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Open Access

Peer-reviewed

Research Article

Multiview state-of-health estimation for lithium-ion batteries using time–frequency image fusion and attention-based deep learning

Peijian Jin,

Roles Software

Affiliations School of Emergency Science and Engineering, Jilin Jianzhu University, Changchun, Jilin, China, Jilin Provincial Key Laboratory of Fire Risk Prevention and Emergency Rescue for Building, Changchun, PR China
⨯
Shuo Yang ,

Roles Data curation

* E-mail: 2389621412@qq.com

Affiliation School of Emergency Science and Engineering, Jilin Jianzhu University, Changchun, Jilin, China

https://orcid.org/0009-0008-3493-7009

⨯
Xinwan Xu,

Roles Methodology

Affiliation School of Emergency Science and Engineering, Jilin Jianzhu University, Changchun, Jilin, China
⨯
Chaoqun Li,

Roles Software

Affiliation School of Emergency Science and Engineering, Jilin Jianzhu University, Changchun, Jilin, China
⨯
Shihao Guo,

Roles Validation

Affiliation School of Emergency Science and Engineering, Jilin Jianzhu University, Changchun, Jilin, China
⨯
Wei Yan,

Roles Project administration

Affiliation School of Emergency Science and Engineering, Jilin Jianzhu University, Changchun, Jilin, China
⨯
Hui Miao,

Roles Data curation

Affiliation Ji Lin Sinopoly New Energy Technology Co, Ltd., Liaoyuan, Jilin, China
⨯
Shimei Sun

Roles Writing – review & editing

Affiliation School of Emergency Science and Engineering, Jilin Jianzhu University, Changchun, Jilin, China
⨯

Multiview state-of-health estimation for lithium-ion batteries using time–frequency image fusion and attention-based deep learning

Peijian Jin,
Shuo Yang,
Xinwan Xu,
Chaoqun Li,
Shihao Guo,
Wei Yan,
Hui Miao,
Shimei Sun

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Published: November 3, 2025
https://doi.org/10.1371/journal.pone.0335351

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