新能源汽车用动力电池管理系统设计  

Design of battery management system for new energy vehicles

作　　者：刘锦绢[1] 刘贤兴[1] 孙金虎 张育华 

机构地区：[1]江苏大学电气信息工程学院,江苏镇江212013 [2]镇江恒驰科技有限公司,江苏镇江212013

出　　处：《电源技术》2013年第6期966-968,共3页Chinese Journal of Power Sources

摘　　要：电池荷电状态(SOC,state-of-charge)是新能源汽车运行时的关键参数之一。提出了由静态自学习残余电量算法、动态安时计量法和扩展卡尔曼滤波算法相结合的SOC综合估算算法。实验结果表明,综合估算算法的估算结果比普通单一算法精确,最大误差只有2%。同时,采用电子开关式集中均衡充电网络,增加了电池组内各个电池单体之间的一致性,避免了电池组内个别单体电池的过充电、过放电现象,大大增加了电池组的使用寿命。Battery SOC is one of the key parameters of a new energy vehicles. In this paper, a combination of self-learning algorithm and dynamic A.H algorithm and extended Kalman filter algorithm was use to estimate battery SOC. The experimental results show that this combinated algorithm is more accurate than the ordinary single algorithm; the error is less than 2%. Meanwhile, by using of the electronic switching networks concentrated equalizer, the designed BMS can compensate the performance inconsistency of the batteries in a battery package and reduce the chances of the batteries working overcharged and overdischarged. So, as a result, the service life of the battery package is extended.

关 键 词：电池管理 SOC估算 均衡充电 

分 类 号：TM912[电气工程—电力电子与电力传动]