# Prepared for: Office of Transportation and Air Quality

U.S. Environmental Protection Agency

2565 Plymouth Road

Ann Arbor, Michigan 48105

Prepared by: Ricardo, Inc.

40000 Ricardo Drive

Van Buren Twp., Michigan 48111

Systems Research and Applications Corporation (SRA)

652 Peter Jefferson Parkway, Suite 300

Charlottesville, Virginia 22911

EPA Contract No.: EP-C-11-007

Work Assignment: 0-12

Ricardo Archive: RD.10/157405.8

Date: 29 November 2011 

# PROJECT REPORT

COMPUTER SIMULATION OF LIGHT-DUTY

VEHICLE TECHNOLOGIES FOR

GREENHOUSE GAS EMIS SION REDUCTION

IN THE 2020–2025 TIMEFRAME

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# The following organizations contributed to this study:

Ricardo, Inc.

SRA International (formerly Perrin Quarles Associates, Inc.)

The U.S. Environmental Protection Agency

The California Air Resources Board

The International Council on Clean Transportation

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# COMPUTER SIMULATION OF LIGHT-DUTY VEHICLE TECHNOLOGIES FOR

GREENHOUSE GAS EMISSION REDUCTION IN THE 2020–2025 TIMEFRAME

EXECUTIVE SUMMARY

Ricardo, Inc. was subcontracted by Systems Re search and Applications Corporation (SRA), a

wholly owned subsidiary of SRA International, Inc., under contract to the United States

Environmental Protection Agency (EPA) to assess the effectiveness of future light duty vehicle

(LDV) technologies on future vehicle performance and greenhouse gas (GHG) emissions in the

2020–2025 timeframe. GHG emissions are a globally important issue, and the EPA's Office of

Transportation and Air Quality (OTAQ) has been c hartered with examining the GHG emissions

reduction potential of LDVs, including passenger cars and light-duty trucks. This program was

performed between October 2009 and November 2011.

The scope of this project was to execute an independent and objective analytical study of LDV

technologies likely to be available within the 2020–2025 timeframe, and to develop a data

visualization tool to allow users to evaluate the effectiveness of LDV technology packages for

their potential to reduce GHG emissions and their effect on vehicle performance. This study

assessed the effectiveness of a broad range of technologies including powertrain architecture

(conventional and hybrid), engine, transmission, and other vehicle attributes such as engine

displacement, final drive ratio, vehicle weigh t, and rolling resistance on seven light-duty vehicle

classes. The methodology used in this program surveyed the broad design space using robust

physics-based modeling tools and then generated a computationally efficient response surface

to enable extremely fast surveying of the design space within a data visualization tool. During

this effort, quality assurance checks were employed to ensure that the simulation results were a

valid representation of the performance of the vehicle. Through the use of the data visualization

tool, the users can query the design space on a real time basis while capturing interactions

between technologies that may not be identified from individual simulations.

This report documents the work done on the program “Computer Simulation of Light Duty

Vehicle Technologies for Greenhouse Gas Emission Reduction in the 2020–2025 Timeframe”.

This work has included identifying and selecting technologies for inclusion in the study,

developing and validating baseline models, and developing the data visualization tool.

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# TABLE OF CONTENTS

1. INTRODUCTION ................................................................................................................... 8

2. OBJECTIVES ........................................................................................................................ 9

3. BACKGROUND .................................................................................................................... 9

3.1 Study Background .......................................................................................................... 9

3.2 Ground Rules for Study ................................................................................................ 10

3.3 Technology Package Selection Process ...................................................................... 11

3.4 Complex Systems Modeling Approach ......................................................................... 12

3.5 Data Visualization Tool ................................................................................................. 1 3

4. TECHNOLOGY REVIEW .................................................................................................... 13

4.1 Advanced Engine Technologies ................................................................................... 13

4.1.1 Advanced Valvetrains ............................................................................................ 14

4.1.1.1 Cam-Profile Switching Valvetrain .......................................................................... 14

4.1.1.2 Digital Valve Actuation Valvetrain ......................................................................... 14

4.1.2 Direct Injection Fuel Systems ................................................................................ 17

4.1.3 Boosting System ................................................................................................... 17

4.1.4 Other Engine Technologies ................................................................................... 18

4.2 Engine Configurations .................................................................................................. 19

4.2.1 Stoichiometric DI Turbo ......................................................................................... 19

4.2.2 Lean-Stoichiometric Switching .............................................................................. 21

4.2.3 EGR DI Turbo ........................................................................................................ 22

4.2.4 Atkinson Cycle ....................................................................................................... 23

4.2.5 Advanced Diesel ................................................................................................... 23

4.2.6 Fueling Map Development Examples .................................................................... 24

4.2.6.1 EBDI ® 

# to EGR DI Turbo ......................................................................................... 24

4.2.6.2 Contemporary to Future Atkinson ......................................................................... 25

4.3 Hybrid Technologies ..................................................................................................... 2 6

4.3.1 Micro Hybrid: Stop-Start ........................................................................................ 26

4.3.2 P2 Parallel Hybrid .................................................................................................. 26

4.3.3 Input Powersplit ..................................................................................................... 27

4.4 Transmission Technologies .......................................................................................... 27

4.4.1 Automatic Transmission ........................................................................................ 28

4.4.2 Dual Clutch Transmission (DCT) ........................................................................... 28

4.4.3 Launch Device: Wet Clutch ................................................................................... 29

4.4.4 Launch Device: Dry Clutch Advancements ........................................................... 29

4.4.5 Launch Device: Multi-Damper Torque Converter .................................................. 30

4.4.6 Shifting Clutch Technology .................................................................................... 30

4.4.7 Improved Kinematic Design .................................................................................. 30

4.4.8 Dry Sump .............................................................................................................. 3 1

4.4.9 Efficient Components ............................................................................................ 31

4.4.10 Super Finishing ..................................................................................................... 31

4.4.11 Lubrication ............................................................................................................ . 31

4.5 Vehicle Technologies ................................................................................................... 31

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# 4.5.1 Intelligent Cooling Systems ................................................................................... 31

4.5.2 Electric Power Assisted Steering .......................................................................... 32

5. TECHNOLOGY BUNDLES AND SIMULATION MATRICES ............................................. 32

5.1 Technology Options Considered ............................................................................... 32

5.2 Vehicle configurations and technology combinations ............................................... 32

6. VEHICLE MODEL ............................................................................................................... 35

6.1 Baseline Conventional Vehicle Models ..................................................................... 35

6.2 Baseline Hybrid Vehicle Models ............................................................................... 36

6.3 Engine Models .......................................................................................................... 36

6.3.1 Warm-up Methodology .......................................................................................... 38

6.3.2 Accessories Models .............................................................................................. 38

6.4 Transmission Models ................................................................................................ 40

6.5 Torque Converter Models ......................................................................................... 42

6.6 Final Drive Differential Model .................................................................................... 42

6.7 Driver Model .............................................................................................................. 43

6.8 Hybrid Models ........................................................................................................... 4 3

7. MODEL VALIDATION RESULTS ....................................................................................... 47

7.1 Validation Cases and 2010 Baseline Vehicle Models ............................................... 47

7.2 Nominal Runs ........................................................................................................... 48

8. COMPLEX SYSTEMS MODEL VALIDATION .................................................................... 48

8.1 Evaluation of Design Space ...................................................................................... 48

8.2 Response Surface Modeling ..................................................................................... 50

9. RESULTS ............................................................................................................................ 5 0

9.1 Basic Results of Simulation ...................................................................................... 50

9.2 Design Space Query ................................................................................................. 50

9.3 Exploration of the Design Space ............................................................................... 51

9.4 Identification and Use of the Efficient Frontier .......................................................... 51

10. RECOMMENDATIONS FOR FURTHER WORK ................................................................ 56

11. CONCLUSIONS .................................................................................................................. 56

12. ACKNOWLEDGEMENTS ................................................................................................... 57

13. REFERENCES .................................................................................................................... 58

APPENDICES ............................................................................................................................. 6 0

Appendix 1, Abbreviations ..................................................................................................... ..... 60

Appendix 2, Assessment of Technology Options ....................................................................... 61

Appendix 3, Baseline Vehicle Parameters and Runs Results .................................................... 63

Appendix 4, Output Factors for Study ......................................................................................... 64

Appendix 5, Nominal Runs Results ............................................................................................ 6 5

ATTACHMENT A ....................................................................................................................... 69

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# LIST OF FIGURES

Figure 3.1: Technology package selection process. ................................................................... 11

Figure 4.1: Honda's VTEC cam profile switching system ........................................................... 15

Figure 4.2: Expected BSFC benefit from CPS system over typical engine operating map. ........ 15

Figure 4.3: INA UniAir digital valve actuation system ................................................................. 16

Figure 4.4: Expected BSFC benefit from DVA system over typical engine operating map. ........ 16

Figure 4.5: General Motors two-stage turbo transient performance ........................................... 18

Figure 4.6: Typical region of fuel enrichment in stoichiometric DI engines, eliminated through

use of a water-cooled exhaust manifold. .................................................................................... 20

Figure 4.7: 2.0- l General Motors SIDI two-stage boosted engine BSFC map ............................ 21

Figure 4.8: Zone of lean operation for Lean-Stoichiometric DI Turbo engine. ............................ 22

Figure 4.9: BSFC map (in g/kW•h) for EBDI ® 

# engine with EGR ................................................. 24

Figure 4.10: BSFC map (in g/kW•h) for Toyota Prius engine ..................................................... 25

Figure 4.11: Comparison of Automatic and DCT Transmission Efficiencies............................... 29

Figure 4.12: Typical transverse wet clutch DCT arrangement .................................................... 30

Figure 6.1: MSC.Easy5 conventional vehicle model. .................................................................. 36

Figure 6.2: Change in BSFC resulting from cylinder heat loss. .................................................. 38

Figure 6.4: Comparison of CVT and optimized DCT gear ratios over drive cycle....................... 41

Figure 6.5: Comparison of shift activity for traditional and optimized shifting strategies. ............ 42

Figure 6.6: 2007 Camry motor-inverter efficiency contour map .................................................. 44

Figure 6.7: High level state flow diagram for the hybrid control strategy. ................................... 44

Figure 6.8: Best BSFC curve superimposed on fueling map. ..................................................... 46

Figure 6.9: Hybrid powertrain energy supervisory strategy. ....................................................... 46

Figure 9.1: Design Space Query screen in Data Visualization Tool. .......................................... 52

Figure 9.2: Design Space Analysis screen in Data Visualization Tool. ....................................... 52

Figure 9.3: Full Size Car Design Space Analysis example ......................................................... 53

Figure 9.4: Full Size Car Design Space Analysis example ......................................................... 53

Figure 9.5: Full Size Car Design Space Analysis example ......................................................... 54

Figure 9.6: Standard Car design space analysis ex ample comparing powertrains with EGR DI

Turbo engine .................................................................................................................. ............. 54

Figure 9.7: Full design space example showing a ll seven vehicle classes using Stoichiometric

DI Turbo engine and advanced automatic transmission with varying vehicle mass and engine

displacement. ................................................................................................................. ............. 55

Figure 9.8: Efficient Frontier screen of Data Visualization Tool with example plot. .................... 55

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# LIST OF TABLES

Table 5.1: Engine technology package definition. ...................................................................... 33

Table 5.2: Hybrid technology package definition. ....................................................................... 33

Table 5.3: Transmission technology package definition. ............................................................ 33

Table 5.4: Baseline and Conventional Stop-Start vehicle simulation matrix. .............................. 34

Table 5.5: P2 and Input Powersplit hybrid simulation matrix. ..................................................... 34

Table 6.1: Vehicle classes and baseline exemplar vehicles. ...................................................... 36

Table 6.3: Accessory loads for conventional stop-start and P2 hybrids. .................................... 39

Table 6.4: Mechanical cooling fan loads for LDT and LHDT. ..................................................... 39

Table 6.5: Transmission gear ratios for six-speed and eight-speed transmissions. ................... 40

Table 7.1: Validation vehicle fuel economy performance. .......................................................... 47

Table 8.1: Continuous input parameter sweep ranges with conventional powertrain. ................ 49

Table 8.2: Continuous input variable ranges for P2 and Powersplit hybrid powertrains. ............ 49

Table A3.1: Baseline Vehicle Parameters and Runs Results. .................................................... 63

Table A5.1: Nominal Runs Results. ............................................................................................ 66

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# 1. INTRODUCTION

Ricardo was subcontracted by Systems Research and Applications Corporation (SRA), a wholly

owned subsidiary of SRA International, Inc., under contract to the United States Environmental

Protection Agency (EPA) to assess the effectiveness of future light duty vehicle (LDV)

technologies on future vehicle performance and greenhouse gas (GHG) emissions in the 2020–

2025 timeframe. GHG emissions are a globally important issue, and the EPA's Office of

Transportation and Air Quality (OTAQ) has been c hartered with examining the GHG emissions

reduction potential of LDVs, including passenger cars and light-duty trucks.

SRA is a company of over 7,000 staff dedicated to solving complex problems of global

significance for government organizations serving the civil government, global health, and

national security markets. SRA’s Air Program s and Climate Change Account works extensively

with OTAQ and other EPA offices on regulatory and voluntary programs to reduce air pollution

and address climate change.

SRA and Ricardo worked closely with the EPA team on nearly every technical and contractual

issue.

The team at EPA OTAQ included the following staff members:

 Matt Brusstar, Director, Advanced Powertrain Center, Testing and Advanced

Technology Division

 Jeff Cherry, Staff Engineer, Light Duty V ehicles and Small Engine Center, Assessment

and Standards Division

 Ann Chiu, Contract Project Officer, Data Analysis and Information Center, Compliance

Division

 Ben Ellies, Staff Engineer, Climate Analysis and Strategies Center, Transportation and

Climate Division

 Joe McDonald, Senior Engineer, Fuels Center, Assessment and Standards Division

In addition to the SRA–Ricardo team working for EPA, other stakeholders for the program

included the International Council on Clean Transportation (ICCT) and the California Air

Resources Board (ARB). ICCT contributed funding for the early portion of the study in

collaboration with ARB. The Advisory Commi ttee provided advice to EPA, and included the

following representatives from ICCT and ARB:

 Steven Albu, Assistant Division Chief, ARB

 Anup Bandivedakar, Senior Researcher, ICCT

 John German, Senior Fellow and Program Director, ICCT

 Paul Hughes, Manager, ARB

Ricardo, Inc., is the US division of Ricardo plc., a global engineering consultancy with nearly

100 years of specialized engineering expertise and technical experience in engines,

transmissions, and automotive vehicle research and development. This program was performed

between October 2009 and November 2011.

The scope of the program was to execute an independent and objective analytical study of LDV

technologies likely to be available for volume production in the 2020–2025 timeframe, and to

develop a data visualization tool to allow users to evaluate the effectiveness of LDV technology

packages for their potential to reduce GHG emissions. An assessment of the effect of these

technologies on LDV cost was beyond the scope of this study.

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# This work was done in collaboration with EPA, and the approach included the following:

 Activities funded by ICCT

o Identify a large set of future technologies that could improve LDV GHG

emissions.

o Assess these technologies for potential benefit and ability to be commercialized

by the 2020–2025 timeframe.

o Reduce this large set to the technologies selected for further study in this

program.

 Activities funded by EPA:

o Extrapolate selected technologies to their expected performance and efficiency

levels in the 2020–2025 timeframe.

o Conduct detailed simulation of the technologies over a large design space,

including a range of vehicle classes, powertrain architectures, engine designs,

and transmission designs, as well as param eters describing these configurations,

such as engine displacement, final drive ratio, and vehicle rolling resistance.

o Interpolate the results over the design space using a functional representation of

the responses to the varied model input factors.

o Develop a Data Visualization Tool to facilitate interrogation of the simulation

results over the design space.

2. OBJECTIVES

The goal of this technical program has been to objectively evaluate the effectiveness and

performance of a large LDV design space with powertrain technologies likely to be available in

the 2020–2025 timeframe, and thereby assess the potential for GHG emissions reduction in

these future vehicles while also understanding the effects of these technologies on vehicle

performance.

3. BACKGROUND

3.1 Study Background

The EPA has an interest in improving the envir onmental performance and efficiency of cars,

trucks, buses, and transportation systems to protect and improve public health, the

environment, and quality of life. Additionally, r eduction of GHG emissions—emphasizing carbon

dioxide (CO 2 

# )—is an increasing priority of national governments and other policymakers

worldwide.

This program builds on the work done earlier by Perrin Quarles Associates (PQA, now part of

SRA) and Ricardo in 2007–2008 to assess the potential effectiveness of GHG-reducing

technologies in LDVs in the 2010–2017 timeframe (Ricardo and PQA, 2008). The earlier

program was also funded by EPA and looked at a series of specific LDV configurations and

from these assessed the benefits.

The purpose of this study is to define and evaluate potential technologies that may improve

GHG emissions in LDVs in the 2020–2025 timeframe. These technologies represent a mixture

of future mainstream technologies and some emerging technologies for the study timeframe.

For this program, however, a large design space was comprehensively examined so that

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# broader conclusions could be drawn about these technologies that could lead to benefits to

GHG emissions reduction.

3.2 Ground Rules for Study

Several ground rules for the study were agreed at the beginning of the program to bound the

design space considered in the study. These ground rules identified content that should be

included in the study as well as content that should be excluded.

Some examples of the ground rules include the following items for the technology assessment:

 Seven vehicle classes will be included, as described below.

 LDV technologies must have the potential to be commercially deployed in 2020–2025. .

 Vehicle sizes, particularly footprint and interior space, for each class will be largely

unchanged from 2010 to 2020–2025.

 Hybrid vehicles will use an advanced hybrid control strategy, focusing on battery state of

charge (SOC) management, but not at the expense of drivability.

 Vehicles will use fuels that are equivalent to either 87 octane pump gasoline or 40

cetane pump diesel.

 2020–2025 vehicles will meet future California LEV III requirements for criteria

pollutants, which are assumed to be equivalent to current SULEV II (or EPA Tier 2 Bin 2)

levels.

 Ricardo would be allowed to use Ricardo proprietary data and expertise to assess

technologies and develop the models, as this allowed the technologies to be assessed

more comprehensively than if only publicly available data were used. Ricardo

confidential business information relevant to the execution of the program was shared

with EPA for the purposes of allowing an external audit of the model inputs developed

for the program.

 Due to the multiple designs that manufacturers may realize for any given advanced

technology, the effect of technologies on overa ll vehicle mass is not incorporated directly

in the Easy5 models. Instead, the model makes the overt simplifying assumption that all

technologies are mass-neutral. The end-user has the flexibility to incorporate their own

assumptions about mass reduction from advanced technologies when exploring the

design space with the Data Visualization Tool.

 Similarly, other road load reductions such as aerodynamic drag and rolling resistance

reduction were addressed as input variables within the complex systems modeling

approach.

Likewise, EPA, along with input from the Advisory Committee agreed for this program that the

technology assessment should exclude the following:

 Charge-depleting powertrains, such as plug-in hybrid electric vehicles (PHEV) or battery

electric vehicles (BEV) 1



# .

 Fuel cell power plants for fuel cell-electric vehicles (FCEV).

 Non-reciprocating internal combustion engi nes (ICE) or external combustion engines.

 Manual transmissions and automated manual transmissions (AMT) with a single clutch.

 Kinetic energy recovery systems (K ERS) other than battery systems.

1 

# While modeling of vehicles with increased electrif ication would be beneficial, the highest priority was

given to vehicle architectures determined most likely to be present in higher volumes during the 2020–

2025 time frame. Due to resource limitations, PHEVs and BEVs were considered outside the scope of

this study and left as candidates for follow-up modeling work.

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#  Intelligent vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) optimization

technology.

 Bottoming cycles, such as organic Rankine cycles, for energy recovery.

 Vehicle safety systems or structures will not be explicitly modeled for vehicles. A full

safety analysis of the technologies presented in this report is beyond the scope of this

study.

The seven vehicle classes considered in this study are the following, with a currently available

example vehicle given for each class:

1. Small (B-class) Car, such as the Toyota Yaris

2. Standard (D-class) Car, such as the Toyota Camry

3. Small Multi-Purpose Vehicle (MPV), such as the Saturn Vue

4. Full Sized Car, such as the Chrysler 300

5. Large MPV, such as the Dodge Grand Caravan

6. Light-Duty Truck (LDT), such as the Ford F150

7. Light Heavy-Duty Truck (LHDT), such as the General Motors HD3500

3.3 Technology Package Selection Process

The program team used the process shown in Fi gure 3.1 to identify the technology options

listed in Appendix 2, Assessment of Technology Options, to the set described in Chapter 4,

Technology Review, and integrated into the technology bundles described in Chapter 5,

Technology Bundles and Simulation Matrices.

F1 

# Figure 3.1: Technology package selection process.

The program team first developed a comprehensive list of potential technologies shown in

Appendix 2 that could be in use on vehicles in the study timeframe, 2020–2025. These

technologies were grouped by subject area, such as transmissions, engines, or vehicle, and

given to Ricardo subject matter experts (SME s) for assessment and evaluation. These SME

assessments were then reviewed with EPA, who also sought input from the Advisory

Committee. Together, the program team determined which technologies would be included

once they were evaluated qualitatively against the following criteria for further consideration:

 Potential of the technology to improve GHG emissions on a tank to wheels basis

 State of development and commercialization of the technology in the 2020–2025

timeframe

 Current (2010) maturity of the technology

The technology options selected were then put together into technology packages for use in the

vehicle performance simulations. An additional consideration was how the inclusion of the 

# Technology

Identification Ricardo

Subject

Matter

Expert

Assessment EPA Review

&

Technology

Discussion Technology

Package

Selection

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# technology would affect simulation matrices presented in Section 5.2, particularly the effect on

the overall number of simulations needed.

3.4 Complex Systems Modeling Approach

Complex systems modeling (CSM) is an objective, scientific approach that supports high-level

decision making when there are a large number of factors to consider that influence the

outcome, as with LDV development for vehicle performance and GHG emissions reduction.

A vehicle is made up of interrelated components and subsystems, which combined make up a

system that by definition provides functionality greater than the sum of its parts. An automotive

system like a vehicle may be defined as a "complex system" based upon the number of

interrelated, interconnected, and interwoven elements and interfaces requiring a great deal of

information to specify (Kinnunen, 2006). An important concept associated with complex systems

is the property of "emergence". In this contex t it means that there may be collective behavior of

the components and subsystems along with the syst em’s response to its environment that are

not predictable or linear in response to changes to the individual behavior of each part.

A number of interdisciplinary scientific efforts ha ve led to the development of "complex systems

theory", which seeks to overcome the limitations of reductionist approaches through the

development of tools and models that are abl e to capture emergence and other behavior of

complex systems (McCarthy, et al. , 2000). Supplementing the use of complex systems theory is

the application of the system engineering proce ss model, which dictates proceeding from the

general to the detailed—a top down approach—and observes the principle of creation and

selection of alternatives. These theories and principles have been developed into a

methodology that utilizes physics-based modeling and simulation in order to enable quantitative

analysis over a multidimensional design space along with advanced visualization techniques in

order to understand the results (Biltgen, et al. , 2006). Ricardo has incorporated this

methodology, now referred to as “complex system modeling (CSM) into its consulting practice

on previous projects (Luskin, 2010).

In this program, many combinations of technologies were used to generate detailed results that

were abstracted and made accessible through a Data Visualization Tool described in

Section 3.5. To be objective, performance metrics were identified by EPA and the Advisory

Committee; these metrics were outputs of the vehicle performance simulation effort and

characterize key vehicle attributes. To be scientific, the performance simulations use a physicsbased modeling approach for detailed simulation of the vehicle.

The design of experiments (DoE) approach surveys the design space in a way that extracts the

maximum information using a limited budget of simulation runs. The purpose of the DoE

simulation matrix was to efficiently explore a comprehensive potential design space for LDVs in

the 2020–2025 timeframe. The simulation matrix was designed to generate selected

performance results over the selected drive cycles , such as fuel consumption or acceleration

times.

A statistical analysis was used to correlate variations in the input factors to variations in the

output factors. Because of the complex nature of the LDV configurations and constituent

technology packages, a neural network approach was used to quantify the relationships

between input and output factors over the design space explored in the simulations. The result

of this analysis was a set of response surface models (RSM) that represent in simplified form

the complex relationships between the input and output factors in the design space.

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# 3.5 Data Visualization Tool

The Data Visualization Tool allows the user to efficiently assess the effects of various

combinations of future technologies on GHG em issions and other vehicle performance metrics.

The tool allows the user to query the RSM and investigate options leading to equivalent GHG

emissions levels. A separate User Guide for the Data Visualization Tool will be released with the

tool and will provide more information on how to use the tool to access the results.

The Data Visualization Tool uses the RSM set generated by the Complex Systems approach to

represent the vehicle performance simulation results over the design space. These simulations

cover multiple variations of vehicle configuration, including several combinations of advanced

powertrain and vehicle technologies in the seven LDV classes. Vehicle configurations with

unacceptable performance, such as combined fuel economy below a certain threshold or

acceleration times longer than some benchmark value, can be excluded from further study.

The tool samples vehicle configurations from a selected subset of the design space by using

Monte Carlo type capabilities to pick input parameter values from a uniform distribution. Defining

selected portions of the design space and plotting the results visualizes the effect of these

parameters on vehicle fuel economy and performance, allowing trade off analysis via

constraints setting to be performed over a wide design space representing the 2020–2025

technologies as applied.

4. TECHNOLOGY REVIEW

Following the process outlined above in Section 3.3, Technology Package Selection Process, a

broad list of potential technologies was identified for consideration in the study and then

narrowed to a subset for inclusion in the study. The technologies in this subset are described in

this chapter.

In the study timeframe of 2020–2025, spark-ignit ed (SI) engines are projected to continue to be

the dominant powertrain in the U.S. LDV market, especially since the efficiency of SI engines is

expected to approach the efficiency of compression ignition (CI, or diesel) engines at the

required 2020–2025 emissions levels. Diesel engines are also included as they are still

expected to be present in the study timeframe, especially in the heavier vehicle classes.

The first two sections of this chapter therefore describe the technologies expected to appear in

future engines generally and in the specific engine configurations considered in the study,

respectively. The other sections in this chapter describe the transmission and driveline, vehicle,

and hybrid system technologies that were included in the overall design space of the study. The

implementation of these technologies in t he vehicle performance models is described in

Chapter 6, Vehicle Model.

4.1 Advanced Engine Technologies

The primary challenge for advanced engines in the 2020–2025 timeframe is to reduce GHG

emissions and maintain performance while meeting increasingly stringent criteria pollutant

standards. This challenge is expected to be me t through a range of improvements, from the

application of highly-efficient downsized engines through to detailed optimization of components

and systems. This section describes specific tec hnologies or systems that are expected to be

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# included in future engines, each of which supports the overall goal of reduced GHG emissions

in future vehicles. Section 4.2, Engine Configurations, describes the complete engine

technology packages that synthesize the effects of the technologies described here to develop

the model inputs used.

4.1.1 Advanced Valvetrains

Several advances in valvetrain technology are ex pected to be available in the study timeframe.

These technologies are expected to apply to engines across the whole set of vehicle classes

examined in the study.

Advanced valvetrain systems improve fuel cons umption and GHG emissions mainly by reducing

pumping losses in the engine. The pumping loss mitigation provides larger benefits at part-load

operation, such as during urban driving. Advanced valvetrains also support engine downsizing,

which provides fuel consumption benefits across the complete engine operating map. Lastly,

they can be used to support faster aftertreatment warm-up through varied timing, leading to

additional, synergistic gains if the faster aftertreatment warm-up creates a benefit to tailpipe-out

NO

x 

# emissions that can be traded off to improve GHG emissions.

Two advanced valvetrain options, cam-profile switching and digital valve actuation, were

included in the study and are discussed below. The effects of these valvetrains were integrated

into the model inputs developed for the complete engine technology packages described in

Section 4.2.

4.1.1.1 Cam-Profile Switching Valvetrain

Cam-profile switching (CPS) systems use a hydr aulically-actuated mechanical system to select

between two or three cam profiles. CPS systems, such as the Honda VTEC, Mitsubishi MIVEC,

Porsche VarioCam, and Audi Valvelift, have been developed by a number of Japanese and

European manufacturers. Figure 4.1 shows a di agram of Honda's VTEC CPS system (Honda,

2011). CPS systems can be designed to improve low-speed torque or to improve fuel economy

by reducing pumping losses at light load. CPS systems are applicable in all LDV classes. The

benefit to fuel consumption is expected to range up to 7% at specific part-load operating points,

as shown in Figure 4.2, and will therefore provide a larger benefit in city driving than in highway

driving.

4.1.1.2 Digital Valve Actuation Valvetrain

Digital valve actuation (DVA) uses a mechanical, hydraulic, or electrical system to actuate the

valves independently of a camshaft. The full realization of DVA in the study timeframe will be a

camless DVA system, where there is no mechanical linkage between the engine crank and the

valves. The engine fueling maps with DVA were assumed to use camless DVA systems, such

as electrohydraulic or electromagnetic system s. Electropneumatic systems are less mature

currently, but may yet be available late in the timeframe. An example DVA system in current

production is the Fiat MultiAir system, which is an electro-hydraulic system (Fiat, 2009),

although it still uses a camshaft to provide the primary timing for the valve open and valve close

events. The Schaeffler Group's INA UniAir DVA syst em is shown in Figure 4.3. The DVA system

could be implemented to provide flexibility with valve event timing, valve lift profiles, or both. As

with the CPS systems, the main benefit in GHG emissions is a result of reducing pumping

losses at part-load operation and lower engine speeds, although the benefits at specific

operating points can range up to 12% as shown in Figure 4.4.

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# F2 

# Figure 4.1: Honda's VTEC cam profile switching system. (Honda, 2011)

F3 

# Figure 4.2: Expected BSFC benefit from CPS system over typical engine operating

map.BMEP [bar]



# 0 2 4 6 8 10



# Engine speed [rev/min] 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000 5 4 3 2 1 0

6 

# CPS benefit [%]

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# F4 

# Figure 4.3: INA UniAir digital valve actuation system. (Schaeffler Group, 2010)

F5 

# Figure 4.4: Expected BSFC benefit from DVA system over typical engine operating

map.BMEP [bar]



# 0 2 4 6 8 10



# Engine speed [rev/min] 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000 0

2

4

6

8

10 

# Variable valve-lift (DVA) benefit [%]

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# 4.1.2 Direct Injection Fuel Systems

Direct injection (DI) fuel systems are the standard fuel injection system in use on current diesel

engines. One of the significant changes expected by the 2020–2025 timeframe is a continued

transition from port fuel injection (PFI) to DI in SI engines as well. For SI engines with DI, the

fuel is injected directly into the combustion cylin der before being ignited. DI fuel systems inject

the fuel at a higher pressure than PFI injectors do, and allow the use of multiple injection events

to support advanced combustion control. SI engines with DI were first introduced in Japan in

1996, and an increasing number of new SI engines now feature DI.

Using DI improves fuel consumption across the full range of engine operation, including at partload and high-load conditions, with an expected benefit of 2–4%. DI improves fuel economy by

facilitating a higher compression ratio in the engine, which improves the engine's volumetric and

thermal efficiency. Although detailed injection control strategies were not specifically modeled,

the effects of DI fuel systems were integrated into the model inputs developed for the complete

engine technology packages described in Section 4.2. The program team used their experience

with research engines and with developing and benchmarking production engines to project that

spray-guided DI will be the mainstream DI technology in use in the 2020–2025 timeframe,

supplanting wall guided DI. Spray-guided DI offers the capability to deliver a stratified charge—

where the fuel concentration decreases away from the spark plug—that will facilitate lower GHG

emissions through unthrottled lean-burn operation.

For diesel engines, emissions requirements will cause the injection pressures to continue to

increase to the 2000–2400 bar injection pressure range. These very high injection pressures

support better combustion and reduced engine-out emissions. In addition, multiple injection

events will be used to better control the onset and progress of the combustion event in the

cylinder.

4.1.3 Boosting System

Using devices to boost the engine's intake air pressure will increase the torque and power

available from a given engine displacement. By increasing the boost pressure while decreasing

engine displacement, the power level is maintained while reducing pumping work in the engine

by shifting engine operation to higher-load operating points.

The advanced engines in the 2020–2025 timeframe are expected to have advanced boosting

systems to increase the pressure of the intake charge up to 3 bar. Various boosting approaches

are possible, such as superchargers, turbochargers, and electric motor-driven compressors and

turbines. The appropriate technology for 2020–2025 will need to provide cost-effective

improvement in performance and efficiency while mitigating turbo lag. Matching a boosting

system to a particular engine is very important to realize the maximum benefits of this

technology. For this study, the effects of the boosting system are already incorporated in the

engine map to produce a reasonably optimized syst em performance over a wide range of input

variables.

Turbocharged engines in the 2020–2025 timeframe are expected to have an advanced boost

strategy that provides a smooth accelerati on feel. The advanced engines with boost systems

were assumed to have two-stage series se quential turbocharger systems. Turbocharging

means that there is some risk of the vehicle per formance being affected by turbo lag, a delay in

the torque rise that results from the dynamics of the gas flow through the engine. This effect is

illustrated in Figure 4.5, which shows the benefits of the two-stage turbo system described by

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# Schmuck-Soldan, et al. (2011), that General Motors had tested against twin-scroll

turbochargers. Figure 4.5 shows the torque response using net mean effective pressure

(NMEP), which equals both the difference between the indicated and pumping mean effective

pressures (IMEP and PMEP, respectively), and the sum of the brake and friction mean effective

pressures (BMEP and FMEP, respectively). Turbo lag is most significant during hard

acceleration events, especially when the engine starts at or near its idle speed and load.

Mitigating turbo lag means carefully choosing the capacities of the high pressure and low

pressure compressors and turbines and connecting pipes to provide acceptable steady-state

torque across the engine speed range and an acceptable transient rate of torque rise, often

expressed as the time required to reach 85% of maximum torque at a given engine speed.

Modeling turbo lag effects is described later in Section 6.3, Engine Models.

F6 

# Figure 4.5: General Motors two-stage turbo transient performance.

( 

# Schmuck-Soldan, et al. , 2011)

4.1.4 Other Engine Technologies

Other engine technologies incorporated into the future engines were further improvements in

engine friction leading to a global reduction in engine fuel consumption. This friction reduction is

expected to result from a combination of tech nology advances, including piston ringpack, bore

finish, lower-viscosity crankcase lubricants, low-friction coatings, valvetrain components, and

bearing technology. The details of these improv ements in engine friction were not explicitly

itemized in this study, and were instead treated as a global engine friction reduction.

Another approach is to optimize the overall engi ne design, for example, by combining engine

components to reduce mass and thermal inertia, giving an improved package and faster warmup. Ancillary systems may also be electrified to remove the front engine accessory drive (FEAD)

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# and allow variable accessory performance independent of engine speed. (See, for example,

Section 4.5.2, Electric Power Assisted Steering.) The combination of components, such as the

exhaust manifold and cylinder head design, will im prove the response time for turbocharging

and aftertreatment warm-up. Electrification of FEAD components, such as the electrical coolant

pump, oil pump, or AC compressor, reduces parasitic losses on the engine and allows

accessory operation to be optimized for the operating point independently of the engine.

4.2 Engine Configurations

Several engine configurations were defined using combinations of the advanced engine

technologies described in Section 4.1 based on an assessment of what would be in mainstream

use in the 2020–2025 timeframe. Five main types of engines were used in the study, and are

described in this section.

The engines considered for the 2020–2025 timeframe were developed using two main methods.

The first method, used with the boosted SI engines, was to review the reported performance of

current research engines, and assume that these current research engines would closely

resemble the production engines of the 2020–2025 timeframe. This method takes current

research engines and refines them to meet production standards, including manufacturability,

cost, and durability. The second method, used with the Atkinson cycle SI and the diesel

engines, was to start from current production engines and then determine a pathway of

technology improvements over the next 10–15 years that would lead to an appropriate engine

configuration for the 2020–2025 timeframe. With both methods, current trends in engine design

and development were extrapolated to obtain an advanced concept performance for the 2020–

2025 timeframe that should be achievable in production volumes. All of the engine fueling maps

developed accounted for the effects of future criteria pollutant standards, assumed to be

equivalent to California ARB's SULEV II or to EPA Tier 2 Bin 2. These fueling maps were

reviewed by EPA and the Advisory Committee to ensure that they were suitable for the study.

The combinations of technologies encompassed in each advanced engine concept provide

benefits to the fueling map, or values of brake-specific fuel consumption (BSFC) over the

operating speed and load ranges of each engine. For these future engines, the BSFC is

improved by up to 10% from current levels. Many of the future engine concepts have low BSFC

values over large zones of the engine operating map, with the best BSFC point often at lower

speeds and part-load conditions. The implementation of these technology packages into the

vehicle performance models is described in Section 6.3.

4.2.1 Stoichiometric DI Turbo

The basic advanced engine configuration is the Stoichiometric DI Turbo SI engine. This

advanced engine assumes continued use of a stoichiometric air-fuel ratio for simplified

aftertreatment using a three-way catalyst. The engine modeled has a peak brake mean effective

pressure (BMEP) of 25–30 bar, which supports significant downsizing compared to current 2010

engines. This high BMEP level is reached through a combination of engine technologies,

including advanced valve actuation, such as CPS; spray-guided DI; and advanced boost

systems, such as series-sequential turbochargers (see Sections 4.1.1, 4.1.2, and 4.1.3,

respectively). The compression ratio of the engines was set at 10.5:1, which provides a balance

between fuel consumption and performance.

Current research engines of this configuration have been developed by several groups. One

example is the Sabre engine described by Coltman, et al . (2008) and by Turner, et al . (2009).

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# The Sabre engine uses CPS to reduce pumping losses at part-load operation (Turner, et al

., 2009), but only uses single-stage turbocharging with DI in a 1.5 l three-cylinder engine to reach

20 bar peak BMEP. Lumsden, et al . (2009) at MAHLE Powertrain have also developed a 1.2 l

, three-cylinder research engine similar to the Stoichiometric DI Turbo SI engine with a peak

BMEP of 28 bar to support up to 50% downsizing.

The Stoichiometric DI Turbo engine was assumed to operate with a stoichiometric air-fuel ratio,

without enrichment, over the complete operating map, even at high-speed, high-load operating

conditions, which significantly improves the fuel consumption in this part of the operating map

as shown in Figure 4.6. This change in operation requires design changes to support the higher

exhaust gas temperatures to ensure protec ting the valves, pistons, and exhaust system

components. For example, the future engine configuration uses a cooled exhaust manifold to

keep the turbine inlet temperatures below 950°C over the full operating range of the engine to

mitigate the need for upgraded materials in the exhaust manifold and turbine. This change also

provides benefits to criteria pollutant emissions, especially over the US06 cycle.

F7 

# Figure 4.6: Typical region of fuel enrichment in stoichiometric DI engines (shown in

blue), eliminated through use of a water-cooled exhaust manifold.

Since the initial conception of the 2020 Stoichiometric DI Turbo, several companies have

engineered new versions of direct injected turbo engines with fueling maps that closely

resemble the maps that were synthesized and us ed in this study. One example is the research

engine executed by General Motors described by 

# Schmuck-Soldan, et al. (2011 ), that uses a

two-stage series sequential boosting system like t hat envisioned for the Stoichiometric DI Turbo

engine in a 2.0- l variant of the Ecotec SIDI engine. Presented at the Internationales Wiener

Motorensymposium, General Motors' engine achieves a maximum BMEP of 26.4 bar. The best

BSFC island shown in Figure 4.7 is rather large and the zone of best BSFC (up to 105% of the

minimum BSFC) marked on the map encompasses almost half of the useable engine operating

range. All of the features described by General Motors are similar to those integrated into the

Stoichiometric DI Turbo engine concept modeled for this program, and consequently the two

engines have very comparable fueling maps. 

# 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

0 1000 2000 3000 4000 5000 6000Normalized Load



# Engine Speed (rpm)

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# Figure 4.7: 2.0- l General Motors SIDI two-stage boosted engine BSFC map.

(Schmuck-Soldan, et al., 2011)

4.2.2 Lean-Stoichiometric Switching

The Lean-Stoichiometric DI Turbo SI engine configuration is similar in all respects to the

Stoichiometric DI Turbo engine described above in Section 4.2.1, except that it uses a fuel-lean

air-fuel ratio with λ ≈ 1.5 at moderate speeds and loads, such as those seen on the FTP75

cycle. Elsewhere, such as on the US06 cycle, the engine switches to stoichiometric operation

with a three-way catalyst, to avoid exceeding the expected temperature and space velocity

limits of the lean aftertreatment system. This mixed-mode operation allows the engine to take

advantage of the efficiency benefits of lean operation while mitigating the technical challenges

associated with lean-burn emissions control. Figure 4.8 illustrates the zones of lean and

stoichiometric operation over the engine operating map.

Fuel lean operation improves fuel consumption by increasing the relative charge volume per unit

of fuel burned, enabling a higher compression ratio, improved charge mixing and less intake

throttling. Nevertheless, while lean operation leads to efficient oxidation of unburned

hydrocarbon and carbon monoxide pollutants in the engine exhaust stream, the presence of

excess oxygen makes reduction of nitrogen oxides (NO

x 

# ) more challenging. Therefore, an

additional emissions control device, such as a lean NO

x 

# trap (LNT) or a urea-based selective

catalytic reduction (SCR) system, would be required to remove NO

x 

# from the net oxidizing

exhaust gas. The program team raised concerns about the effectiveness of these NO

x 

# removal

systems at the high temperatures and exhaust gas flow rates, or space velocities, easily

reached by SI engines at high engine speed or l oad, and also about catalyst durability under hot

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# and oxidizing conditions over the vehicle life. These concerns suggest that meeting criteria

pollutant levels over a drive cycle such as the US06 could be challenging to the expected end of

life, but advances would be made over the inte rvening years to make such systems production

feasible.

Therefore, the engine switches to stoichiometric operation when the exhaust temperature

crosses a threshold above which the NO

x 

# removal system catalysts would suffer accelerated

degradation. This transition zone between lean and stoichiometric operation is shown in

Figure 4.8. At high load conditions, then, the exhaust emissions are treated using typical threeway catalysts. The engine therefore performs exactly like the Stoichiometric DI Turbo engine at

higher load, but has improved BSFC at lower load because it switches to lean operation. A

modest fuel consumption penalty is applied over eac h drive cycle to account for the use of fuel

or other reducing agent to remove NO

x 

# during lean operation.

F9 

# Figure 4.8: Zone of lean operation for Lean-Stoichiometric DI Turbo engine.

4.2.3 EGR DI Turbo

The EGR DI Turbo engine is also similar to the Stoichiometric DI Turbo Engine described in

Section 4.2.1, except that it uses cooled external exhaust gas recirculation (EGR) to reduce

intake throttling and to manage combustion k nock and exhaust temperatures. The recirculated

exhaust gas dilutes the air and fuel charge in the cylinder, thereby moderating the temperature

during combustion and allowing operation without enrichment over a higher range of load and

speed. Additionally, the EGR mitigates the tendency for engine knock, potentially enabling a

higher compression ratio, and reduces the need for throttling at low-load operation, thereby

reducing engine pumping losses.

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# Dual high-pressure and low-pressure EGR loops were assumed for this engine configuration,

which will require additional components such as EGR valves and a heat exchanger (EGR

cooler) to manage the EGR flow and temperature. EGR rates of up to 20–25% are feasible with

this air system (Cruff, et al ., 2010; Beazley, 2010). EGR use allows a modest overall

improvement in fuel consumption across the complete operating map compared to the

Stoichiometric DI Turbo engine.

4.2.4 Atkinson Cycle

The Atkinson cycle is characterized by leaving the intake valves open during the start of the

compression stroke, which lowers the effective compression ratio of the engine back to that of

the normal SI engine, but allows for a larger effective expansion ratio. This change in engine

operation improves fuel consumption, but penalizes torque availability at lower engine speeds.

For this reason, Atkinson cycle engines are typically used only in hybrid vehicle applications,

where the electric machine can be used to provide extra torque during launch or other hard

acceleration events.

Separate Atkinson cycle engine fueling maps were developed for the 2020–2025 timeframe with

both CPS and DVA valvetrains. These fueling maps reflect the differing net benefits of the

valvetrains, including actuation losses. These engines are only used with the P2 parallel and

Input Powersplit hybrid powertrains described in Section 4.3, Hybrid Technologies. The torque

curve and fueling map thus generated also reflect the benefits of so-called downspeeding, or a

lower overall operating speed range, which yields further fuel consumption benefits by reducing

frictional losses in the engine (Hohenner, 2010).

4.2.5 Advanced Diesel

The advanced diesel engines for the 2020–2025 timeframe were developed by starting with

existing production engines and identifying technology advances that would lead to further

improvements in fuel consumption. Several of the technologies discussed in Section 4.1,

Advanced Engine Technologies, are applicable to advanced diesels, including seriessequential, two-stage turbocharging, enhanced EGR and charge air cooling, and CPS. The

composite effects of these technologies were reflected in the improvements made to existing

engine fueling maps to derive the advanced diesel engine fueling maps.

This approach led to different maps being developed for each of the vehicle classes that had

diesel engines available: the Small Car, Fu ll Size Car, Large MPV, LDT, and LHDT. For

example, the LHDT engine torque curve and fueling maps were generated by starting with a

6.6 l diesel engine typical for this class and ap plying the benefits of improvements in pumping

losses or friction to the fueling map. Engine displacements for the advanced diesels were

chosen based on the current torque and power levels available from these engines, the

expected future requirements, and the effects of applying advanced technologies to support

further downsizing. Current diesel engines fo r LDVs already use advanced variable-geometry

boost systems and high-pressure common-rail direct injection for better torque response and

specific power. Improvements in these areas are therefore expected to be incremental, by

contrast with the more extensive changes to SI engine architectures described above. For

example, the peak BMEP of the advanced diesels is in the 17–23 bar range, which is noticeably

lower than that expected for the advanced SI engines.

This difference is, however, consistent with Rica rdo's expectation of the pace and direction of

technology development for diesel engines that comply with the expected emissions

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# requirements defined in the study's ground rules defined in Section 3.2, that is, emissions

standards consistent with today's California SULEV II or EPA Tier 2 Bin 2 standards. A modest

fuel consumption penalty was applied to account for the additional fuel required for particulate

filter regeneration and lean NOx aftertreatment.

4.2.6 Fueling Map Development Examples

Examples of each method of developing the advanced engine fueling maps are presented

below. The first example shows how the EGR DI Turbo engine described in Section 4.2.3 was

developed, and the second, how the Atkinson engi ne described in Section 4.2.4 was developed.

4.2.6.1 EBDI ® 

# to EGR DI Turbo

The EBDI ® 

# engine (Cruff, et al ., 2010; Beazley, 2010) is a recently-developed research engine

that incorporates many of the technologies expected in the EGR DI Turbo engine and was

therefore the starting point for the advanced engine. Adjustments were then made to the EBDI ®



# engine fueling map to make it representative of a production engine expected in the 2020–2025

timeframe.

The current research engine has the fueling map shown in Figure 4.9, where the contours show

BSFC (in g/kW·h) as a function of engine speed and BMEP and the best BSFC point marked is

230 g/kW·h at 2000 rpm and 12 bar BMEP. This engine is designed to reach 30 bar BMEP

running on gasoline and up to 35 bar BMEP on E85. To this end, the EBDI ® 

# engine uses a 10:1

compression ratio and the single-stage turbocharger is sized to reach 2.88 bar boost pressure.

EGR rates vary from 0% up to 23% during operation. The research engine uses direct injection

and has variable intake and exhaust cam phasing.

F10 

# Figure 4.9: BSFC map (in g/kW•h) for EBDI ® 

# engine with EGR. (Beazley, 2010)BMEP - Observed [kPa]



# 0 500 1000 1500 2000 2500 3000

Engine Speed [rev/min] 1000 1500 2000 2500 3000 3500 4000 4500 5000 2 5 2 8 3

6 3 

# 230 450

400

350

300

260

250

245

240

230

220

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# To translate this to the 2020–2025 timeframe's EGR DI Turbo engine, the compression ratio

was increased to 10.5:1, which improves the f uel consumption by approximately 1% across the

map. The EGR DI Turbo engine also assumes use of an advanced boost system as described

in Section 4.1.3 instead of a single-stage system. Switching from the current valvetrain to the

CPS system described in Section 4.1.1.1 will provide up to 7% improvements in the steadystate fueling map, with the best benefits coming at moderate load and low speed as shown in

Figure 4.2. Lastly, a fuel consumption improvement of 3.5% was applied to account for

continued application of friction reduction technologies. The final fueling map used in the study

for the EGR DI Turbo engine is the result of sy nthesizing these technology improvements into a

cohesive whole.

4.2.6.2 Contemporary to Future Atkinson

In the case of the Atkinson cycle engines, th e program team started with a contemporary

example of the class of engine and translated it into the future by applying technology

improvements to an existing fueling map. These technology improvements include those

described in Section 4.1.1, Advanced Valvetrains, and Section 4.1.4, Other Engine

Technologies.

F11 

# Figure 4.10: BSFC map (in g/kW•h) for Toyota Prius engine. (Muta, et al ., 2004)

An example of a contemporary Atkinson cycle engine is the Toyota Prius engine as presented

by Muta, et al . (2004), which uses the fueling map shown in Figure 4.10. To translate the current

map to the study timeframe, several adjustments were made to the fueling map. First, the

engine speed range was modified so that the engine would tend to operate at lower speeds,

which reduces frictional losses in the engine. A dditional friction reduction improvements, such

as those described in Section 4.1.4, Other Engine Technologies, were also applied to the map.

Furthermore, the Atkinson engines in the design space can use either of the advanced

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# valvetrains, the CPS or DVA, which provides additional benefits to fuel consumption at part-load

conditions, especially at lower engine speeds as described in Section 4.1.1 and shown in

Figures 4.2 and 4.4.

These technologies together have the net effect of improving the best BSFC by about 5%, but

more importantly, of substantially improving fu el consumption across the map, especially at

lower-speed and moderate load operating conditions.

4.3 Hybrid Technologies

The selection of hybrid technology for a vehicle is complex, comprising a series of engineering

trade-offs between fuel consumption benefit and sy stem complexity and cost. As the market

share of hybrid vehicles continues to gr ow, consumers will have a range of choices.

A wide range of hybrid configurations were considered in the initial part of the program, with the

program studying three main approaches: micro hybrid (stop-start), P2 parallel, and Input

Powersplit. For this study, it was assumed that the hybrid powertrain configurations will be

studied in all but the LHDT vehicle class as shown in Table 5.2. The implementation of these

hybrid systems into the vehicle m odels is described in Section 6.8.

4.3.1 Micro Hybrid: Stop-Start

The most basic hybridization method shuts off the engine during idle periods, and typically uses

an enhanced starter motor and limited use of driver comfort features during engine off, such as

the radio and some heat but not air conditioning. This approach reduces fuel use over city drive

cycles by minimizing idling, but provides no benef it for highway driving or when air conditioning

is requested.

The stop-start, micro hybrid approach is the lowest -cost hybrid system, and can be implemented

relatively quickly on most vehicles on the market today. Stop-start systems are already in

production and the technology is maturing. Further development will lead to increased user

acceptance, for example, through transparent integration with low impact on vehicle

performance or noise, vibration, and harshness (NVH) and by implementing new technologies

to mitigate the effects on cabin cooling (Weissier, 2011).

The program team has assumed that by the 2020–2025 timeframe, all vehicles with an

otherwise conventional powertrain will have stop-s tart functionality implemented. For the vehicle

models in this study, the starter motor does not provide motive power, but is capable of

recovering enough energy to offset accessory loads.

4.3.2 P2 Parallel Hybrid

The P2 Parallel Hybrid powertrain places an electric machine on the transmission input,

downstream of the engine clutch. This system allo ws stop-start, electrical launch, launch assist,

and regenerative braking functionality. The clutch also allows the engine to be decoupled from

the rear of the driveline, allowing pure elec tric propulsion, or electric vehicle (EV) mode

operation. This wide application of electrical power in a variety of vehicle operating conditions

facilitates downsizing the engine from that in the comparable conventional vehicle.

This hybrid powertrain is expected to significant ly reduce GHG emissions, especially during city

driving. Highway driving fuel consumption is expected to improve because the electric machine

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# in the P2 hybrid allows a smaller, more efficient internal combustion engine to be used. This

smaller engine, however, may limit vehicle performance in situations requiring continuous

engine power, such as a sustained hill climb.

P2 Parallel hybrids are in limited production curr ently, including such vehicles as the Hyundai

Sonata, the Porsche Cayenne, and the Volkswagen Touareg. Prototypes have also been built

by various companies using existing off-the-shelf components.

A P2 Parallel Hybrid system can be used with an automatic transmission, automated manual

transmission (AMT), continuously variable trans mission (CVT), or dual clutch transmission

(DCT). Hellenbroich and Rosenburg (2009) describe a P2 variant with AMT, for example. For

this program, the P2 Parallel Hybrid powertrain was modeled using the DCT, which has fixed

gear ratios and no torque converter, as described in Section 4.4.2.

4.3.3 Input Powersplit

The simplest Powersplit hybrid configuration replaces the vehicle’s transmission with a single

planetary gearset and two electrical machines connected to the planetary gearset. The

planetary gearset splits engine power between the mechanical path and the electrical path to

achieve a continuously variable transmission. In some Input Powersplit configurations, a second

planetary gearset is used to speed up one of the electrical machines while retaining the CVT

functionality. The Toyota Prius and the Ford Hybrid Escape are two examples of Input

Powersplit hybrid vehicles currently sold in the US.

With the appropriate electric accessories, the Input Powersplit system allows for EV mode

operation, as well as stop-start operation, electric launch, launch assist, and regenerative

braking. In addition, the system allows for engine downsizing to help reduce fuel consumption,

although the smaller engine may limit vehicle performance in situations requiring continuous

engine power, such as a sustained hill climb. The Powersplit system provides significant

improvements in fuel consumption in city driving. During highway cycles, the benefits of

regenerative braking and engine start-stop are reduced, although the CVT feature of the engine

helps during the highway cycle as the engine is kept at an efficient operating point.

4.4 Transmission Technologies

The U.S. vehicle market is currently dominated by automatic transmissions, with a development

emphasis on increasing the launch-assist devic e efficiency and on increasing the number of

gear ratios to keep the engine operating in regions of high efficiency. Nevertheless, dual clutch

transmissions (DCT) are expected to be adopted over the next 10 to 15 years because of their

potential to further improve fuel economy and ma intain drivability. CVTs tend to have higher

friction than DCTs and provide a different driving experience than stepped transmissions.

Although CVTs are a current production technology, CVTs were not included in the scope of this

study. The baseline 6-speed transmissions used the same gear ratios as the previous fuel

economy study by Ricardo and PQA, (2008) to maintain continuity between improvement

projections. The 6-speed ratios have a total ratio span of 6.05 which is typical of current 6-speed

transmissions that were designed for fuel ec onomy and performance improvements over their 4-

speed or 5-speed predecessors. The 8-speed ratios offer a first gear ratio that has improved

launch torque multiplication over the 6-speed and two overdrive ratios that provide lower engine

rpm than the 6-speed ratios. The gear step progression of the 8-speed transmission is similar to

current production and provides acceptable drivability, and is shown in Table 6.3.

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# The development of DCT technology is expect ed to be implemented in the U.S. based on

experience with European and Japanese applications. Some vehicles with DCTs are entering

volume production, such as the Ford Fiesta, Ford Focus, and VW Passat. Automatic

transmissions too are still being developed and refined, with new technologies being

implemented in luxury vehicles, and then casc aded down to other vehicle classes. Given that

94% of current U.S. transmissions are automatics, efficiency improvements that mitigate GHG

emissions are expected to come from the following:

 Increased gear count from 4–6 currently to 7 or 8 by 2020–2025

 Improved kinematic design

 Component efficiency improvement or alternative technologies

 Launch devices

 Dry sump technology

The various base transmission technologies are described, followed by launch device options,

and, finally, other technologies expected to impr ove transmission efficiency. The effects of these

various technologies on transmission efficiency were incorporated into the models as described

in Section 6.4, Transmission Models.

4.4.1 Automatic Transmission

The automatic transmission is hydraulically oper ated, and uses a fluid coupling or torque

converter and a set of gearsets to provide a range of gear ratios. Viscous losses in the torque

converter decrease the efficiency of the automatic transmission. For the study timeframe, it was

assumed that eight-speed automatic transmissions will be in common use, as this supports

more efficient operation. The Small Car is an exception, and was assumed to only have enough

package space to support a six-speed transmission. For the 2020–2025 timeframe, losses in

advanced automatic transmissions are expected to be about 20–33% lower than the losses in

current automatic transmissions from the application of the specific technologies described in

Section 4.4. The overall benefits are compiled from Ricardo's confidential business information

on transmission systems. Additional benefits will be realized by having more gear ratios

available to help maintain the engine near its best operating condition.

4.4.2 Dual Clutch Transmission (DCT)

The DCT has two separate gearsets operating in tandem, one with even gears and the other,

odd. As the gear changes, one clutch engages as the other disengages, thereby reducing

torque interrupt and improving shift quality, making it more like an automatic transmission. The

DCT, however, does not require a torque converte r which improves its efficiency compared to

an automatic transmission, and may use either wet or dry type launch clutches. For the study

timeframe, energy losses in both wet clutch and dry clutch DCTs are expected to be 40–50%

lower than in current automatic transmissions. Additional benefits will be realized by having

more gear ratios available to help keep the engine near its best operating condition. As with the

automatic transmission, the Small Car was assumed to only have package space for a sixspeed transmission. An overall comparison of the efficiency of the stepped-gear transmissions

is shown in Figure 4.11.

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# Figure 4.11: Comparison of Automatic and DCT Transmission Efficiencies

4.4.3 Launch Device: Wet Clutch

A wet clutch provides torque transmission during operation by means of friction action between

surfaces wetted by a lubricant. The lubricant is required for cooling during gear shifts when the

clutch is slipping in larger LDV classes. Wet clutch DCTs provide added durability for the higher

torque requirements of larger LDVs, although a secondary lubrication system is needed for the

actuation requirements. As a result, wet clutch systems are expected to be heavier, cost more,

and be less efficient than dry clutch systems. An example of a wet clutch DCT system is shown

in Figure 4.12.

By the 2020–2025 timeframe, wet clutch DCTs ar e expected to develop into so-called damp

clutch DCTs, which approach the efficiency of a dry clutch with the longevity and higher torque

capacity of a wet clutch. In damp clutch DCTs, a limited spray is applied to cool the clutch

materials. A damp clutch requires a lubrication system but is more efficient due to improved

control, leading to reduced windage and churning losses.

4.4.4 Launch Device: Dry Clutch Advancements

The standard dry clutch requires advanced materials to dissipate heat and prevent slipping. The

thermal load resulting from engagement prevents dry clutches from being used in high torque

and heavy duty cycle applications, even though they are more efficient since they significantly

reduce parasitic shear fluid losses and do not require an additional lubrication system. The GHG

emissions benefit of a dry clutch over a wet clutch should be realized at launch and during

transient driving, thus primarily for city drivi ng. Advancements in materials or electric assist

could enable this technology to be used in larger LDVs and more severe duty cycles by the

study timeframe, but is generally assumed to be prevalent in the smaller vehicle classes.

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# Figure 4.12: Typical transverse wet clutch DCT arrangement. (Ricardo and PQA, 2008)

4.4.5 Launch Device: Multi-Damper Torque Converter

Dampers added to the torque converter enable a lower lockup speed, therefore decreasing the

more fuel-intensive period of hydrodynamic power transfer. Multi-dam per systems provide

earlier torque converter clutch engagement; how ever, drivability and limited ratio coverage have

limited the deployment of this technology to date. The technology must be integrated during

transmission design. The GHG emissions benefit should come from reduced slippage and

smoother shifting.

4.4.6 Shifting Clutch Technology

Shift clutch technology improves the thermal capac ity of the shifting clutch to reduce plate count

and lower clutch losses during shifting. Reducing the number of plates for the shifting process

and reducing the hydraulic cooling requirements will increase the overall transmission efficiency

for similar drivability characteristics. Tec hnology deployment has been limited by industry

prioritization of drivability over shift efficiency, especially since shift events are a very small

portion of typical driving. The technology will be best suited to smaller vehicle segments

because of reduced drivability expectations—this technology may not be suitable for higher

torque applications.

4.4.7 Improved Kinematic Design

Improved kinematic design uses analysis to impr ove the design for efficiency by selecting the

kinematic relationships that optimize the part operational speeds and torques. Large

improvements in efficiency have been noted fo r clean sheet designs for six-speed and eightspeed transmissions. This approach will provide a GHG emissions benefit across all vehicle

classes and operating conditions.

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# 4.4.8 Dry Sump

A dry sump lubrication system provides benefits by keeping the rotating members out of oil,

which reduces losses due to windage and churning. This approach will provide a GHG

emissions benefit across all vehicle classes, with the best benefits at higher speeds.

4.4.9 Efficient Components

Continuous improvement in seals, bearings and clutches aimed at reducing drag in the system

should provide GHG emissions benefits without compromising transmission performance.

4.4.10 Super Finishing

This technology approach chemical ly treats internal gearbox parts for improved surface finish.

The improved surface finish reduces drag which increases efficiency over the full range of

operation.

4.4.11 Lubrication

New developments in base oils and additive packages will reduce oil viscosity while maintaining

temperature requirements, thereby improving transmission efficiency over the full range of

operation.

4.5 Vehicle Technologies

Several vehicle technologies were also considered for the study to the extent that they help

support future ranges of vehicle mass, aerodynamic drag, and rolling resistance for each of the

vehicle classes in the study. The potential levels of improvement for these "road load reduction"

technologies were not explicitly quantified; rather, they were included as independent input

variables within the complex systems modeling approach.

Technologies considered include mass reduction through use of advanced materials with a

higher strength to mass ratio and through consolidation and optimization of components and

systems. Aerodynamic drag is expected to see improvements through adoption of both passive

and active aerodynamic features on vehicles in the 2020–2025 timeframe. Continued

improvement in tire design is expected to r educe rolling resistance and thereby provide a benefit

to fuel consumption.

In addition, vehicle accessory systems such as the cooling pumps and power steering systems

are expected to become electrified by the 2020–2025 timeframe. These electrified accessories

should reduce the power required to keep them active, which will also improve fuel

consumption, and are described in greater detail below.

4.5.1 Intelligent Cooling Systems

Intelligent cooling systems use an electric cool ant pump to circulate engine coolant, removing

the power required for this pump from the FEAD. Removing the coolant pump from the FEAD

also enables independent pump speed control. Rather than running at a fixed multiple of the

engine speed, the coolant pump can spin at the appropriate speed for the current cooling

requirements. Standard cooling systems are sized to provide cooling at maximum load and

ambient conditions, but most vehicles only rarely operate under these extreme conditions.

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# Intelligent cooling also enables quicker warm-up of the engine by controlling coolant flow. This

reduces engine friction by increasing engine te mperature during the warm up process. The

effects of the cooling system performance were integrated into the vehicle performance model.

Ricardo estimates this technology will lower f uel consumption over the FTP cycle. BMW is

implementing this technology on their twin-tur bo 3-L inline-6 cylinder engine, introduced in 2007

in their 335i model. This technology is projected to be readily available by the 2020–2025

timeframe.

4.5.2 Electric Power Assisted Steering

Electric Power Assisted Steering (EPAS) uses eit her rack or column-drive electric motors to

assist driver effort instead of a hydraulic pow er assist system. EPAS repl aces the engine-driven

hydraulic pump, hydraulic hoses, fluid reservoir, fl uid, and hydraulic rack. The efficiency of this

system is a result of reduced FEAD losses and improved energy management that comes from

decoupling the load from the engine. This technology is currently available for small and

medium sized passenger vehicles, and it is likely that this w ill be commercially available for

LDVs up to the LDT class by the 2020–2025 timefram e. This technology is required for vehicles

with any electrical launch or EV mobility, so that the vehicle can be steered during EV mode.

5. TECHNOLOGY BUNDLES AND SIMULATION MATRICES

The program team and EPA, with input from the Advisory Committee, bundled the technologies

described in Chapter 4, Technology Review, into a set of technology packages to be evaluated

in the seven LDV classes described in Section 2.2, Ground Rules for Study. These LDV classes

are Small Car, Standard Car, Small MPV, Full Size Car, Large MPV, LDT, and LHDT.

Engineering judgment was used to select technology combinations deemed most appropriate

for each vehicle class. For example, the larger LDV classes were assumed to have wet clutch

DCTs to accommodate the higher torques from their engines.

5.1 Technology Options Considered

Definitions of the hybrid powertrain, engine, and transmission technology packages are

presented in Tables 5.1–5.3. The engine technologies are defined in Table 5.1; hybrids, in Table

5.2; and transmissions, in Table 5.3. Many of the engines in Table 5.1 use some measure of

internal EGR, but for this table "Yes" means significant EGR flow through an external EGR

system. All of the advanced transmissions in Table 5.3 include the effects of the transmission

technologies described in Section 4.4, including dry sump, improved component efficiency,

improved kinematic design, super finish , and advanced driveline lubricants.

5.2 Vehicle configurations and technology combinations

Vehicles were assessed using three basic powertrain configurations: conventional stop-start, P2

hybrid, and Input Powersplit hybrid. Each vehi cle class considered in the study was modeled

with a set of technology options, as shown in Table 5.4 for the baseline and conventional

powertrains and Table 5.5 for the hybrid powertrains. Each of the 2020 engines marked for a

given vehicle class in Table 5.4 was paired with each of the advanced transmissions marked for

the same vehicle class. Tables 5.4 and 5.5 also show the ranges of the continuous

parameters—expressed as a percentage of the nominal value—used in the DoE study for the

conventional and hybrid powertrains, respectively. The ranges were kept purposely broad, to

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# cover the entire span of practical powertrain design options, with some added margin to allow a

full analysis of parametric trends.

T1 

# Table 5.1: Engine technology package definition.

T2 

# Table 5.2: Hybrid technology package definition.

Powertrain Configuration

Function 2010 Baseline Stop-Start P2 Parallel Powersplit

Engine idle-off No Yes Yes Yes

Launch assist No No Yes Yes

Regeneration No No Yes Yes

EV mode No No Yes Yes

CVT (Electronic) No No No Yes

Power steering Belt Electrical Electrical Electrical

Engine coolant pump Belt Belt Electrical Electrical

Air conditioning Belt Belt Electrical Electrical

Brake Standard Standard Blended Blended

T3 

# Table 5.3: Transmission technology package definition.

Transmission Launch Device Clutch

Baseline Automatic Torque Converter Hydraulic

Advanced Automatic Multidamper Control Hydraulic

Dry clutch DCT None Advanced Dry

Wet clutch DCT None Advanced Damp 

# EGR CPS DVA

2010 Baseline NA PFI No No No

Stoich DI Turbo Boost DI No Yes No

Lean-Stoich DI Turbo Boost DI No Yes No

EGR DI Turbo Boost DI Yes Yes No

Atkinson NA DI No Yes Yes

Diesel Boost DI Yes Yes No Engine Fuel

Injection Valvetrain Air

System

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# Table 5.4: Baseline and Conventional Stop-Start vehicle simulation matrix.

TT5 

# Table 5.5: P2 and Input Powersplit hybrid simulation matrix. Vehicle ClassStoich DI Turbowith CPSLean DI Turbowith CPSEGR DI Turbowith CPS2020 Diesel6-SpeedAutomatic6-Speed DryDCT8-SpeedAutomatic8-Speed DryDCT8-Speed WetDCT



# Small Car X X X X X X X

Standard Car X X X X X X

Small MPV X X X X X X

Full Size Car X X X X X X X

Large MPV X X X X X X X

LDT X X X X X X X

LHDT X X X X X X X X Advanced Engine Advanced TransmissionBaseline Engine &2010 6-SpeedAutomatic Trans.2010 Diesel & 20106-Speed AutomaticTransmission



# Parameter

Engine Displacement 50 125

Final Drive Ratio 75 125

Rolling Resistance 70 100

Aerodynamic Drag 70 100

Mass 60 120 DoE Range (%)

Vehicle ClassP2 Hybrid with2020 DCTInput PowersplitStoich DI Turbowith CPSLean DI Turbowith CPSEGR DI Turbowith CPSAtkinsonwith CPSAtkinsonwith DVA



# Small Car X X X X X X X

Standard Car X X X X X X X

Small MPV X X X X X X X

Full Size Car X X X X X X X

Large MPV X X X X X X X

LDT X X X X X X

LHDT Advanced Engine Hybrid Architecture



# Engine Displacement 50 150 50 125

Final Drive Ratio 75 125 75 125

Rolling Resistance 70 100 70 100

Aerodynamic Drag 70 100 70 100

Mass 60 120 60 120

Electric Machine Size 50 300 50 150 Powersplit P2 Hybrid DoE Range (%)

Parameter

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# 6. VEHICLE MODEL

Vehicle models were developed to explore the complete design space defined by the

technologies, vehicle classes, and powertrain architectures included for the 2020–2025

timeframe. The modeling process started by developing baseline models to compare against

data for current (2010) vehicles, as described in Section 6.1, Baseline Conventional Vehicle

Models, and Section 6.2, Baseline Hybrid Vehicle Models. Specific subsystems were also

implemented into the simulation package for the study, and these modeling activities are

described in Sections 6.3–6.8.

6.1 Baseline Conventional Vehicle Models

For each of the seven LDV classes considered in this project, vehicle models were developed

and correlated to a corresponding 2010 exemplar for each LDV class for the purposes of

establishing a comparison against known vehicle data. A detailed comparison between baseline

model results and vehicle test data were used to validate the models. These correlation models

were then modified to form the 2010 baseline m odels by converting all of them to use a 2010-

level six-speed automatic transmission and stop-start systems. These baseline models, while

representing an advance from current production v ehicles, provide a better basis for comparison

with the advanced LDVs for the 2020–2025 timeframe.

The starting point for the vehicle models was to us e the existing road-load coefficients from the

EPA Test Car List, which are represented as the target terms for the chassis dynamometer.

Known as target A-B-C terms, the coefficients were used to derive the physical properties of

rolling resistance, linear losses, and aerodynamic drag. These properties were then used in the

simulation to provide the appropriate load on the vehicle at any given speed.

A physics-based vehicle and powertr ain system model such as the one shown in Figure 6.1 was

developed and implemented in MSC.Easy5TM. MSC.Easy5TM is a commercially available

software package widely used in industry for vehi cle system analysis, which models the physics

in the vehicle powertrain during a drive cycle. Examples of vehicle performance simulation using

MSC.Easy5TM include work by Anderson, et al. (2005) and Fulem, et al. (2006), as well as the

previous EPA study for 2012–2016 LDV configurations (Ricardo and PQA, 2008). Torque

reactions are simulated from the engine through the transmission and driveline to the wheels.

The model reacts to simulated driver inputs to the accelerator or brake pedals, thus enabling the

actual vehicle acceleration to be determined based on a realistic control strategy. The model is

divided into a number of subsystem models. Wi thin each subsystem the model determines key

component outputs such as torque, speeds, and heat rejection, and from these outputs,

appropriate subsystem efficiencies can be calculated or reviewed as part of a quality audit.

The seven vehicle classes considered in this study are shown in Table 6.1, along with the

baseline vehicles for each class. Each of the baseline exemplar vehicle models had vehiclespecific vehicle, engine, and transmission model parameters. The models were exercised over

the FTP75 and HWFET fuel economy drive cycles, and the results compared with the EPA

Vehicle Certification Database (Test Car List) fuel economy data for each of the baseline

exemplar vehicles.

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# Figure 6.1: MSC.Easy5 conventional vehicle model.

T6 

# Table 6.1: Vehicle classes and baseline exemplar vehicles.

Vehicle Class Baseline Exemplar

Small car Toyota Yaris

Standard car Toyota Camry

Small MPV Saturn Vue

Full sized car Chrysler 300

Large MPV Dodge Grand Caravan

LDT Ford F150

LHDT Chevy Silverado 3500HD

6.2 Baseline Hybrid Vehicle Models

For each hybrid technology, Ricardo developed a base line model to calibrate the hybrid control

strategy and vehicle, engine, and driveline param eters. As with the conventional vehicles

described in Section 6.1, a full physical model of each baseline hybrid vehicle was developed

and implemented in MSC.Easy5TM. The hybrid contro l algorithms are also implemented in the

respective MSC.Easy5TM models. The vehicles we re modeled using published information from

various sources and Ricardo proprietary data.

6.3 Engine Models

The engines considered in the design space are defined by their torque curve, fueling map, and

other input parameters. For the 2010 baseline vehicles, the engine fueling maps and related

parameters were developed for each specific base line exemplar vehicle. For the engines used

in the 2020–2025 vehicles, reference engine models were developed, which were then scaled

to each of the LDV classes.

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# As described in Section 4.2, Engine Configurations, and illustrated in Section 4.2.6, Fueling Map

Development Examples, the program team used two methods to develop the engine models for

the 2020–2025 timeframe. The first was to look at the reported performance of current research

engines, and translate these to the production engines of the 2020–2025 timeframe. With this

method, current research engines would be refined to meet production standards, including

manufacturability, cost, and durability. The second method was to start from current production

engines and then determine a pathway of tec hnology improvements ov er the next 10–15 years

that would lead to an appropriate engine configuration for the 2020–2025 timeframe.

The fueling maps and other engine model parameters used in the study were based on

published data and Ricardo proprietary data. These initial maps were then developed into a

map reflecting the effects on overall engine performance of the combination of the future

technologies considered. Specifically, the effects of the valve actuation system, fueling system,

anti-knock calibration, and boost system were integrated into the final torque curves and fueling

maps, therefore subsystem performance maps, such as turbine and compressor efficiency

maps, are not relevant to this study.

Each proposed map was then reviewed and approved by EPA and the Advisory Committee.

This process was repeated for each of the engine technologies included in the simulation

matrix, as shown in Tables 5.4 and 5.5 for conventional stop-start and hybrid powertrain

configurations, respectively.

Engine downsizing effects were captured using a standard engineering method, by changing

the engine displacement in the given vehicle. This approach assumes that the downsized

engines have the same brake mean effective pressure (BMEP), which scales the engine's

delivered torque by the engine swept volume, or displacement. The BSFC of the scaled engine

map is also adjusted by a factor that accounts for the change in heat loss that comes with

decreasing the cylinder volume, and thereby increasing the surface to volume ratio of the

cylinder. These adjustment factors are plotted in Figure 6.2, and are drawn from Ricardo

proprietary data on the effect of displacement on BSFC. The minimum number of cylinders in an

engine was set to three, and the minimum per-cylinder volume, to 0.225 liters. These

constraints then set the minimum engine displacement in the design space to 0.675 liters.

Engine efficiency is therefore function of engine speed and BMEP, with specific fueling rates

(mass per unit time) calculated from the torque. Thus, downsizing the engine directly scales the

delivered torque, and the fueling map is adjusted accordingly. The engine speed range was held

constant over the engine displacement ranges of interest.

Turbo lag was represented in the model by applying a first order transfer function between the

driver power command and the supplied engine power at a given speed. This transfer function

was only used during the performance cycle, which is a hard acceleration from a full stop used

to assess vehicle acceleration performance. The transfer function approximates the torque rise

rate expected in the engines with turbocharger systems during vehicle launch. Adjusting the

time constant in the transfer function allowed the acceleration performance to see the effect of

turbo lag. A time constant of 1.5 seconds was selected to represent the expected delay in

torque rise on the advanced, boosted engines from the spool up of the turbine. Referring back

to the General Motors 2.0- l SIDI engine, turbo transient performance is also characterized by



# Schmuck-Soldan, et al. (2011 ), as shown in Figure 4.5. The transient response depicted here

is in line with the representation used in this study. EPA also reviewed its own engine

development data and corroborated the 1.5 second time constant.

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# Figure 6.2: Change in BSFC resulting from cylinder heat loss.

6.3.1 Warm-up Methodology

A consistent warm-up modeling methodology was developed for the study to account for the

benefits of an electrical water pump and of warm restart for the advanced vehicles. To account

for engine warm-up effects, Ricardo used company proprietary data to develop an engine warmup profile. This engine warm-up profile is used to increase the fueling requirements during the

cold start portion of the FTP75 drive cycle. This correction factor for increased fueling

requirements is applied to the fuel flow calcul ated during the warm-up period in the FTP75 drive

cycle. Section 6.7 provides additional details on how this correction factor was modeled.

6.3.2 Accessories Models

Parasitic loads from the alternator were assumed constant over the drive cycles and were

included in the engine model. Alternator efficiency was assumed to be 55% for baseline vehicle

simulations. Ricardo suggested a 70% efficient alternator in all of the advanced technology

package simulations to represent future altern ator design improvements. EPA agreed that this

assumption was consistent with confidential industry projections.

Power-assisted steering (PAS) systems—full electr ic or electric hydraulic—were modeled as

being independent of engine speed and were included in the engine model for each baseline

vehicle. The EPAS systems assu med no engine parasitic loads on the EPA drive cycles and

acceleration performance cycles, which requi re no steering input. All advanced package

simulations included the benefit of EPAS. The LHDT and LDT classes used electric hydraulic

PAS, whereas the five smaller vehicl e classes used full electric PAS. 

# 250 300 350 400 450 500 550 600 650BSFC change (%)



# Volume per cylinder SI Engine

CI Engine



# 0

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# The LDT and LHDT models also include engine parasitic losses due to a belt-driven engine

cooling fan. The other vehicles were assumed to have electric radiator fans, with the load being

drive cycle dependent and added to the vehicle’s bas e electrical load. These accessory loads

are shown in Tables 6.3 and 6.4.

T7 

# Table 6.3: Accessory loads for conventional stop-start and P2 hybrids.

T8 

# Table 6.4: Mechanical cooling fan loads for LDT and LHDT.

Current production cars have begun incorporating advanced alternator control to capture

braking energy through electrical power generation. This is done by running the alternator near

or at full capacity to apply more load on the engine when the driver demands vehicle

deceleration. It is believed that this feature will be widespread in the near future and, hence, the

study captures it by incorporating this function into the Conventional Stop-Start model. As in the

earlier study (Ricardo and PQA, 2008), the alternator efficiency was increased to 70% to reflect

an improved efficiency design for 2020 vehicle configurations. The advanced alternator control

strategy monitors vehicle brake events and captur es braking energy when available. The control

strategy also limits the maximum power capture to 2800 Watts based on the assumption that

the advanced alternator is limited to 200 Amps at 14 Volts charging for a standard (12V)

advanced glass-mat battery. By integrating power , energy is accumulated from every brake

event and when there is available "stored" brak e energy, the control strategy switches the

parasitic draw from the engine to the battery until the accrued energy is consumed, at which

point the load switches back to the engine. For the five smaller LDV classes, both the fan and

base electrical loads are included in the advanced charging system as electric fans are

employed. The system will only benefit the two truck classes, LDT and LHDT, in terms of base

electrical load as these vehicle classes use mechanical fans. 

# Base FTP

cooling fan HWFET

cooling fan Base FTP

cooling fan HWFET

cooling fan

Small car 153 127 280 84 70 154

Standard car 153 127 280 84 70 154

Small MPV 153 127 280 84 70 154

Full sized car 153 127 280 84 70 154

Large MPV 153 127 280 84 70 154

LDT 153 * * 84 * *

LHDT 153 ** ** — — — Vehicle Class Conventional Accessories (W) P2 Hybrid Accessories (W)



# *LDT **LHDT

500 242 290

1000 500 600

2000 1058 1270

2500 1323 1588

6200 3550 4260 Cooling Fan (W) Engine

Speed (rpm)

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# 6.4 Transmission Models

The transmission models use a simplified efficienc y curve, where the gearbox efficiency is a

function of gear ratio, as shown in Figure 4.11. Efficiencies for each gear ratio were calculated

based on data from several transmission and final drive gear tests, were averaged over the

expected speed and load ranges for the transmission in a given gear, and incorporate hydraulic

pumping losses. Transmission efficiencies were calculated to represent the average of the

leading edge for today’s industry and not one particular manufacturer’s design.

Different efficiency curves were mapped for planetary, automatics, and dual-clutch, with the

DCT efficiency modified depending on whether a dry or wet clutch is used. Advanced automatic

transmission designs are projected to reduce losses by 20–33% from current automatic

transmissions. In addition, the advanced aut omatic transmissions use advanced torque

converters, described below in Section 6.5. Wet clutch DCT efficiencies are also projected to

approach current dry clutch DCT efficiencies.

The gear ratios chosen for the six and eight speed advanced transmission are taken from

current production values for gear ratios. These are shown below in Table 6.5. Moreover,

transmission inertias were adapted from Ricardo proprietary data on contemporary

transmissions and reflect the effects of the technologies described in Sections 4.4.6–4.4.11.

T9 

# Table 6.5: Transmission gear ratios for six-speed and eight-speed transmissions.

In anticipation of future technology packages, it is expected that some advanced level of

transmission shift optimization will be implemented in year 2020–2025 vehicles. For the 2020–

2025 Conventional Stop-Start architecture, an advanced transmission controller was

implemented to determine the most favorable gear for a given driver input and vehicle road

load. This approach takes the place of predefined calibration shift maps based on throttle and

vehicle speed.

The advanced transmission shift optimization strategy tries to keep the engine operating near its

most efficient point for a given power demand. In this way, the new shift controller emulates a

traditional CVT by selecting the best gear ratio for fuel economy at a given required vehicle

power level. In conjunction, gear efficiency of the desired gear is also taken into account. More

often than not, the optimal gear ratio will be in between two of the fixed ratios, and the shift

optimizer will then decide when to shift up or down based on a tunable shift setting. This will

enable the shift optimizer to make proper shift decisions based on the type of vehicle and the

desired aggressiveness of the shift pattern. To protect against operating conditions out of

normal range, several key parameters were identified, such as maximum engine speed,

minimum lugging speed, and minimum delay between shifts. For automatic transmissions, the 8 Spd Advanced 6 Spd Baseline

1 4.700 4.148

2 3.130 2.370

3 2.100 1.556

4 1.670 1.155

5 1.290 0.859

6 1.000 0.686

7 0.840

8 0.670 

# Gear Ratio

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# torque converter is also controlled by the shift optimizer, with full lockup only achievable when

the transmission is not in first gear. Shift time for all transmissions was kept constant at 0.7

second duration as the sensitivity of this parameter was not enough to alter fuel economy

predictions over the EPA drive cycles. Furthermore, torque interrupt during shift is handled

automatically by the MSC.Easy5TM model com ponent. During development of this strategy, it

was noted that fuel economy benefits of up to 5% can be obtained when compared to traditional

shift maps. Figure 6.4 compares the desired gear ratio from a CVT and the comparable DCT

fixed gear ratio selected by the shift optimizer strategy.

F16 

# Figure 6.4: Comparison of CVT and optimized DCT gear ratios over drive cycle.

Analysis of the optimized shift strategy model output data shows no evidence to suggest an

increase in shift busyness compared to a baseline transmission shift strategy for a given

gearset. Figure 6.5 shows transmission gear plotted over time for a section of the FTP drive

cycle for the 2020 Small Car with 6-speed automatic transmission (and stoichiometric DI turbo

engine) nominal run with optimized shifting, compared to the 2010 Small Car baseline. For the

complete FTP cycle, the baseline vehicle shifted a total of 238 times, whereas the 2020 vehicle

with optimized shifting strategy shifted 228 times—in this case, leading to a decrease in shift

busyness. CVT DCT (shift optimizer)

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# Figure 6.5: Comparison of shift activity for traditional and optimized shifting

strategies.

6.5 Torque Converter Models

Torque converter characteristics curves for torque ratio and K-factor were generated using

typical industry standards for efficiency. Each vehicle’s torque converter characteristics for

torque ratio and K-factor were tailored for the application based on Ricardo experience with

production systems. Impeller and turbine rotational inertias are also input to the model and were

estimated based upon Ricardo experience and benchmarking data. Vehicle simulations with

advanced automatic transmissions include a slight im provement in torque converter efficiency.

A lockup clutch model was used with all torque converters and was of sufficient capacity to

prevent clutch slip during all simulation condi tions. For the baseline models with six-speed

automatics, lockup was allowed in fourth, fifth, and sixth gears. During light throttle conditions a

minimum engine operating speed of 1400 rpm for I3 engines, 1300 rpm for I4 engines,

1200 rpm for V6 engines, and 1100 rpm for V8 engines with the converter clutch locked was

considered in developing the baseline lock/unlock maps. The advanced automatic transmission

applications allow torque converter lockup in any gear except first gear, up to sixth for the Small

Car or eighth for the other LDV classes. This aggressive lockup strategy minimizes losses in the

torque converter.

6.6 Final Drive Differential Model

Baseline final drive ratios were taken from published information and driveline efficiencies and

spin losses were estimated based upon Ricardo experience for typical industry differentials. The

spin losses of the 4-wheel-drive LDT and LHDT front axle and transfer case were included in

the model to capture the fuel economy and performance of the 4-wheel-drive powertrain

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# operating in 2-wheel-drive mode. This approach is similar to the EPA procedure for emissions

and fuel economy certification testing.

6.7 Driver Model

The vehicle model is forward facing and has a model for the driver. The driver model applies the

throttle or brake pedal as needed to meet the requi red speed defined by the vehicle drive cycle

within the allowed legislative error. This allows the modeling of the actual vehicle response to

meet the target drive cycle.

The driver model contains the drive cycle time/v elocity trace, controls the throttle and brake

functions, and maintains vehicle speed to the desired set point. Vehicle simulations for fuel

economy were conducted over the EPA FTP75 (city), HWFET (highway) and US06 drive cycles.

The FTP75 cycle consists of three "bags" for a total of 11.041 miles on the conventional

vehicles and an additional bag 4 on hybrid vehicles for a total of 14.9 miles. A ten minute

engine-off soak is performed between bags 2 and 3 (after 1372 seconds of testing). A bag 1

correction factor is applied to the simulated "hot" fuel economy result of the vehicles to

approximate warm-up conditions of increased engine and driveline friction and sub-optimal

combustion. The correction factor reduces the fuel economy results of the FTP75 bag 1 portion

of the drive cycle by 20% on the current bas eline vehicles and 10% on 2020–2025 vehicles that

take advantage of fast warm-up technologies.

6.8 Hybrid Models

The hybrid models include all of the conventi onal vehicle components with the addition or

replacement of components for electric motor-generators, high voltage battery, high voltage

battery controller/bus, transmission, regenerative braking and hybrid supervisory controller. Of

these, the critical systems for the model were the electric machines (motor-generators), power

electronics, and high-voltage battery system. For each of these systems, current, state of the art

technologies such as those described in Staunton, et al . (2006) or Burress, et al . (2008) were

adapted to an advanced, 2020–2025 version of the system.

Technology improvements applied included decreasing losses in the electric machine and

power electronics to represent continued improv ements in technology and implementation, so

that a contemporary motor-inverter efficiency map such as that shown in Figure 6.6 would end

up with higher peak efficiency and a broader island of good efficiency. There are several

potential sources of losses in both the inverter and the motor, and the program team assumed

each source would be improved somewhat, leading to an overall 10% reduction in losses in the

inverter and an overall 25% reduction in losses in the motor.

As for the battery pack, a ground rule of the study is that the battery pack would use a generic

lithium ion chemistry representative of what is expected to be in production by the 2020–2025

timeframe. The assumptions for this future class of batteries include a lower overall internal

resistance. Likewise, future hybrid vehicles ar e assumed to use 40% of the overall SOC range

of the pack, which will reduce the overall battery pack size for a given energy storage

requirement. The capacity of the battery packs in the model was assumed to be sufficiently

large that it did not limit the vehicle performance. The electric machines were swept over a

sufficiently large range such that the design space included configurations where 90% of the

mechanical braking energy on the US06 to be captured by the hybrid electrical system. The

electrical system architecture assumes a DC/DC converter between the battery pack and the

inverter, so the specific pack architecture and voltage are not relevant to the simulation.

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F18 

# Figure 6.6: 2007 Camry motor-inverter efficiency contour map. (Burress, et al. , 2008)

F19 

# Figure 6.7: High level state flow diagram for the hybrid control strategy.

In addition, a Ricardo proprietary methodology was used to identify the optimum boundaries of

fuel consumption for a given hybrid powertrain c onfiguration over the drive cycles of interest:

FTP, HWFET, and US06. The methodology used the drive cycle profile to identify the features

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# and thresholds of a control strategy that could pr ovide fuel consumption over the drive cycle that

approaches the boundary value. The result of this assessment enabled the development of a

robust energy management system to control power flow. The simulation results using the

hybrid controller were then compared against the offline strategy to ensure that the hybrid

controller in the models is obtaining the most out of the hybrid powertrain. Furthermore, the

control strategy was designed to allow for a wide range of input parameters while striving for the

most efficient operation modes. Figure 6.7 illustr ates the state flow diagram for the hybrid

control strategy used as the baseline for th e hybrid control algorithm implemented in

MSC.Easy5TM, as well as the state variables, driver inputs and system parameters that were

used to define the state transitions. There are six main operation state modes,

 Idle engine off mode: This mode will shut the engine off and set the throttle command to

zero.

 Electric vehicle mode: This mode will leav e the engine off and use the throttle command

from the driver to determine the torque command for the electrical machine.

 Engine-Vehicle synch mode: This mode will start the engine.

 Normal driving model: This mode determines the ratio of electrical machine and engine

power that will be transmitted to the wheel to achieve the desired demand.

 Idle mode: This mode starts the countdown for idle engine off mode.

 Regen mode: This mode determines if regenerative braking is possible and how much of the

requested brake torque will be assigned to foundation brakes and to the electrical machine.

The following inputs and variables or states should be defined and available within the controller

in order to full define the state transitions,

 Driver inputs: throttle and brake pedals

 Battery State of Charge (SOC)

 Vehicle speed

 Engine: power and speed

 Motor: max power, max torque, speed, and torque/power.

Because the design space encompasses a large range of engine displacement and motor sizes,

the input parameters were normalized to take into account these changes and automatically

adjust the controller thresholds to meet the new demands. Figure 6.8 depicts the engine

demand curve that targets high efficiency operation.

A key feature of the hybrid controller is that it used a hybrid load following and load averaging

strategy to help keep the engine on or near its line of best efficiency on the engine operating

map with some accommodation for the efficiency of the overall powertrain. If the engine is

required to be on during low-load conditions, the engine can be made to work harder and more

efficiently and store the excess energy in the battery. While there have been concerns about the

effectiveness of a load averaging strategy give n the roundtrip efficiency of energy storage and

retrieval, with the improvements expected in the 2020–2025 timeframe, the engine is likely to be

a critical factor in the balance of efficiency improvements. In the simulation environment, two

identical vehicles were analyzed, one with load averaging active and the other, not. The case

with load averaging showed a slight improvement in fuel consumption over the EPA drive

cycles. In other cases, the energy in the batte ry can be used to provide launch assist or EV

mode driving. All hybrid vehicle simulations we re repeated over the drive cycles until the change

in SOC from start to finish was within 1% of total capacity. Therefore, there is no net

accumulation or net depletion of energy in the battery, and the fuel consumption value reported

is an accurate measure of the effectiveness of technologies. Figure 6.9 shows the energy

supervisory strategy of the hybrid powertrains.

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# Figure 6.8: Best BSFC curve superimposed on fueling map.

F21 

# Figure 6.9: Hybrid powertrain energy supervisory strategy.

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# 7. MODEL VALIDATION RESULTS

Before executing the DoE simulation matrix, the vehicle models described in Chapter 6 were

validated. Baseline exemplar vehicles were modeled, and the simulation results compared

against publicly available data on vehicle performance, including acceleration times and fuel

economy. Details of the model validation process and results are presented below. In addition,

nominal runs were prepared for each major powertrain type to provide a reference point for the

input parameters against which to compare the full design space explored in the DoE simulation

matrix.

7.1 Validation Cases and 2010 Baseline Vehicle Models

Vehicle models were developed for a 2010 validation case for each of the seven LDV classes.

Each LDV class was assigned a representative exemplar vehicle for the purposes of

establishing a baseline against known vehicle data. Ricardo leveraged the peer-reviewed

validation baseline models from its 2008 study with PQA (now SRA) for the five LDV classes

from Standard Car through LDT to provide the validation case models, and to build new

validation case models for the Small Car and LHDT classes. The validation case models are

based on the corresponding exemplar vehicles list ed in Table 6.1, and therefore use automatic

transmissions and engines with comparable charac teristics, including number of gears, peak

torque, and displacement.

Vehicle performance simulation results for the validation case models are shown below in

Table 7.1, comparing the raw fuel economy re sults in the EPA Test Car List (EPA, 2010)

against the calculated results. In addition to the fuel economy tests, the launch performance

was also assessed for each of the exemplar vehicles, with particular attention paid to the 0–60

mph acceleration time, as this is readily avail able for validation. 0–60 mph acceleration times for

the exemplar models were within a few tenths of a second of published times for each vehicle.

Because production P2 hybrids were not available to provide data in 2010, no direct comparison

was made. Furthermore, any production hybrid vehicle will be optimized for a specific

combination of engine, electric machine, and battery, whereas this study used a generic but

effective controller that allowed the entire design space to be robustly simulated.

T10 

# Table 7.1: Validation vehicle fuel economy performance.

Following the model validation phase, 2010 baseline vehicles were established. Rather than

using the validation vehicles and corresponding fuel economy results, a new set of baseline

values were determined to facilitate a uniform comparison between the advanced (future)

concepts and today’s current technologies. These new reference 2010 baseline vehicles add an

efficient alternator and stop-start operation to a common 6-speed automatic transmission, and

retain the engine maps from the validation case models. Appendix 3 presents the 2010 baseline

model fuel economy and CO 2 

# output equivalents for all classes of vehicles considered in this FTP75 HWFET FTP75 HWFET FTP75 HWFET

Small car 2010 Toyota Yaris 37 48 37 48 -0.8% 0.2%

Standard car 2007 Toyota Camry 27 42 27 42 0.9% -1.0%

Small MPV 2008 Saturn Vue 24 37 25 36 3.9% -2.6%

Full sized car 2007Chrysler 300 21 34 22 33 3.7% -4.6%

Large MPV 2007 Dodge Grand Caravan 20 32 20 29 1.6% -9.1%

LDT 2007 Ford F150 16 23 15 23 -4.1% -0.4%

LHDT 2010 Chevy Silverado

3500HD (diesel) — — 13 21 — — Vehicle Class Baseline Exemplars EPA Test List (mpg) Difference (%) Simulation Results (mpg)

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# study. Note that the CO 2 

# equivalents used in these tabl es were provided by the EPA as

9,087 g/gal of fuel for gasoline and 10,097 g/gal for diesel.

7.2 Nominal Runs

Once the models were developed and validated, a series of nominal runs were prepared to

assess the accuracy and robustness of the model . For the conventional vehicles, the nominal

condition was calculated using the same vehicle parameter values, such as for mass and

aerodynamic drag, as the 2010 baseline vehicles . The advanced engine size was then adjusted

to match the baseline 0–60 mph acceleration time, thus defining the nominal displacement for

each advanced engine. In addition, the nominal condition includes use of a baseline six-speed

automatic transmission for all LDV classes and im plementation of stop-start technology. In this

way, the nominal condition is placed on a corner of the design space for each LDV class and

therefore, the nominal conditions serve as the reference point for the design space explored by

the DoE simulations.

For the Powersplit and P2 hybrids, the nomin al engine size was reduced by 20% from the

conventional nominal engine size to allow for motor assist to match the aforementioned 0–60

mph performance metric. The 20% engine displacement reduction for the Powersplit and P2

hybrids was determined using Ricardo's engineering judgment and an assessment of existing

hybridization strategy. The nominal electric ma chine size was then set so that the 0–60 mph

acceleration time was matched for the hybrid nominal cases.

It is not possible to provide validation examples of the nominal vehicle models as they represent

predicted 2020 technology. Also, separate models showing the incremental benefits of

individual technologies were not studied as steps to the overall advanced packages. However,

the program team reviewed detailed output data for over one hundred distinct variables at a 10

Hz sampling rate to confirm that all of the nominal runs reflected reasonable real-world vehicle

behavior. After the nominal runs passed these quality checks, Ricardo proceeded to the DoE

simulation phase of the project.

The full table of nominal runs results for the conventional stop-start, P2 hybrid, and Input

Powersplit hybrid vehicle combinations is in Appendix 5, and presents the key output factors

defined in Appendix 4. These summary results and the rest of the simulation output data were

used to assess the quality of the simulation results before executing the DoE simulation matrix,

for example, by assessing power flows to and from the battery over the drive cycle.

8. COMPLEX SYSTEMS MODEL VALIDATION

Complex systems modeling (CSM) is an objective, scientific approach for evaluating several

potential options or configurations for benefits rela tive to each other and to a baseline. For this

program, the CSM methodology was used to define the design space for LDVs in the 2020–

2025 timeframe, and then to effectively evaluate LDV performance over this large design space.

8.1 Evaluation of Design Space

The purpose of the DoE simulation matrix is to efficiently explore the potential design space for

LDVs in the 2020–2025 timeframe. The simulation matrix was designed to generate selected

performance results, such as fuel consumption or acceleration times, over selected drive cycles.

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# The DoE approach allows an efficient exploration of the design space while limiting the number

of runs needed to survey the design space.

For each discrete combination of vehicle class, powertrain architecture, engine, and

transmission in the design space, the continuous input variables, including applied road load

reductions, were varied over the ranges shown in Tables 8.1 and 8.2 for the conventional and

hybrid powertrains, respectively. These continuous input variable ranges are with respect to the

nominal value for each LDV class. In the analysis, continuous input variables are evaluated

using a combination of the design corner points in a two-level full factorial design and design

points within the space based on a Latin hypercube sampling methodology. Note that vehicle

mass is considered independently of the combination of discrete technologies; for example,

switching from an automatic transmission to a DCT does not automatically adjust the vehicle

mass in the simulation.

To size the electric machines, hybrid vehicle simulations were performed with the conventional

vehicle counterparts to assess the overall brak ing energy over the driv e cycles. This knowledge

was then applied to the hybrid models by sweepi ng the electric machine sizes over the ranges

shown in Table 8.2 until the overall regenerative energy equaled or exceeded 90% of the total

braking energy, excluding the innate vehicle road load losses.

T11 

# Table 8.1: Continuous input parameter sweep ranges with conventional powertrain.

T12 

# Table 8.2: Continuous input variable ranges for P2 and Powersplit hybrid powertrains.

Latin hypercube sampling is a statistical method originally developed by McKay et al. (1979),

used to generate a set of parameter values over a multidimensional parameter space. The

method randomly samples the multidimensional parameter space in a way that provides

comprehensive and relatively sparse coverage for best efficiency. It also allows one to efficiently

continue to fill the multidimensional parameter space by further random sampling. It provides

more flexibility than traditional multi-level factorial designs for assessing a large parametric

space with an efficient number of experiments.

The vehicle simulations were run in batches and the results were collected and processed.

Vehicle fuel economy and performance metrics were recorded as well as diagnostic variables 

# Parameter

Engine Displacement 50 125

Final Drive Ratio 75 125

Rolling Resistance 70 100

Aerodynamic Drag 70 100

Mass 60 120 DoE Range (%)

Engine Displacement 50 150 50 125

Final Drive Ratio 75 125 75 125

Rolling Resistance 70 100 70 100

Aerodynamic Drag 70 100 70 100

Mass 60 120 60 120

Electric Machine Size 50 300 50 150 Powersplit P2 Hybrid DoE Range (%)

Parameter

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# such as the total number of gear shifts and the distance traveled during the drive cycle. The

data were reviewed using a data mining tool and outliers were analyzed, and, as necessary,

debugged and re-run. This approach allowed issues to be detected and diagnosed very quickly

within a large amount of data. Once the data were reviewed and approved, response surface

models were generated.

8.2 Response Surface Modeling

Response surface models (RSM) were generated in the form of neural networks. The goal was

to achieve low residuals while not over-fitting the data. Initially, 66% of the data were used for

fitting the model while the remainder was used to validate the response surface model’s

prediction performance. Once a good fit was found, all the data were used to populate the RSM.

Each neural network fit contains all of the continuous and discrete variables used in the study

for a given transmission. One neural network fit per transmission was generated to improve the

quality of the fits.

9. RESULTS

The key project results consist of the raw data sets obtained from over 350,000 individual

vehicle simulation cases, the Data Visualization Tool developed to query the response surfaces

based upon the raw data sets, and this report describing these results. These key results are

discussed below. A separate User Guide for the Data Visualization Tool will be released with

the tool.

9.1 Basic Results of Simulation

Each of the simulation cases generated data at 10 Hz 2 

# which allowed evaluation of the

performance of a specific vehicle configuratio n in the design space over each of the drive

cycles. These results include parameters such as vehicle speed, calculated engine power, and

instantaneous fueling rate. The detailed data from each simulation run were then distilled into

the main output factors of interest, such as acceleration time and fuel economy, that were then

used in the parametric fit of the RSM.

For this study, the main output factors include raw fuel economy and GHG emissions over each

of the drive cycles studied and performance metr ics, such as 0–60 mph acceleration times. The

complete list of output factors is listed in Appendix 4.

9.2 Design Space Query

The Design Space Query within the Data Visualizati on Tool allows the user to assess a specific

vehicle configuration in the design space by selecting a platform, engine, and transmission and

then setting the continuous variables within the design space range. The generated

performance results are then reported in a table that is exportable to Excel. The user can

assess multiple vehicle configurations and compar e them in Excel. The tool table also allows

the user to apply spreadsheet formulas for quick, on-the-side computation. An example of the

Design Space Query is shown in Figure 9.1.

2 

# To maintain manageable file sizes at an adequate le vel of fidelity, EPA requested that output files be

generated at a 10 Hz sampling rate—far slower than the Easy5 process rate—for its own data quality

checks.

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# 9.3 Exploration of the Design Space

A more comprehensive survey of the design space can be conducted using the Design Space

Analysis in the Data Visualization Tool, which allows the user to assess the performance of

multiple vehicle configurations from a significant portion of the design space simultaneously.

Each design is generated by selecting a vehicle platform, engine, and transmission, and then by

selecting ranges for the continuous input variables. Figure 9.2 shows the screen where the

design space analysis is set up. For each of the continuous variables, values are generated

using a Monte Carlo analysis from a uniform distribution over the range selected.

Once generated, the results at the design points are stored and may be plotted to visualize the

effects of varying vehicle parameters over the design space. By carefully building a design and

varying the parameters, the user can gain an understanding of the effect of each technology

and the interactions between technologies. Figures 9.3–9.5 show examples of plots that

compare two design space analyses. In these cases, the red points are for a Full Size Car with

advanced diesel engine and dry-clutch DCT, whereas the blue points are for a Full Size Car

with stoichiometric DI turbo engine and automatic transmission. The black point is the 2010

baseline value. For these examples, the engine displacement was varied from 50% to 125% of

nominal, or 0.71 to 1.8 l displacement for the stoichiometric DI turbo engine and 1.4 to 3.6 l for

the diesel, and the vehicle mass, from 70% to 100% of nominal, or 2800 to 4000lb.

The example in Figure 9.6 compares various configurations of the Standard Car, all with the

EGR DI Turbo engine but with different powertrains. The two Conventional Stop-Start cases

have the advanced eight-speed automatic and dr y-clutch DCT, shown in blue and gray,

respectively. The Powersplit hybrid is shown in green, and the P2 Hybrid, in red. Again, the

black point is the 2010 baseline value. By contra st, the example in Figure 9.7 compares fuel

economy performance across all seven LDV cla sses. Here, each LDV class has had its engine

displacement and vehicle mass varied from the mi nimum to the maximum of the design space.

9.4 Identification and Use of the Efficient Frontier

Part of assessing the selected regions of the design space is to find configurations that balance

efficiency and performance. The Data Visualization Tool identifies an Efficient Frontier, which is

the bound of the sampled design space that has the most desirable performance. The user

must first define a dataset using the Design Space Query, described above in Section 9.2, and

then select the Efficient Frontier tab in the Data Visualization Tool. An example of the Efficient

Frontier screen is shown in Figure 9.8. The Efficient Frontier is marked out in red, and the user

can click on the data points along the frontier to discover the vehicle configurations that lie on

the frontier.

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# Figure 9.1: Design Space Query screen in Data Visualization Tool.

F23 

# Figure 9.2: Design Space Analysis screen in Data Visualization Tool.

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# Figure 9.3: Full Size Car Design Space Analysis example. Black point is 2010 baseline;

red points are for advanced diesel and dry-clutch DCT; blue points, Stoichiometric DI

Turbo with advanced automatic transmission.

F25 

# Figure 9.4: Full Size Car Design Space Analysis example. Black point is 2010 baseline;

red points are for advanced diesel and dry-clutch DCT; blue points, Stoichiometric DI

Turbo with advanced automatic transmission.

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# Figure 9.5: Full Size Car Design Space Analysis example. Black point is 2010 baseline;

red points are for advanced diesel and dry-clutch DCT; blue points, Stoichiometric DI

Turbo with advanced automatic transmission.

F27 

# Figure 9.6: Standard Car design space analysis example comparing powertrains with

EGR DI Turbo engine. Blue points are with advanced automatic; gray, dry-clutch DCT;

green, Powersplit; and red, P2 Hybrid. Black point is 2010 baseline.

0 5 10 15 20 25 30 35 40 45 50 55 60 65

0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0Combined FTP-HWFET (mpg)



# Engine Displacement (L) Baseline

Stoich DIT+8AT

Diesel+DCT

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# Figure 9.7: Full design space example showing all seven vehicle classes using

Stoichiometric DI Turbo engine and advanced automatic transmission with varying

vehicle mass and engine displacement.

F29 

# Figure 9.8: Efficient Frontier screen of Data Visualization Tool with example plot. 0 10 20 30 40 50 60 70

0 2000 4000 6000 8000 10000 12000Combined FTP-HWFET (mpg)



# Vehicle Mass (lb) Small Car

Standard Car

Small MPV

Full Size Car

Large MPV

Light Duty Truck

HLDT

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# 10. RECOMMENDATIONS FOR FURTHER WORK

Ricardo has the following recommendations for further work on this program:

 Thoroughly analyze and simulate turbo lag effects in the advanced, boosted engines

through engine performance simulation tied in with the vehicle models.

 Run the models over additional drive cycles , such as the NEDC, JC08, or the cold

ambient FTP, to understand how the technology packages may apply to other global

regions.

 Expand the design space to mix 2010 baseline engines and transmissions with the

advanced technologies to better understand the relative contributions of engine or

transmission technology to the performance of the advanced vehicles.

 Include additional engines with different technology packages, such as a version of the

Stoichiometric DI Turbo engine that has a single, fixed cam profile instead of using the

CPS valvetrain.

 Develop correlation models for the P2 and Input Powersplit hybrid powertrains to

establish a baseline within the simulated design space.

 Implement a Two-Mode Powersplit hybrid powertrain to assess the benefits of

hybridization in the larger LDV classes.

 Study the simulation results to understand main and interaction effects between

technologies.

11. CONCLUSIONS

The following conclusions are supported by this program's results:

 An independent, objective, and robust analytical study of the effectiveness of selected

LDV technologies expected to be prevalent in the 2020–2025 timeframe, and their

effects on vehicle performance has been completed.

 A comprehensive review process was completed to identify technologies likely to be

available in the 2020–2025 timeframe and to estimate their future performance given

current trends and expected developments.

 The vehicle performance models were based upon the underlying physics of the

technologies and have been validated with good result to available test data. Quality

assurance checks have been made throughout the study to ensure accuracy of the

trends in the results.

 The Data Visualization Tool allows EPA and other stakeholders to efficiently examine

the design space developed through the progr am's complex systems modeling approach

and to assess trade-offs between various vehi cle configurations and their performance.

The tool provides the necessary functionality to assess specific vehicle designs or more

comprehensively explore the design space.

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# 12. ACKNOWLEDGEMENTS

Ricardo wishes to acknowledge the contributions of the team that supported the technical work

through the course of the program, which included the following:

 David Boggs, Technical Specialist

 Paul Bosker, Program Manager

 Nick Bouhamdan, Program Manager

 Felipe Brandao, Technology Leader

 Anrico Casadei, Senior Project Engineer

 Mark Christie, Vice President of Engineering Operations

 Jennifer Durfy, Project Engineer and Subject Matter Expert

 Josef Fulem, Senior Fuel Cell Product Engineer

 Keith Gilbert, Project Engineer and Subject Matter Expert

 Daniel Gross, Project Engineer

 Tom Gutwald, Innovations Department Manager

 Stuart Horswill, Chief Engineer and Subject Matter Expert

 Henry Huang, Project Engineer

 Neville Jackson, Chief Technology and Innovations Officer

 Fred Jacquelin, Technical Specialist

 Carl Jenkins, Product Group Director

 Angela Johnson, Principal Engineer

 Neil Johnson, Project Engineer and Subject Matter Expert

 John Kasab, Chief Engineer

 Chris Mays, Project Director and Subject Matter Expert

 Shaun Mepham, Product Group Director

 Richard Osborne, Chief Engineer and Subject Matter Expert

 Pascal Reverault, Principal Engineer and Subject Matter Expert

 Cedric Rouaud, Chief Engineer and Subject Matter Expert

 Daniel Shepard, Associate Engineer

 John Stokes, Gasoline Technical Specialist and Subject Matter Expert

 Qiong Sun, Program Manager

 Wayne Thelen, Chief Engineer and Subject Matter Expert

 Marc Wiseman, Principal (Ricardo Strategic Consulting)

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# 13. REFERENCES

Anderson, S.R., D.M. Lamberson, T.J. Blohm, and W. Turner, 2005, "Hybrid route vehicle fuel

economy." SAE Technical Paper 2005-01-1164.

Beazley, R., 2010, "EBDI ® 

# – Application of a high BMEP downsized spark ignited engine".

Presented at 2010 DEER Conference, Detroit, Mich.

Biltgen, P., T. Ender, and D. Mavris, 2006, "Development of a collaborative capability-based

tradeoff environment for complex system architectures. 44 th 

# AIAA Aerospace Sciences Meeting

and Exhibit . AIAA Technical Paper 2006-728

Burress, T.A., C.L. Coomer, S.L. Campbell, L.E. Seiber, R.H. Staunton, and J.P. Cunningham,

2008, "Evaluation of the 2007 Toyota Camry Hybrid Synergy Drive System." ORNL technical

report TM-2007/190.

Coltman, D., J.W.G. Turner, R. Curtis, D. Blake, B. Holland, R.J. Pearson, A. Arden, and H.

Nuglisch, 2008, "Project Sabre: A close-spaced direct injection 3-cylinder engine with

synergistic technologies to achieve low CO 2 

# output." SAE Technical Paper 2008-01-0138.

Cruff, L., M. Kaiser, S. Krause, R. Harris, U. Krueger, M. Williams, 2010, "EBDI ® 

# – Application of

a fully flexible high BM EP downsized spark ignited engine." SAE Technical Paper 2010-01-

0587.

Environmental Protection Agency, 2010, "Test Car List Data Files", available from

www.epa.gov/oms/tcldata.htm.

Fiat Powertrain Technologies, S.p.A., 2009, "MultiAir: The ultimate air management strategy".

http://www.fptmultiair.com/flash_multiair_eng/home.htm

Fulem, J., J.J. Kasab, S. Russell, and C.J. Mitts, 2006, "Advanced computational tools for

systems engineering of fuel cell powertrains." Presented at Fuel Cell Seminar, Nov. 2006.

Hellenbroich, G., and V. Rosenburg, 2009, "FEV's new parallel hybrid transmission with single

dry clutch and electric torque support." Aachener Koloquium Fahrzeug- und Motorentechnik

2009 18 :1209–1222.

Hohenner, H., 2010, "Current trends on powertrain development – Downsizing and

downspeeding." 4 th 

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America, Jun 2010.

Honda Motor Company, 2011, "The VTEC breakthrough: Solving a century-old dilemma".

http://world.honda.com/automobile-technology/VTEC/

Kinnunen, M.J., 2006, Complexity Measures for System Architecture Models . Masters' thesis at

Massachusetts Institute of Technology.

Lumsden, G., D. OudeNijeweme, N. Fraser, and H. Blaxill, 2009, "Development of a

turbocharged direct injection downsizing demonstrator engine". SAE Technical Paper 2009-01-

1503.

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# Luskin, P., 2010, A Systems Engineering Methodology for Fuel Efficiency and its Application to

a Tactical Wheeled Vehicle Demonstrator . Masters' thesis at Massachusetts Institute of

Technology.

McCarthy, I.P., T. Rakotobe-Joel, and G. Frizelle, 2000, "Complex systems theory: Implications

and promises for manufacturing organizations." Int. J. Manufacturing Technology and

Management

, 2 (1-7): 559–579.

McKay, M.D.; Beckman, R.J.; Conover, W.J., 1979, "A comparison of three methods for

selecting values of input variables in the analysis of output from a computer code."

Technometrics 21 (2): 239–245.

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http://www.mscsoftware.com/Products/CAE-Tools/Easy5.aspx. Last accessed 12 Aug 2011

Muta, K., Y. Makoto, and J. Tokieda, 2004, "Development of new-generation hybrid system

THS II – Drastic improvement of power per formance and fuel economy." SAE Technical Paper

2004-01-0064.

Ricardo and PQA, 2008, A Study of Potential Effectiveness of Carbon Dioxide Reducing Vehicle

Technologies . EPA Report 420-R-08-004a.

Schaeffler Group, 2010, "Important Facts About UniAir/MultiAir".

http://www.ina.de/content.ina.de/en/press/pr ess-releases/press-details.jsp?id=3429505

Schmuck-Soldan, S., A. Königstein, and F. Westin, 2011, “Two-Stage Boosting of Spark Ignition

Engines.” Internationales Wiener Motorensymposium 2011 Europe S.r.l., Torino.

Shaw, J.R., 2009, “Testimony to Joint EPA/NHTSA Hearing on Proposed Rulemaking to

Establish Light Duty Vehicle Greenhouse Gas Emissions Standards and Corporate Average

Fuel Economy Standards”. Downloaded from www.autosteel.org last accessed 27 Oct 2009

Staunton, R.H., C.W. Ayers, L.D. Marlino, J.N. Chiasson, T.A., Burress, 2006, "Evaluation of

2004 Toyota Prius Hybrid Electric Drive Syst em". ORNL technical report TM-2006/423.

Turner, J.W.G., R.J. Pearson, R. Curtis, and B. Holland, 2009, "Sabre: A cost-effective engine

technology combination for high efficiency, high performance and low CO2 emissions." Low

Carbon Vehicles 2009: Institution of Mechanical Engineers (IMechE) conference proceedings.

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AEI, 5 July 2011 , pp. 10–12.

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# APPENDICES

Appendix 1, Abbreviations

AMT Automated manual transmission

ARB California Air Resources Board

BEV Battery electric vehicle

BMEP Brake mean effective pressure

BSFC Brake specific fuel consumption

CI Compression ignition

CPS Cam profile switching

CSM Complex systems modeling

CVT Continuously variable transmission

DCT Dual clutch transmission

DI Direct injection

DoE Design of experiments

DVA Digital valve actuation

EGR Exhaust gas recirculation

EPA United States Environmental

Protection Agency

EPAS Electric power assisted steering

EV Electric vehicle

FCEV Fuel cell electric vehicle

FEAD Front end accessory drive

FIE Fuel injection equipment

FMEP Friction mean effective pressure

GHG Greenhouse gas

ICCT International Council on Clean

Transportation

ICE Internal combustion engine

IMEP Indicated mean effective pressure

KERS Kinetic energy recovery system LDT Light-duty truck

LDV Light-duty vehicle

LEV Low emissions vehicle

LHDT Light heavy-duty truck

LNT Lean NOx trap

MPV Multi-purpose vehicle

NA Naturally aspirated

NMEP Net mean effective pressure

NOx Nitrogen oxides

NVH Noise, vibration, and harshness

OEM Original equipment manufacturer

ORNL Oak Ridge National Laboratory

OTAQ Office of Transportation and Air

Quality

PAS Power assisted steering

PFI Port fuel injection

PHEV Plug-in hybrid electric vehicle

PMEP Pumping mean effective pressure

PQA Perrin Quarles Associates

RSM Response surface model

SCR Selective catalytic reduction

SI Spark ignited

SME Subject matter expert

SOC State of charge

SULEV Super ultra low emissions vehicle

V2I Vehicle to infrastructure

V2V Vehicle to vehicle

VA Valve actuation

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# Appendix 2, Assessment of Technology Options

At the start of the program, Ricardo and EPA, with input from the Advisory Committee,

developed a comprehensive list of technology options for further consideration by Ricardo's

Subject Matter Experts. The technologies are listed below. The technologies considered further

for assessment are in the related document "Assessment of Technology Options" (Ricardo

reference RD.11/ 342305.1), included as Attachment A.

Engine technologies considered included the following:

 Engine downsizing

 Direct injection

 Turbocharging

 Valvetrain technologies and subsystems, including

o CPS valvetrains

o DVA or variable valve timing (VVT) valvetrains

 Stratified charge DI

 Homogeneous charge compression ignition (HCCI) or controlled auto-ignition (CAI)

combustion

 Exhaust energy recovery, including

o Mechanical turbo-compounding

o Electrical turbo-compounding

o Thermoelectric devices

 Second-generation biofuels

 Friction reduction technologies

 Closed-loop combustion control

 Adjustments to compression ratio

 Advanced boosting technologies

 Enhanced EGR and charge air cooling

 Pre-turbine catalysis

 Calibration optimization for low GHG emissions

 Narrow speed range operation

 Optimization of engines for use with hybrid powertrains

Engine configurations considered included the following:

 Stoichiometric DI turbocharged

 Lean DI turbocharged

 High-load EGR engines

 Multi-mode (2 stroke–4 stroke)

 Engines optimized for hybrid powertrains, including

o Stop-start powertrains

o Full hybrid powertrains

Hybrid powertrain technologies, including

 Micro hybrid or stop-start system

 Integrated belt starter-generator (BSG)

 Integrated crank starter-generator (ISG) or Integrated motor assist (IMA)

 P2 parallel hybrid powertrain

 Input Powersplit hybrid powertrain

 Two-mode Powersplit hybrid powertrain

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#  Series hybrid

 Parallel hydraulic hybrids

Transmission technologies, including

 Advanced automatic transmissions

 AMTs

 CVTs

 DCTs

 Launch devices

o Wet clutch

o Damp clutch

o Dry clutch

o Multi-damper torque converter

o Magnetic clutch

 Shifting clutch technology

 Smart kinematic design

 Dry sump

 Efficient components

 Super finishing

 Lubricant improvements

Vehicle technologies, including

 Mass reduction through use of

o Advanced high strength steels

o Aluminum alloys

o Magnesium alloys

o Plastics and fiber-reinforced composites

 Mass reduction through component optimization

 Passive and active aerodynamics improvements

 Active aerodynamics systems

 Thermoelectric generators

 HVAC system load reduction

 Tire rolling resistance

 Intelligent cooling systems

 Electric PAS

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# Appendix 3, Baseline Vehicle Parameters and Runs Results

T13 

# Table A3.1: Baseline Vehicle Parameters and Runs Results.Vehicle ClassRepresentativeVehicle EnginePeak TorqueOutput (N-m) Transmission ETW (lb) GCW (lb)OtherTechnologiesEPA City FE,CO2Equivalent(mpg,g/mile)EPA Highway FE,CO2Equivalent(mpg,g/mile)EPA Combined FE,CO2Equivalent(mpg,g/mile)Small Car Yaris1.5L I4 DOHC 4V 145 6 Speed Auto 2,625 N/A70% Eff. Alt w/Regen,Stop-Start39.8, 228.348.7, 186.643.4, 209.5Standard Car Camry2.4L I4 DOHC 4V 219 6 Speed Auto 3,625 N/A70% Eff. Alt w/Regen,Stop-Start30.0, 302.943.5, 208.934.9, 260.6Full Size Car 3003.5L V6 SOHC 4V 335 6 Speed Auto 4,000 N/A70% Eff. Alt w/Regen,Stop-Start23.8, 381.833.7, 269.627.4, 331.3Small MPV Vue2.4L I4 DOHC 4V 219 6 Speed Auto 4,000 N/A70% Eff. Alt w/Regen,Stop-Start27.0, 336.636.1, 251.730.5, 298.4Large MPV Caravan3.8L V6 OHV 2V 319 6 Speed Auto 4,250 N/A70% Eff. Alt w/Regen,Stop-Start22.0, 413.030.7, 296.025.2, 360.4Light-Duty Truck F1505.4L V8 SOHC 3V 495 6 Speed Auto 4,500 N/A70% Eff. Alt w/Regen,Stop-Start16.2, 560.922.6, 402.118.6, 489.4Light Heavy-Duty Truck 3500HD6.0L V8 OHV 2V 515 6 Speed Auto 6,000 15,80070% Eff. Alt w/Regen,Stop-Start11.2, 811.315.1, 601.812.7, 717.0Light Heavy-Duty Truck 3500HD6.6L V8 OHV 4v 895 6 Speed Auto 9,000 21,20070% Eff. Alt w/Regen,Stop-Start15.6, 647.219.0, 531.417.0, 595.1Baseline VehiclesVehicle Class Baseline Exemplars ETW (lb) Mass (kg) Cd·A (m2)Tire RRCoeffWheel velocitycoeff (N·s)Tire rollingradius (m)Wheel inertia(kg·m2)Roadload Powerat 50 mph (hp)Small car 2010 Toyota Yaris 2625 1191 0.736 0.0094 0.100 0.282 0.90 10.8Standard car 2007 Toyota Camry 3625 1644 0.690 0.0082 0.137 0.320 0.91 11.3Small MPV 2008 Saturn Vue 4000 1814 0.925 0.0069 0.400 0.340 0.97 15.1Full sized car 2007Chrysler 300 4000 1814 0.792 0.0113 0.205 0.342 0.97 14.8Large MPV 2007 Dodge Grand Caravan 4500 2041 0.952 0.0072 0.400 0.330 0.94 15.8LDT 2007 Ford F150 6000 2722 1.341 0.0081 0.580 0.382 1.00 22.9LHDT 2010 Chevy Silverado3500HD (diesel)9000 4082 1.394 0.0083 1.192 0.374 1.05 31.1

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# Appendix 4, Output Factors for Study

Raw fuel economy in miles per US gallon and GHG emissions in grams of CO 2 

# per mile over

 FTP75

 HWFET

 US06

 HWFET and FTP combined

Acceleration performance metrics, including

 0–10 mph acceleration time

 0–30 mph acceleration time

 0–50 mph acceleration time

 0–60 mph acceleration time

 0–70 mph acceleration time

 30–50 mph acceleration time

 50–70 mph acceleration time

 Top speed at 5% grade

 Top speed at 10% grade

 Velocity at 1.3 sec

 Velocity at 3.0 sec

 Distance at 1.3 sec

 Distance at 3.0 sec

 Maximum grade at 70 mph at GCW

 Maximum grade at 60 mph at GCVW (LDT and LHDT only)

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# Appendix 5, Nominal Runs Results

The table lists the baseline (2010) vehicles first, followed by results by vehicle class. The P2

Hybrids have an electric machine size listed, and all use the DCT. There were no Conventional

Stop-Start nominal runs that used the DCT. For the Input Powersplit hybrids, only the traction

motor size is listed, as the generator size is a function of the engine and traction motor sizes.

Abbreviations used exclusively in the following table of Nominal Runs Results include the

following:

Baseline The 2010 baseline engine for the given vehicle class

Stoich DIT Stoichiometric DI Turbo engine

Lean DIT Lean-Stoichiometric DI Turbo engine

EGR DIT EGR DI Turbo engine

Adv Diesel Advanced (2020) diesel

Atk CS Atkinson cycle engine with CPS

Atk DVA Atkinson cycle engine with DVA

AT6 Six-speed automatic transmission (baseline or advanced, as appropriate)

AT8 Eight-speed automatic transmission (advanced only)

DCT Dry or wet clutch DCT, per simulation matrix.

PS Powersplit planetary gearset

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# Table A5.1: Nominal Runs Results.EngineVehicle Class Type Displ (L) FTP75 HWFET US06 0-10mph 0-30mph 0-50mph 0-60mph 0-70mph 30-50mph 50-70mph 5% Grade 10% Grade 60 mph 70 mph 1.3 sec3 sec 1.3 sec 3 secSmall Car Baseline 1.5 145 — AT6 39.8 48.7 30.3 1.4 4.0 7.4 9.9 13.0 3.4 5.6 94.6 82.2 — 10 2.6 14.7 9.3 22.8Standard Car Baseline 2.4 219 — AT6 30.0 43.5 29.1 1.0 3.1 6.3 8.3 11.4 3.2 5.1 110.4 86.7 — 15 3.9 20.5 14.1 29.5Full Size Car Baseline 3.5 335 — AT6 23.8 33.7 23.6 1.2 3.2 6.1 7.7 9.5 2.9 3.4 127.5 99.6 — 33 3.2 19.3 12.0 29.2Small MPV Baseline 2.4 219 — AT6 27.0 36.1 24.1 1.1 3.4 6.8 9.0 12.6 3.4 5.8 97.9 85.1 — 13 3.3 18.4 12.5 26.9Large MPV Baseline 3.8 319 — AT6 22.0 30.7 21.0 1.1 2.9 6.1 8.6 11.5 3.2 5.4 95.7 82.2 — 16 3.4 20.4 12.9 31.2LDT Baseline 5.4 495 — AT6 16.2 22.6 15.1 1.1 3.1 6.0 8.2 10.8 2.9 4.8 101.4 88.3 20 — 3.4 19.9 12.6 29.8LHDT Base SI 6.0 515 — AT6 11.2 15.1 9.8 1.0 3.1 6.9 9.9 13.3 3.8 6.4 92.8 69.8 15 — 3.7 20.7 14.2 29.9LHDT Base Diesel 6.6 895 — AT6 15.6 19.0 12.3 1.0 3.0 6.7 9.4 13.1 3.7 6.4 99.3 79.3 17 — 4.0 21.3 14.7 30.4Small Car Stoich DIT 0.74 157 — AT6 53.2 55.1 32.4 1.5 4.0 7.4 10.0 13.1 3.4 5.7 96.2 79.3 — 14 2.4 14.1 8.8 22.3Small Car Lean DIT 0.74 157 — AT6 55.1 56.0 32.6 1.5 4.0 7.4 10.0 13.1 3.4 5.7 96.2 79.3 — 14 2.4 14.1 8.8 22.3Small Car EGR DIT 0.74 157 — AT6 55.1 57.4 33.9 1.5 4.0 7.4 10.0 13.1 3.4 5.7 96.2 79.3 — 14 2.4 14.1 8.8 22.3Small Car Adv Diesel 1.23 221 — AT6 55.8 59.4 41.5 1.23.7 7.3 9.8 13.2 3.6 5.9 94.0 76.0 — 13 3.2 16.8 10.9 25.1Small Car Atk CS 1.66 138 14 DCT6 70.8 59.0 38.1 1.4 3.7 7.5 10.0 13.6 3.8 6.1 85.4 62.1 — 8 2.5 15.5 9.8 24.4Small Car Atk DVA 1.66 138 14 DCT6 71.7 60.5 39.4 1.4 3.7 7.5 10.0 13.6 3.8 6.1 85.4 62.1 — 8 2.5 15.5 9.8 24.4Small Car Stoich DIT 0.59 124 14 DCT6 68.2 57.3 37.0 1.4 3.8 7.2 9.6 12.6 3.4 5.4 87.5 70.7 — 10 2.4 15.1 9.4 23.6Small Car Lean DIT 0.59 124 14 DCT6 68.4 57.7 37.3 1.4 3.8 7.2 9.6 12.6 3.4 5.4 87.5 70.7 — 10 2.4 15.1 9.4 23.6Small Car EGR DIT 0.59 124 14 DCT6 70.2 59.9 39.0 1.4 3.8 7.2 9.6 12.6 3.4 5.4 87.5 70.7 — 10 2.4 15.1 9.4 23.6Small Car Atk CS 1.66 138 40 PS 64.2 59.5 38.0 1.8 4.7 7.9 9.8 12.2 3.2 4.3 93.5 77.4 — 8 1.5 11.1 6.7 18.5Small Car Atk DVA 1.66 138 40 PS 67.3 60.0 39.0 1.8 4.7 7.9 9.8 12.1 3.2 4.2 93.5 77.9 — 8 1.5 11.1 6.7 18.5Small Car Stoich DIT 0.59 124 40 PS 64.7 57.2 35.2 1.9 4.8 8.2 10.4 13.1 3.4 4.9 89.5 71.3 — 8 1.5 10.8 6.5 18.1Small Car Lean DIT 0.59 124 40 PS 65.8 57.4 35.2 1.9 4.8 8.2 10.4 13.1 3.4 4.9 89.1 71.3 — 8 1.5 10.8 6.5 18.1Small Car EGR DIT 0.59 124 40 PS 67.7 60.1 36.7 1.9 4.8 8.2 10.4 13.1 3.4 4.9 89.1 71.3 — 8 1.5 10.8 6.5 18.1Standard Car Stoich DIT 1.04 220 — AT8 44.8 54.5 32.5 1.0 3.1 6.2 8.5 11.4 3.1 5.2 107.7 86.2 — 15 3.7 20.7 14.0 29.7Standard Car Lean DIT 1.04 220 — AT8 46.6 55.5 32.8 1.0 3.1 6.2 8.5 11.4 3.1 5.2 107.7 86.2 — 15 3.7 20.7 14.0 29.7Standard Car EGR DIT 1.04 220 — AT8 46.4 56.7 34.0 1.0 3.1 6.2 8.5 11.4 3.1 5.2 107.7 86.2 — 15 3.7 20.7 14.0 29.7Standard Car Atk CS 2.40 200 24 DCT8 64.6 59.7 39.8 1.2 3.4 6.5 8.6 11.4 3.1 4.9 101.3 78.4 — 11 2.8 17.4 11.0 27.3Standard Car Atk DVA 2.40 200 24 DCT8 65.9 61.0 40.5 1.2 3.4 6.5 8.6 11.4 3.1 4.9 101.3 78.4 — 11 2.8 17.4 11.0 27.3Standard Car Stoich DIT 0.83 176 24 DCT8 61.9 57.2 36.9 1.33.6 6.5 8.6 11.3 2.9 4.8 98.1 77.4 — 12 2.6 16.6 10.5 25.8Standard Car Lean DIT 0.83 176 24 DCT8 62.9 58.0 36.7 1.3 3.6 6.5 8.6 11.3 2.9 4.8 98.1 77.4 — 12 2.6 16.6 10.5 25.8Standard Car EGR DIT 0.83 176 24 DCT8 65.1 59.7 38.4 1.3 3.6 6.5 8.6 11.3 2.9 4.8 98.1 77.4 — 12 2.6 16.6 10.5 25.8Standard Car Atk CS 2.40 200 80 PS 53.3 51.7 36.8 1.4 3.6 6.2 8.0 10.2 2.6 4.0 105.2 85.5 — 10 2.2 15.2 9.3 25.1Standard Car Atk DVA 2.40 200 80 PS 56.4 53.3 37.6 1.4 3.6 6.2 8.0 10.2 2.6 4.0 105.2 85.8 — 10 2.2 15.2 9.3 25.1Standard Car Stoich DIT 0.83 176 80 PS 55.6 51.7 35.4 1.5 3.7 6.6 8.7 11.3 2.9 4.7 99.0 78.1 — 10 2.1 14.9 9.1 24.4Standard Car Lean DIT 0.83 176 80 PS 57.9 53.5 36.0 1.5 3.7 6.6 8.7 11.3 2.9 4.7 99.0 78.1 — 10 2.1 14.9 9.1 24.4Standard Car EGR DIT 0.83 176 80 PS 58.0 54.8 37.1 1.5 3.7 6.6 8.7 11.3 2.9 4.7 99.0 78.1 — 10 2.1 14.9 9.1 24.4Small MPV Stoich DIT 1.13 239 — AT8 38.8 42.6 25.7 1.2 3.3 6.5 8.9 12.0 3.2 5.5 99.8 81.2 — 14 3.1 18.7 11.6 28.3Small MPV Lean DIT 1.13 239 — AT8 40.3 43.1 25.9 1.2 3.3 6.5 8.9 12.0 3.2 5.5 99.8 81.2 — 14 3.1 18.7 11.6 28.3Small MPV EGR DIT 1.13 239 — AT8 40.3 44.4 27.0 1.2 3.3 6.5 8.9 12.0 3.2 5.5 99.8 81.2 — 14 3.1 18.7 11.6 28.3Small MPV Atk CS 2.60 217 20 DCT8 52.9 45.5 29.6 1.4 3.7 7.1 9.3 12.6 3.4 5.5 91.3 76.7 — 10 2.3 15.4 9.4 25.1Small MPV Atk DVA 2.60 217 20 DCT8 54.1 46.8 30.3 1.4 3.7 7.1 9.3 12.6 3.4 5.5 91.3 76.7 — 10 2.3 15.4 9.5 25.1Small MPV Stoich DIT 0.90 190 20 DCT8 50.1 44.2 28.5 1.5 3.9 7.0 9.4 12.3 3.1 5.3 90.6 72.7 — 11 2.1 14.6 8.9 23.7Small MPV Lean DIT 0.90 190 20 DCT8 50.8 44.5 28.5 1.5 3.9 7.0 9.4 12.3 3.1 5.3 90.6 72.7 — 11 2.1 14.6 8.9 23.7Small MPV EGR DIT 0.90 190 20 DCT8 52.0 46.1 29.8 1.5 3.9 7.0 9.4 12.3 3.1 5.3 90.6 72.7 — 11 2.1 14.6 8.9 23.7Small MPV Atk CS 2.60 217 70 PS 44.3 39.6 25.1 1.9 4.6 7.4 9.1 11.1 2.8 3.7 98.3 81.4 — 9 1.4 10.5 6.1 18.0Small MPV Atk DVA 2.60 217 70 PS 49.3 42.3 28.6 1.9 4.6 7.4 9.1 11.1 2.8 3.7 98.3 81.6 — 9 1.4 10.5 6.1 18.0Small MPV Stoich DIT 0.90 190 70 PS 49.1 42.2 27.4 1.9 4.7 8.0 10.3 13.1 3.3 5.1 92.2 73.3 — 8 1.4 10.4 6.1 17.7Small MPV Lean DIT 0.90 190 70 PS 50.8 42.7 27.3 1.9 4.7 8.0 10.3 13.2 3.3 5.2 92.2 73.3 — 8 1.4 10.4 6.1 17.7Small MPV EGR DIT 0.90 190 70 PS 51.3 44.9 28.8 1.9 4.7 8.0 10.3 13.2 3.3 5.2 92.2 73.3 — 8 1.4 10.4 6.1 17.7Velocity (mph) atDistance (m) inTop Speed (mph) on Max grade atAcceleration times (s)Raw fuel economy (mpg)Peak Trq(N.m)EM Pwr(kW)Transmission

# Computer Simulation of LDV Technologies fo r GHG Emission Reduction in the 2020–2025 Timeframe

29 November 2011 Ricardo, Inc. Page 67EngineVehicle Class Type Displ (L) FTP75 HWFET US06 0-10mph 0-30mph 0-50mph 0-60mph 0-70mph 30-50mph 50-70mph 5% Grade 10% Grade 60 mph 70 mph 1.3 sec3 sec 1.3 sec 3 secFull Size Car Stoich DIT 1.41 298 — AT8 37.1 43.2 27.2 1.23.0 5.7 7.4 9.8 2.7 4.1 116.1 95.8 — 20 3.2 19.7 12.1 30.7Full Size Car Lean DIT 1.41 298 — AT8 38.8 44.0 27.6 1.23.0 5.7 7.4 9.8 2.7 4.1 116.1 95.8 — 20 3.2 19.7 12.1 30.7Full Size Car EGR DIT 1.41 298 — AT8 38.6 44.9 28.5 1.23.0 5.7 7.4 9.8 2.7 4.1 116.1 95.8 — 20 3.2 19.7 12.1 30.7Full Size Car Adv Diesel 2.85 503 — AT8 38.2 46.5 32.5 1.12.9 5.6 7.5 9.8 2.7 4.2 113.7 94.9 — 19 3.5 20.2 12.4 31.1Full Size Car Atk CS 3.80 317 28 DCT8 49.9 46.2 31.5 1.23.0 5.5 7.1 9.0 2.5 3.5 113.4 87.9 — 22 2.8 18.6 11.4 30.1Full Size Car Atk DVA 3.80 317 28 DCT8 51.1 47.4 31.9 1.23.0 5.5 7.1 9.0 2.5 3.5 113.4 87.9 — 22 2.8 18.6 11.4 30.1Full Size Car Stoich DIT 1.13 238 28 DCT8 49.8 46.5 31.3 1.3 3.4 6.1 7.7 10.0 2.7 3.9 105.9 86.6 — 15 2.5 16.9 10.5 27.1Full Size Car Lean DIT 1.13 238 28 DCT8 50.4 46.8 31.4 1.3 3.4 6.1 7.7 10.0 2.7 3.9 105.9 86.6 — 15 2.5 16.9 10.5 27.1Full Size Car EGR DIT 1.13 238 28 DCT8 51.7 48.3 32.6 1.3 3.4 6.1 7.7 10.0 2.7 3.9 105.9 86.6 — 15 2.5 16.9 10.5 27.1Full Size Car Atk CS 3.80 317 120 PS 40.3 38.7 29.2 1.3 3.2 5.6 7.1 8.7 2.4 3.1 119.2 103.5 — 16 2.7 17.7 10.7 28.6Full Size Car Atk DVA 3.80 317 120 PS 43.0 40.8 29.8 1.3 3.2 5.6 7.1 8.7 2.4 3.1 119.2 103.5 — 16 2.7 17.7 10.7 28.7Full Size Car Stoich DIT 1.13 238 120 PS 46.6 42.0 29.8 1.3 3.2 6.0 7.8 10.0 2.8 4.0 106.2 87.6 — 12 2.6 17.2 10.4 28.2Full Size Car Lean DIT 1.13 238 120 PS 48.0 41.8 29.9 1.3 3.2 5.9 7.8 10.0 2.7 4.1 106.2 87.7 — 12 2.6 17.2 10.4 28.3Full Size Car EGR DIT 1.13 238 120 PS 47.9 43.6 31.1 1.3 3.2 6.0 7.8 10.0 2.8 4.0 106.2 87.7 — 12 2.6 17.2 10.4 28.2Large MPV Stoich DIT 1.31 277 — AT8 34.8 39.2 23.7 1.1 3.2 6.4 8.6 11.5 3.2 5.1 103.7 84.5 — 15 3.4 19.8 13.2 29.1Large MPV Lean DIT 1.31 277 — AT8 36.0 39.8 23.9 1.1 3.2 6.4 8.6 11.5 3.2 5.1 103.7 84.5 — 15 3.4 19.8 13.2 29.1Large MPV EGR DIT 1.31 277 — AT8 36.2 40.9 24.9 1.1 3.2 6.4 8.6 11.5 3.2 5.1 103.7 84.5 — 15 3.4 19.8 13.2 29.1Large MPV Adv Diesel 2.61 460 — AT8 37.3 43.3 29.4 1.1 3.0 6.2 8.6 11.5 3.2 5.3 101.9 83.9 — 14 3.7 20.9 13.3 30.5Large MPV Atk CS 3.15 263 25 DCT8 48.3 42.4 27.5 1.4 3.6 6.7 8.8 11.6 3.1 4.9 95.5 82.3 — 11 2.4 15.7 9.7 26.0Large MPV Atk DVA 3.15 263 25 DCT8 48.8 43.5 27.7 1.4 3.6 6.7 8.8 11.6 3.1 4.9 95.5 82.3 — 11 2.4 15.7 9.7 26.0Large MPV Stoich DIT 1.05 221 25 DCT8 47.7 42.2 26.2 1.53.8 6.9 9.1 11.9 3.1 5.0 94.3 75.6 — 12 2.2 14.7 9.0 23.9Large MPV Lean DIT 1.05 221 25 DCT8 47.4 42.6 26.8 1.53.8 6.9 9.1 11.9 3.1 5.0 94.3 75.6 — 12 2.2 14.7 9.0 23.9Large MPV EGR DIT 1.05 221 25 DCT8 47.6 43.0 27.6 1.5 3.8 6.9 9.1 11.9 3.1 5.0 94.3 75.6 — 12 2.2 14.7 9.0 23.9Large MPV Atk CS 3.15 263 90 PS 41.7 38.6 26.5 1.8 4.2 7.0 8.8 11.1 2.8 4.1 103.4 86.0 — 11 1.5 11.7 6.8 20.2Large MPV Atk DVA 3.15 263 90 PS 44.3 39.6 27.0 1.8 4.2 7.0 8.8 11.1 2.8 4.1 103.4 86.5 — 11 1.5 11.7 6.8 20.2Large MPV Stoich DIT 1.05 221 90 PS 44.8 39.3 25.8 1.8 4.3 7.5 9.7 12.5 3.2 5.0 100.2 76.5 — 9 1.5 11.5 6.7 19.7Large MPV Lean DIT 1.05 221 90 PS 45.7 40.6 25.7 1.8 4.3 7.5 9.7 12.5 3.2 5.0 100.8 76.5 — 9 1.5 11.5 6.7 19.7Large MPV EGR DIT 1.05 221 90 PS 47.0 41.5 27.3 1.8 4.3 7.5 9.7 12.5 3.2 5.0 100.8 76.5 — 9 1.5 11.5 6.7 19.7LDT Stoich DIT 1.94 410 — AT8 23.8 26.6 16.3 1.1 3.0 6.0 8.1 10.8 3.0 4.8 105.6 86.9 21 — 3.4 20.5 13.2 30.5LDT Lean DIT 1.94 410 — AT8 24.6 27.0 16.4 1.1 3.0 6.0 8.1 10.8 3.0 4.8 105.6 86.9 21 — 3.4 20.5 13.2 30.5LDT EGR DIT 1.94 410 — AT8 24.8 27.7 17.1 1.1 3.0 6.0 8.1 10.8 3.0 4.8 105.6 86.9 21 — 3.4 20.5 13.2 30.5LDT Adv Diesel 4.28 694 — AT8 26.4 30.4 20.5 1.0 2.9 5.8 8.0 10.6 2.9 4.8 104.6 87.2 20 — 3.7 21.4 13.5 31.5LDT Atk CS 4.60 384 50 DCT8 33.2 29.0 19.4 1.1 3.1 5.97.8 10.3 2.8 4.4 95.6 83.8 17 — 3.1 19.1 12.2 29.5LDT Atk DVA 4.60 384 50 DCT8 33.9 29.7 19.7 1.1 3.1 5.9 7.8 10.3 2.8 4.4 95.6 83.8 17 — 3.1 19.1 12.2 29.5LDT Stoich DIT 1.55 327 50 DCT8 32.5 28.4 18.9 1.2 3.3 6.1 7.9 10.4 2.8 4.3 96.1 78.0 16 — 3.0 18.2 11.7 27.9LDT Lean DIT 1.55 327 50 DCT8 33.0 28.6 18.8 1.2 3.3 6.1 7.9 10.4 2.8 4.3 96.1 78.0 16 — 3.0 18.2 11.7 27.9LDT EGR DIT 1.55 327 50 DCT8 33.8 29.6 19.7 1.2 3.3 6.1 7.9 10.4 2.8 4.3 96.1 78.0 16 — 3.0 18.2 11.7 27.9LHDT Stoich DIT 2.30 486 — AT8 16.5 18.3 11.1 1.0 3.2 7.0 9.8 13.4 3.8 6.4 95.1 74.8 16 — 3.6 20.2 13.9 28.6LHDT Lean DIT 2.30 486 — AT8 16.8 18.4 11.2 1.0 3.2 7.09.8 13.4 3.8 6.4 95.1 74.8 16 — 3.6 20.2 13.9 28.6LHDT EGR DIT 2.30 486 — AT8 17.2 19.1 11.7 1.0 3.2 7.0 9.8 13.4 3.8 6.4 95.1 74.8 16 — 3.6 20.2 13.9 28.6LHDT Adv Diesel 6.60 895 — AT8 19.8 21.5 14.1 0.9 2.9 6.3 8.8 11.8 3.4 5.5 101.5 79.3 17 — 4.2 22.2 15.1 31.0Peak Trq(N.m)EM Pwr(kW)TransmissionRaw fuel economy (mpg) Acceleration times (s) Top Speed (mph) on Max grade at Distance (m) in Velocity (mph) at

# Computer Simulation of LDV Technologies fo r GHG Emission Reduction in the 2020–2025 Timeframe

29 November 2011 Ricardo, Inc. Page 68 

# DISCLAIMER

Ricardo Inc. has taken all reasonable care in compiling the analyses and recommendations

provided in this report. However, the information contained in this report is based on information

and assumptions provided by the client or otherwi se available to Ricardo which, in all the

circumstances, is deemed correct on the date of writing. Ricardo does not assume any liability,

provide any warranty or make any representation in respect of the accuracy of the information,

assumptions, and consequently the analyses and recommendations contained in this report.

The report has been compiled solely for the client's use.

Any results of analysis and calculation are intended to be part of subsequent decision-making

during design, development and problem-solving stages. Although analysis may reduce the

effort required to validate a product through testing prior to production, such results shall not be

relied on as a validation in its own right.

Analysis and calculations which are intended to predict physical behaviors are inherently

theoretical in nature as they are subject to a range of assumptions and approximations. Physical

behaviors and the measurements of those behaviors may vary for a variety of factors, some

being outside the control of Ricardo or the capability of the predictive methodology used by

Ricardo. Therefore, where any such predict ions are subsequently compared with measured

data or physical behavior, it is to be expected that differences will be apparent.

# Computer Simulation of LDV Technologies fo r GHG Emission Reduction in the 2020–2025 Timeframe

29 November 2011 Ricardo, Inc. Page 69 

# ATTACHMENT A

Attachment A is the document "Assessment of Technology Options", which includes Ricardo

SME assessments of the technologies considered in study "Computer Simulation of Light Duty

Vehicle Technologies for Greenhouse Gas Emissi on Reduction in the 2020–2025 Timeframe".

These assessments were made of the technologies listed in Appendix 2.Assessment of Technology OptionsTechnologies considered in study"Computer Simulation of LightDuty Vehicle Technologies forGreenhouse Gas Emission Reductionin the 2020–2025 Timeframe"Date30 September 2011ReportRD 11/342305 1RD.11/342305.1ProjectCG001019Prepared forEPA Office of Transportation and Air QualityReport byJennifer DurfyStuart HorswillStuartHorswillChris MaysRichard OsborneJohn StokesWayne Thelenwww.ricardo.comRD.11/342305.1ApprovedJohn J. KasabOutlineIntroductionSpark ignited engine technologiesDiesel engine technologiesHybrid vehicle technologiesTransmission technologiesTransmissiontechnologiesVehicle technologiesConclusions2RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAIntroductionThe following technology assessments were discussed by Ricardo, EPA, andthe Advisory Committee at the start of the study, "Computer Simulation of LightD t Vehicle Technologies for Greenho se Gas Emission Red ction in theDutyVehicleTechnologiesforGreenhouseGasEmissionReductioninthe2020–2025 Timeframe"Purpose of the assessments was to evaluate a large set of potential futuretechnologies against the following criteria:technologiesagainstthefollowingcriteria:–Effectiveness of Technology–Availability of Technology in 2020–2025M k t P t ti f T h l i 20202025–MarketPenetration ofTechnologyin2020––Long-Term Cost Viability–Current Technology MaturityAssessments used the scale on the following slide and were based on theRicardo Subject Matter Experts' experience with the systems consideredBased on the evaluation and discussion,a subset of these technologies was3RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPA, gincluded in the final study.Details of the rating systemEffectiveness of Technology(tank to wheels basis)1 = Worst = no CO2benefit2 = 1% CObenefitLong-Term Cost Viability1 = WORST = no pathway to long-term cost viability3=Needs to"cross commercialization chasm"2=1%CO2benefit5 = 5% CO2benefit8 = 10% CO2benefit10 = Best =≥20% CO2benefit3Needstocrosscommercializationchasm5 = Pathway to volume production costs7 = Return on investment clear10 = Profitable in 2020-2025Availability of Technology in 2020–20251 = University Research Laboratory3 = Technology available but not in vehicles4=First Prototype in vehiclesCurrent Technology Maturity1 = University Research Laboratory3 = Technology available but not in vehicles4 = First Prototype in vehicles4FirstPrototypeinvehicles6 = In Fleet Trials7 = First entry into market10 = Predominant technology in market placeyp6 = In Fleet Trials7 = First entry into market10 = Predominant technology in market placeMarket Penetration of Technology in 2020–20251 = Worst = Demonstrated technology by 20253 = Only in niche applications5 = Available, but not widespread(≥5% of market)4RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPA()7 = Mass-market availability (≥10% of market)10 = Best = Widespread (≥25% of market)OutlineIntroductionSpark ignited engine technologiesDiesel engine technologiesHybrid vehicle technologiesTransmission technologiesTransmissiontechnologiesVehicle technologiesConclusions5RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPABaseline Gasoline EnginesTechnology Assessment – SI EnginesTechnology and StatusConcept:The baseline gasoline engines for2020–2025 light-duty vehicles inRatings of Technology1 10the US market are a rangeof naturally-aspiratedport fuel-injected (PFI)engines, featuring dual-independent cam phaser (VVT) systemsBase Functioning:The baseline vehicles willachieve a fleet averageemissions level of SULEV 2 (approximately EPA Tier 2 Bin 2)COBenefit:Baseline (>35 5 mpg fleet average)MarketEffectiveness(worst) (best)Availability10101CO2Benefit:Baseline(>35.5mpgfleetaverage)Costs:Baseline – powertrain and aftertreatment cost of ~$1500–$2000 forstandard car segmentPenetrationCurrentMaturityLong-TermCost Viability71010Technology ApplicabilityVisualizationThe following vehicle classes are the subject of this study:–Small car (Ford Focus)St d d (T t C )–Standardcar(ToyotaCamry)–Small MPV (Saturn Vue)–Full-size car (Chrysler 300C)–Large MPV (Dodge Grand Caravan)–Truck (Ford F150)6RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPA–Heavy light-duty truck (Ford F250/F350)OutlineIntroductionSpark ignited engine technologiesD id i–ownsizedengines–Advanced valvetrains–Combustion systems and fuels–Engines for hybrid vehiclesDiesel engine technologiesHybrid vehicle technologiesHybridvehicletechnologiesTransmission technologiesVehicle technologies7RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAConclusionsStoichiometric Direct-Injection Turbocharged EnginesTechnology Assessment – SI EnginesTechnology and StatusConcept:Downsizing describes the replacement of a naturally-aspirated engineRatings of Technology1 10with a smaller-displacement turbocharged engine, having equivalent torque andpowerBase Functioning:Downsizing reduces pumping work by shifting operatingpoints to higher load factors, and can also produce reductions in frictional lossesCOBenefit:Drivecycle benefit of 810%MarketEffectiveness(worst) (best)Availability857CO2Benefit:Drive-cyclebenefitof8–10%Costs:15–25% increase in engine and aftertreatment costPenetrationCurrentMaturityLong-TermCost Viability895Technology ApplicabilityVisualizationDownsized DI turbo engines are applicable in all light-duty vehicle classes–Likely to predominate in mid-size vehiclesAs a high compression ratio is maintained, downsized DI turbo engines providefuel economy benefits across the majority of the operating map–As a result, both city andhighway fuel economy will benefit8RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPALean Direct-Injection Turbocharged (LDIT) EnginesTechnology Assessment – SI EnginesTechnology and StatusConcept:In the LDIT concept the octane requirement is controlled using directRatings of Technology1 10injection and lean operation at full loadBase Functioning:LDIT engines combine the downsizing benefits describedon the previous slide withthe additional efficiency benefit of homogeneous leanoperation at high loadCOBenefit:Drivecycle benefit of 2022%MarketEffectiveness(worst) (best)Availability7510CO2Benefit:Drive-cyclebenefitof20–22%Costs:50–60% increase in engine and aftertreatment costPenetrationCurrentMaturityLong-TermCost Viability465Technology ApplicabilityVisualizationLDIT engines are applicable to all vehicle classes–Likely to predominate in mid-size vehicles and premium vehiclesAs a high compression ratio is maintained and lean operation is applied at allconditions LDIT engines provide fuel economy benefits across the majority ofthe operating map–As a result, both city andhighway fuel economy will benefit9RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAHigh-Load EGR EnginesTechnology Assessment – SI EnginesTechnology and StatusConcept:This downsized DI engine conceptis analogous to LDIT, but octaneRatings of Technology1 10requirement is controlled by EGR dilution at full load ratherthan lean operation.Base Functioning:High-load EGR engines combine the benefits of downsizingdescribed previously with the additional efficiency improvement of EGR dilutionat high loadCOBenefit:Drivecycle benefit of 1518%MarketEffectiveness(worst) (best)Availability859CO2Benefit:Drive-cyclebenefitof15–18%Costs:40–45% increase in engine and aftertreatment costPenetrationCurrentMaturityLong-TermCost Viability475Technology ApplicabilityVisualizationHigh-load EGR engines are applicable to all vehicle classesAs a high compression ratio is maintained and EGR dilution is applied at allconditions, High-load EGR engines provide fuel economybenefits across theoperating map–As a result, both city andhighway fuel economy will benefit10RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPATwo-Stroke/Four-Stroke (2S-4S) Switching EnginesTechnology Assessment – SI EnginesTechnology and StatusConcept:The vast majority of passenger cars use the four-stroke cycle, butRatings of Technology1 10some characteristics of two-strokeengines—especially high specific torque—remain attractive for automotiveapplication. 2S-4S engines combine acombustion system capable of operating asboth two-stroke and four-stroke withadvanced valvetrain and boosting systems.Base Functioning:2S-4S engines offer thegreatest opportunityfor engineMarketEffectiveness(worst) (best)Availability7310gg g pp y gdownsizing, and hence improvement in efficiencyCO2Benefit:Drive-cycle benefit of 25–27%Costs:70–80% increase in engine and aftertreatment costPenetrationCurrentMaturityLong-TermCost Viability353Technology ApplicabilityVisualization2S-4S engines operate in four-stroke mode for the majority of drive-cycleoperation, so the emissionsand fuel economy characteristics are those of aheavily downsized 4S DI turbo engineheavilydownsized4SDIturboengine2S-4S engines are most likely to beapplied in premium vehicle segments11RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAOutlineIntroductionSpark ignited engine technologiesD id i–ownsizedengines–Advanced valvetrains–Combustion systems and fuels–Engines for hybrid vehiclesDiesel engine technologiesHybrid vehicle technologiesHybridvehicletechnologiesTransmission technologiesVehicle technologies12RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAConclusionsCam-Profile Switching EnginesTechnology Assessment – SI EnginesTechnology and StatusConcept:Cam-profile switching (CPS) systems allow selection between two orRatings of Technology1 10three cam profiles by means of a hydraulically-actuated mechanical system–CPS systems have been developed bya number of Japanese and EuropeanOEMs, such as the Honda VTEC, Mitsubishi MIVEC, Porsche VarioCam andAudi Valvelift (pictured)Base Functioning:CPS systems can be optimised either to improve lowspeedMarketEffectiveness(worst) (best)Availability876BaseFunctioning:CPSsystemscanbeoptimisedeithertoimprovelow-speedtorque, or to improve fuel economy by reducing pumping losses at light loadCO2Benefit:Drive-cycle benefit of 5–7%Costs:8–10% increase in engine andaftertreatment costPenetrationCurrentMaturityLong-TermCost Viability8107Technology ApplicabilityVisualizationCam-profile switching systems are applicable in all light-duty vehicle classesCPS systems produce most fuel economybenefit for part-load operation, somost benefit occurs for citydriving and less for highway use13RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAOutlineIntroductionSpark ignited engine technologiesD id i–ownsizedengines–Advanced valvetrains–Combustion systems and fuels–Engines for hybrid vehiclesDiesel engine technologiesHybrid vehicle technologiesHybridvehicletechnologiesTransmission technologiesVehicle technologies14RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAConclusionsStoichiometric Direct-Injection EnginesTechnology Assessment – SI EnginesTechnology and StatusConcept:Stoichiometric, homogeneous direct-injection gasolines operate in aRatings of Technology1 10very similar manner to port fuel-injected engines, except that fuel is injecteddirectly into the cylinder. GDI engineswere first introduced in Japan in 1996,and a significant number ofnew gasoline engines now feature direct injection.Base Functioning:The application of direct injection produces modest fueleconomybenefits,resultingfrom the abilityto applyhigher compression ratio.MarketEffectiveness(worst) (best)Availability8103y , g y pp y g pCO2Benefit:Drive-cycle benefit of ~3%Costs:8–10% increase in engine andaftertreatment costPenetrationCurrentMaturityLong-TermCost Viability91010Technology ApplicabilityVisualizationStoichiometric DI engines are applicable in all vehicle classesThe higher compression ratio facilitatedby DI improvesboth part-load and highload efficiency, and therefore both highway and city fuel economy15RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAStratified Charge Direct-Injection EnginesTechnology Assessment – SI EnginesTechnology and StatusConcept:In stratified-charge engines thefuel is injected late in theRatings of Technology1 10compression stroke with single or multiple injections. The aim is to produce anoverall lean, stratified mixture, with a rich area in theregion of the spark plug toenable stable ignition.Base Functioning:Stratified lean operation allows the gasoline engine tooperate unthrottled,eliminatingthe majorityofpumpinglosses.MarketEffectiveness(worst) (best)Availability757p , g j y p pgCO2Benefit:Drive-cycle benefit of 8–10%Costs:15–25% increase in engine and aftertreatment costPenetrationCurrentMaturityLong-TermCost Viability875Technology ApplicabilityVisualizationAs a result of the FIEand aftertreatment costs,lean DI systems are mostapplicable in premium vehiclesAs the fuel economy benefitderives from the reduction of pumping work, leanDI engines produce most improvement in city driving–There is limited benefitfor highway driving16RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAHCCI/CAI CombustionTechnology Assessment – SI EnginesTechnology and StatusConcept:Homogeneous charge compression ignition (HCCI), also known asRatings of Technology1 10controlled auto-ignition (CAI) combustionare distinct fromthe conventional SIand CI engine operating modes–In the idealized case HCCI/CAI combustion initiates simultaneously atmultiple sites within the combustion chamber, and there islittle or no flamepropagationMarketEffectiveness(worst) (best)Availability513p pgBase Functioning:Dual mode operation, with HCCI/CAI at part-load, and SIfor high-load, idle and startingCO2Benefit:Drive-cycle benefit of 2–10% (depending on whether the benefitsof the constituent technologies are included or not)PenetrationCurrentMaturityLong-TermCost Viability451Technology ApplicabilityVisualizationCosts:20–30% increase in engine and aftertreatment costHCCI/CAI combustion is unlikely to be an attractive technology for light-duty455.0ISNOx [g/kWh]HCCI/CAIcombustionisunlikelytobeanattractivetechnologyforlight-dutygasoline vehicles in 2020–2025–The operating envelope for HCCI/CAI combustion is very limited, and theadditional benefits over the necessaryconstituent technologies (advancedvalvetrains, GDI etc.) are also small IMEP [bar]2.53.03.54.04.51.601.200.800.600.400.200.1017RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPA2.0Engine Speed [rev/min]5001000150020002500300035004000Exhaust Energy RecoveryTechnology Assessment – SI EnginesTechnology and StatusConcept:Exhaust energy recovery encompasses a number of technologies,Ratings of Technology1 10such as turbo-compoundingand thermoelectric devices–In turbo-compounding aradial turbine is connected through a mechanicaltransmission directly to the crankshaftBase Functioning:Turbines are generally sized torecover energy at high loadoperation; a variablespeed transmission between engine and turbine can beMarketEffectiveness(worst) (best)Availability733operation;avariable-speedtransmissionbetweenengineandturbinecanbeused to improve the efficient operating rangeCO2Benefit:Turbo-compounding has adrive-cycle benefit of 3–5%Costs:Not established for light-duty vehiclesPenetrationCurrentMaturityLong-TermCost Viability363Technology ApplicabilityVisualizationTurbo-compounding is currently only applied to premium long-haul trucks–In 2020 it will still be most applicable tothe heavy light-duty truck segment,and the benefits will be reduced in comparison to heavy-duty vehicles18RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPASecond-Generation BiofuelsTechnology Assessment – SI EnginesTechnology and StatusConcept:Second-generation biofuels refer to fuels coming from non-foodRatings of Technology1 10sources (in this case gasoline-like fuels)Base Functioning:Wherever possible biofuels should operate in a manneridentical to conventional gasoline–Increasing blending of conventional gasoline and biofuels is likely to occurMarketEffectiveness(worst) (best)Availability9105CO2Benefit:The CO2benefits from the use ofbiofuels are complex anddisputedCosts:There is no significant engine cost associated with the use of single-fuelbiofuels (although appropriate materialsmust be applied in the fuel system)PenetrationCurrentMaturityLong-TermCost Viability5810Technology ApplicabilityVisualizationBiofuels are applicable to all vehicle classesTank-to-wheels fuel economy for biofuelsis similar to that for conventionalgasoline engines – benefits occur fromthe higher octanenumber of ethanolbased fuelsAdditional CO2benefits can be attributed to biofueluse if the complete life-cycleis considered (cellulosic ethanol, etc.)19RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAOutlineIntroductionSpark ignited engine technologiesD id i–ownsizedengines–Advanced valvetrains–Combustion systems and fuels–Engines for hybrid vehiclesDiesel engine technologiesHybrid vehicle technologiesHybridvehicletechnologiesTransmission technologiesVehicle technologies20RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAConclusionsEngines Optimized Micro-Hybrid (Stop-Start) VehiclesTechnology Assessment – SI EnginesTechnology and StatusConcept:Application of stop-start or micro-hybrid concepts requires only veryRatings of Technology1 10minor changes in base engine architecture. Typically a belt-driven startergenerator is applied in place of a separate starter motor and alternator.Base Functioning:See hybrid vehicle slidesCO2Benefit:See hybrid vehicle slidesMarketEffectiveness(worst) (best)Availability10101Costs:Base engine costs are largelyunchanged for stop-start systems.Additional engineering cost is required toimplement the stop-start calibration.PenetrationCurrentMaturityLong-TermCost Viability81010Technology ApplicabilityVisualizationStop-start should applied in all vehicle segments for the 2020 timeframeGiven hybrid inititives, it is likely that most new engine development projects willconsider integrating stop start functionality in program.21RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAEngines Optimized for Full Hybrid VehiclesTechnology Assessment – SI EnginesTechnology and StatusConcept:In hybrid electric vehicle applications the gasoline engine can beRatings of Technology1 10optimised for use in the limited modes required by the full hybrid powertrain.Base Functioning:See hybrid vehicle slidesCO2Benefit:Strong function of degree oflimited operating conditions.Costs:Base engine costs may be slightlyreduced for hybrid vehicleMarketEffectiveness(worst) (best)Availability10102applications through the use oflower specification engines.PenetrationCurrentMaturityLong-TermCost Viability71010Technology ApplicabilityVisualizationEngine technology optimization for hybridpowertrains in infancy. Clear trendtowards system level optimization toobtain best overall performance.Hybrid features such as stop-start,CVT operation, electrical launch, andelectrical assist provide an oportuntity to optimize the engine system in waysnot offered by conventional drivelines.Electrical assist offers opportunity toreduce engine size and specific power inhybrid vehicle and utilize lower specificpower / increased BSFC technologies22RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAy pp gSI Engine Technology ApplicabilityTechnology Assessment – SI EnginesPlease note that the applicability of hybrid powertrains is covered elsewhere inthis report 

# Stoichiometri c Lean Boost D EGR Boost DI 2S-4S Switchi Cam-Profile S Stoichiometri c Stratified-Ch a HCCI/CAI Co m Exhaust Ener g Second-Gene

c DI Turbo I ng Engine witching c Direct injectio n a rge DI m bustion g y Recovery ration Biofuels

nSmall Car (Ford Focus)XXX X XStandard Car (Toyota Camry)XXXXX XSmall MPV (Saturn Vue)XXXXXXVehicleClassificationSmallMPV(SaturnVue)XXXXXXFull-sized Car (Chrysler 300C)XXXX XXXXLarge MPV (Dodge Grand Caravan)XXXX XXXXTruck (Ford F150)XXXXXXXX23RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPATruck(FordF150)XXXXXXXXHeavy light-duty truck (Ford F250/F350)XXXX XX XXXOutlineIntroductionSpark ignited engine technologiesDiesel engine technologiesHybrid vehicle technologiesTransmission technologiesTransmissiontechnologiesVehicle technologiesConclusions24RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPATechnology Area OverviewTechnology Assessment – Diesel EnginesFor this technology area, we have the following thoughts for the situation in2020–2025:Diesel Technology will continue to be developed driven largely by the Europeanmarket but a gradual penetration will be seen in the US marketImprovement is required in technologycost,particularlyturbocharginandq gy p ygaftertreatment for significant penetrationUS market penetration for domestic producers is assumed to commence fromthe heavier vehicles in the study cascading down in size as technology matures,acceptance improves, and CO2legislation drives incremental fleet actionsBaseline is T2B5 (LEV II) applications currently in market–Represents ca. 20% CO2benefit from current baseline SI engine–2020 diesel engines assumed to meet LEV III (approximately currentSULEV II) emissions25RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPATechnology Status – Diesel PowertrainConsideration made across all sectors of studyTechnology Assessment – Diesel EnginesTechnology has very low take rate in US market in passenger car and light dutytruck applications versus EuropeP d t t i ll l il bl i i t d(VW A di–Producttypically only availableinimportedpassenger care.g.,VW,Audi,BMW and Mercedes)–Domestic Product generally offered in LHDT (e.g. Ford Superduty)–European Diesel share is half of market and covers all product families fromEuropeanDieselshareishalfofmarketandcoversallproductfamiliesfromsub-B (Fiat 500 class) to LHDT (Dodge Sprinter Class)–European Market has a competitive CO2driver leading to Diesel greenbranding (e.g. Ford Econetic, Mercedes Bluetec, VW Bluemotion)European Diesel Technology has seen many technology advances–Sequential turbocharging–Combustion correction techniques (e.g. UEGO, cylinder pressure)L EGR l ith h t b–LargeEGRcoolers withhotgasbypass–Third generation FIE – 2000 Bar and multiple injections–Mature DPF technologySCR technology applied26RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPA–SCRtechnologyapplied–Advanced materials – Al alloy heads and blocks, CGI blocksDiesel Technology List for US ApplicationsTechnology Assessment – Diesel EnginesClosed Loop Combustion ControlReduced Compression RatioAdvanced Boosting TechnologiesEnhanced EGR and Charge Air CoolingVariable Valve Timing (With Application To Vary Compression Ratio)VariableValveTiming(WithApplicationToVaryCompressionRatio)Pre-Turbine CatalysisElectric Turbo-CompoundingCalibration "System" Optimization for CO(Engine + Trans + Aftertreatment)Calibration"System"OptimizationforCO2(Engine+Trans+Aftertreatment)Narrow Speed Range OperationSystem Integration at Engine LevelEngine Downsizing–no slide–duplication with SI EngineEngine Friction Reduction – no slide27RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAClosed Loop Combustion ControlTechnology Assessment – Diesel EnginesTechnology and StatusConcept:Provide feedback from combustion bymeans of direct cylinderRatings of Technology1 10pressure measurement and analysis in EMSBase Functioning:Measure cylinder pressure during combustion to providefeedback for air, EGR, and fuel injection control to minimizeerror and correct forfuel quality allowing better trade-off for CO2emissions versus NOx and PMCOBenefit:<1% from maintaining optimal combustionand facilitates furtherMarketEffectiveness(worst) (best)Availability728CO2Benefit:<1%frommaintainingoptimalcombustionandfacilitatesfurthercombustion optimizationCosts:Added variable costs for glowplug, added inputs and processing powerin engine control unit. Additional development time will be required tocharacterize the signal responsesand tune calibration correction responsesPenetrationCurrentMaturityLong-TermCost Viability767Technology ApplicabilityTechnology is applicable to light duty diesel applications commonly fitted withglowplugs. For heavier duty applicationsnot engineered for glowplug alternatehead gasket technology would need to be employedVisualizationheadgaskettechnologywouldneedtobeemployedHighway benefits – closed loop combustionfeedback allows for real world benefitplus closer margin between legal limits and development targets allowing furtherCO2combustion optimizationCity benefits – Furtherreal world benefit availablefrom combustion correctiondi t i t t1 Pl5 M i di h28RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAduringtransienteventsOther – lower cylinder to cylinder variationPicture: www.beru.com1.Plug2. High voltage connection3. Circuit board with electronics4. Gasket5.Measuringdiaphragm6. Glow plug body7. Glow plug heating rodReduced Compression RatioTechnology Assessment – Diesel EnginesTechnology and StatusConcept:Reduction of the compression ratioreduces the peak firing pressureRatings of Technology1 10of the engine. This reducesthe pumping losses and allows for higher specificpower to be achievedBase Functioning:Pumping losses contribute tothe total frictional losses(FMEP) of an engine. Reduction of the losses means less fuelenergy is wastedresultingin higher fuel efficiencyMarketEffectiveness(worst) (best)Availability83gg yCO2Benefit:1% per ratio plus additionalfrom downsizing opportunityCosts:Reduced compression ratio requiresadditional effort to start theengine in colder ambient conditions. An enabler for significant compression ratioreduction would be increased starter energyavailability allowed by high voltageh brid ISG s stemsPenetrationCurrentMaturityLong-TermCost Viability297Technology ApplicabilityApplicable to Diesel ISG applications toenable increased cranking speed for startperformanceHi h b fitI d ifi f th i bl iVisualizationhybridISGsystemsHighwaybenefits–Increasedspecific powerfromthe engine enables enginedownsizing. Reduced pumping loss gives benefit across the full speed and loadrangeCity benefits – As pumping losses are a greater proportion ofpart load operationthe benefit should be more marked in city operationVisualizationNotApplicable29RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAIdle-stop benefits–Idle fuelling will be reduced although pre-cursor of ISGenables full stop-start benefitAdvanced Boosting TechnologiesTechnology Assessment – Diesel EnginesTechnology and StatusConcept:Improvements in air handling through a suite of boostingRatings of Technology1 10technologies either standalone or in combinationBase Functioning:Provision of higher specific torque and power to enabledownsized engines. Technologies include eBoost (e-machine in CHRA orelectrical separation by e-Turbine ande-Compressor); supercharging (advancesto avoid variable drive);variable nozzle compressorMarketEffectiveness(worst) (best)Availability753); pCO2Benefit:2% (more if engine downsized for equivalent performance)Costs:Increase in turbocharger air systemmatching and development time,increased complexity in engine controller.Variable cost of turbocharger doublesplus additional air cooling requirement, sensors and actuatorsPenetrationCurrentMaturityLong-TermCost Viability475Technology ApplicabilityTechnology applicable to all sectors of diesel applicationHighway benefits – improved transient response from engine allows downsizing.M i ll i d i i f f NO d PM t l i iVisualizationMore air allowsimprovedemission performanceforNOx andPMcontrolgivingleeway for CO2reduction.City benefits – much improved transient performanceallowing downsizing.Operation in more efficient area ofturbocharger map gives more noticeable CO2benefit in city driving30RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAIn conjunction with enhanced EGR allows for premixed or homogeneouscombustion in part load operation for veryclean emissions. Design can facilitatethe use of pre-TC catalyst for quick aftertreatment light-offPicture: http://honeywellbooster.comEnhanced EGR Flow & Cooling(Plus Increased Charge Air Cooling)Technology Assessment – Diesel EnginesTechnology and StatusConcept:Low Pressure EGR Circuit for increased EGR flow rate in conjunctionRatings of Technology1 10with separate low temperature cooling circuit to cool EGR and provide additionalcharge air coolingBase Functioning:Increased EGR and cooler charger enables homogeneous,fully premixed and partially premixedcombustion concepts. These conceptsreduce NOx and PM emissions allowing more margin for CO2optimization.Lo er charge temperat re pro ides a larger PV area and increases specificMarketEffectiveness(worst) (best)Availability874LowerchargetemperatureprovidesalargerP-Vareaandincreasesspecificpower and economyCO2Benefit:2–4% from combined emission and cooling benefitCosts:Increased development cost for EGR and cooling system packaging.Additional work to optimize coolingpack. EGR cost increases 40–50% plusincremental costs for additional cooling system components and materialPenetrationCurrentMaturityLong-TermCost Viability767Technology ApplicabilityApplicable to Light Duty Chassis Certification Applications requiring EGR at lowVisualizationincrementalcostsforadditionalcoolingsystemcomponentsandmaterialrevisions necessary to cope with corrosive environment incharge cooler withEGR presentspeed and load:Highway benefits – Fuel economy improvement fromincreased charge coolingand improved compressor efficiency (EGR flows through TC compressor)City benefits – Significantemission benefit allowing combustion to be optimizedmore for CO2. Compressor efficiency improved for reduced pumping lossA significant challenge remainsfor TC compressor d rabilit ith hea EGR flo31RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAAsignificantchallengeremainsforTCcompressordurability withheavyEGRflowratesPicture: VW Tech Report29. Internationales Wiener Motorensymposium 2008Variable Valve Timing(With Application To Vary Compression Ratio)Technology Assessment – Diesel EnginesTechnology and StatusConcept:Variable Valve Events enable valve events to be optimzed forRatings of Technology1 10oeprating point and also enable effective compression ratio variationBase Functioning: Intake and Exhaust Valve Events varied for rapidaftertreatment warm-up and best breathing at operating condition rather thanglobal optimization. With more complex system, compression ratio can also bevaried to reduce frictional losses and increase specific powerMarketEffectiveness(worst) (best)Availability733CO2Benefit:1–2% from warm-up & improved breathing. Additional gain ifaftertreatment warmup createsNOx advantage to be used for CO2benefitCosts:Costs increase for valvetrain technology with some offset inaftertreatment cost. Additional development cost to develop for diesel engineapplication with incremental engine controller costs for drive circuitsPenetrationCurrentMaturityLong-TermCost Viability233Technology ApplicabilityApplicable to complete dieselline-up from small car to MDVHighway benefits – Increased specificpower from the engine enables engined i i R d d i l i b fit th f ll d d l dVisualizationapplicationwithincrementalenginecontrollercostsfordrivecircuitsdownsizing.Reducedpumpingloss givesbenefitacrossthefullspeedandloadrangeCity benefits – As pumping losses are a greater proportion ofpart load operationthe benefit should be more marked in city operationIdle-stop benefits – ability to raise compression ratio allows stop start to be more32RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAreadily employed than reduced compressionratio alone as ISG is not necessaryfor restartPicture: Valeo e-Valve MediaPre-Turbine CatalysisTechnology Assessment – Diesel EnginesTechnology and StatusConcept:Small Oxidation Catalyst (DOC) isplaced before first turbochargerRatings of Technology1 10very close to the engineBase Functioning:Small pre-turbine catalyst withlow thermal inertia lights offquickly allowing further exotherm to warm up rest of aftertreatment more rapidly.Reduced warm-up will require lower use offuel for heating strategies reducingCO2emissionsMarketEffectiveness(worst) (best)Availability872Technology Applicability2CO2Benefit:<1% – more for cold start cycles.Costs:Additional cost for pre-turbine catalyst precious metal partially offsetby reduced precious metal in remainder of aftertreatment systemPenetrationCurrentMaturityLong-TermCost Viability587TechnologyApplicabilityApplicable to all diesel technology applications but with more relevance onapplications with larger engines and large aftertreatmentsystems with greaterthermal inertiaHighway benefits – Minimal benefitand only soon after starting whenVisualizationaftertreatment is coldCity benefits – Benefit most noticeable for real world situations when vehicle isused frequently for short journeys from coldor cool start whenaftertreatment isbelow effective operating temperaturePre-turbine catalyst allows for lessaggressive heating strategies to keepaftertreatment in correctoperating temperature window33RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAaftertreatmentincorrectoperatingtemperaturewindowComponent durability must be considered inplacing catalyst closer to engine andmay require metallic catalyst substratePicture: www.emitec.comElectric Turbo-CompoundingTechnology Assessment – Diesel EnginesTechnology and StatusConcept:Electric turbo-compounding device recovers waste exhaust energyRatings of Technology1 10and converts this to electrical energyBase Functioning:Exhaust energy that would otherwise be wasted is used todrive a turbine coupled to an electricalgenerator to generate electrical power.The electrical power can bestored in conjunction withhybridization or fed backas shaftpower directlyto reduce fuel demand on engineMarketEffectiveness(worst) (best)Availability645py gCO2Benefit:4–5% improvement in fuelefficiency depending on cycleCosts:Technology is proven on heavy duty applications but specificdevelopment would be required for lighter duty matching and application.Incremental variable cost for ETC and power electronics.PenetrationCurrentMaturityLong-TermCost Viability334Technology ApplicabilityAlready applied to heavy duty applications – more applicable to heavierapplicationsHi h b fiti ifi t b fitt 5% d di d t l dVisualizationHighwaybenefits–significantbenefit–upto5%depending onduty cycle andengine load on highwayCity benefits – transient low speed and load does not offer the same quality ofexhaust energy for energy recovery. There is potential for worsened fuel economydue to increased back-pressureat some parts of operation34RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAIdle-stop benefits would be acheivedif coupled with hybridizationMore benefit would be obtained with electrification of accessories.Picture: Source: John Deere, DEER 2006Calibration "System" Optimization for CO2(Engine + Transmission + Aftertreatment)Technology Assessment – Diesel EnginesTechnology and StatusConcept:Application of a sytem level technology selection to add increasedRatings of Technology1 10NOx aftertreatment allowing optimization of engine outemissions for lower CO2and higher NOx (and revised total gearing)Base Functioning:Instead of minimizing engineout NOx for smaller NOxaftertreatment asystem approach for CO2could oversize NOx aftertreatmentand allow increased engine out NOx emissions with reduced engine out CO2.Combined ith transmission ratio selection for COrather than NOMarketEffectiveness(worst) (best)Availability7104CombinedwithtransmissionratioselectionforCO2ratherthanNOxCO2Benefit:2–4% offset by increased DEF utilization and partially offset byincreased fuel consumption during warm-up to light off aftertreatmentCosts:Aftertreatment cost would risein line with additional reductioncapacity. DEF system would also need tobe resized to account for additionalDEF consumptionPenetrationCurrentMaturityLong-TermCost Viability6910Technology ApplicabilityTechnology applicable to all areas of diesel applicationHighway benefits – lower CO2emission by reduced engine speed operation fromhi h i d ti l COlib ti ith i d i t NOVisualizationDEFconsumptionhigher gearing andmore optimalCO2calibration withincreasedengine outNOxCity benefits – lower engine speedand improved transient CO2provide lowerspeed and load benefitsIdle-stop – stop start operation would need to be treated carefully to maintainaftertreatment operating temperature35RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAIncrease DEF consumption woudl offsetcost benefit to end-user and extendpayback durationPicture: Ricardo, Inc.Narrow Speed Range OperationTechnology Assessment – Diesel EnginesTechnology and StatusConcept:Powertrain designed to enable the engine to operate within a narrowRatings of Technology1 10speed band range with full emissions and economy optimization in this rangeBase Functioning:Powertrain coupled to hybridsystems and/or highly flexibletransmissions allowing engine to be optimized for narrow speed band for bestemissions and economy. Contrast to traditional optimization that considersentire speed load range requirements with many compromisesCOB fit24% f ti i ti f b ti l t it bMarketEffectiveness(worst) (best)Availability434CO2Benefit:2–4%from optimization ofcombustion plus more opportunitybylimiting higher engine speed for friction reduction with design factors for narrowspeed range envelopeCosts:Little impact to cost ifhighly flexible transmissions and/or hybrid alreadyselected. Reduced engine optimizationdevelopment offset by increasedpowertrain system developmentPenetrationCurrentMaturityLong-TermCost Viability253Technology ApplicabilityApplicable to all classes of vehicles usinghybrid systems or high numbers of gear ratiosthat allow engine speed range to be very narrowHighway benefits–Improved economy by maintaining engine in high efficiency islandVisualizationpowertrainsystemdevelopment )HighwaybenefitsImprovedeconomybymaintainingengineinhighefficiencyisland.Enhanced benefit if emission spikes in transient operation can be avoided allowingfurther optimization for fuel economyCity benefits – As highway plus ability to set speed and load on engine for rapidaftertreatment warm-up. Engine speed set point can be matched to provide optimalelectrical energy generation efficiency for recharging hybrid energy reserve enhancingidle and stop benefits Engine Torque (Nm )36RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAidleandstopbenefitsConstant speed operation may prove un-desirable noise characteristic compared totraditional powertrain solutionsPicture: Ricardo Inc.Engine Speed (RPM)System Integration at Engine LevelTechnology Assessment – Diesel EnginesTechnology and StatusConcept:Combine components to reduce mass and thermal inertia givingRatings of Technology1 10improved package and faster warm-up. Electrify ancillaries to eliminate FEADand allow variable performance independent of engine speedBase Functioning:Combination of components (e.g. exhaust manifold andcylinder head) to improve response timefor turbocharging and aftertreatmentwarm-up. Electrification of FEAD reducesparasitic losses and allows operationMarketEffectiveness(worst) (best)Availability838p ppto be optimized to most efficient condition for operating point (e.g electricalcoolant pump, oil pump or AC compressor)CO2Benefit:1–2%Costs:Added variable costs for more complex production offset by reducedmaterial Electrification in conj nction ith h bridi ationPenetrationCurrentMaturityLong-TermCost Viability368Technology ApplicabilityTechnology is applicable to all diesel technology sectorsHighway benefits – reduced frictional losses at higher speed and load points byd i i d i ill i t ti l ditiVisualizationmaterial.Electrificationinconjunctionwithhybridization.designing andrunning ancillaries atoptimalconditionsCity benefits – Rapid aftertreatment warm-up reduces fuel consumption in warmup phase and allows earlier transition to warm fuel efficient maps. Ability to runancillaries faster at lower engine speedswill enable lower power loss and shouldenable component downsizing37RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAPicture: Ricardo, Inc.Diesel Engine Technology ApplicabilityTechnology Assessment – Diesel EnginesPlease note that the applicability of hybrid powertrains is covered in a separatepart of this report 

# C R A E

C V P E C N E

losed Loop Co m R educed Compre s A dvanced Boosti n E nhanced EGR a n

C ooling V ariable Valve Ti m P re-Turbine Catal E lectric Turbo-C o C alibration "Syst e N arrow Speed Ra E ngine System In t

m bustion Control

s sion Ratio n g Technologie s n d Charge Air m ing ysis o mpounding e m" Optimizatio n nge Operation t egration

sSmall Car (Ford Focus)X X X XX XX XStandard Car (Toyota Camry)X X XXXXXXSmall MPV(Saturn Vue)X X XXXXXXVehicleClassification( )Full-sized Car (Chrysler 300C)X X XXX XXXXLarge MPV (Dodge Grand Caravan)X X XXXXXXXXTruck(Ford F150)XXXXXXXXXX38RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPA( )XXXXXXXXXXHeavy light-duty truck (Ford F250/F350)X XXXXXXX XOutlineIntroductionSpark ignited engine technologiesDiesel engine technologiesHybrid vehicle technologiesTransmission technologiesTransmissiontechnologiesVehicle technologiesConclusions39RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAHybrid Functionality MatrixTechnology Assessment – Hybridized PowertrainsHybrid technology’s primary purpose is to enable vehicle functionally that offers fuel efficiency.None Micro Micro Mild Full Full Full Full Full FullConventionalBeltstarter /generatorBeltmountedparallelCrankmountedparallel(IMA)P2 parallelhybridInputPowersplitCompoundpowersplit2-modepowersplitSerieshybrid -ElectricalSerieshybrid -HydraulicEngine idle off No Yes Yes Yes Yes Yes Yes Yes Yes YesLaunch assist No NoSmallamountSome Yes Yes Yes Yes No NoRegeneration No NoSmallamountSome Yes Yes Yes Yes Yes YesElectrical onlymobilityNo NO No No Yes Yes Yes Yes Yes YesCVT No No No No No Yes Yes Yes Yes YesPower SteeringBelt Electrical Electrical Electrical Electrical Electrical Electrical Electrical Electrical ElectricalAi di i iB lB lB lB lBelt orBelt orBelt orBelt orBelt orBelt orAir conditioningBeltBeltBeltBeltBeltorelectricalBeltorelectricalBeltorelectricalBeltorelectricalBeltorelectricalBeltorelectricalBrakes Standard Standard StandardStandard orblendedBlended Blended Blended Blended Blended BlendedCity Driving0 + ++ ++ +++ ++++ ++++ ++++ ++++ ++++Highway Driving0 00 + + + + + - -40RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAHybrid Technology Area ConsiderationsTechnology Assessment – Hybridized PowertrainsHybrid technology largely available now but needs cost reduction efforts to providefinancial justification to consumers; largely expected to come through volume increases(economy of scale) & commodity mindset(economyofscale)&commoditymindsetPace of development–Change in fuel prices (or fuel tax legislation) could dramatically accelerate (or slow)hybrid development and implementation. CAFE requirements will drive technologydevelopment in near termdevelopmentinnearterm.–Li-ion battery development largely in fluxas well, but not necessarily an impact tohybrid development, as NiMH is sufficient(i.e., Li-ion required for EV and PHEV but notcurrent strong hybrid technology)Many hybrid applications today being consumed by early (technology) adopters and/orthose focused on environmental impact and energy independence–Hybridization still difficult to justify based purely on financial business case–Governmental legislation(e.g.,CAFE or CO2requirements)largelyresponsible forg (g,2q ) gy phybrid investmentBenefits of hybrid technologies are generally independent of component technologies(Electrical machine & energy storage) due to goodround trip efficiency attributes of currenttechnologies.41RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAtechnologies.–Some small correlation exists, and with parameterization in model, opportunity tosweep parameters to evaluation sensitivity.Micro Hybrid: Stop-StartTechnology Assessment – Hybridized PowertrainsTechnology Description and StatusConcept:Most basic of hybridization, allows for simple engine shut-off duringRatings of Technology1 10idle periods; typically employs enhanced starter motor and limited use of drivercomfort features during engine off (e.g. Radio, some heat, but no A/C)Base Functioning:Decreases wasted fuel by minimzing idling but provides nobenefit for highway use or when airconditioning is required/desiredCOBenefit:35% over city cycles 0% over highwayMarketEffectiveness(worst) (best)Availability9103CO2Benefit:3–5%overcitycycles.0%overhighwayCosts:This is the lowest cost hybridsystem and can be implemented relativelyquickly on most vehicles on the market today. Stop-start systems aresomewhat mature and readily availableoff the shelf. Further development willyield increased user acceptance (e.g. Transparent integration with little to nodetriment to e isting ehicles in terms of NVH acceleration etc )PenetrationCurrentMaturityLong-TermCost Viability8710Technology ApplicabilityStop-start technology can be applied to almost all vehicles including passengercars, medium and heavy duty trucks and even off-highway or agriculturalvehiclesVisualizationdetrimenttoexistingvehiclesintermsofNVH,acceleration,etc.)vehicles.Benefits are limited,though, to vehicle applicationsthat have some periods ofidling. For example, long-haul trucks with extended highway operation will seelittle to no benefit. Similiarly, as air conditioning is not available during engine-offperiods, users may experience some degradation in performance that could beunacceptable42RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAunacceptable.Mild Hybrid: Integrated Belt Starter-Generator (IBSG)Technology Assessment – Hybridized PowertrainsTechnology Description and StatusConcept:The alternator is replaced with anew electric machine that canRatings of Technology1 10provide lauch assist as well as replacingthe electrical supplyof the alternatorduring normal vehicle operation. Typically this machine can also be used forenergy recapture during braking..Base Functioning:Provides stop-start functionality(see “Stop-Start“ slide) aswell as electric launch assist,which,when coupled to a dedicated energyMarketEffectiveness(worst) (best)Availability9105, , p gystorage system with a charge sustaining strategy, can decrease fuelconsumption during acceleration from a stop.CO2Benefit:3–7% over city cycles, ~0% over highway cyclesCosts:Several IBSG systems are on the market today so development costsare largel s nk P rchase costs of the s stem are no decreasing as ol mePenetrationCurrentMaturityLong-TermCost Viability8910Technology ApplicabilityIBSG systems can be applied to a wide variety of applications includingVisualizationarelargelysunk.Purchasecostsofthesystemarenowdecreasingasvolumegrows such that financial payback may be viable soon.passenger cars and medium and heavy duty trucks with benefits seen in citycycles. Due to the small size of the IBSG, relativelylimtied ability to downsize,but some bennefit.43RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAMild Hybrid: Integrated Crank Starter-Generator (ICSG)[also known as Integrated Motor Assist (IMA)]Technology Assessment – Hybridized PowertrainsTechnology Description and StatusConcept:An e-machine is added to or replaces the flywheel. Larger than theRatings of Technology1 10e-machine used in an ISBG, the motor can provide lauch assist andregenerative braking as well additionalpower during a variety of vehicleoperating modes and, thus,is applied in conjunction with a downsized engine.Base Functioning:Provides stop-start functionality and launch assist. Thisprovides the opportunityto use of a smaller engine to increase efficiencyMarketEffectiveness(worst) (best)Availability9107p pp y g ythroughout the operating rangeof the vehicle, not just during launch from astop.CO2Benefit:16–20% on city cycles, ~0% on highway cyclesCosts:ICSG systems are on the markettoday so development costs arelargel s nk P rchase costs of the s stem are no decreasing as ol mePenetrationCurrentMaturityLong-TermCost Viability8910Technology ApplicabilityICSG systemscan be applied to a wide variety of applicationsincludingVisualizationlargelysunk.Purchasecostsofthesystemarenowdecreasingasvolumegrows and the greater fuelefficiency is greatenough to provide reasonablefinancial payback today.ICSGsystemscanbeappliedtoawidevarietyofapplicationsincludingpassenger cars and medium and heavy dutytrucks with benefits mostly seen incity drive cycles. The reduced engine sizes enabled by the hybrid system providehighway bennefits.Typically, these systems have been used with a CVT to avoid Torque converterlosses44RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAlosses.Full Hybrid: P2 parallel HybridTechnology Assessment – Hybridized PowertrainsT h l d St tTechnology andStatusConcept:An e-machine is inserted between the engine and the transmission,typically with a clutch between the engine and e-machine.Larger than the emachine used in an ISBG, the motor can provide lauch assist and regenerativebraking as well additional power duringa variety of vehicle operating modesRatings of Technology1 10and, thus, is applied in conjunction with a downsized engine.Base Functioning:Provides stop-start, electricallaunch, and launch assit. Thisoptimizes the use of asmaller engine to increase efficiency throughout theoperating range of the vehicle, not just during launch from a stop.CO2Benefit:18–22% on city cycles~0% on highway cycles (downsizingMarketEffectiveness(worst) (best)Availability778CO2Benefit:1822%oncitycycles,0%onhighwaycycles(downsizingoffers bennefits)Costs:No P2 parallel hybrids are in production today, so development costswill still need to be invested, however parts bin exists today. The cost of thesystem is higher thana ICSG, however, thesystem has only 1 electrical machineso its costs should be lower than more advanced hybridsPenetrationCurrentMaturityLong-TermCost Viability397Technology ApplicabilityP2 hybrids can be applied to a wide variety of applications including passengerVisualizationsoitscostsshouldbelowerthanmoreadvancedhybridscars and medium and heavy duty trucks with benefits seen mostly in city drivecycles. The reduced engine sizes enabled bythe hybrid system provide highwaybennefits.System can be used with an AT, however, Tomaintain efficiency, a CVT or DCTshould be used to avoid Torque converter losses.45RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAFull Hybrid: Input Power Split HybridTechnology Assessment – Hybridized PowertrainsTechnology Description and StatusConcept:Power split hybrids use an electricmachine directly integrated intoRatings of Technology1 10the transmission, and eitherprovide an additional inputparallel to the engine oract as an additional output from the transmission. Both varieties permit anelectric (only)operating mode.Base Functioning:Power split encompasses all of the aforementionedtechnologyprovidingstop-start,launch,and engine downsizingbenefits inplusMarketEffectiveness(worst) (best)Availability789gy p g p,,g g pthe ability to provide an electric-onlyoperating mode, when used in conjunctionwith the appropriate electric accessories.CO2Benefit:22–33% in city driving, somebennefit in highway drivingCosts:Development is ongoing with roomfor both performance improvementand cost red ction b t initial s stems are no idel spread in the market placePenetrationCurrentMaturityLong-TermCost Viability1068Technology ApplicabilityAs a full or strong hybrid, the power split hybrid offers very good benefit ofVisualizationandcostreductionbutinitialsystemsarenow widelyspreadinthemarketplace(e.g. Ford Fusion and Escape and Toyota Prius).Asafullorstronghybrid,thepowersplithybridoffersverygoodbenefitofhybridizationChallange with cost due to twoelectrical machine solution.Fuel efficiency improvement is found across the range and inall operating cyclessince engine downsizing and electricaccessories optimize performance andefficiency of the combustion engine and the vehicle as a whole46RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAefficiencyofthecombustionengineandthevehicleasawholeFull Hybrid: Two-Mode Power SplitTechnology Assessment – Hybridized PowertrainsTechnology Description and StatusConcept:Two-Mode hybrids use electric machines (usually two) directlyRatings of Technology1 10integrated into the transmission for maximum operating flexibility with operationas input powersplit or compound power split gearing configuration via clutchactuation.Base Functioning:Two-Mode encompasses allof the aforementionedtechnologyprovidingstop-start,launch,and enables engine downsizingbenefitsMarketEffectiveness(worst) (best)Availability779gy p g p,, g gin plus the ability to provide an electric-only operatingmode, when used inconjunction with the appropriate electric accessories.CO2Benefit:22–33% in city drive cycle. Some bennefit in highway drivingCosts:Development is ongoing as Two-Modehardware is still very expensive,pro iding little commercial pa back to the c stomer c rrentlHo e erT oPenetrationCurrentMaturityLong-TermCost Viability857Technology ApplicabilityAs a full or strong hybrid theTwoModehybrid offers maximum benefit ofVisualizationprovidinglittlecommercialpaybacktothecustomercurrently.However,TwoMode systems are proliferating in the market place with GM offering truck andSUV variants now, and BMW, Mercedes andChrysler products coming soon).Asafullorstronghybrid,theTwo-Modehybridoffersmaximumbenefitofhybridization but is alsothe most costly and complexof all architectures toimplement.Fuel efficiency improvement is found across the range and inall operating cyclessince engine downsizing and electricaccessories optimize performance andefficiency of the combustion engine and the vehicle as a whole47RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAefficiencyofthecombustionengineandthevehicleasawholeFull Hybrid: Series ElectricalTechnology Assessment – Hybridized PowertrainsTechnology and StatusConcept:Series electrical hybrid systems include two electrical machines andRatings of Technology1 10a battery. One EM is located on drvie axle and is sized for peak loads, andsecond EM is located on engineand is sized for average loads.Base Functioning:Energy storage systemenables load averageing andengine off operation. As driveline and engine are decoupled, engine can besinglepoint engine or operate on best-efficiencyline engine.MarketEffectiveness(worst) (best)Availability636gp g py gCO2Benefit:22–33% in city drive cycle. Potenally reduced in highwaydriving, depending on degree ofreduced engine size enabled.Costs:The cost implications of two electrical machines (one large and onesmall) and a battery have limited the appealof this technology to the industry.PenetrationCurrentMaturityLong-TermCost Viability453Technology ApplicabilitySeries hybrids are not currently in production, andtechnology approach has notbeen embraced by industry (has been championed in research community) dueVisualizationB ttbeenembracedbyindustry(hasbeenchampionedinresearchcommunity)dueto the costs associated withmultiple large electricalmachine size & a battery.With introduction of EVs, opportuntity forindustry to gain comfert with serieselectrical and increase volumes to reduce costs.Battery48RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAFull Hybrid: Series HydraulicTechnology Assessment – Hybridized PowertrainsTechnology Description and StatusConcept:Hydraulic accumulators are usedto aid in deceleration, then thestored energy is released back into the vehicle for launch assist using hydraulicRatings of Technology1 10storedenergyisreleasedbackintothevehicleforlaunchassistusinghydraulicpumps connected to an axle or transmission.Base Functioning:Kinetic energy that would otherwise be translated to heat inthe braking system is recaptured forlater use. Can also be used for enginedownsizing.MarketEffectiveness(worst) (best)Availability636CO2Benefit:22–33% in city drive cycle. Potenally reduced in highwaydriving, depending on degree ofreduced engine size enabled.Costs:Hydraulic hybridization is still in early development with only a fewdemonstration vehicles on theroad today. Application ofhydraulic hybridizationis much less costlyin vehicles that alreadyemployextensive hydraulic systemsPenetrationCurrentMaturityLong-TermCost Viability453Technology ApplicabilityHydraulic hybrid systems typically suggested in niche applications such as refuseVisualizationy y py y yfor specific vocations (e.g., garbagecompactor) and increased efficiency islimited to vocations with extreme stop-start cycles and agressive deceleration.Hydraulichybridsystemstypicallysuggestedinnicheapplicationssuchasrefusetrucks, where large power required forregeneration is well suited to hydraulicsystems.Potentially reduced fueleconomy in highway driving, depending on degree ofreduced engine size enabled.Hydraulic hybrid technologydevelopment has been significantly slower than49RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAHydraulichybridtechnologydevelopmenthasbeensignificantlyslowerthanelectrical hybrid technology developmentrate, and use of hydraulic driveline isnot consistent withother high profile technology initiatives such as EVs, PHEVsand vehicle electrification.OutlineIntroductionSpark ignited engine technologiesDiesel engine technologiesHybrid vehicle technologiesTransmission technologiesTransmissiontechnologiesVehicle technologiesConclusions50RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPATechnology Area OverviewTechnology Assessment – TransmissionsFor this technology area, we have the following thoughts for the situation for in2020–2025:–North American market will continue tobe dominated by automatic transmissions for IC engines with emphasis onincreasing launch device efficiency and smart kinematics designincreasinglaunchdeviceefficiencyandsmartkinematicsdesign–Higher presence of more fuel efficient AMT’s and DCT’s expected–Increase in simplified single/two speed gearboxes for hybrid applications–CVT development expected to be on thedecline in the North American market(although still being pursued byJapanese market)Pace of development–Development of AMT and DCT technologyexpected to be implemented fromEuropean and Japanese efforts–Detroit 3 actively pursuing DCT technology, with teamingarrangements established between OEMs and Tier 1 todevelop technologiesdeveloptechnologies–Improvements for automatic transmissions are on-going with new technologies being implemented into luxuryvehicles and then cascaded down to other vehicle classes.–Single/two speed gearboxes for hybrid applicationsrequire minimal investment and lead timeComparison to baselineComparisontobaseline–Given 94% of North American transmissions are automatic, improvements in efficiency (resulting in CO2improvements) will be realized through:•Smart kinematics design (2–5%)•Component efficiency improvement oralternative technologies (3%)51RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPA•Launch devices (2–6%)•Dry sump technology (2%)–Estimates of improvement depend on the drive cycle, are not simply additive, andare subject to quality of baselineTransmission SummaryTechnology Assessment – TransmissionsHydraulically operated, using a fluid coupling ortorque converter and a set of gearsets to providef tiAMT operates similarly to a manual transmissionexcept that it does not require clutch actuation orAutomatic (with Torque Converter)AMT (Automatic Manual Transmission)a range ofgear ratiosDecrease in efficiency associated with viscouslosses from torque converterexceptthatitdoesnotrequireclutchactuationorshifting by the driver.Automatic shifting is controlled electronically(shift-by-wire) and performed by a hydraulicsystem or electric motor.P hift lit h l d d thi t h lPoor shiftqualityhas excludedthistechnologyfrom the studyRather than using gears, the CVTs incurrently available vehicles utilize apair of variable-diameterpulleysUses two separate clutchesfor even and odd gear setsEliminates the use of aDCT (Dual Clutch Transmission)CVT (Continuous Variable Transmission)pp yconnected by a belt or chain that canproduce an infinite number ofengine/wheel speed ratios.Reliability and efficiency issuesprevent this technology fromEliminatestheuseofatorque converter and utilizeseither wet or dry type launchclutches52RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPApreventthistechnologyfromroadmap developmentTechnology Area SummaryTechnology Assessment – TransmissionsLaunch Devices–Wet Clutch–Damp Clutch–Dry Clutch–Multi-damper Torque converterq–Magnetic clutchShifting Clutch TechnologyS t Ki ti D iSmartKinematicDesignDry SumpEfficient ComponentsSuper FinishingLubrication53RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPALaunch Device: Wet ClutchTechnology Assessment – TransmissionsTechnology and StatusConcept:provides torque transmission duringoperation by means of frictionRatings of Technology1 10action between surfaceswetted by a lubricantBase Functioning:Increases fuel effieciency byreducing hydraulic parasiticlosses over a conventional torqueconverter when it is slipping.CO2Benefit:Benefit realized at launchand during transient drivingMarketEffectiveness(worst) (best)Availability757Costs:up to 20% less than a conventional torque converterPenetrationCurrentMaturityLong-TermCost Viability665Technology ApplicabilityTechnology applicable to planetary,parallel-axis, AMT and dual clutchtransmissionsRi i l l b i ti t l b i t t ti f b l b i tiVisualizationequires speciallubrication system orlubricantto satisfy gearboxlubricationrequirements and actuation requirements.Parasitic losses of lubrication systemdiminish overallbenefit over torqueconverter.Improvement in city driving, little for highway54RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAPicture: www.cerom.lsu.edu*Note: Effectiveness relates to improvement in transmission efficiencyLaunch Device: Damp ClutchTechnology Assessment – TransmissionsTechnology and StatusConcept:Similar concept as a wet clutch butonly a limited spray is applied toRatings of Technology1 10achieve coolingBase Functioning:Still requires a lubrication systembut is more efficient dueto controlled environment (less windage and churning)CO2Benefit:Similar benefits as a dry clutchMarketEffectiveness(worst) (best)Availability237Costs: ~$25 above wet clutchPenetrationCurrentMaturityLong-TermCost Viability453Technology ApplicabilityVisualizationApplicable to most automatic transmissions– best of both worlds, efficiency of adry clutch matched with the longevity and higher torquecapacity of a wet clutchA f th th l h d i th i i ffi i i li bl tl tAsforthe otherlaunchdevices,theincreasein efficiencyis applicable mostlytocity driving.55RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAPicture: www.cerom.lsu.edu*Note: Effectiveness relates to improvement in transmission efficiencyLaunch Device: Dry Clutch AdvancementsTechnology Assessment – TransmissionsTechnology and StatusConcept:Standard manual clutch require advanced materials to provide heatRatings of Technology1 10dissipation to be used in automatic applications or electric assist (on/off) toprevent slippingBase Functioning:Thermal load resulting from engagement prevent dryclutches from being used in high torque and heavy duty cycle applications butare more effiecient since theydon‘t require an additional lubrication system andMarketEffectiveness(worst) (best)Availability648yq ysignificatntly reduce parasitic shear fluid losses.CO2Benefit:Benefit realized at launchand during transient drivingCosts:Dry Clutch materials +10-20%, Electric motor $1500PenetrationCurrentMaturityLong-TermCost Viability374Technology ApplicabilityAdvancements in material or electricassist could enable this technology to beused in larger vehicles and more severe duty cyclesCit d i i i tVisualizationCitydrivingimprovement56RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAPicture: www.cerom.lsu.edu*Note: Effectiveness relates to improvement in transmission efficiencyLaunch Device: Multi-Damper Torque ConverterTechnology Assessment – TransmissionsTechnology and StatusConcept:Dampers in torque converter enable lower lock-up speedRatings of Technology1 10Base Functioning:The more fuel-intensive period of hydrodynamic powertransfer is shorterCO2Benefit:Increase in efficiency fromreduced slippage and smoothershiftingMarketEffectiveness(worst) (best)Availability655Costs:IncreasePenetrationCurrentMaturityLong-TermCost Viability855Technology ApplicabilityVisualizationMulti-damper systems provide earliermuch early TC clutch engagement,however, drivability and limitied ratio coverage have limited the deployment of thistechnology.Technology is best suited for deploymentin 6 speed tranmssions and required tobe integrated during transmission design.Technology provides improved efficiency for automatic transmissions at anincrease in cost.57RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAPicture: www.zf.com*Note: Effectiveness relates to improvement in transmission efficiencyLaunch Device: Magnetic ClutchTechnology Assessment – TransmissionsTechnology and StatusConcept:Using magnetic force to engage the clutchRatings of Technology1 10Base Functioning:Non contact engagement launch device to prevent frictionallossesCO2Benefit:Benefit realized at launchand during transient drivingCosts:Cost impact unclear due to technology in early stage of developmentMarketEffectiveness(worst) (best)Availability435TechnologyApplicabilityPenetrationCurrentMaturityLong-TermCost Viability443ec o ogy pp cab tyVisualizationTechnology is still under early development and it use will be constrained bylimited torque transfer capabilities, uncertian reliability,and significant engineeringdevelopment to mature.Offers opportuinty to remove hydraulic subsystem compoenets and associatedOffersopportuintytoremovehydraulicsub-systemcompoenetsandassociatedlosses. Technology requires current drawto operate, thus idealy suited for highlyelectrified vehicles.Technology best suited to low torque applications with miniminal refinementvehicles and technology will need to be integrated in clean sheet transmissionswith large ratio coverage58RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAPicture: www.uweb.ucsb.eduwithlargeratiocoverage.*Note: Effectiveness relates to improvement in transmission efficiencyShifting Clutch TechnologyTechnology Assessment – TransmissionsTechnology and StatusConcept:Utilizing high thermal capacity technolgoy to reduce plate count andRatings of Technology1 10lower clutch losses during shiftingBase Functioning:Reduced number of plates for shifting process and reducedhydraulic cooling requirements result in increased overall transmissionefficiency for similiar drivability.COBenefit:Through all driving conditionspotentially including idleMarketEffectiveness(worst) (best)Availability65CO2Benefit:ThroughalldrivingconditionspotentiallyincludingidleCosts:similar to AMT costPenetrationCurrentMaturityLong-TermCost Viability556Technology ApplicabilityVisualizationTechnology deployment required during transmission design phase and has beenlimited by industry prioritization tdrivability over shift efficiency.limitedbyindustryprioritizationtodrivabilityovershiftefficiency.Technology will be best suited to smaller vehicle segments due to reduceddrivability expectations – there will be a struggle to develop this technology forhigher torque applications59RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAPicture: www.cerom.lsu.edu*Note: Effectiveness relates to improvement in transmission efficiencySmart Kinematic DesignTechnology Assessment – TransmissionsTechnology and StatusConcept:Using analysis to design for efficiency by selecting the kinematicRatings of Technology1 10relationships to optimize the part operational speeds and torques for efficiencyBase Functioning:Large improvements in efficiency have been noted forclean sheet designs for 6-speed and 8-speed transissionsCO2Benefit:Increase in efficiency reduces fuel consumptionMarketEffectiveness(worst) (best)Availability67Costs:Low cost – analysis part of design phasePenetrationCurrentMaturityLong-TermCost Viability758Technology ApplicabilityVisualizationAll applications and vehicle classes benefit from this design approachBenefits are realized in city and highway drivingBenefitsarerealizedincityandhighwaydriving60RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAPicture: www.adr3.co.uk*Note: Effectiveness relates to improvement in transmission efficiencyDry SumpTechnology Assessment – TransmissionsTechnology and StatusConcept:Dry sump lubrication systerm keepsthe rotating members out of oilRatings of Technology1 10Base Functioning:Reduces losses due to windage and churningCO2Benefit:Fuel efficiency increases with transmission efficiencyCosts:Adds cost (~$50/pc) but as technology matures cost will go downMarketEffectiveness(worst) (best)Availability524PenetrationCurrentMaturityLong-TermCost Viability752Technology ApplicabilityVisualizationAll applications and vehicle classes benefit from this lubrication designMost benefit achieved at higher speedsMostbenefitachievedathigherspeeds61RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAPicture: www.cerom.lsu.edu*Note: Effectiveness relates to improvement in transmission efficiencyEfficient ComponentsTechnology Assessment – TransmissionsTechnology and StatusConcept:Continous improvement in seals,bearings and clutches all aimed atRatings of Technology1 10reducing drag in the systemBase Functioning:A reduction in drag with outa reduction in performanceincreases the efficiency of the transmissionCO2Benefit:Fuel efficiency increases with transmission efficiencyMarketEffectiveness(worst) (best)Availability455Costs:New materials, designs are expensive when they hit market (20%)PenetrationCurrentMaturityLong-TermCost Viability645Technology ApplicabilityVisualizationAll applications and vehicle classes benefit from this lubrication designCity and highway driving fuel effieciency improvementsCityandhighwaydrivingfueleffieciencyimprovements62RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAPicture: www.cerom.lsu.edu*Note: Effectiveness relates to improvement in transmission efficiencySuper FinishingTechnology Assessment – TransmissionsTechnology and StatusConcept:Chemically treating internal gearboxparts for improved surface finishRatings of Technology1 10Base Functioning:Improved surface finish reduces drag which increasesefficiencyCO2Benefit:Fuel efficiency increases with transmission efficiencyCosts:Currently ~$0.50/partMarketEffectiveness(worst) (best)Availability735PenetrationCurrentMaturityLong-TermCost Viability753Technology ApplicabilityVisualizationAll applications and vehicle classes benefit from this lubrication designCity and highway driving fuel effieciency improvementsCityandhighwaydrivingfueleffieciencyimprovements63RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAPicture: www.geartechnology.com*Note: Effectiveness relates to improvement in transmission efficiencyLubricationTechnology Assessment – TransmissionsTechnology and StatusConcept:Development in the area of lubrication properties is ongoingRatings of Technology1 10Base Functioning:New developments in reducing oil viscosity whilemaintaining temperature requirements will have a positive effect ontransmission efficiencyCO2Benefit:Benefit across all vehicle classes and operating conditionsMarketEffectiveness(worst) (best)Availability355Costs:TBDPenetrationCurrentMaturityLong-TermCost Viability545Technology ApplicabilityAll applications and vehicle classesbenefit from improved lubricationsCity and highway driving fuel effieciency improvementsCityandhighwaydrivingfueleffieciencyimprovements64RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPA*Note: Effectiveness relates to improvement in transmission efficiencyTransmission Technology ApplicabilityTechnology Assessment – TransmissionsLaunch Technology



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tsBAutomatic with Torque Converter X X X X X X XA t ti M l T i iXXXXXXXXBaseTransmissionSystemAutomaticManualTransmissionXXXXXXXXDual Clutch X X ? X X X X X XCVT X X X X X X X XSmall Car (Ford Focus) X X ? X X X X X XStandard Car (Toyota Camry) X X X X X X X X XSmall MPV (Saturn Vue) X X X X X X X X XVehicleClassificationFull-sized car (Chrysler 300C) X X X X X X X XLarge MPV (Dodge Grand Caravan) X X X X X X X XTruck (Ford F150) X X X X X X X X65RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAHeavy light-duty truck (Ford F250/F350) X X X X X X X XOutlineIntroductionSpark ignited engine technologiesDiesel engine technologiesHybrid vehicle technologiesTransmission technologiesTransmissiontechnologiesVehicle technologiesConclusions66RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAVehicle Summary (1 of 3)Technology Assessment – VehicleFor a given set of performance targets, a heavyvehicle will require more power, thus consumeR d ti i i htDependant on the compromises (e.g., formanufacturing flexibility, passenger volume etc),d ti i i ht l th hMass Reduction: Material SubstitutionMass Reduction: Component Optimizationmore energy.Reductionsin weightcan occurthrough material substitution (e.g., steel toaluminum).reductionsin weightcan also occurthroughcomponent optimization.Vehicle Aerodynamics; have a greater influenceon drive-cycles with a higher average speed.Dependant compromises chosen, significantGains from active aero through controlled coolingapertures, vehicle ride height control etc are alsopossible.Aerodynamics: ActiveAerodynamics: Passiveopportunity is available in shape development(passive aero).67RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAVehicle Summary (2 of 3)Technology Assessment – VehicleThermo-Electric Generation (TEG); use the heatin exhaust gas (waste energy) to generatel t i it i th S b k ff t Thi bReduced heat loading; by insulating the body ofthe vehicle, using alternative technologies for thel i d til ti t it i ibl tThermo-Electric GeneratorsHVAC System Load Reductionelectricity usingtheSeebeckeffect.This canbeused to drive ancillaries etc, reducing the powerrequirement of the engine.glazing andventilation systems,itis possibletosignificantly reduce the energy requirements ofthe HVAC systems.PHEW!On-going investment in research by the tirecompanies is reducing the energy necessary todrive a vehicle forwards.Tire Rolling ResistanceImproved engine thermal control using an electriccoolant pump, electric fans and electric 3-wayvalve.Intelligent Cooling Systems68RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAVehicle Summary (3 of 3)Technology Assessment – VehicleReplaces FEAD-driven hydraulic steeringassistance with electric motor. Increasinglyl t i ll d diElectric Power Assisted Steeringprevalentin smallandmedium passenger cars(particularly in Europe).69RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAMass Reduction: SubstitutionTechnology Assessment – VehicleTechnology and StatusConcept: Replacement of current material with HSS/AHSS/Al/Mg/CF* etc.Ratings of Technology1 10Base Functioning: Fuel economy improvements are through areduction in therolling resistance losses, i.e., the frictional force is reduced by reducing thenormal force (weight) of the vehicle. A secondary effect is thata lighter vehiclewith lower inertia can use a smaller powertrain to accelerate that reduced mass.COBenefit:A 10% vehicle mass reduction can deliver a 2 74 1% fuelMarketEffectiveness(worst) (best)Availability10108CO2Benefit:A10%vehiclemassreductioncandelivera2.7–4.1%fueleconomy improvement with constant engine size, buta 4.7–6.7% improvementwhen the engine is downsized to maintain constant performance.Costs: Dependant on material selected and price reductions with increasingvolume supply.PenetrationCurrentMaturityLong-TermCost Viability7710Technology ApplicabilityDirect benefit, in growing market use, inall market sectors, and all powertrainvariations.E bl i di iVisualizationEnables enginedown-sizing.Lowers inertia.70RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPA* HSS=High Strength Steel, AHSS=Advanced HighStrength Steel, Al=Aluminum, MG=Magnesium,CF=Carbon FiberPicture: www.automotive.comAluminum-bodied Jaguar XJMass Reduction: OptimizationTechnology Assessment – VehicleTechnology and StatusConcept: Optimization of vehicle, vehicle systems and components for weight,Ratings of Technology1 10not style, manufacturing flexibility orpassenger volume. Examples; 30% wheelmass-saving, change from body-on-frame to unibody for trucks.Base Functioning: Fuel economy improvements are through a reduction in therolling resistance losses, i.e. the frictional force isreduced by reducing thenormal force,(weight)of the vehicle. A secondaryeffect is due to a lighterMarketEffectiveness(worst) (best)Availability1087,( g ) y gvehicle with lower inertia can use a smaller powertrain to accelerate thatreduced mass.CO2Benefit: 10% mass reduction can improve fuel economy by 6.7%.Costs: Can be a cost REDUCTION; optimizing an aluminum wheel with a30% red ction in eight can gi e a cost SAVING of 2540%PenetrationCurrentMaturityLong-TermCost Viability7710Technology ApplicabilityHas the potential to be applied to many areas of a vehicle. Direct benefit, ingrowing market use, in all market sectors, and all powertrain variations.E bl i di iVisualization30%reductioninweightcangiveacostSAVINGof25–40%.Saves 2.5 kg/wheel(24%)Enables enginedown-sizing.Lowers inertia.Additional significant opportunity existswith vehicle size. Passenger vehicleshave grown SIGNIFICANTLY in the past 3decades. The manufacturers say thatthis is due to meet 'market requirements'. If vehicles can be forced to become71RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAsmaller with each successive iteration, rather than bigger, this equates to lighter.This has the additional benefitof smaller frontal area, thus (aero details remainingconstant), the CdA reduces, thus the energy to drive the vehicle through the air isreduced.Picture: various sourcesAerodynamics: PassiveTechnology Assessment – VehicleTechnology and StatusConcept: Substantial opportunitystill exists to lower the coefficient of drag (CD)Ratings of Technology1 10through body shape development, smoothingunder-floors, faring-in wheels etc.Base Functioning: A reduction in CDhas a direct affecton reduction of theforce required to enable forward motion. As drag force is dependant on thesquare of vehicle speed, athigher speeds, the fuel economy gain is increased.COBenefit:A 10% reduction in drag can give a 2 5% improvement in fuelMarketEffectiveness(worst) (best)Availability7510CO2Benefit:A10%reductionindragcangivea2.5%improvementinfueleconomy.Costs: For most items, such as under-floorshields, wheel farings etc, there issome associated on-cost, some items would be low cost or free, such as bodyshape, and some, such as narrowertires, should be a cost reduction.PenetrationCurrentMaturityLong-TermCost Viability777Technology ApplicabilityThe faster the vehicle travels, the greater benefit thisis. Most effective wheresignificant freeway travel is required. Suits all powertrain variations.D d t th d h h i ht lt th itlVisualizationDependanton methods chosen, mayhave some weightpenalty,thus city-onlyvehicles may be penalized.Additional significant opportunity existswith vehicle size. Passenger vehicleshave grown SIGNIFICANTLY in the past 3decades. The manufacturers say thatthis is due to meet "market requirements". Safety notwithstanding, if vehiclesb f d t b ll ith h i it ti th th72RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAcanbeforcedtobecome smaller witheachsuccessiveiteration, ratherthanbigger, frontal area, thus drag force, will reduce (for the same CD).Suggested possible targets; sedans CD=0.25, SUVs CD=0.30, minivans CD=0.29,hatchbacks CD=0.28.Picture: www.green.autoblog.comApteraAerodynamics: ActiveTechnology Assessment – VehicleTechnology and StatusConcept: Opportunity exists to reduceoverall vehicle drag through improvedRatings of Technology1 10control of drag-affecting features (cooling apertures, ride-height etc). Radiatorgrill sizing is designed for maximum thermal rejection; at high ambients / highvehicle loads. Most of the time, the majority of vehicles need much lesscooling. Thus openings can be significantly reduced, reducing vehicle drag.Base Functioning:Areduction in CDhas a direct affecton reduction of theMarketEffectiveness(worst) (best)Availability1072gDforce required to enable forward motion. As drag force is dependant on thesquare of vehicle speed, athigher speeds, the fuel economy gain is increasedCO2Benefit: Active cooling aperture control could give an 8-10% vehicle dragreduction. A 10% reduction in drag cangive a 2.5% improvement in fueleconomyPenetrationCurrentMaturityLong-TermCost Viability7710Technology ApplicabilityThe faster the vehicle is required to travel, the greater benefitthis is. Mosteffective where significant freeway travel is required Suits all powertrainVisualizationyCosts: Some associated on-costeffectivewheresignificantfreewaytravelisrequired.SuitsallpowertrainvariationsHas some (small) weight penalty, thuscity-only vehicles may be penalized;however, city-only cars could have altered drive-cycles, as unlikely to need todrive up mountains inDeath Valley, at GVWP t ti l i t th h li t t t l C0 008 f73RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAPotentialimprovementsthroughcooling system aperture controlCD0.008forsmall and medium cars and 0.03 for large passenger cars and SUVsWhere available, ride heightreduction with increasing speed reduces the effectivefrontal area, and increases tire coveragePicture: www.parkviewbmw.comThermo-Electric GeneratorsTechnology Assessment – VehicleTechnology and StatusConcept: Convert temperature differentials directly intoelectrical energy usingRatings of Technology1 10the Seebeck effect (temperature differential creates current/voltage same as inthermocouples). A Thermo-Electric Generator (TEG) consists of hot side heatexchanger(s), cold side heat exchanger(s),thermoelectric materials (type andsize depends on operating temperature) and compression assembly.Base Functioning: 40% of energyfrom fuel is lostas exhaust heat. TEGs takeMarketEffectiveness(worst) (best)Availability1075ggyadvantage of high engine exhaust gas temperatures (waste energy) to generateelectricity. This can be used to drive accessories or supplement power to anelectric motor.CO2Benefit: Currently expected to givea 5% fuel economy improvement,includingthe effects of the increased vehicle mass from the system(expectedPenetrationCurrentMaturityLong-TermCost Viability774Technology ApplicabilityWell suited to automotive application Recovers some waste energy; which is upVisualizationg y (pto be in range of stop-start, brake regen, FEADelectrification).Costs: Target cost $100/% FE improvement; currently more than this.Wellsuitedtoautomotiveapplication.Recoverssomewasteenergy;whichisupto 40% of the energyfrom burning fuel.More effective at higher temperature differences, thus closer to the engine*, andat high engine loads.Has some weight penalty, however theenergy developed is expected to morethan offset this74RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAthanoffsetthis.Currently under development by BSST, Ford, BMW, Visteon and others. Materialdevelopment underway. Possible tobe on production vehicles around 2015.* May give some packaging challengesPicture: www.customthermoelectric.comReduced HVAC System LoadingTechnology Assessment – VehicleTechnology and StatusConcept: Increasingly aerodynamic vehiclestypically have larger front and rearRatings of Technology1 10windows (for the same class of vehicle). This increases solar loading.Improved thermal insulation reduces solar loading in the Summer and heat lossin the Winter.Base Functioning: Reduced thermal loading/heat loss reduces the energyrequired byHVAC for cooling/heating. Insulatedpanels,GFPs*,doubleglazing,MarketEffectiveness(worst) (best)Availability1078q y g g p, ,g g,reflective films, active ventilation,reduced thermal mass are all possiblemethods of realizing this. Optimization then enables smaller A/C components.CO2Benefit: Suggest 8–10%, application dependant. May enable a doublingof fuel economy. Recent introduction ofSC03 drive cycle will clarify A/C effects.CostsUndefined b t e pected to impro e mpg (or range) for marketabilitPenetrationCurrent**MaturityLong-TermCost Viability774Technology ApplicabilityTechnology based on building applicationsand applies them to automotive use.VisualizationCosts:Undefined,butexpectedtoimprovempg(orrange)formarketability.Use of SC03 cycle may increase demand for reduced HVAC load.BaseVERY applicable to EVs, hybrids and high-mileage (mpg) vehicles, which aremost sensitive to accessory usage as apercentage of the overall vehicle load.Increases mileage and range.The insulation on it's own has some weightpenalty, however it allows reduction inthe sizing of the HVAC components,so potentially weight neutral.75RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAReduces degradation of interior panels dueto thermal loading / IR attack; mayallow for cheaper materials (offsets the cost of the insulation application).* GFP=Gas Filled Panels **Commerciallyavailable technology, to be optimized in vehiclesPicture: NREL Vehicle Ancillary Load Reduction Project CloseOut ReportInsulatedReduced Tire Rolling ResistanceTechnology Assessment – VehicleConcept: Tire rolling resistance is driven by tread and carcass deformation andTechnology and StatusRatings of Technology1 10relaxation as the tire rotates and moves into contact with the road and away.Hysteresis in the tirefrom this deformation creates heat. Reducing the heatgeneration reduces the rolling resistance.Activity is underway to initiate rollingresistance informationlabeling for tires,similar to that alreadyshown for wear,traction and temperatureperformance.MarketEffectiveness(worst) (best)Availability1078y , ppBase Functioning: Fuel economy improvements are through a reduction in therolling resistance losses. Lower rolling resistance reduces the amount of energynecessary to drive a vehicle forwards.CO2Benefit: 10% rolling resistance reduction can improve fuel economy by23% C rrentl a ailable tires can offer 1020% resistance red ction o erPenetrationCurrent**MaturityLong-TermCost Viability7772-3%.Currentlyavailabletirescanoffer10-20%resistancereductionoverconventional equipment. Further rolling resistance reductions of up to 50% arepredicted to be available inthe next 10-15 years.Costs: 10% rolling resistanceapproximates to $5 increase.Technology ApplicabilityVisualizationTechnologyApplicabilityResearch into rolling resistance, andreducing compromises with traction andwear are on-going.Applicable to ALL vehicle types.On medium-duty trucks changing from duallys to single-wides offer a further76RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAOnmedium-dutytrucks,changingfromduallystosingle-widesofferafurtherbenefit of a weight reduction,potentially allowing furtherimproving fuel savings.**Based on current technology, is moving forwards, inall vehicle markets. Further gains dependant onfurther research by the tire companiesPicture: Bridgestone; Tires & Truck Fuel Economy Edition 4Intelligent Cooling SystemsTechnology Assessment – VehicleConcept: Use an electric coolant pumpto remove the FEAD load. ByTechnology and StatusRatings of Technology1 10removing it from FEAD also enables speedcontrol, so ratherthan running at afixed speed related to engine speed, can be run at a speedsuitable to thecurrent vehicle operating condition. Combines well with electric cooling fan andimproved flow routing control.Base Functioning: Standard coolingsystems are sized toprovide coolingatMarketEffectiveness(worst) (best)Availability1073ggy p gmaximum load and ambient conditions. For majority of life of most vehicles, thisis not required. No FEADload, more efficient operating point control. Enablesquicker warm up from cold. Reducesengine friction by enabling optimumengine temperature operation,rather than over-cooling (on passive systems).Furthergainspossible bycontrolled high temperature running,subject toPenetrationCurrentMaturityLong-TermCost Viability777g p y g p g, jsuitable NOx after-treatment systems being fitted (when necessary).CO2Benefit: 3% fuel economy benefiton FTP cycle (assumes gain fromelectric fan etc already taken).Costs: Higher cost (possibly 5-6 times). Provides packaging flexibility as nol d t b i tdVisualizationlonger needstobe engine mounted.Technology ApplicabilityApplicable to all vehicle types using IC enginesEnables improved soak-condition control usingthe enginepump77RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPApg g ppPicture: Pierburg Pump Technology 2008Electric Power Assisted Steering (EPAS)Technology Assessment – VehicleConcept: Uses either rack or column-driveelectric motors to assist driverTechnology and StatusRatings of Technology1 10effort. Replaces engine-driven pump, hoses, reservoir, fluid and hydraulic rack.Base Functioning: Removes load on FEADfor a system which isn't used formuch of the time (unless cornering or at slow speed).CO2Benefit: On typical usage cycle, expect 2–3% improvementMarketEffectiveness(worst) (best)Availability10310Costs: Reduced warranty, reduced servicing. Cost competitive with hydraulicsystems. Enables integration with safety systemssuch as lane departurewarning, stability control (using "anti-skid" feedback) etc.PenetrationCurrentMaturityLong-TermCost Viability8710Technology ApplicabilityCurrently not available for truck weight-class vehicles. Ongoing developments inthis field are making this more likely for all vehicles inthe 2020-2025 time-frameR i d f hi l ith EV f ti lit t ll th t b td i llVisualizationRequiredfor vehicles withanyEVfunctionality,to allowthemtobe steeredin allsituations78RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAPicture: www.trwauto.comVehicle Technology Applicability

u bstitution n t Optimization o n e ring

uction; Material S u uction; Compone n m ics; Passive m ics; Active

l ectric Generators a d Reduction e sistance Reducti o Cooling Systems o wer Assisted Ste e

Mass Red Mass Red Aerodyna m Aerodyna m Thermo-e l HVAC Lo a Rolling R e Intelligent Electric P oSmall Car (Ford Focus)XXXXXXXXXStandard Car (Toyota Camry)XXXXXXXXXSmall MPV (Saturn Vue)XXXXXXXXX

s sificationFull-sized Car (Chrysler 300C)XXXXXXXXXLarge MPV (Dodge Grand Caravan)XXXXXXXXXTruck (Ford F150)XXXXXXXXX

Vehicle Cla s79RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAHeavy light-duty truck (Ford F250/F350)XXXXXXXXXOutlineIntroductionSpark ignited engine technologiesDiesel engine technologiesHybrid vehicle technologiesTransmission technologiesTransmissiontechnologiesVehicle technologiesConclusions80RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPAConclusionsA substantial list of technologies that could offer some benefit to GHG emissionsin the 2020–2025 timeframe was developedThese technologies were assessed by the Ricardo team–These assessments were reviewed with EPA–AdvisoryCommitteeprovided input to assessmentsppBased on EPA feedback, the large list of potential technologies was reduced tothe set considered further in the study, "Computer Simulation of Light DutyVehicle Technologies for Greenhouse Gas Emission Reduction in the 2020–2025 Timeframe"–These are described further in the main program report(Ricardo reference RD.10/157405.8)81RD.11/342305.130 September 2011CG001019 Prepared for SRA and EPA