A novel combined battery model for state-of-charge estimation in lead-acid batteries based on extended Kalman filter for hybrid electric vehicle applications

In this paper a novel combined battery model for state-of-charge (SoC) estimation in lead-acid batteries, based on extended Kalman filter (EKF) is presented. To obtain a more accurate SoC estimation technique, a combination of the two previously used models (RC and hysteresis battery models) is introduced; trying to compensate deficiencies of the individual models. The changes in the behavior of the battery are considered in the proposed SoC estimation method which makes it suitable for hybrid electric vehicle (HEV) applications. The effectiveness of the proposed method is verified using an experimental test. This Kalman filter modeling approach is shown to give SoC estimation error within 2% compared with Ah counting method; therefore, better results are obtained in comparison with the other conventional methods.