基于信息融合的LiFePO_4动力电池组SOC估计  

SOC estimation for LiFePO_4 high-power batteries based on information fusion

作　　者：何耀[1] 张陈斌[1] 刘兴涛[1] 陈宗海[1] 

机构地区：[1]中国科学技术大学自动化系,合肥230027

出　　处：《控制与决策》2014年第1期188-192,共5页Control and Decision

基　　金：国家自然科学基金项目(61075073);国家863计划项目(2009AA11A113)

摘　　要：针对复杂工况下LiFePO4动力电池组state-of-charge(SOC)估计不准确的问题,基于信息融合技术提出一种SOC估计信息融合架构和多模型切换估计(MMSE)算法.该算法首先对充放电过程进行特征提取和模式分类,针对特定的模式进行模型优化;然后在系统运行时根据特征匹配结果切换估计模型,实现优化估计;最后通过纯电动客车实际运行数据的仿真实验验证了所提出MMSE算法的可行性和有效性.Aiming at the inaccuracy problem of state-of-charge（SOC） estimation under the complex conditions, an SOC estimation information fusion framework and a multi-model switch estimation（MMSE） algorithm based on the information fusion technology are proposed for LiFePO4 high-power batteries. This algorithm carries out the feature extraction and the pattern classification of the charge and discharge processes, and then re-optimizes the estimation model according to the different patterns. The MMSE algorithm switches to the matching estimation model to acquire better performance based on the feature matching. The result of simulation with the running data of pure electric bus shows the feasibility and effectiveness of the SOC estimation based on the MMSE algorithm.

关 键 词：LiFePO4动力电池组 荷电状态 信息融合架构 多模型切换估计 

分 类 号：TM912[电气工程—电力电子与电力传动]