Joint Estimation of State of Charge and Capacity of Lithium-ion Batteries in Electric Vehicle

Considering battery aging and reducing CPU calculation pressure of electric vehicle, real-time assurance of the accuracy of power battery SOC and capacity is very important for the safety of electric vehicles. In this paper, a combined framework of battery SOC and capacity estimation is introduced based on equivalent circuit model. For the problem of traditional Kalman filter that only Gaussian noise can be filtered. An improved extended Kalman filter is proposed to estimate the battery SOC in real time. The accelerated aging experiment method is used to study the effect of the gray model in predicting battery capacity decline and the cumulative error of SOC estimation under battery aging. Through static and dynamic test experiments, the accuracy and robustness of the method proposed in this paper are verified.