 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 optimal time constants of the model from experimental data. Evaluations are conducted on five models including the RINT, RC, Thevenin, PNGV, and DP models for dynamic performance and state of charge, SOC, estimation. 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 using the robust extended Kalman filter approach based on the DP model. This article was authored by Jinxin Fan, Hong Wenhui and Rui Xiong. We are article.tv, links in the description below.