State of Charge Estimation of Power Lithium Battery Based on Extended Kalman Filter

The chemical reaction process of the vehicle power lithium battery is complicated, and the battery has typical time-varying and nonlinear characteristics. High precision SOC (State Of Charge) estimation algorithm takes a long time and is computationally intensive. In practical use, the ampere-hour integral method is applied more, but it is easy to cause time accumulation error. In this paper, considering the simplification and accuracy of the algorithm, the second-order RC equivalent circuit model is built according to the battery test data, and the SOC estimation of the battery is completed by EKF (Extended Kalman Filtering) algorithm. The simulation results show that the estimation accuracy can be kept within 3%.