利用改进SCE算法的锂离子电池参数辨识

针对传统参数辨识方法中存在的易陷入局部最优和精度低问题，提出一种改进洗牌复杂演化算法。首先，根据锂离子电池动态特性的二阶RC等效电路模型，确定待辨识参数。其次，通过本算法来寻找最优模型参数，以更好的模拟电池真实状态。最后，在马里兰大学先进寿命周期工程中心提供的锂离子电池动态工况数据集上进行验证，并对比本算法和其他优化算法的仿真结果。仿真结果表明, 该方法在辨识精度、泛化性能和可靠性方面具有优势。

Parameter identification of lithium ion battery using improved SCE algorithm

Aiming at the problems of local optimization and low precision in traditional parameter identification methods, an improved shuffling complex evolutionary algorithm is proposed in this paper. Firstly, the parameters to be identified are determined according to the second-order RC equivalent circuit model of the dynamic characteristics of lithium-ion batteries. Secondly, ISCE algorithm is used to find the optimal model parameters to better simulate the real state of the battery. Finally, on a lithium-ion battery dynamic behavior dataset provided by the Center for Advanced Life Cycle Engineering at the University of Maryland. Simulation results show that this method has advantages in identification accuracy, generalization performance and reliability.