be accurate and relative to a consistent baseline vehicle. For
this analysis, the baseline absolute fuel economy value for each
vehicle in the analysis fleet is based on CAFE compliance data for each
make and model.\72\ The absolute fuel economy values of the full
vehicle simulations are
[[Page 49643]]
used only to determine incremental effectiveness and are never used
directly to assign an absolute fuel economy value to any vehicle model
or configuration. For subsequent technology changes, we apply the
incremental effectiveness values of one or more technologies to the
baseline fuel economy value to determine the absolute fuel economy
achieved for applying the technology change.
---------------------------------------------------------------------------
\72\ See Section III.C.2 for further discussion of CAFE
compliance data in the Market Data file.
---------------------------------------------------------------------------
As an example, if a Ford F-150 2-wheel drive crew cab and short bed
in the analysis fleet has a fuel economy value of 30 mpg for CAFE
compliance, 30 mpg will be considered the reference absolute fuel
economy value. A similar full vehicle model node in the Autonomie
simulation may begin with an average fuel economy value of 32 mpg, and
with incremental addition of a specific technology X its fuel economy
improves to 35 mpg, a 9.3 percent improvement. In this example, the
incremental fuel economy improvement (9.3 percent) from technology X
would be applied to the F-150's 30 mpg absolute value.
We determine the incremental effectiveness of technologies as
applied to the thousands of unique vehicle and technology combinations
in the analysis fleet. Although, as mentioned above, full-vehicle
modeling and simulation reduces the work and time required to assess
the impact of moving a vehicle from one technology state to another, it
would be impractical--if not impossible--to build a unique vehicle
model for every individual vehicle in the analysis fleet. Therefore, as
discussed in the following sections, the Autonomie analysis relies on
ten vehicle technology class models that are representative of large
portions of the analysis fleet vehicles. The vehicle technology classes
ensure that key vehicle characteristics are reasonably represented in
the full vehicle models. The next sections discuss the details of the
technology effectiveness analysis input specifications and assumptions.
NHTSA seeks comment on the following discussion.
(a) Full Vehicle Modeling and Simulation
As discussed above, for this analysis we use Argonne's full vehicle
modeling tool, Autonomie, to build vehicle models with different
technology combinations and simulate the performance of those models
over regulatory test cycles. The difference in the simulated
performance between full vehicle models, with differing technology
combination, is used to determine effectiveness values. We consider
over 50 individual technologies as inputs to the Autonomie
modeling.\73\ These inputs consist of engine technologies, transmission
technologies, powertrain electrification, lightweighting, aerodynamic
improvements, and tire rolling resistance improvements. Section III.D
broadly discusses each of the technology groupings definitions, inputs,
and assumptions. A deeper discussion of the Autonomie modeled
subsystems, and how inputs feed the sub models resulting in outputs, is
contained in the Autonomie model documentation that accompanies this
analysis. The 50 individual technologies, when considered with the ten
vehicle technology classes, result in over 1.1 million individual
vehicle technology combination models. For additional discussion on the
full vehicle modeling used in this analysis see TSD Chapter 2.
---------------------------------------------------------------------------
\73\ See Autonomie model documentation; ANL--All
Assumptions_Summary_NPRM_022021.xlsx; ANL--Data Dictionary_January
2021.xlsx.
---------------------------------------------------------------------------
While Argonne built full-vehicle models and ran simulations for
many combinations of technologies, it did not simulate literally every
single vehicle model/configuration in the analysis fleet. Not only
would it be impractical to assemble the requisite detailed information
specific to each vehicle/model configuration, much of which would
likely only be provided on a confidential basis, doing so would
increase the scale of the simulation effort by orders of magnitude.
Instead, Argonne simulated ten different vehicle types, corresponding
to the five ``technology classes'' generally used in CAFE analysis over
the past several rulemakings, each with two performance levels and
corresponding vehicle technical specifications (e.g., small car, small
performance car, pickup truck, performance pickup truck, etc.).
Technology classes are a means of specifying common technology
input assumptions for vehicles that share similar characteristics.
Because each vehicle technology class has unique characteristics, the
effectiveness of technologies and combinations of technologies is
different for each technology class. Conducting Autonomie simulations
uniquely for each technology class provides a specific set of
simulations and effectiveness data for each technology class. In this
analysis the technology classes are compact cars, midsize cars, small
SUVs, large SUVs, and pickup trucks. In addition, for each vehicle
class there are two levels of performance attributes (for a total of 10
technology classes). The high performance and low performance vehicles
classifications allow for better diversity in estimating technology
effectiveness across the fleet.
For additional discussion on the development of the vehicle
technology classes used in this analysis and the attributes used to
characterize each vehicle technology class, see TSD Chapter 2.4 and the
Autonomie model documentation.
Before any simulation is initiated in Autonomie, Argonne must
``build'' a vehicle by assigning reference technologies and initial
attributes to the components of the vehicle model representing each
technology class. The reference technologies are baseline technologies
that represent the first step on each technology pathway used in the
analysis. For example, a compact car is built by assigning it a
baseline engine (DOHC, VVT, port fuel injection (PFI)), a baseline
transmission (AT5), a baseline level of aerodynamic improvement
(AERO0), a baseline level of rolling resistance improvement (ROLL0), a
baseline level of mass reduction technology (MR0), and corresponding
attributes from the Argonne vehicle assumptions database like
individual component weights. A baseline vehicle will have a unique
starting point for the simulation and a unique set of assigned inputs
and attributes, based on its technology class. Argonne collected over a
hundred baseline vehicle attributes to build the baseline vehicle for
each technology class. In addition, to account for the weight of
different engine sizes, like 4-cylinder versus 8-cylinder or
turbocharged versus naturally aspirated engines, Argonne developed a
relationship curve between peak power and engine weight based on the
A2Mac1 benchmarking data. Argonne uses the developed relationship to
estimate mass for all engines. For additional discussion on the
development and optimization of the baseline vehicle models and the
baseline attributes used in this analysis see TSD Chapter 2.4 and the
Autonomie model documentation.
The next step in the process is to run a powertrain sizing
algorithm that ensures the built vehicle meets or exceeds defined
performance metrics, including low-speed acceleration (time required to
accelerate from 0-60 mph), high-speed passing acceleration (time
required to accelerate from 50-80 mph), gradeability (the ability of
the vehicle to maintain constant 65 miles per hour speed on a six
percent upgrade), and towing capacity. Together, these performance
criteria are widely used by the automotive industry as metrics to
quantify vehicle performance attributes
[[Page 49644]]
that consumers observe and that are important for vehicle utility and
customer satisfaction.
As with conventional vehicle models, electrified vehicle models
were also built from the ground up. For MY 2020, the U.S. market has an
expanded number of available hybrid and electric vehicle models. To
capture improvements for electrified vehicles for this analysis, DOT
applied a mass regression analysis process that considers electric
motor weight versus electric motor power (similar to the regression
analysis for internal combustion engine weights) for vehicle models
that have adopted electric motors. Benchmarking data for hybrid and
electric vehicles from the A2Mac1 database were analyzed to develop a
regression curve of electric motor peak power versus electric motor
weight.\74\
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\74\ See Autonomie model documentation, Chapter 5.2.10 Electric
Machines System Weight.
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We maintain performance neutrality in the full vehicle simulations
by resizing engines, electric machines, and hybrid electric vehicle
battery packs at specific incremental technology steps. To address
product complexity and economies of scale, engine resizing is limited
to specific incremental technology changes that would typically be
associated with a major vehicle or engine redesign. This is intended to
reflect manufacturers' comments to DOT on how they consider engine
resizing and product complexity, and DOT's observations on industry
product complexity. A detailed discussion on powertrain sizing can be
found in TSD Chapter 2.4 and in the Autonomie model documentation.
After all vehicle class and technology combination models have been
built, Autonomie simulates the vehicles' performance on test cycles to
calculate the effectiveness improvement of adding fuel-economy-
improving technologies to the vehicle. Simulating vehicles' performance
using tests and procedures specified by Federal law and regulations
minimizes the potential variation in determining technology
effectiveness.
For vehicles with conventional powertrains and micro hybrids,
Autonomie simulates the vehicles per EPA 2-cycle test procedures and
guidelines.\75\ For mild and full hybrid electric vehicles and FCVs,
Autonomie simulates the vehicles using the same EPA 2-cycle test
procedure and guidelines, and the drive cycles are repeated until the
initial and final state of charge are within a SAE J1711 tolerance. For
PHEVs, Autonomie simulates vehicles per similar procedures and
guidelines as prescribed in SAE J1711.\76\ For BEVs Autonomie simulates
vehicles per similar procedures and guidelines as prescribed in SAE
J1634.\77\
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\75\ 40 CFR part 600.
\76\ PHEV testing is broken into several phases based on SAE
J1711: Charge-sustaining on the city cycle and HWFET cycle, and
charge-depleting on the city and HWFET cycles.
\77\ SAE J1634. ``Battery Electric Vehicle Energy Consumption
and Range Test Procedure.'' July 12, 2017.
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(b) Performance Neutrality
The purpose of the CAFE analysis is to examine the impact of
technology application that can improve fuel economy. When the fuel
economy-improving technology is applied, often the manufacturer must
choose how the technology will affect the vehicle. The advantages of
the new technology can either be completely applied to improving fuel
economy or be used to increase vehicle performance while maintaining
the existing fuel economy, or some mix of the two effects.
Historically, vehicle performance has improved over the years as more
technology is applied to the fleet. The average horsepower is the
highest that it has ever been; all vehicle types have improved
horsepower by at least 42 percent compared to the 1978 model year, and
pickup trucks have improved by 48 percent.\78\ Fuel economy has also
improved, but the horsepower and acceleration trends show that not 100
percent of technological improvements have been applied to fuel
savings. While future trends are uncertain, the past trends suggest
vehicle performance is unlikely to decrease, as it seems reasonable to
assume that customers will, at a minimum, demand vehicles that offer
the same utility as today's fleet.
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\78\ ``The 2020 EPA Automotive Trends Report, Greenhouse Gas
Emissions, Fuel Economy, and Technology since 1975,'' EPA-420-R-21-
003, January 2021 [hereinafter 2020 EPA Automotive Trends Report].
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For this rulemaking analysis, DOT analyzed technology pathways
manufacturers could use for compliance that attempt to maintain vehicle
attributes, utility, and performance. Using this approach allows DOT to
assess the costs and benefits of potential standards under a scenario
where consumers continue to get the similar vehicle attributes and
features, other than changes in fuel economy. The purpose of
constraining vehicle attributes is to simplify the analysis and reduce
variance in other attributes that consumers may value across the
analyzed regulatory alternatives. This allows for a streamlined
accounting of costs and benefits by not requiring the values of other
vehicle attributes that trade off with fuel economy.
To confirm minimal differences in performance metrics across
regulatory alternatives, DOT analyzed the sales-weighted average 0-60
mph acceleration performance of the entire simulated vehicle fleet for
MYs 2020 and 2029. The analysis compared performance under the baseline
standards and preferred alternative. This analysis identified that the
analysis fleet under no action standards in MY 2029 had a 0.77 percent
worse 0-60 mph acceleration time than under the preferred alternative,
indicating there is minimal difference in performance between the
alternatives. This assessment shows that for this analysis, the
performance difference is minimal across regulatory alternatives and
across the simulated model years, which allows for fair, direct
comparison among the alternatives. Further details about this
assessment can be found in TSD Chapter 2.4.5.
(c) Implementation in the CAFE Model
The CAFE Model uses two elements of information from the large
amount of data generated by the Autonomie simulation runs: Battery
costs, and fuel consumption on the city and highway cycles. DOT
combines the fuel economy information from the two cycles to produce a
composite fuel economy for each vehicle, and for each fuel used in dual
fuel vehicles. The fuel economy information for each simulation run is
converted into a single value for use in the CAFE Model.
In addition to the technologies in the Autonomie simulation, the
CAFE Model also incorporated a handful of technologies not explicitly
simulated in Autonomie. These technologies' performance either could
not be captured on the 2-cycle test, or there was no robust data usable
as an input for full-vehicle modeling and simulation. The specific
technologies are discussed in the individual technology sections below
and in TSD Chapter 3. To calculate fuel economy improvements
attributable to these additional technologies, estimates of fuel
consumption improvement factors were developed and scale
multiplicatively when applied together. See TSD Chapter 3 for a
complete discussion on how these factors were developed. The Autonomie-
simulated results and additional technologies are combined, forming a
single dataset used by the CAFE Model.
Each line in the CAFE Model dataset represents a unique combination
of technologies. DOT organizes the records using a unique technology
state vector,
[[Page 49645]]
or technology key (tech key), that describes the technology content
associated with each unique record. The modeled 2-cycle fuel economy
(miles per gallon) of each combination is converted into fuel
consumption (gallons per mile) and then normalized relative to a
baseline tech key. The improvement factors used by the model are a
given combination's fuel consumption improvement relative to the
baseline tech key in its technology class.
The tech key format was developed by recognizing that most of the
technology pathways are unrelated and are only logically linked to
designate the direction in which technologies are allowed to progress.
As a result, it is possible to condense the paths into groups based on
the specific technology. These groups are used to define the technology
vector, or tech key. The following technology groups defined the tech
key: Engine cam configuration (CONFIG), VVT engine technology (VVT),
VVL engine technology (VVL), SGDI engine technology (SGDI), DEAC engine
technology (DEAC), non-basic engine technologies (ADVENG), transmission
technologies (TRANS), electrification and hybridization (ELEC), low
rolling resistance tires (ROLL), aerodynamic improvements (AERO), mass
reduction levels (MR), EFR engine technology (EFR), electric accessory
improvement technologies (ELECACC), LDB technology (LDB), and SAX
technology (SAX). This summarizes to a tech key with the following
fields: CONFIG; VVT; VVL; SGDI; DEAC; ADVENG; TRANS; ELEC; ROLL; AERO;
MR; EFR; ELECACC; LDB; SAX. It should be noted that some of the fields
may be blank for some tech key combinations. These fields will be left
visible for the examples below, but blank fields may be omitted from
tech keys shown elsewhere in the documentation.
As an example, a technology state vector describing a vehicle with
a SOHC engine, variable valve timing (only), a 6-speed automatic
transmission, a belt-integrated starter generator, rolling resistance
(level 1), aerodynamic improvements (level 2), mass reduction (level
1), electric power steering, and low drag brakes, would be specified as
``SOHC; VVT; ; ; ; ; AT6; BISG; ROLL10; AERO20; MR1; ; EPS; LDB ; .''
\79\
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\79\ In the example tech key, the series of semicolons between
VVT and AT6 correspond to the engine technologies which are not
included as part of the combination, while the gap between MR1 and
EPS corresponds to EFR and the omitted technology after LDB is SAX.
The extra semicolons for omitted technologies are preserved in this
example for clarity and emphasis and will not be included in future
examples.
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Once a vehicle is assigned (or mapped) to an appropriate tech key,
adding a new technology to the vehicle simply represents progress from
a previous tech key to a new tech key. The previous tech key refers to
the technologies that are currently in use on a vehicle. The new tech
key is determined, in the simulation, by adding a new technology to the
combination represented by the previous state vector while
simultaneously removing any technologies that are superseded by the
newly added one.
For example, start with a vehicle with the tech key: SOHC; VVT;
AT6; BISG; ROLL10; AERO20; MR1; EPS; LDB. Assume the simulation is
evaluating PHEV20 as a candidate technology for application on this
vehicle. The new tech key for this vehicle is computed by removing
SOHC, VVT, AT6, and BISG technologies from the previous state
vector,\80\ and adding PHEV20, resulting a tech key that looks like
this: PHEV20; ROLL10; AERO20; MR1; EPS; LDB.
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\80\ For more discussion of how the CAFE Model handles
technology supersession, see S4.5 of the CAFE Model Documentation.
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From here, the simulation obtains a fuel economy improvement factor
for the new combination of technologies and applies that factor to the
fuel economy of a vehicle in the analysis fleet. The resulting
improvement is applied to the original compliance fuel economy value
for a discrete vehicle in the MY 2020 analysis fleet.
5. Defining Technology Adoption in the Rulemaking Timeframe
As discussed in Section III.C.2, starting with a fixed analysis
fleet (for this analysis, the model year 2020 fleet indicated in
manufacturers' early CAFE compliance data), the CAFE Model estimates
ways each manufacturer could potentially apply specific fuel-saving
technologies to specific vehicle model/configurations in response to,
among other things (such as fuel prices), CAFE standards,
CO<INF>2</INF> standards, commitments some manufacturers have made to
CARB's ``Framework Agreement'', and ZEV mandates imposed by California
and several other States. The CAFE Model follows a year-by-year
approach to simulating manufacturers' potential decisions to apply
technology, accounting for multiyear planning within the context of
estimated schedules for future vehicle redesigns and refreshes during
which significant technology changes may most practicably be
implemented.
The modeled technology adoption for each manufacturer under each
regulatory alternative depends on this representation of multiyear
planning, and on a range of other factors represented by other model
characteristics and inputs, such as the logical progression of
technologies defined by the model's technology pathways; the
technologies already present in the analysis fleet; inputs directing
the model to ``skip'' specific technologies for specific vehicle model/
configurations in the analysis fleet (e.g., because secondary axle
disconnect cannot be applied to 2-wheel-drive vehicles, and because
manufacturers already heavily invested in engine turbocharging and
downsizing are unlikely to abandon this approach in favor of using high
compression ratios); inputs defining the sharing of engines,
transmissions, and vehicle platforms in the analysis fleet; the model's
logical approach to preserving this sharing; inputs defining each
regulatory alternative's specific requirements; inputs defining
expected future fuel prices, annual mileage accumulation, and valuation
of avoided fuel consumption; and inputs defining the estimated efficacy
and future cost (accounting for projected future ``learning'' effects)
of included technologies; inputs controlling the maximum pace the
simulation is to ``phase in'' each technology; and inputs further
defining the availability of each technology to specific technology
classes.
Two of these inputs--the ``phase-in cap'' and the ``phase-in start
year''--apply to the manufacturer's entire estimated production and,
for each technology, define a share of production in each model year
that, once exceeded, will stop the model from further applying that
technology to that manufacturer's fleet in that model year. The
influence of these inputs varies with regulatory stringency and other
model inputs. For example, setting the inputs to allow immediate 100%
penetration of a technology will not guarantee any application of the
technology if stringency increases are low and the technology is not at
all cost effective. Also, even if these are set to allow only very slow
adoption of a technology, other model aspects and inputs may
nevertheless force more rapid application than these inputs, alone,
would suggest (e.g., because an engine technology propagates quickly
due to sharing across multiple vehicles, or because BEV application
must increase quickly in response to ZEV requirements). For this
analysis, nearly
[[Page 49646]]
all of these inputs are set at levels that do not limit the simulation
at all.
As discussed below, for the most advanced engines (advanced
cylinder deactivation, variable compression ratio, variable
turbocharger geometry, and turbocharging with cylinder deactivation),
DOT has specified phase-in caps and phase-in start years that limit the
pace at which the analysis shows the technology being adopted in the
rulemaking timeframe. For example, this analysis applies a 34% phase-in
cap and MY 2019 phase-in start year for advanced cylinder deactivation
(ADEAC), meaning that in MY 2021 (using a MY 2020 fleet, the analysis
begins simulating further technology application in MY 2021), the model
will stop adding ADEAC to a manufacturer's MY 2021 fleet once ADEAC
reaches more than 68% penetration, because 34% x (2021-2019) = 34% x 2
= 68%.
This analysis also applies phase-in caps and corresponding start
years to prevent the simulation from showing inconceivable rates of
applying battery-electric vehicles (BEVs), such as showing that a
manufacturer producing very few BEVs in MY 2020 could plausibly replace
every product with a 300- or 400-mile BEV by MY 2025. Also, as
discussed in Section III.D.4, this analysis applies phase-in caps and
corresponding start years intended to ensure that the simulation's
plausible application of the highest included levels of mass reduction
(20% and 28.2% reductions of vehicle ``glider'' weight) do not, for
example, outpace plausible supply of raw materials and development of
entirely new manufacturing facilities.
These model logical structures and inputs act together to produce
estimates of ways each manufacturer could potentially shift to new
fuel-saving technologies over time, reflecting some measure of
protection against rates of change not reflected in, for example,
technology cost inputs. This does not mean that every modeled solution
would necessarily be economically practicable. Using technology
adoption features like phase-in caps and phase-in start years is one
mechanism that can be used so that the analysis better represents the
potential costs and benefits of technology application in the
rulemaking timeframe.
6. Technology Costs
DOT estimates present and future costs for fuel-saving technologies
taking into consideration the type of vehicle, or type of engine if
technology costs vary by application. These cost estimates are based on
three main inputs. First, direct manufacturing costs (DMCs), or the
component and labor costs of producing and assembling the physical
parts and systems, are estimated assuming high volume production. DMCs
generally do not include the indirect costs of tools, capital
equipment, financing costs, engineering, sales, administrative support
or return on investment. DOT accounts for these indirect costs via a
scalar markup of direct manufacturing costs (the retail price
equivalent, or RPE). Finally, costs for technologies may change over
time as industry streamlines design and manufacturing processes. To
reflect this, DOT estimates potential cost improvements with learning
effects (LE). The retail cost of equipment in any future year is
estimated to be equal to the product of the DMC, RPE, and LE.
Considering the retail cost of equipment, instead of merely direct
manufacturing costs, is important to account for the real-world price
effects of a technology, as well as market realities. Absent a
Government mandate, motor vehicle manufacturers will not undertake
expensive development and production efforts to implement technologies
without realistic prospects of consumers being willing to pay enough
for such technology to allow for the manufacturers to recover their
investment.
(a) Direct Manufacturing Costs
Direct manufacturing costs (DMCs) are the component and assembly
costs of the physical parts and systems that make up a complete
vehicle. The analysis used agency-sponsored tear-down studies of
vehicles and parts to estimate the DMCs of individual technologies, in
addition to independent tear-down studies, other publications, and
confidential business information. In the simplest cases, the agency-
sponsored studies produced results that confirmed third-party industry
estimates and aligned with confidential information provided by
manufacturers and suppliers. In cases with a large difference between
the tear-down study results and credible independent sources, DOT
scrutinized the study assumptions, and sometimes revised or updated the
analysis accordingly.
Due to the variety of technologies and their applications, and the
cost and time required to conduct detailed tear-down analyses, the
agency did not sponsor teardown studies for every technology. In
addition, some fuel-saving technologies were considered that are pre-
production or are sold in very small pilot volumes. For those
technologies, DOT could not conduct a tear-down study to assess costs
because the product is not yet in the marketplace for evaluation. In
these cases, DOT relied upon third-party estimates and confidential
information from suppliers and manufacturers; however, there are some
common pitfalls with relying on confidential business information to
estimate costs. The agency and the source may have had incongruent or
incompatible definitions of ``baseline.'' The source may have provided
DMCs at a date many years in the future, and assumed very high
production volumes, important caveats to consider for agency analysis.
In addition, a source, under no contractual obligation to DOT, may
provide incomplete and/or misleading information. In other cases,
intellectual property considerations and strategic business
partnerships may have contributed to a manufacturer's cost information
and could be difficult to account for in the CAFE Model as not all
manufacturers may have access to proprietary technologies at stated
costs. The agency carefully evaluates new information in light of these
common pitfalls, especially regarding emerging technologies.
W
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