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 and voltage gradient curves.
“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]
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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].”
BackgroundMethodPredicting the state of charge and health of batteries using data-driven machine learning
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- 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 › Advanced Battery Technologies Research
- 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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