State‐of‐Charge Estimation of Lithium‐Ion Battery Based on an Improved Dual‐Polarization Model

This article proposes a state‐of‐charge (SOC) estimation method to eliminate the influence of the hysteresis effect and the ambient temperature. First, an improved dual‐polarization (DP) model considering the hysteresis effect and the ambient temperature is established. A hysteresis voltage source is connected in series with a couple of resistance–capacitance pairs in the improved DP model, all the parameters of which are related to the ambient temperature to depict the temperature characteristics of the battery. Second, the forgetting factor recursive least squares method is utilized to identify the parameters under the battery dynamic test data at different temperatures. The proposed model and parameterization scheme integrate the effects of hysteresis and temperature, greatly enhancing the performance of the proposed method at different temperatures. Finally, an extended Kalman filter algorithm for SOC estimation is adopted to verify the improved DP model and the simulation indicates that the error of SOC estimation is within 1.5% at different ambient temperatures. The proposed method can improve the precision of the SOC estimation even if the temperature is below −10 or above 50 °C.