基于改进AFFRLS-AUKF的锂电池SOC估计OA北大核心CSTPCD

The accurate estimation of the state of charge(SOC)of lithium batteries is one of the im-portant prerequisites for ensuring the safe and stable operation of battery management systems.In order to improve the accuracy of SOC estimation of lithium ion batteries,an SOC estimation method of lithium ion batteries combined improved adaptive forgetting factor least squares(AFFRLS)with adaptive unscented Kalman filter(AUKF)algorithm was proposed.The improved AFFRLS was used to identify the parameters of the established second-order RC equivalent circuit model,and the AUKF was used to estimate the SOC of lithium-ion batteries.The average absolute error of the joint estimation is 0.44%and the root mean square error is 0.61%through the verification of DST and UDDS conditions,which shows that the improved AFFRLS-AUKF method improves the accuracy and robustness of parameter identification and battery SOC estimation.