A novel lithium-ion battery model for state of charge estimation under dynamic currents

Abstract

An accurate battery model is one of the most important factors to improve the capability of battery state of charge (SoC) estimation. In this paper, battery hysteresis behaviors under different SoC are considered to decrease battery model error, and the hysteresis voltage based battery model (HVBBM) is presented. The experiment result shows that this model can describe the battery discharging process accurately under dynamic current conditions. A method of the adaptive extended Kalman filter (AEKF) based on HVBBM is applied to estimate battery SoC since AEKF can update the process and measurement noise covariances adaptively during the estimation. The comparison results indicate that the method proposed in this paper can improve SoC estimation accuracy under dynamic currents.