SoC estimation of lithium-ion batteries based on machine learning techniques: A filtered approach
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Decision trees, random forests, and gradient boosting have been used in SOC estimation with reasonable accuracy.
“Methods, including decision trees [39], random forests [40], and gradient boosting [41], have been used in SOC estimation with reasonable accuracy.”
From Review Paper for SOC Estimation Techniques: Challenges and Future Areas for Improvement (2024) · cites this paper as [41]
Cites
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 · see citing works
Zhu, Q., Xu, M., Liu, W., & Zheng, M. (2019) · Energy · doi:10.1016/j.energy.2019.115880 · Cited by 190 · see citing works
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Review Paper for SOC Estimation Techniques: Challenges and Future Areas for Improvement
Rehman, A. (2024) · Power System Technology · doi:10.52783/pst.906 · Cited by 12 · see citing works
- Authors
- Korkmaz, M.
- Affiliations
- Aksaray University (TR)
- Corresponding author
- Korkmaz, Mehmet
- ORCID
- Korkmaz, Mehmet
- Venue
- Journal of Energy Storage
- Publisher
- Elsevier BV
- Published
- 2023-11
- Volume
- 72
- Pages
- 108268
- ISSN
- 2352-152X (ISSN-L)
- OpenAlex
- W4383506408
- Cited by
- 92
- References
- 2
- Citations by year
- 2026: 23 · 2025: 43 · 2024: 22 · 2023: 4
- FWCI
- 6.40
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Journal of Energy Storage (publishedVersion)
- 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
- state of charge estimation, lithium-ion batteries, machine learning, outlier removal, outlier filtering, battery management systems, electric vehicles, bagging, extra trees, loess, interquartile range
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