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

In order to estimate the state of charge (SOC) of lithium iron phosphate (LiFePO4) power battery, the state space model that fit for kalman filter to estimate was established on the basis of PNGV equivalent circuit model. In the case that considering the influence factors such as power battery charge and discharge current, environmental temperature and battery state of health, an improved composite SOC estimation algorithm based on extended kalman filter (EKF) algorithm was proposed, this proposed algorithm integrated using EKF algorithm, improved Ah counting method and open circuit voltage method to estimate SOC. The simulation results show that the proposed algorithm can track the change of the power battery SOC effectively, verify the validity of the proposed algorithm.