Design of a Parallel-Series PHEV for the EcoCAR 2 Competition

INTRODUCTIONThe Ohio State University EcoCAR 2 Challenge Team is

a multi-disciplinary team consisting of more than 40 students.The team has members ranging from high-school students toPh.D. students who participate in a wide variety ofengineering, business, and outreach tasks. As described inthis report, the team's progress through a rigorous vehicledevelopment process has led to the design of a unique vehiclefor the EcoCAR 2 Challenge. The final selected architectureand vehicle technical specifications can be found in AppendixF and Appendix B respectively. The design features:

• Multi-Mode Operation: The vehicle's design allows foroperation in series, parallel, or all-electric operation. Thevehicle's supervisory control performs real-time optimizationof the vehicle's engine and two electric motors.

• High-Efficiency E85 Internal Combustion Engine: Theteam has converted a high-compression ratio natural gasengine to operate on E85 resulting in greater than 40% brakethermal efficiency.

• Automated Manual Transmission: The team has chosen todevelop an automated manual transmission. The system uses

a stock GM transmission with custom actuators and controlsoftware for the clutch and shifting.

• Aggressive Electric Operation - Customer requirementsdrove the team to design a vehicle with high all-electric range(>40 miles) and high all-electric performance.

VEHICLE DESIGN PROCESSVDP Overview

A simplified Vehicle Development Process (VDP) waspresented to the EcoCAR 2 teams by the competitionorganizers at Fall Workshop, which is shown in Figure 1. Theteam used this process and unified it with the V-Diagramprocess used for design of complex systems, of which theteam's EcoCAR 2 vehicle is an excellent example.

The team's VDP V-diagram can be found in Appendix Aand shows the process that will be followed by the Ohio Stateteam to develop both the controls system and powertrain forthe vehicle. The left side of the V-diagram represents thevehicle design process, while the right side of the diagramrepresents the realization and validation process. The twosides are connected at the bottom with the componentrealization step, where the design steps from the left side are

2012-01-1762Published 09/10/2012

Copyright © 2012 SAE Internationaldoi:10.4271/2012-01-1762

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Design of a Parallel-Series PHEV for the EcoCAR 2Competition

Katherine Bovee, Amanda Hyde, Shawn Midlam-Mohler, Giorgio Rizzoni, Matthew Yard, Travis Trippel, Matthew Organiscak, Andrew Garcia, Eric Gallo, Mark Hornak, Andrew Palmer and

Josh HendricksOhio State University

ABSTRACTThe EcoCAR 2: Plugging into the Future team at the Ohio State University is designing a Parallel-Series Plug-in

Hybrid Electric Vehicle capable of 50 miles of all-electric range. The vehicle features a 18.9-kWh lithium-ion battery packwith range extending operation in both series and parallel modes made possible by a 1.8-L ethanol (E85) engine and 6-speed automated manual transmission. This vehicle is designed to drastically reduce fuel consumption, with a utility factorweighted fuel economy of 75 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissionsstandards. This report details the rigorous design process followed by the Ohio State team during Year 1 of thecompetition. The design process includes identifying the team customer's needs and wants, selecting an overall vehiclearchitecture and completing detailed design work on the mechanical, electrical and control systems. This effort was madepossible through support from the U.S. Department of Energy, General Motors, The Ohio State University, and numerouscompetition and local sponsors.

CITATION: Bovee, K., Hyde, A., Midlam-Mohler, S., Rizzoni, G. et al., "Design of a Parallel-Series PHEV for theEcoCAR 2 Competition," SAE Int. J. Fuels Lubr. 5(3):2012, doi:10.4271/2012-01-1762.

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implemented in the vehicle and then validated using the stepson the right side. Validation plans also flow from the left sideof the V-diagram to the right, which provides the tools toevaluate if the realized designs meet the required designobjectives.

Figure 1. EcoCAR 2 Vehicle Development Process

VDP ImplementationThe key to the OSU implementation of the design process

is that it explicitly combines the three “swim lanes” ofdevelopment into a unified diagram for electrical,mechanical, and controls efforts. On the way down the V-diagram, component design tasks form the critical path. Oncea design decision is made, software design tasks then occur inthe yellow area in the diagram. For instance, once the vehiclearchitecture is defined, it is possible to start the design tasksrelated to the vehicle control software. As subsystems andeventually components are defined on the critical path, theassociated work on controls can begin.

On the implementation path, the right side of the diagram,controls realization is the critical path. It is usually notpossible to fully validate a powertrain component or systemuntil controls are available, thus the controls must be realizedprior to full validation of the hardware. Because the controldesign and development was already started (in the yellowarea), control hardware, software, and calibrations should beready by the time hardware is actually realized. Thisapproach accelerates the pace of vehicle development and isheavily reliant upon the use of SIL and HIL techniques toallow controls development without availability of hardware.

In terms of the specifics of the implementation, the OSUteam maintains several documents that allow the team totrack progress. The first document the team has developed isa Test Plan and Procedures (TP&P) document which tracksthe propagation of design and control requirements as theycascade through the various subsystems in the vehicle. TheTP&P document is structured from the high-levelrequirements of the vehicle. By way of example, the vehiclehas a 0-60 mph time target and references the competition

rules for the execution of this particular test since it is acompetition event. The document also captures how higher-level requirements trickle down into subsystems and includeshardware as well as supervisory control software.

The other document the team has developed acts as asupplement to the TP&P document that is specifically forcontrols related tracking. This is the Supervisory Control,SIL, and HIL Development Document. The purpose of thisdocument is to track and document key decisions in thesupervisory control development process, SIL activities, HILactivities, and fault diagnosis work. The document highlightsprogress, plans, and data in the following key areas of thecontrol development: Control Requirements, SystemArchitecture, Control Algorithms, Strategies, and DiagnosticAlgorithms, Safety Critical Systems, Verification andValidation, Systems Integration, and DFMEA/FTA Results.

VDP DeviationsThe team did not have any major deviations in the VDP

process in Year 1. In a few cases, nearly completedsubsystem designs have required extensive rework due todesign objective conflicts between subsystems. In particular,the design of subsystems within the rear powertrain proved tobe a challenge. The rear electric motor system, the energystorage system, and the cargo capacity aspect of consumeracceptability were all in competition for vehicle space. Thiswas compounded by the fact that there are waiver issuesinvolved due to structural modifications of the vehicle. In theend, the competition objectives of these three subsystemswere managed by adhering to OSU's VDP process to makethe best trade-off possible. This is discussed in greater detailin the Packaging and System Integration section of thisreport.

Current VDP StatusFrom a software perspective, the team is currently in the

HIL Control Testing/Validation phase of the V-diagram.Software for each of the three team-developed controls isrunning in the target control hardware on the HIL, or in manycases, with actual plant hardware.

For electrical and mechanical subsystem development, themajority of projects are at the component or subsystemimplementation phase. By way of example, the team'sambitious project to automate a manual transmission is wellunderway. The actuation hardware is built and is being testedwith the developed control system prior to Year 1competition. The team has already secured all other majorpowertrain components and confirmed delivery duringsummer of 2012.

Following the completion of the first year of EcoCAR 2,the controls models for the vehicle supervisory control,electrical and mechanical subsystems and component modelswill be validated and ready to begin the next phase of the V-diagram. In Year 2, the vehicle will be built and thereforeachieve realization of the electrical and mechanicalcomponents and subsystems, as well as full, low-level control

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implementation and basic high-level control functionality. InYear 3, the team will focus on further refinement andvalidation of the vehicle against the original targets set by theteam.

POWERTRAIN CONFIGURATIONThe OSU architecture selection and process is broken into

four major phases: Problem Definition, SpecificationDevelopment, Concept Development, and Concept Selection.Within each phase are more specific steps created to ensurethorough background research and yield the best possiblearchitecture for the OSU team. The process is illustrated inAppendix D.

Goals and Specification DevelopmentsThe team goals and specifications were set by identifying

the different customers of the OSU EcoCAR 2 team,identifying the needs of each customer, and performing acompetitive vehicle benchmarking assessment. This isrepresented in Appendix D as the Problem Definition phase.The team identified four different “customers” for the OhioState EcoCAR 2 vehicle, listed below with a brief descriptionof the reason for their selection. This phase is crucial giventhe inevitable tradeoffs that are necessary in designing avehicle.

• OSU EcoCAR 2 Students: The vehicle designed by theOhio State team needs to have new and challenging aspectsthat have not been done by the team before in order to allowboth new and returning team members to learn more abouthybrid vehicles.

• Outreach Target Audiences: The vehicle designed, built andtested by the Ohio State team needs to appeal to K-12students, the general public, and influencers in a wide rangeof fields. In the coming years, all three of these groups willplay a part in how hybrid vehicles are accepted into thelifestyles of the American public.

• EcoCAR 2 Judges: The Ohio State vehicle needs to impressthe judges in EcoCAR 2 since these judges are responsiblefor assigning the team points based on everything from thevehicle's technical merit to its static consumer acceptability.

• EcoCAR 2 Event Scoring: The vehicle designed by theOhio State team needs to maximize the amount of points thevehicle can receive in the Year 2 and 3 dynamic events.These events score everything from the vehicle's fueleconomy to its performance and drivability.

Customer Needs and WantsEach of the four different customer groups have different

“needs and wants” for the team. These needs and wants arewhat eventually drive the concept selection and vehicletechnical specifications. The engineering, outreach, andbusiness team developed the following list for the fourdefined customers: 1) apply knowledge gained in theclassroom to real world problems; 2) provide good design

project content; 3) provide good research project content; 4)provide good content for presentations; 5) vehicle has betterfuel economy, emissions, and performance than the stockChevrolet Malibu; 6) have strong ties to Ohio businesscommunity; 7) be aesthetically attractive to target audiences;8) have capability to place in top 5; 9) maximize score ondynamic vehicle events; and 10) perform well on staticevents.

Competitive Vehicle AssessmentIn addition to identifying the customers and determining

each customer's unique “needs and wants” for the vehicle'sperformance, the team performed a Competitive VehicleAssessment (CVA). The CVA is a way to benchmark theteam's vehicle against vehicles being sold in the samesegment as the Chevrolet Malibu (Affordable Midsize) aswell as in three other segments. The complete CVA listsmore than 20 key aspects collected from a variety of sourcesthat include the US News Buyers Guide, the US Newswebsite, Yahoo Autos, vehicle manufacturer's websites,motortrend.com, torquestats.com and zerotosixty.com.

Figure 2. Competitive Vehicle Assessment Summary

A few relevant parameters from the CVA that helpeddetermine the team's goals and specifications are shown inFigure 2, namely: 0-60 time, trunk volume, city MPG, andhighway MPG. These stats helped guide the ultimateselection of a target 0-60 time of 7 seconds as well asproviding justification of some loss in trunk volume due topackaging constraints. Because of the relatively large stocktrunk volume of the 2013 Malibu, some intrusion into thisspace would not be out of line with competing vehicles.

Establish Vehicle Design SpecsThe next phase of the selection process shown in

Appendix D involves developing metrics to rank differentconcept designs. These are similar to the VTS targets for thevehicle, but include a number of non-technical factors aswell. The five categories of metrics in the table are:performance, consumer acceptability, risk, educational value,and Ohio focus. These metrics, in addition to the eventualscoring results discussed later, are shown in Appendix E. Theweighting for each of the metrics was determined by theEcoCAR 2 scoring system as well as the team's own goals.The composite fuel economy and the upstream/downstream

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emission metrics were given weightings of 10 since the totalof those two events are worth 30-34% of the points in Years 2and 3 of the competition. The remaining metrics wereassigned weights in a similar fashion to form a decisionmatrix. As mentioned above, these are not the full set ofvehicle technical specifications at this point in the process.

Architecture Selection ProcessHigh Level Component Design Decisions

The results of the process described above led to a list ofquantitative metrics against which to evaluate the candidatearchitectures. However, the large freedom in the design spacemade it difficult to systematically define possiblearchitectures. Free design options include: 1) fuels; 2) energystorage capacity; 3) operating modes (i.e. series, parallel); 4)component sizes; and other such options.

In order to reduce the number of free design variables inthe architecture selection process, the team made high-leveldesign decisions at the start of the architecture selectionprocess to reduce the design parameters that needed to beoptimized in the modeling and simulation portion of theprocess. The key decisions were largely made with respect tofuel and critical components and are consistent with theCustomer Needs/Wants and Vehicle Design Specificationsdetermined in the second phase of the process shown in inAppendix D. Reducing the number of free parametersnarrows the design space sufficiently to allow rigoroussimulation studies to be used to evaluate concept vehicles.

To select fuel type and ESS capacity, the team essentiallyconducted a virtual EcoCAR 2 competition amongst a host ofvehicle types using Argonne National Lab's GreenhouseGases, Regulated Emissions and Energy Use inTransportation (GREET) Model. The team used the GREETmodel to analyze how each of the different fuel combinationsallowed in the EcoCAR 2 competition would affect their finalscore in the EcoCAR 2 Emissions and Energy Consumptionevent, which is the highest scoring event in the competition.Once all calculations were completed, each fuel type wasscored using the EcoCAR 2 competition's normalized scoringmethod, which scales the points awarded to each team basedon the highest and lowest scores.

This analysis considered the following vehicles: aconventional vehicle with E10, E10 HEV, E10 PHEV, aconventional vehicle with dedicated E85, dedicated E85HEV, E85 PHEV, conventional B20, B20 HEV, B20 PHEV,and a hydrogen fuel-cell vehicle. The analysis alsoconsidered the impact of varying all-electric range on theperformance of the vehicle via the utility factor concept usedby the competition.

Based on the results in Figure 3, the hydrogen fuel-cellvehicle would be the best choice for earning points at thecompetition based on its excellent petroleum use reductionand WTW GHG emissions reduction. However, hydrogen isnot well-aligned to the research goals of the team or OhioState's Center for Automotive Research. Therefore, a

hydrogen fueled vehicle was not considered further by theteam. If the use of hydrogen as a fuel is eliminated as anoption, the best remaining fuel combination shown in Figure3 is the E85 PHEV. This decision is consistent with thedesign process as it matches the customer needs and wantsdefined earlier.

Figure 3. Estimated Total Competition Score for Fuel

Based on the choice of E85, the team decided to use a1.8L high compression ratio Honda engine in order to takeadvantage of E85's high octane rating to get better efficiencyfrom the engine. This was a practical result of the team'sprevious experience with this engine and the fact that itrepresents a best-in-class efficiency for a SI engine at 40%brake thermal efficiency. Note that these design decisionsalso support the Customer Needs/Wants, specifically havingbetter fuel economy and emissions than the stock Malibu,having strong ties to the Ohio business community,performing well on static competition events, and providinggood content for presentations, design projects, and researchprojects.

Figure 4. Estimated Total Fuel Economy and EmissionScores for Varying Charge Depleting Ranges

As seen in Figure 4, increasing the charge depleting rangeof the vehicle has a significant effect on raising the overallscore for the EcoCAR 2 Emissions and Energy Consumptionevent. Therefore, it is desired to maximize the chargedepleting range of the vehicle by maximizing the capacity of



its battery pack. This led the team to select the largest batterypack A123 was willing to donate to the team, which was an18.9 kW-hr battery pack.

Concept DevelopmentWith the fuel, engine, and ESS system already defined,

the team was able to focus on developing concepts in amanageable design space. As shown in Appendix D, this is amultistep process. In the Internal Concept Search phase ofthis process, the team started developing conceptarchitectures over the summer of 2011, using a collaborativeand private wiki website hosted by OSU to capture ideasfrom the returning team members who were at variouslocations on internships. The External Concept Searchinvolved conducting a thorough literature review of relevanttopics containing more than 60 references and a review of thepublications and performance of top EcoCAR and Challenge-X team designs. The team used these results in the SearchResult Synthesis section to understand what attributes andsystems would deliver the best possible design.

Candidate Hybrid Vehicle ArchitecturesThe outcome of the Concept Selection Process was four

different architectures that the team felt would best satisfy theVehicle Design Specs, and thus, the customer needs/wants.These four vehicle architectures are: 1) a series PHEV; 2) apost-transmission PHEV; 3) a pre-transmission PHEV; 4) aparallel-series PHEV. Vehicles (1) through (3) are well-known architectures. A diagram of architecture (4) is shownin the Appendix F. Descriptions of each of the candidatearchitectures are given in Table 1.

Table 1. Candidate Architectures

For each of these vehicles, Argonne National Lab'sAutonomie software was used to simulate the differentvehicle architectures in addition to the stock vehicle as abaseline. The team also completed initial packaging studieson each vehicle to ensure the powertrain components theywanted to use could be packaged inside a conventional 2013Chevrolet Malibu. The hybrid vehicle architecturesconsidered by the team were also compared back to theconventional vehicle in order estimate how much of animprovement in fuel economy the hybrid vehicles wouldhave.

Vehicle Model SetupAll four of the hybrid vehicle models used the same

customized initialization files for the engine and battery pack.The engine initialization file was modified to reflect the 1.8LE85 Honda engine that the team had selected using datagathered by the team in the dynamometer test cell. Thebattery initialization file was modified to reflect the 18.9 kW-hr pack that A123 would donate to the team using the dataprovided by A123. All four hybrid vehicle models also usedthe UQM electric machine initialization files that were pre-loaded in Autonomie. The team decided to use all UQMelectric machines in order to maintain some consistencyacross the four hybrid vehicle models, since a supplier for theelectric machines had not yet been identified. These mapswere scaled to achieve the desired power characteristics.

Once the model for each vehicle was set up, the gearratios, control strategy parameters and electric machine sizewere all optimized to give each model the best possibleacceleration time and fuel economy. The team did multipleparametric studies on each of the four hybrid vehicle modelsto learn how the gear ratios, control strategy parameters andelectric machine size affected the vehicle's performance andfuel economy numbers. The results of the parametric studiesallowed the team to select a set of parameters that had thebest balance between acceleration times and high fueleconomy.

Simulation ResultsThe acceleration and fuel economy results from the

Autonomie simulations of the hybrid vehicles and theconventional Malibu are listed in Table 2. All four hybridvehicle architectures had significantly better fuel economythan the conventional Malibu. These fuel economy numbersranged from 63.5 mpgge for the pre-transmission PHEV to72.3 mpgge for the parallel-series PHEV vehicle. All thehybrid vehicles also had all-electric ranges greater than 44miles which gave then utility factors of 0.654 or greater. Theparallel-series PHEV had the longest all-electric range of 50miles.



Table 2. Vehicle Simulation Results

In addition to the good fuel economy and all-electricrange numbers, most of the hybrid vehicles had betteracceleration times than the conventional vehicle. This was bydesign, as this was a feature that was identified in thecustomer needs/wants analysis.

Decision MatrixThe results of the vehicle simulations were used with the

results of the packaging studies to determine which of thefour possible hybrid vehicle architectures best meet the team'sgoals and specifications found the previous section of thisreport. The decision matrix used to evaluate each of the fourarchitectures is shown in Appendix E. The reference vehiclesused in the decision matrix are the conventional ChevroletMalibu vehicle and the twin-clutch E-REV vehicle built byOhio State in the EcoCAR 1 competition. The conventionalChevrolet Malibu was used as the reference for theperformance and consumer acceptability metrics while thetwin-clutch E-REV was used as the reference for the risk,education, and Ohio focus metrics.

The results of the decision matrix in Appendix E showthat the parallel-series PHEV vehicle is the best hybridvehicle architecture choice for the Ohio State team. Thesimulation results showed the parallel-series PHEV had thebest composite fuel economy out of all four vehicles alongwith the longest all-electric range. Additionally, the parallel-series PHEV had better packaging attributes to it than theseries hybrid and post-transmission PHEV due to theseparation of the two motors into two locations.

It was also felt that there was additional performance tobe obtained for the parallel-series PHEV as the Autonomiemodel developed did not take full advantage of all of theoperating modes available to the parallel-series PHEV. Byway of example, the model did not optimally balance the useof the electric motors nor did it take advantage of the seriesmode that is available to the vehicle. These extra elements offunctionality could not be developed in the short timeavailable for architecture selection - nor did they materiallyselect the decision as it would only strengthen the parallel-series performance.

Powertrain Component SelectionBased on the discussion above, the selection of the energy

storage system and the engine were decisions made upstreamof the architecture selection process. These decisions weremade based on sound analysis of the design goals of the

project. The remaining major powertrain components includethe front electric motor and inverter, rear electric motor andinverter, rear transaxle, and front transmission.

The simulation study provided targets for componentspecifications for the remaining powertrain components.These included: torque and power specifications for theelectric motors; gear ratio for the rear drive; desired gearratios range for the transmission; and a number of otherrequirements. Additionally, major systems already selectedprovided constraints, such as the battery voltage range whichimpacted inverter and motor selection.

Beyond technical requirements, business issues alsoimpacted component selection - primarily in the form of teambudget constraints. The team was fortunate to be able topartner with Parker-Hannifin for both permanent magnetmotors and inverters. They provided a limited range ofoptions; however, they matched quite well with the targets.The transmission selection was driven by a number of factors,and is discussed in great detail in the Packaging andIntegration section. The last major component was the reartransaxle. In this case, a deeply discounted unit was securedfrom Borg-Warner which matched the desired ratio from thedesign simulations.

A detailed packaging study has also driven both thechoice of major components and their orientation in the OhioState vehicle. The major components influencing the vehicledesign are given in Table 3 through

Table 3. Front Powertrain Component Summary



Table 4. Rear Powertrain Component Summary

Table 5. Energy Storage Component Summary

Key Tradeoffs in Powertrain DesignAs described in the previous sections, OSU followed a

rigorous design process in order to develop the best possibledesign based on the constraints. Some of the key tradeoffsdiscussed and a summary of the impact are captured in thefollowing list. In the relevant subsections, many moretradeoffs are discussed at the subsystem and component level.

1. Fuel Choice: Analysis demonstrated that hydrogen wasactually a “better” choice based on competition pointstructure; however, the team did not choose this fuel. Instead,E85 and electricity were chosen as the best fuels for the team.Hydrogen poses a high financial cost for hardware as well ashigh technical risk - the team's design process penalized theserisks in favor of E85. As shown in Figure 3 and Figure 4, thecombination of E85 and electricity are the next strongestchoice and align with the team's interest and experience.

2. Energy Storage System Size: Based on the analysisleading to Figure 4, the team's choice of the largest availableA123 Systems battery pack was justified. The larger packoffered with it a higher weight and packaging volume as atrade-off. The team's early packaging analysis proved that thepack could be integrated with no loss of passenger space anda moderate loss of trunk space. A decision matrix analysisproved that this tradeoff was justified for the competition.

3. Front Powertrain - The front axle powertrain presentedseveral key tradeoffs, the most notable of which was selectionof a transmission that would fit within the width of thevehicle with the selected architecture. After reviewingspecifications and CAD on a number of transmissions, the

team determined that none of the available transmissionswould both package in the vehicle and meet the max torquerequirements. The team opted to accept a lower max torquerequirement from the front powertrain, however, the rearelectric motor was increased in size to make up for thereduction.

4. Rear Powertrain - The major tradeoffs in packaging therear axle powertrain were: intrusion on trunk space, intrusionon cabin space, and interference with structural vehiclemembers. These issues were compounded by therequirements of a larger motor in the rear driven by thetransmission issue described in (3) above. This tradeoff isdiscussed in greater detail later in the report; however, theeventual tradeoff was deemed appropriate given the team'sdesign goals.

Powertrain Configuration SummaryThe parallel-series PHEV architecture selected by the

Ohio State team has the following characteristics that make itthe right choice for the Ohio State team. The final step in theprocess outlined in Appendix D is the generation of VTStargets for the actual vehicle. These VTS targets are anoutcome of this process, most of which are derived from thesimulation model that was developed. Key features include:

• Ability to operate in charge depleting, charge sustainingseries, and charge sustaining parallel operation

• Robust, fault tolerant design

• Challenging mechanical, electrical, and control systemdesign problems

• Team-programmed engine, transmission, and vehiclesupervisory controllers

• 50 mile all-electric range

CONTROLS DEVELOPMENTPROCESS

Control Development ProcessThe controls development process is illustrated by the

yellow area of the V-Diagram given in Appendix A. Thedevelopment of controls software has occurred in tandemwith the powertrain design throughout the entire vehicledesign process. First, requirements were defined for high-level supervisory controls followed by subsystem controlsand low-level controls. Next, hardware and software designswere developed for each level of controls. HIL validation andtesting is being performed on all of the vehicle controlsbefore in-vehicle implementation during Year 2.

Control Development ToolsA variety of control development tools are employed by

the Ohio State team throughout the control developmentprocess. The entire control system was designed and



constructed using MATLAB and Simulink, employing avariety of toolboxes contained within these powerful tools. Inaddition to these tools, dSPACE's Hardware-In-the-Loopsimulator was used to develop and validate the controlsystem.

The team employed professional tools to conduct FaultTree Analysis (FTA) and Design Failure Mode and EffectsAnalysis (DFMEA, using Isograph's Reliability Workbenchwith FaultTree+ to conduct FTA, and Byteworx FMEAsoftware to carry out DFMEA.

To determine test coverage for the control models, TheMathworks/Simulink Design Verifier and Model Coveragetools are being used. Both are tools built into MATLAB andSimulink for analyzing Simulink models. Design Verifierensures that all portions of the model are accessible andallows the team to test and prove various properties of themodel. The Model Coverage tool measures how thoroughlymodel objects are tested by determining how many of allpossible simulation pathways in the model have beenexercised during a test. This will ensure that all of the code inthe controllers has been validated through SIL and HILbefore implementation in the vehicle.

Plant Model Development for SIL/HILThe Ohio State team uses a combination of self-developed

models and detailed dSPACE component models in the SILand HIL environments for control development and faulttesting purposes. Table 6 contains a description of the plantmodel components, lists their state in both SIL and HILdevelopment, identifies the source of the model, and lists thereasons the features were implemented into the plant model.

The Software-in-the-Loop models used by the team aremostly self-developed and are combined into a single energybased simulator called EcoSIM. EcoSIM is an energy basedhybrid vehicle simulator developed by Ohio State teams overthe span of over 15 years through FutureCAR, FutureTruck,ChallengeX and EcoCAR competitions, and is adaptable todifferent hybrid powertrains. The EcoSIM simulator containsmodels for each of the powertrain components that consist ofstatic maps, simple transfer functions and simplified softECU's. EcoSIM in the SIL environment is especially usefulfor testing the effectiveness of new control algorithms atimproving fuel economy.

The Hardware-in-the-Loop (HIL) models are used withthe team's dSPACE HIL equipment to test the CANcommunication between the different team programmedcontrollers and test the controller's response to faultconditions within the vehicle. The sources for the individualpowertrain component models range from the teamprogrammed models taken from EcoSIM to the detailed ASMmodels created by dSPACE for the engine, transmission andbattery components. The detailed ASM models have many ofthe sensor/actuator signals found on a real vehicle, allowingthe team to conduct complex fault testing on their HILequipment before the controller code is implemented on thevehicle. The detailed ASM models are not yet implemented

on the team's HIL equipment, but they will be implementedby the Year 1 competition in May 2012.

Table 6. Models and Hardware used by the Ohio StateEcoCAR 2 Team

Finally, the team has also created detailed physics-based,sub-system models for each of the research projects assignedto students on the EcoCAR 2 team. These detailed sub-system models include CFD models for analyzing aeroimprovements, a GT-Power model of the engine, and thermalmodels of the powertrain components.

HIL Test Bench SetupThe Ohio State team's HIL system setup will be

partitioned into four separate cases, outlined in Figure 5 andsummarized in Table 7. This will allow validation from thesub-system controller level to the entire controller networkthat will be developed by the team. Each of these cases has aspecific purpose, to test and validate the three OSU-codedcontrollers as highlighted in Table 7. OSU will be



demonstrating the most aggressive case, Case 4, at Year 1Competition Finals.

Figure 5. HIL Setup Cases

Table 7. HIL Simulation Setup

Controls Development Process SummaryDue to the complexity of the Ohio State team's vehicle

architecture and control architecture, an aggressive SIL andHIL development plan is necessary to ensure a robust controlsystem that is ready for implementation in the vehicle.

CONTROL SYSTEMARCHITECTURE

Control Architecture Design ProcessThe requirements for the vehicle's control system

architecture, supervisory control algorithm and hardware forthe supervisory, engine and transmission controllers are listedin Table 8. These high-level qualitative requirements are usedto guide the selection process and eventually lead toengineering specifications.

These requirements were derived from the needs/wantsthe team had for each of the different controllers and theteam's previous experience in the EcoCAR competition. TheI/O requirements for the engine, supervisory andtransmission/general control module hardware were derivedfrom detailed the I/O lists based on plant hardware. Therequirements for each controller are used in the controlarchitecture section to select the vehicle architecture andcontroller hardware for the Ohio State vehicle.

Table 8. Requirements for Control Architecture andTeam Programmed Controllers

Control System ArchitectureThe control system architecture chosen by the Ohio State

team is shown in Figure 6. The control architecture includes ahigh level vehicle supervisory controller that manages vehiclemode operation and the power split between the differentpowertrain components. Three different CAN networks arethen used for communication between the vehicle'ssupervisory controller and the lower level controllers used to



control individual powertrain components like the engine andthe electric machines.

The Ohio State team chose this specific control systemarchitecture by comparing the control system requirementslisted in Table 8 to different control system architectureconcepts they developed. The final control systemarchitecture show in Figure 6 was chosen because its modulardesign can easily accommodate modifications to the controlsystem and its hierarchical structure allows a single controllerto manage all the lower level component controllers in anorganized manner. The chosen control system architecture isalso tolerant to fault conditions and is compatible with theteam's engine dynamometer, HIL and vehicle testing.

The control architecture chosen by the Ohio State teamhas several strengths and weaknesses associated with it. Thestrengths include:

• Distributed hardware architecture facilitates paralleldevelopment.

• Use of team-developed powertrain controllers increase theflexibility of the system - the team can add new functionalityas needed.

• Use of team-developed powertrain controllers minimizesinterfacing with controllers containing unknown parameters.

Some weaknesses include:

• Heavy reliance upon CAN for critical communicationbetween controllers which allows for a single wiring failureto disable the vehicle

• Increased development time and technical risk due to threeteam-developed controllers

Control System HardwareThe hardware used for the supervisory, engine and

transmission/general control modules was also selected usingthe requirements listed in Table 8. The hardware is selectedin conjunction with software requirements, all of which isdriven by higher level vehicle requirements. For each of the

controllers, the team considered dSPACE, Woodward, ETASand National Instruments hardware. The team considerednon-sponsored controllers, however, the donated controllersmatched very well with the team's control needs. When thiswas factored in with the technical support provided by thesponsors and the fiscal advantages, the team did not seriouslyconsider any other controllers. Details on each of these keydecisions are listed in Table 9.

Table 9. Controllers Component Summary

Supervisory Controller SelectionThe dSPACE MicroAutoBox II (MABX-II) was chosen

for the vehicle's supervisory controller due to the followingstrengths:

• Large amount of computing power

• Ability to compile and flash code quickly

• Long record of reliability with the Ohio State teamOne weakness of the MABX-II is its cost. However,

dSPACE has donated one MABX-II to the team for their HILsetup and the team has set aside enough money in their teambudget to purchase an additional MABX-II. The secondmajor weakness is that it is not ruggedized for installationaggressive areas, such as the engine compartment. TheControl Algorithm and Strategy section contains moreinformation on the algorithms used on the MicroAutoBox IIto determine what mode of operation the vehicle is in andhow the torque request is split between the differentpowertrain components.

Figure 6. Ohio State Control System Architecture



Engine Controller SelectionThe team decided to choose the ETAS FlexECU as the

vehicle's engine controller. This ECU was chosen because itbest meets the Ohio State team's requirements for the enginecontroller hardware. Also, the ETAS FlexECU will enablethe team to achieve the control algorithm requirements andvehicle technical specifications listed in the Engine Controlsection of this document. Some strengths of the controllerare:

• Ability to be packaged in the aggressive environment of theengine bay

• Donated component reduces cost and comes withguaranteed technical support

• Large amount of engine-specific input/output supportSome weaknesses include:

• Requires existing engine code to be redesigned forFlexECU software blocks

• Requires a complete redesign of the existing engine wiringharness

General Controller SelectionThe 128-pin Woodward ECU was selected for

transmission/general control module controller due to itsability to be packaged in an engine bay and wide variety ofinput/output.

Specifically, the high current H-bridge outputs are criticalfor driving the linear actuators required for shifting thetransmission. This is discussed in greater detail in the GeneralControl Module section of the Control Algorithm andStrategy section. Some strengths of the controller are:

• Ability to be packaged in the aggressive environment of theengine bay

• Donated component reduces cost and comes withguaranteed technical support

• Wide variety of I/O available for driving various actuators,pumps, and fans throughout the vehicle

Some weaknesses of the controller are:• Reduced hardware capabilities compared to other

competition sponsored controller

Other ControllersThe vehicle design also relies on a variety of controllers

that manage individual vehicle subsystems, such as theinverters and DC/DC converter. All low-level controllersreport to the supervisory controller, which manages theoverall operation of the vehicle. Benefits of this approachinclude the ability to develop low-level controls on a per-system basis as well as facilitating a flexible hardwareconfiguration to accommodate modifications. The controllersused in the vehicle that are not developed by the OSU teamare:

• A123 Battery Controller: Manages operation of batterypack and high voltage electrical system. Interfaces over CANto supervisory controller.

• Brake Controller: Controls brake operation when giveninput on the brake pedal by driver. Sends friction brake statusover CAN to supervisory controller.

• Body Controller: Interfaces with vehicle body whilecommunicating wheel pulses and vehicle speed over CAN tothe supervisory controller.

• Front Electric Motor Controller: Controls speed of frontelectric motor when given torque requests by the supervisorycontroller. Interfaces over CAN to supervisory controller.

• Rear Electric Motor Controller: Controls speed of rearelectric motor when given torque requests by the supervisorycontroller. Interfaces over CAN to supervisory controller.

Control System Architecture SummaryThe Ohio State team's control system architecture was

designed to enable robust control of the complex hybridpowertrain being implemented in the vehicle. Therequirements for each controller were driven by the team'sneeds/wants and past experience. This led to the team'sdecision to develop the supervisory controller, enginecontroller, and general controller in-house and to utilize theother component's stock controllers. This will allow the teamto implement a robust and customized control algorithm inorder to achieve the vehicle's VTS goals, defined in AppendixB.

CONTROL ALGORITHM ANDSTRATEGY

The team-programmed controllers include the vehicle'ssupervisory controller, engine controller and general controlmodule. The vehicle's supervisory controller determines themode of operation of the vehicle and how the driver's powerdemand is split up between the different powertraincomponents. The engine controller is responsible forcontrolling the engine to meet fuel economy and emissionsstandards. The transmission controller is responsible forcontrolling the actuators used to switch between gears in thetransmission, in addition to controlling different pumps/fansin vehicle that are not associated with a specific controller.

In the following subsections, each of the three team-developed controllers are discussed from the context of: 1)Control Algorithm Requirements; 2) Control StrategySelection; 3) Control Strategy Description; and 4) Ability toMeet Team/VTS Goals.

Supervisory ControlThe first team-developed controller is the supervisory

control. The following sections highlight key informationregarding this controller.



Control Algorithm RequirementsThe Ohio State team started the control strategy

development process by identifying the needs/wants of theteam for the supervisory control algorithm. The teamconcluded that the supervisory control algorithm should beable to determine how much power the engine and twoelectric machines need to provide to meet the driver's powerdemand. The algorithm should also determine what mode ofoperation the vehicle is in and select operating points for eachof the powertrain components that maximize eachcomponent's efficiency to improve the fuel economy of theoverall vehicle. The needs/wants identified by the team led toa series of technical specifications for the supervisory controlalgorithm, which are listed in Table 8.

Control Algorithm SelectionOnce the requirements for the supervisory control

algorithm were determined, the team researched differentcontrol algorithms they could use. These algorithms includedrule-based algorithms, neural networks and an EquivalentConsumption Minimization Strategy (ECMS). Benefits ofECMS: 1) Provides nearly optimal control performance; 2)Requires minimal calibration for the energy managerfunction; 3) the team has experience with the algorithm.Compromises from ECMS: 1) Very resource intensive on thecontroller, which limits controller selection; 2) may lead todrivability problems that must be handled outside of coreoptimization algorithm; 3) requires accurate characterizationof powertrain components for optimization. The teamcompared the advantages and disadvantages to each of thecontrol algorithms and selected the ECMS algorithm for theirvehicle's supervisory controller using a decision matrix. TheEquivalent Consumption Minimization Strategy (ECMS) hasbeen developed by former AVTC team members incollaboration with faculty and research staff at Ohio State'sCenter for Automotive Research. It was first implemented inthe Future Truck 2000 competition vehicle and has beenrefined over the years to include adaptation to drivingconditions and to charge depleting strategies, as described inAppendix C.

Control Strategy DescriptionThe Ohio State team's vehicle supervisory controller uses

a combination of rule-based algorithms and the EquivalentConsumption Minimization Strategy (ECMS) to control thevehicle.

The primary objective of ECMS is to find a localminimum for an equivalent fuel metric while also satisfying anumber of equality and inequality constraints. Theseconstraints are imposed by the driver's power demand, theactuator torque limitations, the high voltage battery state ofcharge (SOC), and power availability and energy capacitylimitations. It then performs an optimization in realtime todetermine which power split is the most efficient for thevehicle for the current operating conditions. A more detaileddescription and equations for the ECMS method are given in

Appendix C. A rule-based strategy is used by the supervisorycontroller to determine the vehicle mode of operation at anypoint in time.

Unlike many rule-based strategies, the rules that governthe transition to different modes are outcomes of the vehiclearchitecture and therefore do not require extensivecalibration. Figure 7 shows how the Ohio State vehicle'ssupervisory controller uses its rule based controller to switchbetween charge depleting mode, engine start mode, chargesustaining series mode, the series to parallel transition modeand the charge sustaining parallel mode. The criteria used toswitch between modes include the battery SOC and the seriesto parallel transition vehicle speed. The team decided againstusing neural networks in their supervisory controller due tothe large amount of vehicle testing data needed to do theinitial calibration of the algorithms.

Figure 7. Supervisory Controller Mode State MachineRepresentation

Examples of the vehicle over the US06 drive cycle incharge sustaining mode are shown in and Figure 8.

Figure 8. US06 Cycle in Charge Sustaining Mode

The first subplot shows the drive cycle speed trace, theactual vehicle speed and the battery SOC. The second subplot



shows the torque traces for the engine (ICE), Front ElectricMachine (FEM) and Rear Electric Machine (REM). The thirdsubplot shows the currently selected gear in the 6-speedtransmission and the vehicle mode. Vehicle Mode 4represents charge sustaining parallel mode. Vehicle Mode 3represents charge sustaining series mode and vehicle Mode 2represents charge depleting mode. The vehicle's chargesustaining fuel economy, charge depleting range and utilityfactor weighted fuel economy that were calculated using datafrom the US06 City, US06 Highway, 505 and HWFET drivecycles are shown in Table 10.

Table 10. Fuel Economy and Acceleration Results

Support of VTS GoalsThe supervisory control algorithm selected by the Ohio

State team has a significant impact on the ability of thevehicle to meet its all-electric range, fuel economy andemissions targets. The control algorithm is responsible forfinding the most efficient power split between the engine andtwo electric machines in order to keep all three componentsoperating in their most efficient operating regions as much aspossible. Therefore it has a large impact on the vehicle'soverall fuel economy and all-electric range. The supervisorycontroller also plays a role in the regulating the vehicle'stailpipe emissions by reducing transient torque requests to theengine which can lead to emissions spikes.

Engine ControlThe second team-developed controller is the engine

control. The following sections highlight key informationregarding this controller.

Control Algorithm RequirementsThe requirements for the vehicle's engine controller are

listed in Table 8. These requirements were derived from theneeds/wants the team had for each of the different controllersand the team's previous experience in the EcoCARcompetition. The team concluded that the engine controlalgorithm should be able to receive a torque request andengine speed and output commands to allow the engine tomatch the input torque request with minimal error. Thealgorithm should also determine the best way for the engineto produce torque while meeting fuel economy and emissionsstandards.

Control Strategy SelectionTo control the various actuators on the engine, several

different strategies were considered for the engine controlcode. The topic of engine control is quite extensive and thereis not sufficient space to fully discuss in this report as theteam has been working on this topic over the duration of thefirst EcoCAR competition. The team is currently working onintegrating EGR and delayed intake valve closure forpumping loss reduction to achieve greater efficiency.

The result of the team's control design was to use strongfeed-forward control that relies on model-based air chargeestimation to estimate fuel mass required. This air chargeestimator also compensates for exhaust gas recycle anddisruptions from the variable cam system. A fuel dynamicsmodel provides additional dynamic compensation. A UEGOsensor is used with a gain-scheduled PID control on fuel massas does an additional PID control on a post-catalyst EGOsensor.

Emissions control of the engine is enhanced by the use ofa control system which uses an electrically heated catalystand air supply system to preheat the catalyst to 500 deg. Cbefore the engine starts. Furthermore, the supervisory controlreduces throttle transients to the engine by using the electricmotors to supply transient torque. The net result of thecontrol is an efficiency and low emissions engine which istightly integrated into the hybrid control system.

Control Strategy DescriptionThe Ohio State team will be largely using the same engine

control algorithm used in EcoCAR 1. This is because thesame 1.8 L Honda CNG engine as the previous competitionwill be implemented into the vehicle. This code wasdeveloped and optimized over several years using theMotohawk libraries provided by Woodward. This reuse ofhardware and software modules is a great benefit to the teamin terms of financial and control development resources.

During this competition, the team will be porting theengine control code to a block set compatible with ETAS'sFlexECU. The team will refine the engine control code anddevelop new algorithms to further decrease the fuelconsumption and emissions while maintaining the powerperformance. Improvements that will be designed andvalidated include the introduction of exhaust gas recirculation(EGR) and delayed intake valve closure (DIVC) to enhancethe already high efficiency, as well as heated fuel injectors(HFI). EGR and DIVC will raise the efficiency of normaloperation towards peak efficiency levels. Heated FuelInjectors (HFI) will complement the current emissionscontrols and electrically heated catalyst by actively reducingemissions, especially CO and THC, by up to 70%.

Support of VTS GoalsThe optimized and validated engine control algorithm will

help the Ohio State team achieve several VTS goals. Theseinclude acceleration, fuel economy, and emissions targets.The engine control algorithm is responsible for providing the



correct control actions to allow the engine to achieve thetorque request from the supervisory controller duringtransient and steady state behavior. This will help with theacceleration targets. The control algorithm will also controlmechanisms like the electrically heated catalyst, EGR valve,and delayed valve closure which will allow the vehicle tomeet the fuel economy and emissions targets.

General Control ModuleThe third team-developed controller is the general control

module. The following sections highlight key informationregarding this controller.

Control Algorithm RequirementsRequirements for the vehicles General Control Module

(GCM) are listed in Table 8. The GCM must control theactuators needed to shift the six-speed transmission, as welldo variable speed control on the various pumps and fansneeded throughout the vehicle's powertrain. In order to shiftthe transmission, two linear actuators are required to movethe shifting mechanism in both the X and Y directions. Theselinear actuators are being driven using two of the GCM's H-bridges, allowing the actuators to move in both directions.

Control Strategy SelectionA variety of different control strategies could be

employed to control the transmission actuators. These controlstrategies include open-loop feed-forward control, stand-alone PID control, compensator control, or a combination ofany of these.

Control Strategy DescriptionTo control the actuators, a feed-forward PID controller

has been developed. The feed-forward component allows thecontroller to achieve the desired response time while the PIDcomponent increases the overall accuracy of the controller. Ifnecessary, gain scheduling will be explored in futuredevelopment. This control has been implemented and will bedemonstrated at the Year 1 Competition Finals.

Support of VTS GoalsAs will be discussed in a later section, the need to

automate a manual transmission was dictated by a number ofconstraints - namely space requirements versus available off-the-shelf transmissions. In this respect, the control algorithmfor controlling the transmission is one of the key technologiesthat allow the use of a highly efficient manual transmission.This supports improvements in all of the efficiency relatedVTS goals by reducing driveline losses.

Control Algorithm and Strategy SummaryAs detailed above, the team has a very aggressive control

development plan. The architecture requires controls for threemajor systems: 1) supervisory control; 2) engine control; and3) automated manual transmission control. The team ismitigating this risk by relying on previous controls as starting

points for (1) and (2) above. The team is taking onconsiderable new development effort to address (3), however,the team's extensive use of SIL and HIL will make thispossible.

PACKAGING AND INTEGRATIONPackaging Goals

The 2013 Malibu brought a unique packaging challengeto the team compared to previous advanced technologyvehicle competitions. As detailed in the overview of thearchitecture selection, rough packaging concepts weredeveloped for each of the considered architectures to ensurethey could be packaged in the vehicle.

For the detailed design of the selected architecture, theteam's packaging goals are summarized in the following list:

• Maintaining or exceeding the high level of safety present inthe stock 2013 Malibu

• Fit all necessary components into vehicle

• Reduce impact on cargo space

• Reduce impact on interior/exterior aesthetics

• Reduce modification of structural members

• Have no impact on passenger capacity

• Maintain appropriate weight balance

• Ease of serviceability and installation

Packaging in Support of ArchitectureSelection

As described earlier in the report, packaging played alarge role in the architecture selection process. In the earlyphases of architecture selection, components were not welldefined, thus, it was difficult to make firm packaging plans -particularly in light of the sedan platform. From thesimulation side, it was also difficult to determine feasiblearchitectures from a packaging standpoint.

To deal with this issue, the CAD team first worked withgeneralized CAD models of components to determinepotential feasibility of proposed architectures. Once it wasdeemed likely to package, weight estimates were fed to thesimulation team. Eventually, the final architecture wasselected and proposed components came back to the CADteam for more refined packaging analysis. The packagingproblem was difficult; however, the initial selectedcomponents were successfully integrated into the vehicle.

Component SummaryKey powertrain components have been summarized in

tables throughout this report:

• Front Powertrain Component Summary - Table 3

• Rear Powertrain Component Summary - Table 4



• Energy Storage Component Summary - Table 5

• Controller Component Summary - Table 9

• Cooling Component Summary - Table 11

Table 11. Cooling Component Summary

Overall Vehicle Packaging DesignA full-page graphic showing the location of each of the

major powertrain components is shown in Appendix H. Agreat deal of team effort went into creating the finalpackaging design of the vehicle. This was compounded bythe relative lack of space in the sedan coupled with therelatively high complexity and component count of the OSUdesign.

Sample Packaging Design ProcessTo provide an example of the depth of the packaging

design process engaged by the team, an example is providedfrom the energy storage system design. This process is fairlytypical of the packaging design conducted for all majorcomponents.

More than a dozen conceptual layouts were consideredand evaluated for the ESS system. These early stage conceptsinvolved basic layouts in CAD with numerous assumptions.This process led to two separate ESS storage concepts for in-depth design. The first concept (Figure 9) consisted of a two-level design. This design had a lower set of 4 batteries. Ofthese 4 batteries, one battery was raised slightly to avoidinterference with a cross member. It also consisted of 3modules mounted above the REM and rear gearbox.

The second concept selected is shown in Figure 10.Similar to the previous design, this design consists of a two-level configuration. Three modules are mounted in the sparewheel well and the upper four modules are mounted above

the REM and rear gearbox. The two steps are connected by achannel that allows HV and LV wires to pass between thetwo groups of modules. The concept shown in Figure 10 wasselected as the final packaging concepts and is described inmuch greater detail later in the Energy Storage section of thereport. The design was selected based on the key benefitslisted next:

• Simplified pack assembly

• Enclosure design reduced from 8.7 ft3 to 7.1 ft3 resulting inan additional 1.6 ft3 of cargo space

• Simplified battery installment and serviceability

• Provides additional clearance for rear EM and transmission

Figure 9. First ESS Packaging Design Concept

Figure 10. Second ESS Packaging Design Concept

Front Powertrain Packaging DesignFront Powertrain Overview

The front powertrain packaging of the Ohio StateEcoCAR 2 vehicle contains the following major components:1) a Honda E85 engine, a Luk Single Disk Dry Clutch; 2) a



Parker Hannifin MPT 2104 electric machine; and 3) a GMMF3 M32 six speed manual transmission. The manualtransmission is automated with SKF linear actuators inconjunction with the Luk clutch. The front powertrain andother associated components are shown in Figure 11.

The bell housing of the M32 transmission is removed, asit no longer houses a clutch, and is replaced by a custom belthousing case. The custom housing accommodates a beltcoupling and bolts to the input of the transmission. TheParker Hannifin electric machine is the input to the beltcoupling, and is bolted to the gearbox, which supports theweight of the machine. The output of the belt coupling isfixed to the input of the transmission, as well as the output ofthe Luk clutch. The input of the clutch is fixed to theflywheel of the engine. A custom engine adapter plate boltsthe custom clutch cover to the engine. The clutch cover isbolted to the other side of the belt coupling housing.

Figure 11. Front Powertrain CAD

The placement of the front powertrain was driven by thefront axle location. In order to ensure that the axle half shaftswould not interfere with the suspension at any part of thesuspension travel, the transmission differential was carefullyplaced so that the original vehicle CV joints were concentricwith the differential output.

Key Design ConstraintsThe most critical clearance is the width of the assembly

across the vehicle. If not carefully controlled, this wouldcause interference between the engine and passenger sideframe rail or the transmission and drivers side frame rail. Thisclearance issue has been the dominant constraint on the frontpowertrain design, dictating the selection of the narrowestavailable transmission (many were considered) as well ascoupling the front electric featuring a narrow, high-power,flexible belt from Goodyear.

Key TradeoffsThe front powertrain design featured a number of

tradeoffs due to tight packaging and difficulty in findingcomponents which would meet the original specifications.These tradeoffs are highlighted below:

• Transmission - As discussed in Powertrain ComponentSelection section, the width constraint led to a particularchallenge. In the end, a transmission with a lower torquecapacity was selected.

• Electric Motor Coupling - Several different methods ofcoupling the electric motor torque to the transmission inputshaft were explored: 1) through-shaft; 2) gears; 3) dry chain;4) wet chain; and 5) flexible belt. Many of these optionsproved impossible, with (4) and (5) being the highest rankedoptions on the design decision matrix. In the end, the flexiblebelt proved the best option due to the lack of lubricationsystem. This, however, gave up a small amount of widthwhich was a critical constraint in this system.

• Transmission Actuators - The team also made tradeoffswith respect to the actuation technology. The team consideredpneumatic, hydraulic, and motor driven actuators. Electriclinear electric actuators were selected for low weight and easeof control. However, the actuators are not as capable in termsof speed and lead to longer shift times. This is overcome bythe aggressive rear motor used in the design which canprovide supplemental torque during shifts.

Rear Powertrain Packaging DesignRear Powertrain Overview

The Ohio State EcoCAR 2 vehicle will utilize a rearpowertrain system, which mounts to the AWD rear cradle.The system consists of the following major components: 1) aParker MPT 2106 electric machine; 2) a Borg WarnereGearDrive gearbox; and 3) the ESS system. Taking intoaccount the rear powertrain, energy storage system, and stockvehicle components, a rear packaging study was conducted tofind the optimal configuration of added components. The twomajor subsystems in this study are the rear electric tractiondrive and the energy storage system. The energy storagesystem is discussed earlier in the report. In this section theemphasis is on the traction drive.

Figure 12. Rear Powertrain CAD

The rear electric machine and gearbox are joined via apair of custom adapter plates. The plate mounting directly tothe Parker 2106 motor is an extended version of the stock end



plate, which saves cross-car distance in the rear powertrainpackaging. The powertrain assembly mounts directly to therear sub-frame by utilizing three rubber powertrain mounts.The two stock mounts on the rear cross-member of the sub-frame will be used to mount the powertrain assembly. Anidentical third mount will be incorporated into the design ofthe modified front cross-member of the sub-frame, which willalso be used to mount the powertrain. The rear powertrainassembly and mounting plates are shown in Figure 12.

Key ConstraintsKey constraints considered in this packaging study were:

1) location of the eGearDrive axle shafts with respect to thestock vehicle in order to maintain clearance; 2) limitations inthe angle of the eGearDrive unit for proper lubrication; 3)serviceability of the battery system; and 4) impact on cargocapacity. The positioning requirements from (1) and (2)above in particular caused interference with the rear cradlecross members - these are requirements and thus could not beavoided.

The largest issue in packaging the rear powertraincomponents was the potential interference with structuralmembers of the stock vehicle. The packaging scheme wasbased around the Borg Warner eGearDrive gearbox, whichallows power to be transferred from the rear Parker Hannifinelectric machine to the wheels. The gearbox was the largestcomponent in the rear of the vehicle, and is constrained tohaving its output aligned with the rear axles. This onlyallowed two degrees of freedom for the packaging: cross-cartranslation and rotation about the rear axle. After an initialpackaging assessment, it was clear that interference with therear sub-frame was necessary.

Key TradeoffsThe final rear powertrain configuration is an optimized

design balancing structural interference, cargo space, designcomplexity, and ease of installation. Two initial designssurfaced, the first of which housed the entire powertrainunder the vehicle to maximize cargo space at the cost ofsignificant structural interference. The second design housedthe output of the gearbox near the center of the rear cradlewith the top of both components rotated into the trunk. Thisdesign minimized structural interference at the cost of cargospace. The team determined that minimizing structuralinterference was the highest priority, so the second designwas chosen. The team decided to directly link the motor andgearbox, rejecting a proposed design utilizing a silent chaindrive. This decision was made to decrease the complexity ofthe design and increase the ease of installation.

Another key tradeoff is the ESS design described earlierin this section. There was a great deal of interconnectionbetween the electric motor system and the energy storagesystem. The selected designs provided the best overallsolution to a difficult packaging scenario.

Electrical System IntegrationVehicle electrical system integration is critical to the

function of an advanced technology vehicle. The OSU teamsplit this effort into the low-voltage system, which isdiscussed here, and the high-voltage system discussed later inthe section on the Energy Storage System.

The vehicle's 12-volt system relies mainly on the stockdistribution system with additional distribution and fusing foradded systems. The system is supplied through a DC/DC stepdown converter with a battery to buffer the voltage andprovide power when the high-voltage system is unavailable.The DC/DC Converter selected is being donated by GeneralMotors and provides a maximum of 3.3kW of power to the12V bus. The system provides power to multiple devices inthe front and rear powertrain as well as accessory devices onthe vehicle. These devices include the transmission andengine controllers, supervisory controller, and the batterycontrol module. Other accessory devices such as the centerstack display are less critical, but provide an importantfeature to the user. Proper fusing techniques are appliedaccording to applicable AWG standards with particularattention to the potential for high encountered temperatures inautomotive applications.

Vehicle Weight AnalysisBaseline Weight Analysis

The first stage in the analysis was to strip out all unneededpowertrain components and systems from the stock vehicle toprovide a baseline weight of the chassis without thepowertrain. This resulted in a weight of 1262 kg. The mass ofthe fixed powertrain components (i.e. things that could not bealtered) were added back in. The fixed weight wasdetermined to be 474 kg giving a total weight of 1736 kgwhen added to the base vehicle.

The next phase involved estimating the weight of addedsupport systems such as mounting brackets, wiring, andcooling. These values were estimated using measured datafrom the EcoCAR 1 vehicle and reasonable assumptions suchas scaling the weight of the battery support system (coolant,cooling plates) with the battery pack total weight. Theestimated weight of support systems is 108.6 kg giving a totalestimated weight of 1897.9 kg for the OSU EcoCAR 2vehicle - an increase of 308.3 kg from the stock ChevroletMalibu. The results show that the front axle will support 974kg while the rear axle will support 874 kg. The front to reardistribution of weight is 53% to 47%. These values are withincompetition rules.

Weight Reduction PotentialBased on the above analysis, the team only has direct

control over the “support system” mass being added to thevehicle. This represents only 6% of the mass of the vehicle.The remaining balance is from essential stock vehiclestructure/components and the weight of the added powertraincomponents.



An additional analysis was conducted to determine thesensitivity of the vehicle to weight and aerodynamic drag.The results show that the vehicle is sensitive to both, costingapproximately 3.3 mpg for each additional 100 kg of weightand approximately 1.32 mpg for each 0.01 increase in dragcoefficient. Due to this, the team sought out strategies toreduce losses of all kinds, but particularly to reduce weight.For perspective, the addition of the large battery pack adds asignificant amount of weight to the design - but this is offsetby the great benefit of the battery for EV operation. Thus, theincrease in weight of the OSU vehicle is a necessary step inachieving the team's selected architecture.

For the support systems, the team has employed thefollowing weight saving strategies:

• Use of Aluminum - unless required for welding to steel,aluminum is the first material considered for team designs

• Use of Composites - in addition to a composite hood, theteam is exploring the use of composites in the energy storagesystem packaging

• Aggressive Designs - all designs are scrutinized from theperspective of weight in terms of materials selection and thesmallest factor of safety deemed acceptable to meet safetyrequirements

• Minimization of Fluid Volume - minimization of fluidvolume though good routing and design; use of air coolingfor batteries

• Minimization of Wire Size and Length - configuration andlocation of electrical components chosen to minimize lengthand size of three phase and DC cables

For the components and vehicle structure, accounting for94% of the vehicle mass, the team is looking at the following:

• Light-Weight Seats - existing relationship with sponsor mayprovide opportunity for lightweight seats to be donated

• Composite Hood Replacement - considering a custom hoodmade from composite material for both aerodynamic andweight saving purposes

To counter the inevitable increased weight of the vehiclearchitecture, the team is also looking into the followingtechniques to reduce vehicle losses:

• Wheel Hub Covers - reduce turbulent flow through andaround the wheels

• Rear Wheel Entry Covers - reduce drag associated with rearwheels

• Low Rolling Resistance Tires - reduce road load of thevehicle due to reduced rolling resistance

• External Rearview Mirror Replacement with Cameras -reduces aerodynamic drag from side mirrors

• Solar Panel on roof - reduces electrical load on the 12Vsystem with potential for high-voltage charging (EcoCARrules do not currently allow this)

• Advanced Thermal Management - uses heat available fromengine/motors/batteries to accelerate warm-up of powertrainlubricants

• Waste Heat Recovery - looking into thermoelectrics torecapture energy lost due to heat generated by the engine

Packaging SummaryBoth the front and rear powertrain areas proved to be

packaging challenges. The team arrived at designcompromises that were able to accommodate the tightpackage without having to relax the original VTS goals. Thiswas due to clever packaging design, but more importantly,because of considering packaging in a meaningful way duringthe architecture selection process. This resulted in a designwhich could indeed be packaged. Although the vehicle designadds weight, the majority of the weight increase is anunavoidable attribute of the aggressive electric tractionsystem. This weight, of course, provides additional efficiencyto the system. Despite this, the team has proposed severalweight reduction strategies and other options to improve theoverall efficiency of the vehicle.

ESS DESIGN AND INTEGRATIONESS Impact on VTS

The ESS has an extremely important impact on the team'sability to meet their VTS goals. To determine the impact ofbattery pack size on the vehicle's utility factor weighted fueleconomy, the team performed a fuel analysis with ArgonneNational Lab's GREET software. Details of this analysis wereprovided earlier in the report in the context of architectureselection. The results demonstrated that using theperformance gains from using the highest energy packavailable from A123 Systems would outweigh the negativeissues of weight and packaging complexity.

The ESS also supports the team's VTS goals by enablingthe vehicle's engine to have start-stop operation. This requiressupplemental systems so that that both A/C and 12V areavailable when the engine is stopped. To fulfill theserequirements, the team decided to use the high voltage A/Cunit and the DC-DC converter being offered by GeneralMotors to the EcoCAR 2 teams. The team's goals of having avehicle with a large utility factor weighted fuel economy, afully functional EV mode, and start-stop operation on theengine led the team to select the A123 seven module 15s3p340V battery pack.

ESS Design GoalsAs described in the architecture selection section, the

largest ESS system was selected based on a comprehensiveanalysis of the impact of this key system. Although there aremany reasons for this, the use of the utility factor concept incompetition performance assessment in key events was thestrongest driver. With this major decision made, the other keydesign decisions that impacted the ESS design were the



selection of electric traction components and the manner inwhich the supervisory control system uses them.

The following subsections highlight the key design targetsin each of three critical areas: Electrical, Thermal, andPackaging.

ESS Electrical DesignESS Electrical Design Targets

The electrical design goals encompass issues related tocable sizing, fusing, EMI, and other concerns. The overallgoal of the design is to provide full-function electricoperation of the vehicle exceeding VTS performance targets.These design targets are driven mainly by the following: 1)Pack current capability; 2) Traction component powercapability; and 3) Supervisory control.

To determine the design targets of the ESS system,EcoSIM was used to run simulations for each of the fourcycles of interest to the EcoCAR 2 competition (505, US06City, US06 Highway, and HWFET), the E&EC event cycleused in EcoCAR, an acceleration trial, and a gradesimulation. These simulations focused upon generatingrequirements for continuous and peak current, state of chargewindows, heat generation, and peak and minimum voltage.These results were then used to determine a set of designtargets described below. In addition to these, voltage andcurrent limits imposed by motors and inverters were alsoconsidered.

Table 12. Key Energy Storage System Design Targets

ESS Electrical DesignThe electrical system designed operates off of a 340 V

battery pack. Each module of the battery interfaces over CANto the battery control module which monitors cell temperatureand voltages as well as managing cell balancing. The ESSelectrical diagram can be found in Appendix G. The teamimplemented a dual fuse technique located mid-pack betweenbattery modules three and four. A 350 amp fuse is used toprotect the battery against high current faults and a 250 ampslow blow fuse is used reduce to wire size.

Arriving at this fusing solution required considerableanalysis. The traditional fuse selection curves provided byfuse manufacturers provide time to blow for constantcurrents. The high momentary peaks of an electric tractiondrive are not well represented by this data. To design the

system, the team ran multiple simulations on aggressive drivecycles to determine the maximum currents that the ESSelectrical system would encounter.

The desired fusing strategy is required to accomplish fourthings: 1) pass momentary current pulses of 800 amps for tenseconds during accelerations; 2) quickly protect the batteryand inverter in the event of system short; 3) have acontinuous rating better than 180 amps with a safety marginto enable the competition grade test in all-electric model; and4) have a continuous rating as low as possible to minimizewire size. The team arrived at a series fuse combinationswhich met these conditions. A 250 amp slow blow fuseallows the passage of high current pulses, passes a continuous180 current with a safety margin, and yet allows for a modestwire size in the system. A 350 amp semiconductor fuse (i.e.fast blow) provides quick response for short circuits. Becauseof the higher rating, it is also more resistant to momentaryhigh current pulses, such as during an acceleration event.

Once the team was able to properly fuse the pack, theteam created an efficient and robust wiring system. The teamfound that most ampacity tables developed by the NationalElectric Code (NEC) and other organizations were tooconservative to provide an appropriate solution to the ESSelectrical system. To fix this, the team ran many wire tests forcontinuous currents and found the steady-state temperaturerise for the cable in order to determine a safe and efficientwire ampacity. A 300 amp test was conducted which resultedin only a 50 deg. C temperature rise. Given the 150 deg. Crating of the wire and the fact that the system is fused to 250A, the system has a sufficient safety margin.

The 340 V ESS Electrical System shown in Appendix G,consists of four primary devices: the battery control module(BCM), the electrical distribution module (EDM), the currentsense module (CSM), and the battery modules. Each of thesedevices ensures the ESS safely provides power to the highvoltage power system in the vehicle. Located mid-pack, twofuses are inserted to protect these devices against high currentfaults and to reduce wire-size for better packaging and weightsaving. To increase the safety of the ESS enclosure, the teamuses a manual service disconnect (MSD) and a high-voltageinterlock loop (HVIL). The MSD allows for safe servicing ofthe ESS and the HVIL contains detection for all vehiclecritical devices. If any of the devices trip the HVIL, the BCMimmediately disables the high voltage power system. Finally,to connect the ESS high voltage components, the team will beusing a 1/0 AWG high-temperature high-flexibility wire ratedto 150°C with a continuous current capacity in excess of 250amps. The diagram also notes fusing and wire sizes for allother key high-voltage components, such as inverters, thecharger, and the DC/DC converter.

ESS Thermal DesignESS Thermal Design Targets

The thermal system is responsible for managingtemperature of the vehicle's ESS system. Key thermal design



goals of the system are: 1) provide full-function electricoperation under all realistic competition thermalconsideration; 2) provide safe operation in any environmentalcondition; and 3) minimize the system weight and complexityof the thermal management system. The thermal system wasdesigned based on thermal loads determined from EcoSimsimulations. Based on EcoSIM, the heat generated for eachdriving cycle is shown in Table 13.

The thermal system was designed to keep the batterytemperature under 48°C when subjected to the above heatloads. This will provide safe operation of the batteries in anyconditions.

Table 13. Thermal Loads for Various Drive Cycles

ESS Thermal DesignHeat will be removed from the modules through custom

made, forced air-cooled, heat exchangers that will also serveas the base of the battery case. The modules will be mounteddirectly to the heat sink base vertically so the bottom of themodules will be cooled. To achieve forced air cooling, twoair blowers will be used. These air blowers will provideairflow of 38 scfm. This cooling design coupled with thecontrol strategy provides adequate cooling for all drivingcycles considered. Table 14 shows the final temperature after50 miles (the expected all electric range) for various drivecycles for the expected worse case conditions the vehicle willexperience. This design required extensive heat transferdesign and simulation using a dynamic thermal model of thesystem.

Table 14. Temperature of Battery for 45°C Ambient and30°C Initial Battery Temp

As can be seen from this data, the battery temperaturenever reaches the maximum temperature of 48°C. If thistemperature were to be reached, the supervisory controlwould enter a mode (i.e. parallel mode) which has drastically

reduced electric demand. In the event that the system waspushed into a critical temperature, the system would enter alimp home mode and eventually disconnect the pack fromservice.

ESS Packaging DesignESS Packaging Design Goals

The ESS packaging system is responsible for mountingthe ESS to the vehicle and containing the system safelywithin the vehicle. Key packaging design goals of the systemare: 1) Reduce mass of the packaging solution; 2) Exceed allapplicable structural requirements; 3) Exceed all applicablesafety requirements; and 4) Minimize loss of passenger/cargospace. The mounting strategy used must also be robust. Itmust be proven that the system can withstand the followingloads: a 20 g side-to-side, back-to-front, and front-to-backforces. The battery pack selected by Ohio State has a mass of151 kg, or 21.57 kg per battery module.

ESS Packaging Design GoalsThe ESS packaging strategy utilizes the cooling plates

discussed previously as mounting plates. Having the coldplates serve a dual purpose allows for weight reduction andan increase in cargo space. The cooling plates also serve as avery sturdy base for the battery system. It is able to withstandthe loads mentioned previously with a minimum factor ofsafety of 2.5 through extensive FEA. In addition to FEA onthe cooling plates, strength calculations were conducted onthe mounting bolts as well as the sheet metal the ESS isbolted to. For the mounting bolts, shear and bearing stresseswere calculated used the same loads that were used to test thestrength of the cooling plates. This resulted in a minimumfactor of safety for the anchor bolts of 5.25. The tearing,bearing, and shear stress were then calculated for the sheetmetal the cooling plates are mounted to. After applying thesame loads, the minimum factor of safety seen in the sheetmetal is 2.9.

The batteries are placed in the rear of the vehicle in a stepconfiguration. This configuration was necessary in order toavoid interference with structural cross members as well asthe rear electric motor and gearbox. The bottom packs rest ona cooling plate that is located where the spare tire waspreviously located. The packs are contained within a box thatwill be integrated into the sheet metal floor and supported bya steel cage structure. To accommodate the stepped packs, araised, structural floor will be built up to support the coolingplate and modules, at the same time closing off the areacontaining the rear electric motor and transmission. Figure 10shows a view of the pack in the vehicle before the lid isinstalled and Figure 13 shows it after the lid is installed.

The overall packaging design allows for easyserviceability. The system utilizes removable plates thatallow the team to assemble the pack from multiple angles.Once fully assembled, the battery pack is safely sealed untilthe MSD is pulled and the HVIL loop is broken. This



combination of easy and safe service provides for a well-balanced ESS.

Figure 13. ESS with Covers

SUMMARY/CONCLUSIONSThe OSU EcoCAR 2 vehicle has been designed according

to the rigorous design process described in this report. Thisprocess started with identification of customer needs andwants which in turn led to high-level vehicle specifications.These specifications then trickled down through thearchitecture selection process, subsystem design, componentdesign, and control development process. This cascade ofspecifications and the resulting verification and validationplan has been captured by the team for use as the design isrealized in hardware and software. The architecture thatemerged from this process features a number of uniquetechnical aspects, such as an in-house developed automatedmanual transmission, sophisticated supervisory controls, andteam-developed engine controls. The overall design will meetor exceed the team's VTS goals and result in an exceptionallearning experience for the team.

REFERENCES1. Paganelli, G., Brahma, A., Rizzoni, G., Guezennec, Y., G.: “Control

Development for a Hybrid-Electric Sport-Utility Vehicle: Strategy,Implementation and Field Test Results”, 2001 American ControlConference, June 2001.

2. Paganelli, G., Ercole, G., Brahma, A., Guezennec, Y., and Rizzoni, G.,“General supervisory control policy for the energy optimization ofcharge-sustaining hybrid electric vehicles,” JSAE Review, vol. 22, no. 4,pp. 511-518, 2001.

3. Musardo, C., Rizzoni, G., Guezennec, Y., and Staccia, B., “A-ECMS:An Adaptive Algorithm for Hybrid Electric Vehicle EnergyManagement,” European Journal of Control, vol. 11, no. 4-5, pp.509-524, 2005.

4. Gu, B. and Rizzoni, G., “An adaptive algorithm for hybrid electricvehicle energy management based on driving pattern recognition,”Proceedings of the 2006 ASME International Mechanical EngineeringCongress and Exposition, 2006.

5. Stockar, S, Marano, V, Canova, M, Rizzoni, G., A Control Study for theEnergy Management of Plug-in Hybrid Electric Vehicles withApplications to Real-World Driving Cycles, IEEE Transactions onVehicular Technology, 2011.

6. Onori, Serrao S. Rizzoni, G., “Equivalent Consumption MinimizationStrategy as a realization of Pontryagin's minimum principle for hybridelectric vehicle control”, submitted to 2009 American ControlConference, St. Louis, Missouri, USA June 10 - 12, 2009.

CONTACT INFORMATIONFor any questions regarding the work presented in this

paper, please contact Ohio State University EcoCAR TeamCo-Advisor Dr. Shawn Midlam-Mohler at [email protected] or Ohio State University EcoCAR Team LeaderKatherine Bovee at [email protected].

ACKNOWLEDGMENTSThe team would like to thank the many people and

entities that make EcoCAR 2 possible, including the headlinesponsors General Motors and the U.S. Department of Energy.Without the support of the numerous sponsors this invaluablelearning experience would not be possible for the team.

DEFINITIONS/ABBREVIATIONSADC - Analog to Digital ConversionAVTC - Advanced Vehicle TechnologyAWD - All-Wheel DriveAWG - American Wire GaugeCAD - Computer Aided DesignCAN - Controller Area NetworkCFD - Computational Fluid DynamicsCNG - Compressed Natural GasCO - Carbone MonoxideCSM - Current Sense ModuleCVA - Competitive Vehicle AssessmentDAC - Digital to Analog ConversionDFMEA - Design Failure Mode and Effects AnalysisDIVC - Delayed Intake Valve ClosureE&EC - Emissions and Energy ConsumptionECU - Electronic Control UnitEDM - Electrical Distribution ModuleEGO - Switching Exhaust Gas Oxygen SensorEGR - Exhaust Gas RecirculationEM - Electric MachineEMI - Electromagnetic InterferenceE-REV - Extended-Range Electric VehicleESS - Energy Storage SystemEVAP - Evaporative Emissions ControlFEM - Front Electric MachineFTA - Fault Tree AnalysisGCM - General Control ModuleGHG - Greenhouse GasesGM - General Motors Greenhouse Gases, RegulatedGREET - Emissions and Energy Use in Transportation



mailto:[email protected]



HEV - Hybrid Electric VehicleHFI - Heated Fuel InjectorsHIL - Hardware-in-the-LoopHV - High VoltageHVIL - High-Voltage Interlock LoopI/O - Input/OutputICE - Internal Combustion EngineLV - Low VoltageMABX - MicroAutoBoxMPG - Miles per GallonMPGGE - Miles per Gallon Gasoline EquivalentMSD - Manual Service DisconnectNEC - National Electric CodeOSU - Ohio State UniversityPHEV - Plug-in Hybrid Electric VehiclePID - Proportional, Integral, DerivativeREM - Rear Electric MachineSI - Spark IgnitionSIL - Software-in-the-LoopSOC - State of ChargeTHC - Total HydrocarbonsTP&P - Testing Plan and ProceduresUEGO - Universal Exhaust Gas Oxygen SensorVDP - Vehicle Development ProcessVTS - Vehicle Technical SpecificationsWTW - Well to Wheel



APPENDIX A: ECOCAR 2 DESIGN PROCESS V-DIAGRAM

APPENDIX



APPENDIX B: OSU ECOCAR 2 VEHICLE TECHNICAL SPECIFICATIONS

APPENDIX C: EQUIVALENT CONSUMPTION MINIMIZATION STRATEGYMinimizing the fuel consumption (or emissions) during a driving cycle is an optimal control problem in which the solution

depends on the entire driving cycle. The solution of the global problem is difficult in simulation and impossible in real time, since ateach instant the future part of the driving cycle is unknown. The Equivalent Consumption Minimization Strategy (ECMS) wasintroduced by Paganelli et al. [1,2] as a method to reduce this global problem to an instantaneous minimization problem, which issolved at each instant, without use of information regarding the future. This algorithm was first successfully implemented in theFutureTruck 2000 competition [1].

The ECMS is based on the concept that, in charge-sustaining vehicles, the difference between the initial and final state of charge ofthe battery is very small, negligible with respect to the total energy used. This means that the electrical energy storage is used only asan energy buffer. Since all the energy ultimately comes from fuel, the battery can be seen as an auxiliary, reversible fuel tank: theelectricity used during the battery discharge phase must be replenished at a later phase using the fuel from the engine (either directlyor indirectly through a regenerative path), and vice-versa. In fact, a particular operating point of the powertrain leads to two cases:

(a). the battery power is positive (discharge case): a recharge using the engine will produce some additional fuel consumption;

(b). the battery power is negative (charge case): the stored electrical energy will be used to alleviate the engine load for runningthe car, which implies a fuel saving.

In both cases, the use of electrical energy can be associated to virtual (future) fuel consumption, which can be summed to theactual fuel consumption to obtain the equivalent fuel consumption:



(1)

where is the fuel mass flow rate (instantaneous fuel consumption), Qlhv is the lower heating value of the fuel (energy content per

unit of mass), Pfuel is the fuel power, Press the electrical power exchange with the energy storage system, and the virtualinstantaneous fuel consumption corresponding to the use of electrical energy. s is called equivalency factor and is used to convertelectrical power into fuel power; it plays an important role in the ECMS, as will be shown later. RESS (rechargeable energy storagesystem) is used instead of battery for more generality, since there are other electrical energy storage devices available (mainlyelectrochemical capacitors, or supercapacitors).

The concept of equivalent fuel consumption is tied with the necessity of attributing a meaningful value to the equivalencyparameter s. This parameter is representative of future efficiency of the engine and the RESS, and its value affects both the chargesustainability and the effectiveness of the strategy: if it is too high, an excessive cost is attributed to the use of electrical energy andtherefore the full hybridization potential is not realized; if it is too low, the opposite happens and the RESS is depleted too soon (lossof charge sustainability). It has also been shown [3] that very good results, comparable with the optimal solution of the global problemcalculated off-line, are obtained by using two values of s, one for charging (Sch) and the other for discharging (Sdis), each of themconstant during a driving cycle. These values are different for different driving cycles and can be adapted during vehicle operationusing adaptive ECMS algorithms [3,4]. The concept of adaptive ECMS was demonstrated in the FutureTruck 2004 competition [3]and at ChallengeX 2006 [4]. In the case of a plug-in HEV, however, charge-depleting behavior is desirable and therefore theequivalence factor can be selected in such a way that it allows to discharge the battery to the lower acceptable limit while minimizingthe desired control objective. In [5] it is shown that it is possible to modify the ECMS algorithm to account for charge depletion.

Finally, it should be noted that it has also been formally shown that the ECMS algorithm, which was developed based on physicalreasoning, is in fact equivalent to the well-known optimal control solution known as Pontryagin's Minimum Principle, and is thereforea theoretically optimal solution if properly implemented [6].

APPENDIX D: ARCHITECTURE SELECTION PROCESS



APPENDIX E: ARCHITECTURE SELECTION MATRIX

APPENDIX F: PARALLEL-SERIES PHEV ARCHITECTURE



APPENDIX G: ESS SCHEMATIC



Bovee et al / SAE Int. J. Fuels Lubr. / Volume 5, Issue 3(November 2012)

APPENDIX H: VEHICLE PACKAGING DESIGN

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Documents

Design of a Parallel-Series PHEV for the EcoCAR 2 Competition