Volume 5: Innovative Solutions for Energy Transitions: Part IV

State-of-health Estimation of Lithium-ion Battery Based on Grey Relational Analysis Method Zhenpo Wang, Changgui Yuan, Xiaohui Li, Xiaoyu Li

Abstract

Lithium-ion battery state-of-health estimation plays an important role in battery management system in electric vehicles. Here, we report a novel method for battery state-of-health estimation through grey relational analysis with entropy weight method. Firstly, an interpolation method is proposed to obtain the differential voltage curves. Then health performance indicators are extracted from the partial differential voltage curve considering the inflection points. Secondly, the evaluation indexes are proposed by using entropy weight method to evaluate the significance of health performance indicators in the partial differential voltage curve. The evaluation indexes of the fresh cycle battery are defined as reference sequence and others as comparative sequences. Then the proposed method to calculate the grey relational degrees between the reference and comparative sequences and the results are applied to analyze battery health condition. At last, the corresponding experiment indicates that the proposed method can accurate estimation battery health condition.

Keywords lithium-ion battery, state of health, differential voltage curve, grey relational analysis method