State of charge and State of health estimation method based on measurement fusion and dual extended Kalman filter for combining the inhomogeneity of cell characteristics

Jin-Hyeng Park, W. Na, Jonghoon Kim
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引用次数: 1

Abstract

This paper proposes an SOC (state of charge) and SOH (state of health) estimation technique using sensor fusion method to solve the problem of battery system stability deterioration due to voltage variation in cell-to-cell. In order to reflect the cell-to-cell variance, we use the measurement fusion method based on the multi cell model. From this model, the dual extended Kalman filter is utilized for estimating the SOC and SOH.
结合细胞特性的不均匀性,基于测量融合和双扩展卡尔曼滤波的电荷状态和健康状态估计方法
本文提出了一种基于传感器融合的SOC(充电状态)和SOH(健康状态)估计技术,以解决电池间电压变化导致电池系统稳定性下降的问题。为了反映细胞间的差异,我们采用了基于多细胞模型的测量融合方法。在此基础上,利用双扩展卡尔曼滤波对系统SOC和SOH进行估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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