AN ADAPTIVE ALGORITHM OF NiMH BATTERY STATE OF CHARGE ESTIMATION FOR HYBRID ELECTRIC VEHICLE

An adaptive algorithm for battery state of charge (SOC) estimation is presented in this paper to solve the critical issue of calculating the remaining energy of battery in hybrid electric vehicle (HEV). To obtain a more accurate SOC estimation value, both coulomb-accumulation and open-circuit voltage contributions are considered in this study. The Extended Kalman filter (EKF) theory which has good adaptability is used respectively in these two contributions. The adaptive control effectiveness is achieved in two aspects: one is the application of Kalman filter which can filter the noise of voltage and current measurement and the other is the open-circuit voltage correction when the battery is in steady state to compensate the deficiencies of coulomb-accumulation. The test results show this adaptive algorithm has high robust property, noise-immune ability and accuracy which is suitable for HEV application.