Simulation Research and Embedded Implementation of Model Based SOC Estimation for Lithium Battery

State of charge (SOC) estimation is one of the key technologies in battery management system of electric vehicle. In order to improve the estimation accuracy of SOC, this paper improves the extended Kalman filter (EKF) algorithm; in the identification of model parameters, this paper uses the least square method based on the forgetting factor to construct a lithium battery time-varying parameter model; and then uses EKF algorithm to realize SOC online estimation. Matlab simulation results show that the improved algorithm is more accurate than the traditional EKF algorithm, and the estimation error is less than 2%. Finally, the algorithm is implemented on the vehicle embedded system by using the automatic code generation technology.