Abstract
We use Thevenin battery model and Kalman filter algorithm to online estimate lithium-ion battery pack state of charge (SOC) in this paper. In order to improve the accuracy of the model we use least square method and Dual Kalman filter (DEKF) algorithms to identify the parameters of model. The battery model can reflect the true state of internal battery well. The principle of Kalman filter algorithm is introduced. The relevant battery testing laboratory is designed. The algorithm has better accuracy when online estimate SOC and adapt to the environment well from experimental results. Finally, the convergence and robustness of DEKF algorithm are verified. It solves the problems that initial estimates are not accuracy and cumulative error.
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