摘要
电池特性建模及模型参数在线估计是电动汽车电池管理系统的关键技术,以磷酸铁锂电池这一非线性系统为研究对象,以包含分数阶元件的简化电池电化学阻抗谱模型为基础,建立了该模型的状态转移方程和系统观测方程,运用分数阶联合卡尔曼滤波器(FJKF)对该模型的扩散极化电压和模型参数进行了在线估计。试验结果表明,该模型能较好地表征磷酸铁锂电池的动态特性,分数阶联合卡尔曼滤波算法在参数估计过程中能够保持很好的精度,同时该方法对多种测试工况都有较好的适用性,算法估计得到的模型参数值具有较好的稳定性。
Battery modeling and online battery model parameter estimation are the key technologies of EV battery management system. Based on the battery simplified electrochemical impedance spectroscopy which contains a fractional component, this paper establishes the state transition and systematic observation equations for the nonlinear system of LiFePO4 secondary battery.Then, the diffusion polarization voltage and model parameters are estimated online with the fractional joint Kalman filter (FJKF). The experimental results show that, this model can reflect the dynamic characteristics very well, and FJKF parameter estimation algorithm can maintain good accuracy.Meanwhile, the method is suitable for a variety of load conditions. The model parameters obtained by this algorithm have good stability.
作者
李晓宇
朱春波
魏国
逯仁贵
Li Xiaoyu;Zhu Chunbo;Wei Guo;Lu Rengui(School of Electrical Engineering and Automation Harbin Institute of Technology Harbin 150001 China)
出处
《电工技术学报》
EI
CSCD
北大核心
2016年第24期141-149,共9页
Transactions of China Electrotechnical Society
基金
国家高技术研究发展计划(863计划)(2012AA111003)
国家自然科学基金(51277037)
黑龙江省应用技术研究与开发计划项目(GA13A202)资助
关键词
磷酸铁锂电池
分数阶电池模型
电化学阻抗谱
分数阶联合卡尔曼滤波
LiFePO4 battery
fractional battery model
electrochemical impedance spectroscopy
fractional joint Kalman filter
