Research On SOC And SOH Estimation Of Li-ion Battery For Electric Vehicles Considering The Influence Of Ambient Temperature And Cycle Numbers

With the development of electric vehicles,the power battery technology and battery management system(BMS)have been extensively investigated by the people.The reaction essence of power lithium-ion battery is a complex electrochemical reaction process,which is prone to affected by ambient temperature,cycle numbers and other factors.It is worth pointing out that there exist for four basic big problems as short mileage,slow charge,difficult charging and battery safety that restrict the development of electric vehicles after it is put forth.To solve these problems,we should first overcome the accurate battery state of charge(SOC)and state of health(SOH)estimation in BMS.Therefore,this paper constructs two types enhanced battery model considering the influence of ambient temperature and cycle times,respectively.Finally,based on the extended Kalman filter(EKF)and adaptive extended Kalman filter(AEKF),the co-estimation scheme of battery SOC/SOH is proposed,and the corresponding simulation and experimental research are carried out.The specific research contents are described as follows:(1)Lithium-ion battery modeling.According to the collected battery test data under different ambient temperatures and different cycles,the variations of ambient temperature and cycle number will affect the battery external characteristics.Thus,two types enhanced battery model are established as:(i)A second-order RC equivalent circuit model(ECM)considering the influence of ambient temperatures and(ii)A second-order RC equivalent circuit model considering the influence of cycle numbers.(2)Parameter identification and simulation verification of the established battery model.After establishment of the battery model,the parameters estimation on these battery models are performed via exponential function fitting method(EFF)and recursive-least square algorithm(RLS),respectively.Meanwhile,the variations of battery parameters on the ambient temperature and cycle numbers are fitted and synthesized.Finally,the accuracy of two types battery models are further verified in MATLAB/Simulink.(3)EKF-based on SOC estimation algorithm.The extended Kalman filter algorithm is employed to estimate battery SOC based on the second-order RC equivalent circuit model considering the influence of ambient temperature.The estimation and experimental results show that this enhanced battery model can well predict the variations of SOC under different operating temperature,compared with the general 2RC-ECM for lithium-ion battery.(4)A co-estimation of SOC/SOH based on AEKF algorithm.The AEKF algorithm is employed to estimate battery SOC/SOH simultaneously based on the second-order RC equivalent circuit model considering the influence of cycle number.The results show that this proposed co-estimation scheme can well predict battery SOC and SOH under different aging levels.