Electric vehicle battery SOC estimation based on fuzzy Kalman filter

Electric vehicle battery management system works in the poor working environment, so that using conventional Kalman filtering algorithm to estimate the state of charge of electric vehicle battery will lead to inaccurate estimation, even divergent filtering. Aiming at the poor adaptive ability, defects of traditional filtering algorithm, the paper designs an improved fuzzy adaptive Kalman filter method, and applies it in the estimation of state of charge of electric vehicle battery. By monitoring the changes of residual online, the method uses the mean and the variance of the residual as the input of fuzzy controller, and adjusts the weight of the system noise and observation noise with fuzzy logic in real time, thus improves the estimation accuracy and realizes the optimal estimation of the filter. The simulation results show that this algorithm can predict the battery SOC effectively, and its accuracy is better than that of conventional Kalman filtering algorithm.