Impact of current rate and temperature on state-of-charge estimation of Li-ion batteries based on the extended Kalman filter

Accurate battery models and precise calculation of the battery state-of-charge (SOC) are necessary for maximizing battery performance, realizing safe operation, and extending the operating range of hybrid electric and plug-in hybrid vehicles. In this paper, by taking various temperatures and charging/discharging current rates into consideration, a comprehensive battery model is developed in which the parameters are extracted based on experimental data. Furthermore, an online SOC estimation method based on the developed model and the Extended Kaiman Filter (EKF) is proposed. The accuracies of the battery model and the SOC estimation method at various temperatures and current rates are evaluated and validated based on a set of simulation and experimental studies.