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State of Charge Estimation of Li-Ion Battery Based on Improved Extended Kalman Filter

Accurate battery state of charge (SOC) estimation can reflect the endurance of power batteries, which plays an important role in the battery management system (BMS). The extended Kalman filter (EKF) estimation of SOC is easily affected by the noise of sampling voltage and current, and there are problems such as low estimation accuracy and easy divergence. This paper adopts the improved EKF to estimate SOC recursively, and the estimation accuracy is improved. Firstly, the second-order RC equivalent circuit model of the battery is established, and then the pulse discharge test is performed to identify the parameters of the model. Finally, simulation verification is carried out based on the discharge conditions of the lithium-ion battery. The results show that improved EKF has better convergence and lower error than EKF, and the average absolute error is less than 0.01.