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Sustainable Energy & Fuels

Article . 2025 . Peer-reviewed

License: Royal Society of Chemistry Licence to Publish

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A novel multi-scenario battery health assessment method combining semi-supervised learning and data augmentation techniques

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2025Publisher:Royal Society of Chemistry (RSC)Journal:Sustainable Energy & Fuels, volume 9, pages 816-832 (eissn: 2398-4902,

Authors: Xianghui Qiu; Jisheng Ren; Shuangfeng Wang;

doi: 10.1039/d4se01231c

A novel multi-scenario battery health assessment method combining semi-supervised learning and data augmentation techniques

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Abstract

Data-driven methods are widely claimed to be the most promising candidates for online battery health assessment estimation.

Related Organizations

South China University of Technology
China (People's Republic of)
South China University of Technology
China (People's Republic of)

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Fields of Science (3) View all

engineering and technology

electrical engineering, electronic engineering, information engineering

Fields of Science

engineering and technology

electrical engineering, electronic engineering, information engineering

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