機械制造專業(yè)外文翻譯

外文原文:UsinganAdvancedVehicleSimulator(ADVISOR)toGuide:HybridVehiclePropulsionSystemDevelopmentKeithB.WipkeNationalRenewableEnergyLaboratory,Golden,COMatthewR.CuddyAbstractAnadvancedvehiclesimulatormodelcalledADVISORhasbeendevelopedattheNationalRenewableEnergyLaboratorytoallowsystem-levelanalysisandtrade-offstudiesofadvancedvehicles.BecauseofADVISOR'sfastexecutionspeedandtheopenprogrammingenvironmentofMATLAB/Simulink,thesimulatorisideallysuitedfordoingparametricstudiestomapoutthedesignspaceofpotentialhighfueleconomyvehicles(3X)consistentwiththegoalsofthePartnershipforNewGenerationofVehicles(PNGV).Fiveseparatevehicleconfigurationshavebeenmodeledincluding3lightweightvehicles(parallel,series,andconventionaldrivetrains)alongwith2vehicleswith1996vehicleweights(parallelandconventionaldrivetrains).Thesensitivityofeachvehicle'sfueleconomytocriticalvehicleparametersisthenexaminedandregionsofinterestforthevehiclesmappedoutthroughparametricstudies.Usingthesimulationresultsforthesevehicles,theeffectofhybridizationisisolatedandanalyzedandthetrade-offsbetweenseriesandparalleldesignsareillustrated.AdvancedVehicleSimulationModel:ADVISORInNovemberof1994,NREL'sCenterforTransportationTechnologiesandSystemscreatedasimulationmodelforadvancedvehiclescalledADVISOR(ADvancedVehIcleSimulatOR)inthegraphical,object-orientedprogramminglanguageofSimulink/MATLABfromtheMathWorks,Inc.ThemodelwascreatedinsupportofthehybridvehiclesubcontractswiththeautoindustryfortheDepartmentofEnergy.ADVISORapproximatesthecontinuousbehaviorofavehicleasaseriesofdiscretestepsduringeachofwhichthecomponentsareassumedtobeatsteadystate.Thatis,ateachtimestep,theeffectsofchangingcurrent,voltage,torque,andRPMareneglected.Thisallowsefficiencyorpowerlosstables,whicharegeneratedbytestingadrivetraincomponentatafixedtorqueandRPM(andcurrentandvoltage,ifapplicable),tobeusedtorelatethepowerdemandsofthecomponentsateachtimestep.AsignificantadvantageofusingamodelthatisintheSimulink/MATLABenvironmentistheflexibilityandeaseofchangingthemodel,suchasreplacingonecontrolstrategyorregenerativebrakingalgorithmwithanother.MATLABalsoallowseasyplottingofresultsthatmakesdetailedanalysisofvehicleconfigurationspossible.ADVISORisdrivenbytheinputdrivingprofileswhichcanbetheclassicspeedvs.time,suchasthefederalurbandrivingschedule(FUDS),oraspeedandgradevs.timedrivingprofile.Withagivendrivingprofilegoal,ADVISORthenworksitswaybackwardsfromtherequiredvehicleandwheelspeedstotherequiredtorquesandspeedsofeachcomponentbetweenthewheelsandtheenergysource,whichiseitherfuelfromthehybridpowerunit(HPU)orelectricityfromthebatteries.Limitsforeachofthecomponentsareincluded,sotheactualspeedvs.timeprofilecomputedistheonethatiswithinthelimitsofallcomponentsandincludesallcomponentlossesandvehicledrag.Figure1showsthetopleveloftheserieshybridmodelinADVISOR.Figure1:ToplevelofADVISORserieshybridmodelValidationofthemodelandcorrelationwithothervehiclesimulationsisextremelyimportanttoestablishthecredibilityofamodel.Throughsubcontractswithuniversityteamswhohavebuiltandtestedsuccessfulhybridvehicles,NRELhasacquiredmanyvalidatedcomponentmodelsthatincludequantifieduncertainties,increasingthecredibilityofthatdata.Finalvehicle-levelvalidationincludingdetaileduncertaintyanalysisisscheduledtobecompletedinSeptember,1996.Inthemeantime,correlationwithestablishedpublicvehiclemodelshasbeenperformed,inadditiontosomecorrelationswithproprietarymodelsintheautomotiveindustry.Basedonthesecomparisons,ADVISORappearstobewithin2%ofmostmodelsbasedonidenticalinputs.Thus,minimaluncertaintyinAdvisor’sresultsisintroducedbyitsalgorithms;uncertaintyintheinputdatawillbetheprimarysourceoftheuncertaintyinAdvisor’sresults.Ttherefirreofallinputdataforthesimulationsinthisanalysisisspecifiedbelow.VehiclesModeledandAssumptionsFivedifferentvehicleconfigurationsweremodeled.BothseriesandparallelhybridswithverylowmassesandhighlyEfficientdrivetrainsweremodeledinordertoobtainPNGV-likehybridvehiclesthatachievedacombinedcity/highwayfueleconomyof80mpg.Thesearereferredtoas"3X"vehiclesbecausetheyget3timesthefueleconomyofaconventionalvehiclewithacombinedcity/highwayfueleconomyof26.6mpg(PNGVbaseline,PNGVProgramPlan).Athirdconfigurationwasobtainedbyunhybridizingthosevehiclestocreateaconventionalvehicle.Thefourthandfifthvehicleconfigurationswerecreatedbytakingaconventionalvehicle(atroughly1.45Xduetoadieselengineandmanualtransmission)andmakingitaparallelhybrid.Table1providesthekeydifferencesbetweenthefivevehicleconfigurationsmodeledandthebaselinefueleconomyforeachvehicleconfiguration,whileTable2givesthesourcesfortheinputdata.Table1:KeyParameterValuesforVehicleConfigurationsModeledVehicleConfig3XParallelHybrid3XSeriesHybrid2.46XLightWt(nonhybrid)1.45XConv.(diesel)1.70XParallelHybridMass(kg)1000.0001000.0001000.0001611.0001611.000BatteryCap.(kWh)1.1003.700n/an/a1.800PeakHPUPower(kW)31.00030.00047.00077.00052.000PeakMotorPower(kW)12.00041.000n/an/a20.0000.4000.4000.4000.7000.700Crollingresistance0.0080.0080.0080.0110.011City(mpg)73.80072.30056.10033.80040.700ScalingHighway(mpg)94.30093.60082.10047.00052.800Combined(mpg)81.80080.50065.40038.70045.300Sinceaccelerationtimefrom0-60mphandgradeabilityat55mphareperformancerequirementsforallvehicles,theHPU,whichinthiscaseisanAudi5-cylinderturbodieselengine,andtheelectricmotorhavebothbeensizedsothatthevehiclesmeettheseperformancetargets.Onemajorassumptioninthescalingofthesetwocomponentsisthatthetorque/speedpowerlossmaps(equivalentinformationasinefficiencymaps)canbescaledbysimplyscalingthetorquescaleonthemap.Itisknownthatthisisnotthemostaccuratescalingmethod,butwasusedforlackofanavailableandjustifiablescalingalgorithm.MassThesourceofthedataforthemassoftheconventional1.45XconventionalvehicleandthehybridizedversionofthisvehiclecamefromtheOTAreportforacurrentFordTaurus.Forthe3Xvehicles,themassof1000kgisroughlythemassforthe"AdvancedConventional"vehiclefortheyear2015fromtheOTAreportinwhichalmostallmetalcomponentsaremadeofaluminum.Thisiscertainlyasignificantreductioninmassfromtoday'svehicles;thisvaluewasusedtoallowtheefficienciesforothercomponentsandparameterstostaywithintoday'stechnologiesoratleastthePNGVgoals.HybridControlStrategiesTheserieshybridusesasimple"thermostat"on/offstrategytooperatetheHPU,withtheHPUoperatingatafixedtorqueandspeedpointwhenitison.Inthisstudy,theHPUturnsonwhenthebatteries'state-of-charge(SOC)dropsbelow40%andturnsoffwhentheSOCrisesabove80%.Theparallelhybridcontrolstrategyhastheeffectofusingthebatteriesforhighlytransientvehiclelaunches,unlessthebatteriesaresolowthattheyneedtobecharged.Itcanbedefinedasfollows,with"high"SOCdefinedas60%and"low"SOCdefinedas50%:TheHPUdoesnotidle(itturnsoffwhennotneeded).Themotorperformsregenerativebrakingregardlessofthebatteries'SOC.TheHPUgenerallyprovidesthepowernecessarytomeetthetraceandthemotorgenerallyhelpsifnecessary,withthefollowingexceptions:whenthebatteries'SOCislowtheHPUlaunchesthevehicleandprovidesextratorquetorechargethebatteries,andwhenthebatteries'SOCishigh,theelectricmotoronlylaunchesthevehicleandno

HPU-chargingofthebatteriesoccurs.Table2:SourcesofDataforSimulationInputsandPerformanceRequirementsVehicleParameterValuesUsedSourceofInputDatacdA0.4,0.7m2PNGVGoals,Moore,T.CCrolling-resistance0.008,.011OTATransmissionEfficiencies:5spdo(parallel,conventional)/1spd.(series)92%/98%AutomotiveEngineering,1996HeatEngine(HPU)Scaled85kWTDIDieselStock,D.,1990Motor/ControllerScaled75kWACInductionLesster,L.,1993EnergyStorage:BatteriesHorizon12N85Electrosource0-60mphtime12.0secondsPNGVGoalsGradeabilityat55mph6.5%indefinitelyMorestringentthanPNGVgoal,whichis6.5%for20MinutesFuelEconomyCalculationToaccountforchangesinthebatterypack'sSOCduringatestcycle,asimplifiedversionoftheproposedSAEHybridVehicleTestProcedureisbeingused.Tocomeupwiththecityfueleconomy,twoFUDSarerunback-to-backfromahighSOCandthenfromalowSOC,causingadecreaseandanincreaseinbatterySOC,respectively.AsimplelinearinterpolationisthenusedtopredictthefueleconomyestimateforthevehicleifthebatterieshadnonetchangeinSOC.Thisensuresafaircomparisonbetweenconventionalvehiclesandhybridvehiclesbyaccountingforanyelectricalenergysurplusordeficitinthehybridvehicle'sbatterypack.WithoutsuchaccountingforthechangeinSOCofthebatterypack,thehybridmightappeartohaveanextremelyhighfueleconomyduetoelectricenergybeingusedinplaceoffuelenergy.SensitivityofFuelEconomytoKe^VehicleParametersAsensitivityanalysisofthekeyparametersforasimulatedvehicleillustrateshowsensitivetheoutput(fueleconomyinthiscase)istochangesintheinputparameters.Thisallowsaside-by-sidecomparisonoftheinputparametersinordertofocusontechnologyareasthatareimportanttothefinalfueleconomy.Inadditiontotherelativecomparisonspossible,italsoprovidesnumbersfromwhichfueleconomychangesduetoinputparameterchangescanbeeasilycalculated.Foreachofthefivebasecasevehicleseachofthekeyparameterswasadjustedupby5%anddownby5%,resultingintwopointsfromwhichtheslopewascalculated.Notethatthesecoefficientsareusefulbeyondthe10%spreadoverwhichtheywerecalculated,buttheabsolutevalueoftheresultstheypredictshouldn'tbetrustedbeyondabout+/-10%.Forthefivevehiclesmodeledasensitivityanalysiswasperformed,andtheresultsareshowninthebarchartofFigure2.RefertoTable1forthebaselineparametersforeachofthefivevehicleslistedinthefigure.NoticethatthesensitivitycoefficientfortheHPUforallfivevehiclesis1.0.Thismeansthatfora1%increaseinengineefficiency,therewillbea1%increaseinfueleconomy.Sincetheengineistheprimeenergyconverteronboardahybridorconventionalvehicle,thisisnotsurprising,butisstillimportanttokeepinmind.BecauseofthislargesensitivitytoHPUefficiency,thereissignificantindustryandgovernmenteffortplacedintoresearchongasturbines,advanceddiesels,stirlingengines,andfuelcells.Figure2:SensitivityofFuelEconomytoKeyVehicleParameters

esErq-AesErq-A.=弟-an』.saEME-lo1.2fl9土白財0,2-6.3心-a.afrt^_HPUC_D"AC__JEA<xe*mric^da^bjtierytta^motorTheresultsinFigure2showthatthesensitivitycoefficientsforthebatteryefficiency(eta_battery)andthemotorefficiency(eta_motor)forthe3Xseriesvehicleareroughly3timesthoseoftheparallelvehicles.Thereasonforthisisthatsinceallofthepowertothewheelsfromaserieshybridcomesfromtheelectricmotor,higherpowerandhencehigherpowerlossesareexperiencedinthemotor.Also,forserieshybridsmoreenergyispassedthroughthebatteriesthaninparallelvehicles,incurringlargerlossesinthebatteries.Intermsoftechnologyrisk,thisindicatesthatseriesHEVsaremoreaffectedbyefficiencyimprovementsinthemotorandbatteriesthanparallelhybrids,andareatagreaterriskofnotmeetingfueleconomygoalsifanticipatedimprovementsdonotcomethrough.Thefourparametersbelowtheaxisareparametersthatdecreasefueleconomywhentheyareincreased.Thegoalistokeeptheseparametersaslowaspossible.Taketheexampleofminimizingaccessoryloadsforaparallel3Xvehicle:forevery1%decreaseinaccessoryload,thereisa0.24%increaseinfueleconomy.Withabaselineaccessoryloadof800W,a10%reduction(80W)resultsina2.4%increaseinfueleconomy.Theseresultsallowafueleconomytradeofftobequantifiedforadditionalfeaturesonacarsuchasdaytime-runninglights.MappingouttheHEVDesignSpaceThroughParametricStudiesFigure3showsfueleconomycontourscomputedwithADVISORasafunctionofaverageHPUefficiencyandvehiclemassforaparallelhybridvehiclewiththeaerodynamicdragandrollingresistanceofthe3XparallevehicleinTable1.Notethatthe80mpgfueleconomycontouristheonethatdefinesthefueleconomygoalforthePNGV.TwovehiclemassesofinterestFigure3areat1000kgandjustabove1600kg,thetwomassesusedintheconstructionofthe5vehicleconfigurations.Itisclearfromthisgraphthatweightsavingscoupledwithdragreductionisstillnotenoughtogetto80mpg(3X)fromtoday'sconventionalsparkignitionenginewhichhasanaverageHPUefficiencyof~25%.Themasswouldhavetobemorethancutinhalf,whichisnotfeasibleinthenearfuture.Likewise,thisgraphshowsitisdifficulttoachieve3XwithonlyHPUefficiencyimprovements,hybridization,andvehicledragreduction.Extrapolatingfromthischart,weinferthata3Xvehicleat1600kgwouldrequireanaverageHPUefficiencyof47%,wellbeyondtheaverageefficiencyrangeofdieselsthissize.Figure3:FuelEconomyasaFunctionofHPUEfficiencyandVehicleMassforaFigure3:FuelEconomyasaFunctionofHPUEfficiencyandVehicleMassforaParallelHybrid8009001000<1001200fSOO140015001600vehiclemass(kg)1Pan#3X；PwaHFEVComMwdFiHlEsnanw.MPGU,|J?|!_,!nToisolatetheeffectsofhybridization,thatis,replacingaconventionalvehicle'spropulsionsystemwithahybridsystem,the3Xhybridswereunhybridizedandthe1.45Xconventionalwashybridizedintheinitialdesignofthefivevehicleconfigurations.ReferringtothecombinedfueleconomyresultsinTable1,thelightweightconventionalgets65.4mpgwhilethe3Xseriesandparallelhybridsget80.5and81.8mpg,respectively.Thus,theeffectofhybridizingalightweightconventionalthatgets65.4mpgisroughlya24%improvement,assumingthatthehybridizationcouldbedoneforthesametotalvehiclemass.Forthe38.7mpgconventionalvehicle,hybridizationaddsa17%boostinfueleconomyinthisparticularcase.Itshouldbenotedthatthesevehicles'hybridsystemsarenotoptimized.Thevaluesofhybridizationestimatedhereshouldnotbetakenasupperlimits,butratherasrepresentativevalues.Anotheraspectofhybridizationthatcanbeexaminedfromtheresultsobtainedonthetwo3Xhybridsisthedifferencebetweenserieshybridsandparallelhybrids.Forthesetwounoptimizedhybrids,thefueleconomycameoutto81.8mpgfortheparalleland80.5mpgfortheseries.Thismeansthatbasedontheassumptionsmadeforthesehybrids,includingtheassumptionthatthemasswouldbethesame,bothhybridconfigurationscomeoutwithalmostexactlythesamefueleconomy.Areasonableargumentcouldbemadethatthebatterypackforaserieshybridwouldhavetobemorepowerfulandheavierthanfortheparallelhybrid.Ifamassof1100kgwereusedfortheserieshybridratherthanthe1000kginitiallyassumed,acombinedfueleconomyofroughly76.5mpgresults.Letusconsidertwoindependenttechnologyimprovementpathstogetbackto80mpg.Figure4isthe2Ddesignspaceoffueleconomyasafunctionofdrivelineefficiency(motor,motorcontroller,andtransmission)andaccessoryloadforthe3Xserieshybridwithamassof1100kg.Figure4:FuelEconomyasaFunctionofDrivelineEfficiencyandAccessoryLoadfor1100kgSeriesHybridAsindicatedbythearrowsgoingfromthedotrepresentingthe1100kgbaselinevehicle,withan800Waccessoryloadandan84.5%efficientelectricdrivetrain,tothe80mpgcontour,therearemanypossiblepathstogetbackto80mpgforthisvehicle:reduceaccessoriesby200W,improvedrivelineefficiencyby4%,orsomecombinationofthetwo.Giventhattheserieshybridconsideredherehasahighlyefficient,developmentalACinductionmotorfeedingintoa98%efficientsingle-geartransmission,theopportunitiesfordrivelineefficiencyimprovementsarelimited.Theprudentdesignermaybemoreinclinedtotrytoreduceauxiliaryloads.ConclusionsAnadvancedvehiclesimulatorcalledADVISORwasdevelopedatNRELfortheDepartmentofEnergytoallowsystem-levelanalysisandtrade-offstudiesofadvancedvehicles.Fivevehicleconfigurationsweremodeledandsensitivitycoefficientsforkeyparametersofthesevehicleswerecalculated.Thefueleconomydesignspaceforaparallelandaserieshybridwereexaminedandpossiblescenariostoreach80mpgwerediscussed.Forthevehiclesmodeled,thefueleconomybenefitduetohybridizationwasfoundtobebetween17-24%.The3Xseriesandparallelvehicleswerefoundtogetthesamefueleconomyatthesamemass,butiftheseriesvehiclewere100kgheavier,itwouldbeachallengetomakeitreach80mpg.ReferencesDuleep,K.G.,"FuelEconomyPotentialofLightDutyVehiclesin2015+,"DraftFinalReport,EnergyandEnvironmentalAnalysis,Inc.,Arlington,Virginia,April1995."EfficiencyGuidelinesforFutureManualTransmissions,"AutomotiveEngineering,Jan.1996.Lesster,L.W.,Lindberg,F.A.,Young,R.M.,andHall,W.B.,"AnInductionMotorPowerTrainforEVs--TheRightPowerattheRightPrice,"AdvancedComponentsforElectricandHybridElectricVehicles:WorkshopProceedings,NationalTechnicalInformationService.October27-28,1993.Moore,T.,Lovins,A.,"VehicleDesignStrategiestoMeetandExceedPNGVGoals,"SAEPaper951906,1995.OfficeofTechnologyAssessment(OTA),"AutomotiveTechnologiestoImproveFuelEconomyto2015,"Washington,DC,December1994.PartnershipforaNewGenerationofVehicles,ProgramPlan,July,1994.SAE,DraftSAEJ1711,MeasuringtheElectricEnergyConsumption,AllElectricRange,FuelEconomy,andExhaustEmissionsofHybridElectricVehicles,1995.Stock,D.,Bauder,R.,"TheNewAudi5-CylinderTurboDieselEngine:TheFirstPassengerCarDieselEnginewithSecondGenerationDirectInjection,"SAESpecialPublication823,SAEPaper#900648,1990.中文譯文:基于advisor的混合動力車輛動力系統(tǒng)的開發(fā)基思B.Wipke，馬修R.Cuddy.美國國家再生能源實驗室，科羅拉多州戈爾登?摘要：全國可再造能源實驗室開發(fā)了一種名為ADVISOR的先進的汽車模型仿真軟件，用來對汽車進行系統(tǒng)分析和交易研究。由于ADVISOR的快速的執(zhí)行速度和MATLAB/Simulink的開放程序環(huán)境，這個仿真系統(tǒng)非常地適用于合乎新一代汽車合作伙伴計劃PNGV要求的，高燃油經(jīng)濟性車輛的參數(shù)設(shè)計和研究。配置五種不同汽車模型，包括3種輕量級車（并聯(lián)型、串聯(lián)型和傳統(tǒng)型）與1996年車重量的2輛車一起（平行和常規(guī)傳動）。還有在1996年加入的2種重型車（并聯(lián)型和傳統(tǒng)型）。對每類車的重要燃料經(jīng)濟敏感性參數(shù)進行分析，并且車的行駛工況參數(shù)進行設(shè)置。通過分析這些車的仿真結(jié)果，來獨立的分析串聯(lián)和并聯(lián)兩種混合動力方式對汽車的影響。先進的汽車仿真模型：ADVISOR1994年11月，國家可再生能源實驗室的交通技術(shù)中心在Mathworks公司的面向?qū)ο蟮木幊陶Z言的MATLAB/Simulink環(huán)境下創(chuàng)造了進的車輛模型仿真系統(tǒng)。這個模型是在汽車工業(yè)的能源部的支持下建立的。ADVISOR可以將汽車各個部件那些不連續(xù)的動作近似地看作為連續(xù)動作狀態(tài)下的穩(wěn)定狀態(tài)。那樣，在每個時刻都將忽略掉電流、電壓、轉(zhuǎn)矩、轉(zhuǎn)速的改變對系統(tǒng)的影響。這樣通過測試動力傳動系統(tǒng)在一個固定的轉(zhuǎn)矩和轉(zhuǎn)速下，在每單位時間步長下對電力的需求，允許有效率或功率的損耗。在Simulink/Matlab的環(huán)境下利用這個模型有一個非常顯著的優(yōu)勢，那就是靈活容易地來改變模型，例如可以更換一種控制策略或是更換一種再生制動算法°MATLAB也可以容易的分析仿真結(jié)果，盡可能詳細地分析車輛的配置。ADVISOR是由輸入一些車輛行駛的參數(shù)來去驅(qū)動的，包含一些經(jīng)典的特性曲線，如美國的城市循環(huán)工況，或者是速度與爬坡能力的特性曲線。在給定驅(qū)動的目標配置文件后，ADVISOR將采取向后的方式從輪轂和各動力源間各部分所需車輪速度要求的扭矩和速度來控制，這取決于混合動力單元或由電池供電。圖1顯示了一系列高級的混合模型的數(shù)值仿真。圖1高級的混合模型的數(shù)值仿真。仿真和交互作用的檢驗是重要的重要之處是建立模型的可信度。通過與那些成功制造和測試混合動力汽車大學(xué)的合作，國家再生能源實驗室獲得了一些驗證組件模型，包含了量化的不確定性，并增加了可信的數(shù)據(jù)。最后車輛幾倍的驗證，包含詳細的不確定性分析在1996年的九月完成。同時，與公共汽車模型相關(guān)的部分已完成，才外還加入了一些汽車行業(yè)中的專用模型。在此基礎(chǔ)上比較，ADVISOR看來是在根據(jù)多數(shù)模型之內(nèi)相同輸入的2%以內(nèi)。因此，在ADVISOR的結(jié)果是通過它的算法來反映最小的不確定性；輸入數(shù)據(jù)的不確定性是分析不確定性的要原因。所以，所有輸入數(shù)據(jù)的來源模仿的在分析下面指定。車輛模型和假設(shè)：五種不同的車輛配置建模。串、并聯(lián)混合動力車以小的質(zhì)量和高效的傳動系統(tǒng)建模是為了得到像PNGV一樣的混合動力車，獲得城市/高速路的燃油經(jīng)濟性在80英里/加侖。這些被稱為“3倍”的車，是因為他們得到3倍于傳統(tǒng)車輛的燃油經(jīng)濟性城市/高速路26.6英里/加侖。第三個配置是創(chuàng)建一個沒有混合動力的常規(guī)的車輛。第四和第五車輛配置是由以傳統(tǒng)的車輛（大概在1.45倍由于柴油機和手操作的傳動系統(tǒng)），并將它變成并聯(lián)混合動力。表1提供五種車輛仿真配置的燃油經(jīng)濟性的差異，而表2給出了數(shù)據(jù)來源的輸入。

表1:車輛配置模型的主要參數(shù)值:VehicleConfig3XParallelHybrid3XSeriesHybrid2.46XLightWt(nonhybrid)1.45XConv.(diesel)1.70XParallelHybridMass(kg)1000.0001000.0001000.0001611.0001611.000BatteryCap.(kWh)1.1003.700n/an/a1.800PeakHPUPower(kW)31.00030.00047.00077.00052.000PeakMotorPower(kW)12.00041.000n/an/a20.000CdA0.4000.4000.4000.7000.700Crollingresistance0.0080.0080.0080.0110.011City(mpg)73.80072.30056.10033.80040.700Highway(mpg)94.30093.60082.10047.00052.800Combined(mpg)81.80080.50065.40038.70045.300縮放比例：因為從0-60英里/小時的加速時間和在55英里/小時和爬坡能力是所有車的性能要求，液壓動力系統(tǒng)，在這種情況下類似奧迪五缸的渦輪柴油引擎和電動機可以滿足這兩個參數(shù)目標。一個主要的假設(shè)下，這兩種結(jié)構(gòu)的轉(zhuǎn)矩/速度（相當于功率損耗效率圖）可以在坐標圖上簡單的標出扭矩比例。眾所周知，這不是最精確的方法,但被用于缺乏一個可合理尺度算法的情況下。質(zhì)量：這些傳統(tǒng)的1.45倍的和混合動力的車輛的質(zhì)量數(shù)據(jù)來源于美國技術(shù)評估局對于當時流行的福特品牌的金牛座車的評估報告。在報告中對于那些質(zhì)量大概在一噸左右的3X型的車輛會在2015年以后用鋁來代替其他的金屬作為制造的主要材料。這與今天的車輛在質(zhì)量比較上是巨幅的減少；并且這些數(shù)據(jù)還可以用在其它的高效率的總成以及作為滿足PNGV計劃中所要求的技術(shù)參數(shù)?；旌蟿恿刂撇呗裕捍?lián)的混合控制是用一個類似于“恒溫器”的東西來操縱液壓動力裝置，當在開啟狀態(tài)時HPU是在一個固定的扭矩和轉(zhuǎn)速下運行。在這項研究中，當電池的充電量低于40%時HPU將打開，而電池的充電電量達到80%以上時將關(guān)閉。并立案的混合控制策略對于那些電池使用時間短的車有影響，除非在電池電量低的時候保持電池充電。它是樣定義的，將60%的SOC狀態(tài)定位高，將50%的SOC狀態(tài)定為低：*HPU不會停機（除非實在不需要時）*不論是否達在電池的充電狀態(tài)發(fā)動機都可以產(chǎn)生在成制動力。*HPU一般會在遇到指令或是在發(fā)動機需要必要的動力時會提供動力，也有一些特殊情況：1、當電量過低時會提高扭矩來重新充電。2、當點亮過高時將不會充電。燃油經(jīng)濟性的計算：為了證明在一個測試循環(huán)中電池組充電狀態(tài)的變化，推薦用一個簡單版本的美國汽車工程是學(xué)會的混合動力汽車測試程序。為了提高城市燃油的經(jīng)濟性，兩個緊接的從高電量狀態(tài)到低電量狀態(tài)的城市循環(huán)工況各自反映了電池電量的減少和增加。在電池充電狀態(tài)變化不大的情況下，可以用一種簡單的線性插值的方法來預(yù)測汽車燃油經(jīng)濟性的評估值。這將確保一個公平的比較常規(guī)的車輛和混合動力汽車對電池組的任何電能盈余或赤字。如果沒有這樣計算電池組的充電狀態(tài)，由于電能被用來代替燃料能源，混合動了可能似乎已經(jīng)具有極高的燃油經(jīng)濟性。表2：數(shù)據(jù)的來源為模仿輸入和性能要求VehicleParameterValuesUsedSourceofInputDataCDA0.4,0.7m2PNGVGoals,Moore,T.CCrolling-resistance0.008,.011OTATransmissionEfficiencies:5spdo(parallel,92%/98%AutomotiveEngineering,1996

車輛的燃油鍵參數(shù)：conventional)車輛的燃油鍵參數(shù)：conventional)/1spd.(series)HeatEngine(HPU)Scaled85kWTDIDieselStock,D.,1990Motor/ControllerScaled75kWACInductionLesster,L.,1993EnergyStorage:BatteriesHorizon12N85Electrosource0-60mphtime12.0secondsPNGVGoalsGradeabilityat55mph6.5%indefinitelyMorestringentthanPNGVgoal,whichis6.5%for20minutes經(jīng)濟性的關(guān)靈敏度分析的關(guān)鍵參數(shù)的模擬車輛說明如何敏感輸出（燃油經(jīng)濟性在這種情況下）是變化的輸入?yún)?shù)。這允許并排比較輸入?yún)?shù)，以便把重點放在提高燃油經(jīng)濟性的重要技術(shù)領(lǐng)域。此外，相對比較有可能的是，由于輸入?yún)?shù)的變化可以很容易地計算出燃油經(jīng)濟性的數(shù)量變化。對于五種基本模型中的每一種都可以對關(guān)鍵參數(shù)進行上下5%的調(diào)整。這表明這些系數(shù)可以在超出10%的情況下計算，但是信任值不能超出正負10%。對于這五種汽車模型的參數(shù)分析的結(jié)果顯示在圖2的條形圖中。參照表1中的五種車的基本參數(shù)。請注意，所有五種車的靈敏度系數(shù)是1.0。這也就是說，增加1%的引擎效率，將增加1%的燃油經(jīng)濟性。由于發(fā)動機是混合動力或常規(guī)車輛的能量轉(zhuǎn)換器，這并不奇怪，但仍然必須牢記。由于這種大型HPU的效率敏感性很強，工業(yè)部和政府正將極大的努力放在研究燃氣輪機，先進的柴油機，斯特林發(fā)動機和燃料電池上。圖2：燃油經(jīng)濟性的主要參數(shù)esesErq-A.=弟-an』.saEME-lo圖2的結(jié)果表明，電池效率和電機效率的敏感性系數(shù)為3倍串聯(lián)式車輛大致是并聯(lián)式車輛的三倍。這樣的理由是，因為所有的到車輪的驅(qū)動力，來自于串聯(lián)式電動機，高功率和高功率損耗發(fā)動機的串聯(lián)。這樣串聯(lián)式的比并聯(lián)式可以通過電池提供更多的動力，也會引起電池更多的消耗。在技術(shù)層面有一定的風(fēng)險，這就是說串聯(lián)式混合動力汽車在提高發(fā)動機效率和電池方面受到的影響比并聯(lián)式的要多，如果不能通過改進來解決將遇到更大的困難。坐標軸下的四個參數(shù)量會在燃油經(jīng)濟性提高的時候減小。我們的目標是讓這些參數(shù)盡可能的維持在低水平。舉例說明盡可能減少負荷對3倍車的影響：每減少1%配件負荷，燃油經(jīng)濟性有0.24%的升幅。觀察負荷為800w的曲線，每降低10%將提高2.4%的燃油經(jīng)濟性。這些結(jié)果使燃油經(jīng)濟性的權(quán)衡是可以量化的附加功能的汽車，如白天行駛的時候開燈?；旌蟿恿ζ嚨脑O(shè)計空間映射參數(shù)的研究：圖3顯示了在advisor的計算了考慮表1中的3倍的并聯(lián)式混合動力車在有空氣阻力和滾動阻力情況下，HPU的平均效率和質(zhì)量的燃油經(jīng)濟性曲線?？梢缘贸?0英里每加侖的曲線是PNGV計劃中所要求的。圖3：HPU效率和裝備質(zhì)量對并聯(lián)式混合動力車燃油經(jīng)濟性的影響

8009001000iloo12008009001000iloo1200f300140015001600vehiclemass(kg)FwvHl-EVConttHdFuHEcononv，MPGfPan4al3X!兩種大眾的質(zhì)量在圖3中顯示的為1000公斤和1600多公斤并且在五種車輛模型中被定義。從這個圖中可