【摘 要】
：
电池动态模型的参数识别以及荷电状态(SOC)估算是电动车电池管理系统(BMS)中的关键技术。电池的频率响应函数可以揭示其在一个宽的频率范围内的动力学行为。系统参数和正弦波输入信号的幅值和相位角之间的关系是一个深入研究电池动力学行为的有效手段。本文在对电池的电化学阻抗谱(EIS)分析的基础上采用分数阶等效电路模型来模拟锂离子电池内部动力学特性。先是对开路电动势与SOC关系进行拟合以实时更新锂电池开路
【出 处】
：
第十六届全国非线性振动暨第十三届全国非线性动力学和运动稳定性学术会议
论文部分内容阅读
电池动态模型的参数识别以及荷电状态(SOC)估算是电动车电池管理系统(BMS)中的关键技术。电池的频率响应函数可以揭示其在一个宽的频率范围内的动力学行为。系统参数和正弦波输入信号的幅值和相位角之间的关系是一个深入研究电池动力学行为的有效手段。本文在对电池的电化学阻抗谱(EIS)分析的基础上采用分数阶等效电路模型来模拟锂离子电池内部动力学特性。先是对开路电动势与SOC关系进行拟合以实时更新锂电池开路电压,结合智能算法与传统算法辨识出锂电池在不同SOC状态下的模型参数,重点分析了SOC与Warburg阻抗元件中分数阶阶次的关系,并发现阶次与电池内部动力学行为存在对应关系。然后通过混合脉冲测试与动态应力测试对模型进行仿真验证。最后,将分数阶微积分算法引入扩展卡尔曼滤波算法(EKF)并在多工况下进行SOC估算,结果证明该算法能准确地在线估计SOC,并能修正初始值不确定和噪声引起的预测偏差,比传统SOC估算方法具有更高的预测精度。
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