The DOI matches its Crossref record; 55 of the 56 references it cites were found in a registry or an index.
Online state of health estimation on NMC cells based on predictive analytics
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In the citing paper
“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]
In the citing paper
“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]
Citations
Cites
1 retracted
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Research works printed but not linked: 1
- A.D, 2014, The value of battery diagnostics and prognostics, J. Energy Power Sources, 1, 242
Cited by
Sorted by citations
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
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].”
BackgroundSelf-citationZhang, Y., Tang, Q., Zhang, Y., Wang, J., Stimming, U., & Lee, A. A. (2020) · Nature Communications · doi:10.1038/s41467-020-15235-7 · Cited by 889
Predicting 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
Random 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
Self-citation
Metadata
- 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 › Battery Modeling and Management
- 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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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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