The BP neural network can effectively improve the accuracy of state of charge (SOC) estimation by the EKF algorithm. However, the BP neural network is strongly influenced by the initial weights and thresholds, which limits its application in the SOC estimation. To improve the current defects of the BP neural network for better application to the SOC estimation, this paper proposes a method to improve the performance of the EKF algo-rithm for SOC estimation by optimizing the BP neural network using the tuna swarm optimization (TSO) al-gorithm. Based on the constructed first-order RC battery mod...
