Cited by 45Advanced Battery Technologies ResearchAdvancements in Battery MaterialsStructural Health Monitoring Techniques

Cross-Material Battery Capacity Estimation Using Hybrid-Model Fusion Transfer Learning

Zhao, Jingyuan, Qu, Xudong, Han, Xuebing, Wu, Yuyan, Burke, Andrew F.·2025·Journal of Power Sources

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Crossref · 10.1016/j.jpowsour.2024.235674

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70 of 70 references verified0 citation errors · 0 not checkable

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Authors
Zhao, J., Qu, X., Han, X., Wu, Y., & Burke, A. F.
Affiliations
  • University of California, Davis (US)
  • Hubei University of Arts and Science (CN)
  • Tsinghua University (CN)
  • Stanford University (US)
Corresponding author
Zhao, Jingyuan
Venue
Journal of Power Sources
Publisher
Elsevier BV
Published
2025-01
Volume
625
Pages
235674
ISSN
0378-7753 (ISSN-L)
OpenAlex
W4403753127
Cited by
45
References
70
Citations by year
2026: 19 · 2025: 24 · 2024: 2
FWCI
4.86
Type
journal article
Language
en
Open access
closed
Locations
Journal of Power Sources (publishedVersion)
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
  • Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
Keywords
battery capacity estimation, battery health assessment, convolutional neural networks, self-attention, lithium iron phosphate batteries, NMC batteries, ternary cathode materials, battery degradation, operational history

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