Strategy of Estimating State of Charge of Lithium-Ion Based on Improved Extended Kalman Filter

To achieve a sufficiently accurate estimation of the battery charge state and reduce the effects of various disrupting elements on the estimation results as much as feasible, This paper presents an SOC (State-of-Charge) estimation scheme that combines the Ampere Hour Integral Method and the Extended Kalman Filter (EKF). The scheme is based on an equivalent circuit model utilizing double RC networks, the DP model. Validated by simulation with HPPC working conditions, simulation results show that the joint algorithm outperforms the Ampere Hour Integral method and EKF methods alone, as well as dependability and practicality.