Comparative estimation of battery SOC based on EKF algorithm and UKF algorithm

Abstract

The state of charge of Li-ion battery in new energy vehicles is an important parameter reflecting the battery and power system. In order to achieve the purpose of real-time SOC estimation, this paper takes the lithium iron phosphate battery as the research object, establishes the RC second-order circuit model in MATLAB/Simulink environment, then discovers the parameters of different SOC and temperature effects on the battery model by establishing the mixed power pulse characteristics experiment, and brings the discerned parameters into the traditional single extended Kalman filter algorithm (EKF) and the parameters identified are brought into the conventional single extended Kalman filter (EKF) and traceless Kalman filter (UKF) algorithms for simulation experiments, and then the different experimental results of the two algorithms are compared and studied. The final experiments show that the traceless Kalman filter algorithm can significantly improve the estimation accuracy and convergence speed of the Li-ion battery charge state.