李华,于少娟

• 1:太原科技大学电子信息工程学院

摘要(Abstract)：

针对卡尔曼滤波(KF)估计SOC过程中噪声的统计特性与实际不符时,滤波精度严重降低问题,为提高SOC估计精度,在二阶RC电池等效电路模型的基础上,提出一种自适应扩展卡尔曼滤波算法(AEKF),通过自适应协方差匹配算法对系统噪声协方差和测量误差协方差进行实时更新,有效解决了滤波参数设置不合理所造成的SOC偏差,实现了系统状态的最优化预测。利用MATLAB进行仿真比较,验证了新算法能够精确地估计SOC,对环境具有一定的适应能力,可以有效校正SOC初值,并降低累积误差和噪声干扰。

关键词(KeyWords)： 磷酸铁锂电池;SOC;扩展卡尔曼滤波器;自适应协方差匹配算法

Abstract:

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基金项目(Foundation):

作者(Author): 李华,于少娟

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