School of Information Science and Technology,,Donghua University,Shanghai 201620,,China
Abstract: With the growth of the new energy vehicle market, market demand for battery management systems(BMS) has also further expanded. For BMS, which guarantees battery safety and prolongs battery life, the estimation of the state of charge(SOC) of a powered lithium battery pack is the focus of BMS research. Based on the study of the problem that the AH integration method is greatly affected by the initial value of the SOC and has a cumulative error, and the extended Kalman filter algorithm(EKF) has a slower convergence when estimating the SOC, a second-order RC equivalent circuit model was used to model and analyze the lithium battery. Considering that the parameters of the lithium battery are affected by SOC changes, the Unscented Kalman Filter(UKF) algorithm was introduced to simulate the SOC of the lithium battery. The experimental results show that the UKF-based SOC estimation is more accurate, the error is smaller, and the convergence speed is faster, which is of great significance to the improvement of the traditional fixed-value battery parameter BMS.
Key words : lithium battery,;unscented Kalman filter;state of charge,;equivalent circuit,;estimation method