1 Argonne National Laboratory

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# Evaluation of Fuel Consumption Potential of

Medium and Heavy Duty Vehicles through Modeling and Simulation

Report to National Academy of Sciences
500 Fifth Street NW Washington DC 20001

October 23, 2009

Contract Number: DEPS

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- 001

Prepared by
A ntoine Delorme, Dominik Karbowski, Phil Sharer2 Argonne National Laboratory

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## Contents 1 Introduction

................................ ................................ ................................ ................................ ........ 10
2 Assumptions

................................ ................................ ................................ ................................ ........ 11
2.1 Data Collection Process and Sources

................................ ................................ .......................... 11
2.2 Vehicle Model Description

................................ ................................ ................................ .......... 11
2.3 Vehicle Specifications

................................ ................................ ................................ .................. 13
2.3.1 Pickup Truck Class 2b

................................ ................................ ................................ .......... 13
2.3.2 Utility Truck Clas s 6

................................ ................................ ................................ ............. 13
2.3.3 Transit Bus

................................ ................................ ................................ ........................... 14
2.3.4 Line Haul Class 8

................................ ................................ ................................ .................. 14
3 Model Validation

................................ ................................ ................................ ................................ . 16
3.1 Line Haul Class 8 Model Vali dation

................................ ................................ ............................. 16
3.1.1 Class 8 Validation with West Virginia University

................................ ................................ 16
3.1.2 Class 8 Validation with U.S.EPA

................................ ................................ .......................... 18
3.2 Comparison between PSAT and Published Studies

................................ ................................ .... 18
3.2.1 Weight Reduction

................................ ................................ ................................ ............... 19
3.2.2 Rolling Resistance and Aerodynamics Reduction

................................ ............................... 19
3.2.3 Improved Transmission

................................ ................................ ................................ ....... 21
4 Importance of Metrics

................................ ................................ ................................ ........................ 22
4.1 Limitations of Traditional Fuel Economy Measurements

................................ ........................... 22
4.2 Introducing Payload in Fuel Efficiency Measurements

................................ ............................... 23
5 Energy/ Power Flow Analysis

................................ ................................ ................................ .............. 25
5.1 Steady

- state

................................ ................................ ................................ ................................ 25
5.2 Standard Drive Cycles

................................ ................................ ................................ ................. 28
6 Impact of Drive Cycles on Fuel Consumption

................................ ................................ ..................... 30
6.1 Im pact of Real World Drive Cycles

................................ ................................ .............................. 30
6.1.1 Pickup Truck Class 2b

................................ ................................ ................................ .......... 30
6.1.2 Line Haul Class 8

................................ ................................ ................................ .................. 31
6.2 Issues Following the Trace

................................ ................................ ................................ .......... 32
6.3 Potential Approach to Representing Fuel Efficiency

................................ ................................ .. 33
7 Impact of Single Technologies on Fuel Consumption

................................ ................................ ......... 35
7.1 Aerodynamic

................................ ................................ ................................ ............................... 353 Argonne National Laboratory

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................................ ................................ ................................ ............. 35
7.1.2 Line Haul Class 8

................................ ................................ ................................ .................. 37
7.2 Type of Fuel

................................ ................................ ................................ ................................ . 39
7.2.1 Pickup Truck Class 2b

................................ ................................ ................................ .......... 40
7.2.2 Utility Truck Class 6

................................ ................................ ................................ ............. 42
7.3 Tractor

- trailer Hybridization

................................ ................................ ................................ ....... 44
7.3.1 Hybridization Principles

................................ ................................ ................................ ...... 44
7.3.2 Hardware Design

................................ ................................ ................................ ................. 45
7.3.3 Control Design

................................ ................................ ................................ ..................... 49
7.3.4 Standard Drive Cycles Results

................................ ................................ ............................. 50
7.3.5 Hybridization and Grade

................................ ................................ ................................ ..... 53
8 Impact of Combined Technologies on Fuel Consumption

................................ ................................ .. 58
8.1 Baseline Vehicle Assumptions

................................ ................................ ................................ ..... 58
8.2 Assumptions for Technology Improvements

................................ ................................ .............. 58
8.2.1 Vehicle Weight

................................ ................................ ................................ .................... 59
8.2.2 Aerodynamics

................................ ................................ ................................ ..................... 59
8.2.3 Rolling Resistance

................................ ................................ ................................ ............... 59
8.2.4 Transmission

................................ ................................ ................................ ....................... 60
8.2.5 Engine

................................ ................................ ................................ ................................ .. 60
8.2.6 Hybrid

................................ ................................ ................................ ................................ .. 60
8.3 Fuel Savings for Various Technology Combinations

................................ ................................ ... 61
8.4 Comparison with TIAX Estimates

................................ ................................ ................................ 65
9 Conclusion

................................ ................................ ................................ ................................ ........... 68 Appendix A

– Overview of Drive Cycles

................................ ................................ ................................ ...... 69 Appendix B

– Energy / Power Flow

................................ ................................ ................................ ............. 76
Bus

- 10% Load

................................ ................................ ................................ ................................ ........ 76
Bus

- 50% Load

................................ ................................ ................................ ................................ ........ 78
Bus

- 100% Load

................................ ................................ ................................ ................................ ...... 80 Class 2b (Pick

- up)

- 10% Load

................................ ................................ ................................ .................. 82 Class 2b (Pick

- up)

- 50% Load

................................ ................................ ................................ .................. 84 Class 2b (Pick

- up)

- 100% Load

................................ ................................ ................................ ................ 86 Class 6 (Pick

- up and De livery)

- 10% Load

................................ ................................ ............................... 884 Argonne National Laboratory

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- up and Delivery)

- 50% Load

................................ ................................ ............................... 90 Class 6 (Pick

- up and Delivery)

- 100% Load

................................ ................................ ............................. 92 Class 8 (Tractor

- Trailer)

- 10% Load

................................ ................................ ................................ ........ 94 Class 8 (Tractor

- Trailer)

- 50% Load

................................ ................................ ................................ ........ 96 Class 8 (Tractor

- Trailer)

- 100% Load

................................ ................................ ................................ ...... 98 Bibliography

................................ ................................ ................................ ................................ .......... 1005 Argonne National Laboratory

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## List of Tables

Table 1: Pickup Truck Class 2b Assumptions

................................ ................................ ............................... 13 Table 2: Utility Class 6 Truck Assumptions

................................ ................................ ................................ .. 14 Table 3: Transit Bus Assumptions

................................ ................................ ................................ ............... 14
Table 4: Line Haul Class 8 Truck Assumptions

................................ ................................ ............................ 15
Table 5: Details of the Peterbilt Truck and Test Conditions

................................ ................................ ....... 16
Table 6: Peterbilt Truck PSAT Validation with C hassis (Test weight 56000 lb)

................................ ........... 17
Table 7: Navistar ProStar Truck PSAT Validation

– Fuel Economy (mpg)

................................ .................... 18 Table 8: Impact of Improved Tr ansmission on Fuel Consumption for a Class 8 Truck

............................... 21 Table 9: Vehicle Applications, Cycles and Weight Assumptions used in Metric Study

.............................. 22 Table 10: Utility Class 6 Truck Vehicle Assumptions for Drag Coefficient Study

................................ ........ 35 Table 11: Utility Class 6 Truck Drive Cycle and Steady States Assumptions for Drag Coefficient Study

.... 35 Table 12: Line Haul Class 8 Truck Vehicle Assumptions for Drag Coefficient Study

................................ ... 37 Table 13: Line Haul Class 8 Truck Drive Cycle and Stea dy States Assumptions for Drag Coefficient Study 38 Table 14: Gasoline and Diesel Assumptions for the Pickup Truck Class 2b

................................ ................ 40
Table 1 5: Fuel Consumption of Gasoline and Diesel Class 2b Vehicles for different Drive Cycles

............. 41 Table 16: Gasoline and Diesel Assumptions for the Utility Truck Class 6

................................ ................... 42 Table 17: Fuel Consumption of Gasoline and Diesel Class 6 Vehicles for different Drive Cycles

............... 43 Table 18: Summary of component sizes

................................ ................................ ................................ ..... 49 Table 19: Summary of Control Strategy

................................ ................................ ................................ ...... 50 Table 20: Main Characteristics of Drive cycles

................................ ................................ ........................... 51
Table 21 : Assumptions for the Pickup Class 2b used in the study of Technology Combination impact on Fuel Consumption

................................ ................................ ................................ ................................ ....... 58 Table 22: Impact of Weight Reduction alone on Fuel Consumption for the Class 2b

................................ 59 Table 23: Impact of Aerodynamics alone on Fuel Consumption for the Class 2b

................................ ...... 59 Table 24: Impact of Rolling Resistance alone on Fuel Co nsumption for the Class 2b

................................ 59 Table 25: Impact of Transmission alone on Fuel Consumption for the Class 2b

................................ ........ 60 Table 26: Impact of Engin e Efficiency alone on Fuel Consumption for the Class 2b

................................ .. 60 Table 27: Impact of Hybridization on Fuel Consumption for the Class 2b

................................ ................. 616 Argonne National Laboratory

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## List of Figures

Figure 1: Example of Vehicle Model in PSAT

................................ ................................ .............................. 11 Figure 2: PSAT GUI Example

................................ ................................ ................................ ........................ 12 Figure 3: Peter bilt Truck

................................ ................................ ................................ .............................. 16 Figure 4: Peterbilt Truck Engine Fuel Rate Comparison

................................ ................................ ............. 17 Figure 5: Navistar ProStar Truck Engine Speed Comparison

................................ ................................ ...... 18 Figure 6: Impact of Gross Vehicle Weight Reduction on Fuel Consumption for a Class 8 Truck

................ 19 Figure 7: Impact of Drag Coefficient Reduct ion on Fuel Consumption (Rolling Resistance fixed at 0.0055)

................................ ................................ ................................ ................................ ................................ .... 20 Figure 8: Impact of Drag Coefficient Reduction on Fuel Consumption (Rolling Resistance fixed at 0.0045)

................................ ................................ ................................ ................................ ................................ .... 20 Figure 9: Comparison of Fuel Economy and Fuel Consumption

................................ ................................ . 22 Figure 10: Comparison of Payload Fuel Economy and Load Specific Fuel Consumption

........................... 23 Figure 11: Comparison of Fuel Economy and Load Specific Fuel Consumption for a Class 8 Truck

........... 24 Figure 12: Power Flow Diagram for a Class 8 Truck ( Steady

- State, 65 mph, 70% load)

............................. 26 Figure 13: Distribution of losses for a Class 8 Truck for Various Steady

- State Speeds (70% load)

............. 26 Figure 14: Distribution of losses for a Class 8 at 65 mph for 10% load (Right) and 100% Load (Left)

........ 27 Figure 15: Distribution of losses for a Class 8, Bus, and Class 6 at 50 mph at GVWR

................................ . 27 Figure 16: Distribution of losses for a Class 2b at 50 mph at GVWR

................................ .......................... 28 Figure 17: Power Flow Diagram for a Bus on CBD cycle (50% load)

................................ ........................... 28 Figure 18: Power Flow Diagram for a Class 6 on HTUF cycle (75% load)

................................ .................... 29 Figure 19: Power Flow Diagram for a Class 8 on HHDDT 65 cycle ( 72% load)

................................ ............ 29 Figure 20: Power Flow Diagram for a Class 8 on UDDS Truck cycle (72% load)

................................ ......... 29 Figure 21: Fuel Consumption as a function o f Average Cycle Vehicle Speed for a sample of Real World Drive Cycles for a Pickup Class 2b

................................ ................................ ................................ ............... 30 Figure 22: Fuel Consumption as a function of Average Cycle Vehicle Speed for a sample of Real World Drive Cycles for a Class 8 Truck

................................ ................................ ................................ ................... 31 Figure 23: Automatic vs Manual Transmission for a Class 8 Truck

................................ ............................. 32 Figure 24: Fuel Consumption as a function of Steady State Vehicle Speeds for different Payloads

.......... 337 Argonne National Laboratory

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– October 2009 Figure 25: Fuel Consumption as a function of Average Cycle Vehicle Speed for RWDC and Steady States for a Pickup Truck Class 2b

. ................................ ................................ ................................ ......................... 34 Figure 26: Impact of Drag Coefficient on Class 6 Fuel Consumption for various Drive Cycles and Steady States.

................................ ................................ ................................ ................................ ......................... 36 Figure 27: Perce nt of Fuel Saved by Reducing the Drag Coefficient for Each Drive Cycle and their Steady State Speed Counterpart for Class 6

................................ ................................ ................................ ........... 37 Figure 28: Impact of Drag Coefficient on Class 8 Fuel Consumption fo r various Drive Cycles and Steady States.

................................ ................................ ................................ ................................ ......................... 38 Figure 29: Percent of Fuel Saved by Reducing the Drag Coefficient for Each Drive Cycle and their Steady State Speed Counterpart for Class 8

................................ ................................ ................................ ........... 39 Figure 30: Fuel Consumption of Gasoline and Diesel Class 2b Vehicles for different Drive Cycles

............ 42 Figure 31: Fuel Consumption of Gasoline an d Diesel Class 6 Vehicles for different Drive Cycles

.............. 44 Figure 32

– Schematic of the series

- parallel configuration (full

- hybrid)

................................ .................... 47
Fi gure 33

– Schematic of the starter

- alternator configuration (mild

- hybrid)

................................ ............ 48 Figure 34: Fuel Consumption of conventional and hybrid trucks on standard cycles

................................ 51 Figure 35: Fuel Saved by hybrid trucks with respect to conventional truck, on standard cycles

............... 52 Figure 36: Percentage of Braking Energy Recovered at the Wheels

................................ .......................... 52 Figure 37: Average Engine Efficiency of conventional and hybrid trucks on standard cycles

.................... 53 Figure 38: Sectional View of roads (partial) with the same maximum (3%) grade but 3 different hill periods

................................ ................................ ................................ ................................ ........................ 54 Figure 39: Motor use uphill and downhill on a road with a hill period of 1 km, and 2.5% (left) or 4% (right) maximum grade, for a full

- hybrid

................................ ................................ ................................ .... 55 Figure 40: Section View of the actual trip for a conventional and a full

- hybrid truck (4% maximum grade, 1 km hill period)

................................ ................................ ................................ ................................ .......... 56 Figure 41: Fuel Consumption of Conventional, Mild

- hybrid and full hybrid trucks on a sinusoidal road as a function of grade (and for various hill periods).

................................ ................................ ......................... 57 Figure 42: Fuel savings of hy brid trucks with respect to conventional truck as a function of maximum grade (for various hill periods)

................................ ................................ ................................ .................... 57 Figure 43: Fuel Consumption Savings by combining Aerodynamics and Weight improvements o n a Conventional and Hybrid Baseline.

................................ ................................ ................................ ............. 62 Figure 44: Fuel Consumption Savings by combining Aerodynamics, Rolling Resistance and Weight improvements on a Conventional and Hybrid Baseline.

................................ ................................ ............ 63 Figure 45: Fuel Consumption Savings by combining Aerodynamics, Rolling Resistance, Transmission and Weight improvements on a Conventional and Hybrid Baseline.

................................ ................................ 648 Argonne National Laboratory

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................................ ................................ ................................ ................................ ...................... 64 Figure 47: Fuel Consumption Savings by combining all technology i mprovements and hybridization on a Conventional Baseline.

................................ ................................ ................................ ................................ 65 Figure 48: Fuel Consumption Savings of Improvement Package using Simulation or TIAX Estimates

....... 66 Figure 49: Fuel Consumption Savings of Improvement Package using Simulation or TIAX Estimates when using the same baseline Transmission

................................ ................................ ................................ ........ 679 Argonne National Laboratory

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## Acknowledgement

This report was prepared for the National Academy of Sciences (NAS) as part of their prime contract with the National Highway Traffic Safety Administration (NHTSA) to assess fuel consumption technologies for medium and heavy duty vehicles. The Transportation Research Board’s Division on Engineeri ng and Physical Sciences was responsible for this work and assigned the effort to the Board on Energy and Environmental Systems. The project identifier is BEES

- J

- 08

- A. The NAS project director was Mr. Duncan Brown and the ANL principal investigator was Phi l Sharer . Dr. Andrew Brown, Jr. chaired the NAS committee, initiated the project, and provided valuable guidance to help direct and focus ANL’ s research along with the other members of the committee. We would also like to thank all the companies who provid ed state

- of

- the

- art component data and control logic to allow proper modeling and simulation of numerous medium and heavy duty trucks applications.10 Argonne National Laboratory

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## 1 **Introduction**

The main objective of this report is to provide quantitative data to support the Committee in its task of establishing a report to support rulemaking on medium

- and heavy

- duty fuel efficiency improvement. In particular, it is of paramount importance for the Committee to base or illustrate their conclusions on established models and actual state

- of

- the art data. The simulations studies presented in the report have been defined and requested by the members of the National Academy committee to provide quantitative inputs to support their recommendations. As such, various technologies and usage scena rios were considered for several applications. One of the objective is to provide the results along with their associated assumptions (both vehicle and drive cycles), information generally missing from public discussions on literature search. Finally, the advantages and limitations of using simulation will be summarized. The study addresses several of the committee tasks, including:

- Discussion of the implication of metric selection

- Assessing the impact of existing technologies on fuel consumption through e nergy balance analysis (both steady

- state and standard cycles) as well as real world drive cycles

- Impact of future technologies, both individually and collectively11 Argonne National Laboratory

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## 2 **Assumptions**

**2.1 Data Collection Process and Sources** 

The vehicle configurations and technical specifications described below were gathered from different sources. Various collaborations with component and vehicle manufacturers as well as literature review were considered

. Although eight vehicle applications were modeled , only four of them were actu ally simulated due time constraints and greater interest from the Committee. Therefore, we will only provide the assumptions for these four vehicles: Pickup T ruck (C lass 2b ) , Utility Truck (C lass 6 ) , Transit Bus (Class 8) and Line Haul Truck (Class 8)

. 

### 2.2 **Veh icle**  **Model Description**

The Powertrain Analysis Toolkit (PSAT), developed by Argonne National laboratory, has been used to perform the vehicle simulations. PSAT is a forward

- looking simulation package (also called driver

driven). A driver model follows any standard or custom driving cycle, sending a power demand to the vehicle controller, which, in turn, sends a demand to the propulsion components. Component models react to the demand and feed back their status to the vehicle controller, and the process ite rates to achieve the desired result. Each component model is a Simulink/Stateflow box, which uses the Bond gra ph formalism

. The components boxes are then “assembled” according to the powertrain configuration chosen by the user in the Graphical User Interf ace (GUI)

.

Figure 1 : Example of Vehicle Model in PSAT Clutch command Motor command

Shift command Brake command

Engine command Accelerator/Brak e pedal

Controller Commands12 Argonne National Laboratory

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– October 2009 The user

- friendly GUI ( Figure 2 ) allows the user to build a vehicle model within a few minutes.
First, the user selects the drivetrain configuration. Each configura tion is built according to user input so that vehicle architectures can be compared and the most appropriate one selected. More than 300 pre

selected configurations are available. Secondly, the user selects a model for each powertrain component, its initi alization file, and tunes the initial parameters. Similarly, the controller strategy is chosen and tuned. The user then selects the combination of cycles to be simulated , and finally launches the simulation. Once the simulation is completed , the GUI provid es the user with a wide range of plots and calculation, particularly useful for analysis.

Figure 2 : PSAT GUI Example The plant models used in the study were based on steady

- state lookup tables to represent the losses. The shift ing algorithm and vehicle level control logics have been developed to be adapted to any combination of components and validated for several applications with OEMs. All the results are provided for hot operating conditions.13 Argonne National Laboratory

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### 2.3 **Vehicle Specifications**

**2.3.1 Pick**  **up Truck Class 2b** 

Because this vehicle class is close to its light duty counterpart (Class 2a), the assumptions used were all derived from the literature. The amount of information for this application was widely available

. The assumptions for the Pickup Truck were based on the GMC Sierra 2500 HD [ 1 ] . This vehicle has a Gross Vehicle Weight ( GVWR ) of 4172 kg and consequently belongs to the class 2b. Furthermore, as shown later in paragraph 7.2 , this particular pickup also offer the advantage of offering specifications for both gasoline and diesel configurations. T able 1 summarizes the main assumptions used. The engines specified by the manufacturer were not available in the modeling and simulation da tabase . As such, the Cummins ISB 6.7L and the GM LM7 5.3L were selected as alternatives. For more details about how these engines were scaled to match the manufacturer specifications, please see paragraph 7.2

. Unless specified, the pickup truck class 2b was simulated with the diesel engine.
Component Model Characteristics Engine Diesel: Cummins 6.7L 272kW Gasoline: GM LM7 5.3L 276kW Transmission Allison 1000

- Automatic 6 Speed Ratios : 3.1 , 1.81 , 1.41 , 1, 0.71, 0.61 Final Drive Ratio 3.73 Tire P245/75/R16 Radius = 0.387 m Rolling Resistance = 0.007 Vehicle Losses Drag Coefficient = 0.44 Frontal Area = 3.233 m 2 Curb Weight 2659 kg GVWR 4172 kg Max Payload 1513 kg Table 1 : Pickup Truck Class 2b Assumptions
**2.3.2 Utility Truck Class 6** 

The following ass umptions for the Utility Truck c lass 6 are based on the GMC C

- series C5C042 2WD regular cab. As for the pickup truck class 2b, this brand and model of truck has the advantage of being produced with both g aso line and diesel options , which will be used later in paragraph 7.2 . The Cummins ISB 6.7L for diesel and the GM LM7 5.3L were used and scaled to match specifications. The vehicle losses specifications (drag coefficient and fr ontal area) were derived from the PACCAR T270 truck. Unless specified, the Utility Truck class 6 was simulated with the diesel engine.14 Argonne National Laboratory

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– October 2009 Component Model Characteristics Engine Diesel : Cummins ISB 6.7L 246 kW Gasoline : GM LM7 5.3L 240 kW Transmission Alli son 1000 Series Automatic 6 Speed Ratios : 3.1 , 1.81 , 1.41 , 1, 0.71, 0.61 Torque Converter AllisonTC211 Final Drive Ratio Diesel : 4.8 8 Gasoline : 5.29 Tire P245/70/R19.5 Radius = 0. 419 m Rolling Resistance = 0.009 Vehicle Losses Drag Coefficient = 0 .6 Frontal Area = 9 m 2 Curb Weight 4472 kg GVWR 11791 kg Max Payload 7319 kg Table 2 : Utility Class 6 Truck Assumptions
**2.3.3 Transit Bus** 

The assumptions shown below for the transit bus application are all based on the 40 ft Orion V model. The curb weight was set to 13061 kg (28800 lb ) and the GVWR to 18412 kg (40,600 lb ) as specified by the manufacturer.
Component Model Characteristics Engine Cummins ISL 8.9L 243 kW Transmission Allison B500 Automatic 6 Speed Ratios : 3. 51 , 1.91 , 1.43 , 1, 0.74, 0.64 Torque Converter AllisonTC54 1 Final Drive Ratio Diesel : 4. 33 Tire 12R22.5 Radius = 0. 541 m Rolling Resistance = 0.00 8 Vehicle Losses Drag Coefficient = 0.65 Frontal Area = 7.96 m 2 Curb Weight 13061 kg GVWR 1 8412 kg Max Payload 5 4 passengers @ 150 lb = 3673 kg Table 3 : Transit Bus Assumptions
**2.3.4 Line Haul Class 8** 

The Line Haul class 8 truck was designed through collaborations with component and vehicle manufacturers . The baseline truck which was used to coll ect component data was a Kenworth T660 with a GVWR of 36280 kg ( 80,000 lb )

. This model of truck is equipped with a Cummins ISX 14.9L engine15 Argonne National Laboratory

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– October 2009 available in the PSAT database. A 10 speed manual transmission was selected due to its wide usage for the applicatio n.
Component Model Characteristics Engine Cummins ISX 14.9L 317 kW Transmission Fuller FRM 15210B Manual 10 Speed Ratios : 1 st gear 14.8, 10 th gear 1.0 Final Drive Ratio 2.64 Tire P295/75 R22.5 Radius = 0. 51054 m Rolling Resistance = 0.00 5 Vehicle Losse s Drag Coefficient = 0.565 Frontal Area = 10.38 m 2 Curb Weight 8936 kg(tractor)

– 6759 kg(empty trailer) GVWR 36280 kg Max Payload 20586 kg Table 4 : Line Haul Class 8 Truck Assumptions16 Argonne National Laboratory

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## 3 **Model Validation**

The purpose of this chap ter is to provide examples of vehicle validation using PSAT for the applications considered. While additional validation s have been performed in collaboration with

manu facturers, the results could not be shared to the proprietary information


### 3.1 **Line Haul Cla ss 8 Model Validation** 

**3.1.1 Class 8 Validation with West Virginia University** 

A model of a 1996 long haul Peterbilt, tested at West Virginia University, was developed and validated. Figure 3 shows the Peterbilt truck used in this research. Table 5 presents the d etails of the vehicle configuration.

Figure 3 : Peterbilt Truck

Table 5 : Details of the Peterbilt Truck and Test C onditions Description Model Characteristics Vehicle Manufacturer Peterbilt

Vehicle Model Year 1996 Gross Vehicle Weight 20909 kg / 46000 lb (tractor only) 36364 kg / 80000 lb (assumed value with trailer) Vehicle tested weight 25455 kg / 56000 lb Odometer Reading (mile) 441097 Transmission Type Manual Transmission Configuration 18 speed Engine Type Caterpillar 3406E17 Argonne National Laboratory

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– October 2009 Engine Model year 1996 Engine Displacement (liter) 14.6 Number of Cylinders 6 Primary Fuel D2

Test Cycle UDDS (also termed TEST_D) Test Date 4/21/06

As for any validation, the critical aspect is to match the efforts a nd flows of the different components along with the fuel rate at every sample time of the test. Figure 4 show a good correlation between the instantaneous fuel rates from simulation and test.

Figure 4 : Peterbilt Truck Engine Fuel Rate Comparison Table 6 shows the summary of the fuel consumption results for the test conditions considered.

Table 6 : Peterbilt Truck PSAT Validation w ith Chassis (Test weight 56000 lb)

Parameters Measured Simulation Relative Erro r UDDS Cycle (mile) 5.44 5.37 1.29 Fuel Econ. (MPG) 3.82 3.82 0.00 Fuel Cons (Gal/100 mile) 26.17 26.17 0.00 Fuel Mass (kg) 4.58 4.52 1.31 Eng. Fuel Rate (g/s) 4.40 4.30 1.27

CO 2 (g/mile) 2639.8 2685.5

- 1.73 

### 0 500 1000 1500 0 5 10 15 20 25

UDDS Time (s)Engine Fuel Rate (g/s) 

### Measured PSAT18 Argonne National Laboratory

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– October 2009 **3.1.2 Class 8 Validation with U.S.EPA** 

Anot her long haul application was validated in collaboration with the U.S. Environmental Protection Agency. The vehicle, tested at SouthWest Research Institute (SwRI) was modeled in PSAT and validated using dynamometer test data. The truck is a Navistar ProSta r with a Cummins ISX ST400 and a 10 speed manual transmission from EATON. Figure 5 shows the close correlation between the simulated and measured engine speed. The other components effort and flow were matched as well resulting in good comparison for the f uel economy for several cycles as shown in Table 7.

Figure 5 : Navistar ProStar Truck Engine Speed Comparison

Table 7 : Navistar ProStar Truck PSAT Validation

– Fuel Economy (mpg) Cycle Measured Simulation Re lative Error 7D 6.03 5.99 0.6

8D 7.31 7.1 2.8



### 3.2 **Comparison between PSAT and Published Studies** 

Since a large portion of the study focus es on evaluating the impact of several technologies on fuel consumption, i n this section , we will vary a few parameters that are essential to fuel consumption19 Argonne National Laboratory

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– October 2009 reduction and compare the results with other published studies. Additional simulations will then be performed to (a) verify some published values form the literature as well as (b) generate new analysis to generate values for missing applications or technologies.

**3.2.1 Weight Reduction** 

Simulations were performed to assess the impact of GVWR reduction on fuel consumption. The baseline truck had a GVWR of 36280 kg . The vehicle was simulated for different weight on the HHDD T65 drive cycle which combines the various HHD DT cycles developed by the CARB [ 2 ]

. The fuel consumption results and the percentage of fuel saved are shown below along with estimates by S w R I in the NESCCAF study ( Presentation to NAS

- December 4 2008)

.

Figure 6 : Impact of Gross Vehicle Weight Reduction on Fuel Consumption for a Class 8 Truck The simulations show a 9.6% fuel consumption reduction when decreasing the GVWR from 80,000 to 65,000 lb. In othe r terms, we can expect a 0.6% fuel saving for every 1,000 lb weight reduction. In comparison, the NESCCAF study estimates were 0.5% and the Smartway ones 0.4%. However, it is important to keep in mind that the use of different engine maps, transmissions, s hifting schedules, drive cycles or accessories can affect these estimates.

**3.2.2 Rolling Resistance and Aerodynamics Reduction** 

Simulations were performed to assess the impact of drag coefficient reduction on fuel consumption. The baseline truck is a line haul c lass 8 with a GVWR of 36280 kg , a drag coefficient of 0.63 and a rolling resistance coefficient of 0.0068. As for the previous paragraph, the truck was simulated on the HHDDT65 cycle and the simulation results were compared with other studies. 

### 0 2 4 6 8 10 12

16 16.5

17 17.5

18 18.5

19 19.5

29478 kg (65000 lb) 31745 kg (70000 lb) 34013 kg (75000 lb) 36280 kg (80000 lb)Percent of fuel savedFuel Consumption(gallon/100miles)



## GVWR (lbs) Fuel Consumption

Percent Fuel Saved

Percent Fuel Saved (NESCCAF Estimate)20 Argonne National Laboratory

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Figure 7 : Impact of Drag Coefficient Reduction on Fuel Consumption (Rolling Resistance fixed at 0.0055)

Figure 8 : Impact of Drag Coefficient Reduction on Fuel Consumption (Rolling Resistance fixed at 0.0045) 

### 0 5 10 15 20 25

0 5 10 15 20 25

0.4 0.45 0.5 0.55 0.6 0.63Percent fuel savedFuel Consumption (gallon/100miles)



## Drag Coefficient 

# Impact of Drag Coefficient Reduction on Fuel Consumption (Crr=0.0055)

Fuel Consumption

Percent Fuel Saved

Percent Fuel Saved (NESCCAF Estimate)

0 5 10 15 20 25 30 35

0 5 10 15 20 25

0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.63Percent Fuel SavedFuel Consumption (gallon/100miles)



## Drag Coefficient 

# Impact of Drag Coefficient Reduction on Fuel Consumption (Crr=0.0045)

Fuel Consumption

Percent Fuel Saved

Percent Fuel Saved (NESCCAF Estimate)21 Argonne National Laboratory

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– October 2009 Figure 7 depicts the set of simulations which used a fixed rolling resistance of 0.0055. T he drag coefficient varied from 0.63 to 0.4. Results show that reducing the drag coefficient from 0.63 to 0.5 lead to a 15.2% fuel consumption red uction. In comparison, t he NESCCAF study indicated 14% fuel savings for the same scenario.
Figure 8 shows a more aggressive scenario as the rolling resistance value is set to 0.0045 and the drag coefficient is then lowered from 0 .63 to 0.3. In this case, reducing the drag coefficient from 0.63 to 0.4 leads to a 26.7% fuel consumption reduction. Again, these results are close to the NESCCAF estimates which indicated 24.6% fuel savings for this situation.

**3.2.3 Improved Transmission** 

Usin g a line haul class 8 truck, we studied the impact of increasing the number of transmission gears on fuel consumption. Based on two existing class 8 truck configurations, we simulated two vehicles were equipped with a 10 spe ed manual and an 18 speed manual transmission respectively. The drive cycle used was the HHDDT65 and the trucks w ere simulated at a GVWR of 36280 kg

. The results are shown in Table 8.

Table 8 : Impact of Improved Transmission on Fuel Consumption for a Class 8 Truc k Component Baseline Truck Improved Truck Transmission Fuller FRM 15210B Manual 10 Speed Ratios : 1 st gear 14.8, 10 th gear 1.0 Fuller RTLO 18918B Manual 18 Speed Ratios : 1 st gear 14.4, 10 th gear 0.73 Final Drive Ratio 2.64 3.55 Simulation Vehicle Mass 36280 kg 36280 kg

Fuel Consumption (gallon/100mile) 18.42 18.38

The simulations resulted in no significant changes in fuel consumption. This study is very sensitive to the shifting logic design and to the use of a drive cycle including grade

. Indeed, by tuning the shifting control parameters to en sure that the 18 speed shifts at lower engine speeds than the 10 speed, the fuel saving could reach 1 to 2 % . Estimates collected from OEMs by TIAX mentioned a 1 to 5% fuel consumption reduction which is in the s ame range as the simulation predictions.22 Argonne National Laboratory

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## 4 **Importance of Metrics**

**4.1 Limitations of Traditional Fuel Economy Measurements** 

The use of fuel economy versus fuel consumption is very often discussed for light duty vehicles. Due to its inverse relationship with fue l consumption, fuel economy fails to accurately represent the actual saving in fuel. The main issue using fuel economy is that a 10 mpg reduction will not be translated in the same amount of fuel saving if the original value was 40 or 20. The use of fuel c onsumption is thus often recommended especially for a comparison between several vehicles. However, for heavy duty vehicles even fuel consumption itself has some limitations that are discussed below

. Four different vehicles are considered: pickup class 2b, utility class 6, transit bus and line haul class 8. Each vehicle is simulated on its specific drive cycle at two different payloads: 10% payload and GVWR. The following table summarizes the simulation assumptions.

Table 9 : Vehicle Applications, Cycles and Weight Assumptions used in Metric Study Pickup Truck Utility Transit Bus Line Haul Cycle(s) used UDDS+HWFET HTUF P&D Class6 Manhattan HHDDT65 Weight @ 10% payload (kg) 2810 5204 13428 17753 Weight @ GVWR (kg) 4172 11791 18412 3 6280

Figure 9 : Comparison of Fuel Economy and Fuel Consumption
On Figure 9 , we repr esented both fuel economy in mile/gallon and fuel consumpti on in gallons/100miles for the four vehicle applications . T he two extremities of the blue bar are for the 10% payload and GVWR simulations. One notices that from one vehicle class to another, the fuel efficiency23 Argonne National Laboratory

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– October 2009 differences are not clearly shown. For example, when looking at the fuel consumption plot, it appears t hat the class 6 and class 8 truck are as fuel efficient. However, these two vehicles do not realize the same work, i.e. they do not carry the same weight. Furthermore, when considering the class 2b application, the impact of driving with 10% payload or at GVWR is not significantly emphasized since the bar on the fuel consumption plot is almost reduced to a single point. Consequently, the use of payload becomes necessary to fairly and accurately measure fuel efficiency and compare heavy duty vehicles.



### 4.2 **Intro ducing Payload in Fuel Efficiency Measurements** 

Using the same vehicle simulations as for the previous paragraph, we will now represent the results using payload fuel economy (mpg multiplied by the payload weight) and load specific fuel consumption (fuel c onsumption divided by the payload weight). The unit s are respectively “ton.mpg” and “gallons/100miles/ton” using metric tons.

Figure 10 : Comparison of Payload Fuel Economy and Load Specific Fuel Consumption
The trend shown in Figure 10 is completely different than what was depicted on Figure 9 . The fuel consumption variations due to different payload are now clearly described. For example, according to the load specific fuel cons umption ( LSFC ) graph (on the right), the transit bus is almost 10 times more fuel efficient when fully loaded than when carrying 10% load. T he line haul class 8 truck is now the most fuel efficient vehicle among the four applications as the amount of fuel consumed in regard to the load carried is the best. These four applications can now be fairly compared by taking the payload into consideration when measuring their fuel efficiency.24 Argonne National Laboratory

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– October 2009 Figure 11 : Comparison of Fuel Economy and Load Specific Fuel Consumption for a Class 8 Truck Figure 11 compares the fuel economy and LSFC for different payloads . In this case, a class 8 line haul truck was simulated at various weights (0, 10, 20, 30...90, 100% payload) on the H HDDT65 cycle and its fuel economy as well as its LSFC were reported on the graph. Note that in order to avoid division by zero, the LSFC starts at 10% payload. When solely looking at the fuel economy, the graph analys is would tell us that carrying an empty trailer or the full load would only have a change of 25% in the fuel efficiency. However if LSFC is considered, the change in fuel efficiency between 10% load and GVWR is nearly 90%. This better depicts the impact of the payload on the efficiency of the w ork done by the truck.25 Argonne National Laboratory

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## 5 **Energy / Power Flow**  **Analysis**

To improve the fuel consumption of specific vehicles, one needs to understand the origin of the losses throughout the drivetrain for different operating conditions (e.g., speed, grade). This paragraph describes the methodology used to generate the energy / power flow analysis for several applications on both steady

- states and drive cycles. While the process is described below for a specific example, the complete set of results is provided in Appendix 1

. 

### 5.1 **Steady**

**- state** 

All heavy

- duty vehicles classes described in section 2.3 were simulated and analyzed at various steady

- state speeds and load s . Even though the simulation s included an acceleration phase to avoid initialization issues, the numerical value s provided are solely based on the steady

- state part of the cycle, during which the vehicle speed is constant. The speed ranges simulated ranged from 20 to 50 mph for the bus, 30 to 70 mph for the class 2b and clas s 6 , and 50 to 70 mph for the class 8. The load, meaning the payload, is hereafter expressed in percentage of the maximum payload. 0% means that the simulation vehicle weight is the weight of the empty vehicle, while 100 % means the GVWR. An example of pow er flow diagram is displayed on Figure 12

. Average power, an intensive physical property, is preferred to simply energy, an extensive physical property. In the case of a steady

state, the average power is also the instantaneous power. The diagram can simply become an energy balance by multiplying the average power by the trip time, or an energy consumption balance by dividing the average power figures by the average speed. For example, in the case of Figure 12 , the engine input average power is 395 kW, which at 65 mph average speed is equivalent to 395/65 = 6 kWh/mi.
A block represents a power converting component (engine, motor, transmission or axle), an accessory (mechani cal or electrical) or a loss due to the interaction with environment (tires/rolling resistance, aerodynamic drag). For an automatic transmission ( class 2b, class 6, bus), the “transmission” block encompasses the gearbox and the torque converter. “Axle” inc ludes the final drive(s) and the transfer case when there is one (class 8).

The a rrows represent the power flow; their width is proportional to the energy / average power exchanged, though arrow sizes are not comparable between different power flow diagram s
. Horizontal arrows represent exchanged flows between blocks, while vertical ones represent losses. The leftmost

arrow which is the input to both the engine and the entire system represents the power contained in the fuel . Each block contains a “%Loss” v alue, which represents the contribution to the total losses (i.e. ratio of component loss to engine input), as well as efficiency for power converting devices.26 Argonne National Laboratory

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– October 2009 Figure 12 : Power Flow Diagram for a Class 8 Truck (Steady

- State, 65 mph, 70% load) Various power flow diagrams are available in Appendix A

. Other diagrams are available to analyze the sensitivity to load, speed or application. For example, Figure 13 illustrates the impact of speed on the repartition of losses. Pie charts can show the impact of load ( Figure 14 ) or application ( Figure 15 , Figure 16 ).

Figure 13 : Distribution of losses for a Class 8 Truck for Various Steady

- State Speeds (70% load) engine **η** =41.9% %Loss=58.1% 395 kW

230 kW mech. acc. **η** =N/A %Loss=1.3% 166 kW

5.2 kW elec. acc. **η** =N/A %Loss=0.1% 161 kW

0.36 kW gearbox **η** =98.1% %Loss=0.8% 160 kW

3.04 kW axle **η** =98% %Loss=0.8% 157 kW

3.13 kW tires **η** =N/A %Loss=16.5% 154 kW

65.4 kW aero **η** =N/A %Loss=22.4% 88.6 kW

88.5 kW

40 50 60 70 80 0 20 40 60 80 100 120

Average speed (mph)Contribution to total loss (%) Repartition of losses - class8 / SS / 70 % Load engine mech. acc. elec. acc. gearbox axle tires
aero Total losses x.1 (kW)27 Argonne National Laboratory

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– October 2009 Figure 14 : Distribution of losses for a Class 8 at 65 mph for 10% l oad (Right) and 100% Load (Left)

Figure 15 : Distribution of losses for a Class 8, Bus, and Class 6 at 50 mph at GVWR 58%

1% < 1% < 1% < 1% 19% 21% Loss Repartition - class8 / SS 65 mph / 100% Load (Losses = 425 kW)

59%

2% < 1% < 1% < 1% 11%

26% Loss Repartition - class8 / SS 65 mph / 10% Load (Losses = 338 kW) engine mech. acc. elec. acc. gearbox axle tires
aero

59%

2% < 1% < 1% < 1% 21% 15% Loss Repartition - class8 / SS 50 mph / 100% Load (Losses = 260 kW) engine mech. acc. elec. acc. gearbox axle tires
aero

59%

7% < 1%

1% < 1%

16% 15% Loss Repartition - bus / SS 50 mph / 100% Load (Losses = 239 kW)

63%

< 1% < 1%

2% < 1% 15% 19% Loss Repartition - cl6 / SS 50 mph / 100% Load (Losses = 198 kW)28 Argonne National Laboratory

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– October 2009 Figure 16 : Distribution of losses for a Class 2b at 50 mph at GVWR



### 5.2 **Standard Dr ive Cycles** 

A similar methodology can be used to analyze power flows on non

- steady

- speed cycles. Similarly to the steady

- state diagrams, the numerical values associated to a flow represent the average power of that flow (total flow energy divided by time). A new block is however necessary, and is called “inertia”. It represents the kinetic energy the vehicle acquires when accelerating and that it loses when decelerating. Most of it is lost in friction losses during braking. A regenerative braking system, as used in hybrids, can recover part of that energy and add it back to the system. Several diagrams for various applications and corresponding duty cycles are showed hereinafter ( Figure 17 , Figure 18 , Figure 19 and Figure 20 ).

Figure 17 : Power Flow Diagram for a Bus on CBD cycle (50% load) 77% < 1% 1% < 1% 10% 11% Loss Repartition - cl2b / SS 50 mph / 100% Load (Losses = 92.4 kW) engine elec. acc. trans. axle tires
aero

engine **η** =40.1% %Loss=59.9% 123 kW

73.6 kW mech. acc. **η** =N/A %Loss=13.8% 49.3 kW

17 kW elec. acc. **η** =N/A %Loss=1.6% 32.3 kW

2 kW trans. **η** =80.8% %Loss=4.7% 30.3 kW

5.81 kW axle **η** =97% %Loss=0.6% 24.5 kW

0.725 kW tires **η** =N/A %Loss=5.6% 23.8 kW

6.88 kW aero **η** =N/A %Loss=0.9% 16.9 kW

1.06 kW inertia **η** =N/A %Loss=12.7% 15.9 kW Energy Balance - bus / cbd2 (13 mph average) / 50% Load / 26.1 gal/100mi29 Argonne National Laboratory

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– October 2009 Figure 18 : Power Flow Diagram for a Class 6 on HTUF cycle (75% load)

Figure 19 : Power Flow Diagram for a Class 8 on HHDDT 65 cycle (72% load)

Figure 20 : Power Flow Diagram for a Class 8 on UDDS Tr uck cycle (72% load) engine **η** =30.4% %Loss=69.6% 56.1 kW

39.1 kW mech. acc. **η** =N/A %Loss=0.5% 17 kW

0.276 kW elec. acc. **η** =N/A %Loss=1% 16.8 kW

0.554 kW trans. **η** =83.5% %Loss=4.8% 16.2 kW

2.68 kW axle **η** =98% %Loss=0.5% 13.5 kW

0.269 kW tires **η** =N/A %Loss=5.8% 13.3 kW

3.24 kW aero **η** =N/A %Loss=3.1% 10 kW

1.73 kW inertia **η** =N/A %Loss=14.7% 8.28 kW Energy Balance - cl6 / HTUF Class 6 P&D (10 mph average) / 75% Load / 15.0 gal/100mi

engine **η** =40.9% %Loss=59.1% 317 kW

187 kW mech. acc. **η** =N/A %Loss=1.5% 130 kW

4.84 kW elec. acc. **η** =N/A %Loss=0.1% 125 kW

0.36 kW trans. **η** =98.1% %Loss=0.7% 125 kW

2.36 kW axle **η** =98% %Loss=0.8% 122 kW

2.43 kW tires **η** =N/A %Loss=15.6% 120 kW

49.6 kW aero **η** =N/A %Loss=16.8% 70.1 kW

53.2 kW inertia **η** =N/A %Loss=6.1% 16.9 kW Energy Balance - cl8 / HHDDT65 ( 50 mph average) / 72 % Load / 17.0 gal/100mi

engine **η** =36.9% %Loss=63.1% 164 kW

104 kW mech. acc. **η** =N/A %Loss=2.7% 60.5 kW

4.35 kW elec. acc. **η** =N/A %Loss=0.2% 56.1 kW

0.36 kW trans. **η** =97.8% %Loss=0.7% 55.7 kW

axle **η** =98% %Loss=0.7% 54.5 kW

1.08 kW tires **η** =N/A %Loss=9.7% 53.5 kW

16 kW aero **η** =N/A %Loss=4.9% 37.5 kW

8.07 kW inertia **η** =N/A %Loss=20.3% 29.4 kW Energy Balance - cl8 / udds truck (18 mph average) / 72 % Load / 24.2 gal/100mi

1.21 kW30 Argonne National Laboratory

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## 6 **Impact of Drive Cycles on Fuel Consumption**

**6.1 Impact of Real World Drive Cycles** 

In this paragraph, we will study the impact of real world drive cycles on fuel consumption . W e will first compare this study with the drive cycles general ly used for simulation and then look at the differences with steady states results from P aragraph 5

. **6.1.1 Pickup Truck Class 2b** 

For the pickup truck application, real world drive cycles gathered by the U.S. EPA in Kansas City in 20 05 were used for simulation. This set of data consists in 110 daily driving cycles recorded on various light duty car, SUVs and pickup trucks. We assumed that the driving patterns of a pickup truck class 2b were close enough to light duty vehicles to justi fy the use of Kansas City cycles. Only the speed as a function of time was extracted from the set of cycles. This information then bec ame the cycle constraint to follow by the driver model of the pickup truck class 2b vehicle. The fuel consumption results are plotted on Figure 21 as well as the UDDS and HWFET cycles commonly used for this application.

Figure 21 : Fuel Consumption as a function of Average Cycle Vehicle Speed for a sample of Real World Drive Cycles for a Pickup Class 2b 10 20 30 40 50 60 4 6 8 10 12 14 16 18Fuel Consumption (gallons/100mile)

Average Cycle Vehicle Speed (mile/hour) Fuel Consumption for a Pickup Class 2b on Real World Drive Cycles
RWDC Interpolation UDDS HWFET31 Argonne National Laboratory

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– October 2009 For a clearer analysis of the data, an interpolation of the Kansas City cycle simulations was also reported on Figure 21 . The green and black stars represent the UDDS and HWFET fuel consumptions resp ectively. This graph mainly shows that by using a combination of the UDDS and the HWFET cycles

we can reach the area where most of the RWDC are located (around an average vehicle speed of 30 to 35 mph). However, the fuel consumption of these two cycles tak en separately or combined is still lower than the trend shown by RWDC which is a common remark.

While the c orrelation coefficient of the interpolation is only 0.64 , the graph clearly shows a high correlation between fuel consumption and average cycle spee d

. The difference for a specific average speed is mainly due to the driver aggressiveness.

**6.1.2 Line Haul Class 8** 

For the class 8 application, the real world drive cycles gathered for the simulations were recorded by Oak Ridge National Laboratory. The limite d number of data (8 cycles) limits the analysis. An interpolation of the simulation fuel consumption results was performed but more RWDC would be needed to better attempt to characterize a trend between average cycle vehicle speed and fuel consumption.

F igure 22 : Fuel Consumption as a function of Average Cycle Vehicle Speed for a sample of Real World Drive Cycles for a Class 8 Truck 0 10 20 30 40 50 60 70 14 16 18 20 22 24 26 28 30 32Fuel Consumption (gallons/100mile) Fuel Consumption for a Line Haul Class8 on Real World Drive Cycles
RWDC Interpolation HHDDT6532 Argonne National Laboratory

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– October 2009 As shown in Figure 21, the fuel consumption o n the HHDDT65 cycle is lower than the RWDC with a sim ilar average cycle vehicle speed. This is the same conclusion as for the pickup truck class 2b. Note that the correlation coefficient of the interpolation is only about 0.66 and shows that more RWDC would be necessary to get a better fitting.



### 6.2 **Issues Follo wing the Trace** 

One of the many challenges of heavy duty vehicle modeling is to select a drive cycle that can be driven by most configuration of a vehicle class including different weights, transmissions, etc... T his can indeed become a crucial issue especia lly for class 8 trucks where manual configurations are widely available and weight can dramat ically vary ( from a 10% load to GVWR )

. For an 18 speed manual transmission for example, the typical average shifting time is around two seconds and the shifting

ev ents are extremely frequent. On the other hand, automatic transmissions have little power interruptions and a lower gear number . Consequently, if we compare both transmissions on the same drive cycle, with the rest of the powertrain being identical , the ve hicles might not follow the trace similarly.

Figure 23 : Automatic vs

. Manual Transmission for a Class 8 Truck33 Argonne National Laboratory

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– October 2009 Figure 23 clearly depicts this issue. On this graph, we show the beginning of the HHDDT65 dr ive cycle (in blue) as well as the vehicle speed of a manual (red) and automatic (green) class 8 truck attempting to follow this trace. The multiple shifting events of the manual truck moves the vehicle speed away fr om the trace whereas the automatic truck better follows the speed demand. Consequently, if we compare the simulation results for these two trucks, the manual vehicle has a better fuel consumption than the automatic because it has a lower average speed throughout the cycle since it does not follo w the same trace. Therefore, there is a need of introducing an additional parameter in the fuel efficiency results: the average cycle vehicle speed.



### 6.3 **Potential Approach**  **to Representing Fuel Efficiency** 

This paragraph shows a graphical example of how fuel e fficiency could be represented for regulatory purposes and in order to fairly compare different truck configuration s within the same vehicle class. The steady state results simulated for the line haul class 8 in paragraph 5 are used and plotted on Figure 24

.

Figure 24 : Fuel Consumption as a function of Steady State Vehicle Speeds for different Payloads Figure 24 gives an original approach to decid e w hat fuel consumption to expect from a class 8 truck according to its cycle average vehicle speed and the weight of load carried. Taking the previous example 

### 50 55 60 65 70 75 10 12 14 16 18 20

Speed [mph]Fuel Consumption [gal/100 mi] 

### Fuel Consumption for Various Fractions of Maximum Payload (class8, SS) 0 % Load 10 % Load 20 % Load 30 % Load 40 % Load 50 % Load 60 % Load 70 % Load 80 % Load 90 % Load 100 % Load34 Argonne National Laboratory

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– October 2009 of the manual and automatic transmission class 8 trucks simulated on the HHDDT65 cycle, we could de termine what fuel consumption such trucks should achieve according to their cycle average speed

. This would lead to two different values since they did not follow the trace similarly. If the truck with an automatic transmission loaded at GVWR completed the HHDDT65 at an average speed of 60 mph, the 100% load curve on Figure 24 would then indicate 16 gallons/100miles fuel consumption for this particular truck. On the other hand , if the truck with a manual transmissio n completed the same cycle at an average speed of 58 mph, the same curve would indicate 15.5 gallons/100miles. Consequently, these two trucks will not have the same criteria to meet for regulation and the truck with the manual transmission might not be the most fuel efficient one even if its fuel consumption value is lower. The question brought by the previous paragraph is: how accurately can steady states predict fuel consumption ? To answer this we will take the same graph as Figure 24 but for a pickup truck class 2 b and we will merge it with the RWDC fuel consumptions data ( see paragraph 6.1.1 ). The resulting plot is shown on Figure 25

.

Figure 25 : Fuel Consumption as a function of Average Cycle Vehicle Speed for RWDC and Steady States for a Pickup Truck Class 2b. As expected, steady states are sho wing better fuel consumptions than RWDC for the same average vehicle speed. However, the d ifference is not dramatic and the trend between the steady state curves and the RWDC interpolated curve is similar.35 Argonne National Laboratory

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– October 2009 

## 7 **Impact of Single Technologies on Fuel Consumption**

In the following sections, the impact of several technologies on fuel consumption will b e assessed, including:

- Aerodynamics

- Fuel

- Hybridization


### 7.1 **Aerodynamic**

**7.1.1 Utility Truck Class 6** 

The configuration used for the Utility Class 6 Truck had the following specifications :

Table 10 : Utility Class 6 Truck Vehicle Assumptions for Drag Coefficient Study
Simulation 1 Simulation 2 GVWR 11791 kg Simulation Vehicle Mass 9070 kg Rolling Resistance 0.007 Drag Coefficient 0.7 0.55

Six different steady state speeds along with several driving cycles were chosen to represent various d riving conditions. T he Truck UDDS represents urban type driving and the HTUF cycle is similar to the light duty UDDS cycle. Finally, the HHDDT Cruise and High Speed were developed by CARB and are both highway cycles with an average vehicle speed of 40 mph and 50 mph respectively.

Table 11 : Utility Class 6 Truck Drive Cycle and Steady States Assumptions for Drag Coefficient Study Steady States Driving Cycles 10 mph Truck UDDS 20 mph HTUF P&D Class 6 30 mph HHDDT Cruise 40 mph HHDD T High Speed 55 mph 65 mph

The simulation results are shown on Figure 26

. F uel consumption is shown in gallons/100miles as a function of average vehicle speed. Note: the fuel efficiency results for steady state s were computed by removing the acceleration part which leads to the steady state , ensuring that the results are pure36 Argonne National Laboratory

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– October 2009 steady states. The lines represent the steady states (plain for Cd=0.55 and dotted for Cd=0.7) and the scattered points (circles for Cd=0. 55 and x for Cd=0.7) depict the drive cycles

.

Figure 26 : Impact of Drag Coefficient on Class 6 Fuel Consumption for various Drive Cycles and Steady States.

Figure 26 shows that the fuel consumption valu es from steady states and drive cycles are much closer to each other when the average vehicle speed of the cycle is high (>40 mph) whereas they widely differ in low average vehicle speed areas. This is understandable considering that most of the drive cycle s with an average vehicle speed of 40 mph or higher usually represent highway driving and consequently do not have much acceleration / deceleration . On the other hand, a drive cycle with a low average vehicle speed (e.g., 25 mph ) characterize s an urban cyc le with multiple transient phases leading to higher fuel consumption than a steady state cycle at the same speed.
Figure 27 shows the percentage of fuel consumption reduction when the drag coefficient is lowered fr om 0.7 to the 0.55 for drive cycles and their associated steady state speed. The values were generated by taking the average speed for each of the four cycles and calculated the steady state fuel consumption values corresponding to the speed by intersectin g the lines from Figure 26

. 

### 0 10 20 30 40 50 60 70 0 2 4 6 8 10 12 14 16 18 20Fuel Consumption (gallons/100miles)



### Cycle Average Vehicle Speed Fuel Consumption vs Cycle Average Vehicle Speed for a Class 6 Truck

Drive Cycles with Cd=0.55 Drive Cycles with Cd=0.7 Steady States with Cd=0.55 Steady States with Cd=0.7 UDDS Truck HHDDT Cruise HHDDT High Speed HTUF Class 637 Argonne National Laboratory

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– October 2009 Figure 27 : Percent of Fuel Saved by Reducing the Drag Coefficient for Each Drive Cycle and their Steady State Speed Counterpart for Class 6
In Figure 27 , it appears that the drag coefficient reduction has consistently a greater impact on the fuel consumption of drive cycles than the one from steady states. However , the difference seems to be greater at average vehicle speeds between 25 and 45 mph than at low and high speeds. The benefits from aero dynamics being related to the cube of the vehicle speed, any higher speed portion above the average will decrease the fuel consumption. Since higher speed variations are seen for lower average

s peeds, the diffe rence between Steady State and drive cycl e is greater at average speeds.

**7.1.2 Line Haul Class 8** 

The configuration used for the Line Haul Class 8 Truck has the following specifications:

Table 12 : Line Haul Class 8 Truck Vehicle Assumpti ons for Drag Coefficient Study
Simulation 1 Simulation 2 GVWR 36280 kg Simulation Vehicle Mass 29931 kg Rolling Resistance 0.007 Drag Coefficient 0.6 0.5 0 5 10 15Percentage Improvement from high to low Cd Comparison of Aerodynamic Fuel Savings for Drive Cycles vs Steady States

HTUF Class 6/

21 mph SS UDDS Truck/ 26 mph SS HHDDT Cruise/ 42 mph SS HHDDT High Speed/ 53 mph SS Drive Cycles Steady States38 Argonne National Laboratory

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– October 2009 Six different steady state speeds and driving cycles were used to represent various driving cond itions. As for the Utility class 6 vehicle, the Line Haul is simulated on the Truck UDDS cycle as well as the three HHDDT cycles developed by CARB

.
Table 13 : Line Haul Class 8 Truck Drive Cycle and Steady States Assumptions for Drag Coefficient Study Steady States Driving Cycles 15 mph Truck UDDS 20 mph HHDDT Transient 30 mph HHDDT Cruise 40 mph HHDDT High Speed 55 mph 65 mph

The simulation results are shown on Figure 28

. The lines re present the steady states (plain for Cd=0.5 and dotted for Cd=0.6) and the scattered points (circles for Cd=0.5 and x for Cd=0.6) depict the drive cycles.

Figure 28 : Impact of Drag Coefficient on Class 8 Fuel Consumption for vari ous Drive Cycles and Steady States. 

### 10 20 30 40 50 60 70 0 5 10 15 20 25 30Fuel Consumption (gallons/100miles)



### Cycle Average Vehicle Speed Fuel Consumption vs Cycle Average Vehicle Speed for a Class 8 Truck

Drive Cycles with Cd=0.5 Drive Cycles with Cd=0.6 Steady States with Cd=0.5 Steady States with Cd=0.6 HHDDT Transient UDDS Truck HHDDT High Speed HHDDT Cruise39 Argonne National Laboratory

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– October 2009 As shown in Figure 28 , fuel consumptions achieved during s teady states are closer to one from the drive cycles when the average vehicle speed is higher than 40 mph.

Figure 29 : Percent of Fuel Saved by Reducing the Drag Coefficient for Each Drive Cycle and their Steady State Speed Counterpart for Class 8
In Figure 29 , the same conclusions as for the class 6 utility truck can be drawn. However an other interesting point can be made. Except for the lowest vehicle speed drive cycle, both trucks were simulated on the same cycles but the fuel savings vary widely from the class 6 to the class 8. For example, the class 6 truck reduced its fuel consumptio n by more than 14% on the HHDDT cruise against only 6% for the long haul . This difference is due to the similar aerodynamic specifications of these trucks taking into consideration the weight discrepancy (9 tons vs 30 tons). The aerodynamic losses represen ting a greater percentage of the overall powertrain losses for the class 6, the drag coefficient reduction will have a greater impact on the vehicle fuel efficiency.



### 7.2 **Type of Fuel**

This paragraph explore s the impact of using either Gasoline or Diesel fuels for two vehicle applications: the pickup truck class 2b and the utility truck class 6. 0 1 2 3 4 5 6 7Percentage Improvement from high to low Cd Comparison of Aerodynamics Fuel Savings for Cycles vs Steady States

HHDDT Transient/ 17 mph SS UDDS Truck/ 26 mph SS HHDDT Cruise/ 42 mph SS HHDDT High Speed/ 53 mph SS Drive Cycles Steady States40 Argonne National Laboratory

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– October 2009 **7.2.1 Pickup Truck Class 2b** 

7.2.1.1 Assumptions

The GMC Sierra 2500 HD pickup truck was selected since both gasoline and diesel engines were available. Table 14 shows the main sp eci fications [ 1 ] :

Table 14 : Gasoline and Diesel Assumptions for the Pickup Truck Class 2b
Diesel Gasoline GVWR 4172 kg 4172 kg Towing Capacity 4535 kg 4535 kg Engine Model DURAMAX 6.6L V8 VORTEC 6.0L E ngine Power/Torque 272 kW / 895 Nm 268 kW / 515 Nm Gearbox Allison 1000 Series

– 6 Speed Allison 1000 Series

– 6 Speed Axle Ratio 3.73 3.73 Tires 245/75R16 245/75R16

Since the latest Duramax and the Vortec engines are not available in PSAT, similar en gines were used and scaled to match the specifications. The Gasoline engine is a GM V8 LM7 5.3L with overhead valves, two valves per cylinder and sequential fuel injection which offers very similar specifications than the Vortec engine in terms of rated ma ximum torque and power [ 5 ]

. T he closest available diesel engine was a Cummins ISB 6.7L calibrated for vehicle test procedure purposes (i.e. suitable for a class 2b pickup truck contrary to other heavier duty versions of the ISB engine calibrated for emissions) . The engine power and torque curves of the Duramax can be found in the literature [ 3 ]

. The power and torque curves of the Cummins ISB being proprietary data , they will not be shown in the repor t

. However, we can mention that after scaling, the engine had a peak torque of 940 Nm at 1600 rpm and a peak power of 272 kW at 2950 rpm. No cylinder deactivation technology was considered for this study.

7.2.1.2 Simulation Scenarios

Two different sets of simula tions were completed for this vehicle:

- Scenario A : The first scenario uses the peak power values found in the literature for the two GMC Sierra versions (272 kW for diesel and 268 kW for gasoline).

- Scenario B : The second scenario uses an automated sizin g algorithm to ensure that both vehicles have the same performance specifications. Using the diesel as a reference, we simulated an acceleration test from 0 to 60 mph. T he gasoline vehicle was then designed to match the performance . Note: the diesel vehicl e takes into consideration a 6% penalty in41 Argonne National Laboratory

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– October 2009 acceleration time due to turbo lag. The vehicles achieved the acceleration test in 9 seconds and the resulting engine powers were 272 kW for diesel and 276 kW for gasoline.

7.2.1.3 Simulation Results

Four different driv e cycles were used to offer various aggressiveness conditions. Due to the similarities with light duty pickup truck, the UDDS, HWFET, LA92 and US06 cycles were selected . All vehicles were simulated at gross vehicle weight.

T able 15 shows the fuel consumpti on for the two vehicles according to the different scenarios

. All values are in gallon /100miles and unadjusted. For the diesel vehicle s, the first value is volumetric fuel consumption (gallons of diesel consumed per 100 miles) and the second one in parenth esis is in gasoline fuel consumption equivalent

.
Table 15 : Fuel Consumption of Gasoline and Diesel Class 2b Vehicles for different Drive Cycles

UDDS HWFET LA92 US06 Scenario A Gasoline 8.56 5.34 9.03 8.86 Diesel 6.99 (7.78) 3.9 9 (4.44) 7.19 (7.99) 6.41 (7.13) Percent Fuel Saved 18.3% (9.1%) 25.3% (16.9%) 20.4% (11.5%) 27.7% (19.5%) Scenario B Gasoline 8.65 5.38 9.07 8.84 Diesel 6.99 (7.78) 3.99 (4.44) 7.19 (7.99) 6.41 (7.13) Percent Fuel Saved 19.2% (10.1%) 25.8% (17.5%) 20.7% (11.9%) 27.5% (19.3%)

The amount of fuel saved by a diesel pickup truck compared to its gasoline counterpart ranges bet ween 19 .2 to 27.5 % when comparing volumetric fuel consumptions (9.1 to 19.5% when in gasoline equivalent) . The trend showed by th e different cycles is that the more aggressive/faster the driving pattern, the greater the advantage of diesel. These results could seem lower than the common Diesel/Gasoline comparison for light duty vehicles (commonly used value of 30% for volumetric fu el consumption) . In this case, the two class 2b trucks were simulated at GVWR. However, these vehicles are designed to be able to tow an additional 10,000 to 15,000 lb trailer. Consequently, both engines did not operate at full load since the simulation di d not require so. Both engines are operated at low loads (typically lower than 200 Nm) where the ir efficiency map s are similar. These are the typical conditions observed on the UDDS cycle which explains why the fuel consumption advantage of the diesel is only around 19 %. On the other hand when the engine is operated at higher loads (more than 200 Nm), the diesel engine operates a higher efficiencies than for the diesel engine

. As a consequence, the US06 cycle shows a greater fuel consumption advantage for the diesel engine (around 28 %)

.42 Argonne National Laboratory

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– October 2009 Figure 30 : Fuel Consumption of Gasoline and Diesel Class 2b Vehicles for different Drive Cycles

**7.2.2 Utility Truck Class 6** 

7.2.2.1 Assumptions

The GMC C

- series C5C042 2WD regular cab was selected since both gasoline and diesel engines were available. Table 16 shows the main specifications [4]:

Table 16 : Gasoline and Diesel Assumptions for the Utility Truck Class 6
Diesel Gasoline GVWR 11791 kg 11791 kg Engine Model DURAMAX 6.6L V8 V ORTEC 8.1L Engine Power/Torque 246 kW / 820 Nm 240 kW / 610 Nm Gearbox Allison 2200 HS/RDS Series

– 6 Speed Allison 2200 HS/RDS Series

– 6 Speed Axle Ratio 4.88 5.29 Tires 245/70R19.5 245/70R19.5

As for the pickup Class 2B application, we used the GM LM7 5.3L gasoline engine since it is the closest data available in the PSAT database. For diesel, we used a Cummins ISB 6.7L engine calibrated for 

### UDDS LA92 HWFET US06 3 4 5 6 7 8 9 10Fuel Consumption (gallons/100miles)



### Drive Cycle Fuel Consumption for a Pickup Truck Class 2B on various cycles Diesel Gasoline43 Argonne National Laboratory

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– October 2009 engine dynamometer certification and thus not the same version as for the pickup truck . The gasoline engine was scaled to match the peak power specification. For the Cummins ISB diesel engine was scaled as well . The original power and torque curves as they are defined for this GMC truck for the two engines can be found in the literature [ 3 ]

.

7.2.2.2 Simulation Scenarios

For the Class 6 vehicle , a single simulation scenario was used. The engine peak power was directly derived from the GMC truck used as a reference. The value of 240 kW was used for the gasoline engine peak power and 246 kW fo r the diesel one.

7.2.2.3 Simulation Results

Three drive cycles were used for simulation: the HTUF Pickup and Delivery Class6, HHDDT65 and the Truck UDDS. The vehicles were run at a GVWR of 26,000 lbs (11,791 kg). The following table shows the fuel consumption r esults in unadjusted gallons/100miles . For the diesel vehicles, the first value is in Diesel fuel consumption and the second one in parenthesis is in Gasoline fuel consumption equivalent.

Table 17 : Fuel Consumption of Gasoline and D iesel Class 6 Vehicles for different Drive Cycles
HTUF Class 6 Truck UDDS HHDDT65 Gasoline 21.41 20.53 18.69 Diesel 15.92 (17.73) 15.31 (17.03) 13.81 (15.38) Percent Fuel Saved 25.6% (17.2%) 25.4% (17%) 26.1% (17.7%)

The amount of fuel saved by the d iesel configuration compared to the gasoline is 26% on average for volumetric fuel consumptions (around 17% when in gasoline equivalent) . This value is closer to the common Gasoline/Diesel comparison accepted for light duty vehicles. Indeed, a quick ratio of the engine map peak efficiency would give a 16% advantage for the diesel engine. In the case of the class 6, the engine is operated closer to the full load and to its peak efficiency more often

.44 Argonne National Laboratory

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– October 2009 Figure 31 : Fuel Consumption of Gasoline and Diesel Class 6 Vehicles for different Drive Cycles



### 7.3 **Tractor**

**- trailer**  **Hybridization**

**7.3.1 Hybridization Principles** 

Hybrid electric vehicles have demonstrated their ability to significantly reduce fuel consumption for several medium and heavy duty ap plications. While much work is available in the literature for buses, delivery truck or utility trucks, little information is available for long hauls. This section focuses on analyzing the hybridization potential of several powertrain configurations for Class 8 long haul.

Most of the energy losses occurring in a truck come from the engine. On a urban cycle, the engine average efficiency is only 37 %, which means the engine could be operated more efficiently. On the other hand, on the highway there is les s opportunity for improvement as the engine is already operated close to its peak efficiency (41 % average) . Operating the engine more efficiently can be achieved mainly in two ways: not using the engine at all during those low efficiency operation moments , or shifting the operation point to a more efficient level

– for example by increasing the engine output and storing it an energy storage system, or by decreasing the engine speed. The losses due the tires and aerodynamic losses cannot be displaced by hyb ridization, since the vehicle follow s the same cycle, and re quires the same amount of power regardless of the source of power. The losses due to the driveline could be in part displaced if the electric power source is put 

### HTUF udds HHDDT65 0 5 10 15 20Fuel Consumption (gallons/100miles)



### Drive Cycle Fuel Consumption for a Class 6 on various cycles

Diesel Gasoline45 Argonne National Laboratory

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– October 2009 closer to the wheels (e.g. series w/o transmission, post

- transmission parallel , in

- hub motors, etc.), but that is not a practical solution for heavy

- duty applications. The accessory load can be affected by hybridization, as some of the mechanical accessories (pumps, compressors, etc.) can be replaced by electric systems. This is a difficult exercise to replicate in simulation, as it requires the knowledge of the mechanical accessory load in both conventional and hybrid case. In this study, some of the load is displaced from mechanical to el ectrical.

A conventional vehicle also loses much of the kinetic energy it acquired during acceleration through friction when braking. A regenerative braking system can recover part of this energy and recharge the energy storage system, and that energy can in turn be used for the accessory load and/or for propulsion. Hybridization could lead to other indirect fuel savings opportunities, that are not necessarily well represented in a cycle

- type testing procedure (either actual on a dynamometer or in simulatio n). If performance (meaning here higher acceleration capability) is improved or shifting time is reduced , the vehicle will be less likely to “ lose ” the trace

– i.e. the vehicle speed dropping below the target trace speed

– and will not need to accelerate a s much later , while performing more “ work ” ( higher distance). On the other hand the availability of improved performance can lead the driver to request more power in real

- world driving conditions , possibly leading to a less efficient use of the hybrid syst em.

**7.3.2 Hardware**  **Design**

7.3.2.1 Hybrid Configurations Overview

A hybrid vehicle can have one or more electric machines that can be positioned at various points of the powertrain , leading to a large number of configurations. The main configuration families are prese nted hereinafter.

Series . In a series configuration, the vehicle is only propelled by electrical power. T he engine output power is converted into electricity through a generator and then is either stored in the battery or converted back into mechanical pow er by the propulsion motor. The latter can be directly connected to the final drive, or to a gearbox with a lower number of gears than a conventional one thanks to high torque availability at low speed and increased motor speed range. This configuration is generally the easiest to implement because the propulsion is 100 % electric, while the generator set is almost an independent system, relatively easy to control. A drawback of this configuration is that both electric machines have to be oversized: the pro pulsion one to the vehicle power/torque requirements, and the generator to the engine power. Another drawback is that at cruising speed the de facto electric transmission has a poor efficiency due to the double conversion of engine mechanical energy. One n ote that variations of series configurations are currently trying to address this limitation.46 Argonne National Laboratory

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– October 2009 Parallel . In a parallel configuration, the vehicle can either be propelled directly from thermal or electrical power . The vehicle usually has at least one clutch and a multispeed gearbox close to a conventional model. That means the engine

- to

- wheels path goes through the gearbox, in a similar fashion to a conventional powertrain, thus resulting in a relatively good efficiency at cruising speeds. The electric machin e can e ither provide positive torque, contributing to the propulsion of the vehicle, or recharge the energy storage by diverting part of the engine torque. There are several variants of the configuration, based on the position of the electric machine

.
In a starter

- alternator position, the electric machine is between the engine flywheel and the clutch; when the clutch is open, the motor is disconnected from the drivetrain. This configuration is used in micro

- hybrids or mild

- hybrids allowing the engine to be shut down at idle, and quickly start ed again it back when the driver requires the vehicle to start moving. Its main advantage is its ease of implementation and cost effectiveness. However expected gains are limited by the level of regenerative braking.

In a pre
- transmission, the electric machine is between the clutch and the gearbox. In a post

transmission, the electric machine is between the gearbox and the final drive (or transfer case). When the clutch is open the engine is disconnected from the drivetr ain, while the electric machine is not, therefore allowing an electric

- only mode. In the pre

- transmission case, the electric machine benefits from the gearbox torque multiplication, which provides more freedom in terms of electric machine speed range choic e, and ensures that the electric machine can be operated above its base speed most of the time. On the other hand, in the post

- transmission case, the motor

- to

- wheels path is more efficient as it does not include the transmission; also there is no torque in terruption during shifting. For both pre

and post

- transmission configurations, the clutch control is often a challenging engineering problem.

Series

- parallel . This configuration combines the benefits of the series and parallel pre

- /post

transmission con figurations. When the clutch is open, the engine can be off or can be on and generate electricity through the generator, creating a series path. Generally the series

- path is used at low speeds, while parallel is chosen for higher cruising speeds. The serie s
- parallel can be combined with gearboxes with a lower number of gears One mode power split

. Th is configuration is used by Toyota (e.g., Prius) and Ford (e.g., Escape)

. The engine and a motor

- generator are connected to a planetary gearset, to the output of which another electric machine is connected. In this configuration, the engine power is split: part of it is transferred to the wheels, while another goes through the electrical path, with a double energy conversion, similar to the series. The planetary g earset and the electric machines act as a n electric

- variable transmission (EVT). The engine speed can be chosen relatively independently from the vehicle speed; the control can therefore choose to consistentyly operate the engine in an efficient area. At c ruising speed, the EVT may not be as efficient as a conventional gearbox, depending of the level of recirculation. Furthermore, this configuration leads to significant oversizing on heavier vehicles in order for them to be a b le to operate in a broad range of operations.47 Argonne National Laboratory

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– October 2009 Multi

- mode transmission . A multi

- mode transmission combines several power

- split modes, each of them suitable for different operational requirements, therefore avoiding component oversizing. It can also be combined with fixed gear (s)

- adding parallel paths

- for extra flexibility on grades or cruising.

7.3.2.2 Configurations selected for the study

Two hybrid configurations were selected for this study: series

- parallel and starter

- alternator. The conventional series configuration is not well suite d for tractor

- trailer applications because it is not efficient at cruising highway speeds, which is the most frequent use of such a truck. A multimode hybrid with fixed gear could be an option, but due to the complexity of its design and its control, it wi ll not be considered in this study . The parallel pre

- transmission is similar to the series

- parallel.

The series

- parallel with one electric machine in pre

- transmission position (between the clutch and the gearbox) is chosen to be a full

- hybrid, with electri c
- only mode capability. Thanks to another electric machine , the series mode will allow easy engine starts, as well as a recharging capability when the vehicle is stopped.

Figure 32
– Schematic of the series

- parallel configuration (full

- hybrid)
The starter

- alternator, thanks to a low power electric machine and low energy battery is selected for a “mild

- hybrid” truck, i.e. with engine shut

- downs at idle and regenerative braking possi ble, but with no elec tric

- only mode. Thanks to a low power electric machine and low energy battery, the mild

- hybrid requires lower upfront investment than the full

- hybrid option. Engine
To Driveline Clutch Gearbox

Energy Storage System Elec. Acc. Mech

. Acc. MG2 MG148 Argonne National Laboratory

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– October 2009 Figure 33
– Schematic of the starter

- altern ator configuration (mild

- hybrid)

7.3.2.3 Component S izing

For light

- duty applications, typical sizing requirements are made of four criteria: acceleration (e.g. 0

- 60 mph time ), passing (30 to 50 mph time), gradeability at a given speed and top speed. For a hybri d, the electric system cannot be used for the grade requirement, as there would not be enough energy to sustain a continuous grade over a long period, so the engine must be sized for that specific requirement. The electric system can however be used for t he acceleration/passing requirement,; because the most restrictive factor is in general the acceleration requirement, an engine downsizing can the refore be achieved

– that is generally the case with production light

- duty hybrids. The same type of requireme nts could be applied to tractor

- trailers. However, there is no industry

- wide standard, as trucks are customized to fleets requirements. Another major difference between the two applications is that heavy

- duty vehicles often operate at maximum power, especi ally during grades. F rom a conventional truck, no engine downsizing can be done because the battery energy limits the electric propulsion to a short duration, while grades can be long. In this study the engine size is therefore the same as in for the conve ntional version. In the case of the less expensive and simpler starter

- alternator, the electric machine power is set at 50 kW. For the series

- parallel truck, the same size of electric machine is used for the generator (motor 2), while the propulsion electr ic machine (motor 1) has a 200 kW power. A electric machine power sensitivity or a design optimization study could provide a more precise choice of electric machine power, but is out of the scope of the present study. The battery power matches the electric machine power, while the battery energy is based on hotel loads. The average load is estimated to 1.5 kW, including air

- conditioning in the summer, cabin and engine block heating and various electric accessories (fridge, tv, lights, etc.). This value is b ased on exi sting literature and accessory/ idle

- specific devices specifications. In the case of the full

- hybrid, the Engine
To Driveline Clutch Gearbox

Energy Storage System Elec. Acc. Mech

. Acc. Motor

- Generator49 Argonne National Laboratory

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– October 2009 battery energy is such that it can provide the 1.5 kW load for the duration of a hotel stop of 10 hours, if fully loaded at the beginning of the stop. The usable battery energy for a lithium

- ion technology is 60% of its total energy (operating range between 90% and 30% of state

- of

- charge), resulting in a 25 kWh battery. In the case of the mild

- hybrid, the battery is only 5 kWh to limit the cos t of the system. It would be sufficient for a 2 hour period, after which the engine would have to be started in order to quickly recharge the battery. Since the power at which the engine would be operated would considerably be higher than during a conventi onal idling, this solution would still be more efficient. For both hybrid trucks, the gearbox remains unchanged compared to the conventional.. In the case of the series

- parallel, the number of gears could however probably be reduced. If the truck is always operated in series mode up to a certain vehicle speed, some of the higher gear ratios can be removed, provided that the propulsion electric machine has the proper speed and torque range s
. Finding the right combination of gear number, ratio and electric ma chine design is a study in itself that is outside of the scope of the present study. A specific transmission is however unlikely to bring significant energy efficiency improvements, as the full

- hybrid simulated here is already very efficient. A different gearbox could however reduce cost, space and improve drivability.

Table 18 : Summary of component sizes
Conventional Mild Hybrid Full Hybrid Engine Power (kW) 317 317 317

MG1 Power (kW)

- 50 200 MG2 Power (kW)

- - 50

Battery Ene rgy (kWh)

- 5 25 Battery Power (kW)

- 50 200 Transmission 10 speed (14.8

- 1) 10 speed (14.8

- 1) 10 speed (14.8

- 1) Mech. Acc. (kW) 5.2 1 1 Elec. Acc. (kW) 0.3 3 3 Mass (t) 26.26 26.26 26.26

**7.3.3 Control**  **Design**

The vehicle level controller manages th e different hybrid powertrain components : engine, electric machine (s) and transmission (clutch and gearbox) in order to optimize fuel consumption, while maintaining the battery state

- of

- charge within appropriate levels. Table 19 summarize s the control for both configurations.50 Argonne National Laboratory

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– October 2009 Table 19 : Summary of Control Strategy Mild Hybrid Full Hybrid Engine ON/OFF

- ON when the vehicle is moving.

- OFF when the vehicle is stopped - ON if the power r equest is above a certain threshold, or if motor is saturated

- OFF if the power request is below a certain threshold, and below a vehicle speed threshold SOC regulation

- hysteresis: if SOC is below a threshold, engine is ON and charges the battery until the SOC reaches a higher threshold

- the level of torque assist depends on the SOC - hysteresis: if SOC is below a threshold, engine is ON and charges the battery until the SOC reaches a higher threshold

- the level of torque assist depends on the SOC Sh ifting/Transmission

- same shifting control as for conventional manual - series mode at low speeds, parallel otherwise; clutch open when engine is off.

- quick shifting time due to speed synchronization by electric motors Torque Assist

- difference betwee n requested torque and peak engine torque if the engine is saturating

- percentage of total torque demand, when it is high enough

- no assist above a vehicle speed threshold that depends on SOC - difference between requested torque and peak engine torque i f the engine is saturating

- percentage of total torque demand, when it is high enough

- no assist above a vehicle speed threshold that depends on SOC Braking

- engine fuel is cut

- off

- clutch locked to allow regenerative braking - engine fuel is cut

- off

- clutch locked if engine is ON, open otherwise

**7.3.4 Standard Drive Cycles**  **Results**

All versions of the truck (conventional, mild and full hybrid) were simulated on various standard cycles, both highway cycles (HHDDT 65, HHDDT Cruise, HHDDT high speed) and t ransient/urban (HHDDT Transient, UDDS Truck ).

Table 20 summarizes the main characteristics of each cycle. When testing or simulating a hybrid vehicle, it is necessary to ensure that the results are n ot biased by the battery energy

– the test/simulation needs to be “ charge balanc ed”. S everal iterations of the same cycles were r un, so that difference in battery SOC (between the start and the end of the simulation), and therefore the battery energy used become neglig ible.51 Argonne National Laboratory

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– October 2009 Table 20 : Main Characteristics of Drive cycles
Average Speed (mph) Max. Speed (mph) Max. Accel. (m/s 2 ) Max. Decel. (m/s 2 ) Distance (mi) Duration (s) Time Stopped (%) HHDDT 65 50 66.7 2

- 2.8 26.5 1904 5 HHDDT Cruise 39.9 59 .1 0.42

- 0.59 23.1 2083 6 HHDDT High Speed 50.2 66.1 0.69

- 1.2 10.5 757 6 HHDDT Transient 15.3 47.5 1.32

- 2.4 2.8 668 17 UDDS Truck 18.7 57.7 1.9

- 2.1 5.5 1060 33

Figure 34 shows the fuel consumption of all 3 trucks, while Figure 35 illustrates the fuel savings compared to conventional. For both hybrids, the fuel savings are lower on the highway cycles, which is to be expected since the hybrid system does not help much at cruising speeds where the engine already operates efficiently. The mild

- hybrid shows fewer saving than the full hybrid, peaking at 11 %, while the full

- hybrid can save up to 40% on a urban cycle.

Figure 34 : Fuel Consumption o f conventional and hybrid trucks on standard cycles 16.1 13.8 16.4 24.5 22.7

15.7 13.3 15.9 22.0 20.1

15.3
12.6 15.2 14.8 16.2

0.0 5.0 10.0 15.0 20.0 25.0 30.0

HHDDT65 HHDDT Cruise HHDDT High Speed HHDDT Transient udds_truckFuel Consumption (gal/100 mi) CONV MILD FULL52 Argonne National Laboratory

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– October 2009 Figure 35 : Fuel Saved by hybrid trucks with respect to conventional truck, on standard cycles Most of the gains originate in the energy recovered during braking. Figure 36 shows the fraction of the total braking energy that is recovered at the wheel

– meaning not including the driveline and electric machine losses involved in the channeling of that energy into the battery. The recovery r ate depends on the cycle aggressiveness during deceleration. O n the HHDDT Cruise cycle, which has the lowest deceleration levels among all the cycles, the full

- hybrid manages to recover almost all of the braking energy

– i.e. mechanical brakes are not rar ely used

– but only half of it in the HHDDT 65. The mild

- hybrid recovers about 25% of the braking energy on most cycles , and peaking at 55% on the HHDDT Cruise . This is due to the much lowe r power of the electric machine, combined with a higher torque inter ruption time during shifting.

Figure 36 : Percentage of Braking Energy Recovered at the Wheels 2.8 4.0 3.5 10.3 11.3

5.3 9.0 7.3 39.5

28.8

0 5 10 15 20 25 30 35 40 45

HHDDT65 HHDDT Cruise HHDDT High Speed HHDDT Transient udds_truckFuel Savings w.r.t. to conventional (%) CONV MILD FULL

24.62 55.24

32.8 22.92 20.9 57.79 97.8

80.12 75.62 74.57

0 10 20 30 40 50 60 70 80 90 100

HHDDT65 filtererd HHDDT Cruise HHDDT High Speed HHDDT Transient udds_truckRecovered Braking Energy (%) CONV MICRO MILD53 Argonne National Laboratory

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– October 2009 The engine efficiency does however not improve significantly in most cases, as shown on Figure 37 . In particular, in the mild

- hybrid case, the engine efficiency is even slightly lower than in the conventional case. The main difference in engine operations between the conventional and the mild

hybrid is that the engine is shut down when the vehicle is stopped for the mild

- hybrid while the operations are similar when the vehicle is moving. In addition, the mechanical accessory load is much higher for the conventional (5 kW vs. 1 kW), and additional load generally improves efficiency. For the full hyb rid, the efficiency improvement s are limited on the highway cycles but are significant on the transient/urban cycles, where the low efficiency operations can be replaced by electric

- only mode.

Figure 37 : Average Engine Efficiency of conventional and hybrid trucks on standard cycles
**7.3.5 Hybridization and Grade** 
7.3.5.1 Description of the Study

In the previous simulations, the road driven was flat

– i.e. no grade. In real

- world, trucks regularly drive uphill or downhill. Driving downhill may i nvolve braking, which can be an opportunity for fuel savings when using regenerative braking. Due to the lack of real world drive cycles that included grade, t o illustrate the potential benefits of hybridization in a “hilly” terrain, idealized sinusoidal r oad profile s w ere created. The elevation of such a road is a sinusoidal function of the horizontal distance, with a “hill” period varying between 1 and 3 km. Maximum grades also vary from 0 to 4 %. All combinations of maximum grade and period were analyzed

. Figure 38 shows an example of elevation change as a function of horizontal distance for roads with same maximum grades but different hill periods. The hill period can be seen as twice the approximate distance tra veled between the bottom of the hill (“valley”) and the top of the hill (“summit”). The vehicle speed target is 60 mph. The maximum positive grade is achieved halfway to the “summit”, and the maximum negative grade halfway between54 Argonne National Laboratory

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– October 2009 the “summit” and the “val ley”

– there is a (horizontal) phase difference of a quarter of a period between the grade and the elevation.

Figure 38 : Sectional View of roads (partial) with the same maximum (3%) grade but 3 different hill periods

7.3.5.2 Adaptive Co ntrol

The control described in 7.3.3 was designed to ensure proper SOC fluctuations, but on steady

states, it generally needs to be tuned to operate efficiently. For example, the default set of control paramete rs does not allow torque assist at higher speeds and as a result, the battery SOC increases after each downhill braking event. The control was therefore tuned so that the energy recovered downhill is spent for accessories during the entire hill and for tor que assist during uphill. The tuning is generally a function of maximum grade. The strategy adopted is likely to be the optimal way of driving such a cycle as it does not involve any battery charging from the engine (except at low grades). The results may therefore be slightly optimistic for hybrids, but an intelligent controller, e.g. GPS based, should be able to come close to that solution in a real

- world situation.

An illustration of the control can be seen on Fig ure 39 for two different maximum grade values. At time t=266, the negative grade is maximal in both cases, and the electric machine can recuperate some energy from braking, all the more that the grade is intense. At time t=247s, the grade is maximal and s o is the level of torque assist. However, one can notice that the powers, and energies, are different from one grade to the other, while SOC is balanced in both cases. 0 2 4 6 8 10 0 5 10 15 20 25 30

Horizontal Distance (km)Elevation (m) Hill Period D = 1 km Hill Period D = 2 km Hill Period D = 3 km55 Argonne National Laboratory

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– October 2009 Figure 39 : Motor use uphill and downhill on a road with a hi ll period of 1 km, and 2.5% (left) or 4% (right) maximum grade, for a full

- hybrid
7.3.5.3 Simulation P aradigm

A simulation performed on a time basis, as it is done in PSAT may lead in some cases to an incorrect representat ion of how a trip is performed

– the same reasoning applies to dynamometer tests with a vehicle speed trace. When the simulation is performed based on time, the vehicle speed and grade targets are given at each time step. So long the vehicle follows the speed trace closely, the difference between what the vehicle is supposed to do (as per the cycle) and what it actually does (in simulation) is negligible, and gives a good representation of making a similar trip in real life. This is a

non
- issue for light

- duty applications, where the vehicle is alw ays able to meet the trace. On the other hand, heavy

- duty vehicles, especially tractor

- trailers, often operate close to their peak power. There are therefore more chances that the vehicle cannot follow the trace. A loss of speed relative to the trace leads to a lower travelled distance; when looking at consumption per unit of distance, this is somehow cancelled, but still different works are performed. In particular this is an issue for grades. Let’s take a simple example: let’s assume that the target speed is 90 km/h and there is a constant grade during 30s and then there is a flat portion; let us assume truck A can go uphill at 90 km/h, but truck B can go only 75 km/h with that grade. After 30 s, truck A would have climbed 750 m, and truck B only 625 m. Af ter 30 s, both trucks go on the flat portion whereas truck B has still 125 m left to the end of the hill! In this study, the conventional truck is not able to sustain all the grades, contrary to the full

- hybrid. Using the grade signal and the actual vehicl e speed (from simulation), the sectional views of the roads actually performed are showed on Figure 40 for the conventional and the full

- hybrid. The difference of phase is due to the acceleration part (on flat terr ain) done before starting the hills: the shifting time is much shorter for the hybrid , involving little or no vehicle speed loss contrary to the conventional truck. Since the conventional truck is not able to sustain the target speed (60 mph) during the wh ole hill, after the time the climbing is supposed to last, the elevation gain is lower. Going downhill, the truck has no issues meeting the speed target, the elevation loss will be what it is supposed to be. As a result the conventional truck ends up lower (in terms of elevation) than the hybrid truck. After 30 km in such hills, 240 245 250 255 260 265 270 275 -150 -100 -50

0 50 100

Time (s) Grade x10 (%) **∆** SOCx10 (%) Motor Mech. Power (kW)

240 245 250 255 260 265 270 275 -150 -100 -50

0 50 100

Time (s) Grade x10 (%) **∆** SOCx10 (%) Motor Mech. Power (kW)56 Argonne National Laboratory

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– October 2009 with a maximum grade of 4%, the conventional ends up 7 m (more than half the elevation of one hill) below where it started, while the full

- hybrid is at the same level.

Figure 40 : Section View of the actual trip for a conventional and a full

- hybrid truck (4% maximum grade, 1 km hill period) The quantitative impact on fuel consumption of that is not addressed in this study, but the reader should keep in mind the uncertainty added by an inability to follow the trace. Another uncertainty in the representativeness of this simulation is the constant speed assumptions . It may be the case that the driver will not brake downhill so that he can be at a higher speed before starting the next hill. If there is no braking, there is little or no gain to expect from hybrid models.

7.3.5.4 Results

Figure 41 shows the fuel consumption of the three versions of the trucks on various hills. T he fuel savings achieved by both hybrid trucks are showed on Figure 42

. With a 1% grade, there is no need for the driver to brake in order to stay at 60 mph and regenerative braking is not possible, so hybridizati on gains are limited. At 2% grade, there is some limited amount of braking, but even at full recuperation rate, the energy recovered is not enough to supply the energy for the accessory load. Charge balancing is hard to achieve in that mode, and charging from engine may occur, which explains the difference in trends. 4 4.2 4.4 4.6 4.8 5 0 2 4 6 8 10 12

Horizontal Distance (km)Elevation (m) Conventional Mild Hybrid Full

- hybrid57 Argonne National Laboratory

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– October 2009 At or above 2.5 %, the downhill grade is steep enough to recover enough energy for the accessory load and for some torque assist. Above 3% grade, the mild

- hybrid savings stop increasing beca use the additional braking energy available cannot be recovered by the small motor. For high grades, the fuel savings for the full hybrid are all the higher that the hill period is shorter. This is not due to the hybrid itself, but to the conventional, whi ch consumes more fuel when the hill period is shorter (and elevation is lower).

Figure 41 : Fuel Consumption of Conventional, Mild

- hybrid and full hybrid trucks on a sinusoidal road as a function of grade (and for various hill periods).

Figure 42 : Fuel savings of hybrid trucks with respect to conventional truck as a function of maximum grade (for various hill periods) 0 1 2 3 4 13 14 15 16 17 18

Max Grade (%)Fuel Cons. (gal/100 mi) Conv

Hill Period=1 km Hill Period=2 km Hill Period=3 km

0 1 2 3 4 13 14 15 16 17 18

Max Grade (%) Mild HEV

Hill Period=1 km Hill Period=2 km Hill Period=3 km

0 1 2 3 4 13 14 15 16 17 18

Max Grade (%) Full HEV

Hill Period=1 km Hill Period=2 km Hill Period=3 km

0 1 2 3 4 0 2 4 6 8 10 12 14

Max Grade (%)Fuel Savings (%) Mild

Hill Period=1 km Hill Period=2 km Hill Period=3 km

0 1 2 3 4 0 2 4 6 8 10 12 14

Max Grade (%)Fuel Savings (%) Full

Hill Period=1 km Hill Period=2 km Hill Period=3 km58 Argonne National Laboratory

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## 8 **Impact of Combined Technologies on Fuel Consumption**

The objective of this paragra ph is to evaluate the impact of various technology improvement packages on fuel consumption. The objective is to demonstrate and quantify that the gain of several technologies is not the sum of the gain of each separate ones

. The pickup truck class 2b was considered for the study.


### 8.1 **Baseline Vehicle Assumptions** 

Table 21 : Assumptions for the Pickup Class 2b used in the study of Technology Combination impact on Fuel Consumption Component Model Characteristics Source
– Based on... Engi ne Gasoline

– GM LM7 5.3L

– 268kW (34.7% peak efficiency) Transmission Allison 1000 Automatic 6 Speed Ratios : 3.1 , 1.81 , 1.41 , 1, 0.71, 0.61 GMC Sierra 2500HD

Final Drive Ratio 3.73 GMC Sierra 2500HD Tire P245/75/R16

– Radius = 0.387 m Rolli ng Resistance = 0.007 GMC Sierra 2500HD

Aero Drag Coeff icient = 0.44 Curb Weight 2659 kg GMC Sierra 2500HD GVWR 4152 kg Max Payload 1513 kg GMC Sierra 2500HD

The assumptions for the baseline pickup truck vehicle are based on the 2009 GMC Sier ra 2500 HD. As previously explained, the GM LM7 5.3L was selected as an alternate gasoline engine since the Vortec 6.0L data was not available. The engine was scaled to match the Vortec specifications. Although a 6

- speed automatic transmission appears to b e the standard reference gearbox for a 2009 pickup class 2b, we will also consider the case of having a 4

- speed automatic vehicle.



### 8.2 **Assumptions for Technology Improvements**

Since the technology improvements could have different impact s on fuel consumption whether they are applied to a conventional or a hybrid, we will consider two different paths. The first path will use a baseline conventional vehicle which will benefit of successive technology improvements (such as aero, transmissions...) with hybridiz ation only applied at the end . The second path will start from a baseline hybrid vehicle which will also benefit of aerodynamic improvements, optimized transmissions... In the following individual technology tables, we will show both the fuel consumption reductio ns in59 Argonne National Laboratory

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– October 2009 comparison to conventional and hybrid baselines. In bold are the assumptions that were used for simulation. The results were generated based on the combined drive cycle (UDDS + HWFET).

**8.2.1 Vehicle Weight** 

Table 22 : Impact of Weigh t Reduction alone on Fuel Consumption for the Class 2b Weight Reduction (kg) Percent Fuel Saved for Conventional (%) Percent Fuel Saved for Hybrid (%)

- 100 + 1.05 + 0.97

- 136 + 1. 39 + 1.39

- 200 + 2.09 + 2.02

For the package simulation, we will use a weight reduction of 300 lb (about 136 kg).

**8.2.2 Aerodynamics** 

Table 23 : Impact of Aerodynamics alone on Fuel Consumption for the Class 2b Drag Coefficient Percent Fuel Saved for Conventional (%) Percent Fuel Saved for Hybrid (%) 0.44 0 0 0.35 +2.66 +3.40 0.34 +2.98 +3.81 0.33 +3.29 +4.22

If the drag coefficient is reduced from 0.44 to 0.34 (

- 22%), we could expect up to 3% fuel savings for the conventional and almost 4% for the hybrid . This is consistent with light duty fuel consumption red uction estimates which predict a 1.5% fuel saving for each 10% reduction in drag coefficient.

**8.2.3 Rolling Resistance** 

Table 24 : Impact of Rolling Resistance alone on Fuel Consumption for the Class 2b Rolling Resistance Percent Fuel Save d for Conventional (%) Percent Fuel Saved for Hybrid (%) 0.007 0 0 0.00665 +0.57 +0.85 0.0063 +1.18 +1.59 0.0059 +1.82 +2.43 0.0058 +2.02 +2.6960 Argonne National Laboratory

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– October 2009 Several rolling resistance improvements were considered and are described in Tab le 24 . The value corresponding to a 10% rolling resistance improvement was chosen and could allow about 1.18% of fuel savings

. **8.2.4 Transmission** 

Table 25 : Impact of Transmission alone on Fuel Consumption for the Class 2b
Gearbox Percen t Fuel Saved if reference is 6

- Speed (Conventional) Percent Fuel Saved if reference is 4

- Speed (Conventional) Percent Fuel Saved if r eference is 6

- Speed (Hybrid) 6

- Speed Automatic 0 +4.59 0 8

- Speed Automatic +1.72 +6.23 1.39 An 8 speed automatic transmi ssion was selected as the improved technology. If the baseline is a 6

- Speed automatic, only 1.72% of savings could be expected. However, if the reference vehicle is now equipped with a 4

- Speed automatic gearbox, then the amount of fuel saved could reach 6. 23%.

**8.2.5 Engine** 

The modeling assumptions for the engine technology focused on the improvement of the efficiency through linear scaling of the entire map . Other technologies such as gasoline direct injection, turbo charging and downsizing could be considered but were not modeled.

Table 26 : Impact of Engine Efficiency alone on Fuel Consumption for the Class 2b Engine Peak Efficiency (%) Percent Fuel Saved for Conventional (%) Percent Fuel Saved for Hybrid (%) 34.7 0 0

35 +0.77

- 36 + 3.54

- 37 +6.16

- 38 +8.59 +8.86

The peak efficiency was linearly scaled to match the improvement goal. If this value is increased from 34.7% to 38%, roughly 9% of fuel savings can be expected for both conventional and hybrid

. For all the package simul ations where engine improvement was applied, a 38% peak efficiency value was used.

**8.2.6 Hybrid** 

The hybridization of the class 2b truck was assumed to be a parallel Hybrid Electric Vehicle equipped with a 50 kW electric machine . The features offered by such te chnologies are Engine Start/Stop61 Argonne National Laboratory

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– October 2009 operation s, regenerative braking, e lectric launch at low vehicle speeds and a blend of engine power and motor power depending on the Battery State of Charge

.
Table 27 : Impact of Hybridization on Fue l Consumption for the Class 2b Rolling Resistance Percent Fuel Saved compared to Conventional(%) Parallel HEV

– 50kW motor

– No change in weight +14.81

Parallel HEV

– 50kW motor

– + 100Kg weight +13.94

Parallel HEV

– 100 kW motor

– No change in weight +15 .27

Parallel HEV

– 100 kW motor

– +200Kg weight +13.42

Drive cycles such as UDDS or HWFET do not require a electric machine with a power greater than 50 kW in order to capture most of the braking energy. Consequently, the hybrid option with a 100kW elect ric machine was dismissed. The option which was chosen for package simulations was the 50kW electric machine with no change in weight.



### 8.3 **Fuel Savings for V**  **arious Technology Combinations**

In most cases, the sum of the fuel consumption benefits of individual technologies is greater than the ir combination. It is also interesting to notice that the fuel consumption reduction is always higher for the hybrid than for the conventional when the same technologies are applied.62 Argonne National Laboratory

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– October 2009 Figure 43 : F uel Consumption Savings by combining Aerodynamics and Weight improvements on a Conventional and Hybrid Baseline. Figure 43 shows an example of improvement package. In this case, a reduction in drag coefficient and weight is applie d to both the conventional and the hybrid baseline vehicles. The sum of individual technologies either equals the combination (for the conventional) or is greater than the combination (for the hybrid). This figure shows that by combining a lighter weight w ith improved aerodynamics, fuel consumption could drop by 4 to 5%. For most technology improvement s , t he hybrid baseline benefits more from these changes than the conventional. If we take the example of the drag coefficient, this can be explained by the fa ct that reducing it not only lowers the vehicle aerodynamic losses but also lowers the energy provided by the motor and thus the battery will require less charging from the engine. 

### 4.4% 5.1%

1.4% 1.4% 3.0% 3.8%

0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0%

Each technology (Conv) Combination (Conv) Each technology

(Hybrid) Combination (Hybrid)Percent Fuel Saved 

## Impact of Aero and Weight reduction on Fuel Consumption

Cd
Weight
Hybrid improvements63 Argonne National Laboratory

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– October 2009 Figure 44 : Fuel Consumption Savings by combinin g Aerodynamics, Rolling Resistance and Weight improvements on a Conventional and Hybrid Baseline. Figure 44 considers an additional improvement with the reduction of rolling resistance. In this situation also, the hybrid fuel savi ngs are greater than for the conventional when looking at individual technologies or packages. The combination of a light weighted vehicle with low rolling resistance and improved aerodynamics could save between 5.5 to 6.6%. 

### 5.5% 6.6%

1.4% 1.4% 3.0% 3.8% 1.2% 1.6%

0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 8.0% 9.0% 10.0%

Each technology (Conv) Combination (Conv) Each technology

(Hybrid) Combination (Hybrid)Percent Fuel Saved 

### Impact of Aero, Rolling Resistance and Weight on Fuel Consumption

RR

Cd

Weight

Hybrid improvements Baseline improvements64 Argonne National Laboratory

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– October 2009 Figure 45 : Fuel Consumption Savings by combining Aerodynamics, Rolling Resistance, Transmission and Weight improvements on a Conventional and Hybrid Baseline. Figure 45 adds the impact of an improved transmission to the previous fig ure. The percentage showed is for an 8

- Speed transmission in comparison to a 6

- Speed baseline vehicle . Since the reference vehicle has already an efficient transmissi on, this package does not reduce fuel consumption by a significant amount.

Figure 46 : Fuel Consumption Savings by combining all improvements on a Conventional and Hybrid Baseline. 

### 6.9% 7.9%

1.4% 1.4% 3.0% 3.8% 1.2% 1.6% 1.7% 1.4%

0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 8.0% 9.0% 10.0%

Each technology (Conv) Combination (Conv) Each technology

(Hybrid) Combination (Hybrid)Percent Fuel Saved 

### Impact of Aero, Rolling Resistance, Weight and Transmission on Fuel Consumption

Transmission

RR
Cd Weight Hybrid improvements Baseline improvements

14.9% 15.9%

1.4% 1.4% 3.0% 3.8% 1.2% 1.6% 1.7% 1.4% 8.6% 8.9%

0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0% 14.0% 16.0% 18.0% 20.0%

Each technology

(Conv) Combination (Conv) Each technology

(Hybrid) Combination (Hybrid)Percent Fuel Saved Impact of All Technologies on Fuel Consumption

Engine
Transmission

RR
Cd Weight Hybrid improvements Baseline improvements65 Argonne National Laboratory

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– October 2009 As showed by Figure 46 , adding the improved engine efficiency to the combination package increases the fuel savi ngs dramatically. This package can provide up to 15% fuel savings for the conventional and 16% for the hybrid.

Figure 47 : Fuel Consumption Savings by combining all technology improvements and hybridization on a Conventional Basel ine. Finally, Figure 47 shows the impact of the full improvement package (including all the previous discussed technologies and the hybridization of the vehicle to a parallel HEV). This combination predicts a 28.4% fuel consumptio n reduction.



### 8.4 **Comparison with TIAX Estimates**

This section compare s the fuel consumption reduction simulation estimates with the values generated by TIAX for the NAS committee

. 28.4%

1.4% 3.0% 1.2% 1.7% 8.6% 14.8%

0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0%

Each technology (Conv) Combination(Conv)Percent Fuel Saved 

### Impact of All technologies and Hybridization on Fuel Consumption Hybrid CS
Engine

Transmission

RR

Cd
Weight

Baseline improvements66 Argonne National Laboratory

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– October 2009 Figure 48 : Fuel Consumption Savings of Improvement Package using Simulation or TIAX Estimates
In Figure 48 , one notices that t he main differences come from the transmission and the engine. TIAX used a 4

- Speed transmission baseline vehicle whereas the simulation assumptions were b ased on a 6

- Speed configuration. In addition , the engine improvements for simulation only focused on peak efficiency while TIAX considered more advanced technologies. On Figure 49 the same comparison is made where both simulation and TIAX use a 4

- Speed baseline vehicle. Therefore the only major difference between the two studies remains in the engine technology improvement. For all the other technologies, TIAX and PSAT estimates are not significantly different. 28.4% 44.5%

1.4% 0.8% 3.0% 3.0% 1.2% 2.0% 1.7% 7.5% 8.6% 23.0% 14.8% 18.0%

0.0% 10.0% 20.0% 30.0% 40.0% 50.0%

Each technology

(PSAT) Combination (PSAT) Each technology (TIAX) Combination (TIAX)Percent Fuel Saved Technology Combination Impact for Simulation vs TIAX

Hybrid CS Engine Transmission RR Cd Weight Hybrid improvements Baseline improvements67 Argonne National Laboratory

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– October 2009 Figure 49 : Fuel Consumption Savings of Improvement Package using Simulation or TIAX Estimates when using the same baseline Transmission 31.7% 44.5%

1.4% 0.8% 3.0% 3.0% 1.2% 2.0% 6.2% 7.5% 8.6% 23.0% 14.8% 18.0%

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0%

Each technology (PSAT) Combination (PSAT) Each technology (TIAX) Combination (TIAX)Percent Fuel Saved 

### Technology Combination Impact for Simulation vs TIAX (same baseline transmission)

Hybrid CS Engine Transmission RR Cd Weight Hybrid improvements Baseline improvements68 Argonne National Laboratory

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## 9 **Conclusion**

Numerous simulation studies were performed to provide quantitative inputs to support the National A cademy committee recommendations. The simulation tool along with the vehicle and component assumptions was defined. Specific drive cycles were selected for the different applications considered. The study of the different metrics pointed out to the need to use fuel consumption rather than fuel economy. In addition, the payload should be considered as well to properly represent the work of the truck. As such, some metric related to Load Specific Fuel Consumption seem most appropriate to evaluate truck techno logies. The energy / power analysis highlighted the importance of the engine losses compared to the rest of the drivetrain. In addition, the average vehicle speed should be carefully considered when evaluating a technology since its influence on fuel co nsumption will greatly differ. While the average vehicle speed of a drive cycle correlates well with fuel consumption, the fuel consumed is always higher than during steady

- state operations, especially for urban driving (low average speed). Since a particu lar technology might have different influence based on the vehicle weight, representing its impact of several payloads would allow a more accurate evaluation.

T he impact of several individual technologies, both individual and cumulated, was assessed, inclu ding aerodynamic, rolling resistance, fuel type, transmission, engine and hybridization. The difference between the sums of each individual technology was compared with the gains of the cumulated technologies. The study demonstrated the usefulness of vehi cle modeling and simulation to assess the potential of numerous technologies for different drive cycles and operating conditions (e.g., payloads). However, because of the large number of applications and the fact that some vehicles are specifically designe d for customers, there is currently no widely accepted Vehicle Technical Specifications

– VTS

- (e.g., maximum vehicle speed, grade, performance...) for each option. Since technologies should be compared based on similar VTS, the definition of the vehicle ch aracteristics for powertrains such as HEVs becomes problematic. In addition, the limited access to specific state

- of

- the

- art data for all applications leads to using component with similar technologies, which is non

- ideal.69 Argonne National Laboratory

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## Appendix A

**– Overview of Drive**  **Cycles**70 Argonne National Laboratory

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– October 200972 Argonne National Laboratory

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– October 200973 Argonne National Laboratory

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– October 200974 Argonne National Laboratory

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– October 200975 Argonne National Laboratory

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## Appendix **B**

**– Energy / Power Flow** 

**Bus**

**- 10% Load** 

engine **η** =38% %Loss=62% 90.7 kW

56.3 kW mech. acc. **η** =50.6% %Loss=18.7% 34.4 kW

17 kW elec. acc. **η** =88.5% %Loss=2.2% 17.4 kW

2 kW trans. **η** =89.3% %Loss=1.8% 15.4 kW

1.64 kW axle **η** =97.1% %Loss=0.4% 13.8 kW

0.4 kW tires **η** =20.2% %Loss=11.8% 13.4 kW

10.7 kW aero **η** =16.3% %Loss=2.5% 2.71 kW

2.27 kW Power Flow Diagram - bus / SS 20 mph / 10% Load

engine **η** =39.9% %Loss=60.1% 138 kW

82.8 kW mech. acc. **η** =69% %Loss=12.4% 54.9 kW

17 kW elec. acc. **η** =94.7% %Loss=1.5% 37.9 kW

2 kW trans. **η** =94.7% %Loss=1.4% 35.9 kW

1.89 kW axle **η** =97% %Loss=0.7% 34 kW

1.01 kW tires **η** =38.3% %Loss=14.8% 33 kW

20.3 kW aero **η** =3.4% %Loss=8.8% 12.6 kW

12.2 kW Power Flow Diagram - bus / SS 35 mph / 10% Load

engine **η** =41.2% %Loss=58.8% 220 kW

129 kW mech. acc. **η** =81.3% %Loss=7.7% 90.7 kW

17 kW elec. acc. **η** =97.3% %Loss=0.9% 73.7 kW

2 kW trans. **η** =96.8% %Loss=1% 71.7 kW

2.27 kW axle **η** =97% %Loss=0.9% 69.4 kW

2.07 kW tires **η** =53.3% %Loss=14.3% 67.4 kW

31.4 kW aero **η** =1.2% %Loss=16.1% 35.9 kW

35.5 kW Power Flow Diagram - bus / SS 50 mph / 10% Load77 Argonne National Laboratory

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– October 2009 10 20 30 40 50 60 0 20 40 60 80 100 120

Average speed (mph)Contribution to total loss (%) Repartition of losses - bus / SS / 10 % Load engine mech. acc. elec. acc. trans. axle tires
aero Total losses x.1 (kW)

62% 19% 2% 2% < 1% 12% 3% 20 mph (Losses = 90.2 kW)

61% 17% 2% 2% < 1% 13% 4% 25 mph (Losses = 102 kW)

60% 15% 2% 1% < 1% 15% 7% 30 mph (Losses = 113 kW)

60% 12% 1% 1% < 1% 15% 9% 35 mph (Losses = 137 kW)

59% 11% 1% 1% < 1% 15% 12% 40 mph (Losses = 156 kW)

59% 9% 1% 1% < 1% 15% 14% 45 mph (Losses = 187 kW)

59%
8% < 1%

1% < 1%

14% 16% 50 mph (Losses = 219 kW) engine mech. acc. elec. acc. trans. axle tires
aero78 Argonne National Laboratory

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### Bus

**- 50% Load** 

engine **η** =38.1% %Loss=61.9% 93.8 kW

58.1 kW mech. acc. **η** =52.5% %Loss=18.1% 35.8 kW

17 kW elec. acc. **η** =89.3% %Loss=2.1% 18.8 kW

2 kW trans. **η** =89.5% %Loss=1.9% 16.8 kW

1.77 kW axle **η** =97.1% %Loss=0.5% 15 kW

0.437 kW tires **η** =18.6% %Loss=12.6% 14.6 kW

11.8 kW aero **η** =16.3% %Loss=2.4% 2.71 kW

2.27 kW Power Flow Diagram - bus / SS 20 mph / 50% Load

engine **η** =40% %Loss=60% 144 kW

86.2 kW mech. acc. **η** =70.4% %Loss=11.8% 57.4 kW

17 kW elec. acc. **η** =95% %Loss=1.4% 40.4 kW

2 kW trans. **η** =94.5% %Loss=1.5% 38.4 kW

2.11 kW axle **η** =97% %Loss=0.7% 36.3 kW

1.07 kW tires **η** =35.8% %Loss=15.7% 35.2 kW

22.6 kW aero **η** =3.4% %Loss=8.5% 12.6 kW

12.2 kW Power Flow Diagram - bus / SS 35 mph / 50% Load

engine **η** =41.2% %Loss=58.8% 229 kW

134 kW mech. acc. **η** =82% %Loss=7.4% 94.3 kW

17 kW elec. acc. **η** =97.4% %Loss=0.9% 77.3 kW

2 kW trans. **η** =96.9% %Loss=1% 75.3 kW

2.34 kW axle **η** =97% %Loss=1% 73 kW

2.18 kW tires **η** =50.7% %Loss=15.3% 70.8 kW

34.9 kW aero **η** =1.2% %Loss=15.5% 35.9 kW

35.5 kW Power Flow Diagram - bus / SS 50 mph / 50% Load79 Argonne National Laboratory

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– October 2009 10 20 30 40 50 60 0 20 40 60 80 100 120

Average speed (mph)Contribution to total loss (%) Repartition of losses - bus / SS / 50 % Load engine mech. acc. elec. acc. trans. axle tires
aero Total losses x.1 (kW)

62% 18% 2% 2% < 1% 13% 2% 20 mph (Losses = 93.3 kW)

61% 16% 2% 2% < 1% 14% 4% 25 mph (Losses = 106 kW)

59% 14% 2% 1% < 1% 16% 7% 30 mph (Losses = 118 kW)

60% 12% 1% 1% < 1% 16% 9% 35 mph (Losses = 143 kW)

59% 10% 1% 1% < 1% 16% 11% 40 mph (Losses = 163 kW)

59% 9% 1% 1% < 1% 16% 13% 45 mph (Losses = 194 kW)

59%
7% < 1%

1% < 1%

15% 16% 50 mph (Losses = 228 kW) engine mech. acc. elec. acc. trans. axle tires
aero80 Argonne National Laboratory

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### Bus

**- 100% Load** 

engine **η** =39.9% %Loss=60.1% 92.6 kW

55.7 kW mech. acc. **η** =54% %Loss=18.4% 36.9 kW

17 kW elec. acc. **η** =90% %Loss=2.2% 19.9 kW

2 kW trans. **η** =91.9% %Loss=1.6% 17.9 kW

1.45 kW axle **η** =97.1% %Loss=0.5% 16.5 kW

0.482 kW tires **η** =16.8% %Loss=14.4% 16 kW

13.3 kW aero **η** =15.5% %Loss=2.5% 2.69 kW

2.27 kW Power Flow Diagram - bus / SS 20 mph / 100% Load

engine **η** =40.1% %Loss=59.9% 151 kW

90.5 kW mech. acc. **η** =71.9% %Loss=11.3% 60.5 kW

17 kW elec. acc. **η** =95.4% %Loss=1.3% 43.5 kW

2 kW trans. **η** =94.3% %Loss=1.6% 41.5 kW

2.38 kW axle **η** =97% %Loss=0.8% 39.1 kW

1.16 kW tires **η** =33.2% %Loss=16.8% 38 kW

25.4 kW aero **η** =3.5% %Loss=8.1% 12.6 kW

12.2 kW Power Flow Diagram - bus / SS 35 mph / 100% Load

engine **η** =41.3% %Loss=58.7% 240 kW

141 kW mech. acc. **η** =82.8% %Loss=7.1% 98.8 kW

17 kW elec. acc. **η** =97.6% %Loss=0.8% 81.8 kW

2 kW trans. **η** =97% %Loss=1% 79.8 kW

2.43 kW axle **η** =97% %Loss=1% 77.4 kW

2.31 kW tires **η** =47.8% %Loss=16.4% 75.1 kW

39.2 kW aero **η** =1.2% %Loss=14.8% 35.9 kW

35.5 kW Power Flow Diagram - bus / SS 50 mph / 100% Load81 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 10 20 30 40 50 60 0 20 40 60 80 100 120

Average speed (mph)Contribution to total loss (%) Repartition of losses - bus / SS / 100 % Load engine mech. acc. elec. acc. trans. axle tires
aero Total losses x.1 (kW)

60% 18% 2% 2% < 1% 14% 2% 20 mph (Losses = 92.1 kW)

61% 15% 2% 2% < 1% 15% 4% 25 mph (Losses = 111 kW)

59% 14% 2% 1% < 1% 17% 6% 30 mph (Losses = 124 kW)

60% 11% 1% 2% < 1% 17% 8% 35 mph (Losses = 150 kW)

59% 10% 1% 1% < 1% 17% 11% 40 mph (Losses = 171 kW)

59% 8% < 1%

1% < 1% 17% 13% 45 mph (Losses = 203 kW)

59%
7% < 1%

1% < 1%

16% 15% 50 mph (Losses = 239 kW) engine mech. acc. elec. acc. trans. axle tires
aero82 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 

### Class 2b (Pick

**- up)** 

**- 10% Load** 

engine **η** =7.8% %Loss=92.2% 89.2 kW

82.2 kW mech. acc. **η** =100% %Loss=0% 6.97 kW

0 kW elec. acc. **η** =89.4% %Loss=0.8% 6.97 kW

0.74 kW trans. **η** =89.9% %Loss=0.7% 6.23 kW

0.63 kW axle **η** =97.1% %Loss=0.2% 5.6 kW

0.163 kW tires **η** =41.5% %Loss=3.6% 5.44 kW

3.18 kW aero **η** =6.9% %Loss=2.4% 2.26 kW

2.1 kW Power Flow Diagram - cl2b / SS 30 mph / 10% Load

engine **η** =16.1% %Loss=83.9% 112 kW

93.6 kW mech. acc. **η** =100% %Loss=0% 18 kW

0 kW elec. acc. **η** =95.9% %Loss=0.7% 18 kW

0.74 kW trans. **η** =94.8% %Loss=0.8% 17.2 kW

0.891 kW axle **η** =97% %Loss=0.4% 16.4 kW

0.486 kW tires **η** =62.4% %Loss=5.3% 15.9 kW

5.96 kW aero **η** =1.6% %Loss=8.7% 9.91 kW

9.75 kW Power Flow Diagram - cl2b / SS 50 mph / 10% Load

engine **η** =24.4% %Loss=75.6% 163 kW

123 kW mech. acc. **η** =100% %Loss=0% 39.6 kW

0 kW elec. acc. **η** =98.1% %Loss=0.5% 39.6 kW

0.74 kW trans. **η** =96% %Loss=1% 38.9 kW

1.56 kW axle **η** =97% %Loss=0.7% 37.3 kW

1.11 kW tires **η** =74.4% %Loss=5.7% 36.2 kW

9.27 kW aero **η** =0.6% %Loss=16.5% 26.9 kW

26.8 kW Power Flow Diagram - cl2b / SS 70 mph / 10% Load83 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 20 40 60 80 0 20 40 60 80 100 120

Average speed (mph)Contribution to total loss (%) Repartition of losses - cl2b / SS / 10 % Load engine mech. acc. elec. acc. trans. axle tires
aero Total losses x.1 (kW)

92% < 1% < 1% < 1% 4% 2% 30 mph (Losses = 88.9 kW)

92% < 1% < 1% < 1% 4% 3% 35 mph (Losses = 109 kW)

86% < 1% < 1% < 1% 6% 6% 40 mph (Losses = 80.7 kW)

85% < 1% < 1% 6% 8% 45 mph (Losses = 94.1 kW)

84% < 1% < 1% < 1% 5% 9% 50 mph (Losses = 111 kW)

78% < 1% < 1% 7% 13% 55 mph (Losses = 102 kW)

78% < 1% 1% < 1% 6% 14% 60 mph (Losses = 121 kW)

77% < 1% 1% < 1% 6% 15% 65 mph (Losses = 140 kW)

76% < 1% 6% 16% 70 mph (Losses = 162 kW) engine elec. acc. trans. axle tires
aero84 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 

### Class 2b (Pick

**- up)** 

**- 50% Load** 

engine **η** =8.6% %Loss=91.4% 89.2 kW

81.5 kW mech. acc. **η** =100% %Loss=0% 7.71 kW

0 kW elec. acc. **η** =90.4% %Loss=0.8% 7.71 kW

0.74 kW trans. **η** =90.5% %Loss=0.7% 6.97 kW

0.66 kW axle **η** =97.1% %Loss=0.2% 6.31 kW

0.184 kW tires **η** =36.9% %Loss=4.3% 6.12 kW

3.86 kW aero **η** =6.9% %Loss=2.4% 2.26 kW

2.1 kW Power Flow Diagram - cl2b / SS 30 mph / 50% Load

engine **η** =17.3% %Loss=82.7% 112 kW

92.2 kW mech. acc. **η** =100% %Loss=0% 19.4 kW

0 kW elec. acc. **η** =96.2% %Loss=0.7% 19.4 kW

0.74 kW trans. **η** =95% %Loss=0.8% 18.6 kW

0.938 kW axle **η** =97% %Loss=0.5% 17.7 kW

0.526 kW tires **η** =57.8% %Loss=6.5% 17.1 kW

7.24 kW aero **η** =1.6% %Loss=8.7% 9.9 kW

9.75 kW Power Flow Diagram - cl2b / SS 50 mph / 50% Load

engine **η** =25.3% %Loss=74.7% 164 kW

123 kW mech. acc. **η** =100% %Loss=0% 41.7 kW

0 kW elec. acc. **η** =98.2% %Loss=0.5% 41.7 kW

0.74 kW trans. **η** =96.2% %Loss=1% 40.9 kW

1.57 kW axle **η** =97% %Loss=0.7% 39.4 kW

1.18 kW tires **η** =70.5% %Loss=6.9% 38.2 kW

11.3 kW aero **η** =0.6% %Loss=16.3% 26.9 kW

26.8 kW Power Flow Diagram - cl2b / SS 70 mph / 50% Load85 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 20 40 60 80 0 20 40 60 80 100 120

Average speed (mph)Contribution to total loss (%) Repartition of losses - cl2b / SS / 50 % Load engine mech. acc. elec. acc. trans. axle tires
aero Total losses x.1 (kW)

92% < 1% < 1% 4% 2% 30 mph (Losses = 88.9 kW)

91% < 1% < 1% < 1% 4% 3% 35 mph (Losses = 109 kW)

85% < 1% < 1% < 1% 7% 6% 40 mph (Losses = 80.7 kW)

84% < 1% < 1% 7% 8% 45 mph (Losses = 94.1 kW)

83% < 1% < 1% 7% 9% 50 mph (Losses = 111 kW)

77% < 1% 1% < 1% 8% 12% 55 mph (Losses = 104 kW)

77% < 1% 1% < 1% 7% 14% 60 mph (Losses = 123 kW)

76% < 1% 1% < 1% 7% 15% 65 mph (Losses = 142 kW)

75% < 1% 7% 16% 70 mph (Losses = 164 kW) engine elec. acc. trans. axle tires
aero86 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 

### Class 2b (Pick

**- up)** 

**- 100% Load** 

engine **η** =9.7% %Loss=90.3% 89.2 kW

80.5 kW mech. acc. **η** =100% %Loss=0% 8.63 kW

0 kW elec. acc. **η** =91.4% %Loss=0.8% 8.63 kW

0.74 kW trans. **η** =91.1% %Loss=0.8% 7.89 kW

0.699 kW axle **η** =97.1% %Loss=0.2% 7.19 kW

0.211 kW tires **η** =32.4% %Loss=5.3% 6.98 kW

4.72 kW aero **η** =6.9% %Loss=2.4% 2.26 kW

2.1 kW Power Flow Diagram - cl2b / SS 30 mph / 100% Load

engine **η** =22.7% %Loss=77.3% 92.6 kW

71.6 kW mech. acc. **η** =100% %Loss=0% 21 kW

0 kW elec. acc. **η** =96.5% %Loss=0.8% 21 kW

0.74 kW trans. **η** =95.4% %Loss=1% 20.3 kW

0.935 kW axle **η** =97% %Loss=0.6% 19.3 kW

0.575 kW tires **η** =52.8% %Loss=9.6% 18.8 kW

8.85 kW aero **η** =1.6% %Loss=10.5% 9.9 kW

9.75 kW Power Flow Diagram - cl2b / SS 50 mph / 100% Load

engine **η** =26.5% %Loss=73.5% 167 kW

122 kW mech. acc. **η** =100% %Loss=0% 44.2 kW

0 kW elec. acc. **η** =98.3% %Loss=0.4% 44.2 kW

0.74 kW trans. **η** =96.4% %Loss=0.9% 43.5 kW

1.58 kW axle **η** =97% %Loss=0.8% 41.9 kW

1.25 kW tires **η** =66.2% %Loss=8.3% 40.7 kW

13.8 kW aero **η** =0.6% %Loss=16.1% 26.9 kW

26.8 kW Power Flow Diagram - cl2b / SS 70 mph / 100% Load87 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 20 40 60 80 0 20 40 60 80 100 120

Average speed (mph)Contribution to total loss (%) Repartition of losses - cl2b / SS / 100 % Load engine mech. acc. elec. acc. trans. axle tires
aero Total losses x.1 (kW)

90% < 1% < 1% < 1% 5% 2% 30 mph (Losses = 88.9 kW)

90% < 1% < 1% 5% 3% 35 mph (Losses = 109 kW)

83% < 1% < 1% < 1% 8% 6% 40 mph (Losses = 80.7 kW)

82% < 1% < 1% 8% 8% 45 mph (Losses = 94.1 kW)

77% < 1% 1% < 1% 10% 11% 50 mph (Losses = 92.4 kW)

76% < 1% 1% < 1% 9% 12% 55 mph (Losses = 106 kW)

75% < 1% 1% < 1% 9% 13% 60 mph (Losses = 125 kW)

74% < 1% < 1% 9% 15% 65 mph (Losses = 144 kW)

74% < 1% 8% 16% 70 mph (Losses = 166 kW)
engine elec. acc. trans. axle tires
aero88 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 

### Class 6 (Pick

**- up and Delivery)** 

**- 10% Load** 

engine **η** =22.7% %Loss=77.3% 83.4 kW

64.5 kW mech. acc. **η** =97.4% %Loss=0.6% 18.9 kW

0.5 kW elec. acc. **η** =94.6% %Loss=1.2% 18.4 kW

1 kW 17.4 kW

1.67 kW axle **η** =98% %Loss=0.4% 15.7 kW

0.31 kW tires **η** =53% %Loss=8.7% 15.4 kW

7.24 kW aero **η** =2.6% %Loss=9.5% 8.17 kW

7.96 kW trans. **η** =90.4% %Loss=2% Power Flow Diagram - cl6 / SS 30 mph / 10% Load

engine **η** =38% %Loss=62% 282 kW

175 kW mech. acc. **η** =99.5% %Loss=0.2% 107 kW

0.5 kW elec. acc. **η** =99.1% %Loss=0.4% 107 kW

1 kW trans. **η** =96.6% %Loss=1.3% 106 kW

3.61 kW axle **η** =98% %Loss=0.7% 102 kW

2.03 kW tires **η** =81.5% %Loss=6.6% 99.9 kW

18.5 kW aero **η** =0.3% %Loss=28.8% 81.4 kW

81.2 kW Power Flow Diagram - cl6 / SS 65 mph / 10% Load

engine **η** =36.7% %Loss=63.3% 152 kW

96.2 kW mech. acc. **η** =99.1% %Loss=0.3% 55.8 kW

0.5 kW elec. acc. **η** =98.2% %Loss=0.7% 55.3 kW

1 kW trans. **η** =94.7% %Loss=1.9% 54.3 kW

2.87 kW axle **η** =98% %Loss=0.7% 51.5 kW

1.02 kW tires **η** =73.6% %Loss=8.8% 50.4 kW

13.3 kW aero **η** =0.6% %Loss=24.3% 37.1 kW

36.9 kW Power Flow Diagram - cl6 / SS 50 mph / 10% Load89 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 20 40 60 80 0 20 40 60 80 100 120

Average speed (mph)Contribution to total loss (%) Repartition of losses - cl6 / SS / 10 % Load engine mech. acc. elec. acc. trans. axle tires
aero Total losses x.1 (kW)

78% < 1% 1% 2% < 1% 9% 10% 30 mph (Losses = 83.1 kW)

77% < 1% 2% < 1% 8% 11% 35 mph (Losses = 111 kW)

63% < 1% 1% 2% < 1%

11% 21% 40 mph (Losses = 90 kW)

63% < 1% < 1%

2% < 1%

10% 23% 45 mph (Losses = 116 kW)

63% < 1% < 1%

2% < 1%

9% 24% 50 mph (Losses = 152 kW)

61%
< 1% 1% < 1%

8% 28% 55 mph (Losses = 178 kW)

62% < 1% 1% < 1%

7% 28% 60 mph (Losses = 226 kW)

62% < 1% 1% < 1%

7% 29% 65 mph (Losses = 281 kW)

63% < 1% 1% < 1%

6% 29% 70 mph (Losses = 350 kW) engine mech. acc. elec. acc. trans. axle tires
aero90 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 

### Class 6 (Pick

**- up and Delivery)** 

**- 50% Load** 

engine **η** =26.6% %Loss=73.4% 87.7 kW

64.3 kW mech. acc. **η** =97.9% %Loss=0.6% 23.4 kW

0.5 kW elec. acc. **η** =95.6% %Loss=1.1% 22.9 kW

1 kW trans. **η** =90.9% %Loss=2.3% 21.9 kW

1.99 kW axle **η** =98% %Loss=0.4% 19.9 kW

0.393 kW tires **η** =41.9% %Loss=12.9% 19.5 kW

11.3 kW aero **η** =2.6% %Loss=9.1% 8.16 kW

7.95 kW Power Flow Diagram - cl6 / SS 30 mph / 50% Load

engine **η** =37.9% %Loss=62.1% 311 kW

193 kW mech. acc. **η** =99.6% %Loss=0.2% 118 kW

0.5 kW elec. acc. **η** =99.1% %Loss=0.3% 117 kW

1 kW trans. **η** =96.7% %Loss=1.2% 116 kW

3.85 kW axle **η** =98% %Loss=0.7% 112 kW

2.25 kW tires **η** =73.8% %Loss=9.3% 110 kW

28.9 kW aero **η** =0.3% %Loss=26.1% 81.4 kW

81.1 kW Power Flow Diagram - cl6 / SS 65 mph / 50% Load

engine **η** =37.3% %Loss=62.7% 172 kW

108 kW mech. acc. **η** =99.2% %Loss=0.3% 64.2 kW

0.5 kW elec. acc. **η** =98.4% %Loss=0.6% 63.7 kW

1 kW trans. **η** =94.2% %Loss=2.1% 62.7 kW

3.64 kW axle **η** =98% %Loss=0.7% 59.1 kW

1.18 kW tires **η** =64.1% %Loss=12.1% 57.9 kW

20.8 kW aero **η** =0.6% %Loss=21.4% 37.1 kW

36.9 kW Power Flow Diagram - cl6 / SS 50 mph / 50% Load91 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 20 40 60 80 0 20 40 60 80 100 120

Average speed (mph)Contribution to total loss (%) Repartition of losses - cl6 / SS / 50 % Load engine mech. acc. elec. acc. trans. axle tires
aero Total losses x.1 (kW)

74% < 1% 1% 2% < 1% 13% 9% 30 mph (Losses = 87.4 kW)

73% < 1% 2% < 1% 12% 11% 35 mph (Losses = 115 kW)

61% < 1% < 1%

2% < 1%

16% 19% 40 mph (Losses = 101 kW)

62% < 1% < 1%

2% < 1%

14% 20% 45 mph (Losses = 133 kW)

63% < 1% 2% < 1%

12% 21% 50 mph (Losses = 172 kW)

61%
< 1% 1% < 1%

12% 24% 55 mph (Losses = 201 kW)

62% < 1% 1% < 1%

10% 25% 60 mph (Losses = 251 kW)

62% < 1% 1% < 1%

9% 26% 65 mph (Losses = 310 kW)

63% < 1% 1% < 1%

8% 27% 70 mph (Losses = 379 kW) engine mech. acc. elec. acc. trans. axle tires
aero92 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 

### Class 6 (Pick

**- up and Delivery)** 

**- 100% Load** 

engine **η** =31.1% %Loss=68.9% 93.1 kW

64.1 kW mech. acc. **η** =98.3% %Loss=0.5% 28.9 kW

0.5 kW elec. acc. **η** =96.5% %Loss=1.1% 28.4 kW

1 kW trans. **η** =91.3% %Loss=2.6% 27.4 kW

2.4 kW axle **η** =98% %Loss=0.5% 25 kW

0.497 kW tires **η** =33.2% %Loss=17.6% 24.6 kW

16.4 kW aero **η** =2.6% %Loss=8.5% 8.15 kW

7.94 kW Power Flow Diagram - cl6 / SS 30 mph / 100% Load

engine **η** =37.5% %Loss=62.5% 198 kW

124 kW mech. acc. **η** =99.3% %Loss=0.3% 74.4 kW

0.5 kW elec. acc. **η** =98.6% %Loss=0.5% 73.9 kW

1 kW trans. **η** =94% %Loss=2.2% 72.9 kW

4.35 kW axle **η** =98% %Loss=0.7% 68.6 kW

1.37 kW tires **η** =55.2% %Loss=15.2% 67.2 kW

30.1 kW aero **η** =0.6% %Loss=18.6% 37.1 kW

36.9 kW Power Flow Diagram - cl6 / SS 50 mph / 100% Load

engine **η** =38.1% %Loss=61.9% 345 kW

214 kW mech. acc. **η** =99.6% %Loss=0.1% 131 kW

0.5 kW elec. acc. **η** =99.2% %Loss=0.3% 131 kW

1 kW trans. **η** =96.8% %Loss=1.2% 130 kW

4.16 kW axle **η** =98% %Loss=0.7% 126 kW

2.51 kW tires **η** =66% %Loss=12.1% 123 kW

41.9 kW aero **η** =0.3% %Loss=23.5% 81.3 kW

81.1 kW Power Flow Diagram - cl6 / SS 65 mph / 100% Load93 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 20 30 40 50 60 70 0 20 40 60 80 100 120

Average speed (mph)Contribution to total loss (%) Repartition of losses - cl6 / SS / 100 % Load engine mech. acc. elec. acc. trans. axle tires
aero Total losses x.1 (kW)

69% < 1% 1% 3% < 1% 18% 9% 30 mph (Losses = 92.8 kW)

69% < 1% 3% < 1% 16% 10% 35 mph (Losses = 120 kW)

61%
< 1% < 1%

2% < 1%

19% 16% 40 mph (Losses = 120 kW)

62% < 1% 2% < 1%

17% 17% 45 mph (Losses = 155 kW)

63% < 1% 2% < 1%

15% 19% 50 mph (Losses = 198 kW)

61%
< 1% 1% < 1% 15% 21% 55 mph (Losses = 230 kW)

61% < 1% 1% < 1%

13% 23% 60 mph (Losses = 282 kW)

62% < 1% 1% < 1%

12% 24% 65 mph (Losses = 344 kW)

62% < 1% 1% < 1%

11% 24% 69 mph (Losses = 397 kW) engine mech. acc. elec. acc. trans. axle tires
aero94 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 

### Class 8 (Tractor

**- Trailer)** 

**- 10% Load** 

engine **η** =38.7% %Loss=61.3% 196 kW

120 kW mech. acc. **η** =N/A %Loss=2.7% 75.9 kW

5.21 kW elec. acc. **η** =N/A %Loss=0.2% 70.7 kW

0.36 kW gearbox **η** =98.1% %Loss=0.7% 70.3 kW

1.34 kW axle **η** =98% %Loss=0.7% 69 kW

1.37 kW tires **η** =N/A %Loss=13.9% 67.6 kW

27.3 kW aero **η** =N/A %Loss=20.5% 40.3 kW

40.3 kW Power Flow Diagram - class8 / SS 50 mph / 10% Load

engine **η** =40.7% %Loss=59.3% 280 kW

166 kW mech. acc. **η** =N/A %Loss=1.9% 114 kW

5.2 kW elec. acc. **η** =N/A %Loss=0.1% 109 kW

0.36 kW gearbox **η** =98.1% %Loss=0.7% 109 kW

2.06 kW axle **η** =98% %Loss=0.8% 106 kW

2.12 kW tires **η** =N/A %Loss=12.4% 104 kW

34.6 kW aero **η** =N/A %Loss=24.8% 69.7 kW

69.6 kW Power Flow Diagram - class8 / SS 60 mph / 10% Load

engine **η** =40.5% %Loss=59.5% 407 kW

242 kW mech. acc. **η** =N/A %Loss=1.3% 165 kW

5.2 kW elec. acc. **η** =N/A %Loss=0.1% 160 kW

0.36 kW gearbox **η** =98.1% %Loss=0.7% 159 kW

3.03 kW axle **η** =98% %Loss=0.8% 156 kW

3.11 kW tires **η** =N/A %Loss=10.5% 153 kW

42.6 kW aero **η** =N/A %Loss=27.2% 111 kW

111 kW Power Flow Diagram - class8 / SS 70 mph / 10% Load95 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 40 50 60 70 80 0 10 20 30 40 50 60 70 80 90 100

Average speed (mph)Contribution to total loss (%) Repartition of losses - class8 / SS / 10 % Load engine mech. acc. elec. acc. gearbox axle tires
aero Total losses x.1 (kW)

61%

3% < 1% < 1% < 1% 14% 21% 50 mph (Losses = 196 kW)

60%

2% < 1% < 1% < 1% 13% 23% 55 mph (Losses = 234 kW)

59%

2% < 1% < 1% < 1% 12% 25% 60 mph (Losses = 280 kW)

59%

2% < 1% < 1% < 1% 11% 26% 65 mph (Losses = 338 kW)

59%

1% < 1% < 1% < 1% 10% 27% 70 mph (Losses = 406 kW)

engine mech. acc. elec. acc. gearbox axle tires
aero96 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 

### Class 8 (Tractor

**- Trailer)** 

**- 50% Load** 

engine **η** =39.6% %Loss=60.4% 225 kW

136 kW mech. acc. **η** =N/A %Loss=2.3% 89.1 kW

5.21 kW elec. acc. **η** =N/A %Loss=0.2% 83.9 kW

0.36 kW gearbox **η** =98.1% %Loss=0.7% 83.5 kW

1.59 kW axle **η** =98% %Loss=0.7% 81.9 kW

1.63 kW tires **η** =N/A %Loss=17.8% 80.3 kW

40 kW aero **η** =N/A %Loss=17.9% 40.3 kW

40.3 kW Power Flow Diagram - class8 / SS 50 mph / 50% Load

engine **η** =41.7% %Loss=58.3% 314 kW

183 kW mech. acc. **η** =N/A %Loss=1.7% 131 kW

5.2 kW elec. acc. **η** =N/A %Loss=0.1% 126 kW

0.36 kW gearbox **η** =98.1% %Loss=0.8% 125 kW

2.38 kW axle **η** =98% %Loss=0.8% 123 kW

2.44 kW tires **η** =N/A %Loss=16.2% 120 kW

50.7 kW aero **η** =N/A %Loss=22.2% 69.7 kW

69.6 kW Power Flow Diagram - class8 / SS 60 mph / 50% Load

engine **η** =40.9% %Loss=59.1% 453 kW

268 kW mech. acc. **η** =N/A %Loss=1.1% 186 kW

5.2 kW elec. acc. **η** =N/A %Loss=0.1% 180 kW

0.36 kW gearbox **η** =98.1% %Loss=0.8% 180 kW

3.42 kW axle **η** =98% %Loss=0.8% 177 kW

3.51 kW tires **η** =N/A %Loss=13.8% 173 kW

62.4 kW aero **η** =N/A %Loss=24.4% 111 kW

111 kW Power Flow Diagram - class8 / SS 70 mph / 50% Load9 7 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 40 50 60 70 80 0 10 20 30 40 50 60 70 80 90 100

Average speed (mph)Contribution to total loss (%) Repartition of losses - class8 / SS / 50 % Load engine mech. acc. elec. acc. gearbox axle tires
aero Total losses x.1 (kW)

60%

2% < 1% < 1% < 1% 18% 18% 50 mph (Losses = 225 kW)

59%

2% < 1% < 1% < 1% 17% 20% 55 mph (Losses = 264 kW)

58%

2% < 1% < 1% < 1% 16% 22% 60 mph (Losses = 314 kW)

58%

1% < 1% < 1% < 1% 15% 24% 65 mph (Losses = 375 kW)

59%

1% < 1% < 1% < 1% 14% 24% 70 mph (Losses = 453 kW)

engine mech. acc. elec. acc. gearbox axle tires
aero98 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 

### Class 8 (Tractor

**- Trailer)** 

**- 100% Load** 

engine **η** =40.6% %Loss=59.4% 260 kW

155 kW mech. acc. **η** =N/A %Loss=2% 106 kW

5.21 kW elec. acc. **η** =N/A %Loss=0.1% 100 kW

0.36 kW gearbox **η** =98.1% %Loss=0.7% 100 kW

1.9 kW axle **η** =98% %Loss=0.8% 98.1 kW

1.95 kW tires **η** =N/A %Loss=21.5% 96.1 kW

55.8 kW aero **η** =N/A %Loss=15.5% 40.3 kW

40.3 kW Power Flow Diagram - class8 / SS 50 mph / 100% Load

engine **η** =42.3% %Loss=57.7% 359 kW

207 kW mech. acc. **η** =N/A %Loss=1.4% 152 kW

5.2 kW elec. acc. **η** =N/A %Loss=0.1% 146 kW

0.36 kW gearbox **η** =98.1% %Loss=0.8% 146 kW

2.78 kW axle **η** =98% %Loss=0.8% 143 kW

2.85 kW tires **η** =N/A %Loss=19.7% 141 kW

70.8 kW aero **η** =N/A %Loss=19.4% 69.7 kW

69.6 kW Power Flow Diagram - class8 / SS 60 mph / 100% Load

engine **η** =40.6% %Loss=59.4% 520 kW

309 kW mech. acc. **η** =N/A %Loss=1% 211 kW

5.2 kW elec. acc. **η** =N/A %Loss=0.1% 206 kW

0.36 kW gearbox **η** =98.1% %Loss=0.8% 206 kW

3.91 kW axle **η** =98% %Loss=0.8% 202 kW

4.01 kW tires **η** =N/A %Loss=16.7% 198 kW

87.1 kW aero **η** =N/A %Loss=21.3% 111 kW

111 kW Power Flow Diagram - class8 / SS 70 mph / 100% Load99 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 59%

2% < 1% < 1% < 1% 21% 15% 50 mph (Losses = 260 kW)

58%

2% < 1% < 1% < 1% 21% 18% 55 mph (Losses = 302 kW)

58%

1% < 1% < 1% < 1% 20% 19% 60 mph (Losses = 359 kW)

58%

1% < 1% < 1% < 1% 19% 21% 65 mph (Losses = 425 kW)

59%

1% < 1% < 1% < 1% 17% 21% 70 mph (Losses = 519 kW)

engine mech. acc. elec. acc. gearbox axle tires
aero

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

Average speed (mph)Contribution to total loss (%) Repartition of losses - class8 / SS / 100 % Load engine mech. acc. elec. acc. gearbox axle tires
aero Total losses x.1 (kW)100 Argonne National Laboratory

– Report to NAS

– Contract DEPS

- BEES

- 001

– October 2009 

### Bibliography

1. http://www.gmc.com/sierra/2500HD/ 2. http://www .dieselnet.com/standards/cycles/hhddt.html 3. http://eogld.ecomm.gm.com/images/mediumduty/techspecs/engine.pdf 4. http://eogld.ecomm.gm.com/NASApp/mediumduty/gmmd_home.jsp 5. http://media.gm.com/us/powertrain/en/product_services/2007/Spec%20Sheet/Gen %20III/ 2007%20LM7_L59%20V8.xls