Research On Estimation Of State-of-Charge And State-of-Health Of Lithum-Ion Batteries

The invention of car changed the way people travel and live.Since 21 st century,people have been expecting cars to be cleaner and more environmentally friendly.Therefore,electric vehicles have received extensive attention.Battery is the core component of electric vehicles.Battery management system(BMS)is crucial whose core function is estimation of state of charge(SOC)and state of health(SOH).In the SOC estimation methods based on equivalent circuit models,the parameters of model change with factors such as discharge rate,SOC,ambient temperature and battery aging.This phenomenon causes inaccuracies of the equivalent circuit model,which in turn causes SOC estimation error.At the same time,the inaccuracy of SOC estimation caused by different ambient temperature is also one of the core challenges in the research of SOC estimation.Realizing SOH online estimation at different ambient temperatures is also a goal pursued in the research of SOH estimation.Evaluating the effect of equivalent circuit model parameters' change on model accuracy and SOC estimation accuracy is defined as the sensitivity analysis problem in this paper.Then a unified,quantitative local sensitivity analysis process and definition is proposed in this paper.The local sensitivity of the second-order resistance-capacitance model under nine battery conditions is analyzed in detail.Three commonly used equivalent circuit models are evaluated from the perspective of sensitivity and model accuracy.Then,the global sensitivity analysis method based on Sobol method is used to analyze the global sensitivity of the second-order resistance-capacitance model under two battery conditions.The Sobol method is compared with the local sensitivity analysis method proposed in this paper from the perspective of definition,analysis method and implementation method.Based on the results of sensitivity analysis,the SOC online estimation method based on Dual Extended Kalman Filter(DEKF)algorithm is designed in this paper,but only the high sensitivity parameters are estimated online,while the other parameters use the offline values.This method is compared to the other two methods under the Urban Dynamometer Driving Schedule(UDDS).The comparison results show that the method designed in this paper can shorten the running time of SOC online estimation and save computing resources under the premise of ensuring the accuracy of SOC estimation.For the influence of ambient temperature on the SOC estimation process,a fitting formula for fitting the battery capacity at different ambient temperatures is proposed in this paper,which is based on the Arrhenius formula.At the same time,a fitting formula for fitting the open circuit voltage(OCV)and SOC curves at different ambient temperatures is proposed.Then the two fitting formulas are verified.Aiming at the influence of ambient temperature on the parameters of battery equivalent circuit model,the corresponding processing strategy is proposed.In this way,the second-order resistance-capacitance model is improved to adapt to different ambient temperatures.Based on the improved second-order resistance-capacitance model,the SOC and SOH online joint estimation method based on DEKF which considers the effects of ambient temperature is proposed in this paper.This method extends the online estimation of SOH to different ambient temperatures.The method is then verified under UDDS operating condition at multiple ambient temperatures.The verification results show that the method proposed in this paper has good SOC and SOH estimation accuracy at different ambient temperatures.