中国电机工程学报2016，Vol.36Issue(22)：6246-6253,8.DOI:10.13334/j.0258-8013.pcsee.160226
平方根采样点卡尔曼滤波在磷酸铁锂电池组荷电状态估算中的应用
Application of Square Root Sigma Point Kalman Filter to SOC Estimation of LiFePO4 Battery Pack
摘要
Abstract
State of charge (SOC) estimation technique is one of the most important functions of battery management system. The main purpose of this paper is to accurately estimate SOC of each cell in the series connected LiFePO4 battery pack. Firstly a comprehensive battery model was established based on Thevenin model and Ah counting model; and then a square root sigma point Kalman filter (SRSPKF) was adopted for SOC estimation, besides, a recursive least square (RLS) algorithm was also used to identify model parameters, in this way, model parameter identification and SOC estimation can be realized simultaneously by combined SPKF-RLS method. Theoretically speaking, by using SRSPKF, the system states were propagated in the form of square root of its variance, and thus the computation complexity of conventional SPKF can be significantly reduced. Experimental results show that, compared with SPKF, SRSPKF possesses a stronger error suppression capability of state estimation, and more accurate SOC estimation results can be obtained by SRSPKF.关键词
磷酸铁锂电池/等效模型/荷电状态估算/平方根采样点卡尔曼滤波Key words
LiFePO4 battery/equivalent model/SOC estimation/square root sigma point Kalman filter (SRSPKF)分类
信息技术与安全科学引用本文复制引用
张金龙,佟微,漆汉宏,张纯江..平方根采样点卡尔曼滤波在磷酸铁锂电池组荷电状态估算中的应用[J].中国电机工程学报,2016,36(22):6246-6253,8.基金项目
国家自然科学基金项目(51477148)；河北省自然科学基金项目(E2014203198)。Project Supported by National Natural Science Foundation of China (51477148) （51477148）
Hebei ProvincialNatural Science Foundation of China (E2014203198) （E2014203198）
