Page - 143 - in Emerging Technologies for Electric and Hybrid Vehicles

energies Article DesignandImplementationofaSmartLithium-Ion BatterySystemwithReal-TimeFaultDiagnosis CapabilityforElectricVehicles ZuchangGao1,ChengSiongChin2,*, JoelHayKingChiew1, JunboJia 1 andCaizhiZhang3 1 SchoolofEngineering,TemasekPolytechnic,Singapore529757,Singapore;zuchang@tp.edu.sg (Z.G.); joelchk@tp.edu.sg (J.H.K.C.); jiajunbo@tp.edu.sg (J.J.) 2 FacultyofScience,AgricultureandEngineering,NewcastleUniversity,NewcastleuponTyneNE17RU,UK 3 SchoolofAutomotiveEngineering,ChongqingUniversity,Chongqing400044,China; czzhang@cqu.edu.cn * Correspondence: cheng.chin@newcastle.ac.uk;Tel.:+44-65-6908-6013 Received: 13September2017;Accepted: 26September2017;Published: 27September2017 Abstract:Lithium-ionbattery (LIB)powersystemshavebeencommonlyusedforenergystorage in electricvehicles. However, it isquite challenging to implementa robust real-time faultdiagnosis andprotection scheme to ensurebattery safety andperformance. Thispaperpresents a resilient framework for real-time fault diagnosis andprotection in abattery-power system. Basedon the proposedsystemstructure, theself-initializationschemeforstate-of-charge (SOC)estimationand the fault-diagnosis schemewere tested and implemented in an actual 12-cell series battery-pack prototype. The experimental results validated that the proposed system can estimate the SOC, diagnose the faultandprovidenecessaryprotectionandself-recoveryactionsunder the loadprofile foranelectricvehicle. Keywords: lithium-ion;energy-storagesystem; faultdiagnosis;protection;electricvehicle 1. Introduction Asoneofmanyenergystorage solutions, lithium-ionbatteries (LIBs) areattractingmoreand more attention from researchers andusers due to their high energy density, high power density, long lifespan and environmental friendliness [1,2]. The LIBs have been used in energy-storage applications insolarpanel systemsfromthose thatusea fewkilowatt-hours inresidential systemsto multi-megawattbatteries ingridpowersystems. Therearealsobroadapplicationsinsomehigh-power applications such as electric vehicles using large numbers of serial or parallel battery cells [3–8]. However,despitebeingapromisingcandidate forenergystoragesolutions, thesebatteriesare facing somechallenges, suchasensuringsafeoperationof thebattery-powersystemthatdependson the accurate state-of-charge (SOC) estimation [9–11]. The safety of the LIB power system is crucial, especiallywhen thebattery-power systemisgroupedbyaconsiderablenumberofbatterycells in serialorparallel topology,or inabatterystack, togiveahigherpowerdensity. TheLIBscandeteriorate if theyare tooperatebeyondthebatteryspecifications [9,10]. The estimations of SOC in the batterymanagement system (BMS) can improve the system performance and reliability. However, battery discharge and charge involve complex chemical andphysical processeswhile in operation. It is thereforenot easy to estimate the SOCaccurately undervariousoperationalconditions [12–14]. ThereareseveralkindsofLIBs in themarket, suchas thosecontainingLiFeO4, lithiumpolymersandLiCoO2.With thedifferentdynamicbehaviorof the batteriesandtheir topology, specificSOCalgorithmsaresometimesrequired. Therehavebeenmany development and researchworks in recent years to improve SOCestimation accuracy [13,15–18]. Firstly, the standardmeasurement-basedestimationapproaches, suchas the coulomb-countingor Energies 2017,10, 1503;doi:10.3390/en10101503 www.mdpi.com/journal/energies143