A fast state-of-charge estimation algorithm for LiFePO4 batteries utilizing extended Kalman filter

Abstract

This paper proposes a fast state-of-charge (SOC) estimation algorithm for LiFePO4 batteries utilizing an extended Kalman filter (EKF). The proposed algorithm controls error covariance to expedite the SOC convergence against an initial error and alleviate undesired SOC fluctuation with a simplified hysteresis model. The new model not only well describes OCV hysteresis of the battery, but also requires less resources by linearization. To validate the performance of the proposed estimation method, a scaled-down hybrid electric vehicle (HEV) current profile is used for a 14Ah LiFePO4 battery cell. The experimental results verify the improved estimation speed as well as the feasibility of the proposed linearized model.