 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. 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 LIM-204 battery module. The dynamic performance and state of charge SOC estimation are evaluated for five models, including the DP model, through dynamic stress test, DST, and federal urban driving schedules, FUDS, experiment. The DP model has the best dynamic performance and provides the most accurate SOC estimation. The sensitivity of different SOC initial values is also investigated based on the accuracy of SOC estimation with the robust extended Kalman filter, RECF, approach based on the DP model, showing that errors resulting from SOC initial value are significantly reduced and true SOC is convergent within an acceptable error. This article was authored by Jinxin Fan, Hongwen Hee, and Roy Xiong. We are article.tv, links in the description below.