Online state of health estimation on NMC cells based on predictive analytics
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Features derived from the charging and discharging curve are by far the most commonly used inputs for battery health prediction.
“Features derived from the charging and discharging curve are by far the most commonly used inputs because typical battery management systems collect current–voltage data13–18.”
From Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning (2020) · cites this paper as [16]
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 [78]
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- Authors
- Berecibar, M., Devriendt, F., Dubarry, M., Villarreal, I., Omar, N., Verbeke, W., & Van Mierlo, J.
- Affiliations
- Vrije Universiteit Brussel (BE)
- University of Hawaiʻi at Mānoa (US)
- Ikerlan (ES)
- Corresponding author
- Berecibar, Maitane
- Venue
- Journal of Power Sources
- Publisher
- Elsevier BV
- Published
- 2016-07
- Volume
- 320
- Pages
- 239-250
- ISSN
- 0378-7753 (ISSN-L)
- OpenAlex
- W2343549641
- Cited by
- 202
- References
- 56
- Citations by year
- 2026: 9 · 2025: 11 · 2024: 26 · 2023: 25 · 2022: 23 · 2021: 29 · 2020: 31 · 2019: 22 · 2018: 9 · 2017: 12 · 2016: 5
- FWCI
- 13.94
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Power Sources (publishedVersion)
- Lirias (submittedVersion)
- VUBIR (Vrije Universiteit Brussel) (submittedVersion)
- Funders
- Basque Government (IE14-388)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
- Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
- Keywords
- state of health estimation, lithium-ion batteries, NMC cells, battery management systems, incremental capacity analysis, differential voltage analysis, battery degradation, supervised learning, multilayer perceptron, support vector machine, ordinary least squares, online estimation
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