Propagation mechanisms and diagnosis of parameter inconsistency within Li-Ion battery packs

Fei Feng*, Xiaosong Hu, Lin Hu, Fengling Hu, Yang Li, Lei Zhang

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

222 Citations (Scopus)

Abstract

Traction batteries constitute a core technology for electric vehicles. The cells used in such batteries are usually connected in a series-parallel structure. Significant degradation in energy density, cycle life, and safety occurs with battery usage, thanks to discrepancies among cell parameters, such as resistance, capacity, and State of Charge. Hence, it is imperative to explore propagation mechanisms of parameter inconsistency and develop methods to diagnose them. The state of the art in the two aspects are elaborated from three perspectives of internal, external, and coupling effects. Modeling approaches for parameter inconsistency available in the existing literature are comprehensively surveyed, with the purpose of spurring innovative ideas for establishing new models. Methods of data processing and feature extraction are systematically summarized in order to promote diagnostic efficiency and credibility. Moreover, methods of battery inconsistency evaluation and diagnosis are reviewed with the aim of catalyzing the development of new diagnostic algorithms. Finally, existing problems and future trends in the field of battery pack inconsistency research are elucidated.

Original languageEnglish
Pages (from-to)102-113
Number of pages12
JournalRenewable and Sustainable Energy Reviews
Volume112
DOIs
Publication statusPublished - Sept 2019

Keywords

  • Diagnosis method
  • Feature extraction
  • Li-ion battery packs
  • Parameter inconsistency
  • Propagation mechanism

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