review·Renewable and Sustainable Energy Reviews·Jul 12, 2019GREEN OA

Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review

YLYi LiKLKailong LiuCorresponding authorAFAoife FoleyAZAlana ZülkeMBMaitane Berecibar

Centre National de la Recherche Scientifique · The Faraday Institution · +5 more institutions

Indexed incrossref

Abstract

No abstract available for this paper.

Citation impact

1,124
total citations
FWCI
55.34
Percentile
100%
References
152
Citations per year

Authors

8
  • YL
    Yi Li

    Centre National de la Recherche Scientifique, The Faraday Institution, Vrije Universiteit Brussel, Lancaster University

  • KL
    Kailong LiuCorresponding

    University of Warwick

  • AF
    Aoife Foley

    Queen's University Belfast

  • AZ
    Alana Zülke

    Centre National de la Recherche Scientifique, Lancaster University, The Faraday Institution

  • MB
    Maitane Berecibar

    Vrije Universiteit Brussel

Topics & keywords

Topics
  • Primary topicAdvanced Battery Technologies Research100%
  • Advancements in Battery Materials99%
  • Reliability and Maintenance Optimization99%
Keywords
  • Estimation
  • Lithium (medication)
  • Ion
  • Computer science
  • Reliability engineering
  • Environmental science
  • Psychology
  • Chemistry
No related works found for this paper.

Funding

  • IC
    Imperial College London
  • EC
    European Commission
    Award: 685716
  • QU
    Queen's University Belfast
  • QU
    Queen's University
  • EA
    Engineering and Physical Sciences Research Council
  • IU
    Innovate UK
    Award: 104183
  • H2
    Horizon 2020