# Peer Review of the Greenhouse Gas Emissions Model (GEM) and EPA’s Response to Comments

Phase II

# Peer Review of the Greenhouse Gas Emissions Model (GEM) and EPA’s Response to Comments

Phase II

Assessment and Standards Division Office of Transportation and Air Quality U.S. Environmental Protection Agency

Prepared for EPA by
Versar, Inc.

EPA Contract No. EP-C-12-045 Work Assignment No. 44

EPA-420-R-15-009

June 2015External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

TABLE OF C ONTENTS

A. INTRODUCTION

................................................................................................................... 1

B. CHARGE TO REVIEWERS

.................................................................................................. 3

C. SUM MARY OF PEER REVIEWER COMMENTS BY QUESTION

................................... 6

GENERAL IMPRESSIONS

................................................................................................... 7 CHARGE QUESTION 1

........................................................................................................ 7 CHARGE QUESTION 2

........................................................................................................ 8 CHARGE QUESTION 3

........................................................................................................ 9 CHARGE QUESTION 4

...................................................................................................... 10 CHARGE QUESTION 5

...................................................................................................... 10

D. PEER REVIEWER COMMENTS BY CHARGE QUESTION

.............................................. 12

Table 1. General Impressions

................................................................................................ 13 Table 2. Charge Question 1

................................................................................................... 18 Table 3. Charge Question 2

................................................................................................... 27 Table 4. Charge Question 3

................................................................................................... 54

Ta ble 5. Charge Question 4

................................................................................................... 57 Table 6. Charge Question 5

................................................................................................... 60 Table 7. Specific Observations on Tool Description Entitled, “Vehicle Simulation Model” 65 Table 8. Specific Observations on Electronic Model Entitled, “GEM Tool”

....................... 76

E. INDIVIDUAL PEER REVI EWER COMMENTS

............................................................... 82

Peer Reviewer # 1

................................................................................................................. 83

Peer Reviewer # 2

................................................................................................................. 92

Peer Reviewer # 3

............................................................................................................... 108

Peer Reviewer # 4

............................................................................................................... 114

iExternal Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

A. INTRODUCTION

EPA, the National Highway Traffic Safety Administration (NHTSA), and the California Air Resources Board (CARB), in looking to reduce greenhouse gas emissions (GHG) and to improve fuel efficiency in medium

- (MD) and heavy -duty (HD) vehicles, are considering recognizing the efficiency of various powertrain technologies within the context of any new full vehicle emission standard(s). For this option, it becomes critical to develop methods that assess the expected real world performance of those technologies, including vehicle engine, transmission and axle technologies.

Enhancements have also been made to their HD vehicle simulation software tool, GEM (Greenhouse Gas Emission Model). At present, GEM is used by vehicle manufacturers to certify the expected GHG emissions of their products. With the enhancements, GEM could potentially have the ability to model a majority of the advanced technologies being incorporated into these vehicles and their engines and that are being recognized by engine and chassis dynamometer emission testing today.

EPA and the other agencies consider the GEM tool as a principal support for the second round of HD GHG emissions regulations which are under development at the present time in both NHTSA and EPA. The model has undergone a form al peer review in an earlier iteration of the GEM tool (Phase I) and this newest version of GEM (Phase II) is the subject of this peer review.

EPA is looking to assure the regulated community of the high quality of the agencies’ predictive tool and that the proposed structure (and overall development process) of the GEM model results in a tool that is simple, accurate and well -suited for the diversity of vehicles to which it may be applied. The purpose of the requested peer review is for EPA to receive wri tten comments from experts on the concepts and methodologies upon which GEM relies and whether or not the model can be expected to execute these algorithms correctly.

The purpose of the requested letter review is for EPA to receive written comments from individual experts on GEM Phase II tool and supporting documentation (“Vehicle Simulation Model”)

.

Versar selected four senior scientists with expertise/experience in the following areas to serve as peer reviewers . The reviewers are familiar with the use of models to characterize vehicle simulations/operations; specifically, model design and model code and logic. Additionally, reviewers have expertise in one or more of the following areas:

• vehicle operations and analysis, including the physical process o f generating and controlling vehicle emissions;

• linkages between mobile source emission modeling and transportation modeling and planning; and

• application of current mobile source emissions models, w.r.t., heavy-duty vehicles, for analysis for regulatory purposes and/or policy evaluation, e.g., HD GHG Notice of Proposed Rulemaking.

1External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Peer Reviewers :

Chris topher M. Atkinson

, Sc. D. Atkinson, LLC Morgantown, WV 26508

Nigel N. Clark, Ph.D. West Virginia University Morgantown, WV 26506-6203

Oscar F. Delgado- Neira , Ph.D. The International Council on Clean Transportation Washington, DC, 20005

Ashok Nedungadi, Ph.D., PE Future Is Now Consulting San Antonio, TX 78256

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B. C HARGE TO REVIEWERS

EPA developed a forward- looking MATLAB/Simulink -based tool, the Greenh ouse Gas Emissions Model or GEM, for Class 2b through Class 8 vehicle compliance in 2011. At present, this model is being used by all medium

- and heavy

- duty vehicle manufacturers for their vehicle certifications. In order to meet EPA’s upcoming Phase 2 GHG rulemaking requirements, recognizing most of the vehicle technologies that are measured by both engine and chassis dynamometer testing, the original GEM tool (version1) has been considerably enhanced.

Specifically, the following key technical features ha ve been implemented into GEM:

• Engine controller, including engine fuel cut-off algorithm during braking and deceleration, and more stable engine idle speed controller;

• Transmission model, which includes upgraded manual transmission, newly developed

automat ic transmission and automated manual transmission; and

• Upgraded driver model, with distance-based driver.

EPA has comprehensively validated its GEM model against over 130 vehicle variants, where all tests, including vehicle chassis and powertrain dynamometers, are conducted at Southwest Research Institute in San Antonio, TX. The summarized comparisons can be seen in the figure below. As can be seen, good agreements between simulation and testing data were obtained, with a few exceptions. For those outliers, it was found that the chassis roller may not be using friction force to correctly represent the truck running on the road, thus causing the chassis dynamometer testing to underestimate fuel consumption.

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It should be pointed out that CO2 reduct ion stringency standards in all certification categories are derived from GEM simulation runs by first selecting a range set of vehicle parameters and engine fuel maps. All to -be- certified vehicles from vehicle manufacturers use their own vehicle

parameter s together with some of the agencies pre-defined parameters to run GEM, and then their results are compared to what the agencies proposed. Since the comparisons are done in a relative base to see if the vehicles can meet standards, it is hoped that this kind of accuracy shown below would be adequate for use of certification purpose.

Please note that GEM includes a pull-down menu mechanism by which it is able to account for those technologies that GEM is unable to model at the present time in development (due to either time constraints or lack of experimental data needed to validate the model). Unlike a model/tool used for research and development simulations where the model can be continuously upgraded and developed, GEM as a compliance tool is constrained by legislative authorities which makes both upgrading the tool and delivering the updated version to users difficult.

Charge Questions

EPA’s vehicle simulation model, GEM, was created to serve as the primary tool to certify Class 7/8 combination tractors and trailers and Classes 2b – 8 vocational vehicles in meeting EPA’s and NHTSA’s proposed vehicle GHG emission levels and fuel efficiency requirements. As both agencies’ proposed compliance tool, GEM needed the following modeling attributes:

1) Models a wide array of MD and HD vehicles over various drive cycles; 2) Built with open source code (provides transparency in the model’s operation); 3) Available free to any user with minimal, or no, prior modeling experience; 4) Provides both optional and preset elements at input; and 5) Managed by both EPA and NHTSA for compliance purposes.

In general, the purpose of this peer review is fo r EPA to receive written comments on the concepts and methodologies upon which the model relies and whether or not the model can be expected to execute these algorithms correctly. In making comments on the model, please distinguish between recommendations for clearly defined improvements that can be readily made based on data or literature reasonably available and improvements that are more exploratory or dependent on information not readily available. Any comment(s) should be sufficiently clear and

detaile d to allow a thorough understanding by the Agencies or other parties familiar with the

model.

1. Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or issues that were not discussed or addressed by the GEM tool or its component sections?

2. Please comment on the appropriateness and completeness of the contents of the overal l model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following:

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a) Elements in each system used to describe different vehicle categories; b) Performance of each component model including the reviewer’s assessment of the underlying equations and/or physical principles coded into that component; c) Input and output structures and how they interact with the model to obtain the expected result, i.e., fuel consumption and CO 2 over the given driving cycles; and d) Default values used for the input file, as shown in “Vehicle Simulation Model”

document.

3. When using the standard of good engineering judgment, is the program execution optimized by the chosen methodologies?

4. Please comment on the clarity, completeness and accuracy of the intended output/results (CO 2 emissions or fuel efficiency output file).

5. In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? Any recommendations for specific improvements to the functioning of the outputs of the model?

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C. SUMMARY OF PEER REVIEWER COMMENTS BY QUESTION

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- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Summary of Peer Review Comments on EPA’s Heavy- Duty Greenhouse Gas Em ission Model (GEM): Phase II and Supporting Documentation

GENERAL IMPRESSIONS

Overall, the reviewers found EPA’s Heavy -Duty Greenhouse Gas Emission Model (GEM): Phase II and supporting documentation to be well structured, articulate, and a valuable resource for the EPA to represent the relative efficiency and emissions of heavy

- duty vehicles. Reviewers commented that the tool will be very useful for compliance purposes since it is a reasonable compromise between accounting for all technology differen ces and advances

, while remaining simple to execute. A number of improvements in the model and supporting documentation were suggested by the reviewers.

One reviewer commented that the overall dynamic performance of the model prediction is difficult to judge because the results present a single -valued, integrated snap-shot of the model prediction, and the time- based instantaneous fuel efficiency and carbon dioxide emissions predictions are not available for review.

Another reviewer commented that the material does not address quantitatively the experimental error that is likely in these types of comparisons, and measurement errors associated with rolling resistance and drag are not included in the data comparison. Overall agreement with experimental data (as vehicle fuel economy) does not validate each component model to the same degree, and this should be acknowledged more clearly.

Additional suggestions were on the supporting documentation. One reviewer noted that there is an overall lack of key detail on certain technical features , such as descriptions of features, how they were developed, and quantitative results in several areas.

CHARGE QUESTION 1

Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or issues that were n ot discussed or addressed by the GEM tool or its component sections?

In general, the reviewers found that the EPA’s overall approach to meet the agency’s compliance requirements is valid using the GEM Phase II model. The reviewers commented that a success ful approach must yield well-defined, unambiguous results for manufacturers and agencies and also incorporate real world driving dynamics. All of the reviewers acknowledged that the input functions of the model were substantially more beneficial than the original GEM Phase I model. For example, adding fuel maps to the simulation by adding actual maps and drivetrain parameters make s the results more realistic, allow s the model to capture the effects of matching engine and driveline, and ideally promotes righ t sizing of the engines to application.

One limitation a reviewer noted was that the model is oriented toward diesel engines. Naturally aspirated gasoline, boosted gasoline, and natural gas engines are likely to increase in the next

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five years and may wa rrant separate and careful consideration because their characteristics, torque curves, and efficiency maps differ substantially from the diesel engine properties.

A few reviewers noted some limitations to the model that were unaddressed by GEM Phase II model. For instance, it is possible for the vehicle not to meet the driving cycle as a result of excessive grade or weight or other issues with the transmission/engine – the unaddressed issue in this regard is a feedback alert to the user during the time in stances when the vehicle is significantly slowed down or does not meet the desired driving cycle. Another limitation is that GEM Phase II model does not address thermal characteristics of the engine cooling system or the heat rejection of the transmission fluids – these thermal issues affect the operational duty

- cycle of the engine fan, which will affect fuel economy.

One reviewer noted that in order for the public to have confidence in the regulatory program that is built on a mix of engine- and vehicle-model-specific inputs and modeled GEM outputs, the underlying data sh ould b e p re sen te d in ful l in do wnl oadab le da ta file s (e. g., in Exc el ) as in

other EP A r eg ul a tio ns.

Additional issues and limitations are addressed in the reviewers’ individual responses to the question.

CHARGE QUESTION 2

Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following:

a) Elements in each system used to describe different vehicle categories;

Overall, the model structure and its systems are appropriate and mostly complete for the designated purpose of the model. The specific selection of engines and transmissions chosen will

cover a large portion of the current heavy-duty vehicle fleet. The modular structure and the hierarchical arrangement of modules to mimic a real vehicle system makes the integration of additional modules and capabilities easier to implement. One reviewer commente d that GEM Phase II cannot predict the benefits of learning algorithms, look- ahead strategies, and intelligent vehicle systems for the optimization of powertrain efficiency on specific routes , but acknowledged that e merging approaches would take great effo rt to configure.

One reviewer provided detailed comments on specific issues regarding model structure, individual systems, and default values, including: fixed payloads, drop-down technologies driver subsystem, transmission subsystem, engine fueling maps, modeling of idle cycle, trailers, and

accessories.

b) Performance of each component model including the reviewer’s assessment of the underlying equations and/or physical principles coded into that component;

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T he reviewers generally found the underlying equations and/or physical principles to be sufficient to characterize real world driving situations

. For example, one reviewer commented

that the distance

- based approach was an important step to represent real life, but also commented

that accelerations and grade of cycles must also represent real life. Other suggestions for improvements were also made. A couple reviewers commented on the steady -state maps and on the transient adjustment factor (TAF). For example, one reviewer noted that the use of an eng ine model steady -state map with a generic TAF does not encourage manufacturers to improve transient fuel efficiency, and provided two possible solutions. Another reviewer commented that in the case of nominally steady operation, the use of a steady

- state f ueling map is well

- justified, but the quasi-steady assumption required to allow the extension of the use of such a map to transient operation requires additional justification. The reviewer also noted that the use of a single TAF for a specific engine or p owertrain configuration has the potential to cause prediction

inconsistencies. Comments were also made for other components, such as axle efficiency. One reviewer noted that it can be dangerous to employ the overall fuel economy computation to

compare two approaches to modeling a single component, particularly if that component represents a small loss.

c) Input and output structures and how they interact with the model to obtain the expected result, i.e., fuel consumption and CO2 over the given driving cycles ;

One reviewer commented that the format for the input and output structures follows good coding standards, making the input/output structures easy to use. One concern is whether there are any other parameters or fitting techniques used to obtain the obs erved correlations that were not

listed in the documentation. Another reviewer commented, as guidance, that the manufacturers will be obliged to use the executable version of GEM Phase II a large number of times to compute an average value for compliance.

d) Default values used for the input file, as shown in “Vehicle Simulation Model” document.

Generally, the default data of GEM Phase II is complete and appropriate to execute a simulation of heavy

- duty vehicle powertrain over one of the drive cycles available in the default drive cycle library. However, one reviewer thought it was not clear under what circumstances the user will be able or allowed to make modifications in the final model implementation. For instance, it is not clear that engine cooling fan loads have been adequately accounted for in the model as these are typically not considered in the engine dynamometer testing from which engine fueling maps are normally derived , and they can modify observed fueling rates by about 10% or more under specific engine operating conditions.

CHARGE QUESTION 3

When using the standard of good engineering judgment, is the program execution optimized by the chosen methodologies?

T he reviewers generally agreed that the chosen methods and execution of the model shows strong engineering judgment throughout. Two reviewers commented that it is difficult to comment on the execution optimization of GEM- II. However, one of these reviewers stated that

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the results , computational time, and outputs displayed indicate that the chosen methodologies are

suitable. The other reviewer stated that it appears that there are no S -functions within Simulink, which would make the execution faster if there are any non -standard user defined functions. Another reviewer commented that modeling accuracy would be raised if certain missing

components were considered, such as longitudinal slip of tires, rolling resistance during crosswind correction, and the effects of yaw on drag.

CHARGE QUESTION 4

Please comment on the clarity, completeness and accuracy of the intended output/results (CO2 emissions or fuel efficiency output file).

Some of the reviewers provided suggestions for making the data reports more complete. Some of these sug gestions included adding (or clearly identifying) results for each drive cycle, adding actual simulated speeds and a measure of deviation from the speed -distance, and summarizing the results of the energy audit

. One reviewer commented that users might be tempted to scale the

load -based results in an inappropriate fashion. Another reviewer commented that the results are sufficiently comprehensive for the user who is not executing the program in MATLAB for research and design purposes, and that for a manufacturer a very succinct output would be

sufficient.

CHARGE QUESTION 5

In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? Any recommendations for specific improvements to the functioning of the outputs of the model?

The reviewers provided a number of recommendations for improving the quality of the tool or functioning of the model output. One reviewer suggested that GEM provide two different output reports, including one in an aggregated format with information only relevant for compliance purposes and one in a disaggregated format by cycle with other detailed information. In addition, the output fields should provide a range of valid and acceptable values for parameters such as number of shifts, ratio of number of shifts to number of gears in the transmission, distance traveled, and ratio of actual time to target time. Another suggestion wa s to make consistent the number of significant digits during each simulation, as the current presentation ha s a varying number of significant digits which does not meet recommended practices in the presentation of

results and data. One reviewer also recommended adding language to remind users that if GEM is used to compare two competing but very different techno logy packages, it may not have the fidelity or granularity to evaluate which is better. Another recommendation was to provide a quantitative discussion of choice of test weight for GEM. A further step suggested by one reviewer would be to allow users to input their own cycles as is currently done with the VECTO (Vehicle Energy Consumption calculation Tool) model in Europe. A number of other potential model enhancements were recommended by another reviewer, such as including the ability to create input data from a user provided spreadsheet, allowing users to select plots of key component performance, having more detailed explanations of user provided data, providing feedback during execution (i.e. percent complete), having pre- defined sample input data

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availa ble, including the ability to turn on the feed forward term for the driver model, and having

the ability to model accessory power draw in certain cases.

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D. PEER REVIEWER COMMENTS BY CHARGE QUESTION

12External Peer Review of EPA’s Heavy

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Reviewer Name

Reviewer 1 Table 1. General Impressions

Reviewer Comment

The purpose of GEM in determining standards, providing a compliance tool, and estimating real- world benefits is clearly articulated. The proposed Phase II GEM tool has evolved substantially from the Phase I version, particularly by allowing additional user inputs that are necessary to acknowledge fuel efficiency design improvements. As a compliance tool GEM should seek to account for all technology advances and differences, yet remain simple to execute and employ readily

measured and well -defined input variables. The Phase II GEM model has reached a reasonable compromise between these conflicting goals, and this is made clear in the narrative. The overall architecture is sound, the present component models are appropriate to the task in nearly all cases, and they are clearly described. The model yields credible results and credible responses to input variable changes. The overall model predicts fuel efficiency to within 5% of experimental meas urements, and a clear summary of these comparisons is presented. However, the material does not address quantitatively the experimental error that is likely in these comparisons, and measurement errors associated with rolling resistance and drag are not in cluded in the data comparison. Overall agreement with experimental data (as vehicle fuel economy) does not validate each component model to the same degree, and this should be acknowledged more clearly. As one example, overall fuel economy data are used to compare a component model with a fixed efficiency value. The difference overall was only 1.67%, but this represented more than a third of the losses for that component. The move to a distance- based strategy is justified and well -described, and represents a laudable advance. Addition of several transmission models is presented, as are thoughts on the addition of transient adjustment factors. Little is said of the “powertrain variant architecture,” although this may EPA Response to Comment

Significant progress ha s been made since we

initiated the GEM Peer Review. The technical research workshop held at Southwest Research

Institute on December 10-11, 2014 features the progress done so far to the public. In this workshop, both experimental errors and GEM errors were addressed. The detailed progress reports can be seen at http://www.epa.gov/otaq/climate/regs

heavy

- duty.htm

. The supporting document , “Vehicle Simulation Model”, does provide partial validations on the component level, such as the engine and

transmission

, for selective cases. Due to the large number of vehicle tests and GEM

simulations on over 130 vehicle variants, it would be challenging to show every single case

validation at a component level. More importantly, the certification is only c onducted at the final integrated and weighted fuel efficiency and CO2 level, and therefore, the

focus of the model validations is on the overall performance comparisons. The supporting document, “Vehicle Simulation Model”, indicates that hybrid vehicles would not be part of the certification with GEM, and therefore, the powertrain described in this report only talks about the conventional

powertr ain system. We are seeking comment in the NPRM regarding the proposed transient correction

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Table 1. General Impressions

Reviewer Name Reviewer Comment EPA Response to Comment

prove important for integrated powertrains with or without a hybrid component. Transient Adjustment Factors are not yet finalized, and transient operation may warrant more than a single correction factor approach. factor of 1.05. We will finalize the transient correction factor after receiving all comments

from stakeholders.

Reviewer 2 This document summarizes the findings of the review of the US EPA's Heavy -Duty Greenhouse Gas Emission Model (Phase 2 GEM) and supporting documentati on ("Vehicle Simulation Model"). The tool will serve as the principal support for the second round of Heavy-Duty GHG emissions regulations, which are under development by NHTSA and EPA. The agencies are considering recognizing the efficiency of various vehicle, engine, and transmission technologies and they consider critical to develop methods that assess the expected real world performance of those technologies. The main purpose of this review is to evaluate how well the developed model can serve as a regu latory and compliance tool. The following represent my review of the tool and accompanying report based on my experience in modeling heavy -duty vehicles with full- vehicle simulation tools, as well as

from our assessment at the International Council on Clean Transportation (ICCT) of other heavy-duty vehicle regulatory

models used around the world.

After reviewing the Matlab/Simulink model and the accompanying report, my general impression is that the "Phase 2 GEM" constitutes a valuable development effort b y EPA to develop a rigorous tool that represents the relative efficiency and emissions of vehicles. The new modeling tools’ comprehensiveness, qualityand amount of data inputs, and modeling structure reflect state-ofthe- art modeling techniques and accurately represent relative efficiency differences of vehicles in real -world conditions. The literature on vehicle simulation modeling is

abundant over the last few decades . Some of

the literature used in the supporting documents provides some equations for certain

components.

The “Vehicle Simulation Model” document

was intended to represent a high level overview of the purpose and scope of Phase 2 GEM for regulatory purposes and therefore does not provide detailed technical insight into the model implementation. This document closely resembles the Draft RIA Chapter 4 in cluded with the Notice of Proposed Rulemaking (NPRM) for the HD Phase 2 program. Also the final RIA Chapter 4 will add a few more

reference s to provide more insight into the design and implementation of the model.

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Table 1. General Impressions

Reviewer Name Reviewer Comment EPA Response to Comment

The model architecture is clear and easy to follow and has incorporated some key features that will enhance its overall accuracy with respect to real world performance of technologies,

and will allow the model to capture fuel consumption reductions

from a broader range of technologies. Overall, the tool offers arigorous and comprehensive simulation accounting of both enginespecific and full

- vehicle effects in a manner th at is suitable for the regulatory compliance purposes as indicated. The model will be capable of performing its intended purpose of reflecting technology benefits for compliance purposes of most of the technologies that the agencies are considering.

Some new vehicle modeling features are especially important, namely the ability of the model to incorporate user- defined engine fueling maps and driveline parameters, the development ofdifferent transmission options, the enhanced transmission gearshifting strategy, the inclusion of a distance -based routes with road grade, and the more comprehensive treatment of vocational truck technologies. The accompanying testing effort that was u ndertaken to validate the model is impressive and thorough, as capturing the effect of combinations of technologies in such close agreement with powertrain and chassis dynamometer testing is a difficult task. The model development demonstrates a thorough development process, and also shows a strong commitment to transparently presenting the data and methodology that were

involved.

The comments below provide additional details, as well as some suggestions that could also be considered by the agencies in th e final model development.

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Table 1. General Impressions

Reviewer Name Reviewer Comment EPA Response to Comment

Although the tool itself offers a suitable modeling platform, the

document that describes modeling approach could provide further details in a number of areas. It appears as though the documentation available for this peer revie w was at an early draft stage. There is an overall lack of detail on key technical features that are new in the model. Interested readers would gain from better descriptions of such features, how they were developed, and perhaps, more quantitative results in several areas. Also, the quality of the report may be enhanced with more consistent use of terminology and a reduction in the number of self- references. Further details regarding areas where such documentation and enhanced information would be helpful a re described below.

Reviewer 3 The EPA Heavy

- Duty Greenhou se Gas Emission Model (GEM) Phase 2 documentation accurately represents the structure, format, logic and algorithmic description of the model as presented. Thesupporting documentation is for the most part, clear and selfexplanatory. The results produced by the GEM model appear to be sound, although each set of results is presented as integrated fuel efficiency and carbon dioxide emissions results. As such the results present a single

- valued, integrated snap -shot of the model prediction, and the time- based instantaneous fuel efficiency and carbon dioxide emissions predictions are not available for review. The overall dynamic performance of the model prediction is thus difficult to judge in the greater context of what is usually fully transient vehicle opera tion. Furthermore, in the version reviewed, the ability to vary input parameters and vehicle and drivetrain attributes is limited to modifying input files and not through a graphical user interface as described in the review instructions. We do agree that addition of a graphic user

interface (GUI) could help the reviewers to understand the code better. However, the agencies do not intend to develop a GUI for single GEM runs based on discussions with the regulated stakeholders

.

Instead of a GUI, the NPRM i ncludes a macro

enabled input file based on an Excel spreadsheet (in addition to a standalone executable) with some simple interactive features (highlighting of out of range variables, for example) and a single button to allow batch processing of GEM runs.

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Table 1. General Impressions

Reviewer Name Reviewer Comment EPA Response to Comment

Reviewer 4 Accuracy of information:

The document provided, “Vehicle Simulation Model” provides a good background on GEM- II, its differences from GEM -I, and the Phase I certification process. Section 1.2, “Model Code Description” describes the model components and subcomponents, in adequate detail for the user to understand the depth

and breadth of GEM- II. No underlying equations are provided.The section on Model validation is an important section for GEMII. The extent of the validation and the comparisons with dynamometer testing is impressive. This gives the reader additional confidence in the results produced by GEM- II. The validation process is well documented, concluding with the graph that summarizes all the 130 vehicle validations performed. The validation also includes graphs of component performance (engine speed, engine fuel rate, and transmission gear number) as a

function of time

The document does not explain the variable target.veh_style. The structure format used for the user input dat a is useful in collecting

all user -provided data.

A final conclusions section is missing in the document provided. ‘target_veh_style’ is an internal variable used to track the regulatory subcategory of the simulation run and is not part of the user

inter face.

A final conclusion section could be added into the document, but it is not a critical element,

since the documentation was included in the Draft RIA Chapter 4 and is more like a user guide to help the user to understand the structure of the program.

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Table 2 . Charge Question 1 Charge Question 1 : Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or issues that were not discussed or addressed by the GEM tool or its component sections?

Reviewer

Name Reviewer Comment EPA Response to Comment

Reviewer 1 Throughout this review, except where different fuels are mentioned, fuel efficiency improvement and GHG reduction are considered to be synonymous.

Beyond the need for assurance of compliance is the need to reduce fuel use and climate change emi ssions from heavy-duty vehicles in revenue use. A successful EPA approach must be examined from two perspectives. First, it is necessary that the approach yields

well -defined, unambiguous results to allow a manufacturer to compare against a standard without the process being unreasonably onerous. Second, it is necessary that that the vehicle attributes and behaviors embodied in the certification process are substantially representative of real world circumstances. These two necessities

are often in conflict , because the real world scenario is complex, variable, and long in duration, whereas the standard must be concise and precise. The conflict is far greater in the heavy duty trucking arena than for light- duty vehicles or rail because truck

architectures va ry widely, and are used in an even wider fashion.

Employing a model such as GEM to assure compliance provides

some relief in the conflict described above because the model can be executed for a variety of activities and scenarios without excessive cost of time and resources. However, as the model is challenged to predict these varied (and emerging) scenarios with fidelity, the model complexity rises. As a result, the empirical tables or computational sub

- models needed within the model grow The agencies discuss the proposed regulatory approach of separate engine and vehicle standards in the preamble to the HD Phase 2 NPRM and how it may impact the criteria pollutants. We wi ll consider the comments received during the comment period and make any needed changes in the final rule.

18External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 2 . Charge Question 1 Charge Question 1 : Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or issues that were not discussed or addressed by the GEM tool or its component sections?

Reviewer

Name Reviewer Comment EPA Response to Comment

in number and de mand substantial engineering time to prepare and verify. One might argue that “the more one models, the more one measures,” recognizing too that precise test protocols must accompany each measurement.

Compromise is necessary between four fundamental needs : 1. Relevance of the model to real world truck operation. Else the real world improvements will not match the changes in standards

2. Accuracy of the model in predicting measured fuel efficiency (and GHG production). Else confidence in the model will be lost and the compliance will become artificial

3. Accuracy of the model in predicting differential effects of technology changes on fuel efficiency (and GHG production). Else the drivers for technology advancement will be lost 4. Control complexity and cost of modeling and compliance. Else the cost transferred to the consumers will be inappropriate

The overall new GEM approach shows awareness of these necessities, and reaches a reasonable compromise. However, when some parameters are fixed by the agency, manufacturers may be discouraged from pursuing certain development opportunities in the following way. Both future fuel pricing and future fuel efficiency standards are unknown. If high fuel prices transcend the

19External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 2 . Charge Question 1 Charge Question 1 : Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or issues that were not discussed or addressed by the GEM tool or its component sections?

Reviewer

Name Reviewer Comment EPA Response to Comment

standards, then manufacturers will pursue every cost

- effec tive tool to reduce fuel use. However, if fuel prices are low and are not the driving force, and the GEM approach offers default values for factors such as engine transient adjustment factors or transmission efficiencies, some opportunities for real world reduction may be left on the table. GEM cannot rely on economic drivers to address technology advances that are not modeled.

GEM is a vehicle -based tool that is geared towards road-load demands rather than engine- specific (“%load” and “%speed”)

demands. Only the new distance -based cycles give a nod toward engine power. Criteria pollutants are still characterized using a paradigm based on engine rated output. Allowing different measurement methodologies for efficiency and criteria pollutant production will open a window for separate hardware and software optimization for each test. This may demean the benefits of the separate standards to some degree: in

- use compliance for criteria pollutant measurement will not close this gap because

measurement allowance for criteria pollutants reduces stringency for criteria pollutants.

Reviewer 2 The proposed Phase 2 standards are predicated on the performance of a broader range of technological improvements than Phase 1, including changes to transmissions and better integration of engines and transmissions, so a more comprehensive model is required. The model in its current form will be capable of performing its intended purpose of reflecting technology benefits for compliance purposes of most of the technologies that the In principal, we agree with the comments that the input and output data should be available to public. The agencies will

con sider in a separate action whether the GEM inputs and outputs submitted by manufacturer to demonstrate compliance

with the Phase 2 standards are confidential

20External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 2 . Charge Question 1 Charge Question 1 : Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or issues that were not discussed or addressed by the GEM tool or its component sections?

Reviewer

Name Reviewer Comment EPA Response to Comment

agencies are considering.

The model is enhanced in various aspects with respect to its previous Phase 1 version. Fuel maps are one of the most important

elements in simulation -based models and the new feature of using actual maps and drivetrain parameters would make the results mor e realistic, allow the model to capture the effects of matching engine and driveline, and ideally promote right sizing of the engines to application. Different transmission options are included in the model. The shifting behavior is now more realistic sinc e is based on both throttle and speed inputs, and includes the effects of a clutch friction model. Phase 1 GEM shifting strategy was based only on vehicle speed and there was no torque interruption during shifting. Road grade has a major impact on fuel consumption and its addition to the tests cycles would also make the results more

realistic. The treatment of vocational technologies, which were

limited to the tires in Phase 1, is considerably enhanced. The approach followed by EPA to tackle the diversity of vocational truck applications is appropriate. A few drive cycles are simulated (ARB transient, 55 mph and 65 mph cruise with grade, and a new idle cycle) and weighted differently based on specific application.

EPA’s approach involved a good amount of testing and validation. It must be said that most of these validation efforts only covered fuel consumption results from reduced weight, better aerodynamics, and better tires. The validation effort for transmission types and engine

- transmission

- vehicle in teraction business information (CBI). The agencies

cannot release information claimed as CBI by manufacturers to the public.

21External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 2 . Charge Question 1 Charge Question 1 : Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or issues that were not discussed or addressed by the GEM tool or its component sections?

Reviewer

Name Reviewer Comment EPA Response to Comment

was less comprehensive. However , based on the results presented,

Phase 2 GEM model would be accurate enough to support regulation and drive technology adoption.

More broadly, I make one final comment on how the overall modeling approach may meet EPA’s overall goals for the regulation, related to the public release of the GEM input and output data. The existing and Phase 2 heavy-duty vehicle regulation approach relies on the GEM inputs and outputs to

determine compliance. The GEM data are analogou s to the light

duty vehicle gram/mile 1 , heavy -duty vehicle gram/brakehorsepower 2 , and light- duty vehicle mile

- per

- gallon 3 compliance values. For the heavy -duty use of the GEM in the greenhouse gas emission regulatory program to meet the agency’s own standard, the input and output data from GEM would ideally be made publicly available just as the regulatory data for the other regulations for each engine and vehicle. For the public to have confidence in the regulatory program that is built on a mix of engin e- and vehicle

- model -specific inputs and modeled GEM outputs, the underlying data would b e p re sen te d in ful l in

do wnl oadab le da ta file s (e. g., in Exc el ) as in ot her EP A

r eg ul a tio ns.

References :

1 EPA http://www.epa.gov/otaq/crttst.htm

2 EPA http://www.epa.gov/otaq/certdata.htm

3 EPA http://www.epa.gov/otaq/tcldata.htm,

22External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 2 . Charge Question 1 Charge Question 1 : Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or issues that were not discussed or addressed by the GEM tool or its component sections?

Reviewer

Name Reviewer Comment EPA Response to Comment

http://www.fueleconomy.gov/feg/download.shtml

Reviewer 3 The model appears to meet the stated purpose for which it was intended, which is the prediction of integrated cycle- based vehicle fuel efficiency and carbon dioxide emissions for vehicles with preselected physical and drivetrain attributes. While this was the subject of some detailed explanation in the model documentation, the assumption of quasi- steady engine fueling and its extension to fully transient engine operation is not without complexity in the

assessment of it s validity. A further, acknowledged inadequacy of the model in its current form is the limited ability of the user to modify specific vehicle attributes, and component values and

efficiencies. The agencies agree with the comments, and we fully recognize th is limitation of the model in terms of the ability of the user to modify some

vehicle attributes . As explained in the supporting document “Vehicle Simulation Model” and Draft RIA Chapter 4 the

certification is conducted o n a relative bas is

, and the report shows relative errors in the range

of 2 -3%, which is not perfect, but it is adequate for the purpose of certification.

User inputs are limited to reduce complexity and to provide a more common basis for determining regulatory stringencies and to reduce the expense and number of test procedures required to provide accurate inputs

to the model. The agencies are seeking comment in the preamble of the HD Phase 2 NPRM regarding the inputs to GEM and the test procedures associated with them.

Reviewer 4 EPA’s overall approach to meet the agency’s compliance requirements consists of making a validated simulation model (GEM

– II) available to OEMs so that they can check the compliance of their vehicles against the agency’s guidelines. The

extensive validation of GEM

– II against dynamometer testing of the actual vehicle shows a good correlation between simulation and GEM PID controller s are not tunable modules, meaning that the user has no option to change any constants associated with this model. At this time, we have validated GEM against 130 vehicle variants without noticing any issues

23External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 2 . Charge Question 1 Charge Question 1 : Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or issues that were not discussed or addressed by the GEM tool or its component sections?

Reviewer

Name Reviewer Comment EPA Response to Comment

hardware to within ±5%. Most validations are well within ±3%. This provides the user with a high level of confidence that the physics has been correc tly implemented and there are no unresolved “bugs” in GEM- II.

Further, an additional level of confidence is achieved, with select validation from four representative vehicle classes, namely: Class 8 Kenworth T700 truck, the Class 6 Ford F650 tow truck, t he Class 6 box truck, and the New Flyer Refuse truck. There is a very good

correlation between GEM

- II predicted engine speeds and transmission gear shifting versus the same on the actual vehicle.

Recommendation: It is recommended that representative vehicles

from each of the classes be modeled in GEM -II and validation results presented similar to 1.3.1 of the GEM- II Manual. It is the understanding of the reviewer, based on the provided manual that the following trucks were tested on a vehicle chassis: Cla ss 6 Kenworth T270, Class 6 Ford F650, Class 8 Kenworth T700, Class 8 Cascadia Line Haul truck, and Class 8 New Flyer refuse truck.

Issues/Results that were not addressed by GEM

- II :

During this review, the following unaddressed issues were

identified for GEM- II:

• GEM

- II includes several PID controllers within its overall

structure. For example, the engine idle speed controller of associated with PID controller. It should also be noted that many of the PID controllers, like the engine idle speed control, are scaled by

non- user

- defined parameters like engine inertia

or vehicle mass to match their application.

The planned interface which manufacturers will use to certify via GEM does not provide the option to output plots. The functionality is not considered necessary to complete the compliance requirements identified in the rule.

Thermal modeli ng is always an issue. Ideally, it should be included in some form. However, it is challenging to develop a correlation to qualitatively predict the thermal impact associated with cooling and transmission heat rejection in terms of a certification tool. This development can be expensive and time consuming. This could place an additional

burden on manufacture r s who must submit certifiable report s to the agencies, which complicates the process of the certification.

M echanical load s can be also modeled through a simple correlation. However, simi lar to the thermal modeling issue, this could place an

24External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 2 . Charge Question 1 Charge Question 1 : Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or issues that were not discussed or addressed by the GEM tool or its component sections?

Reviewer

Name Reviewer Comment EPA Response to Comment

the engine is implemented as a PID with three gains. T he unaddressed issue in this regard is stability feedback to the user caused by unrealistic hunting for the idle speed. What

safe -guards are in place within GEM to inform the user of clutch chattering since GEM does not model second order inertial effects caused during clutch engagement.

• It is possible for the vehicle not to meet the driving cycle as a result of excessive grade or weight or other issues with the transmission/engine. The unaddressed issue in this regard is a feedback alert to the user during the time instances when the vehicle is significantly slowed down and does not meet the desired driving cycle. The output file

does not alert the user on the number of time instances when vehicle tracking was compromised.

• GEM

- II does not address thermal ch aracteristics of the engine cooling system or the heat rejection of the

transmission fluids. These thermal issues affect the operational duty- cycle of the engine fan, which will affect the fuel economy. At present, GEM

- II models the parasitic loads as a constant average number.

Recommendation: Allow the user the ability to introduce an engine load dependent mechanical accessory curve which is more realistic than a constant average number. A simple heat model may be used to capture the effect of thermal

cha racteristics of the multiple radiators in a typical MD and HD engine.

• Although GEM

- II does not model tire slip/lockup during a additional burden on manufacturers who must submit certifiable reports to the agencies, which complicates the process of the certification

The supporting document, “Vehicle Simulation Model”, does show some detailed comparisons in a sub-model level, such as engine and transmission. It is extremely time consuming

to show all 130 vehicle variants at such a detailed level. Furthermore, certification only requires composite and weighted values, and

there fore, the program should serve th is requirement as long as those composite and weighted values are correlated well against the testing data.

In terms of transmission shifting, all independent transmission manufacturer s we contacted are reluctant to share their shifting strategies with the vehicle manufacturers due to

concerns over proprietary information. Therefore, the agencies developed their own generic shifting algorithm for modeling purposes. If GEM under-predicts the benefits of the transmission, manufacturers have the option to conduct powertrain testing where an engine and transmission are evaluated in a

25External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 2 . Charge Question 1 Charge Question 1 : Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or issues that were not discussed or addressed by the GEM tool or its component sections?

Reviewer

Name Reviewer Comment EPA Response to Comment

hard deceleration, the effect of ignoring this on fuel economy is negligible.

• The validation results included kinematic comparisons (speeds, gear number) between GEM- II and the actual vehicle on a chassis dynamometer. While, the kinematic comparisons look very favorable, the dynamic comparisons (engine load and engine fueling) are missing in the results

section of GEM- II.

• The transmission shift strategy can affect fuel economy and

emissions. GEM

- II allows the user to preselect different transmission types (manual, automatic or automated

manual). However, it was not clear how to modify the

GEM

- II default shift strategy with an OEM pro prietary shift strategy.

• Although GEM- II results have been extensively validated against dynamometer test data in a controlled lab environment, it is unclear how well GEM- II will compare against real world road testing, especially with temperature

fluctuat ions. For example, the lack of a thermal model in the engine model may cause GEM

- II results to deviate from

on-the- road test data, where the engine fan is cycled on and off based on thermal loads on the engine. Each time, the engine fan turns on, fuel econ omy is affected. powertrain dyno cell.

The agencies full y recognize the importance of the GEM validation against real

- world v ehicle operations. However, it is expensive and time consuming to launch such a program. Currently, the agencies are work ing with SwRI to conduct this task in the hope that full GEM validation against real -world vehicle operations can be released to p ublic in the second half of

2015.

26External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: a) Elements in each system used to describe different vehicle categories;

Reviewer

Name Reviewer Comment EPA Response to Comment

Reviewer 1 The proposed GEM Phase II model represents a substantial advance over the model used to implement the first phase of truck efficiency legislation, and encourages more technology advances from manufacturers in consequence. Improvements in truck efficiency are based primarily on reductions in aerodynamic drag, tire rolling resistance and engine brake specific fuel consumption, and this was recognized in the first GEM model. Practically, there is less to be gained from aerodynamic improvements in most vocational truck operation than in long haul trucking and the GEM model as presented neglects vocational truck aerodynamics, and the modelers are right to exclude aerodynamic parameter entries for low speed trucks. However, the overall GEM structure is capable of modeling aerodynamic improvement s for niche vocational designs, and has the flexibility to extend beyond the present exclusion of the drag coefficient. In this way, the capabilities of the model, as received, will be far greater than the executable version that is finally used for compli ance.

A major theme in the industry is that efficiency gains are significant from design integration, particularly powertrain integration. But it is understood that combined powertrain control is proprietary. The supporting language might address this more clearly, noting that the GEM model employs just steady

- state maps and a defined set of gear ratios, and cannot predict the benefits of more sophisticated integration. In a The comments on gasoline and natural gas engines are well taken. The agencies are currently conducting a program at SwRI to address gasoline engine performance related to the rulemaking. We are also actively collecting the engine performance

data on both types of engines from manufacturers.

The GEM Phase 2 shift algorithm is based on the torque curve and fuel map of the engine and such will adapt shift points uniquely for every engine map provided, regardless of fuel type. Manufacturers will have the option to perform powertrain testing to account for improvements, such as those mentioned by the reviewer.

The agencies are seeking comment on whether to include GEM inputs for vocational vehicle aerodynamics i n the preamble to the HD Phase 2

NPRM.

27External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following:
similar fashion GEM cannot predict the benefits of learning algorithms, look- ahead strategies and intelligent vehicle systems for the optimization of powertrain efficiency on specific routes. These are emerging approaches, but it is acknowledged that it would take great effort to configure GEM

to deal with these details and it would be difficult to assure their generic benefit in revenue service. GEM has some check

a-box options proposed for features that cannot be modeled.

The model, as provided, was oriented to diesel engines. The shift strategies also considered the engine torque cur ve for execution. Naturally aspirated gasoline, boosted gasoline and natural gas engines are likely players in the next five years and may warrant separate and careful consideration because their characteristics, torque curves and efficiency maps differ

su bstantially from the diesel engine properties.

Reviewer 2 Overall the model structure and its systems are appropriate and,

in large part, complete. Generally, the performance of each component model and the underlying equations and physical principles are valid throughout (see some finer details below). The input and output structures interact with the model to obtain the expected result in a way that is sound. The following sub-sections comment on specific issues regarding model structure, individual systems, as well as default values, in no particular order of importance.

Fixed payloads Phase 1 GEM had predefined engines, driveline parameters, and payloads for every category. An issue that may arise when Fixed Payload

The agencies are fully aware of the technical issues related to payload. However, allowing payload as a variable means that agencies must develop a

standard that varies with payload, which would complicate the rulemaking, specifically the process of certification. Furthermore, it would be challengi ng to verify the in -use payload of a vehicle application, making audit challenging

. In addition, this approach would force tractors running without trailer, or bobtail, to be considered

28External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: using user

- defined engine fueling maps in combination wit h predefined payloads is that some simulated vehicles, with lower

power- to

- weight ratios, will show higher deviations from the target speed

- distance trace. This affects the simulation results since these underpowered vehicles will take more time to complete the assigned route and will show a lower average speed. This could lead to underpowered vehicles being improperly credited.

Appropriate matching of engine, transmission gear ratios, axle ratios, and tire radius is only going to be promoted if the GEM payloads closely match actual vehicle operation. Right sizing of powertrains to application does not seem to be promoted when

pay loads are predefined for a particular vehicle category. In order to recognize engine power matching to vehicle road load, payload needs to be a user input rather than a predefined parameter. The regulatory approach and modeling would ideally recognize and promote market diversity and identify potential discrepancies between actual payloads and GEM payloads. There is an existing trend towards smaller engines, but also some applications require larger engines. On the otherhand, if the truck manufacturer is allowed to input vehiclespecific payloads, some issues may arise in terms of enforceability (How do the regulatory agencies ensure that the vehicles are operated close to the payload values at which they were certified?), that may also open the door for th e manufacturers to report numbers for their own benefit, and adds complexity. out of compliance because they are not carrying the declared payload. Therefore, the agencies simplify the process by proposing fix ed payload values.

Pull-Down Technologies

Pull-down technologies are also known as the

techn ology improvement inputs for the rulemaking. The supporting document, “Vehicle Simulation Model” and the HD Phase 2 NPRM preamble describe many aspects of the pull-down technologies. We also seek comment on whether the technology improvement inputs should be in terms of percent reduction or absolute grams of

CO 2 per ton- mile. Basically, t he agencie s have been actively talking to all relevant manufacturers regarding these technologies as selectable items.

We proposed a conservative approach recognizing these potential technologies. All the technologies considered as pull-downs would be those that G EM would not be able to model or are not fully recognized over the limited certification drive cycles . Technologies mentioned by this reviewer, such as electric coolant pump s would only show a partial benefit in the engine fuel mapping process,

and therefo re the pull-down item associated with it

accounts for the other remainder of the benefit seen

on the road.

29External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: An option could be to adjust the payload on a few pre

- defined bins based on certain parameters that are indicative of vehicle

road load (e.g. engine displacement, engine power, final drive ratio). Under this option, a performance criterion that captures

the trace

- following capabilities of the simulated truck (e.g. a set
threshold of percent difference between target speed and simulated speed) can be used to force certain engine -v ehicle combinations to switch to a lower payload bin if they don’t follow the trace according to the specified criterion. Another option would be to impose a CO2 penalty based on the ratio of simulated average speed to target average speed. Ideally, the allowed deviations from the target trace should be minimized

for the simulations to be considered valid and allow comparisons between them.

Drop -down technologies The agencies have identified a list of technologies that provide fuel consumption benefits b ut are difficult to simulate accurately. They are developing feature -based drop-down menus that make post- simulation adjustments (percent reductions) to the results. It appears that manufacturers have not taken much advantage of the Phase 1 advanced techno logy structure to earn credits so it is important to try to include most of the technologies in some way. However, drop-down menus inherently assume that all the technology variants within a technology category provide the same fuel consumption

benefits. Not all the models and brands of a certain technology feature would provide the same fuel consumption benefits. There is the risk of giving artificial credits to products that Although these values used by GEM are fixed as default values, the user does have the option to use

off

- cycle credit proposed by the rule, similar t o the innovative credits in Phase 1, to quantify the additional benefits of individual technology.

Dr iver Subsystem

All the driver model related constants are not tunable. We tested these pre

- selected PI controller related constants against over 130 v ehicle variants without any noticeable issues. In addition, the driver controller constants are scaled by vehicle mass and therefore adjust automatically for each

simulation run.

Transmission

The auto

- shifting tables for all three types of

transmissions are different in the form of internal

constants which are not user-tunable . The supporting document, “V ehicle Simulation Model”, and HD Phase 2 NPRM Draft RIA Chapter 4 includes a table to show the impacts of

the shift algorithm on overall vehicle performance as opposed to using manufacturer -supplied shift

table s

. We agree with th e reviewer that we need to

p rovide a clearer description of this subject and it will be clarified in Draft RIA Chapter 4

.

30External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: perform at a lower level than the value that is selected from the drop- down menu, thus rewarding poor performers. Also, technology products with better than average levels of performance would not get additional credits, which is a disincentive to make investments in the development of such technologies. The default improvement values (percent reductions) developed by the agencies were not shared for this peer review but they are of relevance and need to be determined with care. Currently, the users have no flexibility to enter their own values. Giving the users the flexibility to ente r their own values (after testing and with proper documentation) could offer a way to reward good performers.

It seems that applying adjustment factors in terms of percent reductions rather than applying predefined credits in units of go2/ton- mile or gal /ton- mile may punish good performers. Assuming that truck A emits 90 go2/ton- mile and truck B emits 100 gCO2/ton- mile. If a certain technology improvement value is set at 5%, and both trucks use such technology, truck A would get 4.5 gCO2/ton- mile credit an d truck B would get 5 gCO2/ton- mile credit. This discrepancy of incentives can

exacerbate if the trucks use more than one drop

- down technology and the agencies decide that the percent improvements are additive. So it would be good for the agencies to suppo rt whether and why percentage -based (versus gCO2/ton- mile based) are most appropriate. Also the agencies might address, in such drop-down menus whether such technology improvements are indeed additive or not. Another issue with drop

- down technologies is that there is the We fully agree with the reviewer’s comments on the powertr ain test. As a matter of fact, the powertrain test is one of the options that

manufacturers can use to address benefits GEM is

unable to fully capture

.

Engine Fuel maps

The proposed engine fuel mapping procedure is

detailed in the proposed regulations in 40 CFR part

1036. It is always challenging to use a steady state map approach to account for transient operation. While there are many ways that the vehicle model can be improved for those behaviors, there are always

trade -o ff s in terms of computational speed and accuracy. Furthermore, including more advanced models, such as model based control could substantially improve accuracy, but the collection of test data plus calibration of the model against the data would be beyon d the agencies ’ capabilities, and could be expensive, time consuming and error -prone. This kind of advanced modeling could take much longer to run as opposed to the proposed executable version of GEM, which only takes a few seconds to complete

one certification vehicle. It is very typical for a

vehicle manufacturer to run thousand s of

31External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: potential for double counting of technology benefits

. As an example, an electric coolant pump is listed as a drop -down technology. Depending on the engine mapping process, the resultant engine fuel map may already capture the benefits from that technology. Running a simulation with such a map, and later improving the results using a drop- down menu will double count the benefits. If EPA could respond to how potential double-counting situations are minimal, that would be helpful. simulation s for certification. It is not practical to introduce such complicated modeling processes to perform ce rtification at this time.

We propose a single transient factor in the HD Phase 2 NPRM, as the reviewer recommended. We are also seeking comment on the transient

correction factor.

Driver subsystem In vehicle simulation modeling, it would seem that the driver ideally would be excluded entirely as a factor that could influence the GEM regulatory compliance results. Using the

same driver model for all the vehicles seems to be an appropriate choice. However , additional documentation is needed for this subsystem. There are no details about how the proportional and integral gains of the PI controller have been selected. Are they representative of current drivers? Are they

tuned to enhance the trace- following capabilities of the model?

The look- ahead feature also lacks documentation. Is it bringing any advantage to the trace- following capabilities of the model? How was the time span value for such feature selected? Ideally EPA would provide some consideration and discussion of such factors to provide greater assurance that no anomalies occur in compliance results from company

- to -company technology strategies as well as tested -versus- real

- world results for t he relative technology benefits.

Transmission subsystem Modeling of idle cycle

The HD Phase 2 NPRM described in Chapter 2 of

t he Draft RIA and Preamble Section V provides more detailed description on modeling of the idle cycle.

Regarding "trace following ” and the idle calculation, f or tractor

- trailers the idle weight is

zero a nd the simulation grams/mile are multiplied by target mph and also divided by target mph so what remains is simulation grams/mile which will reflect the modeled performance (or under

- performance) of the

vehicle.

For vocational vehicles the same is true with regards to the simulation grams/mile over th e drive cycles. Idle consumption takes places at zero speed and is measured in grams/hour so there is a

32External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following:

There are some transmission

- related features that are confusing and need to be clarified. The report mentions that the different transmission models: manual (MT), automated manual (AMT), and torque converter automatic (AT) are built of similar components, but each features a unique control algorithm.
However, the model seems to use the same "auto shift algorithm" to determine the operating gear for any transmission type. The differences in the control algorithm of the three different transmissions are not clear and need to be provided. Since transmissions are an important new addition for Phase 2 GEM, it is important to let the reader know that the control strategy (e.g. shift points) or the selection of predefined transmission parameters (e.g. efficiencies and inertias at
different gears) are not creating any artificial advantage of one technology type over the others. I suggest presenting a comparison of the same simulated truck with different transmission types. It is also important to highlight in the report that the new transmission controller is based on both speed and throttle position, and differs from the Phase 1 transmission controller, which was solely based on vehicle speed. The rule-based approach of the "auto shift algorithm" would ideally be documented.

It would be appropriate for the agencies to acknowledge that

Phase 2 GEM simulations can capture some but not all of the

benefits of powertrain integration. The simulation would adequately capture engine down speeding since the users have to input specific transmission gear ratios, final drive ratio, and tire radius. However, there are many complexities in the control conversion factor required to obtain grams/mile. The target weighted average speed represents that

conversion factor and does not alter the modeled

ve hicle performance (or under

- performance) over the drive cycles.

Trailer

The HD Phase 2 NPRM described in Chapter 2 of

the Draft RIA and Preamble Section VI provides more detailed description on how trailers are

handled. Tractor manufacturers determine t he coefficient of drag area for a tractor

- trailer

combination. The trailer used in this

determination is a “reference trailer” that is specified in the regulations (40 CFR part 1037). Details of the test procedures for the tractors

are included in the HD Phase 2 NPRM Section III.

Accessories

The agencies chose the same approach as Phase 1 to model accessories, mainly because it is not an easy task to model accessory improvements, which requires time consuming and expensive testing and validation of the model. Allowing user input of accessory loads would require each user to know ahead of time the expected load for each vehicle in use and while potentially providing more accurate

33External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: strategy when it comes to integrating engine and transmission.

Inte grated engine -transmission powertrain approaches with advanced controls and shifting algorithms that many companies are developing could result in significantly more (or less) benefit than the agencies determine as the appropriate default

emission

- reduction effect.

As an example, if two different vehicles have the same driveline parameters (tire radius, final drive ratio, transmission gear ratios, transmission inertias, and transmission efficiencies) and AMT transmissions from different manufacturers, they will obtain the same simulation results in GEM but, due to differing control strategies and other design characteristics, they will

show different fuel consumption benefits in reality. It cannot be expected that all the AMT transmissions bring the same fu el consumption benefits. The drop-down menu option won't

handle these differences unless there is an option to choose

manufacturer -specific transmissions or otherwise input such

data.

As a result, there is an opportunity here to leverage the powertrain testing and provide the option for manufacturers to better capture the fuel efficiency gains coming from the control strategies and other complexities that are not adequately captured in GEM. Another advantage of powertrain testing is

that the manufacturer s would not need to disclose confidential information. The results from powertrain testing can then be implemented as correction factors for the GEM results. Using correction factors, GEM results could be multiplied by a fixed results would place an unreasonable burden on the

user and manufacture rs. If the accessory is normally part of the engine, the engine mapping

conducted on the dynamometer should be able to

account for some of those losses, thus being modeled through the engine fuel map. If accessory improvement comes from the vehicle, and GEM is

unable to model it

, manufacturers can either use pull-down technology or use innovative credit to recognize these accessories

.

34External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: percent improvement obtained by comparing the results ofpowertrain test and GEM simulations under the same torquespeed trace. 4 The default benefits for transmission improvements would ideally be set to be appropriately conservative (i.e., lowest expected value based on various

indus try results) in GEM. The drop-down menu could still then

be offered as a default, for the manufacturers that decide not to use the powertrain testing. Then, for the powertrain option, companies would ideally be provided clear testing procedures and guidanc e to demonstrate the emission -reduction impact of their advanced powertrain approaches with physical vehicle testing in simulated real -world conditions.

Engine fueling maps

The inclusion of manufacturer- specific engine maps is a critical feature to reflect company differences and detailed engine

specific characteristics that reflect real -world fuel consumption and emissions. This is an important addition to GEM, but there is lack of documentation of the engine mapping procedure. I imagine that a fairly pre scriptive procedure (including number of points, preconditioning and warming procedures, fuel properties, etc.) is described somewhere else in the larger regulatory development document but this chapter would ideally include a brief description of the procedure so the reader knows which engine accessories are included or excluded during the engine mapping procedure.

It is noted that there are many advanced features that may affect fueling but are not captured by using a steady

- state fuel

35External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following:

map. Manufacturers are going away from traditional map

- based strategies and are going towards model-based controls. Diverse thermal management strategies are utilized, and some engines use dual torque curves. Have the agencies considered how to handle these technologies? This could have important implications for how tested steady

- state engine maps, and GEM modeling, and real- world emissions characteristics could differ. As a result, we recommend that the agencies discuss such industry approaches in the rulemaking and inves tigate ways to ensure that tested results are aligned with real

- world engine and vehicle operation the results in fuel consumption and

emissions.

The approach used to quantify the transient correction factor (run GEM with the engine map, then use the torq ue

- speed points in the engine dynamometer and compare measured versus simulated results) is appropriate. Ideally the transient correction factor may be obtained for each individual engine. However, since there is a need for selection of a vehicle in

GEM in order to get the torque- speed trace. It would become a hard task for the agencies to try and run a transient correction

factor for each vehicle

- engine configuration. For practicality, I recommend provisionally using a single correction factor and

maintain ing the option to refine it over the years with additional testing.

Modeling of idle cycle The idle cycle modeling would gain from increased documentation. Using a gCO2/mile value for an idle cycle at

36External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: first seems counterintuitive (i.e., there are no miles traveled) so a complete description of the calculation method would clarify. It would be desirable to present some validation results for the idle cycle modeled in GEM compared to experimental results. Some of the engine auxiliaries may not be enabled whi le doing the test, and the map could be underestimating actual idle speed fueling rates. There are also engine thermal management strategies that are used to keep appropriate after treatment system temperatures. These strategies vary from manufacturer

to m anufacturer and could increase idle fueling substantially.

The "trace following" issue discussed above also has implications in the calculation of idle cycle g/mile value. For this calculation the fuel rate in units of grams per hour [g/h] is

converted to units of grams per mile [g/mile] using the weighted average speed over the three non- idle cycles. The target speed is used for this calculation and not the actual simulated speed, which may penalize smaller engines. I suggest

EPA to consider if this issue might be significant.

Trailers Although there is a parameter in GEM for trailer tires' rolling resistance, it is not clear how trailer aerodynamics is going to be modeled in GEM. Trailer aerodynamics can bring about

two -thirds of tractor- trailer aerodyna mic benefits, so this is a critical area that requires documentation and specification of the procedures for the vetting, binning, and including the input data. My understanding is that the Coda input parameter is for the tractor only (mid

- roof and low roo f tractors are tested in its

37External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: bobtail configuration), or for the tractor using a "reference" 53

­ ft dry van trailer (for high

- roof tractors coast -down test). Trailer aerodynamic devices can reduce the overall tractor

trailer combination aerodynamic drag and ideally the Coda

used in simulation should represent the combination. It seems that there is no current provision to include the effect of trailer aerodynamics as an input in GEM. The report needs to clarify how the GEM model is handling trailer parameters (including aerodynamics, tires rolling resistance, and weight reduction) and if the model is going to use a predefined "reference" trailer for all the tractors. Ideally agencies would give credit to tractor

trailer integrated designs although it would be difficult for the agencies to ensure in -use compliance of matching of tractors

and trailers.

Accessories There are opportunities for fuel savings from mechanical accessories and electric accessories but the agencies decided to keep with the Phase 1 approach of having pre-defined and not customizable power from accessories. If these parameters are assigned default values, there are no incentives to implement new technologies that could have greater impact. Allowing

accessories power consumption to be user-d efined inputs can

be used to promote developments in technologies that reduce the power requirements of accessories such as the alternator,

air -conditioning compressor, power steering pump, or cooling fan. There are other opportunities for engine accessori es such as oil, coolant, and fuel pumps, but is not clear at this point if all those savings are going to be captured by the engine

38External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: mapping process.

References:

4 Se e Sha r pe
, De lgado, M unc ri ef ( 2015 ) Co m pa ra ti ve

assess m en t of heav y- du ty veh icle r egu lator y des ign op ti on s for U.S. gr eenhou se gas an d e ffi ci enc y regula ti on

. h tt p :// www .t he i cc t. org/ us

- phase2

- hdv - regula ti on

- des ignop ti on s Reviewer 3 The elements in each of the systems (engine, transmission, axle, vehicle attributes etc.) seem appropriate and complete. The specific selection of the engines and transmissions chosen will cover a large portion of the current heavy- duty vehicle fleet, although of course any specific, single selection of powertrain hardware or powertrain hardware attributes

necessa rily limits the range of vehicles that can be simulated

with that same selection. Non

- conventional or alternative powertrains can be certified through powertrain testing.

Reviewer 4 The three main powertrain components that can affect fuel economy and greenhouse gas emissions in a vehicle are: engine fuel map, transmission type and efficiency map, and vehicle aerodynamic improvements (including tire rolling friction improvements and weight reduction technologies). In this regard, GEM

- II addresses all th e aforementioned components by providing steady state maps for each powertrain component, which an informed user can change to represent spe cific technology improvements. GEM

- II comes with certain standard transmission models, namely: manual, automatic, an d

automated manual transmissions. The user would select the appropriate transmission and GEM- II would automatically

select the user

- specified transmission. The proposed Phase 2 version of GEM for certification is an executable version code, which does not require Matlab/Simulink license. In additional, a plain text format ted file will be used

for user inputs. There is no need for user to understand the coding structure of GEM in a

Matlab/Simulink format. Neither manufacturers nor users will be able to modify the structure of GEM in any way. The Phase 2 GEM User Guide, provided with the NPRM, will provide details on

how to use GEM.

A technology improvement such as a proprietary

39External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following:

Recommendation: It is recommended that additional instructions are provided if the user wants to ch ange the engine

map. Ideally, this would be done from a user specified spreadsheet in a GEM

- II compatible format, since the user may not be fluent in Matlab. In this regard, a clear explanation of all the variables used in GEM-II would also help significan tly. For example, it was not clear how to change the transmission shift schedule if an OEM chose to do so. Further, since GEM- II is modular with hierarchical layout of component layers, it is challenging for an OEM user to insert a technology improvement deep within one layer and not affect the layers

above or the execution of GEM- II. It is not clear, from this initial review, how a technology improvement such as a proprietary transmission shift schedule can be evaluated in terms of gains in fuel economy an d greenhouse gases. This comment applies to other technology improvements as well, such as partial engine cylinder deactivation (power on demand)

or electrification of certain mechanical accessories.

The vehicle categories that GEM

- II addresses range fro m Class 2B to Class 8 HD conventional vehicle powertrains. This is achieved by four root- level systems in GEM

- II at the root level, namely: the ambient, driver, vehicle, and powertrain modules.

Each of the aforementioned modules consists of several submod ules organized in a hierarchical manner. Each root

- level module outputs a data bus that is mixed into a single data bus. The aforementioned four main systems of GEM-II correspond to the four main components of a HD vehicle, namely: driver, transmission shift schedule would not be considered under the current GEM. Rather, the agencies encourage the user to use the powertrain option described in Chapter 3 of the HD Phase 2

NPRM RIA to address any benefits associated with the transmission and its integration with the engine

that GEM is unable to model.

40External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following:

ambient conditio ns, vehicle chassis and powertrain modules.

This one- to

- one correspondence between the root

- level GEM

- II models and an actual HD vehicle makes for an easily understandable structure. Further, the modular organization of

the GEM

- II contributes to easier deb ugging and isolation of a numerical problem during simulation.

The powertrain module is the most populated module in GEMII. It contains the engine, transmission and driveline submodules and accessories (mechanical and electrical). The flow

of data information corresponds to an actual vehicle powertrain, with the engine output driving the transmission, which in turn drives the driveline components.

The modular layout of GEM-II, its correspondence with a real conventional vehicle is therefore approp riate and complete for

the reasons stated above. The modular structure and the hierarchical arrangement of modules to mimic a real vehicle system makes the integration of additional modules and capabilities easier to implement. The signals are clearly marked and follow a logical naming convention that facilitates the addition of additional modules and capabilities into GEM

- II. b) Performance of each component model including the reviewer’s assessment of the underlying equations and/or physical principles coded into that component;

Reviewer 1 MATLAB/Simulink remains an excellent basis for the GEM model. It is well suited for the exploratory and development framework, as well as the production of a more limited

executable model. The agencies use their own auto

- shift algorithm for all transmissions for many reasons as described by the supporting document – “ Vehicle Simulation Model”. We recognize that this is not an ideal modeling approach, but we do offer the powertrain

41External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: GEM may be viewed on three levels. At the highest level, the MATLAB/Simulink platform allows GEM to be anything it chooses, with the addition or alteration of modules and component models. At the secon d level, there is the model provided for review, which has the innate ability to deal with a wide range of cycles and truck configurations. At the lowest level will be the final executable version, where certain parameters are fixed, and where the duty cycles are chosen for determination of compliance. Only the second and lowest

levels can be considered in this review.

This GEM model is being produced at a time where engine control strategy development and integrated powertrain controls are advancing rapid ly. Also, transmission options are now far wider than in the earlier GEM model, where unsynchronized manual, synchronized manual and traditional automatic transmissions dominated the marketplace. GEM is challenged in modeling and giving credit for the tech nology subtleties that will emerge in the marketplace over the next five

years. The use of distance, rather than time, as a basis for the test cycles represents a great and important advance. It was widely recognized two decades ago that light duty automo biles were capable of far more aggressive performance than was embodied in the FTP-75, although the FTP-75 was used as the norm, and

still embodied allowances for vehicles that could not follow its modest accelerations. In the heavy -duty arena sustained us e of full engine power both on grades and during acceleration is the norm. All else being equal, a more powerful truck will testing approach that allows manufacturers to quantify the be nefits associated with their own more advanced shifting technologies and integration benefits with the engine.

We are fully aware of the limitations of the steady state engine fuel map s that are proposed for GEM.

We proposed the concept of the transient correction

factor for the transient cycle to minimize the deficiency of the steady state map. We are also

aware that this transient correction factor is derived from the diesel engine test, where gasoline and natural gas engines may behave differently. We are currently asking for comments on this approach. We will make refinement s in our final rulemaking, as needed based on the comments we

receive . In addition, manufacturers have the option to conduct powertrain testing to demonstrate their engine’s transient performance.

At this time, we are proposing a single value for axle mechanical efficiency, and ask for comments of whether we should use a look-up table to model axle efficiency based on axle efficiency test results

. The agencies will make appropriate adjustments in

the final rule based on the comments received

.

It is not straight forward to model tire rolling resistance as function of speed without

42External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: complete its duties in less time than an underpowered vehicle, and often the more powerful choice represents the overall economic optimum. However, the more powerful truck will spend less time at full power, and will enjoy a reduced average

“%load” in revenue service. The adoption of the distance- based approach is an important step toward matching the GEM model

to real -would use. Howev er, as standards are finalized, the accelerations and grades of cycles embodied in the GEM execution must represent real life as well. If the grades and acceleration values are not appropriately challenging, the

distance -based approach will look more like a time

- based approach, because underpowered trucks will be able to follow

the trace in the minimum time allowed. This would divorce the

market incentives from the environmental incentives and create a false impression of fuel efficiency capability at the e xpense of economic reality. It is important that the grades and test weights used are realistic and representative. Further, the indication of the ratio (actual / minimum time for cycle completion) is a very beneficial output value.

A driver’s habits are known to have a measurable impact on truck fuel efficiency. This is in part due to gear selection that influences the engine operating envelope, and in part due to transient pedal demand (driver PI controller), that may cause an engine to depart from stead y- state mode to a greater or lesser degree. The GEM load demand controller and GEM gear selection algorithms can be configured to reflect different driving habits. If the chosen GEM driver yields a better fuel efficiency than would be expected of the natio nal average comprehensive tire data. Besides, just like the comments made by this reviewer, deta iled tire data of this kind are not in the public domain and test methods are not universally defined. It is challenging for the agencies to develop a more

advanced tire model at this time.

The agencies present details of the proposed road grade cycles in the HD Phase 2 NPRM preamble and welcome comment on the representativeness of these and other road grade profiles developed. The agencies will reflect the final road grade profiles in

the final version of the HD Phase 2 GEM.

43External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: driver, then GEM will fail to grant auto

- shifting technology and certain engine control strategies their full potential contribution to efficiency gain. It is recommended that this issue is at least explored to provide driver sensitivity results to the accompanying document.

The engine model in the new GEM is still a steady

- state map. The documentation acknowledges that transient fuel efficiency will differ from steady

- state efficiency at the same speed and load in time. A transient adjustment factor (TAF) seems likely for the final version, but the use of a steady- state map with a TAF does not encourage manufacturers to improve transient fuel efficiency if a generic TAF is assigned. This reviewer appreciates that manufacturers are unwilling to reveal strategies that represent a substantial fraction of product value, yet they cannot take advantage of their improvements in the model without this information. Two solutions are possible:

(i) Determine a manufacturer

- specific TAF rather than an

agency -s pecified TAF, or (ii) Determine an alternate fuel efficiency map for transient (e.g. Heavy -Duty FTP) operation, and use that map or both steady state and transient maps for the transient cycle.

In addition, TAF will need to be considered carefully for gasolin e and natural gas engines, where enrichment management has an important effect on fuel efficiency. In a similar way, cylinder deactivation strategies may be difficult to

44External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: characterize for throttled engines, because the deactivation strategy is not well repr esented by a steady

- state map. It is important to have a TAF strategy that acknowledges successes of manufacturers in lowering transient operation disadvantages.

The EPA developers have sought comment on the issue of axle efficiency. It can be dangerous t o employ the overall fuel economy computation to compare two approaches to modeling a single component, particularly if that component represents a small loss. In one case, the overall fuel economy differed by 1.67% when a simplified efficiency was compare d with a lookup table for rear axle efficiency. This 1.67% represented more than a third of the loss associated with that component. To place this in further perspective, the 1.67% can be compared to the 3-5% contributions of a major component, such as sid e skirts on a semi- trailer at freeway speeds. Generically, if a component model with higher fidelity is available, in the opinion of this reviewer, it is worth including the detail in GEM, even if the component model is fixed in GEM. Furthermore, the exist ence of such a model may provide a

clearer pathway for entering technology advances by a manufacturer who improves that component in the future.

The tires in GEM are simply characterized by a rolling

resistance coefficient and an effective loaded radius. It is known that the coefficient varies with vehicle speed and contact area, while longitudinal slip can change the revolutions per mile by a few percent under driving torque and braking, which could bias results more substantially when grade is

45External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: present. T his could be coded into GEM, but it is probably more appropriate to treat it as a comment, since detailed tire data of this kind are not in the public domain and test methods are not universally defined.

Reviewer 2 See response f or part A.

Reviewer 3 One concern with the structure and form of the model is that a steady

- state engine fueling map is used in each case to simulate transient engine operation and hence dynamic vehicle operation. This is in addition to the simulation o f operation under nominally steady vehicle speeds or cruise operation. In the case of nominally steady operation, the use of a steady

- state fueling map is well -justified, but the quasi- steady assumption required to allow the extension of the use of such a map to transient operation requires additional justification. Heavy duty compression ignition engines have high rotational inertias (due to the relatively high mass components required to survive the high combustion pressures), high mechanical friction (du e to high effective compression ratios) and relatively slow air and exhaust transfer processes (due to the excess air flow rates accompanying their lean, un -throttled operation). In addition they have relatively high thermal mass due to their large physica l mass required to withstand the stresses and strains resulting from high combustion pressures. All of these features conspire to result in deleterious combustion effects under highly transient engine operation. In most cases the end effect of these phenom ena is to reduce the engine brake thermal efficiency under transient modes, beyond that which would be expected under steady or quasi-steady fueling operation. In most cases the additional fuel that is required to undertake a We are fully aware of the limitations of the steady state engine fuel maps that are used for GEM. We introduce the concept of the transient correction factor for the transient cycle to minimize the deficiency of the steady state map. We are also

aware that this transient correction factor is derived from the diesel engine test, w here gasoline and natural gas engines may behave differently. We are currently asking for comments on this approach. We will make refinements in our final rulemaking.

46External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: specific engine transient torq ue trajectory, beyond that estimated using a quasi -steady fueling assumption, would typically be less than 10% of the total integrated fueling, but in most cases the effect on integrated fuel efficiency over transient duty cycles is non-negligible.

In general, incorporating an additional component into the full accounting of the vehicle load by over- accounting for the actual total rotational inertia (in the form of an effective or “added” mass or inertia) of the drivetrain and driveline system does

allo w for the quasi-steady assumption to hold. However in general a quasi

- steady, forward -looking simulation such as is used in this model, tends to under- predict the actual vehicle energy usage under transient duty cycle operation. I notice that

this issue is addressed in Chapter 1.4.1.8 Transient Adjustment Factor, but the designation of a single correction factor for a specific engine or powertrain configuration is likely to be unsuitable in some cases, and has the potential to cause prediction inconsistencies. Note further that the required correction factor might not be uniquely engine- specific, but might vary for the same engine in different vehicle and powertrain configurations.

Reviewer 4 GEM

- II follows the model of a single wheel with a

concentrated mass at the center of the wheel. The physics

coded into the modules are based on Newton’s second law of motion for this concentrated mass. At the time of this review, no other dynamic equations were found in GEM- II, except in the clutch and torque converter. The e ngine, accessory, transmission and driveline components are characterized by The model physics are Newt onian, as noted, and follow textbook equations for Newton’s laws and conservation of energy.

47External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: steady state maps. The equivalent mass of rotating inertia components are also correctly included in the vehicle module

of GEM

- II. Rotating inertias are correctly reflected

downst ream to the tire. The inertia is converted to a virtual

mass which is added to the entire vehicle mass. The wide

validation of GEM- II against real vehicle data indicates that the physics has been correctly implemented in GEM

- II. c) Input and output structures and how they interact with the model to obtain the expected result, i.e., fuel consumption and CO2 over the given driving cycles;

Reviewer 1 The accompanying explanatory document emphasizes that the input and output structure has not been finalized. A comment, intended as guidance, is that manufacturers will be obliged to use the executable version of GEM a large number of times to cover each order or each truck technology change over the year. This is needed to compute an average value for compliance. The EPA should make every effort to insure that

the final version can be interfaced with the manufacturers’

software to insure that t he process is efficient and reasonably inexpensive, while keeping that version of the model locked to insure compliance.

The .csv output files, viewed in Excel, provide a representation of likely input and output files. These summaries are very

useful and appropriate. The agencies are talking to various manufacturers to make sure that our input and output structure can be integrated with their software. The HD Phase 2 NPRM preamble seeks comments from stakeholders on suggestions to minimize the compliance burden associated with GEM.

Reviewer 2 See response for part A.

Reviewer 3 A further concern that is not discussed in the documentation is whether any model fitting parameters were employed to obtain the fits observed, between the GEM- derived fuel efficiency and CO2 emissions values and the dynamometer

- measured results. Some model constants were adjusted to match the individual vehicles, however all simulations for a particular vehicle are run with the same configuration.

48External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: In other words, beyond the parameters described and the accompanying constants used in the dynamic force and energy equations, were any other fitting techniques (or fitting parameters) u sed to obtain the observed correlations between the simulated cycle

- averaged results and the SwRI chassis dynamometer results? Presumably there were dynamometer parameters and coefficients fitted using vehicle coast -down data (and dynamometer operational p arameters), but beyond these, are there any other fitting parameters used to obtain the correlations shown? Discrepancies between simulated and

measured results of less than 2 -3% are probably not significant, except in the presence of a consistent bias between the measured and predicted, for any one vehicle, cycle or technology considered. E xamples of adjusted model constants are

transmission shift delay s, rpm limits , up and down shifting constraints, first gear skip, etc. However once these model constants are tuned, they are not adjusted for individual drive cycles or tests. In other words, vehicle-specific constants are set up to

match the behavior of the vehicle but are not tuned

for individual results . Input values directly from experiment, such as coast down data related to aero drag coefficient and tire rolling resistance

coefficients are taken as inputs and not further adjusted.

Reviewer 4 Input for GEM

- II: A structure format is used to store the inputs to create the input

data for the execution of GEM- II. The structure format is organized as follows: component.variable.units. For example, the input variable “engine.idle_fuel_map_speed_radps” identifies the engine speed vector of the engine idle fuel map expressed in rad per sec. Similarly, the input variable “transmission.clutch.input_inertia_kgm2 refers to the clutch

inertia of the transmi ssion, expressed in kgm2. This format follows good coding standards, making the inputs easy to pair to the appropriate component it refers to, the particular variable name, and the units used. Further, a modular approach is used to store the input data for each component in separate easily identified files in the “param_files” folder. Although this reviewer makes excellent comments

on the model data structure s based on Matlab/Simulink, the actual code used f or certification is only an executable version of the

code , meaning that it will not require a

Matlab/Simulink license and the user would not touch the source code, and therefore, the se comments are not relevant to the certification tool.

49External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following:

Output for GEM- II: When the workspace has been populated with the input data,
the simulation model “REVS_VM ” vehicle model is executed

over the user- selected drive cycle. Ea ch major component model (GEM_CVM, vehicle, driver, ambient) has a bus_out output port which contains a structure of component output data, which is used within other components. In addition,

GEM -II uses a datalog structure to store simulation output data for later post processing to calculate emissions and fuel

economy. All the simulation output is stored in a single datalog structure with multiple fields, each describing the component that the data pertains to. For example, datalog.vehicle.speed_mps refer s to data log from the vehicle component of the variable vehicle speed in m/s. This format is an accepted coding standard within other vehicle simulation packages (such as PSAT from ANL, RAPTOR from SwRI) as well, making the output easy to pair to the appr opriate component it refers to, the particular variable name, and the

units used. Similarly, all variables that are used to perform an energy balance are prefixed by “audit”.

Interaction with the model to obtain the expected results: The bus_out structure from the various components are stored in “goto” blocks which are paired with “from” blocks to distribute data from one block to another. The use of paired “goto” and “from” blocks is an accepted method of decluttering the simulation model and avoiding c risscrossing signal lines, thereby significantly facilitating the understanding of

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Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: information flow from one component to another. d) Default values used for the input file, as shown in “Vehicle Simulation Model” document.

Reviewer 1 The default values are not particularly important at this stage of development. They are sufficiently representative of recent or current technology to provide reasonable inputs and to assess the ability to predict real -world values. However, this is an appropriate point to acknowledge and discuss the comparison of GEM output with real-world measurements, as described in the supporting material.

The real -world d ata serve to verify the ability of GEM to model a variety of trucks. These data do not extend to the validation of truck tire rolling resistance or aerodynamic drag value selections because the validation was conducted using roller and powertrain dynamomet ers, where these values were entered and were the same values used in GEM. Generally GEM matched the measured fuel efficiency values to within 5%, and the deviation may be attributed both to measurement error and to the inherent simplifications in modeling . There are some systematic errors evident in the comparison. For example, the T700 truck efficiency is underpredicted (GEM vs. measured) on the high speed tests and overpredicted on the low speed tests. This trend differed for the T270 and F650 trucks.

Th e refuse truck fuel efficiency was uniformly overpredicted. This leads to the conclusion that GEM may be capable of predicting overall fuel efficiency accurately (at the 5% difference level), but that one should still be cautious of comparing the performan ce of very different technologies using

the GEM tool. The agencies agree with this reviewer ’s comments.

I t is a daunting task to verify every GEM sub

model, which would require significant investment

to collect data and then validate each sub -model. Just as this reviewer pointed out, the single overall predicted efficiency is of interest to the manufacturer because it predicates compliance

. GEM works reasonably well to predict this single value, namely, fuel economy over 130 vehicle

variants. The agencies have ma d e significant improvemen ts

on the driving cycle. The a ddition of road grade to

55 and 65 mp h cruise cycle s is just one example. The agencies are seeking comment on the proposed drive cycles and road grades in the HD Phase 2

NPRM

. We will refine GEM as necessary based on the comments for the final rulemaking.

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Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following:

The narrative states that “While it is encouraging that GEM accurately simulates overall vehicle performance in an absolute sense, it is actually more important that GEM is accurate in relative compari sons.” This is true in the sense that GEM should encourage the best technology pathways through comparison, but it is nevertheless the single overall predicted efficiency that is of interest to the manufacturer because it predicates compliance. As an example, when the axle ratios were adjusted for a vocational truck from the chosen value of 3.76 to high (4.06) and low (3.46) values, the predicted transient fuel economy values were 5.55, 5.49 and 5.6 respectively. In contrast to this small variation, the fue l economy values for the 65mph operation were 7.14, 6.88 and 7.37 respectively, attributable to the 9% difference in engine speed between the high and low ratios. This reviewer has confidence in these relative values where a variable input is changed. Howe ver, a comparison between two vehicles with identical chassis and bodies, but with different engines, transmission types and tire rolling resistance challenges several parts of GEM in a differential sense, and a greater comparative error must be anticipate d. One cannot argue that the overall agreement with the measured data verifies each sub -model

within GEM.

The use of single variables to represent a more complex reality

is discussed elsewhere in this review.

The cycles chosen for evaluating vehicle perf ormance can be

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Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: changed readily in GEM. Although incorporation of grades represents a substantial advance, the current choice of fixed 55mph and 65mph steady speeds may cause designers to “teach to the test.” [The CBD cycle, used in a previous age to quanti fy transit bus performance, suffered from problems of this kind because all steady state operation was at 20mph.] The output data for the tractor (through engine speed / vehicle speed ratio) show that the highest gear was used for both fixed speeds. Use of a test cycle where speeds varied slowly through the 50 to 70 mph range could avoid pitting real world optima against model optima, and would encourage engine downspeeding strategies that are successful in revenue service where speed limits are

not necessa rily 55 and 65mph.

Reviewer 2 See response for part A.

Reviewer 3 The default values as defined in the “Vehicle Simulation Model” are reasonable and currently fall within the ranges of expected vehicle values. It is not clear however under what

circumstances the user will be able or allowed to make modifications in the final model implementation. For instance, it is conceivable that the interplay between future auxiliary mechanical or electrical loads on an engine might be significantly modified through conversion of mechanical auxiliaries to electrical or electronic devices. In that case, that

will shift the relative balance in those loads. Moreover it is not clear that engine cooling fan loads have been adequately accounted for in the model, as these are typically not considered in the engine dynamometer testing from which engine fueling maps are normally derived. This exclusion alone can modify observed fueling rates by 10% or more under The example mentioned by this reviewer o f the

coolant fan is an example of a technology that

GEM can not directly model at this time due to lack of data and the extra burden of testing that would be required to calibrate such a model . In general, GEM will recognize all technologies that can be

measured during d yna mometer cell testing through the engine fuel mapping procedure. Those that cannot be measured or cannot be modeled through

GEM will be accounted for in different ways through (1) the pull-down technologies item or technical improvement input values (2) Powertrain test options (3) Innovative credit

53External Peer Review of EPA’s Heavy

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Table 3 . Charge Question 2 Charge Question 2 : Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following: specific engine operating conditions.

Other default values including transmission gear ratios, transmission efficiencies, axle effici encies, tire rolling resistance, and vehicle aerodynamic drag product seem

reasonable.

Reviewer 4 The default data used in GEM

- II is complete and appropriate to execute a simulation of HD vehicle powertrain over one of the drive cycles available in the GEM

- II default drive cycle library.

The default ambient conditions summarized in ambient_param.m are appropriate. The default driver parameters, summarized in driver_param.m, contain driver gains as well as the time that the driver can look ahead in the drive cycle. The driver gains represen t an average driver, which the user can change to emulate an aggressive driving pattern

versus a calmer driver.

The default engine maps of 270 kW, 345 kW, and 455 kW power ratings includes inertia, idle speed. Default transmission maps for the manual, au tomatic, auto

- manual are also available. Default tire radius, axle ratios, rolling resistance of the tires of the steering axles and drive axles are also included. The certification tool is an executable version , and

the user will not be able to access the source code

for certification

. Therefore, the user will not have flexibility to change model constants, such as driver gain.

Table 4 . Charge Question 3 Charge Question 3 : When using the standard of good engineering judgment, is the program execution optimized by the chosen methodologies?

Reviewer

Name Reviewer Comment EPA Response to Comment

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Table 4 . Charge Question 3 Charge Question 3 : When using the standard of good engineering judgment, is the program execution optimized by the chosen methodologies?

Reviewer

Name Reviewer Comment EPA Response to Comment

Reviewer 1 The GEM tool as presented to the reviewers provided a workable compromise between accuracy and simplicity. It is evident that GEM may be improved in accuracy by increasing input data, in particular the substitution of data tables for single values. However, these tables would need to be created for each component at substantial expense. Also, it would be better to use real values or tables or strategie s from manufacturers, but each of these might require audit and prescribed measurement methods, and in many cases the manufacturer considers them to be proprietary. The present GEM is close to being optimized: clearly development is still taking place.

As a general observation, the engine and transmission receive

substantial attention in GEM and in much work on truck efficiency improvement. They seem to be of interest at the single percentage level. However, tire rolling resistance is a major influence for vocational trucks, and drag coefficient controls the dominant loss for freeway tractors. Yet these two components are each represented by a single parameter. Beyond just GEM, a more detailed consideration of these components (e.g. longitudinal slip of tires, rolling resistance during crosswind correction, effects of yaw on drag) would assist in raising modeling accuracy. If that cannot be considered expediently for this version of GEM, it should be considered in the future, or even embedded in the tables s o that it can be applied without altering the code. We fully agree with this reviewer ’s comments. The

current version of GEM is a balance of model fidelity and simplicity. The agencies could develop

more advanced features , but at high er cost of development and long er duration, which would not be able to meet the timeline of this rulemaking. In the future, many advanced technical features including the tire model mentioned here could be

considered.

The agencies are proposing to account for the effects of yaw on drag in Phase 2 in the CdA input to GEM. The HD Phase 2 NPRM preamble Section III describes the test procedures to determine the wind average yaw coefficient of drag value and we seek comment on the proposed approach.

Reviewer 2 The chosen methods and execution of the model shows strong engineering judgment throughout. A good indication of proper We apprecia te the comments made by this reviewer.

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Table 4 . Charge Question 3 Charge Question 3 : When using the standard of good engineering judgment, is the program execution optimized by the chosen methodologies?

Reviewer

Name Reviewer Comment EPA Response to Comment

execution is the overall good agreement between the Phase 2 GEM simulations and testing data obtained with chassis and power train dyn amometers. The errors shown are well within +/­ 5%, which is within the test- to

- test variability of chassis dynamometer testing. Execution at this level of fidelity meets

our own criteria that we have utilized to validate tractor

- trailer

simulation results. 5 the validation results show that the balance between model accuracy and simplicity is adequate. As a result, the program would be effective to model a diverse set of technology changes and be used in regulatory applications.

References:

5 See Delgado an d Lutsey (2015). Advanced tractor- trailer efficiency technology potential in the 2020-2030 timeframe http://www.theicct.org/us

- tractor

- trailer

- efficiency

- technology

Reviewer 3 This issue is difficult to address through the level of observation afforded to the reviewer at this stage of development of the model. It is not obvious that the program execution is optimized, but the results, computational time and outputs displayed indicate that the chosen methodologies are suitable for this

purpose. We appreciate the comments made by this reviewer.

Reviewer 4 Overall, GEM

- II uses industry accepted coding practices throughout the software modules. The following is a partial list of these accepted practices:

• Valid variable naming structure used

–

• Data bus used for each component –

• Modular components with no signals crossing –

• Useful comments to assist the user with following the The comments made by this review are well taken in terms of improvement of the Matlab/Simulink

version of the source code. We s hould point out that

the certification tool is an executable version of GEM, and the user would not be allowed to use the

Matlab/Simulink version of the source code to perform certification.

56External Peer Review of EPA’s Heavy

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Table 4 . Charge Question 3 Charge Question 3 : When using the standard of good engineering judgment, is the program execution optimized by the chosen methodologies?

Reviewer

Name Reviewer Comment EPA Response to Comment

code

–

• Energy audit adds to the confidence level of the results

of the simulation.

• File name that is executed is echoed back to the user. If there is a simulation abort, the debug is easier

• Data that is being loaded is echoed back to the user so

the user knows what data is being used.

• Component modules are linked to libraries. A change in the library module propagates to all vehicle models during execution.

At this point in the review, I do not have adequate data to comment on the execution optimization of GEM

- II. Linear interpolation modules from the standard Simulink library are used within GEM-II, thereby optimizing execution. If there are any non-standard user defined functions used within the GEM- II simulation model, the execution can be made conside rably faster through the use of s- functions within Simulink. At the time of this review, no S

- function were found in the model.

Table 5 . Charge Question 4 Charge Question 4 : Please comment on the clarity, completeness and accuracy of the intended output/results (CO2 emissions or fuel efficiency output file).

Reviewer

Name Reviewer Comment EPA Response to Comment

Reviewer 1 The .csv output results are sufficiently comprehensive for the user who is not executing the program in MATLAB for research Yes, a succinct report with .csv format will be used

as output.

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Table 5 . Charge Question 4 Charge Question 4 : Please comment on the clarity, completeness and accuracy of the intended output/results (CO2 emissions or fuel efficiency output file).

Reviewer

Name Reviewer Comment EPA Response to Comment

and design purposes. Presumably a report similar to the .csv is anticipated as the executable version output. In fact, to the manufacturer, who is executing this at time of sale within a larg er accounting loop, a very succinct output would be

sufficient.

Reviewer 2 The data reports did not appear to be fully complete, but the accuracy of the output/results appears to meet reasonable expectations. The input and output structure of GEM was not finalized when released for peer review, however some samples of the output files were provided to give the reviewer a flavor of the potential structure. In my opinion, for completeness, the output file needs to include results for each different cycle and not only for the weighted aggregation of cycles. Some metrics can be added to the output file to facilitate troubleshooting and give the user a better perspective. As mentioned before, actua l simulated speeds and a measure of deviation from the speed

distance trace would ideally also be provided for transparency of the results. Based on the validation results, accuracy with respect to measured data was provided and seems to be within 5%,

whic h is acceptable output accuracy based on comparable modeling as well as real

- world testing. Phase 2 GEM will use the same output information to report certification as Phase 1 GEM, meaning that output file would only include the weighted aggregation of cyc les for the sake of certification. However, the user does have the option to access

the source code to find out more for those intermediate results, although the results from

source code would not be allowed for certification.

Reviewer 3 The model output s and results seem clear, complete and accurate. One caveat with interpreting or using the freight efficiency or load efficiency -based results lies in the use, further interpretation or extension of these results. Users might be tempted to “scale” the load -based results in an inappropriate fashion – for example, if the returned result for the computed carbon dioxide emissions is 100 gCO2ptm (grams CO2 per ton

For certification, GEM use s default payloads for

each regulatory subcategory, meaning that the user would not have option to make any change on the payload, thus avoiding the issue mentioned by this

reviewer.

58External Peer Review of EPA’s Heavy

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Table 5 . Charge Question 4 Charge Question 4 : Please comment on the clarity, completeness and accuracy of the intended output/results (CO2 emissions or fuel efficiency output file).

Reviewer

Name Reviewer Comment EPA Response to Comment

mile) for say a 30 ton vehicle over a specific cycle, there might be the temptation on the part of users to employ that same numerical result to predict the CO2 emissions for the same vehicle loaded to 40 tons over the same cycle. However this assumption is not correct, as the vehicle fuel consumption is a function not just of load or weight- related ter ms (rolling resistance, grade, acceleration etc.) but also terms that are invariant with load or weight (such as aerodynamic drag), and this is not reflected in an emissions per ton

- mile result.

Reviewer 4 The output data from a simulation execution is summarized in a spreadsheet, which is da te and time stamped, allowing the user to verify that the output data corresponds to the simulation executed. The output data contains data on which technology improvement (weight reduction, vehicle speed limiter, single drive axle, par time single drive a xle, low friction axle lubrication, predictive cruise control, high efficiency AC compressor, electrified engine cooling pump, extended engine idle reduction, automatic tire inflation ) was assessed, engine, transmission type, fuel economy and CO2 emissions.

The output data, summarized above, serves the original purpose

of GEM -II, which is to enable users to demonstrate compliance with regulatory standards either without any modifications to the HD vehicle, or analyze the fuel economy and CO2 emissions, when one or more technology improvements are employed. However, information on the drive cycle is missing or not clearly

identified. In addition, key plots of vehicle tracking the drive cycle, engine operating speed

- torque points over the drive cycle

, GEM is a certification tool, and as such produce s simplified result s, which can not only be easily connected to the agencies’ certifica tion tool box for compliance , but also can be directl y linked to the

manufacturer ’s information technology system. For more comprehensive outputs and plots, the user has the option to use the Matlab/Simulink version of the source code to provide a better understand ing of the

results. GEM as a certification tool is not meant to be used as a development aid. Again, the results

from source code would not be allowed for

certification.

59External Peer Review of EPA’s Heavy

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Table 5 . Charge Question 4 Charge Question 4 : Please comment on the clarity, completeness and accuracy of the intended output/results (CO2 emissions or fuel efficiency output file).

Reviewer

Name Reviewer Comment EPA Response to Comment

engine efficiency contour plots, transmission operating points, and other plots that assist OEMS to further fine tune the powertrain and improve fuel economy/ CO2 emissions in case of

non- compliance. It would be desirable to have the results of the

energ y audit summarized in the output file. The date stamp column is appropriate for the user to cross check simulation runs.

Table 6 . Charge Question 5 Charge Question 5 : In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? Any recommendations for specific improvements to the functioning of the outputs of the model?

Reviewer

Name Reviewer Comment EPA Response to Comment

Reviewer 1 Wor ds of caution may help in presenting GEM to the user and to the public. It is important to state that GEM has acceptable accuracy in predicting the fuel efficiency of a specific vehicle under specific circumstances. However, it is equally important to

stat e that if GEM is used to compare two competing, but very different, technology packages, it may not have the fidelity or granularity to evaluate which is better. GEM may not determine the relative difference between the two with high fidelity, and

that rel ative difference will depend on the vehicle vocation or test cycle used. Although modeling test weights were provided for the example vehicles, there was no quantitative discussion of choice of test weight for GEM. Test weights receive only brief mention i n the supporting documentation. It is possible that within vehicle classes, or across regions with different topography, engine size Test weight is set to a default value for each regulatory subcategory, which means that the user would not have option to make changes. This is necessary, because allowance of different t e st weight s per vehicle can result in numerous standards for the same class vehicle, which would be challenging for the purpose of compliance. The agencies provide details reg arding the proposed payloads and test weights in Chapter 3 of the HD Phase 2 Draft RIA and seek comments regarding the weights in the preamble.

60External Peer Review of EPA’s Heavy

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Table 6 . Charge Question 5 Charge Question 5 : In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? Any recommendations for specific improvements to the functioning of the outputs of the model?

Reviewer

Name Reviewer Comment EPA Response to Comment

may be selected based on the anticipated load. The distance based strategy shows an appreciation for this issue, but some compensation with test weight for engine size could be considered. Perhaps test weights could be selected so that the time to complete the route remains within reasonable bounds for more lightly powered vehicles, but at least that highly powered

vehicles ar e acknowledged to be appropriate for some occupations, loads or regions. The vocational tractor option in Phase I is not a comprehensive solution.

Reviewer 2 Phase 2 GEM could generate two different output reports. One that only includes the most relevant information on an aggregated format and is used only for compliance purposes, and a second one, that is very detailed and includes results disaggregated by cycle and other relevant information that may help the users to troubleshoot their results, learn the inner workings of the model and potentially suggests enhancements to it. I suggest including a summary of the energy audit in the output. Also, provide the average engine efficiency over the cycle for the different test cycles, as well as the ratio of average engine efficiency to maximum engine efficiency, which is an indication of how well the transmission parameters are matched to keep the engine operating near its peak efficiency range.

The output file provides some basic “sanity checks” such as number of shifts, ratio of number of shifts to number of gears in the transmission, distance traveled, and ratio of actual time to target time. Please also provide ranges of valid or acceptable values for these parameters so the user can be aware of any GEM is a certification tool, and as such produces simplified results, which can not only be easily connected to the agencies’ certification tool box for compliance, but also can be directly linked to the manufacturer information technology system. For more comprehensive outputs and plots, the user has the option to use the Matlab/Simulink version of th e source code to provide a better understanding of the

results. GEM as a certification tool is not meant to be used as a development aid. Again, the results

from source code would not be allowed for

certification.

61External Peer Review of EPA’s Heavy

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Table 6 . Charge Question 5 Charge Question 5 : In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? Any recommendations for specific improvements to the functioning of the outputs of the model?

Reviewer

Name Reviewer Comment EPA Response to Comment

potenti al issues with the simulation.

A further step that could allow the tool to be much more useful would be to allow users to input their own cycles as is currently

done with VECTO 6 (Vehicle Energy Consumption calculation Tool) model in Europe. The VECTO tool has a “declaration mode” for compliance, and an “engineering mode” which offers the ability to edit inputs and allow users to explore what the tool can do. This would be critical for transparency and follow the best practice as seen in the Europe situatio n. It would also be highly useful for individuals in the heavy-duty vehicle supplychain to explore the variation of the results with respect to realworld duty cycle factors. Especially considering the very diverse use of heavy -duty vehicles in local, reg ional, and long

- distance conditions, this capability would allow dealers and fleet managers to gauge how fuel consumptions for particular relevant driving patterns differs from the cycle. This would help ensure the technologies that are more suited to particular duty cycles are being selected in the market place, and it would also help overcome the prevailing market barrier, whereby knowledge, data, and confidence on truck efficiency has been limited. 7

References:

6 See Luz et al (2014) http://ec.europa.eu/clima/policies/transport/vehicles/heavy/docs/f inal_report_co2_hdv_en.pdf

7 Se e Roe th et al ( 2015 ) h tt p :// www .t he i cc t. org/ hdv -t echno l ogy

m a rk e t

- ba rri e r s

- no rt h

- a m e ri c a

62External Peer Review of EPA’s Heavy

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Table 6 . Charge Question 5 Charge Question 5 : In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? Any recommendations for specific improvements to the functioning of the outputs of the model?

Reviewer

Name Reviewer Comment EPA Response to Comment

Reviewer 3 The version reviewed here do es not include the graphical user interface (with “pull -down menus”) described in the instructions. The ability to modify input parameters and vehicle attributes will improve the user experience, while obviously presumably not impacting the model outputs. Due care and attention should be paid to the number of significant digits presented in the output results. For example, in the results presented from a single specific simulation (shown below):

>> GEM_Phase2_Idle_55_65_CARB_HHDDT_Transient

Distance = 32.414 mi Fuel Consumption = 5.4059 gallons Fuel Consumption = 17184.1217 grams Fuel Economy = 5.996 mpg Fuel Consumption = 530.140 g/mile CO2 Emission = 1697.77 g/mile

The number of significant digits in the model simulation outputs presented above (some of which are directly related through derivation or calculation) varies from 4 to 9. This does not meet recommended practices in the presentation of results and data. Moreover, industry experience in the measurement of real -world fuel efficiency during over the road truck testing dictates that measured fuel consumption variations of less than 1-2% should not be considered significant or compelling, and this level of variation could correspond to variations in the 2nd or 3rd significant figures in fuel consumption in most cases. The agencies have consulted with all major

manufactures o n whether a graphic user interface (GUI) needs to be developed. At this time, none of them support this idea. The reason is that a GUI would prevent the GEM output from being integrated with their internal information technology system. At the same time, a GUI would provide

convenience to those individual user or small entities for use. In order to compromise this issue, the agencies decide not to propos e a GUI. Rather, the input file is designed in such a simple way that the individual users can easily use it for their own

purpose , and an interactive Excel spreadsheet will be made available as mentioned previously.

The number of the significant digits shown in the output screen is not the same as those in certification output file (.csv). It should also be noted that the same output format is used for light duty vehicles where the magnitude of the numbers is much smaller and therefore the significant d igits are fewer. No attempt was made to tune this output, which is not part of the certification process, for heavy duty

test results.

63External Peer Review of EPA’s Heavy

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Table 6 . Charge Question 5 Charge Question 5 : In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? Any recommendations for specific improvements to the functioning of the outputs of the model?

Reviewer

Name Reviewer Comment EPA Response to Comment

Reviewer 4 The following modules will enhance GEM

- II:

• A module that is able to create the input data for a GEM

II execu tion from a user provided spreadsheet with predefined tabs for the engine, transmission, drive cycle, vehicle parameters, and technology improvement. Users are more familiar with spreadsheets than the Matlab

environment.

• A GUI module that guides the user to create a HD vehicle

model.

• A module that allows users to select plots of key component performance. These plots may be summarized in the output spreadsheet data file.

• A more detailed explanation of all the user provided data “target.X” and the various choices available for each of the user provided data. For example, what are the choices that the user has for the variable target.veh_style ?

• GEM

- II execution takes place within the Simulink environment. During execution, no feedback is provided

to the user on the status of the simulation. The user is waiting on a blank screen

– Percent complete of the simulation and which drive cycle is being executed would

be useful feedback for the user.

• Predefined sample input data for all class of vehicles to

assist users to easily modify them if necessary, since some users may not be familiar with Matlab.

• The ability to turn on the feed forward term for the driver model in case of tracking problems in drive cycles with grade. Many comments made by this reviewer are very helpful in terms of the Matlab/Simulink version of GEM. As pointed out earlier, only the executable

version of GEM is allowed for certification where

the Matlab/Simulink environment is not needed. Because of that, the user has no option to make any

model constant modification s.

A GUI is helpful for individual users. However, it may not be helpful for large vehicle manufacturers where they need to connect their information technology system with the output of GEM. The agencies attempt to balance the needs of individual users and large organizations. The combination of the proposed input file and GEM User Guide should be as user friendly as a GUI.

64External Peer Review of EPA’s Heavy

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Table 6 . Charge Question 5 Charge Question 5 : In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? Any recommendations for specific improvements to the functioning of the outputs of the model?

Reviewer

Name Reviewer Comment EPA Response to Comment

• The ability to model accessory power draw as a function of engine speed and engine temperature. The engine cooling fan power cycle will affect fuel economy and

CO2 emissions.

Table 7. Specific Observations on Tool D escription E ntitled, “Vehicle Simulation Model”

Reviewer

Name Page Paragraph Reviewer Comment EPA Response to Comment

Reviewer 1 8 1

Axle lookup table is a better approach The agencies note the comment but determined no revisions are required to

the documentation

8 2 “Brakes” Addition of the inertia component to axle is curious/ a curious description. This is rather a retarding torque. Perhaps the inertia becomes a force if MATLAB is viewed over time steps. I was confused by this language. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM.

10 2 It would be good to see (as well) the equivalent to Figure 1 -3 with the proposed locked shifting strategies in GEM, rather than actual strategies as discussed on p. 10. Some of the comparisons are shown in

Table 4.

16 2 Need to be cautious about claims in modeling changes. Effect of change in Crr is clear, but GEM may have difficulty with relative accuracy in changing transmission type. The agencies note the comment but determined no revisions are required to

the documentation

16 2 Note in presenting these agreements that Crr or Cd changes are entered as dynamometer A -B- C coefficients, and these are not real world The agencies note the comment but determined no revisions are required to

the documentation

65External Peer Review of EPA’s Heavy

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Table 7. Specific Observations on Tool D escription E ntitled, “Vehicle Simulation Model”

Reviewer

Name Page Paragraph Reviewer Comment EPA Response to Comment

measurements. Essentially the dynamometer is partially modeling these effects.

17 Table 1

- 3 And the figure. Note that the 1.8% error represents a 17% error based on the difference, if this figure is intended to show the accuracy of predicting

differences rather than absolutes. The agencies note the comment but

determined no revisi ons are required to

the documentation

18 2 GEM is using automated shifting, essentially, for both MT and AMT, and this will be used (with PI control pedal) for impact assessment. Yet this paragraph brings human drivers to the fore. Philosophically, that the human drivers are the truth and the accuracy of revenue service, more than the model or powertrain cell. The agencies note the comment but determined no revisions are required to

the documentation

19 Fig 1

- 9 to

1

- 13 Are these with default or manufact urer’s shift tables? Yes.

22 Table 1

- 4 Little or no shifting occurs in the 55 and 65 cycles.

That should be stated. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

23 End of

page Text should explain in a little more detail how these powertrain tests may be inserted into GEM The agencies note the comment but determined no revisions are required to

the documentation

Reviewer 2 2 2 Th e li s t o f k e y te chn i ca l fe a ture s m a y i nc l u d e t h e f

ac t t ha t the new model uses dist anc e- ba sed cyc le s ins te ad of ti me- ba sed cyc le s, an d the f ac t t ha t te st

cyc le s n o w i nc l u d e ro a d g r ad e

. It is a distance

- base model

2 2 The claim "more stable engine idle speed controller"

is not discussed in the text. Some metric or quantification of what is meant by "more stable" needs to be provided. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

2 3 Regarding “substantial effort has been put forth to It is mainly used for internal u se.

66External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 7. Specific Observations on Tool D escription E ntitled, “Vehicle Simulation Model”

Reviewer

Name Page Paragraph Reviewer Comment EPA Response to Comment

accurately track and audit power flows through the model to ensure conservation of energy" The report lack details about the energy audit. Was the energy audit developed just for internal quality control or is it going to be provided to the end users in an output

file?

3 1 R eg a rdi n g " t h e ro a d g r ad ie n t ha s b ee n m odifie d t o

acc ept a ro ad grade t hat va rie s as a fu nc tio n of

dist anc e tr av ele d" P le ase in tro duce the co nc ept of

dist anc e- ba sed versus any pros/cons of the new method and why did you change the approach. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

3 2 Driver subsystem. This section (1.2.2.2) is not clear to the reader and, in my opinion, needs rewriting. There are various confusing statements such as "the feed forward calculations using drive cycle

accelerations and vehicle mass have been removed".

The section also mentions (page 4, paragraph 1) that

a ratio of speeds (which is non-dimensional) is integrated to produce the current cycle position (which has units of distance), which is dimensionally

incorrect. I recommend showing the equations to avoid confusing the reader. Regarding the statement "the addition of distance compensation allows all simulated vehicles to complete an equivalent trip

such as trave ling from point A to point B" Does that mean that without distance compensation the vehicles would not complete the trip? The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

3 2 Ho w w er e t h e p ro p ortio na l an d i n tegr a l c o n s t an t s o f

the PI con troller es ti ma ted ? Is the same driver

s u b s y s te m used i n de p e n de n tl y of tr an s m i ss io n The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

67External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Reviewer

Name T Page Paragraph able 7. Specifi

Reviewer Comment c Observations on Tool D escription E ntitled, “Vehi EPA Response to Comment cle Simulation Model”

choice ? Ho w wa s t h e loo k

- ah e a d fee d

- for wa r d

c o n tro l i m p le m e n ted ?

4 2 Co n s ide r removing the m e n tio n to t h e " va ri an t

power train ar ch ite ctu re " since it is not men tio ned anywh er e el s e i n t h e re p ort

. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

5 1 P le a s e c l a rif y t ha t t h e e n gi n e m a p i s n o t a p r e

d eter mined pa ram ete r as in Pha se 1 GEM, but a

u s er

- d efi n e d i np ut. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

5 3 F o r c o n s i s te nc y w it h p re v io us s e c tio n
, p le a s e show the p ro posed const an t power lo ss magn it ude

o f ele c tri c s u b s y s te m

. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

5 4 Please change "four different variants” for "three different variants” (MT, AMT, AT). The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

11 Th er e i s a n appa re n t i nc o n gr u e nc e i n Pa g e 5

, pa ragr ap h 4, wh ich men tio ns t ha t e ac h tr an sm i ss io n

" fe a ture s a un iqu e con tro l a lgorit hm mat ch ing

be hav ior s obs er ved du ri ng vehicl e te s ti ng "

howev er , in Pag e 5, pa r ag r ap h 5 it is men tio ned

t ha t "all of the tr an sm i ss io n mod el s us e an auto
sh if t a lgorit hm to deter mine the op er a ti ng gear over the cyc le ". Are the auto sh if t algorithm pa ram eter s chan ge d ba sed on tr an sm i ss io n t yp e? I s there really a unique control a lgorit hm fo r e ac h

tr an sm i ss io n t yp e ? The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

5 5 Th e " a u t o s h ifti n g o p ti m i z er " n eed s p ro p e r documenta tio n. Ho w doe s i t w or k? A reference paper ( Newman, K., Kargul, J., and Barba, D., "Development and Testing

of an Automatic Transmission Shift Schedule Algorithm for Vehicle Simulation," SAE Int. J. Engines

68External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 7. Specific Observations on Tool D escription E ntitled, “Vehicle Simulation Model”

Reviewer

Name Page Paragraph Reviewer Comment EPA Response to Comment

8(3):2015, 2015, doi:10.4271/2015

- 01

- 1142 .)

has been added into Draft RIA chapter 4 for

more information

6 1 Th e c l u t c h m ode l i s a k e y n e w a dditio n an d l ack s

p ro per documenta tio n.

P le ase su pp ort claims such as " re a li s ti c ac tu a tio n dura tio ns an d m or e acc urate phy sics of tor qu e

c o n s er va tio n an d lo ck u p b e hav ior " w it h d a t a

. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

6 2 P le a s e c l a rif y wha t y o u m e a n b y “This l ay o ut i s more sim il ar to a m an ua l tr an sm i ss io n, but the

app li ca tio n for a pl an et ary gearbox is a

re aso nab l e approximation as thi s t yp e of gearbox

ca n utili ze a va riet y of to polog ie s" i s confusing to

m e

. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

8 2 Th e s t a te m e n t " Th e b r ak e m o d e l a l s o add s a

rot a tio na l in erti a componen t to the ax le " is

mis le ad ing si nc e the in erti a of br ak es is set to z er o i n G E M

. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

9 2 P le a s e p ro v id e a t ab l e w it h a c o m p let e li s t o f p re

d efi ned an d us er -d efi ne d pa ram eter s. Th er e is no

n ee d fo r s p e c ifi c va l u e s
, j u s t t h e li s t o f pa r a me ter s

. It is included in the NPRM

12 1 De s c ri p tio n o f te s t c o n ditio n n u m b e r 6 re a d s
, "Run a new set of ro ad lo ad c oeffi c ie nts to

re p re sent a vehicle con fi g ur a tio n op ti mized fo r fue l effi c ie nc y fo r e ac h vehicle t ha t wa s tested ."

To be consis te nt w it h the other te st co nd itio ns de sc ri bed p le ase qu an tif y th e red uc tio ns in rolli ng

re s i s t anc e
, a erod yna m i c dr a g
, an d m a s s fo r t h i s The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

69External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Reviewer

Name T Page Paragraph able 7. Specifi

Reviewer Comment c Observations on Tool D escription E ntitled, “Vehi EPA Response to Comment cle Simulation Model”

pa rti c u l a r " o p ti m i z ed packa ge " ca s e

. 13 Figure 1

- 3

to 1-6 I n t h e lege n d

, i t i s n o t c le a r i f t h e 55 m p h an d 6 5 mph te sts contai n gr ad e or not. Also, the " utilit y"

cyc l e i s n o t de s c ri b e d i n t h e text

. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

15 Figure 1

- 6 A lt h o u g h is m e n tio n e d in t h e te x t

, i t s ee m s t ha t
the ref use tr uck wa s no t te s te d u nd er the refu se

cyc le . Also, it s ee ms t ha t it was not te s te d u nd er d iffere nt te st co nd itio n s as the re maining vehic le s. An y re a s o n fo r t h i s ? P le a s e e xp l a i n. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

16 1 C han g e " n u m eri ca ll y " fo r " n u m eri ca l.” The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

18 2 Th e s t a te m e n t " I n s o m e ca s e s
, i t i s ha r d t o

qu an tif y wh ich m et hod, vehicl e simula tio n o r

c ha ss is dyna mom ete r te st, i s m or e acc ura te " i s v er y mis le ad i ng

. Th e cha ss i s dyna mom ete r test

a lt hough imp erfe ct, is a meas ure men t and it was

tre a te d as a " true " va lu e in the va lid a tio n p ro cess (F ig u re s 1-3, 1-5, an d 1-6). Acc ur ac y ca n only be

measured in refere nc e t o a tr ue va lue. Th e cha ss is

d yna mom ete r te st was s ele c te d as such an d the

model cann ot hope to hav e b ette r acc ur ac y t ha n

t h e te s t

. Add ed SwRI technical research workshop

as one of the references to Draft RIA Chapter 4. ( US EPA, “Technical Research Workshop supporting EPA and NHTSA Phase 2 Standards for MD/HD Greenhouse Gas and Fuel Efficiency

— December 10 and 11, 2014,” http://www.epa.gov/otaq/climate/re gs

heavy

- duty.htm )

18 3 I n t h e s t a te m e n t " G E M is capab l e of cap turi n g the

im pac t on the tot a l vehicle CO 2 emi ss io ns an d

fue l consump tio n d ue to an y te chn ology imp ro vement" the w or d " any " is mis le ad ing si nc e the va lid a tio n effor t wa s only done over

a ero dyna mic, rolling re sist anc e an d mass

pa r a m eter s

. M oreo v er
, there i s c ert a i n l y a s e t o f The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

70External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 7. Specific Observations on Tool D escription E ntitled, “Vehicle Simulation Model”

Reviewer

Name Page Paragraph Reviewer Comment EPA Response to Comment

te chn olo g ie s that G E M i s i ncapab l e of m o d el

. 17 Table 1

- 3 Corre c t t h e n u m b er s o n t h e " Delt a " c ol u m n

. D ue

to ro unding it is not eviden t t ha t the column

re p re sents the d iffere nc e b et w ee n the two p re v iou s columns. For e xa mple in th e fo u rt h ro w we hav e 3.9% - 4.9% = -0.9%. In the same Tab le , p le ase

ca lculate the rel a ti ve erro r (consis te n t with Figure 1-8). Is this rel a ti v e error more relevant than the

“delt a”? W ha t is th e m ax imum acc ept ab le rel a ti ve

error ? The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

22 P le a s e a d d a t ab l e t ha t s u mm a ri z e s t h e

te chn olo g ie s cap ture d by the simula tio n a n d th e technologies t ha t are no t cap ture d but ar e accounted for via drop -down menus . A th ir d (o p tio na l) column may i nc lude te chn olog ie s t ha t

c urre n tl y are not eit her simula te d, nor re co gn ize d by dro p-down menus but poten ti a ll y may be

i nc lu ded in future regul a tio ns. We have detailed the technologies included as inputs to GEM and technology improvement inputs (drop-down) in the HD Phase 2 NPRM preamble. We welcome comment on other technologies that would only be considered as part of the innovative technology credit program and therefore not simulated or recognized by the drop-down

menu.
22 Section

1.4.1.1 R eg a rdi n g " A s d e s c ri b e d i n C hap te r 1

. 2

. 2

, o n e o f

the ma jo r chang es i n th e H D Pha se 2 v er s io n o f

GEM is to a llo w m an uf ac turer s to en te r th ei r

tr an sm i ss io n gea r numbe r v er sus gea r ra tio "

C hap te r 1.2.2 doe s no t men ti on t ha t f ac t. P le as e ch ec k through ou t the re port to av oid i ss ue s w it h

t h e s e s elf

- refere nc e s

. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

23 1 R eg a rdi n g t h e s t a te m e n t " M an u f ac t u rer s a l s o hav e

an op tio n to s ele ct th e t yp e of tr an sm i ss io n, which

is eit her m an ual or automa ti c" It is not c le ar if

tr an sm i ss io n t yp e i s a req u ire d i np ut o r a n The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

71External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 7. Specific Observations on Tool D escription E ntitled, “Vehicle Simulation Model”

Reviewer

Name Page Paragraph Reviewer Comment EPA Response to Comment

o p tio na l i np u t

. A l s o
, t h e u s e r s h o u l d ha v e t h re e

o p tio n s ( AT

, M T

, an d A MT )

, n o t j u s t t w o

. 23 Table 1

- 4 Table heading should mention that the results are from simulations in GEM, not measurements. Also, it is not clear if the 55mph and 65mph cruise contain grade. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

23 4 The report mentions that due to lack of data, DCT,

DCT with TC and Allison TC-10 AT transmissions were not validated. That assertion implies that MT,

AMT and AT were validated. Since transmission technologies were not tested at the same level of

detail as road load reduction technologies, it is important to acknowledge the different level of

validation between transmissions and road-load reduction technologies. The agencies note the comment but determined no revisions are required to

the documentation

23 Last Paragraph Regarding DCT and other transmission types not
included in the model, the report says, "The

manufacturers still have the options to use powertrain dyno tests to quantify the benefits of these or any other special transmissions". It is not

clear if the resu lts of the power train tests are going

to be used to correct the GEM simulation results or are going to replace the GEM simulation results altogether. Please clarify. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

24 1 R eg a rdi n g OE M o v erridi n g t h e ax l e effi c ie nc y i np ut, "the i np uts would b e d eter mined by using the p re sc ri bed test p ro cedu re ” It is not c le ar wh ich te st p ro cedur e is th e re p or t referri ng to

. P le a s e a d d a refere nc e t o s u c h p ro c ed u re

. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

24 Last Rolling resistance coefficients are usually expressed The text has been corrected (or clarified)

72External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Table 7. Specific Observations on Tool D escription E ntitled, “Vehicle Simulation Model”

Reviewer

Name Page Paragraph Reviewer Comment EPA Response to Comment

Paragraph in units of kilograms per metric ton (1 t = 1,000 kg). The units used (kg/ton) may imply short ton (1 ton = 2,000 lbs.). Please correct and be consistent throughout the document. in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

25 1 Th e "R e g io na l ", “M ulti

- p u rp o s e ", and " U r ban "

compos it e duty cyc le s ar e not desc ri bed in the

d o c u m e n t. More can be seen in Chapter 3.4.2.3 about idle cycle as stated in the same paragraph

25 3 P le a s e s u pp or t y o ur s t a te m e n t

, " W e c o nc lu d e d t ha t
fo r the 55 mph an d 6 5 mph duty cyc le s, GEM's

in ter pola tio n of s te ady -state data t ab le s wa s

su fficie n tl y acc urate v er s us the meas ure d results "

W ha t wa s the observe d accuracy of using s te adystat e maps fo r the 5 5 an d 65 mph c rui se cyc le s?

Ho w m u c h acc u r ac y i s s u ffi c ie n t ? This statement is based on the engineering judgment.

25 3 Th e 55 m p h c r u i s e i s na m e d "u r ba n h ig hwa y w it h

ro ad grade ", the 65 mp h c rui se is na med "rural

h ig hwa y w it h ro ad gra de

, an d the A RB tr an s ie nt

cyc le is na med "u r ba n lo ca l ". P le ase tr y to use
consis te nt na mes throu gh out. Also, si nc e the

c rui se cyc le s in Pha se 1 w er e ti me- ba sed an d did

not i nc lude ro ad grade, the Pha se 2 cruise ro u te s (di st anc e- ba sed with gr ad e ) are no t equi va le n t to
the m an d usin g th e sam e na m e i s m is le a di ng . I

thin k a dis ti nc tio n ca n be m ad e by using the ter m

" route " fo r the dist anc e- ba sed te sts an d " cyc le "

fo r the ti me- ba s ed , or simply na me them " 55 mph

c rui s e w it h g r ad e " an d " 6 5 m p h c r u i s e w it h gr a de ". The agencies note the comment but determined no revisions are required to

the documentation

29

­ 30 Table 1

- 6

& 1 -7 A uto m a ti c tr an sm i ss io n s have t h e s a m e effi c ie nc y fo r all gears ( 98 %), an d such effi c ie nc y is

eq u i va le n t t o t ha t o f m an u a l an d a u to m a te d m an u al We chose this based on the comments from

manufacture rs’ input plus our engineering judgment

.

73External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Reviewer

Name T Page Paragraph able 7. Specifi

Reviewer Comment c Observations on Tool D escription E ntitled, “Vehi EPA Response to Comment cle Simulation Model”

tr an sm i ss io n s in d ire c t drive

. W a s this advan t ag e observed during testing ? If po ss ib le

, please

document w it h meas ure d da ta showing the ben efit s

o f A T ove r M T i n ter m s o f g e a r b o x effi c ie ncy

. Reviewer 3 1

Use “dynamometer” and not “dyno” The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

Et

seq.
Use “Phase 2” and not “Phase II” The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

5 1.2.2.3.1

Use “watts” or “W” and not “Watts” The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

5 1.2.2.3.1

“it may o make use” requires clarification The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

7 1.2.2.3.3.7 “ With the new gear engaged the clutch is reengaged and the engine is again allowed to operate at full load.” This statement presupposes that the transmission was shifting under full engine load, which is not necessarily the case for high power engines under benign operating cycles. The agencies note the comment but determined no revisions are required to

the documentation

7 1.2.2.3.4 “ This includes drive shafts as well as driven and passive axles, consisting of a differential, brakes and

tires.” Passive axles will not ordin arily include a differential, only driven axles will. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

8 1.2.2.4 “The vehicle system consists of the chassis, its mass and forces associated with aerodynamic drag and changes in road grade”. Why “changes in road grade”? Any constant road grade (other than zero) The text has been corrected (or clarified) in Chapter 4 of the Draft RI A to the HD

Phase 2 NPRM

74External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Reviewer

Name T Page Paragraph able 7. Specifi

Reviewer Comment c Observations on Tool D escription E ntitled, “Vehi EPA Response to Comment cle Simulation Model”

will have an effect on the apparent vehicle load, and not just changes in grade.

9 1.2.2.4 “computes acceleration [not accelerations] from the input force and equivalent mass which is integrated to generate vehicle speed and distance traveled” The text has been corrected (or clarified) in Chapter 4 of the Dra ft RIA to the HD

Phase 2 NPRM

9 1.2.3.2

Use “Matlab” or “MATLAB” and not both. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

10 1.3

“ Validations use all actual vehicle variables

conducted at Chassis dyno cell,” needs editing. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

11 Ref. 3 is not the SwRI report as stated. It is an ASME Technical Paper. The Technical Paper is the report

12 A +

- 15% variation in aerodynamic drag, for example, is unlikely to span the full range of expected values in the future for HD vehicles. Presumably aerodynamic modifications to Class 8 vehicles may result in significantly lower drag coefficients, or drag products (CdA) This was just for the purposes of the tech study, these are not GEM limitations

13 1.3.2 For the Class 8 T700 tests, at high fuel efficiency,the GEM model appears to consistently underpredict the actual measured vehicle fuel economy.

This consistent offset is of concern. The reverse is

observed for the Class 6 truck tests. In the technical research workshop held at SwRI in December, 2015, the testing variability is discussed in details. It is very challenging to validate GEM for those hig hly transient cycles for a heavy truck.

20 Fig 1

- 11

Caption is incorrect. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

21 Fig 1

- 13 Vertical axis incorrect unit designation. It is NM for torque

22 Do not use the term “aero drag”. It should be “aerodynamic drag”. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

75External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Reviewer

Name T Page Paragraph able 7. Specifi

Reviewer Comment c Observations on Tool D escription E ntitled, “Vehi EPA Response to Comment cle Simulation Model”

Phase 2 NPRM

22 “tire radius” should be “tire rolling radius” or

‘effective radius’. The text has been c orrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

Reviewer 4 5 2 The last sentence reads “If a manufacturer uses a hybrid powertrain for the power take- off devices, it may o make use of ....”. The “o” after may is a typo. The text has been corrected (or clarified) in Chapter 4 of the Draft RIA to the HD

Phase 2 NPRM

3 2 Distance compensation is critical for all vehicle

simulations – Therefore, this is a good feature that has been implemented in GEM

- II The agencies note the comment but determined no revisions are required to

the documentation

6 4 Please explain what is included in spin losses, since this may not be clear to all OEM users. The agencies note the comment but determined no revisions are required to

the documentation

9 3 The GEM

- II executable is very appropriate for users

who are not fluent in the Matlab/Simulink

environment. Further, the executable prevents users from making any changes to GEM -II to support compliance. The agencies note the comment but determined no revisions are required to

the documentation

Reviewer

Name Input Tab le 8.

Variable Specific Observations on E lectronic M odel E ntitled

, “GEM Tool”

Reviewer Comment EPA Response to Comment

Reviewer 1 No Specific Comments or Observations

Provided.

Reviewer 2 File: “GEM_run_postproc.m” Lines: 104 to

108. Potential issue: It seems to me that the equation is not dimensionally correct (I might be wrong). Additive terms should have the same units and the equation seems The equation, while lengthy, is correct. Simplified, the equation amounts to grams/hour * hour/mile which equates to grams/mile.

76External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Tab le 8. Specific Observations on E lectronic M odel E ntitled

, “GEM Tool”

Reviewer

Name Input Variable Reviewer Comment EPA Response to Comment

to be adding gCO2/h terms with gCO2/mile terms. Please check for missing terms and/or appropriate use of parenthesis.

File: “GEM_run_postproc.m” Line: 101. The calculation performed for case 4 is identical to the calculation performed for case 3, making it redundant. Please eliminate case 4 (neutral idle with start/stop), or correct the equation to

account for a 90% reduction in neutral idle emissions (not drive idle emissions). This is correct, for certification neutral idle and start/stop will not be credited simultaneously, only the start/stop credit is available. This code is from the evaluation phase of GEM development.

“vehicle.chas

sis.
frontal_area_

m2” The name is misleading. Please rename to “drag_area”. Drag area is CdA, aerodynamic drag coefficient is Cd and

frontal area is A. The model supports separate variables for Cd and Area. For certification, we set the Cd t o 1.0 and apply the Cd*A to the area variable. This does not

affect simulation results. File: “load_GEM_params.m” Lines: 76 to 85. These equations set weight reduction penalties for spark-ignited CNG (525 lbs), compression-ignited CNG (900 lbs), and compression- ignited LNG (600 lbs). Please set a weight reduction penalty for the missing case: spark

- ignited LNG. We are seeking comment on the weight penalties associated with natural gas vehicles in the preamble

to the HD Phase 2 NPRM. W e will adjust the values accordingly for the final version of GEM,

based on the comments received.

File: “load_GEM_params.m” Line: 94. I

am confused about the variable “vehicle.chassis.mass_dynamic_kg” as

defined here is a constant. However , during

the simulation (variable: datalog.vehicle.dynamic_mass_kg) the equivalent mass of the rotational components vary depending on the active The chassis. dynamic_mass_kg represents the weight

of the chassis (“static_mass_kg”) plus the effective

mass of the r otating inertia of the tires/wheels (125 lbs mass per wheel as consistent with other EPA test procedures ). The upstream inertias are calculated dynamically during model execution, as noted, and

added to the chassis. dynamic_mass_kg to determine

the vehicle ’s total effective inertia. The datalog

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Tab le 8. Specific Observations on E lectronic M odel E ntitled

, “GEM Tool”

Reviewer

Name Input Variable Reviewer Comment EPA Response to Comment

gear. variable represents the total vehicle inertia during

simulation , not just the inertia of the chassis.

F ile : “lo ad_ G E M _pa r a ms

. m ” Li n e s : 11 7

an d 143 . I t is not c le ar wha t e xac tl y the

va ri able s “tr an sm i ss io n.au to sh ift. cost_m ap ” an d

tr an sm i ss io n.au to sh ift.req u ired _c ost _b en efit _ra tio” re p re sent, an d ho w are they

used in the m odel . Othe r features such as “re s tri c t skip sh ift s ”, re s tri ct sh if t pa rit y”,

“di s ab le coast s av ing do wn sh ift s” are not

w el l do cumen te d in the .m file s or i n the

re p ort. These features are not user inputs but are described in a technical paper, SAE 2015-01-1142.

F ile : “lo ad_ G E M _pa r a ms

. m ” L i n e : 13 1

. Th e c a l c u l a t i o n of

“ Tr an sm i ss io n .ge a r.i n ertia_k gm 2”

i nv olves a multip lic a tio n by 0. Th erefor e it would p ro duce an a rr ay of z eroe s. Also,

a ss uming t ha t the va lu e of 0 is chang ed

to a fi n it e const an t, it s ee m s that the

model is a ss umin g the sam e in erti a va lue

fo r all the d iffere nt gears. Is t ha t

s i m p lifi ca tio n acc ur a te ? For the transmission in question, the total inertia is represented by the common input and common output inertia, the inertias referred to are the “gear specific” inertias which for an AMT or MT are set to zero since all gears always spin with the input or output. Since this is not a user input the default

value makes little difference for certification purposes since all users will use the same value.

File: “load_GEM_params.m” Line: 134.

The calculation of “transmission.gear.spin_loss_torque_Nm” involves a division by a factor of 3.73 for

all the transmissions that are not C78_AMT. I am wondering what that factor represents. Also, if that factor is still The 3.73 is a scale factor which scales the default Class 8 spin losses down to a level c omparable t o the a utomatic transmission while maintaining the

same loss trend as the Class 8 AMT with respect to speed. The default transmission losses will receive additional scrutiny between now and the final rule. In addition the peer review does not necessarily

78External Peer Review of EPA’s Heavy

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Tab le 8. Specific Observations on E lectronic M odel E ntitled

, “GEM Tool”

Reviewer

Name Input Variable Reviewer Comment EPA Response to Comment

valid for a potential C78_MT transmission. have specific default values for every transmission type by capacity (LD versus HHD, etc). Energy Audit. Net system kinetic energy change is 0 kJ, which is the result of the test cycle starting and ending at 0 mph speed. The test cycle seems to start and end at the same altitude (symmetric grade profile traveled at constant speed), so one can expect the net system potential energy change to be 0kJ as well. Since both kinetic and potential energy are conservative and not dissipative forms of energy, I was confused about the energy audit accounting

for energy “consumed” by gradient at about

17% of the losses for a tractor- trailer. Checking the equations, it seems that the energy audit is performed only for positive

tractive loads. If that i s the case I am confused about the energy consumed by the

brakes at about 7% of the losses for a

tractor -trailer. They should be really low if one is only considering positive tractive loads. The brakes are mostly applied for negative tractive loads (e.g. driving downhill). Am I missing something here? For auditing purposes, the potential energy changes are split between “Energy Consumed” (going uphill) and “Energy Provided” (going downhill). In the case of a driving cycle which starts and ends at the

same altitude but has some gradient in

- between you will see equal (within model tolerances) entries in both of these audit categories.

All of the “Energy Consumed” audit values represent energy sinks, the brakes are included among these since they dissipate kinetic energy.

In any case, the audit report is for internal use only and does not represent a user or certification output.

Why the weighted average speed For tractor

- trailers the idle weight is zero and th e (weighted_avg_speed_mph) used in post simulation grams/mile are multiplied by target mph processing (file: “GEM_run_postproc.m”) and also divided by target mph so what remains is

is based on the target speed

- distance trace simulation grams/mile which will reflect the

and not in the actual simulated speed

- modeled performance (or under

- performance) of the

79External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Tab le 8. Specific Observations on E lectronic M odel E ntitled

, “GEM Tool”

Reviewer

Name Input Variable Reviewer Comment EPA Response to Comment

distance trace? This decision has implications for underpowered vehicles that deviate substantially from the target trace since their actual average speed may differ substantially from the t arget speed. This also has implications for the

calculation of idle fuel rates for vocational

vehicles since the conversion factor from idle fuel rate in [kg/h] to [kg/mile] is the weighted average speed. vehicle.

For vocational vehicl es the same is true with re gard to the simulation grams/mile over the drive cycles. Idle consumption takes places at zero speed and is measured in grams/hour so there is a conversion factor required to obtain grams/mile. The target weighted average speed represents that conversion

factor and does not alter the modeled vehicle performance (or under- performance) over the drive cycles.

Reviewer 3

Aerodynamic drag -- Audit data for
GEM_Phase2_Idle_55_65_CARB_HHDD T_Transient drive cycle

–

“Energy Consumed by Cd” should refer to

“CdA” and not “Cd” alone. True, but the audit report is for internal use only and does not represent a user or certification output so the shorthand here is of little importance.

Engine

Accessories Engine Accessories = 846.16 kJ 0.23%

It seems as though engine accessory loads

are under-accounted for in this implementation of the model – a 0.23% loss for a full transient cycle seems inappropriately low. For peer review, the accessory load is set to 1300 W

combined mechanical and electric load for all vehicle classes. The agencies are seeking comment on the predefined values in GEM in the HD Phase 2 NPRM preamble and will make the necessary adjustments for the final version of GEM.

Usable System Energy Provided =

373988.49 kJ

Engine Energy = 309402.35 kJ

Engine Efficiency = 42.08 % The maps provided were mathematically generated and do not necessarily represent actual fuel maps. In any case this would represent the total efficiency over the drive cycle. These audit results are not user or certification outputs and will not be available

80External Peer Review of EPA’s Heavy

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Tab le 8. Specific Observations on E lectronic M odel E ntitled

, “GEM Tool”

Reviewer

Name Input Variable Reviewer Comment EPA Response to Comment

This integrated “engine efficiency” is high for the average efficiency expected across a fully transient cycle

– does this refer to the peak engine efficiency encountered? dur ing certification.

Reviewer 4 Avoid taking the derivative in the Simulink

models. This can cause instabilities if the signal fluctuates rapidly Point taken, the use of derivative blocks is

minimized in GEM.

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E. INDIVIDUAL PEER REVIEWER COMMENT S

82External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Peer Reviewer # 1

83External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation


### Peer Review Comments on EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

I. GENERAL IMPRESSIONS

The purpose of GEM in determining standards, providing a compliance tool, and estimating realworld benefits is clearly articulated. The proposed Phase II GEM tool has evolved substantially from the Phase I version, particularly by allowing additional user inputs that are nece ssary to acknowledge fuel efficiency design improvements. As a compliance tool GEM should seek to account for all technology advances and differences, yet remain simple to execute and employ readily -measured and well-defined input variables. The Phase II G EM model has reached a reasonable compromise between these conflicting goals, and this made clear in the narrative. The overall architecture is sound, the present component models are appropriate to the task in nearly all cases, and they are clearly descri bed. The model yields credible results and credible responses to input variable changes. The overall model predicts fuel efficiency to within 5% of experimental measurements, and a clear summary of these comparisons is presented. However,

the material does not address quantitatively the experimental error that is likely in these comparisons, and measurement errors associated with rolling resistance and drag are not included in the data comparison. Overall agreement with experimental data (as vehicle fuel

ec onomy) does not validate each component model to the same degree, and this should be acknowledged more clearly. As one example, overall fuel economy data are used to compare a component model with a fixed efficiency value. The difference overall was only 1.67%, but this represented more than a third of the losses for that component. The move to a distance- based strategy is justified and well -described, and represents a laudable advance. Addition of several transmission models is presented, as are thoughts on the addition of transient adjustment factors. Little is said of the “powertrain variant architecture,” although this may prove important for integrated powertrains with or without a hybrid component. Transient Adjustment Factors are not yet finalized, and transient operation may warrant more than a single correction factor approach.

II. RESPONSE TO CHARGE QUESTIONS

1. Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or issues that were not discussed or addressed by the GEM tool or its component sections?

Throughout his review, except where different fuels are mention ed, fuel efficiency improvement and GHG reduction are considered to be synonymous.

Beyond the need for assurance of compliance is the need to reduce fuel use and climate change emissions from heavy-duty vehicles in revenue use. A successful EPA approach must be examined from two perspectives. First, it is necessary that the approach yields well -defined, unambiguous results to allow a manufacturer to compare against a standard without the process being unreasonably onerous. Second, it is necessary that that the vehicle attributes and behaviors embodied in the certification process are substantially representative of real world circumstances. These two necessities are often in conflict, because the real world scenario is complex, variable,

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and long in duratio n, whereas the standard must be concise and precise. The conflict is far greater in the heavy duty trucking arena than for light- duty vehicles or rail because truck architectures vary widely, and are used in an even wider fashion.

Employing a model such as GEM to assure compliance provides some relief in the conflict described above because the model can be executed for a variety of activities and scenarios without excessive cost of time and resources. However, as the model is challenged to predict

these v aried (and emerging) scenarios with fidelity, the model complexity rises. As a result, the empirical tables or computational sub -models needed within the model grow in number and demand substantial engineering time to prepare and verify. One might argue that “the more one models, the more one measures,” recognizing too that precise test protocols must accompany

each measurement.

Compromise is necessary between four fundamental needs:

1) Relevance of the model to real world truck operation.

Else the real wo rld improvements will not match the changes in standards. 2) Accuracy of the model in predicting measured fuel efficiency (and GHG production). Else confidence in the model will be lost and the compliance will become artificial. 3) Accuracy of the model in pred icting differential effects of technology changes on fuel efficiency (and GHG production). Else the drivers for technology advancement will be lost 4) Control complexity and cost of modeling and compliance. Else the cost transferred to the consumers will be inappropriate.

The overall new GEM approach shows awareness of these necessities, and reaches a reasonable compromise. However, when some parameters are fixed by the agency, manufacturers may be discouraged from pursuing certain development opportunities in the following way. Both future fuel pricing and future fuel efficiency standards are unknown. If high fuel prices transcend the standards, then manufacturers will pursue every cost- effective tool to reduce fuel use. However, if fuel prices are low and are not the driving force, and the GEM approach offers default values for factors such as engine transient adjustment factors or transmission efficiencies, some opportunities for real world reduction may be left on the table. GEM cannot rely on economic drivers to address technology advances that are not modeled.

GEM is a vehicle -based tool that is geared towards road-load demands rather than enginespecific (“%load” and “%speed”) demands. Only the new distance

- based cycles give a nod toward engine power. Criteria pollutants are still characterized using a paradigm based on engine rated output. Allowing different measurement methodologies for efficiency and criteria pollutant production will open a window for separate hardware and software optimization for each test. This may demean the benefits of the separate standards to some degree: in

- use compliance for criteria pollutant measurement will not close this gap because measurement allowance for criteria pollutants reduces stringency for criteria pollutants

.

2. Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following:

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- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

a) Elements in each system used to describe different vehicle categories;

The proposed GEM Phase II model represents a substantial advance over the model used to implement the first phase of truck efficiency legislation, and encourages more technology advances from manufacturers in consequence. Improvements in truck efficiency are based primarily on reductions in aerodynamic drag, tire rolling resistance and engine brake specific fuel consumption, and this was recognized in the first GEM model. Practically, t here is less to be gained from aerodynamic improvements in most vocational truck operation than in long haul trucking and the GEM model as presented neglects vocational truck aerodynamics, and the modelers are right to exclude aerodynamic parameter entries for low speed trucks. However, the overall GEM structure is capable of modeling aerodynamic improvements for niche vocational designs, and has the flexibility to extend beyond the present exclusion of the drag coefficient. In this way, the capabilities of the model, as received, will be far greater than the executable version that is finally used for compliance.

A major theme in the industry is that efficiency gains are significant from design integration, particularly powertrain integration. But it is un derstood that combined powertrain control is proprietary. The supporting language might address this more clearly, noting that the GEM model employs just steady -state maps and a defined set of gear ratios, and cannot predict the benefits of more sophisticated integration. In a similar fashion GEM cannot predict the benefits of learning algorithms, look- ahead strategies and intelligent vehicle systems for the optimization of powertrain efficiency on specific routes. These are emerging approaches, but it is acknowledged that it would take great effort to configure GEM to deal with these details and it would be difficult to assure their generic benefit in revenue service. GEM has some check -a-box options proposed for features that cannot be modeled.

The model, as provided, was oriented to diesel engines. The shift strategies also considered the engine torque curve for execution. Naturally aspirated gasoline, boosted gasoline and natural gas engines are likely players in the next five years and may warrant separate and careful consideration because their characteristics, torque curves and efficiency maps differ substantially from the diesel engine properties.

b) Performance of each component model including the reviewer’s assessment of the underlying equations and/or physical principles coded into that component;

MATLAB/Simulink remains an excellent basis for the GEM model. It is well suited for the exploratory and development framework, as well as the production of a more limited executable

model.

GEM may be vie wed on three levels. At the highest level, the MATLAB/Simulink platform allows GEM to be anything it chooses, with the addition or alteration of modules and component models. At the second level, there is the model provided for review, which has the innate ability to deal with a wide range of cycles and truck configurations. At the lowest level will be the final executable version, where certain parameters are fixed, and where the duty cycles are chosen for determination of compliance. Only the second and l owest levels can be considered in this review.

This GEM model is being produced at a time where engine control strategy development and integrated powertrain controls are advancing rapidly. Also, transmission options are now far

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- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

wider than in the earlier GEM model, where unsynchronized manual, synchronized manual and traditional automatic transmissions dominated the marketplace. GEM is challenged in modeling and giving credit for the technology subtleties that will emerge in the marketplace over the next

f ive years.

The use of distance, rather than time, as a basis for the test cycles represents a great and important advance. It was widely recognized two decades ago that light duty automobiles were capable of far more aggressive performance than was embod ied in the FTP-75, although the

FTP -75 was used as the norm, and still embodied allowances for vehicles that could not follow its modest accelerations. In the heavy -duty arena sustained use of full engine power both on grades and during acceleration is the norm. All else being equal, a more powerful truck will complete its duties in less time than an underpowered vehicle, and often the more powerful choice represents the overall economic optimum. However, the more powerful truck will spend

less time at full power, and will enjoy a reduced average “%load” in revenue service. The adoption of the distance-based approach is an important step toward matching the GEM model to

real -would use. However, as standards are finalized, the accelerations and grades of cycl es embodied in the GEM execution must represent real life as well. If the grades and accelerationvalues are not appropriately challenging, the distance-based approach will look more like a timebased approach, because underpowered trucks will be able to f ollow the trace in the minimum

time allowed. This would divorce the market incentives from the environmental incentives and create a false impression of fuel efficiency capability at the expense of economic reality. It is important that the grades and test weights used are realistic and representative. Further, the indication of the ratio (actual / minimum time for cycle completion) is a very beneficial output

value.

A driver’s habits are known to have a measurable impact on truck fuel efficiency. This is in part due to gear selection that influences the engine operating envelope, and in part due to transient pedal demand (driver PI controller), that may cause an engine to depart from steady

- state mode to a greater or lesser degree. The GEM load demand cont roller and GEM gear selection algorithms can be configured to reflect different driving habits. If the chosen GEM driver yields a better fuel efficiency than would be expected of the national average driver, then GEM will fail to grant auto-shifting techno logy and certain engine control strategies their full potential contribution to efficiency gain. It is recommended that this issue is at least explored to provide driver sensitivity results to the accompanying document.

The engine model in the new GEM is still a steady -state map. The documentation acknowledges that transient fuel efficiency will differ from steady

- state efficiency at the same speed and load in time. A transient adjustment factor (TAF) seems likely for the final version, but the use of a

st eady -state map with a TAF does not encourage manufacturers to improve transient fuel efficiency if a generic TAF is assigned. This reviewer appreciates that manufacturers are unwilling to reveal strategies that represent a substantial fraction of product v alue, yet they cannot take advantage of their improvements in the model without this information. Two solutions are possible:

(i) Determine a manufacturer

- specific TAF rather than an agency -specified TAF, or (ii) Determine an alternate fuel efficiency map for transient (e.g. Heavy

- Duty FTP) operation, and use that map or both steady state and transient maps for the transient cycle.

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- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

In addition, TAF will need to be considered carefully for gasoline and natural gas engines, where enrichment management has an important effect on fuel efficiency. In a similar way, cylinder deactivation strategies may be difficult to characterize for throttled engines, because the deactivation strategy is not well represented by a steady

- state map. It is important to have a TAF

s trategy that acknowledges successes of manufacturers in lowering transient operation disadvantages.

The EPA developers have sought comment on the issue of axle efficiency. It can be dangerous to employ the overall fuel economy computation to compare two a pproaches to modeling a single component, particularly if that component represents a small loss. In one case, the overall fuel economy differed by 1.67% when a simplified efficiency was compared with a lookup table for rear axle efficiency. This 1.67% rep resented more than a third of the loss associated with that component. To place this in further perspective, the 1.67% can be compared to the 3- 5% contributions of a major component, such as side skirts on a semi- trailer at freeway speeds. Generically, if a component model with higher fidelity is available, in the opinion of this reviewer, it is worth including the detail in GEM, even if the component model is fixed in GEM. Furthermore, the existence of such a model may provide a clearer pathway for enterin g technology advances by a manufacturer who improves that component in the future.

The tires in GEM are simply characterized by a rolling resistance coefficient and an effective loaded radius. It is known that the coefficient varies with vehicle speed and contact area, while longitudinal slip can change the revolutions per mile by a few percent under driving torque and braking, which could bias results more substantially when grade is present. This could be coded into GEM, but it is probably more appropria te to treat it as a comment, since detailed tire data of this kind are not in the public domain and test methods are not universally defined.

c) Input and output structures and how they interact with the model to obtain the expected result, i.e., fuel consu mption and CO2 over the given driving cycles;

The accompanying explanatory document emphasizes that the input and output structure has not been finalized. A comment, intended as guidance, is that manufacturers will be obliged to use the executable version of GEM a large number of times to cover each order or each truck technology change over the year. This is needed to compute an average value for compliance. The EPA should make every effort to insure that the final version can be interfaced with the manufacturers’ software to insure that the process is efficient and reasonably inexpensive, while keeping that version of the model locked to insure compliance.

The .csv output files, viewed in Excel, provide a representation of likely input and output files. These summaries are very useful and appropriate.

d) Default values used for the input file, as shown in “Vehicle Simulation Model” document.

The default values are not particularly important at this stage of development. They are sufficiently representativ e of recent or current technology to provide reasonable inputs and to assess the ability to predict real -world values. However, this is an appropriate point to acknowledge and discuss the comparison of GEM output with real- world measurements, as

described in the supporting material.

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- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

The real -world data serve to verify the ability of GEM to model a variety of trucks. These data do not extend to the validation of truck tire rolling resistance or aerodynamic drag value

selections because the validation was co nducted using roller and powertrain dynamometers, where these values were entered and were the same values used in GEM. Generally GEM matched the measured fuel efficiency values to within 5%, and the deviation may be attributed

both to measurement error an d to the inherent simplifications in modeling. There are some systematic errors evident in the comparison. For example, the T700 truck efficiency is underpredicted (GEM vs. measured) on the high speed tests and overpredicted on the low speed

tests. This tr end differed for the T270 and F650 trucks. The refuse truck fuel efficiency was uniformly overpredicted. This leads to the conclusion that GEM may be capable of predicting overall fuel efficiency accurately (at the 5% difference level), but that one should still be cautious of comparing the performance of very different technologies using the GEM tool.

The narrative states that “While it is encouraging that GEM accurately simulates overall vehicle performance in an absolute sense, it is actually more important that GEM is accurate in relative comparisons.” This is true in the sense that GEM should encourage the best technology pathways through comparison, but it is nevertheless the single overall predicted efficiency that is of

interest to the manufacturer because it predicates compliance. As an example, when the axle ratios were adjusted for a vocational truck from the chosen value of 3.76 to high (4.06) and low (3.46) values, the predicted transient fuel economy values were 5.55, 5.49 and 5.6 respectively. In contrast to this small variation, the fuel economy values for the 65mph operation were 7.14,

6.88 and 7.37 respectively, attributable to the 9% difference in engine speed between the high

and low ratios. This reviewer has confidence in these relative v alues where a variable input is changed. However, a comparison between two vehicles with identical chassis and bodies, but with different engines, transmission types and tire rolling resistance challenges several parts of GEM in a differential sense, and a greater comparative error must be anticipated. One cannot argue that the overall agreement with the measured data verifies each sub

- model within GEM.

The use of single variables to represent a more complex reality is discussed elsewhere in this

review.

The cycles chosen for evaluating vehicle performance can be changed readily in GEM. Although incorporation of grades represents a substantial advance, the current choice of fixed 55mph and 65mph steady speeds may cause designers to “teach to the test.” [The CBD cycle, used in a previous age to quantify transit bus performance, suffered from problems of this kind because all steady state operation was at 20mph.] The output data for the tractor (through engine speed / vehicle speed ratio) show that the highest gear was used for both fixed speeds. Use of a test cycle where speeds varied slowly through the 50 to 70 mph range could avoid pitting real world optima against model optima, and would encourage engine downspeeding strategies that are

successful in reven ue service where speed limits are not necessarily 55 and 65mph.

3. When using the standard of good engineering judgment, is the program execution optimized by the chosen methodologies?

The GEM tool as presented to the reviewers provided a workable compro mise between accuracy and simplicity. It is evident that GEM may be improved in accuracy by increasing input data, in particular the substitution of data tables for single values. However, these tables would need to be created for each component at substan tial expense. Also, it would be better to use real values

89External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

or tables or strategies from manufacturers, but each of these might require audit and prescribed measurement methods, and in many cases the manufacturer considers them to be proprietary. The present GEM is close to being optimized: clearly development is still taking place.

As a general observation, the engine and transmission receive substantial attention in GEM and in much work on truck efficiency improvement. They seem to be of interest at the single percentage level. However, tire rolling resistance is a major influence for vocational trucks, and drag coefficient controls the dominant loss for freeway tractors. Yet these two components are each represented by a single parameter. Beyond just GEM , a more detailed consideration of these components (e.g. longitudinal slip of tires, rolling resistance during crosswind correction, effects of yaw on drag) would assist in raising modeling accuracy. If that cannot be considered expediently for this version of GEM, it should be considered in the future, or even embedded in the tables so that it can be applied without altering the code.

4. Please comment on the clarity, completeness and accuracy of the intended output/results (CO2 emissions or fuel efficiency output file).

The .csv output results are sufficiently comprehensive for the user who is not executing the program in MATLAB for research and design purposes. Presumably a report similar to the .csv is anticipated as the executable version output. In fact, to the manufacturer, who is executing this at time of sale within a larger accounting loop, a very succinct output would be sufficient.

5. In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool ? Any recommendations for specific improvements to the functioning of the outputs of the model?

Words of caution may help in presenting GEM to the user and to the public. It is important to state that GEM has acceptable accuracy in predicting the fuel efficiency of a specific vehicle under specific circumstances. However, it is equally important to state that if GEM is used to compare two competing, but very different, technology packages, it may not have the fidelity or granularity to evaluate which is better. GEM may not determine the relative difference between the two with high fidelity, and that relative difference will depend on the vehicle vocation or test cycle used.

Although modeling test weights were provided for the example vehicles, there was no quantitative discussion of choice of test weight for GEM. Test weights receive only brief mention in the supporting documentation. It is possible that within vehicle classes, or across regions with different topography, engine size may be selected based on the anticipated load. The distance based strategy shows an appreciation for this issue, but some compensation with test weight for engine size could be considered. Perhaps test weights could be selected so that the time to complete the route remains wit hin reasonable bounds for more lightly powered vehicles, but at least that highly powered vehicles are acknowledged to be appropriate for some occupations, loads or regions. The vocational tractor option in Phase I is not a comprehensive

solution.

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- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

III. SPECIFIC OBSERVATIONS

Specific Observations on T ool D escription E ntitled, “Vehicle Simulation Model” Page Paragraph Comment or Question

8 1 Axle lookup table is a better approach

8 2 “Brakes” Addition of the inertia component to axle is curious/ a curious description. This is rather a retarding torque. Perhaps the inertia becomes a force if MATLAB is viewed over time steps. I was confused by this language.

10 2 It would be good to see (as well) the equivalent to Figure 1

- 3 with the proposed locked shifting strategies in GEM, rather than actual strategies as discussed on p. 10.

16 2 Need to be cautious about claims in modeling changes. Effect of change in Crr is clear, bur GEM may have difficulty with relative accuracy in changing transmission type

. 16 2 Note in presenting these agreements that Crr or Cd changes are entered as dynamometer A -B- C coefficients, and these are not real world measurements. Essentially the dynamometer is partially modeling these effects.

17 Table 1

- 3 And the figure. Note that the 1.8% error represents a 17% error based on the difference, if this figure is intended to show the accuracy of predicting differences rather than absolutes.

18 2 GEM is using automated shifting, essentially, for both MT and A MT, and this will be used (with PI control pedal) for impact assessment. Yet this paragraph brings human drivers to the fore. Philosophically, that the human drivers are the truth and the accuracy of revenue service, more than the model or powertrain cell.

19 Fig 1

- 9 to 1

­ 13 Are these with default or manufacturer’s shift tables?

22 Table 1

- 4 Little or no shifting occurs in the 55 and 65 cycles. That should be

stated.

23 End of page Text should explain in a little more detail how these powertrain tests may be inserted into GEM

Specific Observations on E lectronic M odel E ntitled

, “GEM Tool” Input Variable Comment or Question No Specific Comments or Observations Provided.

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Peer Reviewer # 2

92External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation



### Peer Review Comments on EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

I. GENERAL IMPRESSIONS

This document summarizes the findings of the review of the US EPA's Heavy- Duty Greenhouse Gas Emission Model (Phase 2 GEM) and supporting documen tation ("VehicleSimulation Model"). The tool will serve as the principal support for the second round of HeavyDuty GHG emissions regulations, which are under development by NHTSA and EPA. The agencies are considering recognizing the efficiency of variou s vehicle, engine, and transmission technologies and they consider critical to develop methods that assess the expected real world performance of those technologies. The main purpose of this review is to evaluate how well the developed model can serve as a regulatory and compliance tool. The following represent my review of the tool and accompanying report based on my experience in modeling heavy-duty

vehicles with full

- vehicle simulation tools, as well as from our assessment at the International Council on Clean Transportation (ICCT) of other heavy-duty vehicle regulatory models used

around the world.

After reviewing the Matlab/Simulink model and the accompanying report, my general impression is that the "Phase 2 GEM" constitutes a valuable development effort by EPA to develop a rigorous tool that represents the relative efficiency and emissions of vehicles. The new modeling tools’ comprehensiveness, quality and amount of data inputs, and modeling structure

reflect state -of-the-art modeling techniques an d accurately represent relative efficiency

differences of vehicles in real -world conditions.

The model architecture is clear and easy to follow and has incorporated some key features that will enhance its overall accuracy with respect to real world perfor mance of technologies, and

will allow the model to capture fuel consumption reductions from a broader range of technologies. Overall, the tool offers a rigorous and comprehensive simulation accounting of both engine- specific and full

- vehicle effects in a m anner that is suitable for the regulatory compliance purposes as indicated. The model will be capable of performing its intended purpose of reflecting technology benefits for compliance purposes of most of the technologies that the agencies are considering

.

Some new vehicle modeling features are especially important, namely the ability of the model to incorporate user

- defined engine fueling maps and driveline parameters, the development of different transmission options, the enhanced transmission gear-shif ting strategy, the inclusion of

a distance -based routes with road grade, and the more comprehensive treatment of vocational truck technologies. The accompanying testing effort that was undertaken to validate the model is impressive and thorough, as capturing the effect of combinations of technologies in such close agreement with powertrain and chassis dynamometer testing is a difficult task. The model development demonstrates a thorough development process, and also shows a strong

commitment to transparently presenting the data and methodology that were involved.

The comments below provide additional details, as well as some suggestions that could also be considered by the agencies in the final model development.

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Although the tool itself offers a suitable modeling platform, the document that describes modeling approach could provide further details in a number of areas. It appears as though the documentation available for this peer review was at an early draft stage. There is an overall lack

of detail on k ey technical features that are new in the model. Interested readers would gain from better descriptions of such features, how they were developed, and perhaps, more quantitative results in several areas. Also, the quality of the report may be enhanced with more consistent use of terminology and a reduction in the number of self- references. Further details regarding areas where such documentation and enhanced information would be helpful are described below.

II. RESPONSE TO CHARGE QUESTIONS

1. Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or issues that were not discussed or addressed by the GEM tool or its component sections?

The proposed Phase 2 standards are predicated on the performance of a broader range of technological improvements than Phase 1, including changes to transmissions and better integration of engi nes and transmissions, so a more comprehensive model is required. The model

in its current form will be capable of performing its intended purpose of reflecting technology benefits for compliance purposes of most of the technologies that the agencies are considering.

The model is enhanced in various aspects with respect to its previous Phase 1 version. Fuel maps are one of the most important elements in simulation -based models and the new feature of using actual maps and drivetrain parameters would make t he results more realistic, allow the model to capture the effects of matching engine and driveline, and ideally promote right sizing of the engines to application. Different transmission options are included in the model. The shifting behavior is now more realistic since is based on both throttle and speed inputs, and includes the effects of a clutch friction model. Phase 1 GEM shifting strategy was based only on vehicle speed and there was no torque interruption during shifting. Road grade has a major impact on fuel consumption and its addition to the tests cycles would also make the results more realistic.

The treatment of vocational technologies, which were limited to the tires in Phase 1, is considerably enhanced. The approach followed by EPA to tackle t he diversity of vocational truck applications is appropriate. A few drive cycles are simulated (ARB transient, 55 mph and 65 mph cruise with grade, and a new idle cycle) and weighted differently based on specific application.

EPA’s approach involved a good amount of testing and validation. It must be said that most of these validation efforts only covered fuel consumption results from reduced weight, betteraerodynamics, and better tires. The validation effort for transmission types and enginetransmissio n- vehicle interaction was less comprehensive

. However, based on the results presented, Phase 2 GEM model would be accurate enough to support regulation and drive technology adoption.

More broadly, I make one final comment on how the overall modeling approach may meet EPA’s overall goals for the regulation, related to the public release of the GEM input and output

data. The existing and Phase 2 heavy -duty vehicle regulation approach relies on the GEM inputs and outputs to determine compliance. The GEM data are analogous to the light-duty vehicle

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gram/mile 1 , heavy

- duty vehicle gram/brake

- horsepower 2 , and light- duty vehicle mile

- per

gallon 3 compliance values. For the heavy-duty use of the GEM in the greenhouse gas emission regulatory program to meet the agency’s own standard, the input and output data from GEM would ideally be made publicly available just as the regulatory data for the other regulations for each engine and vehicle. For the public to have confidence in the regulatory program that is built on a mix of engine- and vehicle -model-specific inputs and modeled GEM outputs, the underlying

data would b e p re sen te d in ful l in do wnl oadab le da ta file s (e. g., in Exc el ) as in other EP A

r eg ul a tio ns.

References :

1 EPA http://www.epa.gov/otaq/crttst.htm

2 EPA http://www.epa.gov/otaq/certdata.htm

3 EPA http://www.epa.gov/otaq/tcldata.htm, http://www.fueleconomy.gov/feg/download.shtml

2. Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following:

a) Elements in each system used to describe different vehicle categories; b) Performance of each component model including the reviewer ’s assessment of the underlying equations and/or physical principles coded into that component; c) Input and output structures and how they interact with the model to obtain the expected result, i.e., fuel consumption and CO2 over the given driving cycles; d) D efault values used for the input file, as shown in “Vehicle Simulation Model” document.

Overall the model structure and its systems are appropriate and, in large part, complete. Generally, the performance of each component model and the underlying equations and physical principles are valid throughout (see some finer details below). The input and output structuresinteract with the model to obtain the expected result in a way that is sound. The following subsection s comment on specific issues regarding model structure, individual systems, as well as default values, in no particular order of importance.

Fixed payloads Phase 1 GEM had predefined engines, driveline parameters, and payloads for every category. An issue that may arise when using user -defined engine fueling maps in combination with predefined payloads is that some simulated vehicles, with lower power- to

- weight ratios, will show higher deviations from the target speed- distance trace. This affects the simulation results

since these u nderpowered vehicles will take more time to complete the assigned route and will show a lower average speed. This could lead to underpowered vehicles being improperly

credited.

Appropriate matching of engine , transmission gear ratios, axle ratios , and tir e radius is only going to be promoted if the GEM payloads closely match actual vehicle operation. Right sizing of powertrains to application does not seem to be promoted when payloads are predefined for a particular vehicle category. In order to recognize engine power matching to vehicle road load, payload needs to be a user input rather than a predefined parameter. The regulatory approach and modeling would ideally recognize and promote market diversity and identify potential discrepancies between actual p ayloads and GEM payloads. There is an existing trend towards

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smaller engines, but also some applications require larger engines. On the other hand, if the truck manufacturer is allowed to input vehicle- specific payloads, some issues may arise in terms of

e nforceability (How do the regulatory agencies ensure that the vehicles are operated close to the payload values at which they were certified?), that may also open the door for the manufacturers to report numbers for their own benefit, and adds complexity.

An option could be to adjust the payload on a few pre-defined bins based on certain parameters

that are indicative of vehicle road load (e.g. engine displacement, engine power, final drive ratio). Under this option, a performance criterion that captures the trace- following capabilities of the simulated truck ( e.g. a set threshold of percent difference between target speed and simulated speed) can be used to force certain engine- vehicle combinations to switch to a lower payload bin if they don’t follow the trace according to the specified criterion. Another option would be to impose a CO2 penalty based on the ratio of simulated average speed to target average speed. Ideally, the allowed deviations from the target trace should be minimized for the simulations to be considered valid and allow comparisons between them.

Drop -down technologies The agencies have identified a list of technologies that provide fuel consumption benefits but are

d ifficult to simulate accurately. They are developing feature -based drop-down menus that make

post- simulation adjustments ( percent reductions) to the results. It appears that manufacturers have not taken much advantage of the Phase 1 advanced technology str ucture to earn credits so it is important to try to include most of the technologies in some way. However, drop-down menus inherently assume that all the technology variants within a technology category provide the same

fuel consumption benefits. Not all t he models and brands of a certain technology feature would provide the same fuel consumption benefits. There is the risk of giving artificial credits to products that perform at a lower level than the value that is selected from the drop - down menu,

thus r ewarding poor performers

. Also , technology products with better than average levels of performance would not get additional credits, which is a disincentive to make investments in the development of such technologies. The default improvement values (percent reductions) developed by the agencies were not shared for this peer review but they are of relevance and need to be determined with care. Currently, the users have no flexibility to enter their own values. Giving the users the flexibility to enter their own values (after testing and with proper documentation) could offer a way to reward good performers.

It seems that applying adjustment factors in terms of percent reductions rather than applying predefined credits in units of go 2/ton- mile or gal/ton

- mile may punish good performers. Assuming that truck A emits 90 go 2/ton- mile and truck B emits 100 gCO2/ton

- mile. If a certain technology improvement value is set at 5%, and both trucks use such technology, truck A would get 4.5 gCO2/ton- mile credit and truck B would get 5 gCO2/ton-mile credit. This discrepancy of

incentives can exacerbate if the trucks use more than one drop- down technology and the agencies

decide that the percent improvements are additive. So it would be good for the agencies to support wheth er and why percentage

- based (versus gCO2/ton

- mile based) are most appropriate.

Also the agencies might address, in such drop- down menus whether such technology improvements are indeed additive or not. Another issue with drop-down technologies is that there is the potential for double counting of technology benefits. As an example, an electric coolant pump is listed as a drop -down technology. Depending on the engine mapping process, the resultant engine fuel map may already capture the benefits from that technology. Running a simulation with such a map, and

96External Peer Review of EPA’s Heavy

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later improving the results using a drop-down menu will double count the benefits. If EPA could respond to how potential double- counting situations are minimal, t hat would be helpful.

Driver subsystem In vehicle simulation modeling, it would seem that the driver ideally would be excluded entirely as a factor that could influence the GEM regulatory compliance results. Using the same driver

model for all the vehicle s seems to be an appropriate choice. However , additional documentation

is needed for this subsystem. There are no details about how the proportional and integral gains of the PI controller have been selected. Are they representative of current drivers? Are they tuned

to enhance the trace

- following capabilities of the model? The look- ahead feature also lacks documentation. Is it bringing any advantage to the trace- following capabilities of the model? How was the time span value for such feature selected? Id eally EPA would provide some consideration and discussion of such factors to provide greater assurance that no anomalies occur in compliance results from company

- to

- company technology strategies as well as tested -versusreal

- world results for the relative technology benefits.

Transmission subsystem

There are some transmission

- related features that are confusing and need to be clarified. The report mentions that the different transmission models: manual (MT), automated manual (AMT), and torque converter automatic (AT) are built of similar components, but each features a unique control algorithm

. However, the model seems to use the same "auto shift algorithm" to determine the operating gear for any transmission type. The differences in the control algorithm o f the three different transmissions are not clear and need to be provided. Since transmissions are an important new addition for Phase 2 GEM, it is important to let the reader know that the control strategy (e.g. shift points) or the selection of predefined transmission parameters (e.g.

efficiencies and inertias at different gears) are not creating any artificial advantage of one technology type over the others. I suggest presenting a comparison of the same simulated truck with different transmission types . It is also important to highlight in the report that the new transmission controller is based on both speed and throttle position, and differs from the Phase 1 transmission controller, which was solely based on vehicle speed. The rule-based approach of the "auto shift algorithm" would ideally be documented.

It would be appropriate for the agencies to acknowledge that Phase 2 GEM simulations can capture some but not all of the benefits of powertrain integration. The simulation would adequately capture engine down speeding since the users have to input specific transmission gear ratios, final drive ratio, and tire radius. However, there are many complexities in the control strategy when it comes to integrating engine and transmission. Integrated engine

- tran smission powertrain approaches with advanced controls and shifting algorithms that many companies are developing could result in significantly more (or less) benefit than the agencies determine as the Appropriate default emission

- reduction effect.

As an e xample, if two different vehicles have the same driveline parameters (tire radius, final drive ratio, transmission gear ratios, transmission inertias, and transmission efficiencies) and AMT transmissions from different manufacturers, they will obtain the same simulation results in GEM but, due to differing control strategies and other design characteristics, they will show different fuel consumption benefits in reality. It cannot be expected that all the AMT

transmissions bring the same fuel consumption benefits. The drop- down menu option won't

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handle these differences unless there is an option to choose manufacturer

- specific transmissions or otherwise input such data.

As a result, there is an opportunity here to leverage the powertrain testing and provide the option for manufacturers to better capture the fuel efficiency gains coming from the control strategies and other complexities that are not adequately captured in GEM. Another advantage of powertrain testing is that the manufacturers would not need to disclose confidential information. The results from powertrain testing can then be implemented as correction factors for the GEM results. Using correction factors, GEM results could be multiplied by a fixed percent improvement obtained by comparing the results of powertrain test and GEM simulations under the same torque- speed trace. 4 The default benefits for transmission improvements would ideall y be set to be appropriately conservative (i.e., lowest expected value based on various industry

results ) in GEM

. The drop -down menu could still then be offered as a default, for the

manufacturers that decide not to use the powertrain testing. Then, for the powertrain option, companies would ideally be provided clear testing procedures and guidance to demonstrate the

emission -reduction impact of their advanced powertrain approaches with physical vehicle testing

in simulated real

- world conditions.

Engine fueling maps

The inclusion of manufacturer- specific engine maps is a critical feature to reflect company

differ ences and detailed engine

- specific characteristics that reflect real -world fuel consumption and emissions. This is an important addition to GEM, but there is lack of documentation of the engine mapping procedure. I imagine that a fairly prescriptive proced ure (including number of points, preconditioning and warming procedures, fuel properties, etc.) is described somewhere else in the larger regulatory development document but this chapter would ideally include a brief description of the procedure so the reader knows which engine accessories are included or excluded during the engine mapping procedure.

It is noted that there are many advanced features that may affect fueling but are not captured by using a steady

- state fuel map

. Manufacturers are going away from traditional map

- based strategies and are going towards model-based controls. Diverse thermal management strategies are utilized, and some engines use dual torque curves. Have the agencies considered how to handle these technologies? This could have im portant implications for how tested steady

- state engine maps, and GEM modeling, and real- world emissions characteristics could differ. As a result, we recommend that the agencies discuss such industry approaches in the rulemaking and investigate ways to en sure that tested results are aligned with real

- world engine and vehicle operation the results in fuel consumption and emissions.

The approach used to quantify the transient correction factor (run GEM with the engine map, then use the torque-speed points i n the engine dynamometer and compare measured versus simulated results) is appropriate. Ideally the transient correction factor may be obtained for each individual engine. However, since there is a need for selection of a vehicle in GEM in order to get the torque-speed trace. It would become a hard task for the agencies to try and run a transient

correction factor for each vehicle -engine configuration. For practicality, I recommend provisionally using a single correction factor and maintaining the option to refine it over the years with additional testing.

Modeling of idle cycle

98External Peer Review of EPA’s Heavy

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The idle cycle modeling would gain from increased documentation. Using a gCO2/mile value for an idle cycle at first seems counterintuitive (i.e., there are no miles traveled) so a complete description of the calculation method would clarify

. It would be desirable to present some validation results for the idle cycle modeled in GEM compared to experimental results. Some of the engine auxiliaries may not be enabled while doing the test, and the map could be underestimating actual idle speed fueling rates. There are also engine thermal management strategies that are used to keep appropriate after treatment system temperatures

. These strategies vary from manufacturer to manufacturer and could increase idle fueling substantially.

The "trace following" issue discussed above also has implications in the calculation of idle cycle g/mile value. For this calculation the fuel rate in units of grams per hour [g/h] is converted to

units of grams per mile [g/mile] using the weighted average speed over the three non- idle c ycles. The target speed is used for this calculation and not the actual simulated speed, which may penalize smaller engines. I suggest EPA to consider if this issue might be significant.

Trailers Although there is a parameter in GEM for trailer tires' rolling resistance, it is not clear howtrailer aerodynamics is going to be modeled in GEM. Trailer aerodynamics can bring about twothirds of tractor- trailer aerodynamic benefits, so this is a critical area that requires documentation and specification of the procedures for the vetting, binning, and including the input data. My understanding is that the Coda input parameter is for the tractor only (mid-roof and low roof tractors are tested in its bobtail configuration), or for the tractor using a "reference" 53-ft dry van trailer (for high

- roof tractors coast -down test ). Trailer aerodynamic devices can reduce the

overall tractor

- trailer combination aerodynamic drag and ideally the Coda used in simulation

should represent the combination. It seems that there is no current provision to include the effect

of trailer aerodynamics as an input in GEM. The report needs to clarify how the GEM model is handling trailer parameters (including aerodynamics, tires rolling resistance, and weight reduction) and if the model is going to use a predefined "reference" trailer for all the tractors. Ideally agencies would give credit to tractor -trailer integrated designs although it would be difficult for the agencies to ensure in- use compliance of matching of tractors and trailers.

Accessories There are opportunities for fuel savings from mechanical accessories and electric accessories but the agencies decided to keep with the Phase 1 approach of having pre-defined and not customizable power from accessories. If these parameters ar e assigned default values, there are

no incentives to implement new technologies that could have greater impact. Allowing

accessories power consumption to be user -defined inputs can be used to promote developments in technologies that reduce the power requirements of accessories such as the alternator, air

conditioning compressor, power steering pump, or cooling fan. There are other opportunities for engine accessories such as oil, coolant, and fuel pumps, but is not clear at this point if all those

sav ings are going to be captured by the engine mapping process.

References:

4 Se e Sha rpe
, De lgado, M unc ri ef ( 2015 ) Co m pa ra ti ve assess m en t of heav y- du ty veh icle

r egu lator y des ign op ti on s for U.S. gr eenhou se ga s an d e ffi ci enc y regula ti on

. h tt p :// www .t he i cc t. org/ us

- phase2

- hdv - r egula ti on

- des ign- op ti on s 3. When using the standard of good engineering judgment, is the program execution optimized by the chosen methodologies?

99External Peer Review of EPA’s Heavy

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The chosen methods and execution of the model shows strong engineering judgment throughout. A good indication of proper execution is the overall good agreement between the Phase 2 GEM simulations and testing data obtained with chassis and power train dynamometers. Th e errors shown are well within +/-5%, which is within the test- to

- test variability of chassis dynamometer testing. Execution at this level of fidelity meets our own criteria that we have utilized to validate

tractor

- trailer simulation results. 5 the validat ion results show that the balance between model accuracy and simplicity is adequate. As a result, the program would be effective to model a diverse set of technology changes and be used in regulatory applications.

References:

5 See Delgado and Lutsey (201 5). Advanced tractor

- trailer efficiency technology potential in the

2020-2030 timeframe http://www.theicct.org/us

- tractor

- trailer

- efficiency -technology

4. Please comment on th e clarity, completeness and accuracy of the intended output/results (CO2 emissions or fuel efficiency output file).

The data reports did not appear to be fully complete, but the accuracy of the output/results appears to meet reasonable expectations. The input and output structure of GEM was not
finalized when released for peer review, however some samples of the output files were provided to give the reviewer a flavor of the potential structure. In my opinion, for completeness, the output file needs to include results for each different cycle and not only for the weighted aggregation of cycles. Some metrics can be added to the output file to facilitate troubleshooting and give the user a better perspective. As mentioned before, actual simulated speeds an d a

measure of deviation from the speed

- distance trace would ideally also be provided for transparency of the results. Based on the validation results, accuracy with respect to measured data was provided and seems to be within 5%, which is acceptable output accuracy based on comparable modeling as well as real

- world testing.

5. In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? Any recommendations for specific improvements to the functioning of the outputs of the model?

Phase 2 GEM could generate two different output reports. One that only includes the most relevant information on an aggregated format and is used only for compliance purposes, and a second one, that is very detailed and includes results disaggregated by cycle and other relevant information that may help the users to troubleshoot their results, learn the inner workings of the model and potentially suggests enhancements to it. I suggest including a summary of the energy audit in the output. Also, provide the average engine efficiency over the cycle for the different test cycles, as well as the ratio of average engine efficiency to maximum engine efficiency, which is an indication of how well the transmission parameters are matched to keep the engine operating near its peak efficiency range.

The output file provides some basic “sanity checks” such as number of shifts, ratio of number of shifts to number of gears in the transmission, distance traveled, and ratio of actual time to target time. Please also provide ranges of valid or acceptable values for these parameters so the user can be aware of any potential issues with the simulation.

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A further step that could allow the tool to be much more useful would be to allow users to input their own cycles as is currently done with VECTO 6 (Vehicle Energy Consumption calculation Tool) model in Europe. The VECTO tool has a “declaration mode” for compliance, and an “engineering mode” which offers the ability to edit inputs and allow users to explore what the tool can do. This would be critical for transparency and follow the best practice as seen in the Europe situation. It would also be highly useful for individuals in the heavy-duty vehicle supply

chain to explore the variation of the resul ts with respect to real

- world duty cycle factors. Especially considering the very diverse use of heavy -duty vehicles in local, regional, and longdistance conditions, this capability would allow dealers and fleet managers to gauge how fuel consumptions fo r particular relevant driving patterns differs from the cycle. This would help ensure the technologies that are more suited to particular duty cycles are being selected in the market place, and it would also help overcome the prevailing market barrier, whe reby knowledge, data, and confidence on truck efficiency has been limited. 7

References:

6 See Luz et al (2014) http://ec.europa.eu/clima/policies/transport/vehicles/heavy/docs/final_report_co2_hdv_en.pdf

7 Se e Roe th et al ( 2015 ) h tt p :// www .t he i cc t. org/ hdv -t echno l ogy -ma rk et- ba rri ers- no rt h-ame ri ca

III. SPECIFIC OBSERVATIONS

Specific Observations on T ool D escription E ntitled, “Vehicle Simulation Model” Page Paragraph Comment or Question

2 2 Th e li s t o f k e y te chn i ca l fe a ture s m a y i nc l u d e t h e f ac t t ha t t h e n e w model uses dist anc e- ba sed cyc le s ins te ad of ti me- ba sed cyc le s,

an d t h e f ac t t ha t te s t cyc le s n o w i nc l u d e ro a d g r ad e

. 2 2 The claim "more stable engine idle speed controller" is not discussed in the text. Some metric or quantification of what is meant by "more

stable" needs to be provided.

2 3 Regarding “substantial effort has been put forth to accurately track and audit power flows through the model to ensure conservation of energy" The report lack details about the energy audit. Was the energy audit developed just for int ernal quality control or is it going to be provided to the end users in an output file?

3 1 R eg a rdi n g " t h e ro a d g r ad ie n t ha s b ee n m odifie d t o acc e p t a ro a d grade t hat va rie s as a fu nc tio n of dist anc e tr av ele d" P le ase in tro duce the co nc ept of dist anc e- ba sed versus any pros/cons of the new method and why did you change the approach.

3 2 Driver subsystem. This section (1.2.2.2) is not clear to the reader and, in my opinion, needs rewriting. There are various confusing

statements such as "the feed forward calculations using drive cycle

accelerations and vehicle mass have been removed". The section also mentions (page 4, paragraph 1) that a ratio of speeds (which is nondimensional ) is integrated to produce the current cycle position (which has units of distance) , which is dimensionally incorrect. I

recommend showing the equations to avoid confusing the reader.

101External Peer Review of EPA’s Heavy

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Specific Observations on T ool D escription E ntitled, “Vehicle Simulation Model” Page Paragraph Comment or Question Regarding the statement "the addition of distance compensation allows all simulated vehicles to complete an equivalent trip such as traveling from point A to point B" Does that mean that without distance compensation the vehicles would not complete the trip?

3 2 Ho w w er e t h e p ro p ortio na l an d i n tegr a l c o n s t an t s o f t h e P I

con troller es ti ma ted ? Is the same dri ver subsys te m used indepen de n tl y of tr an smi ss io n choice ? Ho w wa s the look- ah ead

fee d

- for wa r d c o n tro l i m p le m e n ted ?

4 2 Co n s ide r removing the m e n tio n to t h e " va ri an t power train

a r ch ite c t u re " s i n c e i t i s n o t m e n tio n e d anywh er e el s e i n t h e re p ort

. 5 1 P le a s e c l a rif y t ha t t h e e n gi n e m a p i s n o t a p r e

- d eter m i n e d

pa r a m ete r a s i n Pha s e 1 G E M

, b ut a u s er

- d efi n e d i np ut.

5 3 F o r c o n s i s te nc y w it h p re v io us s e c tio n
, p le a s e s h o w t h e p ro p o s e d

c o n s t an t p o w e r lo s s m a g n it u d e o f ele c tri c s u b s y s te m

. 5 4 Please change "four different variants” for "three different variants” (MT, AMT, AT).

11 Th er e i s a n appa re n t i nc o n gr u e nc e i n Pa g e 5

, pa r a gr ap h 4

, wh i c h

men tio ns t ha t e ac h tr an sm i ss io n " fe a ture s a un iqu e con tro l

a lgorit hm mat ch ing be hav iors obs er ved du ri ng vehicl e te s ti ng "

howev er , in Pag e 5, pa r ag r ap h 5 it is men tio ned t ha t "all of the

tr an sm i ss io n mod el s us e an auto sh if t a lgorit hm to deter mine the

op er a ti ng gear over the cyc le ". Are the auto sh ift a lgorit hm

pa ram eter s chan ged ba sed on tr an sm i ss io n t yp e? I s there really a unique control a lgorit h m fo r e ac h tr an sm i ss io n t yp e ?

5 5 Th e " a u t o s h ifti n g o p ti m i z er " n eed s p ro p e r d o c u m e n t a tio n

. Ho w doe s i t w or k ?

6 1 Th e c l u t c h m ode l i s a k e y n e w a dditio n an d l ack s p ro p e r documenta tio n.

P le ase su pp ort claims such as " re a li s ti c ac tu a tio n dura tio ns an d

more acc ur ate phy sics of tor qu e cons er va tio n an d lo ck up b e hav ior " w it h d a t a

. 6 2 P le a s e c l a rif y wha t y o u m e a n b y “This l ay o ut i s m or e s i m il a r t o a

m an ua l tr an sm i ss io n, but the app li ca tio n for a pl an et ary gearbox

is a re aso nab l e approximation as thi s t yp e of gearbox ca n utili ze a

va riet y o f to p olo g ie s " i s c o n f u s i n g t o m e

. 8 2 Th e s t a te m e n t " Th e b r ak e m o d e l a l s o add s a rot a tio na l i n erti a

componen t to the ax le " is mis le ad ing si nc e the in erti a of br ak es is

s e t t o z er o i n G E M

. 9 2 P le a s e p ro v id e a t ab l e w it h a c o m p let e li s t o f p re

- d efi n e d an d

us er -d efi ne d pa ram eter s. Th er e is no n ee d fo r spec ifi c va lues, just

t h e li s t o f pa r a me ter s

. 12 1 De s c ri p tio n o f te s t c o n ditio n n u m b e r 6 re a d s
, "Run a n e w s e t o f

ro ad lo ad c oeffi c ie nts to re p re sent a vehicle con fi g ur a tio n

o p ti m i z e d fo r fue l effi c ie nc y fo r e ac h v e h i c l e t ha t wa s tested

. "

102External Peer Review of EPA’s Heavy

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Specific Observations on T ool D escription E ntitled, “Vehicle Simulation Model” Page Paragraph Comment or Question

T o b e c o n s i s te n t w it h t h e ot h e r te s t c o nd itio n s d e sc ri b e d p le a s e

qu an tif y th e red uc tio ns in rolli ng re sist anc e, a erod yna mic dr ag, an d

m a s s fo r t h i s pa rti c u l a r " o p ti m i z ed packa ge " ca s e

. 13 Figure 1

- 3 to

1-6 I n t h e lege n d

, i t i s n o t c le a r i f t h e 55 m p h an d 6 5 m p h te s t s contai n gr ad e or not. Also, the " utilit y" cyc le is not desc ri bed in

t h e text

. 15 Figure 1

- 6 A lt h o u g h is m e n tio n e d in t h e te x t

, i t s ee m s t ha t t h e ref u s e tr u c k

wa s no t te s te d u nd er the refu se cyc le . Also, it s ee ms t ha t it was

not te s te d u nd er d iffere nt te st co nd itio n s as the re maining

v e h i c le s

. An y re a s o n fo r t h i s ? P le a s e e xp l a i n. 16 1 C han g e " n u m eri ca ll y " fo r " n u m eri ca l.”

18 2 Th e s t a te m e n t " I n s o m e ca s e s
, i t i s ha r d t o q u an tif y wh i c h m et h od

, vehicl e simula tio n o r c ha ss is dyna mom ete r te st, i s more acc ur a te "

i s v er y mis le ad i ng

. Th e cha ss i s dyna mom ete r test a lt h ou gh imp erfe ct, is a meas ure men t and it was tre a te d as a " true " va lu e in the va lid a tio n p ro cess (F ig u re s 1-3, 1-5, an d 1-6). Acc ur ac y ca n only be meas ure d in refere nc e t o a tr ue va lue. Th e cha ss is

d yna mom ete r te st was s ele c te d as such an d the model cann ot
h o p e to hav e b ette r acc u r ac y t ha n t h e te s t

. 18 3 I n t h e s t a te m e n t " G E M is capab l e of cap turi n g the i m pac t on t h e

tot a l vehicle CO 2 emi ss io ns an d fuel consump tio n due to an y

te chn olo gy imp ro vement" the w or d " any " is mis le ad ing si nc e the

va lid a tio n effor t wa s only done over a ero dyna mic, rolling

re sist anc e an d mass pa ram eter s. Moreov er
, there is c ert ainl y a set
of te chn olog ie s that GEM is i ncapab l e of mod el

.

17 Table 1

- 3 Corre c t t h e n u m b er s o n t h e " Delt a " c ol u m n

. D ue t o ro u n d i n g i t i s

not eviden t t ha t the column re p re sents the d iffere nc e b et w ee n the

two p re vious columns. For e xa mple in th e fo u rt h ro w we hav e 3.9% - 4.9% = -0.9%. In the same Tab le , p le ase ca lculate the

rel a ti ve error (consis te n t with Figure 1-8). Is this rel a ti v e error

more relevant than the “delt a”? W ha t is th e m ax imum acc ept ab le

rel a ti ve error ?

22 P le a s e a d d a t ab l e t ha t s u mm a ri z e s t h e te chn olo g ie s cap ture d b y the simula tio n a n d th e technologies t ha t are no t cap ture d but ar e accounted for via drop -down menus . A th ir d (o p tio na l) column may i nc lude te chn olog ie s t ha t c urre n tl y are not eit her sim ul a te d,

nor re co gn ize d by drop-down menus but poten ti a ll y may be

i nc lu d e d i n futu re regul a tio n s

. 22 Section

1.4.1.1 R eg a rdi n g " A s d e s c ri b e d i n C hap te r 1

. 2

. 2

, o n e o f t h e m a jo r chang es i n th e H D Pha se 2 v er s io n o f GEM is t o a llo w

m an uf ac turer s to en te r th ei r tr an sm i ss io n gea r numbe r v er sus gea r

ra tio " C hap te r 1.2.2 doe s no t men ti on t ha t f ac t. P le as e ch ec k

t h rou gh ou t t h e re p or t t o av oi d i ss ue s w it h t h e s e s elf

- refere nc e s

.

103External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Specific Observations on T ool D escription E ntitled, “Vehicle Simulation Model” Page Paragraph Comment or Question

23 1 R eg a rdi n g t h e s t a te m e n t " M an u f ac t u rer s a l s o hav e a n o p tio n t o

s ele ct th e t yp e of tr an sm i ss io n, which is eit her m an ual or

automa ti c" It is not c le ar if tr an sm i ss io n t yp e is a req u ire d i np ut

or an op tio na l i np ut. Also, the user should ha ve th re e op tio ns ( AT

, M T

, an d A MT )

, n o t j u s t t w o

. 23 Table 1

- 4 Table heading should mention that the results are from simulations in GEM, not measurements. Also, it is not clear if the 55mph and 65mph cruise contain grade.

23 4 The report mentions that due to lack of data, DCT, DCT with TC and

Allison TC -10 AT transmissions were not validated. That assertion implies that MT, AMT and AT were validated. Since transmission technologies wer e not tested at the same level of detail as road load

reduction technologies, it is important to acknowledge the different

level of validation between transmissions and road-load reduction technologies.

23 Last Paragraph Regarding DCT and other transmissi on types not included in the model, the report says, "The manufacturers still have the options to use powertrain dyno tests to quantify the benefits of these or any other special transmissions". It is not clear if the results of the power train tests are g oing to be used to correct the GEM simulation results or are going to replace the GEM simulation results altogether. Please clarify.

24 1 R eg a rdi n g OE M o v erridi n g t h e ax l e effi c ie nc y i np ut

, " t h e i np ut s would b e d eter mined by using the p re sc ri bed test p ro cedu re ” It is

not c le ar wh ich te st p ro cedur e is th e re p or t referri ng to . P le ase

a d d a refere nc e t o s u c h p ro c ed u re

. 24 Last Paragraph Rolling resistance coefficients are usually expressed in units of kilograms per metric ton (1 t = 1,000 kg). The units used (kg/ton) may imply short ton (1 ton = 2,000 lbs.). Please correct and be consistent throughout the document.

25 1 Th e "R e g io na l ", “M ulti

- p u rp o s e ", and " U r ban " c o m p o s it e duty

c y c le s a r e n o t de s c ri b e d i n t h e d o c u m e n t.

25 3 P le a s e s u pp or t y o ur s t a te m e n t

, " W e c o nc lu d e d t ha t fo r t h e 5 5 m p h

an d 6 5 mph duty cyc le s, GEM's in ter pola tio n of s te ady -state data

t ab le s wa s su fficie n tl y acc urate v er s us the measured results " W ha t

wa s the observed accuracy of using s te ady-stat e maps fo r the 5 5

an d 65 m p h c rui s e cyc le s ? Ho w m u c h acc u r ac y i s s u ffi c ie n t ?

25 3 Th e 55 m p h c r u i s e i s na m e d "u r ba n h ig hwa y w it h ro a d gr a de ", t h e 65 mp h cruise is na med "rural h ig hwa y w it h ro ad gr a de

, an d the

A RB tr an s ie nt cyc le is na med "u r ba n lo ca l ". P le ase tr y to use
consis te nt na mes throu gh out. Also, si nc e the cruise cyc le s in

Pha se 1 w er e ti me- ba sed an d did not i nc lude ro ad gra de , the

Pha se 2 cruise ro u te s (di st anc e- ba sed with gr ad e) are not equi va le nt to them an d using the same na me is mis le ading. I thin k a d i s ti nc tio n ca n b e m ad e b y u s i n g t h e ter m " route " fo r t h e

104External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Specific Observations on T ool D escription E ntitled, “Vehicle Simulation Model” Page Paragraph Comment or Question

d i s t anc e

- ba s e d te s t s an d " cyc le " fo r t h e ti m e

- ba s ed

, o r s i m p l y

na me them " 55 mph c rui se w it h gr ad e" an d "65mph cruise w it h

gr a de ".

29

- 30 Table 1

- 6 &

1-7 A uto m a ti c tr an sm i ss io n s have t h e s a m e effi c ie nc y fo r a l l ge a r s ( 98 %), an d such effi c ie nc y is eq ui va le nt to t ha t o f m an ual an d

au to ma te d m an u al tr an sm i ss io n s in d ire c t drive . Wa s this

advan t ag e observed during testing ? If po ss ib le

, please document

w it h meas ure d da ta showing the ben efit s of AT over MT in ter ms

o f g e a r b o x effi c ie ncy

.

Specific Observations on E lectronic Model E ntitled

, “GEM Tool” Input Variable Comment or Question File: “GEM_run_postproc.m” Lines: 104 to 108. Potential

issue: It seems to me that the equation is not dimensionally correct (I might be wrong). Additive terms should have the same units and the equation seems to be adding gCO2/h terms with gCO2/mile terms. Please check for missing terms and/or appropriate use of parenthesis.

File: “G EM_run_postproc.m” Line: 101. The calculation performed for case 4 is identical to the calculation performed for case 3, making it redundant. Please eliminate case 4 (neutral idle with start/stop), or correct the equation to account for a 90% reduction in neutral idle emissions (not drive idle emissions).

“vehicle.chassis.frontal
_area_m2” The name is misleading

. Please rename to “ drag area ”. Drag area is Coda , aerodynamic drag coefficient is Cd and

frontal area is A. File: “load_GEM_params.m” Lines: 76 to 85. These equations set weight reduction penalties for spark- ignited CNG (525 lbs.), compression-ignited CNG (900 lbs.), and compression-ignited LNG (600 lbs. ). Please set a weight reduction penalty for the missing ca se: spark

- ignited LNG.

File: “load_GEM_params.m ” Line : 94. I am confused

about the variable “vehicle.chassis.mass_dynamic_kg” as defined here is a constant. However , during the simulation (variable: datalog.vehicle.dynamic_mass_kg) the equivalent mass of the rotational components vary depending on the active gear.

F ile : “lo ad_ G E M _pa r a ms

. m ” Li n e s : 11 7 an d 143

. I t i s

not c le ar wha t e xac tl y the va ri able s “tr an sm i ss io n.au to sh ift. cost_m ap ” an d

tr an sm i ss io n.au to sh ift.req u ired _c ost _b en efit _ra tio”

re p re sent, an d ho w are they used in the model. Othe r features such as “re s tri c t s k i p s h ift s ”, re s tri c t s h if t

105External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Specific Observations on E lectronic Model E ntitled

, “GEM Tool” Input Variable Comment or Question

pa rit y ”

, “di s ab l e c o a s t s av i n g do wn s h ift s ” a r e n o t w el l

do c u m e n te d i n t h e

. m file s o r i n t h e re p ort.

F ile : “lo ad_ G E M _pa r a ms

. m ” L i n e : 13 1

. Th e c a l c u l a t i o n of “ Tr an sm i ss io n .ge a r.i n ertia_k gm 2”

i nv olves a multip lic a tio n by 0. Th erefor e it would

p ro duce an a rr ay of z eroe s. Also, a ss uming t ha t the

va lu e of 0 is chang ed to a fi n it e const an t, it s ee m s that

the model is a ss umin g the sam e in erti a va lue fo r all the

d iffere n t g e a r s

. I s t ha t s i m p lifi ca tio n acc ur a te ? File: “load_GEM_params.m” Line: 134. The calculation of “transmission.gear.spin_loss_torque_Nm” involves a division by a factor of 3.73 for all the transmissions that
are not C78_AMT. I am wondering what that factor

represents. Also, if that factor is still valid for a potential
C78_MT transmission. Energy Audit. Net system kinetic energy change is 0 kJ,

which is the result of the test cycle starting and ending at 0 mph speed. The test cycle seems to start and end at the same altitude (symmetric grade profile traveled at constant speed), so one can expect the net system potential energy change to be 0kJ as well. Since both kinet ic and potential energy are conservative and not dissipative forms of

energy, I was confused about the energy audit accounting

for energy “consumed” by gradient at about 17% of the

losses for a tractor -trailer. Checking the equations, it

seems that the ene rgy audit is performed only for positive

tractive loads. If that is the case I am confused about the energy consumed by the brakes at about 7% of the losses

for a tractor -trailer. They should be really low if one is only considering positive tractive loads . The brakes are mostly applied for negative tractive loads (e.g. driving downhill). Am I missing something here? Why the weighted average speed (weighted_avg_speed_mph) used in post processing (file: “GEM_run_postproc.m”) is based on the target speed

d istance trace and not in the actual simulated speed

distance trace? This decision has implications for underpowered vehicles that deviate substantially from the target trace since their actual average speed may differ substantially from the target speed. This also has implications for the calculation of idle fuel rates for

vocational vehicles since the conversion factor from idle fuel rate in [kg/h] to [kg/mile] is the weighted average speed.

106External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

107External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Peer Reviewer # 3

108External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation


### Peer Review Comments on EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

I. GENERAL IMPRESSIONS

The EPA Heavy -Duty Greenhouse Gas Emission Model (GEM) Phase 2 documentation accurately represents the structure, format, logic and algorithmic description of the model as presented. The supporting documentation is for the most part, clear and self-explanatory. The results produced by the GEM model appear to be sound, although each set of results is presen ted as integrated fuel efficiency and carbon dioxide emissions results. As such the results present a single -valued, integrated snap-shot of the model prediction, and the time-based instantaneous fuel efficiency and carbon dioxide emissions predictions are not available for review. The overall dynamic performance of the model prediction is thus difficult to judge in the greater context of what is usually fully transient vehicle operation. Furthermore, in the version reviewed, the ability to vary input param eters and vehicle and drivetrain attributes is limited to modifying input files and not through a graphical user interface as described in the review instructions.

II. RESPONSE TO CHARGE QUESTIONS

1. Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or issues that were not discussed or addressed by the GEM tool or its component sections?

The model appears to meet the stated purpose for which it was intended, which is the prediction of integrated cycle -based vehicle fuel efficiency and carbon dioxide emissions for vehicles with preselected physical and drivetrain attri butes. While this was the subject of some detailed explanation in the model documentation, the assumption of quasi- steady engine fueling and its extension to fully transient engine operation is not without complexity in the assessment of its validity. A further, acknowledged inadequacy of the model in its current form is the limited ability of the user to modify specific vehicle attributes, and component values and efficiencies.

2. Please comment on the appropriateness and completeness of the contents of t he overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following:

a) Elements in each system used to describe different vehicle categories;

The elements in each of the systems (engine, transmission, axle, vehicle attributes etc.) seem appropriate and complete. The specific selection of the engines and transmissions chosen will cover a large portion of the current heavy -duty vehicle fleet, although of cour se any specific, single selection of powertrain hardware or powertrain hardware attributes necessarily limits the range of vehicles that can be simulated with that same selection.

b) Performance of each component model including the reviewer’s assessment of the underlying equations and/or physical principles coded into that component;

109External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

One concern with the structure and form of the model is that a steady- state engine fueling map is used in each case to simulate transient engine operation and hence dynamic veh icle operation. This is in addition to the simulation of operation under nominally steady vehicle speeds or cruise operation. In the case of nominally steady operation, the use of a steady- state fueling map is

well -justified, but the quasi- steady assumptio n required to allow the extension of the use of such a map to transient operation requires additional justification. Heavy duty compression ignition engines have high rotational inertias (due to the relatively high mass components required to survive the high combustion pressures), high mechanical friction (due to high effective compression ratios) and relatively slow air and exhaust transfer processes (due to the excess air flowrates accompanying their lean, un -throttled operation). In addition they have r elatively high thermal mass due to their large physical mass required to withstand the stresses and strains resulting from high combustion pressures. All of these features conspire to result in deleterious combustion effects under highly transient engine o peration. In most cases the end effect of these phenomena is to reduce the engine brake thermal efficiency under transient modes, beyond that which would be expected under steady or quasi-steady fueling operation. In most cases the

additional fuel that is required to undertake a specific engine transient torque trajectory, beyond that estimated using a quasi -steady fueling assumption, would typically be less than 10% of the total integrated fueling, but in most cases the effect on integrated fuel efficiency over transient duty cycles is non-negligible.

In general, incorporating an additional component into the full accounting of the vehicle load by

over- accounting for the actual total rotational inertia (in the form of an effective or “added” mass

or inert ia) of the drivetrain and driveline system does allow for the quasi-steady assumption to hold. However in general a quasi- steady, forward -looking simulation such as is used in this model, tends to under- predict the actual vehicle energy usage under transie nt duty cycle operation. I notice that this issue is addressed in Chapter 1.4.1.8 Transient Adjustment Factor, but the designation of a single correction factor for a specific engine or powertrain configuration is likely to be unsuitable in some cases, and has the potential to cause prediction inconsistencies. Note further that the required correction factor might not be uniquely engine-specific, but might vary for the same engine in different vehicle and powertrain configurations.

c) Input and output structu res and how they interact with the model to obtain the expected result, i.e., fuel consumption and CO2 over the given driving cycles;

A further concern that is not discussed in the documentation is whether any model fitting parameters were employed to ob tain the fits observed, between the GEM- derived fuel efficiency and CO2 emissions values and the dynamometer-measured results. In other words, beyond the parameters described and the accompanying constants used in the dynamic force and energy equations, were any other fitting techniques (or fitting parameters) used to obtain the observed correlations between the simulated cycle

- averaged results and the SwRi chassis dynamometer results? Presumably there were dynamometer parameters and coefficients fitted using vehicle

coast -down data (and dynamometer operational parameters), but beyond these, are there any other fitting parameters used to obtain the correlati ons shown? Discrepancies between simulated and measured results of less than 2-3% are probably not significant, except in the presence of a consistent bias between the measured and predicted, for any one vehicle, cycle or technology

considered.

d) Default va lues used for the input file, as shown in “Vehicle Simulation Model” document.

110External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

The default values as defined in the “Vehicle Simulation Model” are reasonable and currently fall within the ranges of expected vehicle values. It is not clear however under what

circumstances the user will be able or allowed to make modifications in the final model implementation. For instance, it is conceivable that the interplay between future auxiliary mechanical or electrical loads on an engine might be significantly modifi ed through conversion of mechanical auxiliaries to electrical or electronic devices. In that case, that will shift the relative balance in those loads. Moreover it is not clear that engine cooling fan loads have been adequately accounted for in the model, as these are typically not considered in the engine dynamometer testing from which engine fueling maps are normally derived. This exclusion alone can modify observed fueling rates by 10% or more under specific engine operating

conditions.

Other default values including transmission gear ratios, transmission efficiencies, axle efficiencies, tire rolling resistance, and vehicle aerodynamic drag product seem reasonable.

3. When using the standard of good engineering judgment, is the program execution optim ized by the chosen methodologies?

This issue is difficult to address through the level of observation afforded to the reviewer at this stage of development of the model. It is not obvious that the program execution is optimized, but the results, computational time and outputs displayed indicate that the chosen methodologies are suitable for this purpose.

4. Please comment on the clarity, completeness and accuracy of the intended output/results (CO2 emissions or fuel efficiency output file).

The model out puts and results seem clear, complete and accurate. One caveat with interpreting or using the freight efficiency or load efficiency -based results lies in the use, further interpretation or extension of these results. Users might be tempted to “scale” the load -based results in an inappropriate fashion – for example, if the returned result for the computed carbon dioxide emissions is 100 gCO2ptm (grams CO2 per ton- mile) for say a 30 ton vehicle over a specific cycle, there might be the temptation on the part of users to employ that same numerical result to predict the CO2 emissions for the same vehicle loaded to 40 tons over the same cycle. However this assumption is not correct, as the vehicle fuel consumption is a function not just of load or weight

- related terms (rolling resistance, grade, acceleration etc.) but also terms that are invariantwith load or weight (such as aerodynamic drag), and this is not reflected in an emissions per tonmile result.

5. In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? Any recommendations for specific improvements to the functioning of the outputs of the model?

The version reviewed here does not include the graphical user interface (with “pull-down menus”) descri bed in the instructions. The ability to modify input parameters and vehicle attributes will improve the user experience, while obviously presumably not impacting the model

outputs.

111External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Due care and attention should be paid to the number of significant digits presented in the output results. For example, in the results presented from a single specific simulation (shown below):

>> GEM_Phase2_Idle_55_65_CARB_HHDDT_Transient

Distance = 32.414 mi Fuel Consumption = 5.4059 gallons Fuel Consumption = 17184.1217 grams Fuel Economy = 5.996 mpg Fuel Consumption = 530.140 g/mile

CO2 Emission = 1697.77 g/mile

The number of significant digits in the model simulation outputs presented above (some of which are directly related through derivation or calculation) varies from 4 to 9. This does not meet recommended practices in the presentation of results and data. Moreover, industry experience in

the measurement of real

- world fuel efficiency during over the road truck testing dictates that

measured fuel consumption variations of less than 1-2% should not be considered significant or compelling, and this level of variation could correspond to variations in the 2nd or 3rd significant figures in fuel consumption in most cases.

III. SPECIFIC OBSERVATIONS

Specific Observations on T ool D escription E ntitled, “Vehicle Simulation Model” Page Paragraph Comment or Question

1 Use “dynamometer” and not “dyno” Et seq. Use “Phase 2” and not “Phase II”

5 1.2.2.3.1 Use “watts” or “W” and not “Watts”

5 1.2.2.3.1 “ it may o make use” requires clarification

7 1.2.2.3.3.7 “ With the new gear engaged the clutch is reengaged and the engine is again allowed to operate at full load.” This statement presupposes that the transmission was shifting under full engine load, which is not necessarily the case for high power engines under benign operating cycles.

7 1.2.2.3.4 “ This includes drive shafts as well as driven and passive axles, consisting of a differential, brakes and tires.” Passive axles will not ordinarily include a differential, only driven axles will.

8 1.2.2.4 “ The vehicle system consists of the chassis, its mass and forces associated with aerodynamic drag and changes in road grade”. Why “changes in road grade”? Any constant road grade (other than zero) will have an effect on the apparent vehicle load, and not just changes in grade.

9 1.2.2.4 “ computes acceleration [not accelerations] from the input force and equivalent mass which is integrated to generate vehicle speed and

distance traveled”

9 1.2.3.2 Use “Ma tlab” or “MATLAB” and not both.

10 1.3 “ Validations use all actual vehicle variables conducted at Chassis dyno cell,” needs editing.

11 Ref. 3 is not the SwRI report as stated. It is an ASME Technical Paper.

112External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Specific Observations on T ool D escription E ntitled, “Vehicle Simulation Model” Page Paragraph Comment or Question

12 A +

- 15% variation in aerodynamic drag, for example, is unlikely to span the full range of expected values in the future for HD vehicles. Presumably aerodynamic modifications to Class 8 vehicles may result in significantly lower drag coefficients, or drag products (CdA)

13 1.3.2 For the Class 8 T700 tests, at high fuel efficiency, the GEM model appears to consistently under- predict the actual measured vehicle fuel economy. This consistent offset is of concern. The reverse is

observed for the Class 6 truck tests.

20 Fig 1

- 11 Caption is incorrect.

21 Fig 1

- 13 Vertical axis incorrect unit designation.

22 Do not use the term “aero drag”. It should be “aerodynamic drag”.

22 “tire radius” should be “tire rolling radius” or ‘effective radius’.

23 “ Lack of testing data for other types of transmission, GEM would not be able to be validated in time against those three cases” requires editing.

Specific Observations on E lectronic Model E ntitled

, “GEM Tool” Input Variable Comment or Question

-- Audit data for
GEM_Phase2_Idle_55_65_CARB_HHDDT_Transient drive cycle

-­ Aerodynamic drag “Energy Consumed by Cd” should refer to “CdA” and not “Cd”

alone. Engine

Accessories Engine Accessories = 846.16 kJ 0.23% It seems as though engine accessory loads are under

- accounted for in this implementation of the model – a 0.23% loss for a full transient cycle seems inappropriately low. Usable System Energy Provided = 373988.49 kJ

Engine Energy = 309402.35 kJ

Engine Efficiency = 42.08 % This integrated “engine efficiency” is high for the average efficiency expected across a fully transient cycle

– does this refer to the peak engine efficiency encountered?

113External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

Peer Reviewer # 4

114External Peer Review of EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation


### Peer Review Comments on EPA’s Heavy

- Duty Greenhouse Gas Emission Model (GEM): Phase II and Supporting Documentation

I. GENERAL IMPRESSIONS

Accuracy of information:

The document provided, “Vehicle Simulation Model” provides a good background on GEM- II,

its differences from GEM -I, and the Phase I certification process. Section 1.2, “Model Code Description” describes the model components and sub-components, in adequate detail for the user to understand the depth and breadth of GEM- II. No underlying equations are provided. The section on Model validation is an important section for GEM- II. The extent of the validation and the comparisons with dynamometer testing is impressive. This gives the reader additional confidence in the results produced by GEM- II. The validation process is well documented, concluding with the graph that summarizes all the 130 vehicle validations performed. The validation also includes graphs of component performance (engine speed, engine fuel rate, and transmission gear number) as a function of time

The document does not explain the variable target.veh_sytyle. The structure format used for the user input data is useful in collecting all user-provided data.

A final conclusions section is missing in the document provided.

II. RESPONSE TO CHARGE QUESTIONS

1. Please comment on EPA’s overall approach to the stated purpose of the model (meet agencies’ compliance requirements) and whether the particular attributes found in the resulting model embodies that purpose. Were there critical results or issues that were not

discussed or addressed by the GEM tool or its component sections?

EPA’s overall approach to meet the agency’s compliance requirements consists of making a validated simulation model (GEM

– II) available to OEMs so that they can check the compliance

of their vehicle s against the agency’s guidelines. The extensive validation of GEM – II against dynamometer testing of the actual vehicle shows a good correlation between simulation and

hardware to within ±5%. Most validations are well within ±3%. This provides the user w ith a high level of confidence that the physics has been correctly implemented and there are no unresolved “bugs” in GEM- II.

Further, an additional level of confidence is achieved, with select validation from four representative vehicle classes, namely: Class 8 Kenworth T700 truck, the Class 6 Ford F650 tow truck, the Class 6 box truck, and the New Flyer Refuse truck. There is a very good correlation

between GEM -II predicted engine speeds and transmission gear shifting versus the same on the

actual vehicle.

Recommendation: It is recommended that representative vehicles from each of the classes be modeled in GEM-II and validation results presented similar to 1.3.1 of the GEM- II Manual. It is the understanding of the reviewer, based on the provided manual that the following trucks were

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tested on a vehicle chassis: Class 6 Kenworth T270, Class 6 Ford F650, Class 8 Kenworth T700, Class 8 Cascadia Line Haul truck, and Class 8 New Flyer refuse truck.

Issues/Results that were not addressed by GEM

- II:

During this review, the following unaddressed issues were identified for GEM- II:

• GEM

- II includes several PID controllers within its overall structure. For example, the engine idle speed controller of the engine is implemented as a PID with three gains. The

unadd ressed issue in this regard is stability feedback to the user caused by unrealistic hunting for the idle speed. What safe-guards are in place within GEM to inform the user of clutch chattering since GEM does not model second order inertial effects caused

d uring clutch engagement.

• It is possible for the vehicle not to meet the driving cycle as a result of excessive grade or weight or other issues with the transmission/engine. The unaddressed issue in this regard is a feedback alert to the user during the tim e instances when the vehicle is significantly slowed down and does not meet the desired driving cycle. The output file does not alert the user on the number of time instances when vehicle tracking was compromised.

• GEM

- II does not address thermal characteri stics of the engine cooling system or the heat rejection of the transmission fluids. These thermal issues affect the operational duty

- cycle of the engine fan, which will affect the fuel economy. At present, GEM-II models the parasitic loads as a constant average number. Recommendation: Allow the user the ability to introduce an engine load dependent mechanical accessory curve which is more realistic than a constant average number. A simple heat model may be used to capture the effect of thermal characteristics of the multiple radiators in a typical MD and HD engine.

• Although GEM-II does not model tire slip/lockup during a hard deceleration, the effect of ignoring this on fuel economy is negligible.

• The validation results included kinematic comparisons (speeds, gear number) between

GEM

- II and the actual vehicle on a chassis dynamometer. While, the kinematic comparisons look very favorable, the dynamic comparisons (engine load and engine fueling) are missing in the results section of GEM

- II.

• The transmission shift strategy can affect fuel economy and emissions. GEM

- II allowsthe user to preselect different transmission types (manual, automatic or automatedmanual). However, it was not clear how to modify the GEM- II default shift strategy with an OEM proprietar y shift strategy.

• Although GEM- II results have been extensively validated against dynamometer test data in a controlled lab environment, it is unclear how well GEM- II will compare against real world road testing, especially with temperature fluctuations. F or example, the lack of a thermal model in the engine model may cause GEM -II results to deviate from on-theroad test data, where the engine fan is cycled on and off based on thermal loads on the engine. Each time, the engine fan turns on, fuel economy is affected.

2. Please comment on the appropriateness and completeness of the contents of the overall model structure and its individual systems and their component models (i.e., using the MATLAB/Simulink version), if applicable, and considering the following:

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The th ree main powertrain components that can affect fuel economy and greenhouse gas emissions in a vehicle are: engine fuel map, transmission type and efficiency map, and vehicle aerodynamic improvements (including tire rolling friction improvements and weight reduction technologies). In this regard, GEM-II addresses all the aforementioned components by providing steady state maps for each powertrain component, which an informed user can change to represent specific technology improvements. GEM

- II comes with cer tain standard transmission models, namely: manual, automatic, and automated manual transmissions. The user would select the appropriate transmission and GEM- II would automatically select the user

- specified

transmission.

Recommendation: It is recommended that additional instructions are provided if the user wants to change the engine map. Ideally, this would be done from a user specified spreadsheet in a

GEM -II compatible format, since the user may not be fluent in Matlab. In this regard, a clear explanatio n of all the variables used in GEM-II would also help significantly. For example, it was not clear how to change the transmission shift schedule if an OEM chose to do so. Further,

since GEM -II is modular with hierarchical layout of component layers, it is challenging for an OEM user to insert a technology improvement deep within one layer and not affect the layers

above or the execution of GEM- II. It is not clear, from this initial review, how a technology improvement such as a proprietary transmission shi ft schedule can be evaluated in terms of gains in fuel economy and greenhouse gases. This comment applies to other technology improvements as well, such as partial engine cylinder deactivation (power on demand) or electrification of

certain mechanical acce ssories.

a) Elements in each system used to describe different vehicle categories;

The vehicle categories that GEM -II addresses range from Class 2B to Class 8 HD conventional vehicle powertrains. This is achieved by four root- level systems in GEM

- II at the root level, namely: the ambient, driver, vehicle, and powertrain modules. Each of the aforementioned modules consists of several sub-modules organized in a hierarchical manner. Each root- level module outputs a data bus that is muxed into a single data bus. The aforementioned four main systems of GEM -II correspond to the four main components of a HD vehicle, namely: driver, ambient conditions, vehicle chassis and powertrain modules. This one- to -one correspondence

between the root- level GEM -II models and an actual HD vehicle makes for an easily understandable structure. Further, the modular organization of the GEM- II contributes to easier debugging and isolation of a numerical problem during simulation.

The powertrain module is the most populated module in G EM

- II. It contains the engine,

transmission and driveline sub- modules and accessories (mechanical and electrical). The flow of data information corresponds to an actual vehicle powertrain, with the engine output driving the transmission, which in turn drives the driveline components.

The modular layout of GEM-II, its correspondence with a real conventional vehicle is therefore appropriate and complete for the reasons stated above. The modular structure and the hierarchical arrangement of modules to mimic a real vehicle system makes the integration of additional modules and capabilities easier to implement. The signals are clearly marked and follow a logical naming convention that facilitates the addition of additional modules and capabilities into GEM

- II.

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b) Performance of each component model including the reviewer’s assessment of the underlying equations and/or physical principles coded into that component;

GEM

- II follows the model of a single wheel with a concentrated mass at the center of the wheel.

The physics coded into the modules are based on Newton’s second of motion for thisconcentrated mass. At the time of this review, no other dynamic equations were found in GEMII, except in the clutch and torque converter. The engine, accessory, transmission and driveline components are characterized by steady state maps. The equivalent mass of rotating inertia components are also correctly included in the vehicle module of GEM- II. Rotating inertias are correctly reflected downstream to the tire. The inertia is converted to a virtual mass which is

added to the entire vehicle mass. The wide validation of GEM- II against real vehicle data indicates that the physics has been correctly implemented in GEM

- II.

c) Input and output structures and how they interact with the model to obtain the expected result, i.e., fuel consumption and CO2 over the given driving cycles;

Input for GEM- II: A structure format is used to store the inputs to create the input data for the execution of GEM- II. The structure format is organized as follows: component.variable.units. For example, the input variable “engine.idle_fuel_map_speed_radps” identifies the engine speed vector of the engine idle fuel map expressed in rad per sec. Similarly, the input variable “transmission.clutch.input_inertia_kgm2 refers to the clutch inertia of the transmission, expressed in kgm2. This format follows good coding standards, making the inputs easy to pair to the appropriate component it refers to, the particular variable name, and the units used. Further, a modular approach is used to store the input data for each component in separate easily identified files in the “param_files” folder.

Output for GEM- II: When the workspace has been populated with the input data, the simulation model “REVS_VM

vehicle model is executed over the user- selected drive cycle. Each major component model (GEM_CVM, vehicle, driver, ambient) has a bus_out output port which contains a structure of component output data, which is used within other components. In addition, GEM- II uses a

da talog structure to store simulation output data for later post processing to calculate emissions and fuel economy. All the simulation output is stored in a single datalog structure with multiple fields, each describing the component that the data pertains to. For example, datalog.vehicle.speed_mps refers to data log from the vehicle component of the variable vehicle speed in m/s. This format is an accepted coding standard within other vehicle simulation packages (such as PSAT from ANL, RAPTOR from SwRI) as well, making the output easy to pair to the appropriate component it refers to, the particular variable name, and the units used. Similarly, all variables that are used to perform an energy balance are prefixed by “audit”.

Interaction with the model to obtain the expected results: The bus_out structure from the various components are stored in “goto” blocks which are paired with “from” blocks to distribute data from one block to another. The use of paired “goto” and “from” blocks is an accepted method of decluttering the simulation model and avoiding crisscrossing signal lines, thereby significantly facilitating the understanding of information flow from one component to another.

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d) Default values used for the input file, as shown in “Vehicle Simulation Mod el” document.

The default data used in GEM-II is complete and appropriate to execute a simulation of HD vehicle powertrain over one of the drive cycles available in the GEM- II default drive cycle library. The default ambient conditions summarized in ambient_param.m are appropriate. The default driver parameters, summarized in driver_param.m, contain driver gains as well as the time that the driver can look ahead in the drive cycle. The driver gains represent an average driver, which the user can change to emulate an aggressive driving pattern versus a calmer

driver.

The default engine maps of 270 kW, 345 kW, and 455 kW power ratings includes inertia, idle speed. Default transmission maps for the manual, automatic, auto

- manual are also available.

Default t ire radius, axle ratios, rolling resistance of the tires of the steering axles and drive axles

are also included.

3. When using the standard of good engineering judgment, is the program execution optimized by the chosen methodologies?

Overall, GEM

- II use s industry accepted coding practices throughout the software modules. The following is a partial list of these accepted practices:

• Valid variable naming structure used

–

• Data bus used for each component –

• Modular components with no signals crossing –

• Us eful comments to assist the user with following the code

–

• Energy audit adds to the confidence level of the results of the simulation.

• File name that is executed is echoed back to the user. If there is a simulation abort, the debug is easier

• Data that is being loaded is echoed back to the user so the user knows what data is being

used.

• Component modules are linked to libraries. A change in the library module propagates to all vehicle models during execution.

At this point in the review, I do not have adequate data to comment on the execution optimization of GEM

- II. Linear interpolation modules from the standard Simulink library are used within GEM-II, thereby optimizing execution. If there are any non -standard user defined

functions used within the GEM- II simulation model, the execution can be made considerably faster through the use of s-functions within Simulink. At the time of this review, no S-function

were found in the model.

4. Please comment on the clarity, completeness and accuracy of the intended output/results (CO2 emissions or fuel efficiency output file).

The output data from a simulation execution is summarized in a spreadsheet, which is date and time stamped, allowing the user to verify that the output data corresponds to the simulation executed. The output data contains data on which technology improvement ( weight reduction, vehicle speed limiter, single drive axle, par time single drive axle, low friction axle lubrication, predictive cruise control, high efficiency AC compressor, elect rified engine cooling pump,

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extended engine idle reduction, automatic tire inflation )was assessed, engine, transmission type, fuel economy and CO2 emissions.

The output data, summarized above, serves the original purpose of GEM-II, which is to enable

use rs to demonstrate compliance with regulatory standards either without any modifications to the HD vehicle, or analyze the fuel economy and CO2 emissions, when one or more technology improvements are employed. However, information on the drive cycle is missing or not clearly

identified. In addition, key plots of vehicle tracking the drive cycle, engine operating speedtorque points over the drive cycle, engine efficiency contour plots, transmission operating points, and other plots that assist OEMS to further fine tune the powertrain and improve fuel economy/

CO2 emissions in case of non- compliance. It would be desirable to have the results of the energy audit summarized in the output file. The date stamp column is appropriate for the user to cross

check simulation runs.

5. In your opinion, are there any procedures or observations that would have added to the quality of the GEM tool? Any recommendations for specific improvements to the functioning of the outputs of the model?

The following modules will e nhance GEM

- II:

• A module that is able to create the input data for a GEM

- II execution from a user provided spreadsheet with pre-defined tabs for the engine, transmission, drive cycle, vehicle parameters, and technology improvement. Users are more familiar w ith spreadsheets than the Matlab environment.

• A GUI module that guides the user to create a HD vehicle model.

• A module that allows users to select plots of key component performance. These plots may be summarized in the output spreadsheet data file.

• A mor e detailed explanation of all the user provided data “target.X” and the various choices available for each of the user provided data. For example, what are the choices that the user has for the variable target.veh_style ?

• GEM

- II execution takes place with in the Simulink environment. During execution, no feedback is provided to the user on the status of the simulation. The user is waiting on a blank screen – Percent complete of the simulation and which drive cycle is being

executed would be useful feedback for the user.

• Predefined sample input data for all class of vehicles to assist users to easily modify them if necessary, since some users may not be familiar with Matlab.

• The ability to turn on the feed forward term for the driver model in case of tracking problems in drive cycles with grade.

• The ability to model accessory power draw as a function of engine speed and engine temperature. The engine cooling fan power cycle will affect fuel economy and CO2

emissions.

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III. SPECIFIC OBSERVATIONS

Specific Ob servations on T ool D escription E ntitled, “Vehicle Simulation Model” Page Paragraph Comment or Question

5 2 The last sentence reads “If a manufacturer uses a hybrid powertrain for the power take-off devices, it may o make use of ....”. The “o” after may is a typo

3 2 Distance compensation is critical for all vehicle simulations

–Therefore, this is a good feature that has been implemented in GEMII

6 4 Please explain what is included in spin losses, since this may not be

clear to all OEM users.

9 3 The G EM

- II executable is very appropriate for users who are not

fluent in the Matlab/Simulink environment. Further, the executable prevents users from making any changes to GEM-II to support compliance.

Specific Observations on E lectronic Model E ntitled

, “GEM Tool” Input Variable Comment or Question

NA NA Avoid taking the derivative in the Simulink models. This can cause instabilities if the signal fluctuates rapidly.

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