The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Battery health estimation with degradation pattern recognition and transfer learning
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Cites
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G. S., Davis, A., Dean, J., Devin, M., et al. (2016) · arXiv · doi:10.48550/arxiv.1603.04467 · Cited by 9,408
Data-driven prediction of battery cycle life before capacity degradation
Severson, K. A., Attia, P. M., Jin, N., Perkins, N., Jiang, B., Yang, Z., Chen, M. H., Aykol, M., Herring, P. K., Fraggedakis, D., et al. (2019) · Nature Energy · doi:10.1038/s41560-019-0356-8 · Cited by 3,228
The lithium-ion battery: State of the art and future perspectives
Zubi, G., Dufo-López, R., Carvalho, M., & Pasaoglu, G. (2018) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2018.03.002 · Cited by 2,563
A review on the key issues of the lithium ion battery degradation among the whole life cycle
Han, X., Lu, L., Zheng, Y., Feng, X., Li, Z., Li, J., & Ouyang, M. (2019) · eTransportation · doi:10.1016/j.etran.2019.100005 · Cited by 1,745
Zhang, Y., Xiong, R., He, H., & Pecht, M. G. (2018) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2018.2805189 · Cited by 1,326
Hu, X., Xu, L., Lin, X., & Pecht, M. (2020) · Joule · doi:10.1016/j.joule.2019.11.018 · Cited by 1,320
Self-citationData-driven health estimation and lifetime prediction of lithium-ion batteries: A review
Li, Y., Liu, K., Foley, A. M., Zülke, A., Berecibar, M., Nanini-Maury, E., Van Mierlo, J., & Hoster, H. E. (2019) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2019.109254 · Cited by 1,193
Waag, W., Fleischer, C., & Sauer, D. U. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2014.02.064 · Cited by 1,059
Long Short-Term Memory Networks for Accurate State-of-Charge Estimation of Li-ion Batteries
Chemali, E., Kollmeyer, P. J., Preindl, M., Ahmed, R., & Emadi, A. (2018) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2017.2787586 · Cited by 906
Han, X., Ouyang, M., Lu, L., Li, J., Zheng, Y., & Li, Z. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.11.029 · Cited by 822
Cited by
Prognostics of battery capacity based on charging data and data-driven methods for on-road vehicles
Deng, Z., Xu, L., Liu, H., Hu, X., Duan, Z., & Xu, Y. (2023) · Applied Energy · doi:10.1016/j.apenergy.2023.120954 · Cited by 268
Self-citationWang, Y., Guo, S., Cui, Y., Deng, L., Zhao, L., Li, J., & Wang, Z. (2025) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2025.116125 · Cited by 107
Almaita, E., Alshkoor, S., Abdelsalam, E., & Almomani, F. (2022) · Journal of Energy Storage · doi:10.1016/j.est.2022.104761 · Cited by 84
He, Y., Deng, Z., Chen, J., Li, W., Zhou, J., Xiang, F., & Hu, X. (2024) · Journal of Energy Chemistry · doi:10.1016/j.jechem.2024.06.024 · Cited by 75
Self-citationTakyi-Aninakwa, P., Wang, S., Zhang, H., Yang, X., & Fernandez, C. (2022) · Applied Energy · doi:10.1016/j.apenergy.2022.120043 · Cited by 75
Metadata
- Authors
- Deng, Z., Lin, X., Cai, J., & Hu, X.
- Venue
- Journal of Power Sources
- Publisher
- Elsevier BV
- Published
- 2022-03
- Volume
- 525
- Pages
- 231027
- ISSN
- 0378-7753 (ISSN-L)
- OpenAlex
- W4210592941
- Cited by
- 300
- References
- 35
- FWCI
- 17.32
- Type
- journal article
- Language
- en
- Open access
- closed
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- Deng, Z., Lin, X., Cai, J., & Hu, X. (2022). Battery health estimation with degradation pattern recognition and transfer learning. Journal of Power Sources. https://doi.org/10.1016/j.jpowsour.2022.231027
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
