A Sliding Mode Observer SOC Estimation Method Based on Parameter Adaptive Battery Model

Abstract

Errors of a battery model will dramatically enlarge as the internal parameters of a battery varying. To reduce the systematic errors, a parameter adaptive battery model is proposed. Based on it, sliding mode algorithm is adopted to estimate the SOC of a battery. The experimental platform is constructed and the UDDS driving cycles is used to verify the method. The results show the error of SOC estimation is less than 2% and it indicates the monitoring algorithm is of great value to power batteries which are generally used in variable environment.