 This paper presents an improved Thevenin model named dual polarization DP model for evaluating lithium ion batteries in electric vehicle applications. The DP model simulates electrochemical and concentration polarization separately using an extra RC circuit. The genetic algorithm is used to identify the optimal time constant of the model based on experimental data from a hybrid pulse power characterization HPPC test on a limb 204 battery module. The dynamic performance and state of charge SOC estimation are evaluated using the dynamic stress test DST and robust extended Kalman filter RECF approach respectively. The DP model has the best dynamic performance and provides the most accurate SOC estimation. Sensitivity analysis shows that errors resulting from initial SOC values are significantly reduced and true SOC is convergent within an acceptable error. This article was authored by Jinxin Fan, Hong Wenhui and Rui Xiong. We are article.tv, links in the description below.