BatteryManagement SystemsandBattery SOCEstimation
Battery Management Systems and Battery SOC Estimation
BatterySystems:TheBottleneckof HEV.PHEV,BEVMarketPenetrationMainChallengesforBEV:Price:Need to reach economicthresholdsManycostreductionpotentialsRange:MustbecomparabletoICEandPHEVInfrastructuresFastcharging stations(manypotential solutions)Life-cycle,replacement costs,vehicle resalevaluePerceptions:safety,reliability,etc
Battery Systems: The Bottleneck of HEV, PHEV, BEV Market Penetration Main Challenges for BEV: • Price: Need to reach economic thresholds Many cost reduction potentials • Range: Must be comparable to ICE and PHEV • Infrastructures Fast charging stations (many potential solutions) • Life-cycle, replacement costs, vehicle resale value • Perceptions: safety, reliability, etc
RolesofBatteryManagementSystems(BMS):Monitoring of operation status : SocChargeand dischargedecisions:When andhowCell balancingDiagnosisPrediction of remaininglife: SOHMainDifficulties:AccurateEstimationoftheStateofCharge(SOC)AccurateEstimationoftheBatteryKeyParametersAccurateEstimationof theStateof Health(SOH)DiagnosisduringOperation
Roles of Battery Management Systems (BMS): • Monitoring of operation status : SOC • Charge and discharge decisions: When andhow • Cell balancing • Diagnosis • Prediction of remaining life: SOH Main Difficulties: • Accurate Estimation of the State of Charge (SOC) • Accurate Estimation of the Battery Key Parameters • Accurate Estimation of the State of Health (SOH) • Diagnosis during Operation
WhyisSOC,SOH,parameterestimationcriticallyimportant?AccurateSOCestimationAccurateparameterestimation口Avoidovercharge/over-discharge(Safety)Lessconservativeoperationhigher effectivecapacity,longerrangeBetterqualityofservice (whentocharge)OptimalcoordinationwithotherpowersourcesPromptand reliablediagnosisOptimaloperationforlongercyclelives
Why is SOC, SOH, parameter estimation critically important? Accurate SOC estimation • Avoid overcharge/over-discharge (Safety) • Less conservative operation higher effective capacity, longerrange • Better quality of service (when to charge) • Optimal coordination with other powersources • Prompt and reliable diagnosis • Optimal operation for longer cyclelives Accurate parameterestimation
Implicationsof Real-TimeandIndividualized ModelingOff-Line ModelingReal-Time ModelingEquipmentCheap,Expensive,comprehensivesimpleHighLowData AccuracyData SizeLarge data can be storedDo not want to store large dataTimingData must be real-time processedData can be processed again andagainonthereal clockModel StructureMust use simplified andComplicatedmodelscanbeusedidentifiablemodelsOperating ConditionsControlledinalabenvironmentUncontrolledrealenvironmentAgingNewandold systemsTypicallynewsystemsPopulationOftenusetypical systemsMust deal with large variations inthepopulationChallengesNoteasy,Muchmore difficultNotmuchtimeavailabletobetime consumingconsumedControlForadaptive control,diagnosis,Forrobustandoptimalcontroand decision
Implications of Real-Time and IndividualizedModeling Off-Line Modeling Real-Time Modeling Equipment Expensive, comprehensive Cheap, simple Data Accuracy High Low Data Size Large data can be stored Do not want to store large data Timing Data can be processed again and again Data must be real-time processed on the real clock Model Structure Complicated models can be used Must use simplified and identifiable models Operating Conditions Controlled in a lab environment Uncontrolled real environment Aging Typically new systems New and old systems Population Often use typical systems Must deal with large variations in the population Challenges Not easy, time consuming Much more difficult, Not much time available to be consumed Control For robust and optimal control For adaptive control, diagnosis, and decision