In order to estimate the state of charge (SOC) of LiFePO4 battery more accurately, an improved Extended Kalman Filter (EFK) algorithm is proposed to estimate the parameters in the least squared identification model. A second-order RC equivalent circuit is used as the battery model, and an additive term is introduced into the state equation for real-time parameter update. Besides, a fuzzy controller is applied to online adjust measurement noise variance. Simulation experiments have been performed for SOC estimation and the estimation accuracy is remarkably better than that obtained from a general EKF algorithm.