文章摘要
孙国强,任佳琦,成乐祥,等.基于分数阶阻抗模型的磷酸铁锂电池荷电状态估计[J].电力系统自动化. DOI: 10.7500/AEPS20180317003.
, et al.State of Charge Estimation of LiFePO4 Battery Based on a Fractional-order Impedance Model[J].Automation of Electric Power Systems. DOI: 10.7500/AEPS20180317003.
基于分数阶阻抗模型的磷酸铁锂电池荷电状态估计
State of Charge Estimation of LiFePO4 Battery Based on a Fractional-order Impedance Model
DOI:10.7500/AEPS20180317003
关键词: 锂离子电池  荷电状态估计  分数阶阻抗模型  分数阶无迹卡尔曼滤波
KeyWords: lithium-ion battery  state of charge(SOC)  fractional-order impedance model  fractional-order unscented Kalman filter(FUKF)
上网日期:2018-10-09
基金项目:国家自然科学基金,江苏省自然科学基金醒目,国家电力公司科技项目
作者单位E-mail
孙国强 河海大学能源与电气学院 hhusunguoqiang@163.com 
任佳琦 河海大学能源与电气学院 webrenjiaqi@126.com 
成乐祥 南京市供电公司 chenglx@js.sgcc.com.cn 
朱瑛 河海大学能源与电气学院 yingzhu@hhu.edu.cn 
卫志农 河海大学能源与电气学院 wzn_nj@263.com 
臧海祥 河海大学能源与电气学院 zanghaixiang@hhu.edu.cn 
摘要:
      锂电池荷电状态(SOC)估计是电池管理系统中不可或缺的重要组成部分。锂电池传统整数阶等效电路模型未充分考虑其内部电化学反应现象,故将导致SOC估计结果偏离真实状态。文章以磷酸铁锂电池为研究对象,提出一种基于分数阶阻抗模型的锂电池SOC估计方法,该方法利用分数阶元件表征锂电池内部固液界面的输运现象和极化效应,基于分数阶微分理论建立状态转移方程和系统观测方程,并针对锂电池高度非线性的工作特性,利用无迹变换(UT)逼近原始状态分布,运用分数阶无迹卡尔曼滤波算法估计锂电池SOC。实验结果表明,分数阶阻抗模型能准确描述锂电池工作特性,所提出的FUKF算法在估计精度和跟踪速度上有一定提高。
Abstract:
      State of charge (SOC) estimation plays an important role in the lithium-ion battery management system. Traditional integer-order equiv-alent models capture the lithium battery dynamics with limited knowledge, resulting in the SOC estimation results deviating from the true states. This paper proposes a novel fractional-order impedance model for LiFePO4 battery SOC estimation. The proposed method employs the constant phase element (CPE) to build the lithium-ion battery impedance model and introduces a fractional-order calculous to establish the state transition and systematic equation. Unscented transformation (UT) is adopted for the non-linear characteristic of the lithium-ion battery and then a fractional-order unscented Kalman filter (FUKF) is synthesized to estimate the lithium-ion battery SOC. Experimental results show that the proposed method performs well in the modeling and SOC estimation of lithium-ion batteries.
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