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基于扩展卡尔曼滤波的LiFePO4电池荷电状态估计

更新时间:2020-06-10 11:19:46 大小:189K 上传用户:xiaohei1810查看TA发布的资源 标签:卡尔曼滤波 下载积分:5分 评价赚积分 (如何评价?) 收藏 评论(0) 举报

资料介绍

为了准确估计电池的荷电状态(state—of—charge),在研究电池电化学阻抗谱模型的基础上得出了适合工程应用的电池简化等效电路模型,通过实验对模型进行了参数估计,并在模型的基础上采用扩展卡尔曼滤波法(EKF)对电池的SOC进行估计并使用Matlab进行了仿真验证,结果证明扩展卡尔曼滤波法能准确地估计电池的SOC0

To accurately estimate the state-of-charge (SOC) of the battery, based on the study of electrochemical impedance spectroscopy model, a simple equivalent circuit model was gained, which was appropriate to real application. And then based on some experiments, the parameter of the equivalent circuit model was estimated. The extended Kalman filter was used to predict the SOC of battery. In the end, Matlab was used to verify this method, and the result show that the EKF can accurately estimate the SOC of battery.

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基于扩展卡尔曼滤波的LiFePO4电池荷电状态估计.pdf 189K

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