梯次锂电池及其BMS的应用研究

Application research on cascade lithium battery and its battery management system(BMS)

以退役的动力锂电池梯次应用性能为研究基础,运用分数阶卡尔曼滤波算法和粒子滤波算法公式推演验证,采用离线辨识法构建锂电池健康寿命模型,从而准确、快速地判别出锂电池的健康状态。用于梯次应用锂电池项目的电池管理系统,除常规的自动充放电控制,以及电流、电压和温度告警保护等功能外,分别从研究内容、试验方法和试验结果 3个方面,重点对健康状态、有源均衡和荷电状态等功能进行了研究。

Based on the research on the application performance of retired power lithium batteries,the fractional Kalman filter algorithm and the particle filter algorithm were used to deduce and verify the formula,and the offline identification method was used to build a lithium battery health life model,thereby accurately and quickly determine the health status of the lithium battery.The battery management system(BMS) could be used for echelon application lithium battery projects,in addition to the functions of conventional automatic charging discharge control and current,voltage,temperature alarm protection,from three aspects of research content,test methods and test results,the research was carried out focusing on functions such as health status,active balance and state of charge.