The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Specialized deep neural networks for battery health prognostics: Opportunities and challenges
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Citations
Cites
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Cited by
Sorted by citations
Battery Safety: Machine Learning-Based Prognostics
Zhao, J., Feng, X., Pang, Q., Fowler, M., Lian, Y., Ouyang, M., & Burke, A. F. (2024) · Progress in Energy and Combustion Science · doi:10.1016/j.pecs.2023.101142 · Cited by 216
Self-citationBattery safety: Fault diagnosis from laboratory to real world
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Self-citationZhao, J., Feng, X., Wang, J., Lian, Y., Ouyang, M., & Burke, A. F. (2023) · Applied Energy · doi:10.1016/j.apenergy.2023.121949 · Cited by 152
Self-citationArtificial Intelligence in Gas Sensing: A Review
Chowdhury, M. A. Z., & Oehlschlaeger, M. A. (2025) · ACS Sensors · doi:10.1021/acssensors.4c02272 · Cited by 150
Rapid health estimation of in-service battery packs based on limited labels and domain adaptation
Deng, Z., Xu, L., Liu, H., Hu, X.-S., Wang, B., & Zhou, J.-J. (2023) · Journal of Energy Chemistry · doi:10.1016/j.jechem.2023.10.056 · Cited by 110
Metadata
- Authors
- Zhao, J., Han, X., Ouyang, M., & Burke, A. F.
- Affiliations
- University of California, Davis (US)
- Tsinghua University (CN)
- Corresponding author
- Ouyang, Minggao
- Burke, Andrew F.
- Venue
- Journal of Energy Chemistry
- Publisher
- Elsevier BV
- Published
- 2023-12
- Volume
- 87
- Pages
- 416-438
- ISSN
- 2095-4956 (ISSN-L)
- OpenAlex
- W4386566202
- Cited by
- 129
- References
- 52
- Citations by year
- 2026: 23 · 2025: 55 · 2024: 44 · 2023: 7
- FWCI
- 9.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Energy Chemistry (publishedVersion)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Battery Modeling and Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
- Keywords
- lithium-ion batteries, battery health prognostics, deep learning, transformer models, transfer learning, physics-informed machine learning, generative adversarial networks, deep reinforcement learning, battery state estimation, battery management
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