电动汽车动力电池关键状态参数估计及管理

Estimation and Management of Key State Parameters of Electric Vehicle Power Battery

通过分析电动汽车电池管理系统相关技术,提出了二阶等效电路模型并考虑了均衡电路的影响,建立了基于扩展卡尔曼滤波器(Extended Kalman Filter, EKF)的荷电状态估计算法规则,并将实验数据与真实数据进行了对比,验证了该模型SOC算法满足设计要求,同时对该设计现存的不足提出改进建议,并对今后的发展进行了预期。

By analyzing the relevant technologies of electric vehicle battery management system,a second-order equivalent circuit model is proposed,and the influence of balanced circuits is taken into account to establish a state of charge estimation algorithm rule based on Extended Kalman Filter(EKF).Experimental data is compared with real data to verify that the SOC algorithm of the model meets the design requirements,and improvement suggestions are proposed for the existing shortcomings of the design,and expectations are made for future development.