Page - 155 - in Emerging Technologies for Electric and Hybrid Vehicles

Energies 2017,10, 1503 Figure17.Over-dischargedfaultdetectionandself-recoverycurve. 4.Conclusions In this paper, anoverall structure of a 12-cell series LIBpower system integratedwith smart real-timefault-diagnosisandself-recoveryschemeswasproposedandimplemented. Several common faults,suchastheexternalshort-circuit,over-charged,over-discharged,over-current,over-temperature andopen-wire faults,were investigatedandvalidated in theactual implementation. Theexperimental resultsofLIBsunder thereal loadprofileconfirmedtheefficacyof thestate-of-chargeestimationand faultdiagnosiscapabilities for theelectricvehicleapplication. Itensuredthesafetyof theusersand, inparticular,prolongedthe lifeof thebatterycells inanelectricvehiclewithhumanpresence. Future workwill includethestudyof theagingandrecyclingofcells to improvethebatteryperformanceat areasonable implementationandoperatingcost. Acknowledgments:Thisworkwassupportedbyequipmentandmanpower fromtheTemasekPolytechnicand NewcastleUniversity. Theauthorswould like to thankallpartners forprovidingresearchsupport. AuthorContributions:ZuchangGaoiscreditedwith the theoretical formulation, simulationandexperimental worksperformedinthispaper.ChengSiongChinfromdefinedtheflowofthepaper, ideasofsmartbatterypower systemwith faultdiagnosiscapabilitiesandparticipated in themodelsimulationandverificationthatdrove this researchwithZuchangGao, JunboJiaandJoelHayKingChiewtotest its relevance for industrialapplications. CaizhiZhangprovidedtheacademicsupportandadviceduringtheproject.Allauthorsdiscussedandprovided commentsatall stages. Conflictsof Interest:Theauthorsdeclarenoconflictof interest. References 1. Zou,C.;Manzie,C.;Nesic,D.A framework for simplificationofpde-based lithium-ionbatterymodels. IEEETrans. ControlSyst. Technol.2016,24, 1594–1609. [CrossRef] 2. Gao,Z.; Jia, J.;Xie, J.;Toh,W.D.;Lin,P.;Lyu,H.; Julyanto,D.;Chin,C.S.;Woo,W.L.Modellingandsimulation ofa12-cellbatterypowersystemwithfault control forunderwater robot. InProceedingsof the2015IEEE 7thInternationalConferenceonCyberneticsandIntelligentSystems(CIS)andIEEEConferenceonRobotics, AutomationandMechatronics (RAM),SiemReap,Cambodia,15–17 July2015;pp.261–267. 3. Xiong, R.; He,H.; Sun, F.; Zhao,K. Evaluation on state of charge estimation of batterieswith adaptive extendedkalmanfilterbyexperimentapproach. IEEETrans.Veh. Technol. 2013,62, 108–117. [CrossRef] 4. Kim,T.;Wang,Y.;Fang,H.;Sahinoglu,Z.;Wada,T.;Hara,S.;Qiao,W.Model-basedconditionmonitoring for lithium-ionbatteries. J.PowerSources2015,295, 16–27. [CrossRef] 5. Ablay,G.Onlineconditionmonitoringofbatterysystemswithanonlinearestimator. IEEETrans. EnergyConvers. 2014,29, 232–239. [CrossRef] 155