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Battery state of health estimation using variable separation algorithm based on quasi-Newton

  • Cheng Wang,
  • Jing Chen,
  • Lianyuan Cheng,
  • Yingjiao Rong

摘要

In this paper, two variable separation algorithms based on quasi-Newton are proposed to estimate and predict the battery state of health. Based on the coupling characteristic of the state of health model, the variable separation algorithm can reduce the dimensionality and then improve the identification accuracy. Additionally, the introduction of the rank-one quasi-Newton method and rank-two quasi-Newton method improves the convergence rate. Theory and experiment validate the effectiveness of the proposed algorithms.