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磷酸铁锂电池倍率容量特性建模及荷电状态估算
引用本文:张金龙,佟微,李端凯,漆汉宏,张纯江.磷酸铁锂电池倍率容量特性建模及荷电状态估算[J].电工技术学报,2017,32(7).
作者姓名:张金龙  佟微  李端凯  漆汉宏  张纯江
作者单位:燕山大学电气工程学院电力电子节能与传动控制河北省重点实验室 秦皇岛 066004
基金项目:河北省自然科学基金,国家自然科学基金
摘    要:针对磷酸铁锂蓄电池,首先采用解析型动力学电池模型(KBM)对电池的倍率容量特性进行描述,进而推导出双井荷电状态(SOC)的数学表达式;为建立SOC与电池电压的联系,进一步将KBM与电动势模型相结合形成综合模型;最后,基于该综合模型及非线性滤波算法实现SOC估算。实验结果表明,该模型可以体现锂电池的倍率容量特性及可用容量恢复特性,双井SOC估算结果可更全面地体现锂电池的SOC;此外,这种基于非线性滤波的SOC估算策略还具备初始误差自校正能力。

关 键 词:磷酸铁锂电池  倍率容量特性  非线性滤波  荷电状态估算

Rate Capacity Modeling and State of Charge Estimation of LiFePO4 Battery
Zhang Jinlong,Tong Wei,Li Duankai,Qi Hanhong,Zhang Chunjiang.Rate Capacity Modeling and State of Charge Estimation of LiFePO4 Battery[J].Transactions of China Electrotechnical Society,2017,32(7).
Authors:Zhang Jinlong  Tong Wei  Li Duankai  Qi Hanhong  Zhang Chunjiang
Abstract:Aiming at LiFePO4 battery,firstly the rate capacity performance is described by kinetic battery model(KBM) in this paper.And then the mathematical expression of state of charge(SOC) for the double well is derived.In order to further connect SOC with battery terminal voltage,a comprehensive model is established by combining KBM with an electromotive force(EMF) model.Finally SOC estimation is realized based on this combined model and a nonlinear filter.Experimental results show that,battery rate capacity performance and available capacity recovery phenomenon can be manifested through this combined model,also the battery state of charge can be described more thoroughly.Besides,the nonlinear filter based SOC estimation strategy also shows an error-correcting capability.
Keywords:LiFePO4 battery  rate capacity performance  nonlinear filter  state of charge estimation
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