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1、Model-BasedElectrochemicalEstimationofLithium-IonBatteriesKandlerA.Smith,ChristopherD.Rahn,andChao-YangWangrelevantsolid-stateandelectrolytediffusiondynamicsandAbstract—AlinearKalmanfilterbasedonareducedorderelectrochemicalmodelisdesignedtoestimateinternalbatteryaccuratelypredictscurrent/vol
2、tageresponse.potentials,concentrationgradients,andstateofcharge(SOC)Derivationofadynamicelectrochemicalmodelsuitablefromexternalcurrentandvoltagemeasurements.Theestimatesforbatterystateestimationiscomplicated,however,bythearecomparedwithresultsfromanexperimentallyvalidatedinfinitedimensionali
3、tyoftheunderlyingpartialdifferentialone-dimensionalnonlinearfinitevolumemodelofa6Ahhybridequation(PDE)system.UsingspatiallydiscretizedPDEs,electricvehiclebattery.Thelinearfiltergives,towithin~2%,performanceinthe30%-70%SOCrange,exceptinthecaseofdistributedparameter-typeestimationalgorithmshave
4、beenseverecurrentpulsesthatdrawelectrodesurfacedevelopedforthelead-acidbattery[6]andthenickel-metalconcentrationstonearsaturationanddepletion;however,thehydridebattery[7],althoughwithhighorder(30-100states)estimatesrecoverasconcentrationgradientsrelax.With4to7incomparisontoequivalentcircuitmo
5、del-basedalgorithmsstates,thefilterhaslowordercomparabletoempirical(2-5states).Recently,weusedamodelorderreductionequivalentcircuitmodelsbutprovidesestimatesofthebattery’stechniquetoderivealow-orderLi-ionbatterymodelinstateinternalelectrochemicalstate.variableform[8],[9]directlyfromthephysica
6、lgoverningI.INTRODUCTIONequations[4],[5].Here,weemploythatmodelinalinearstateestimationalgorithmandvalidateitsinternalestimatesODEL-BASEDbatterymonitoringalgorithmsenablethMagainstanexperimentallyvalidated313ordernonlinearefficientandreliableintegrationofbatteriesintofinite-volumemodelofa6AhH
7、EVbattery[10].hybridelectricvehicle(HEV)powertrains.ExamplesincludethegeneralizedrecursiveleastsquaresalgorithmofII.MODELANDFILTERVerbruggeandKoch[1]andtheextendedKalmanfilteralgorithmofPlett[2].BothalgorithmsuseanassumedAschematicofthe1Dbatt
