Online Fault Diagnosis of External Short Circuit for Lithium-Ion Battery Pack

Rui Xiong*, Ruixin Yang, Zeyu Chen, Weixiang Shen, Fengchun Sun

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

155 Citations (Scopus)

Abstract

Battery safety is one of the most crucial issues in the utilization of lithium-ion batteries (LiBs) for all-climate electric vehicles. Short circuit, overcharge, and overheat are three common field failures of LiBs. In this paper, online fault diagnosis for external short circuit (ESC) of LiB packs is investigated. The experiments are carried out to obtain and compare ESC characteristics of 18650-type NMC battery pack and single cell. Based on the analysis of experimental results, a two-step equivalent circuit model is established to describe the ESC process and an online model-based scheme is proposed to diagnose ESC faults of battery packs. The proposed scheme is evaluated by experimental data. The results show that it can effectively diagnose ESC faults in 3.5 s after their occurrences with the terminal voltage error less than 25 mV. The proposed scheme has shown great generalization ability. ESC faults of battery packs under different number of cells connected in series and unavailable current information can also be diagnosed at the terminal voltage error less than 48 and 60 mV, respectively.

Original languageEnglish
Article number8648476
Pages (from-to)1081-1091
Number of pages11
JournalIEEE Transactions on Industrial Electronics
Volume67
Issue number2
DOIs
Publication statusPublished - Feb 2020

Keywords

  • All-climate electric vehicles
  • battery safety
  • external short circuit (ESC)
  • fault diagnosis
  • genetic algorithm (GA)
  • lithium-ion battery (LiB)

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