Seite - 158 - in Emerging Technologies for Electric and Hybrid Vehicles

energies Article ImprovedBatteryParameterEstimationMethod ConsideringOperatingScenariosfor HEV/EVApplications JufengYang1,2,BingXia2,3,YunlongShang2,4,WenxinHuang1,*andChrisMi2,* 1 DepartmentofElectricalEngineering,NanjingUniversityofAeronauticsandAstronautics, Nanjing211106,China; jufeng.yang@mail.sdsu.edu 2 DepartmentofElectricalandComputerEngineering,SanDiegoStateUniversity, SanDiego,CA92182,USA;bixia@eng.ucsd.edu(B.X.); shangyunlong@mail.sdu.edu.cn(Y.S.) 3 DepartmentofElectricalandComputerEngineering,UniversityofCaliforniaSanDiego, SanDiego,CA92093,USA 4 SchoolofControlScienceandEngineering,ShandongUniversity, Jinan250061,China * Correspondence: huangwx@nuaa.edu.cn(W.H.); cmi@sdsu.edu(C.M.); Tel.:+86-138-5149-7182 (W.H.);+1-619-594-3741 (C.M.) AcademicEditor: RuiXiong Received: 3October2016;Accepted: 13December2016;Published: 22December2016 Abstract:Thispaperpresentsan improvedbatteryparameterestimationmethodbasedontypical operating scenarios in hybrid electric vehicles and pure electric vehicles. Comparedwith the conventionalestimationmethods, theproposedmethodtakesboththeconstant-currentchargingand thedynamicdrivingscenarios intoaccount,andtwoseparatesetsofmodelparametersareestimated through different parts of the pulse-rest test. Themodel parameters for the constant-charging scenario are estimated from thedata in thepulse-chargingperiods,while themodel parameters for thedynamicdriving scenario are estimated from thedata in the rest periods, and the length of the fitted dataset is determined by the spectrum analysis of the load current. In addition, theunsaturatedphenomenoncausedbythe long-termresistor-capacitor (RC)network isanalyzed, andthe initialvoltageexpressionsof theRCnetworks in thefitting functionsare improvedtoensure ahighermodelfidelity. Simulationandexperimentresultsvalidatedthe feasibilityof thedeveloped estimationmethod. Keywords: lithium-ionbattery;operatingscenario;equivalentcircuitmodeling;parameterestimation 1. Introduction Lithium-ionbatterieshavebeenwidelyused in the energy storage systemsofhybrid electric vehicles (HEVs)andpureelectricvehicles (EVs)becauseof their lowself-dischargerate,highenergy andpowerdensities. Toensure the safeandreliableoperationof lithium-ionbatteries, thebattery managementsystem(BMS) isof significant importance. Themain taskofaBMSincludesmonitoring ofcritical states, faultdiagnosisandthermalmanagement [1–7]. 1.1. Reviewof theLiterature The performance of a BMS is highly dependent on the accurate description of battery characteristics. Hence, a proper battery model, which can not only correctly characterize the electrochemical reactionprocesses, but alsobe easily implemented in embeddedmicrocontrollers, isnecessary forahigh-performanceBMS.Thereare twocommonformsofbatterymodelsavailable in the literature: theelectrochemicalmodelandtheequivalentcircuitmodel (ECM).Theelectrochemical Energies 2017,10, 5;doi:10.3390/en10010005 www.mdpi.com/journal/energies158