## The Baseline Vehicle Fleet

1-1 

# Table of Contents

CHAPTER 1: THE BASELINE VEHICLE FLEET

1.1 Why do the agencies establish a baseline and refere nce vehicle fleet? ............ 1-2 1.2 The 2008 baseline vehicle fleet ...................

................................................... ... 1-3 1.2.1 Why did the agencies choose 2008 as the baseline mo del year? ............... 1-3 1.2.2 On what data is the baseline vehicle fleet based? . ..................................... 1-3 1.3 The MY 2011-2016 Reference Fleet ..................

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- 13 1.3.1 On what data is the baseline vehicle fleet based? .

...................... 1-131

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- 13 1.3.2 How do the agencies develop the reference vehicle f leet? ......... 1-151

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- 15 1.3.3 What are the sales volumes and characteristics of t he reference fleet? 1-231

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- 23 1.3.4 How is the development of the baseline fleet for th is proposal different from NHTSA’s historical approach and why is this ap proach preferable? .. 1-261

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- 26 1.3.5 How does manufacturer product plan data factor into the baseline used in this proposal? ....................................

................................................... ..... 1-311

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- 30 1.3.6 Have the agencies performed any analysis using manu facturer product plan data factor?

.................................................. ................................................... . 1-31 1

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## Draft Joint Technical Support Document

1-2 

# CHAPTER 1: The Baseline Vehicle Fleet

The passenger cars and light trucks sold currently in the United States, and those which are anticipated to be sold in the MY 2012-201 6 timeframe, are highly varied and satisfy a wide range of consumer needs. From two-s eater miniature cars to 11-seater passenger vans to large extended cab pickup trucks, American consumers have a great number of vehicle options to accommodate their util ity needs and preferences. Recent volatility in oil prices and the state of the econo my have demonstrated that consumer demand and choice can be sensitive to these factors . Although it is impossible for anyone or any organization to precisely predict the future , a characterization and quantification are required for the future fleet to assess impacts of rules which would affect that future fleet. In order to do this, the various leading pu blically available sources are examined, and a series of models are relied upon that help us to project the composition of a reference fleet. This chapter describes the proces s for accomplishing this.



# 1.1 Why do the agencies establish a baseline and refere nce vehicle fleet?

In order to calculate the impacts of the EPA and NH TSA proposed regulations, it is necessary to estimate the composition of the future vehicle fleet absent these proposed regulations in order to conduct comparisons. EPA i n consultation with NHTSA has developed a comparison fleet in two parts. The fir st step was to develop a baseline fleet based on model year 2008 data. EPA and NHTSA creat e a baseline fleet in order to track the volumes and types of fuel economy-improving and CO 2 

## -reducing technologies which are already present in today’s fleet. Creating a b aseline fleet helps to keep, to some extent, the agencies’ models from adding technologi es to vehicles that already have these technologies, which would result in “double countin g” of technologies’ costs and benefits. The second step was to project the basel ine fleet sales into MYs 2011-2016. This is called the reference fleet, and it represen ts the fleet that would exist in MYs 2011- 2016 absent any change from current regulations. T he third step was to add technologies to that fleet such that each manufacturer’s average car and truck CO 2 

## levels are in compliance with their MY 2011 CAFE standards. This final “reference fleet” is the light duty fleet estimated to exist in MYs 2012-2016 with out these proposed rules. All of the agencies’ estimates of emission reductions/fuel eco nomy improvements, costs, and societal impacts are developed in relation to the r espective reference fleets. The chapter describes the first two steps of the development of the baseline and reference fleets. The third step of technology addition is developed sepa rately by each agency as the outputs of the OMEGA and Volpe models. The process is describ ed in section II of the preamble and in each agency’s respective RIAs.

## The Baseline Vehicle Fleet

1-3 

# 1.2 The 2008 baseline vehicle fleet

1.2.1 Why did the agencies choose 2008 as the baseline mo del year?

For this proposed rule, the baseline vehicle fleet developed by EPA in consultation with NHTSA and is comprised of model y ear 2008 data. MY 2008 was used as the basis for the baseline vehicle fleet, becaus e it is the most recent model year for which full data is publicly available. Vehicle man ufacturers have 90 days after their last vehicle is produced to submit their CAFE data to EP A. 1 

## Most manufacturers interpret this to mean 90 days after the end of the calendar year. For example, in calendar year 2007, model year 2008 vehicles were tested and cert ified by the EPA. These MY 2008 vehicles were then sold in the latter part (often f all) of 2007 until the following fall of 2008. In early 2009 (calendar year), the manufactu rers then submit their total sales of MY 2008 vehicles. After these sales figures were s ubmitted, EPA and NHTSA combined the sales with the previously measured and reported fuel economies to calculate the sales-weighted average fleet fuel eco nomy. The analysis for this present rulemaking was conducted in early to mid 2009 calen dar year, thus the full sales figures for MY 2009 vehicles have not yet been submitted. Even though the fuel economies (and some other specifications) of the MY 2009 vehicles were known, since they were tested earlier, the sales were not yet known for each comp any exactly. Therefore, the agencies chose to use MY 2008 as the baseline since it was t he most complete data set available. NHTSA and EPA may update the baseline to MY 2009 or MY 2010 between this notice and the final rule if the data is complete and if t ime permits.



## 1.2.2 On what data is the baseline vehicle fleet based?

As part of the CAFE program, EPA measures vehicle C O 2 

## emissions and converts them to mpg and generates and maintains the federal fuel economy database. Most of the information about the 2008 vehicle fleet was gather ed from EPA’s emission certification and fuel economy database , most of which is available to the public

. The data obtained from this source included vehicle production volume , fuel economy, carbon dioxide emissions, fuel type, number of engine cylinders, d isplacement, valves per cylinder, engine cycle, transmission type, drive, hybrid type , and aspiration. However, EPA’s certification database does not include a detailed description of the types of fuel economy-improving/CO 2 

## -reducing technologies considered in this proposal, because this level of information is not necessary for emission certification or fuel economy testing. Thus, the agency augmented this description with pu blicly-available data which includes more complete technology descriptions from Ward’s Automotive Group Wards Automotive

. 2,a



## In a few instances when required vehicle informat ion was not available from these two sources (such as vehicle footprint), this information was obtained from

a 

### Note that Wards Auto.com is a fee-based service, but all information is pub lic to subscribers.

## Draft Joint Technical Support Document

1-4 publicly-accessible internet sites such as Motortre nd.com, Edmunds.com and other sources to a lesser extent (such as articles about specific vehicles revealed from internet search engine research. 3,b



## The baseline vehicle fleet for the analysis in this rule is comprised of publiclyavailable data to the largest extent possible. How ever, a few relatively low-impact technologies were added based on confidential infor mation provided from some manufacturers (within their product plan submission s to NHTSA and EPA). This was done because the data was not available from any ot her source. These technologies include low friction lubricants, electric power ste ering, improved accessories, and low rolling resistance tires. This confidential inform ation has been excised from the baseline data submitted to the docket, though the summary re sults are still used, so that any specific information cannot be traced back to any s pecific manufacturer. This discrepancy between the public baseline and the one used by the agencies is relatively minor and should only result in small differences i n the outputs of the Volpe and OMEGA models for certain manufacturers.

Creating the 2008 baseline fleet Excel file was an extremely labor intensive process. EPA in consultation with NHTSA first cons idered using EPA’s CAFE certification data, which contains most of the requ ired information. However, since the deadline for manufacturers to report this data did not allow enough time for early modeling review, it was necessary to start this pro cess using an alternative data source.

The agencies next considered using EPA’s vehicle em issions certification data, which contains much of the required information, ho wever it lacked the production volumes that are necessary for the OMEGA and Volpe models. The data set also contains some vehicle models manufacturers have cer tified, but not produced. A second data source which would supply production volumes a nd eliminate extraneous vehicles was needed. Data from a paid subscription to Ward’s Automotive Group Wards Automotive was used as the second source for data, which conta ins production volumes and vehicle specifications.

The vehicle emissions certification dataset came in two parts, an engine file and a vehicle file. Since there was a common index in the two files, the engine and vehicle data were easily combined into one spreadsheet. Th e agencies had hoped to supplement this dataset with production volume data from Ward’s Automotive Group Wards Automotive, but the Ward ’ s data does not have production volumes for individ ual vehicles down to the resolution of the specific eng ine and transmission level. Although production volumes from Ward’s Automotive Group Wards Automotive could not be used, the subscription did provide specific details on individual vehicles and engines. The Ward ’ s data used came in two parts (engine file and vehi cle file), and also required mapping. In this case, mapping was more difficult since there was no common index between the two files. A new index was implanted i n the engine file and a search equation in the vehicle file, which identified most of the vehicle and engine

b 

### Motortrend.com and Edmunds.com are free, no-fee in ternet sites.

## The Baseline Vehicle Fleet

1-5 combinations. Each vehicle and engine combination was reviewed and corrections were made manually when the search routine failed to giv e the correct engine and vehicle combination. The combined Ward ’ s data was then mapped to the vehicle emissions certification data by creating a new index in the c ombined Ward ’ s data and using the same process that was used to combine the Ward ’ s engine and vehicle files. In the next step, CAFE certification data had to be merged in o rder to fill out the needed production volumes.

NHTSA and EPA reviewed the CAFE certification data for model year 2008 as it became available. The CAFE certification dataset c ould have been used with the Ward ’ s data without the vehicle emission certification dat aset, but was instead appended to the combined Ward ’ s and vehicle certification dataset. The two forme r datasets were then mapped into the CAFE dataset using the same Excel m apping technique described above. Finally, EPA and NHTSA obtained the remaining attri bute and technology data, such as footprint, curb weight, and others (for a complete list of data with sources see Table 1-1 below) from other sources (such as the internet and the confidential product plan data), thus completing the baseline dataset.

This was the first time a baseline fleet was create d using this method. Given the long delay before the CAFE certification data becam e available, EPA explored creating the alternative dataset. It is possible to create the same baseline with CAFE certification data, the Ward ’ s engine data, a limited amount of product plan dat a, and some internet searches.

Table 1-1 below shows the baseline data that was co mpiled, its definition (description) and source. The data that is marked “not available” is data NHTSA would normally get from product plans. Some of the desir ed model inputs, such as the presence of low rolling resistance tires, reduced engine fri ction, improved accessories, are not available from public sources and the agencies had to rely on manufacturer’s confidential product plans. The Technology Effectivenesses Basi s and the Cost Effectiveness Basis values reflect the percent of a technology package’ s effectiveness and cost present in the baseline fleet, and they are described in further d etail in chapters 3.1 and 3.5, respectively. Those technologies that are not acco unted for in the baseline—that is, the ones marked “not available”—run the risk of getting double counted by the agencies’ models, but those effects are expected to be small.

Table 1-1 Data, Definitions, and Sources

Data Item Definition Where The Data is From

Manufacturer Common name of company that manufactured vehicle. May include more name plates than Cert

Manufacturer Name. Certification data

CERT Manufacturer Name Certification name of company that manufactured vehicle Certification data Name Plate Name of Division Certification data Model Name of Vehicle Certification data Reg Class EPA Fuel Economy Class Name Certification data Field Code Changed

## Draft Joint Technical Support Document

1-6 Class If a car’s Footprint<43 then "SubCmpctAuto" If a car’s 43<=Footprint<46 then "CompactAuto" If a car’s 46<=Footprint<53 then "MidSizeAuto” If a car’s Footprint >=53 then “LargeAuto” If a S.U.V.’s Footprint < 43 then “SmallSuv” If a S.U.V.’s 43<=Footprint<46 then

"MidSizeSuv” If a S.U.V’s Footprint >=46 then “LargeSuv” If a Truck’s Footprint < 50 then “SmallPickup” If a Truck’s Footprint>=50 then “LargPickup” If a Van’s Structure is Ladder then “CargoVan” If a Van’s Structure is Unibody then “Minivan” Derived From Certification data and Footprint

CSM Class CSM Worldwides class for the vehicle. Used to weight vehicles based on CSM data. CSM Worldwide

Traditional Car/Truck C= Car, T=Truck. As defined in the certification database. Not used in calculations. Certification data
EPA Interpretation of New NHTSA

Car/Truck C= Car, T=Truck. EPA Best guess, some incorrect. Using NHTSA below. Left in for historical

reasons. Not used in calculations. EPA Derived from NHTSA Definition Total Production Volume Total number of vehicles produced for that model. C ertification data Fuel Econ. (mpg) EPA Unadjusted Fuel Economy Certification data

Curb Weight (lb) Vehicles Curb Weight Some from Edmonds.com or Motortrend.com, Others from product plans with a subset verified with Edmonds.com or Motortrend.com for accuracy.
Area (sf) Average Track x Wheelbase Calculated from track width and wheel base Fuel Gas or Diesel Wards Disp (lit.) Engine Cylinder Displacement Size in Liters Wards/Certification data
Effective Cyl Number of Cylinder + 2 if the engine has a turbo or super charger. Derived From Certification data. Actual Cylinders Actual Number of Engine Cylinders Certification dat a Valves Per Cylinder Number of Valves Per Actual Cylinder Certification data
Valve Type Type of valve actuation. Wards (Note:Type E is from Cert Data) Engine Cycle As Defined by EPA Cert. Definition Wards Horsepower Max. Horsepower of the Engine Wards Torque Max. Torque of the Engine Wards
Trans Type A=Auto AMT=Automated Manual M=Manual CVT= Conti nuously Variable Transmission Certification data Trans Type Code with number of Gears Certification data Num of Gears Number of Gears Certification data

Structure Ladder or Unibody General Internet Searches using Google.com Drive Fwd, Rwd, Awd, 4wd Cer tification data

Wheelbase

Length of Wheelbase Some from Edmonds.com or Motortrend.com, Others from product plans with a subset verified with Edmonds.com or Motortrend.com for accuracy.

Track Width (front) Length of Track Width in inches Some from Edmonds.com or Motortrend.com, Others from product plans with a subset verified with Edmonds.com or Motortrend.com for accuracy.

Track Width (rear) Length of Track Width in inches Some from Edmonds.com or Motortrend.com, Others from product plans with a subset

## The Baseline Vehicle Fleet

1-7 verified with Edmonds.com or Motortrend.com for accuracy.
Footprint Average Track x Wheelbase Calculated from track width and wheel base

Curb Weight Curb Weight of the Vehicle Some from Edmonds.com or Motortrend.com, Others from product plans with a subset verified with Edmonds.com or Motortrend.com for accuracy.

GVWR

Gross Vehicle Weight Rating of the Vehicle Some from Edmonds.com or Motortrend.com, Others from product plans with a subset verified with Edmonds.com or Motortrend.com for accuracy. HYBRID Is the Vehicle a Hybrid? Certification data HYBRID TYPE Type of Hybrid Certification data Turbo Turbo Charged Engine Certification data Super Charged Super Charged Certification data Turbo and/or Super Charged Either or both Turbo charged / Super Charged Certif ication data SOHC Single Overhead Cam Engine Wards DOHC Dual Overhead Cam Engine Wards OHV Overhead Valve Engine Wards

1 LUB Low friction lubricants—incremental to base engine Obtained from product plans from manufacturers that report this information. 2

2 EFR Engine friction reduction—incremental to base engine Obtained from product plans from manufacturers that report this information. 2
3 CCPS VVT - Coupled Cam Phasing (CCP) on SOHC Wards 1
4 DVVLS Discrete Variable Valve Lift (DVVL) on SOHC Wards 1
5 DEACS Cylinder Deactivation on SOHC Wards 1
6 ICP VVT - Intake Cam Phasing (ICP) Wards 1
7 DCP VVT - Dual Cam Phasing (DCP) (independent) Wards 1
8 DVVLD Discrete Variable Valve Lift (DVVL) on DOHC Wards 1
9 CVVL Continuously Variable Valve Lift (CVVL) Wards 1
10 DEACD Cylinder Deactivation on DOHC Wards 1
11 DEACO Cylinder Deactivation on OHV Wards 1
12 CCPO VVT - Coupled Cam Phasing (CCP) on OHV Wards 1
13 DVVLO Discrete Variable Valve Lift (DVVL) on OHV Wards 1
14 CDOHC Conversion to DOHC with DCP Not available 15 SGDI Stoichiometric Gasoline Direct Injection (GDI) Ward s 1
16 CBRST Combustion Restart Not available 17 TRBDS Turbocharging and Downsizing Not available 18 EGRB Exhaust Gas Recirculation (EGR) Boost Not available

## Draft Joint Technical Support Document

1-8 19 DSLT Conversion to Diesel (from TRBDS) Not available 20 DSLC Conversion to Diesel (from CBRST) Not available 21 6MAN 6-Speed Manual/Improved Internals Certification dat a 22 IATC Improved Auto. Trans. Controls/Externals Not availa ble 23 CVT Continuously Variable Transmission Certification da ta 24 NAUTO 6/7/8-Speed Auto. Trans with Improved Internals Cer tification data 25 DCTAM Dual Clutch or Automated Manual Transmission Certification data

26 EPS Electric Power Steering Obtained from product plans from manufacturers that report this information. 2

27 IACC Improved Accessories Obtained from product plans from manufacturers that report this information. 2
28 MHEV 12V Micro

- Hybrid Not available 29 HVIA Higher Voltage/Improved Alternator Not available 30 BISG Belt Mounted Integrated Starter Generator Certific ation data 31 CISG Crank Mounted Integrated Starter Generator Certification data 32 PSHEV Power Split Hybrid Certification data 33 2MHEV 2-Mode Hybrid Certification data 34 PHEV Plug-in Hybrid Not available 35 MS1 Material Substitution (1%) Not available 36 MS2 Material Substitution (2%) Not available 37 MS5 Material Substitution (5%) Not available

38 ROLL Low Rolling Resistance Tires Obtained from product plans from manufacturers that report this information. 2
39 LDB Low Drag Brakes Not available 40 SAXU Secondary Axle Disconnect-Unibody Not available 41 SAXL Secondary Axle Disconnect-Ladder Not available Import Car Cars Imported Certification data Index Index Used to link EPA and NHTSA baselines Created

Volume 2011 Projected Production Volume for 2011 Calculated based on 2008 volume and AEO and CSM adjustment factors.

Volume 2012 Projected Production Volume for 2012 Calculated based on 2008 volume and AEO and CSM adjustment factors.

Volume 2013 Projected Production Volume for 2013 Calculated based on 2008 volume and AEO and CSM adjustment factors. Volume 2014 Projected Production Volume for 2014 Calculated based on 2008

## The Baseline Vehicle Fleet

1-9 volume and AEO and CSM adjustment factors.

Volume 2015 Projected Productio n Volume for 2015 Calculated based on 2008 volume and AEO and CSM adjustment factors.

Volume 2016 Projected Production Volume for 2016 Calculated based on 2008 volume and AEO and CSM adjustment factors.

Vehicle Type Number Vehicle Type Number assigned to a vehicle based on its number of cylinders, valves per cylinder, an d

valve actuation technology. Mapping done by Agencie s

Footprint: PU Average Car Foot Print is normal. Truck footprint is the production weighted average for each vehicle. Derived from data from Edmunds.com or Motortrend.com. Production volumes or specific footprints from product plans.

Footprint: PU Cutoff Same as above, but footprint valve for trucks limited to 66 before weighting. Meaning valves

greater than 66 equal 66. Derived from data from Edmunds.com or Motortrend.com. Production volumes or specific footprints from product plans.
NHTSA Defined New NHTSA

Car/Truck New NHTSA Car Truck value as determined by NHTSA. Used in calculations. NHTSA

CO2 CO2 calculated from MPG. CO2 weighted 1.15 times higher for diesel vehicles. Certification dat a

Thesholded FootPrint Footprint valve that will be set to 41 for values l ess than 41, Will be set to 56 for car values > 56, and will be set to 66 for truck values >66 Used in Summary Calculations Derived from data from Edmunds.com or Motortrend.com. Production volumes or specific footprints from product plans.

TEB Tech 1 Percentage of Tech Package 1 Calculated using a macro in another spread sheet. Calculated based on the technology in t he "Data" sheet.

TEB Tech 2 Percentage of Tech Package 2 Calculated using a macro in another spread sheet. Calculated based on the technology in the "Data" sheet.

TEB Tech 3 Percentage of Tech Package 3 Calculated using a macro in another spread sheet. Calculated based on the technology in the "Data" sheet.

TEB Tech 4 Percentage of Tech Package 4 Calculated using a macro in another spread sheet. Calculated based on the technology in the "Data" sheet.

TEB Tech 5 Percentage of Tech Package 5 Calculated using a macro in another spread sheet. Calculated based on the technology in the "Data" sheet.

TEB Tech 6 Percentage of Tech Package 6 Calculated using a macro in another spread sheet. Calculated based on the technology in the "Data" sheet.

CEB Tech 1 Percentage of Cost of Tech Package 1 Calculated using a macro in another spread sheet. Calculated based on the technology in the "Data" sheet.

CEB Tech 2 Percentage of Cost of Tech Package 2 Calculated using a macro in another spread sheet.

## Draft Joint Technical Support Document

1-10 Calculated based on the technology in the "Data" sheet.

CEB Tech 3 Percentage of Cost of Tech Package 3 Calculated using a macro in another spread sheet. Calculated based on the technology in the "Data" sheet.

CEB Tech 4 Percentage of Cost of Tech Package 4 Calculated using a macro in another spread sheet. Calculated based on the technology in the "Data" sheet.

CEB Tech 5 Percentage of Cost of Tech Package 5 Calculated using a macro in another spread sheet. Calculated based on the technology in the "Data" sheet.

CEB Tech 6 Percentage of Cost of Tech Package 6 Calculated using a macro in another spread sheet. Calculated based on the technology in the "Data" sheet. Notes: 1. For engines not available in the Wards WardsAuto.com engine file, an internet search was done to find th is information. 2. These data were obtained from manufacturer’s pr oduct plans. They were obtain to block (where poss ible) the model from adding technology that was already on a vehicle. 3. Ward’s Automotive Group Wards data obtained from "2008 Light Vehicle Engines" .



## The sales volumes for the MY 2008 baseline fleet ar e included in the section below on reference fleet under the MY 2008 columns. Table 1-2 displays the technologies present in the baseline fleet.

Table 1-2 2008 Technology PercentagesTurboSuper ChargedSOHCDOHCOHVLUBCCPSDVVLSDEACSICPDCPDVVLD

All Trucks 0.0% 0.2% 23.7% 47.6% 28.7% 61.4% 4.1% 5.8% 0.0% 5.3% 36.6% 1.5%
All Cars 2.5% 0.1% 17.4% 73.3% 9.2% 48.5% 1.4% 7.4% 1.3% 3.2% 47.9% 0.2%
BMW Trucks 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 94.7% 0.0%
BMW Cars 0.0% 0.0% 13.9% 86.0% 0.0% 0.0% 11.9% 11.9% 0.0% 0.0% 85.8% 1.5% Chrysler Trucks 0.0% 0.0% 38.9% 4.1% 56.9% 76.9% 0.0% 0.0% 0.0% 0.0% 3.9% 0.0% Chrysler Cars 0.9% 0.0% 20.8% 71.5% 7.7% 28.5% 0.0% 0.0% 0.0% 0.0% 41.7% 0.0%
Ford Trucks 0.0% 0.1% 62.9% 34.3% 2.8% 3.9% 26.5% 0.0% 0.0% 0.0% 9.3% 0.0%
Ford Cars 3.1% 0.9% 14.2% 85.8% 0.0% 6.4% 4.0% 0.0% 0.0% 0.0% 5.2% 0.0%
Subaru Trucks 0.0% 0.0% 70.5% 29.5% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 29.5% 27.4%
Subaru Cars 0.0% 0.0% 69.2% 30.8% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 30.8% 0.9%
GM Trucks 0.0% 0.0% 0.0% 30.8% 69.2% 92.7% 0.0% 0.0% 0.0% 14.7% 30.8% 0.0%
GM Cars 2.6% 0.0% 0.0% 56.2% 43.8% 92.0% 0.0% 0.0% 0.0% 11.5% 28.8% 0.0%
Honda Trucks 0.0% 0.0% 64.3% 35.7% 0.0% 0.0% 0.0% 64.3% 0.0% 0.0% 31.5% 4.2%
Honda Cars 0.0% 0.0% 57.2% 42.8% 0.0% 0.0% 0.0% 57.2% 10.7% 0.0% 42.6% 0.3% Hyundai Trucks 0.0% 0.0% 0.0% 100.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 29.6% 0.0% Hyundai Cars 0.0% 0.0% 0.0% 100.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 32.2% 0.0%
Tata Trucks 0.0% 20.3% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0%
Tata Cars 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% Field Code Changed

Formatted Table

## The Baseline Vehicle Fleet

1-11 Kia Trucks 0.0% 0.0% 0.0% 100.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 17.2% 0.0%
Kia Cars 0.0% 0.0% 0.0% 100.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 10.2% 0.0%
Mazda Trucks 0.0% 0.0% 0.6% 99.4% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 99.3% 0.0%
Mazda Cars 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.9% 0.9% 0.9% 0.9% 99.9% 0.9%
Daimler Trucks 0.0% 0.0% 36.2% 63.8% 0.0% 0.0% 0.0% 0.0% 0.0% 46.7% 0.0% 0.0%
Daimler Cars 0.0% 0.0% 54.6% 45.4% 0.0% 0.0% 0.0% 0.0% 0.0% 30.3% 0.0% 0.0%
Mitsubishi Trucks 0.0% 0.0% 100.0% 0.0% 0.0% 100.0% 37.7% 0.0% 0.0% 0.0% 0.0% 0.0%
Mitsubishi Cars 0.0% 0.0% 100.0% 0.0% 0.0% 100.0% 42.9% 0.0% 0.0% 0.0% 0.0% 0.0%
Nissan Trucks 0.0% 0.0% 0.0% 100.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0%
Nissan Cars 0.0% 0.0% 0.0% 100.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0%
Porsche Trucks 12.4% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 100.0% 100.0%
Porsche Cars 17.4% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 28.7% 82.6% 0.0%
Suzuki Trucks 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Suzuki Cars 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% Toyota Trucks 0.0% 0.0% 0.0% 100.0% 0.0% 89.1% 0.0% 0.0% 0.0% 0.0% 78.3% 0.0% Toyota Cars 0.0% 0.0% 0.0% 100.0% 0.0% 69.9% 0.0% 0.0% 0.0% 0.2% 99.4% 0.0%
VW Trucks 0.6% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 78.9% 99.4% 78.9%
VW Cars 43.1% 0.0% 85.0% 15.0% 0.1% 0.0% 0.0% 0.0% 0.0% 1.9% 14.1% 0.8%

Table 1

- 2 2008 Technology PercentagesCVVLDEACDDEACOCCPODVVLOSGDI6MANCVTNAUTODCTAMEPSBISGCISG

All Trucks 2.8% 0.0% 10.5% 1.4% 0.0% 2.9% 1.0% 2.6% 19.9% 0.0% 0.9% 0.0% 0.0%
All Cars 5.2% 0.0% 1.2% 5.7% 0.0% 4.7% 2.3% 11.5% 18.5% 0.8% 12.6% 0.0% 0.4%
BMW Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 6.3% 0.7% 0.0% 99.3% 0.0% 0.0% 0.0% 0.0%
BMW Cars 0.0% 0.0% 0.0% 0.0% 0.0% 7.7% 14.6% 0.5% 83.3% 1.1% 0.0% 0.0% 0.0% Chrysler Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 0.2% 4.3% 3.6% 21.4% 0.0% 0.0% 0.0% 0.0% Chrysler Cars 0.0% 0.0% 5.2% 0.0% 0.0% 0.0% 0.9% 18.5% 3.9% 0.0% 0.0% 0.0% 0.0%
Ford Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 1.0% 0.0% 1.8% 18.8% 0.0% 0.0% 0.0% 0.0%
Ford Cars 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 1.2% 1.9% 36.8% 0.0% 0.0% 0.0% 0.0%
Subaru Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Subaru Cars 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 4.1% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
GM Trucks 0.0% 0.0% 39.1% 5.0% 0.0% 0.0% 0.0% 0.0% 18.6% 0.0% 0.0% 0.0% 0.0%
GM Cars 0.0% 0.0% 4.0% 28.8% 0.0% 6.0% 1.1% 0.0% 12.3% 0.0% 0.0% 0.1% 0.0%
Honda Trucks 31.5% 0.0% 0.0% 0.0% 0.0% 4.2% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Honda Cars 42.6% 0.0% 0.0% 0.0% 0.0% 0.0% 3.1% 3.2% 0.0% 0.0% 0.0% 0.0% 3.2% Hyundai Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 25.0% 0.0% 0.0% 0.0% 0.0% Hyundai Cars 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.2% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Tata Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0%
Tata Cars 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 91.6% 0.0% 0.0% 0.0% 0.0%
Kia Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Kia Cars 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Mazda Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 23.5% 0.0% 0.1% 57.2% 0.0% 0.0% 0.0% 0.0%
Mazda Cars 0.9% 0.9% 0.9% 0.9% 0.9% 11.4% 3.8% 0.1% 19.2% 0.0% 0.0% 0.0% 0.0%
Daimler Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 15.9% 0.0% 0.0% 99.3% 0.0% 0.0% 0.0% 0.0%
Daimler Cars 0.0% 0.0% 0.0% 0.0% 0.0% 1.7% 0.3% 0.0% 67.4% 10.4% 0.0% 0.0% 0.0% Formatted Table

## Draft Joint Technical Support Document

1-12 Mitsubishi Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 14.4% 23.3% 0.0% 0.0% 0.0% 0.0%
Mitsubishi Cars 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 1.4% 44.2% 7.6% 0.0% 0.0% 0.0% 0.0%
Nissan Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 1.2% 16.5% 0.0% 0.0% 16.5% 0.0% 0.0%
Nissan Cars 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 4.5% 69.4% 0.0% 0.0% 32.3% 0.0% 0.0%
Porsche Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 1.4% 0.0% 98.6% 0.0% 0.0% 0.0% 0.0%
Porsche Cars 0.0% 0.0% 0.0% 0.0% 0.0% 17.4% 51.9% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Suzuki Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Suzuki Cars 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% Toyota Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 5.7% 1.4% 4.7% 19.2% 0.0% 0.0% 0.0% 0.0% Toyota Cars 0.0% 0.0% 0.0% 0.0% 0.0% 7.6% 0.1% 16.7% 22.5% 0.0% 64.0% 0.0% 0.0%
VW Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0%
VW Cars 0.0% 0.0% 0.0% 0.0% 0.0% 46.0% 6.4% 5.4% 65.7% 14.3% 0.0% 0.0% 0.0%

Table 1

- 2 2008 Technology PercentagesPSHEV2MHEVPHEVAuto 4 SpeedAuto 5 SpeedAuto 6 SpeedAuto 7 SpeedAuto 8 SpeedManual 5 SpeedManual 6 SpeedCVTAutomated Manual5 SpeedAutomated Manual6 SpeedAutomated Manual7 Speed

All Trucks 0.8% 0.1% 0.0% 37.9% 37.3% 18.6% 1.4% 0.0% 1.1% 1.0% 2.6% 0.0% 0.0% 0.0%
All Cars 2.7% 0.0% 0.0% 39.1% 22.9% 16.4% 1.7% 0.4% 4.9% 2.3% 11.5% 0.3% 0.5% 0.0%
BMW Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 99.3% 0.0% 0.0% 0.0% 0.7% 0.0% 0.0% 0.0% 0.0%
BMW Cars 0.2% 0.0% 0.2% 0.0% 0.0% 82.6% 0.8% 0.0% 0.3% 14.6% 0.5% 0.0% 0.0% 1.1% Chrysler Trucks 0.0% 0.0% 0.0% 34.9% 35.5% 21.4% 0.0% 0.0% 0.3% 4.3% 3.6% 0.0% 0.0% 0.0% Chrysler Cars 0.0% 0.0% 0.0% 67.0% 8.2% 3.9% 0.0% 0.0% 1.4% 0.9% 18.5% 0.0% 0.0% 0.0%
Ford Trucks 0.0% 0.0% 0.0% 55.9% 20.9% 18.8% 0.0% 0.0% 2.7% 0.0% 1.8% 0.0% 0.0% 0.0%
Ford Cars 0.0% 0.0% 0.0% 36.3% 18.2% 36.8% 0.0% 0.0% 5.6% 1.2% 1.9% 0.0% 0.0% 0.0%
Subaru Trucks 0.0% 0.0% 0.0% 62.1% 29.5% 0.0% 0.0% 0.0% 8.4% 0.0% 0.0% 0.0% 0.0% 0.0%
Subaru Cars 0.0% 0.0% 0.0% 69.6% 2.4% 0.0% 0.0% 0.0% 23.9% 4.1% 0.0% 0.0% 0.0% 0.0%
GM Trucks 0.0% 0.5% 0.0% 75.5% 5.0% 19.0% 0.0% 0.0% 0.4% 0.0% 0.0% 0.0% 0.0% 0.0%
GM Cars 0.0% 0.1% 0.0% 77.9% 5.4% 12.3% 0.0% 0.0% 3.2% 1.1% 0.0% 0.0% 0.0% 0.0%
Honda Trucks 0.0% 0.0% 0.0% 0.0% 99.7% 0.0% 0.0% 0.0% 0.3% 0.0% 0.0% 0.0% 0.0% 0.0%
Honda Cars 0.0% 0.0% 0.0% 0.0% 87.3% 0.0% 0.0% 0.0% 6.4% 3.1% 3.2% 0.0% 0.0% 0.0% Hyundai Trucks 0.0% 0.0% 0.0% 29.8% 45.0% 25.0% 0.0% 0.0% 0.2% 0.0% 0.0% 0.0% 0.0% 0.0% Hyundai Cars 0.0% 0.0% 0.0% 76.4% 16.7% 0.0% 0.0% 0.0% 6.7% 0.2% 0.0% 0.0% 0.0% 0.0%
Tata Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Tata Cars 0.0% 0.0% 0.0% 0.0% 8.4% 91.6% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Kia Trucks 0.0% 0.0% 0.0% 23.1% 75.7% 0.0% 0.0% 0.0% 1.2% 0.0% 0.0% 0.0% 0.0% 0.0%
Kia Cars 0.0% 0.0% 0.0% 51.5% 41.0% 0.0% 0.0% 0.0% 7.5% 0.0% 0.0% 0.0% 0.0% 0.0%
Mazda Trucks 0.0% 0.0% 0.0% 10.1% 29.6% 57.2% 0.0% 0.0% 3.0% 0.0% 0.1% 0.0% 0.0% 0.0%
Mazda Cars 0.0% 0.0% 0.0% 33.3% 29.7% 19.2% 0.0% 0.0% 13.9% 3.8% 0.1% 0.0% 0.0% 0.0%
Daimler Trucks 0.0% 0.0% 0.0% 0.0% 0.7% 0.0% 99.3% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Daimler Cars 0.0% 0.0% 0.0% 0.0% 22.0% 0.0% 67.4% 0.0% 0.0% 0.3% 0.0% 10.4% 0.0% 0.0%
Mitsubishi Trucks 0.0% 0.0% 0.0% 62.3% 0.0% 23.3% 0.0% 0.0% 0.0% 0.0% 14.4% 0.0% 0.0% 0.0%
Mitsubishi Cars 0.0% 0.0% 0.0% 30.8% 4.5% 7.6% 0.0% 0.0% 11.6% 1.4% 44.2% 0.0% 0.0% 0.0%
Nissan Trucks 0.0% 0.0% 0.0% 0.0% 81.6% 0.0% 0.0% 0.0% 0.7% 1.2% 16.5% 0.0% 0.0% 0.0%
Nissan Cars 1.1% 0.0% 0.0% 7.0% 19.1% 0.0% 0.0% 0.0% 0.0% 4.5% 69.4% 0.0% 0.0% 0.0%
Porsche Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 98.6% 0.0% 0.0% 0.0% 1.4% 0.0% 0.0% 0.0% 0.0%
Porsche Cars 0.0% 0.0% 0.0% 0.0% 33.7% 0.0% 0.0% 0.0% 14.4% 51.9% 0.0% 0.0% 0.0% 0.0% Formatted Table

## The Baseline Vehicle Fleet

1-13 Suzuki Trucks 0.0% 0.0% 0.0% 0.0% 99.5% 0.0% 0.0% 0.0% 0.5% 0.0% 0.0% 0.0% 0.0% 0.0%
Suzuki Cars 0.0% 0.0% 0.0% 76.2% 13.1% 0.0% 0.0% 0.0% 10.7% 0.0% 0.0% 0.0% 0.0% 0.0% Toyota Trucks 4.7% 0.0% 0.0% 9.0% 63.9% 19.2% 0.0% 0.0% 1.9% 1.4% 4.7% 0.0% 0.0% 0.0% Toyota Cars 16.9% 0.0% 0.0% 35.7% 19.5% 19.8% 0.0% 2.6% 5.5% 0.1% 16.7% 0.0% 0.0% 0.0%
VW Trucks 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
VW Cars 0.0% 0.0% 0.0% 0.0% 0.0% 65.7% 0.0% 0.0% 8.2% 6.4% 5.4% 0.0% 14.3% 0.0%



## These technology tables indicate that some manufact urers are already implementing some of these technologies in their 20 08 fleet. VW stands out as having a significant number of turbocharged direct injection engines, though it is uncertain whether their engines are also downsized. Some of the valve and cam technologies are quite common today: for example, nearly half the fl eet has dual cam phasing, while Honda and GM are have considerable levels of engine s with cylinder deactivation (DEAC). Honda also has already implemented continu ously variable valve lift (CVVL) on a majority of their engines. Moreover, Toyota has the highest penetration of hybrid technologies. Finally, regarding the technologies obtained from the product plans: many of the manufacturers who reported the lubricating o il information, indicated that low friction (or low viscosity) oil will be used more f requently in the future. Therefore, it is likely that this technology is underreported for th e fleet as a whole since it was assumed that the usage of low viscosity oils was zero for t he companies who did not provide product plans. The lack of reporting of these type s of technologies (if they exist in the fleet) will probably lead to a slightly higher cost of compliance for these companies than what the agencies show in the Preamble for the MY 2 011 costs. However, as described in the section II.D of the Preamble, these technolo gies alone do not necessarily guarantee a better fuel economy compared to other vehicles in their footprint class. There are many other considerations at play, most notably, weight and power.

The section below provides further detail on the co nversion of the MY 2008 baseline into the MY 2011-2016 reference fleet. It also described more of the data contained in the baseline spreadsheet.



# 1.3 The MY 2011-2016 Reference Fleet

The reference fleet aims to reflect the current mar ket conditions and expectations about conditions of the vehicle fleet during the ru lemaking time frame. Fundamentally, constructing this fleet involved projecting the MY 2008 baseline fleet into the MY 2011- 2016 model years. It also included the assumption that none of the models had changes during this period. Projecting what the fleet will look like in the future is a process that is inherently full of uncertainty. NHTSA and EPA ther efore relied on many sources of reputable information to make these projections.



## 1.3.1 On what data is the baseline vehicle fleet based?

## Draft Joint Technical Support Document

1-14 EPA and NHTSA have based the projection of total ca r and light truck sales on recent projections made by the Energy Information A dministration (EIA). EIA publishes a long-term projection of national energy use annua lly called the Annual Energy Outlook (AEO). 4 

## This projection utilizes a number of technical an d econometric models which are designed to reflect both economic and regulator y conditions expected to exist in the future. In support of its projection of fuel use b y light-duty vehicles, EIA projects sales of new cars and light trucks. Due to the state of flux of both energy prices and the economy, EIA published three versions of its 2009 A nnual Energy Outlook. The Preliminary 2009 report was published early (in Nov ember 2008) in order to reflect the dramatic increase in fuel prices which occurred dur ing 2008, after the development of the 2008 AEO. The official 2009 report was published i n March of 2009. A third 2009 report was published a month later which reflected the economic stimulus package passed by Congress earlier this year. For the analysis in this rule, NHTSA and EPA use the sales projections of this latest report, referred to as t he updated 2009 AEO.

In their updated 2009 report, EIA projects that tot al light-duty vehicle sales gradually recover from their currently depressed le vels by roughly 2013. In 2016, car and light truck sales are projected to be 9.5 and 7 .1 million units, respectively. While the total level of sales of 16.6 million units is simil ar to pre-2008 levels, the fraction of car sales is higher than that existing in the 2000-2007 timeframe. This reflects the impact of higher fuel prices, as well as the effects of the E ISA (which called for a minimum fleet average of 35 mpg by 2020). Note that EIA’s defini tion of cars and trucks follows that used by NHTSA prior to the MY 2011 CAFE final rule published earlier this year. The MY 2011 CAFE final rule reclassified a number of 2- wheel drive sport utility vehicles from the truck fleet to the car fleet. EIA’s sales projections of cars and trucks for the 2011-2016 model years under both the new and old NH TSA truck definition are shown in Table 1-3 and Table 1-4 below, respectively. Actua l vehicle sales for MY 2008 are also shown under the new NHTSA truck definition. Slight differences exist between the total car and truck sales projections. These differences are less than 0.1% and are due to the iterative process described further below to shift sales between car and truck market segments.

Table 1-3 AEO Volumes New NHTSA Car Truck Definitio n After Projections

2008 Baseline Sales 2011

Projected Volume 2012

Projected Volume 2013

Projected Volume 2014

Projected Volume 2015

Projected Volume 2016

Projected Volume

All Trucks 5,620,847 5,547,326 5,530,583 5,720,280 5,810,895 5 ,717,300 5,586,953

All Cars 8,220,517 8,235,204 9,255,624 9,977,341 10,479,350 10,890,967 11,067,608

Total 13,841,364 13,782,530 14,786,207 15,697,621 16,290, 245 16,608,267 16,654,561



### Table 1-4 AEO Volumes Old NHTSA Car Truck Definitio n Before Projections

2011 Projected Volume 2012

Projected Volume 2013

Projected Volume 2014

Projected Volume 2015

Projected Volume 2016

Projected Volume Field Code Changed Field Code Changed

## The Baseline Vehicle Fleet

1-15 All Trucks 7,007,298 7,725,263 8,261,773 8,776,298 9,241,209 9 ,468,365
All Cars 6,954,580 7,125,693 7,391,939 7,440,095 7,334,371 7 ,112,689 Total 13,961,878 14,850,955 15,653,713 16,216,393 16,575,580 16,581,055



## In addition to a shift towards more car sales, sale s of segments within both the car and truck markets have also been changing and are e xpected to continue to change in the future. Manufacturers are introducing more crossov er models which offer much of the utility of SUVs but using more car-like designs. I n order to reflect these changes in fleet makeup, EPA and NHTSA considered several available forecasts. After reviewing information from a number of forecasting organizati ons, the agencies decided to purchase forecasts from two well-known industry analysts, CS M-Worldwide (CSM), and J.D. Powers. 5 

## NHTSA and EPA decided to use the forecast from CS M, for several reasons. One, CSM agreed to allow us to publish their high l evel data, on which the forecast is based, in the public domain. Two, it covered nearl y all the timeframe of greatest relevance to this proposed rule (2012-2015 model ye ars). Three, it provided projections of vehicle sales both by manufacturer and by market segment. Four, it utilized market segments similar to those used in the EPA emission certification program and fuel economy guide. As discussed further below, this al lowed the CSM forecast to be combined with other data obtained by NHTSA and EPA. The breakdown of car and truck sales by manufacturer and by market segment f or the 2016 model year and beyond were assumed to be the same as CSM’s forecast for t he 2015 calendar year.



## 1.3.2 How do the agencies develop the reference vehicle f leet?

The process of producing the 2011-2016 reference fl eet involved combining the baseline fleet with the projection data described a bove. This was a complex multistep procedure, which is described in this section.

1.3.2.1 How was the 2008 baseline data merged with the CSM data?

Merging the 2008 baseline data with the 2011-2016 C SM data required a thorough mapping of certification vehicles to CSM v ehicles by individual make and model. One challenge the agencies faced when deter mining a reference case fleet was that the sales data projected by CSM had different market segmentation than the data contained in EPA’s internal database. In order to create a common segmentation between the two databases, side-by-side comparison of the s pecific vehicle models in both datasets was performed, and additional “CSM segment ” modifier in the spreadsheet was created, thus mapping the two datasets. The refere nce fleet sales based on the “CSM segmentation” was then projected

The baseline data and reference fleet volumes are a vailable to the public. The baseline Excel spreadsheet in the docket is the res ult of the merged files. 6 

## It provides Formatted Table

## Draft Joint Technical Support Document

1-16 specific details on the sources and definitions for the data. The Excel file contains several tabs. They are: “Data”, “Data Tech Definit ions”, “SUM”, “SUM Tech Definitions”, “Truck Vehicle Type Map”, and “Car Ve hicle Type Map”. “Data” is the tab with the raw data. “Data Tech Definitions” is the tab where each column is defined and its data source named. “SUM” is the tab where the raw data is processed to be used in the OMEGA and Volpe models. The “SUM” tab minus columns A-F and minus the Generic vehicles is the input file for the models. The “Generic” manufacturer (shown in the “SUM” tab) is the sum of all manufacturers and is calculated as a reference, and for data verification purposes. It is used to validate the manufacturers’ totals. It also gives an overview of the fleet. Table 1-5 shows the sum of the models chosen. The number of models is determined by the number of unique segmen t and vehicle type combinations. These combinations of segment and vehicle type (the vehicle type number is the same as the technology package number) are determined by th e technology packages discussed in.the EPA DRIA (chapter 1). “SUM Tech Definition s” is the tab where the columns of the “SUM” tab are defined. The “Truck Vehicle Type Map” and “Car Vehicle Type Map” map the number of cylinder and valve actuation technology to the “tech package” vehicle type number.

Table 1-5 Models from the SUM Tab Model

Model C ar Like LargeSuv >=V8 Vehicle Type: 13 Car Like LargeSuv V6 Vehicle Type: 16 Car Like LargeSuv V6 Vehicle Type: 12 Car Like LargeSuv V6 Vehicle Type: 9 Car Like LargeSuv I4 and I5 Vehicle Type: 7 Car Like MidSizeSuv V6 Vehicle Type: 8 Car Like MidSizeSuv V6 Vehicle Type: 5 Car Like MidSizeSuv I4 Vehicle Type: 7 Car Like SmallSuv V6 Vehicle Type: 12 Car Like SmallSuv V6 Vehicle Type: 4 Car Like SmallSuv I4 Vehicle Type: 3 LargeAuto >=V8 Vehicle Type: 13 LargeAuto >=V8 Vehicle Type: 10 LargeAuto >=V8 Vehicle Type: 6 LargeAuto V6 Vehicle Type: 12 LargeAuto V6 Vehicle Type: 5 MidSizeAuto >=V8 Vehicle Type: 13 MidSizeAuto >=V8 Vehicle Type: 10 MidSizeAuto >=V8 (7 or >) Vehicle Type: 6 MidSizeAuto V6 Vehicle Type: 12 MidSizeAuto V6 Vehicle Type: 8 MidSizeAuto V6 Vehicle Type: 5 MidSizeAuto I4 Vehicle Type: 3



## In the combined EPA certification and CSM database, all of the 2008 vehicle models were assumed to continue out to 2016, though their volumes changed in proportion to CSM projections. Also, any new model s expected to be introduced within Field Code Changed

## The Baseline Vehicle Fleet

1-17 the 2009-2016 timeframe are not included in the dat a. These volumes are reassigned to the existing models. All MY 2011-2016 vehicles are mapped to the existing vehicles by a process of mapping to manufacturer market share a nd overall segment distribution. The mappings are discussed in the next section. Furthe r discussion of this limitation is discussed below in section 1.3.4. The statistics o f this fleet will be presented below since further modifications were required to the volumes as the next section describes.

1.3.2.2 How were the CSM forecasts normalized to the AEO fo recasts?

The next step in the production of the reference fl eet is one of the more complicated steps to explain. Here, the projected CSM forecasts for relative sales of cars and trucks by manufacturer and by market segment wa s normalized (set equal) to the total sales estimates of the updated 2009 Annual En ergy Outlook (AEO). NHTSA and EPA used projected car and truck volumes for this p eriod from AEO 2009. However, the AEO projects sales only at the car and truck level, not at the manufacturer and modelspecific level, which are needed for the analysis. The CSM data provided year-by-year percentages of cars and trucks sold by each manufac turer as well as the percentages of each vehicle segment. Using these percentages norm alized to the AEO-projected volumes then provided the manufacturer-specific mar ket share and model-specific sales for model years 2011-2016 (it is worth clarifying t hat the agencies are not using the model-specific sales volumes from CSM, only the vol umes by manufacturer and segment). This process is described in greater det ail in the following paragraphs.

In order to determine future production volumes, mu ltipliers were developed by manufacturer and vehicle segment that could be appl ied to MY 2008 volumes. The process for developing the multipliers is complicat ed, but is easiest to explain as a threestep process, though the first step is combined wit h both the second and third step, so only one multiplier per manufacturer and vehicle se gment is developed.

The three steps are: 1. Adjust total car and truck sales to match AEO proje ctions. 1. 2. Adjust Car sales to match CSM market share projecti ons for each manufacturer and car segment. 1. 3. Adjust Truck sales to match CSM market share projec tions for each manufacturer and truck segment.

The first step is the adjustment of total car and t ruck sales in 2008 to match AEO projections of total car and truck sales in 2011-20 16. The volumes for all of the trucks in 2008 were added up (TruckSum2008), and so were the volumes of all the cars (CarSum2008). A multiplier was developed to scale the volumes in 2008 to the AEO projections. The example equation below shows the general form of how to calculate a car or truck multiplier. The AEO projections are s hown above in Table 1-3.

Example Equation : TruckMultiplier(Year X) = AEOProjectionforTrucks(Ye ar X) / TruckSum2008 Formatted: Bullets and Numbering

Field Code Changed

## Draft Joint Technical Support Document

1-18 CarMultiplier(Year X) = AEOProjectionforCars(Year X ) / CarSum2008

Where: Year X is the model year of the multiplier.

The AEO projection is different for each model year . Therefore, the multipliers are different for each model year. The multipliers can be applied to each 2008 vehicle as a first adjustment, but multipliers based solely on AEO have limited value since it can only give an adjustment that will give the correct total numbers of cars and trucks without the correct market share or vehicle mix. A correct ion factor based on the CSM data, which does contain market share and vehicle segment mix, is therefore necessary, so combining the AEO multiplier with CSM multipliers ( one per manufacturer, segment, and model year) will give the best multipliers.

There were several steps in developing an adjustmen t for Cars based on the CSM data. CSM provided data on the market share and ve hicle segment distribution. The first step in determining the adjustment for Cars was to total the number of Cars in each vehicle segment by manufacturer in MY 2008. A tota l for all manufacturers in each segment was also calculated. The next step was to multiply each segment the volume of each segment for each manufacturer by the CSM marke t share. The AEO multiplier was also applied at this time. This gave projected vol umes with AEO total volumes and market share correction for Cars. This is shown in the “Adjusted for 2011 AEO and Manufacturer Market Share” column of Table 1-6.

The next step is to adjust the sales volumes for CS M vehicle segment distribution. The process for adjusting for vehicle segment is mo re complicated than a simple one step multiplication. In order to keep manufacturers’ vo lumes constant and still have the correct vehicle segment distribution, vehicles need to move from segment to segment while maintaining constant manufacturers’ totals. Six rules and one assumption were applied to accomplish the shift. The assumption (b ased on the shift in vehicle sales in the last year) is that people are moving to smaller veh icles in the rulemaking time frame. A higher level (less detailed) example of this proced ure is provided in the preamble section II.

1. Vehicles from CSM’s “Luxury Car,” “Specialty Car,” and “Other Car” segments, if reduced will be equally distributed to the remai ning four categories (“Full-Size Car,” “Mid-Size Car,” “Small Car,” “Mini Car”). If these sales increased, they were taken from the remaining four categories so th at the relative sales in these four categories remained constant. 2. Vehicles from CSM’s “Luxury Car,” “Specialty Car,” and “Other Car” segments, if increased will take equally from the remaining c ategories (“Full-Size Car,” “Mid-Size Car,” “Small Car,” “Mini Car”). 3. All manufacturers have the same multiplier for a gi ven segment shift based on moving all vehicles in that segment to achieve the CSM distribution. Table 1-6 shows how the 2011 vehicles moved and the multiplie rs that were created for each adjustment. This does not mean that new vehic le segments will be added (except for Generic Mini Car described in the next step) to manufacturers that do Field Code Changed

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## The Baseline Vehicle Fleet

1-19 not produce them. Vehicles within each manufacture r will be shifted as close to the distribution as possible given the other rules. Table 1-7 has the percentages of Cars per CSM segment. These percentages are multip lied by the total number of vehicles in a given year to get the total sales in the segment. Table 1-6 shows the totals for 2011 in the “2011 AEO-CSM Sales Goal” co lumn. 4. When “Full-Size Car,” “Mid-Size Car,” “Small Car” a re processed, if vehicles need to move in or out of the segment, they will mo ve into or out of the next smaller segment. So, if Mid-Size Cars are being pr ocessed they can only move to or be taken from Small Cars. Note: In order to ac complish this, a “Generic Mini Car” segment was added to manufacturers who did not have a Mini (type) Car in production in 2008, but needed to shift down vehicl es from the Small Car segment. 5. The data must be processed in the following order: “Luxury Car,” “Specialty Car,” “Other Car,” “Full-Size Car,” “Mid-Size Car,” “Small Car.” The “Mini Car” does not need to be processed separately. By using this order, it works out that vehicles will always move toward the correct d istribution. There are two exceptions, BMW and Porsche only have “Luxury Car,” “Specialty Car,” and “Other Car” vehicles, so their volumes were not cha nged or shifted since these rules did not apply to them. 5. 6. When an individual manufacturer multiplier is appli ed for a segment, the vehicles move to or from the appropriate segments as specifi ed in the previous rules and as shown in Table 1-6.

Table 1-6 Example: 2011 Model Year Volume Shift

CSM Segment 2008 MY

Sales Adjusted for

2011 AEO and Manufacturer Market Share Luxury, Specialty,

Other Adjustment Full Size

Adjustment Midsize

Adjustment Small Car

Adjustment 2011 AEOCSM Sales Goal
All Full

- Size Car 730,355 501,245 520,885 411,025 411,025 411,025 411,025 All Luxury Car 1,057,875 1,076,470 970,680 970,680 970,680 970,680 970,666 All Mid-Size Car 1,970,494 1,946,981 2,033,087 2,14 2,948 1,838,095 1,838,095 1,838,095 All Mini Car 599,643 686,738 733,339 733,339 733,33 9 991,309 991,349
All Small Car 1,850,522 2,007,527 2,099,343 2,099,343 2,404,196 2,146,226 2,146,226 All Specialty Car 754,547 783,982 637,785 637,785 637,785 637,785 637,759 All Others 3,259 4,355 12,178 12,178 12,178 12,178 12,178
Number Vehicles that shift and Where All Full-Size Car 19,640 (109,861) - - All Luxury Car (105,790)

- - - All Mid-Size Car 86,107 109,861 (304,853) - All Mini Car 46,601 - - 257,970 All Small Car 91,816 - 304,853 (257,970) All Specialty Car (146,198)

- - - All Others 7,823 - - - Individual Manufacturer Multiplier

All Full-Size Car 0.789 CHAPTER 2: CHAPTER 3: All Luxury Car 0.902 CHAPTER 4: CHAPTER 5: CHAPTER 6: Field Code Changed

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## Draft Joint Technical Support Document

1-20 All Mid-Size Car 0.858 CHAPTER 7:
All Mini Car 1.352
All Small Car All Specialty Car 0.814 CHAPTER 8: CHAPTER 9: CHAPTER 10:
All Others 2.796 CHAPTER 11: CHAPTER 12:

CHAPTER 13:



### Table 1-7 CSM – Percent of Cars per Segment CSM Segment 2011 2012 2013 2014 2015 2016 Compact Car 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% Full-Size Car 5.9% 4.3% 4.7% 4.9% 4.9% 4.9% Luxury Car 13.9% 13.7% 14.6% 15.0% 15.1% 15.1% Mid-Size Car 26.2% 29.0% 27.9% 27.5% 27.9% 27.9% Mini Car 14.1% 15.5% 15.5% 15.4% 15.4% 15.4% Small Car 30.6% 27.5% 26.5% 26.1% 25.8% 25.8% Specialty Car 9.1% 9.8% 10.7% 10.9% 1 0.6% 10.6% Others 0.2% 0.2% 0.2% 0.2% 0.2% 0.2%



## Mathematically, an individual manufacturer multipli er is calculated by making the segment the goal and dividing by the previous total for the segment (shown in Table 1-6). If the number is greater than 1, the vehicles are e ntering the segment, and if the number is less than 1, the vehicles are leaving the segment. So, for example, if Luxury Cars have an adjustment of 1.5, then for a specific manufactu rer who has Luxury Cars, a multiplier of 1.5 is applied to its luxury car volume, and the total number of vehicles that shifted into the Luxury segment is subtracted from the rema ining segments to maintain that company’s market share. On the other hand, if Larg e Cars have an adjustment of 0.7, then for a specific manufacturer who has Large Cars , a multiplier of 0.7 is applied to its Large Cars, and the total number of vehicles leavin g that segment is transferred into that manufacturer’s Mid-Size Cars.

After the vehicle volumes are shifted using the abo ve rules, a total for each manufacturer and vehicle segment is maintained. Th e total for each manufacturer segment for a specific model year ( e.g. , 2011 General Motors Luxury Cars) divided by the MY 2008 total for that manufacturer segment ( e.g. , 2008 General Motors Luxury Cars) is the new multiplier used to determine the f uture vehicle volume for each vehicle model. This is done by taking the multiplier (whic h is for a specific manufacturer and segment) times the MY 2008 volume for the specific vehicle model ( e.g. , 2008 General Motors Luxury Car Cadillac CTS). This process is r epeated for each model year (2011- 2016).

The method used to adjust CSM Trucks to the AEO mar ket share was different than the method used for Cars. The process for Car s is different than Trucks because it is not possible to predict how vehicles would shift be tween segments based on current market trends. This is because of the added utili ty of some trucks that makes their sales more insensitive to factors like fuel price. Again , CSM provided data on the market Formatted: None, Indent: First line: 2 ch, Space Before: 0 pt, After: 0 pt, No bullets or numbering, Don't keep with next, Hyphenate

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## The Baseline Vehicle Fleet

1-21 share and vehicle segment distribution. The proces s for having the fleet match CSM’s market share and vehicle segment distribution was i terative.

The following totals were determined:

• The total number of trucks for each manufacturer in 2008 model year.

• The total number of trucks in each truck segment in 2008 model year.

• The total number of truck in each segment for each manufacturer in 2008 model
year.

• The total number of trucks for each manufacturer in a specific future model year based on the AEO and CSM data. This is the goal fo r market share.

• The total number of trucks in each truck segment in a specific future model year based on the AEO and CSM data. This is the goal fo r vehicle segment distribution. Table 1-8 has the percentages of Tru cks per CSM segment

Table 1-8 CSM – Percent of Trucks per Segment CSM Segment 2011 2012 2013 2014 2015 2016 Full-Size CUV 4.1% 3.3% 4.0 % 4.4% 4.5% 4.5% Full-Size Pickup 20.0% 17.9% 18.1% 20.1% 20.8% 20.8% Full-Size SUV 3.3% 2.8% 1.6% 1.2% 1.3% 1.3% Full-Size Van 3.5% 3.3% 4.0% 3.9% 4.0% 4.0% Mid-Size CUV 14.5% 15.8% 17.5% 18.1% 18.4% 18.4% Mid-Size MAV 3.8% 3.3% 2.6% 2.2% 2.2% 2.2% Mid-Size Pickup 3.6% 5.8% 6.4% 6.4% 6.6% 6.6% Mid-Size SUV 3.2% 2.3% 1.8% 1.6% 1.6% 1.6% Mid-Size Van 11.9% 11.3% 10.7% 10.0% 8.7% 8.7% Small CUV 27.3% 28.4% 27.0% 26.1% 26.2% 26.2% Small MAV 1.9% 3.4% 4.1% 4.1% 4.1% 4.1% Small SUV 2.8% 2.4% 2.2% 2.0% 1.8% 1.8%



## To start, two different types of tables were create d. One table had each manufacturer with its total sales for 2008 (similar to Table 1-9). This table will have the goal for each manufacturer, and a column added for each iteration with the current total. The second table has a truck segment total by manuf acturer. The second table starts out with a “Generic” manufacturer (Table 1-10) which is the table where the goal resides. Each manufacturer (BMW is shown in Table 1-11) is t hen listed below the “Generic” manufacturer. With each iteration, a new total is added for each segment that is calculated and added to the table. This is not sho wn in the tables below. A process of first adjusting the numbers in the tables to the go al for market share distribution was done. This was followed by adjusting to the goal f or vehicle segment distribution. Each time an adjustment was done a new column was added. An adjustment was done by creating a multiplier (either segment distribution based or manufacturer distribution based) and applying it to each vehicle segment tota l in the current iteration. A manufacturer-based multiplier is calculated by taki ng the goal total for a manufacturer and dividing by the current total (starting with 20 08 model year volumes) for a manufacturer. A segment distribution-based multipl ier is calculated by taking the goal distribution volumes in the Generic manufacturer se t and dividing them by the current Field Code Changed

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## Draft Joint Technical Support Document

1-22 volume. Table 1-9, Table 1-10, and Table 1-11 belo w illustrate two iterations using BMW.

Table 1-9 Manufacturer Truck Totals

2008 Model Year Sales Manufacturer Distribution 2 011Volume Goal Multiplier for Iteration 1
BMW 61,324 139948 139948/61324=2.28



### Table 1-10 Segment Specific Truck Totals for All Ma nufacturers

Manufacturer CSM Segment 2008 Model Year Sales Segment Distribution

2011Volume Goal Multipliers

Generic 1 Full-Size Pickup 1,195,073 1,390,343 1. 30 Generic Mid-Size Pickup 598,197 251,433 0.38 Generic Full-Size Van 33,384 244,393 8.30
Generic Mid

- Size Van 719,529 826,733 1.37 Generic Mid-Size MAV 191,448 263,765 1.26 Generic Small MAV 235,524 133,309 0.57 Generic Full-Size SUV 530,748 232,375 0.46 Generic Mid-Size SUV 347,026 221,607 0.70 Generic Small SUV 377,262 194,496 0.75 Generic Full-Size CUV 406,554 287,313 0.69 Generic Mid-Size CUV 798,335 1,007,583 0.99
Generic Small CUV 1,441,589 1,901,229 1.16 

### Note: 1. Generic means all manufacturers.

Table 1-11 Segment Specific Truck Totals for BMW

Manufacturer CSM Segment 2008 Model Year Sales Iteration 1 Adjust for Market Share Iteration 2 Adjust for

Segment Distribution BMW Full-Size Pickup BMW Mid-Size Pickup BMW Full-Size Van BMW Mid-Size Van BMW Mid-Size MAV 3,882 2.28*3,882 =8,551 1.26*8,851=11,137 BMW Small MAV BMW Full-Size SUV BMW Mid-Size SUV BMW Small SUV BMW Full-Size CUV BMW Mid

- Size CUV 36,409 2.28*36,409=83,013 0.99*83,013=82,603 BMW Small CUV 21,033 2.28*21,033=47,955 1.16*47,955=55,592 Total BMW Vehicles 61,324 139,819 149,332 Field Code Changed Field Code Changed Field Code Changed

## The Baseline Vehicle Fleet

1-23 Using this process, the numbers will get closer to the goal of matching CSM’s market share for each manufacturer and distribution for ea ch vehicle segment after each of the iterations. The iterative process is carried out u ntil the totals nearly match the goals.

After 19 iterations, all numbers were within 0.01% of CSM’s distributions. The calculation iterations could have been stopped soon er, but they were continued to observe how the numbers would converge.

After the market share and segment distribution wer e complete, the totals need to be used to create multipliers that could be applied to the original individual 2008 model year vehicle volumes (each unique manufacture models vol ume). The total for each manufacturer segment divided by the 2008 model year total for each manufacturer segment gives a multiplier that can be applied to e ach vehicle based on its manufacturer and segment.

The above process is done for each model year neede d (2011-2016). The multipliers are then applied to each vehicle in 2008 model year , which gives a volume for each vehicle in 2011 through 2016 model year. The “refe rence case” (which is the technology being applied to 2012-2016 fleet to meet the 2011 c afe standard) is discussed below in section 4.1, with the results being presented in se ction 4.2.



## 13.1.1 1.3.3 What are the sales volumes and characteristics of t he reference fleet?

Table 1-12 and Table 1-13 below contain the sales v olumes and percentages that result from the process above for MY 2008 and 2011- 2016. The forecast from CSM used in this proposal is CSM’s forecast from the 2nd qua rter of 2009. CSM also provided to EPA an updated forecast in the 3rd quarter of 2009, which we were unable to use for this proposal due to time constraints. However, we have placed a copy of the 3rd Quarter CSM forecast in the public docket for this rulemaki ng, and we will consider its use, and any further updates from CSM or other data received during the comment period when developing the analysis for the final rule. 7



### Table 1-12 Vehicle Segment Volumes

Reference Class Segment

a Actual and Projected Sales Volume

2008 2011 2012 2013 2014 2015 2016 Large Auto 557,693 390,306 361,186 382,212 390,640 410,847 416,829 Mid-Size Auto 3,097,859 2,649,352 3,153,248 3,470,0 51 3,722,450 3,929,107 4,022,893 Compact Auto 1,976,424 1,966,447 2,128,221 2,318,08 4 2,480,435 2,582,171 2,643,374 Sub-Compact Auto 1,364,434 1,887,350 2,114,147 2,24 0,751 2,348,611 2,452,342 2,512,431 All Cars 6,996,410 6,893,455 7,756,803 8,411,098 8, 942,136 9,374,467 9,595,527

Large Pickup 1,581,880 1,535,300 1,533,514 1,620,983 1,776,746 1,813,145 1,785,188 Small Pickup 177,497 57,694 112,916 140,210 138,240 136,667 145,324 Large SUV 2,783,949 2,670,474 2,642,285 2,713,398 2 ,718,252 2,705,080 2,625,901 Field Code Changed Field Code Changed

## Draft Joint Technical Support Document

1-24 Mid-Size SUV 1,263,360 1,469,957 1,563,424 1,544,25 2 1,502,608 1,490,577 1,446,932 Small SUV 285,355 84,525 138,914 180,559 178,377 16 0,839 156,230 Mini Van 642,055 749,650 717,454 699,786 657,057 56 1,199 543,558 Cargo Van 110,858 321,476 320,898 387,335 376,831 3 66,294 355,901 All Trucks 6,844,954 6,889,076 7,029,404 7,286,523 7,348,109 7,233,800 7,059,034

a This is no longer the CSM segment, but the segment used for the subsequent analysis in this ru le.



### Table 1-13 Manufacturer Volumes2008BaselineSales2011ProjectedVolume2012ProjectedVolume2013ProjectedVolume2014ProjectedVolume2015ProjectedVolume2016ProjectedVolume

Total Vehicles 13,841,364 13,782,531 14,786,207 15,697,621 16,290, 246 16,608,267 16,654,561 All Trucks 6,844,954 6,889,076 7,029,404 7,286,523 7,348,109 7,233,800 7,059,034 All Cars 6,996,410 6,893,455 7,756,803 8,411,098 8, 942,136 9,374,467 9,595,527
BMW Trucks 61,324 139,959 142,861 141,949 144,022 139,034 135, 569

BMW Cars 291,796 272,572 283,471 323,191 352,248 371,668 380 ,804 Chrysler Trucks 956,792 402,659 282,472 244,441 222,545 112,381 109 ,674 Chrysler Cars 700,413 193,704 178,635 175,072 169,046 136,583 138 ,602

Ford Trucks 846,596 943,583 1,025,575 1,107,535 1,202,141 1,230 ,889 1,202,442

Ford Cars 1,021,792 1,229,762 1,348,260 1,424,345 1,446,097 1 ,503,175 1,511,354

Subaru Trucks 82,546 117,896 88,877 77,593 76,913 73,425 74,135

Subaru Cars 116,035 153,644 149,192 135,946 135,141 130,588 131 ,022

GM Trucks 1,512,047 1,313,927 1,209,642 1,320,438 1,342,856 1 ,355,820 1,322,512

GM Cars 1,607,460 1,156,366 1,484,580 1,620,301 1,708,507 1 ,789,813 1,820,234

Honda Trucks 505,140 571,178 669,948 724,500 687,208 691,641 675 ,173

Honda Cars 1,006,639 996,396 1,155,008 1,352,607 1,493,242 1,5 62,496 1,593,092 Hyundai Trucks 53,158 127,199 141,028 135,751 134,274 132,978 129, 763 Hyundai Cars 337,869 570,431 580,538 558,975 562,862 590,579 596 ,891

Tata Trucks 55,584 31,344 42,168 46,256 53,335 48,583 47,372

Tata Cars 9,596 18,572 22,878 32,822 35,534 40,586 41,584

Kia Trucks 59,472 97,706 78,789 74,596 72,192 69,894 68,310

Kia Cars 221,980 302,347 304,524 309,667 331,198 347,533 351 ,081

Mazda Trucks 55,885 59,782 71,930 71,136 66,919 59,361 57,998

Mazda Cars 246,661 317,948 313,489 318,669 338,487 340,069 345 ,489

Daimler Trucks 79,135 97,926 109,351 115,684 125,189 113,366 110,5 41

Daimler Cars 208,052 177,493 172,172 190,133 204,335 229,562 235 ,205

Mitsubishi Trucks 15,371 9,268 10,098 11,440 9,124 7,349 7,171

Mitsubishi Cars 85,358 67,779 64,843 61,169 56,478 52,368 53,459

Nissan Trucks 305,546 420,666 477,897 478,571 474,558 454,488 444 ,471

Nissan Cars 717,869 793,873 958,696 1,031,569 1,073,307 1,104,2 72 1,123,486

Porsche Trucks 18,797 21,401 20,767 20,639 19,379 16,822 17,273

Porsche Cars 18,909 30,909 31,605 35,813 38,470 36,175 37,064

Suzuki Trucks 35,319 25,194 30,391 29,750 30,545 27,204 26,526

Suzuki Cars 79,339 91,355 86,537 86,220 81,480 75,965 77,427 Toyota Trucks 951,136 1,059,161 1,019,375 1,019,048 1,045,671 1,0 81,323 1,057,837 Toyota Cars 1,260,364 1,473,999 1,697,762 1,862,201 1,985,033 2 ,114,273 2,154,115

VW Trucks 26,999 108,477 109,415 100,952 104,023 102,743 100, 186

## The Baseline Vehicle Fleet

1-25 VW Cars 290,385 388,054 423,433 458,641 467,885 465,263 476 ,699



## Table 1-14 also shows how the change in fleet make- up may affect the footprint distributions over time. The resulting data indica tes that the average footprint level of the fleet will shrink by 1.2% (1% for cars and 2% for t rucks, and sales weighted). Thus, the combination of AEO and CSM projections produces a f uture vehicle fleet which is only slightly smaller in terms of footprint than that wh ich was sold in 2008. At the same time, 2008 sales volumes were likely significantly lower than sales earlier in the decade due to the spike in fuel prices. These projections indica te that the footprint size of the future fleet will not rebound in the future.

Table 1-14 Production Foot Print Mean

Model Year Foot Print Mean for Car & Truck Combined Foot Print Mean for Car Foot Print Mean for Truck

2008 49 45.4 54.1 2011 48.9 45 54.8 2012 48.5 44.9 54.5 2013 48.5 45 54.7 2014 48.6 45 55.1 2015 48.5 45 55.2 2016 48.4 45 55.2



## Table 1-15 and Table 1-16 below show the changes in engine cylinders over the model years. The current assumptions show that eng ines will be downsized over the timing of this rule. The biggest shift occurs betw een MY 2008 and 2013. This shift is caused by the expected changes in class and segment mix as predicted by AEO and CSM, and does not represent engine downsizing attributab le to the proposed rules.

Table 1-15 Truck Percentages of 4, 6, 8 Cylinder En gines by Model Year

Model Percent of Total Sales of 4,6,8 Cylinders Trucks

2008 2011 2012 2013 2014 2015 2016 All Trucks 8 Cylinders 33.7% 32.3% 30.4% 29.9% 31.7% 32.6% 32.6% All Trucks 6 Cylinders 55.8% 56.3% 56.8% 57.6% 56.5% 55.4% 55.3% All Trucks 4 Cylinders 10.5% 11.4% 12.8% 12.4% 11.9% 12.0% 12.1%

Table 1-16 Car Percentages of 4, 6, 8 Cylinder Engi nes by Model Year

Model Percent of Total Sales of 4,6,8 Cylinders Cars

2008 2011 2012 2013 2014 2015 2016 All Cars 8 Cylinders 5.2% 4.1% 3.9% 4.2% 4.3% 4.4% 4.5% All Cars 6 Cylinders 36.7% 32.8% 32.4% 32.6% 32.6% 32.6% 32.5% Field Code Changed

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## Draft Joint Technical Support Document

1-26 All Cars 4 Cylinders 58.1% 63.1% 63.7% 63.1% 63.1% 62.9% 63.1%



## 13.1.2 1.3.4 How is the development of the baseline fleet for th is proposal different from NHTSA’s historical approach and why is this approach preferable?

As described in detail at the opening of this chap ter, NHTSA has historically based its analysis of potential new CAFE standards on detailed product plans the agency has requested from manufacturers planning to produc e light vehicles for sale in the United States. Although the agency has never compe lled manufacturers to submit such information, most major manufacturers and some smal ler manufacturers have voluntarily provided it when requested.

As in this and other prior rulemakings, NHTSA has requested extensive and detailed information regarding the models that manu facturers plan to offer, as well as manufacturers’ estimates of the volume of each mode l they expect to produce for sale in the U.S. NHTSA’s recent requests have sought infor mation regarding a range of engineering and planning characteristics for each v ehicle model ( e.g. , fuel economy, engine, transmission, physical dimensions, weights and capacities, redesign schedules), each engine ( e.g. , fuel type, fuel delivery, aspiration, valvetrain configuration, valve timing, valve lift, power and torque ratings), and each transmission ( e.g. , type, number of gears, logic).

The information that manufacturers have provided i n response to these requests has varied in completeness and detail. Some manufa cturers have submitted nearly all of the information NHTSA has requested, for most or al l of the model years covered by NHTSA’s requests, and have closely followed NHTSA’s guidance regarding the structure of the information. Other manufacturers have submitted partial information, information for only a few model years, and/or info rmation in a structure less amenable to analysis. Still other manufacturers have not re sponded to NHTSA’s requests or have responded on occasion, usually with partial informa tion.

In recent rulemakings, NHTSA has integrated this i nformation and estimated missing information based on a range of public and commercial sources (such as those used to develop today’s market forecast). For manu facturers which do not respond, NHTSA has estimated fleet composition based on the latest-available CAFE compliance data (the same data used as part of the foundation for today’s market forecast). NHTSA has then adjusted the size of the fleet based on AE O’s forecast of the light vehicle market and normalized manufacturers’ market shares based o n the latest-available CAFE compliance data.

Compared to this approach, the market forecast the agencies have developed for this analysis has both advantages and disadvantages

.

## The Baseline Vehicle Fleet

1-27 Most importantly, today’s market forecast is much m ore transparent. The information sources used to develop today’s market forecast are all either in the public domain, available to the public upon request, or av ailable commercially. As a result, NHTSA and EPA are able to docket the market inputs actually used in the agencies’ respective modeling systems, such that any reviewer may independently repeat and review the agencies’ analyses. Previously, althoug h NHTSA provided this type of information to manufacturers upon request ( e.g. , GM requested and received outputs specific to GM), NHTSA was otherwise unable to rele ase market inputs and the most detailed model outputs ( i.e. , the outputs containing information regarding spec ific vehicle models) because doing so would violate requirements protecting manufacturers’ confidential business information from disclosure. 8 

## Therefore, this approach provides much greater opportunity for the public to replicat e and review the agencies’ analyses and comment accordingly.

Another advantage of this market forecast is the ag encies’ ability to more fully assess the incremental costs and benefits of the pr oposed standards. In the past two years, NHTSA has requested and received three sets of future product plan submissions from the automotive companies, most recently this p ast spring. These submissions are intended to be the actual future product plans for the companies. In the most recent submission it is clear that many of the firms have been and are clearly planning for future CAFE standard increases for model years 2012 and la ter. This is not surprising, as NHTSA’s proposed standards for MY 2011-2015 and the 2007 passage of EISA have prompted the companies to expect that there will be increases in the CAFE standards for MY 2012 and later, as well as the likelihood of fut ure GHG standards. The results for the product plans for many firms show a significant inc rease in their projected application of fuel-saving (and CO 2 

## -reducing) technologies by MY 2016. However, for t he purposes of assessing the costs of the model year 2012-2016 sta ndards, the use of the product plans present a difficulty – specifically, how to assess the increased costs of the proposed future standards if the companies have already anticipated the future standards, such that the costs are now part of the agencies’ baseline. The approach used for this proposal does not raise this concern, as the underlying data come s from model year 2008 production. On the other hand, manufacturers’ plans for MY 2010 and MY 2011 are less subject to this concern, because manufacturers’ expectations r egarding these model years were informed by knowledge of the MY 2010 and MY 2011 st andards. The agencies are hopeful that manufacturers will agree to make publi c their plans for one or both of these model years, potentially facilitating the developme nt of a baseline fleet that better balances multiple concerns.

In addition, by developing a baseline fleet from co mmon sources, the agencies have been able to avoid some errors—perhaps related to interpretation of requests—that have been observed in past responses to NHTSA’s req uests. For example, while reviewing information submitted to support the Marc h 2009 CAFE final rule, NHTSA staff discovered that one manufacturer had misinter preted instructions regarding the specification of vehicle track width, leading to im portant errors in estimates of vehicle footprints. Although the manufacturer resubmitted the information with corrections after

## Draft Joint Technical Support Document

1-28 being alerted by the agency, this new approach help s the agencies reduce the potential for such errors and inconsistencies by utilizing common data sources and procedures.

An additional advantage of the approach used for th is proposal is a consistent projection of the change in fuel economy and CO 2 

## emissions across the various vehicles from the application of new technology. In the pas t, manufacturer product plans would include the application of new fuel economy improve ment technology for a new or improved vehicle model with the resultant estimate from the manufacturer of the fuel economy levels for the vehicle. However, manufactu rers did not always provide to NHTSA detailed analysis which showed how they forec asted what the fuel economy performance of the new vehicle was – that is, wheth er it came from actual test data, from vehicle simulation modeling, from best engineering judgment or some other methodology. Thus, it was not always possible for NHTSA to review the methodology used by the manufacturer, nor was it always possibl e to review what approach the different manufacturers utilized from a consistency perspective. With the approach used for this proposal, the baseline market data comes f rom actual vehicles which have actual fuel economy test data, so there is no question wha t is the basis for the fuel economy or CO 2 

## performance of the baseline market data, as it is actual measured data.

Another advantage of today’s approach is that futur e market shares are based on a forecast of what will occur in the future, rather t han on a static value. In the past, NHTSA has utilized a constant market share for each model year, based on the most recent year available for example from the CAFE com pliance data, that is, a forecast of the 2011-2015 time frame where company market share s do not change. In the approach used today, the forecasts from CSM have been utiliz ed to determine how future market shares among the companies may change over time. c



## The approach that NHTSA and EPA have taken in devel oping the market forecast does, however, have some disadvantages. Most impor tantly, it produces a market forecast that does not represent some important cha nges likely to occur in the future.

Some of the changes not captured by this approach a re specific. For example, the current market forecast includes some vehicles for which manufacturers have announced plans for elimination or drastic production cuts su ch as the Chevrolet Trailblazer, the Chrysler PT Cruiser, the Chrysler Pacifica, the Dod ge Magnum, the Ford Crown Victoria, the Hummer H2, the Mercury Sable, the Pon tiac Grand Prix, and the Pontiac G5. These vehicle models appear explicitly in mark et inputs to NHTSA’s analysis, and are among those vehicle models included in the aggr egated vehicle types (representative vehicles) appearing in market inputs to EPA’s analy sis.

Conversely, the agencies’ market forecast does not include some forthcoming vehicle models, such as the Chevrolet Volt, the Che vrolet Camaro, the Ford Fiesta and several publicly announced electric vehicles, inclu ding the announcements from Nissan. Nor does it include several MY 2009 and 2010 vehicl es, such as the Honda Insight, the

c 

### The agencies note, however, that CSM or other data could also be applied to product plan data in order to adjust market share over time.

## The Baseline Vehicle Fleet

1-29 Hyundai Genesis and the Toyota Venza, as the starti ng point for vehicle definitions was MY 2008. Additionally, the market forecast does no t account for publicly-announced technology introductions, such as Ford’s EcoBoost s ystem, whose product plans specify which vehicles and how many are planned to have thi s technology. Were the agencies to rely on manufacturers’ product plans, today’s marke t forecast would account for not only these specific examples, but also for similar examp les that have not yet been announced publicly.

The agencies believe that including specific new ve hicle models such as the Volt or Insight after MY 2008 would most likely have a s mall impact on the estimates of the final technology required to comply with the propos ed standards. However, including them would make the standards appear to cost less r elative to the reference case. First, the projections of sales by vehicle segment and man ufacturer include these expected new vehicle models. Thus, to the extent that these new vehicles are expected to change consumer demand, they should be reflected in the re ference case. While projecting the characteristics of the new vehicles with MY 2008 ve hicles, the primary difference between the new vehicles and 2008 vehicles in the s ame vehicle segment is the use of additional CO 2 

## -reducing/fuel-saving technology. Both the NHTSA a nd EPA models add such technology to facilitate compliance with the p roposed standards. Thus, the future projections of the vehicle fleet generally shift ve hicle designs towards those of these newer vehicles. The advantage of the agencies appr oach is that it helps clarify the costs of this proposal, as the cost of all fuel economy i mprovements beyond those required by the MY 2011 CAFE standards are being assigned to th e proposal. In some cases, the new vehicles being introduced by manufacturers are actu ally in response to their anticipation of this rulemaking. The agencies approach prevents some of these technological improvements and their associated cost from being a ssumed in the baseline. Thus, the added technology will not be considered to be free for the purposes of this rule.

We note that, as a result of these issues, the mark et file may show sales volumes for certain vehicles during MYs 2012-2016 even thou gh they will be discontinued before that time frame. Although the agencies recognize t hat these specific vehicles will be discontinued, they are included in the market forec ast because they are useful for representing successor vehicles that may appear in the rulemaking time frame to replace the discontinued vehicles in that market segment.

Other market changes not captured by today’s approa ch are broader. For example, Chrysler Group LLC has announced plans to offer small- and medium-sized cars using Fiat powertrains. The product plan subm itted by Chrysler includes vehicles that appear to reflect these plans. However, none of these specific vehicle models are included in the market forecast the agencies have d eveloped starting with MY 2008 CAFE compliance data. The product plan submitted b y Chrysler is also more optimistic with regard to Chrysler’s market share during MYs 2 012-2016 than the market forecast projected by CSM and used by the agencies today.

Additionally, some technical information manufactur ers that have provided in product plans regarding specific vehicle models is, at least as far as NHTSA and EPA

## Draft Joint Technical Support Document

1-30 have been able to determine, not available from pub lic or commercial sources. While such gaps do not bear significantly on the agencies ’ analysis, the diversity of pickup configurations necessitated utilizing a sales-weigh ted average footprint value d 

## for many manufacturers’ pickups. Since the modeling only ut ilizes footprint in order to estimate each manufacturer’s CO 2 

## or fuel economy standard and all the other vehicle characteristics are available for each pickup confi guration, this approximation has no practical impact on the projected technology or cos t associated with compliance with the various standards evaluated. The only impact which could arise would be if the relative sales of the various pickup configurations changed, or if the agencies were to explore standards with a different shape or attribute. Thi s would necessitate recalculating the average footprint value in order to maintain accura cy.

The agencies have carefully considered these advant ages and disadvantages of using a market forecast derived from public and com mercial sources rather than from manufacturers’ product plans, and the agencies beli eve that the advantages outweigh the disadvantages for the purpose of proposing standard s for model years 2012-2016. NHTSA’s inability to release confidential market in puts and corresponding detailed outputs from the CAFE model has raised serious conc erns among many observers regarding the transparency of NHTSA’s analysis, as well as related concerns that the lack of transparency might enable manufacturers to provi de unrealistic information to try to influence NHTSA’s determination of the maximum feas ible CAFE levels. While NHTSA does not agree with some observers’ assertion s that some manufacturers have deliberately provided inaccurate or otherwise misle ading information, today’s market forecast is fully open and transparent, and is ther efore not subject to such concerns.

With respect to the disadvantages, the agencies are hopeful that manufacturers will, in the future, agree to make public their pla ns regarding model years that are very near, such as MY 2010 or perhaps MY 2011, so that t his information can be incorporated into an analysis that is available for public revie w and comment. In any event, because NHTSA and EPA are releasing market inputs used in t he agencies’ respective analyses, manufacturers, suppliers, and other automobile indu stry observers and participant can submit comments on how these inputs should be impro ved, as can all other reviewers

d 

### A full-size pickup might be offered with various c ombinations of cab style ( e.g. , regular, extended, crew) and box length ( e.g. , 51⁄2’, 61⁄2’, 8’) and, therefore, multiple footprint sizes. CAFE compliance data for MY2008 data does not contain footprint information, and does not contain information that can be used to reliably identify which pickup entries correspond t o footprint values estimable from public or commerc ial sources. Therefore, the agencies have used the kno wn production levels of average values to represent all variants of a given pickup line ( e.g. , all variants of the F-150 and the Sierra/Silverad o) in order to calculate the sales-weighted average footprint value for each pickup family. Again, this has little impact on t he results of the modeling effort. In the extreme, on e single footprint value could be used for every ve hicle sold by a single manufacturer as long as the fuel e conomy standard associated with this footprint valu e represented the sales-weighted, harmonic average of the fuel economy standards associated with each vehicle’s footprint values.

## The Baseline Vehicle Fleet

1-31 

## 13.1.3 1.3.5 How does manufacturer product plan data factor into the baseline used in this proposal?

In the spring of 2009, many manufacturers submitted product plans in response to NHTSA’s recent request that they do so. NHTSA and EPA both have access to these plans, and both agencies have reviewed them in deta il. A small amount of product plan data was used in the development of the baseline. The specific pieces of data are:

• Wheelbase

• Track Width Front

• Track Width Rear

• EPS (Electric Power Steering)

• ROLL (Reduced Rolling Resistance)

• LUB (Advance Lubrication i.e. low weight oil)

• IACC (Improved Electrical Accessories)

• Curb Weight

• GVWR (Gross Vehicle Weight Rating)

The track widths, wheelbase, curb weight, and GVWR could have been looked up on the internet (159 were), but were taken from the product plans when available for convenience. To ensure accuracy, a sample from e ach product plan was used as a check against the numbers available from Motortrend.com. These numbers will be published in the baseline file since they can be easily looked u p on the internet. On the other hand, EPS, ROLL, LUB, and IACC are difficult to determine without using manufacturer’s product plans. These items will not be published i n the baseline file, but the data has been aggregated into the agencies’ baseline in the technology effectiveness and cost effectiveness for each vehicle in a way that allows the baseline for the model to be published without revealing the manufacturers data.



## 13.1.4 Have the agencies performed any analysis using manu facturer product plan data factor?

In addition to performing analysis using the baseli ne common to both agencies, NHTSA has conducted a separate analysis that does m ake use of these product plans. The analysis is documented in the Preliminary Regul atory Impact Analysis (PRIA) accompanying NHTSA’s Notice of Proposed Rulemaking (PRIA). However, NHTSA performed this separate analysis for purposes of co mparison only. NHTSA use d the publicly available baseline for all analysis relate d to the development and evaluation of the proposed new CAFE standards Formatted: Bullets and Numbering

## Draft Joint Technical Support Document

1-32 References

1 

### CFEIS (Certification Fuel Emissions Information Sy stem) Database: CFEIS is an EPA database system.

2 

### WardsAuto.com : Used as a source for engine specifications.

3 

### Motortrend.com and Edmunds.com: Used as a source f or foot print and vehicle weight data.

4 Energy Information Administration’s 2009 Annual Ene rgy Outlook.

5 CSM World Wide, CSM World Wide is a paid service pr ovider; J.D. Power Automotive Forecasting, J.D. Pow er Automotive Forecasting is a paid service provider.

6 

### The baseline Excel file (“2008-2016 Production Sum mary Data _Definitions Docket 08_27_2009”) is available in the docket (Docket EPA-HQ-OAR-2009-047 2).

7 

### “CSM North America Sales Forecast Comparison 2Q09 3Q09 For Docket.” 2 nd 

### and 3 rd 

### quarter forecasting results from CSM World Wide ( Docket EPA-HQ-OAR-2009-0472 ).

8 

### See 49 CFR Part 512.