Battery SOC Estimation Based on LM-ICDKF Algorithm

Abstract

In order to estimate the accurate and real-time dynamic battery state of charge (SOC), owing to greater errors of extended Kalman filter (EKF) in estimating SOC, a method has been proposed to estimate the battery SOC based on LM-ICDKF algorithm. By using the two order RC equivalent circuit model, the MATLAB simulation tools are used to simulate the algorithm, this paper compares LM-ICDKF algorithm with the extended Kalman filter algorithm and the center differential Kalman filter algorithm. From the simulation results, we can indicate that the SOC estimation based on LM-ICDKF has good convergence, and improves the estimation accuracy of SOC.