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Parameter identification and state of heath evaluation for Nickel-Metal Hydride batteries based on an improved clustering algorithm

机译:基于改进聚类算法的镍金属氢化物电池的参数识别与良性评价

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The modelling of the chemical reactor behavior is always difficult task due to the absence of more detailed knowledge about the considered chemical transformation. We treat in this context the Nickel-Metal Hydride (Ni-MH) battery system. In this paper, an improved fuzzy c-regression model is proposed in order to develop a Ni-MH battery model on which a modified distance is introduced in the objective function of fuzzy c-regression model algorithm in the purpose of taking into account the outliers. After that the obtained model is employed to estimate the Ni-MH battery's State Of Heath (SOH). The experimental results indicate that the proposed method can be ensured an acceptable accuracy of the SOH estimation for Ni-MH battery system.
机译:由于没有关于考虑的化学转化的更详细知识,化学反应器行为的建模始终是困难的任务。我们在这种情况下治疗镍 - 金属氢化物(Ni-MH)电池系统。在本文中,提出了一种改进的模糊C-回归模型,以便开发一个Ni-MH电池模型,其中在模糊C-回归模型算法的目标函数中引入了模糊C-返回模型算法的目的,以考虑到异常值。之后,使用所获得的模型来估计Ni-MH电池的HEATH状态(SOH)。实验结果表明,可以确保所提出的方法可接受的Ni-MH电池系统的SOH估计精度。

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