State of Charge Estimation of Lithium-Ion Batteries Over Wide Temperature Range Using Unscented Kalman Filter

Abstract

With the development of electric vehicles in recent years, lithium-ion batteries have been widely used. Accurate state of charge (SOC) estimation plays an important role in the safety of electric vehicles. Since the temperature has the significant influence on charge and discharge performance of the battery, it is critical to achieve accurate SOC estimation over the wide temperature range. In this paper, a polymer ternary lithium-ion battery is focused, and a Thevenin equivalent circuit model with temperature compensation is established. The validity of the established battery model was verified by the dynamic stress test. On this basis, the ternary lithium-ion battery SOC was estimated using the unscented Kalman filter (UKF). The New European Driving Cycle is used to verify the effectiveness of the proposed algorithm. The simulation and experimental results show that the established Thevenin equivalent circuit model with temperature compensation can accurately represent the battery dynamics. Based on this model, the SOC was estimated using the UKF and the maximum errors are within 3%. Therefore, the proposed SOC estimation method is verified to be effective and robust.