 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 show that the DP model has the best dynamic performance and provides the most accurate state of charge 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 Jin Qin-Fan, Hong Wen-Hee and Rui Xiong.