The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
A novel state of health estimation method of Li-ion battery using group method of data handling
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“Processed external features are normally extracted from differential charging curves under constant current rate, such as IC/DV curves [77,78] and voltage gradient curves (dV/dt) [79,80].”
From Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review (2019) · cites this paper as [79]
Citations
Cites
A review on the key issues for lithium-ion battery management in electric vehicles
Lu, L., Han, X., Li, J., Hua, J., & Ouyang, M. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2012.10.060 · Cited by 4,837
Rashid, R. (1988) · Cited by 2,641
Polynomial Theory of Complex Systems
Ivakhnenko, A. G. (1971) · IEEE Transactions on Systems Man and Cybernetics · doi:10.1109/tsmc.1971.4308320 · Cited by 1,700
Prognostics methods for battery health monitoring using a bayesian framework
Saha, B., Goebel, K., Poll, S., & Christophersen, J. (2009) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2008.2005965 · Cited by 831
Hu, C. K., Youn, B. D., & Chung, J. (2011) · Applied Energy · doi:10.1016/j.apenergy.2011.08.002 · Cited by 561
Weng, C., Cui, Y., Sun, J., & Peng, H. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.02.012 · Cited by 561
Wu, J., Zhang, C., & Chen, Z. (2016) · Applied Energy · doi:10.1016/j.apenergy.2016.04.057 · Cited by 531
Self-citationChen, Z., Mi, C. C., Fu, Y., Xu, J., & Gong, X. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.03.158 · Cited by 280
Self-citationA new model for State-of-Charge (SOC) estimation for high-power Li-ion batteries
He, Y., Liu, X., Zhang, C., & Chen, Z. (2012) · Applied Energy · doi:10.1016/j.apenergy.2012.08.031 · Cited by 276
Self-citationLiu, X., Chen, Z., Zhang, C., & Wu, J. (2014) · Applied Energy · doi:10.1016/j.apenergy.2014.02.072 · Cited by 235
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Data-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
“Processed external features are normally extracted from differential charging curves under constant current rate, such as IC/DV curves [77,78] and voltage gradient curves (dV/dt) [79,80].”
BackgroundMethodPredicting the state of charge and health of batteries using data-driven machine learning
Ng, M.-F., Zhao, J., Yan, Q., Conduit, G. J., & Seh, Z. W. (2020) · Nature Machine Intelligence · doi:10.1038/s42256-020-0156-7 · Cited by 793
Yang, D., Zhang, X., Pan, R., Wang, Y., & Chen, Z. (2018) · Journal of Power Sources · doi:10.1016/j.jpowsour.2018.03.015 · Cited by 765
Self-citationRandom forest regression for online capacity estimation of lithium-ion batteries
Li, Y., Zou, C., Berecibar, M., Nanini-Maury, E., Chan, J. C.-W., van den Bossche, P., Van Mierlo, J., & Omar, N. (2018) · Applied Energy · doi:10.1016/j.apenergy.2018.09.182 · Cited by 727
Wei, J., Dong, G., & Chen, Z. (2018) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2017.2782224 · Cited by 643
Self-citation
Metadata
- Authors
- Wu, J., Wang, Y., Zhang, X., & Chen, Z.
- Affiliations
- University of Science and Technology of China (CN)
- Corresponding author
- Chen, Zonghai
- Venue
- Journal of Power Sources
- Publisher
- Elsevier BV
- Published
- 2016-09
- Volume
- 327
- Pages
- 457-464
- ISSN
- 0378-7753 (ISSN-L)
- OpenAlex
- W2501990625
- Cited by
- 235
- References
- 30
- Citations by year
- 2026: 6 · 2025: 17 · 2024: 22 · 2023: 29 · 2022: 25 · 2021: 43 · 2020: 41 · 2019: 20 · 2018: 17 · 2017: 15
- FWCI
- 15.10
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Power Sources (publishedVersion)
- Funders
- National Natural Science Fund of China (61375079)
- China Scholarship Council (201606340099)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Battery Modeling and Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Keywords
- lithium-ion batteries, state of health estimation, group method of data handling, polynomial neural network, battery management, battery health monitoring
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