Cited by 793Battery Modeling and ManagementAdvancements in Battery MaterialsMachine Learning in Materials Science

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Predicting the state of charge and health of batteries using data-driven machine learning

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Ng, Man-Fai, Zhao, Jin, Yan, Qingyu, Conduit, Gareth J., Seh, Zhi Wei·2020·Nature Machine Intelligence

DOI 10.1038/s42256-020-0156-7

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Authors: Ng, M.-F., Zhao, J., Yan, Q., Conduit, G. J., & Seh, Z. W.
Affiliations: Agency for Science, Technology and Research (SG)
Nanyang Technological University (SG)
University of Cambridge (GB)
Corresponding author: Yan, Qingyu
Conduit, Gareth J.
Seh, Zhi Wei
ORCID: Ng, Man-Fai
Zhao, Jin
Yan, Qingyu
Conduit, Gareth J.
Seh, Zhi Wei
Venue: Nature Machine Intelligence
Publisher: Springer Science and Business Media LLC
Published: 2020-03-02
Volume: 2
Issue: 3
Pages: 161-170
ISSN: 2522-5839 (ISSN-L)
DOI: 10.1038/s42256-020-0156-7
OpenAlex: W3009652674
Semantic Scholar: 86788a38467e1f2f1df713f5d5694bfee9f8ae29
Cited by: 793
References: 120
Citations by year: 2026: 126 · 2025: 152 · 2024: 164 · 2023: 134 · 2022: 110 · 2021: 81 · 2020: 26
FWCI: 32.46
Type: journal article
Language: en
Update notices: correction (2020-06-12)
Open access: green
www.repository.cam.ac.uk
Licence: www.springernature.com/gp/researchers/text-and-data-mining (tdm)
www.springernature.com/gp/researchers/text-and-data-mining (vor)
Locations: Nature Machine Intelligence (publishedVersion)
Apollo (University of Cambridge) (submittedVersion)
Apollo
Funders: National Research Foundation Singapore (NRF-NRFF2017-04)
Topics: Physical Sciences › Engineering › Automotive Engineering › Battery Modeling and Management
Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
Keywords: battery state of health, remaining useful life, battery modeling, equivalent circuit model, physics-based battery model, data-driven machine learning, high-throughput experimentation, explainable machine learning, energy storage, battery management

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