Abstract
Battery SOC estimation is the core of the battery management system, SOC directly affect the battery management system (BMS) decision-making and control. In this design, the Kalman filter correction method is taken into account and the influence of charge and discharge rate, temperature and charge/discharge cycles on the SOC estimation is considered. Based on this method, the Kalman filter correction algorithm is proposed, and its application in the pure electric vehicle battery management system. The results show that Kalman filter correction algorithm effectively corrects the error of Ah method, improves the estimation precision, and provides a more accurate SOC estimation method for battery management system.
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