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

Abstract

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.