Abstract
In this paper, Methods of SOC estimation of Extended Kalman Filter (EKF) is studied based on the characteristics of Nickel-Metal Hydride (Ni-MH) battery pack with 120 cells in series and 8Ah capacity for HEV. In the study of EKF-based SOC estimation, the improved Thevenin circuit model is adopted, and a new hybrid pulse power characterization （HPPC） test is designed to identify the model parameters by using piecewise linear regression method. In this way, the precision of the circuit model is improved. In addition, The Kalman gain matrix is optimized for EKF iterative algorithm by two ways: a constant gain is increased taking into account the entire process; a dynamic gain which increases at the beginning of abrupt change and decreases rapidly after abrupt change is set up. The improvement achieves a good tracing prediction.
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