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State-of-health estimation for Li-ion batteries by combing the incremental capacity analysis method with grey relational analysis

  • Xiaoyu Li
  • , Zhenpo Wang*
  • , Lei Zhang
  • , Changfu Zou
  • , David D. Dorrell
  • *Corresponding author for this work
  • Beijing Institute of Technology
  • Chalmers University of Technology
  • University of KwaZulu-Natal

Research output: Contribution to journalArticlepeer-review

Abstract

An accurate battery state-of-health (SOH) monitoring is crucial to guarantee safe and reliable operation of electric vehicles (EVs). In this paper, an incremental capacity analysis (ICA) method for battery SOH estimation is proposed. This uses grey relational analysis in combination with the entropy weight method. First, an interpolation method is employed to obtain incremental capacity (IC) curves. The health indexes are then extracted from the partial IC curves for grey relational analysis, and the entropy weight method is used to evaluate the significance of each health index. The battery SOH is assessed by calculating the grey relational degree between the reference and comparative sequences. Experimental tests are conducted on two battery cells with the same specifications to verify the efficacy of the proposed method. The results show that the maximum estimation error is limited to within 4%, thus proving its effectiveness.

Original languageEnglish
Pages (from-to)106-114
Number of pages9
JournalJournal of Power Sources
Volume410-411
DOIs
Publication statusPublished - 15 Jan 2019

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Entropy weight method
  • Grey relational analysis
  • Incremental capacity analysis
  • Lithium-ion batteries
  • State-of-health

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