A review of state of health and remaining useful life estimation methods for lithium-ion battery in electric vehicles: challenges and recommendations
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In reviews where both SOH and RUL are surveyed, data-driven approaches are still not covered in depth.
“In the reviews where both are surveyed, e.g.[7,21], data-driven approaches are still not covered in depth.”
From Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review (2019) · cites this paper as [21]
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“[7,21], data-driven approaches are still not covered in depth.”
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- Authors
- Lipu, M. S. H., Hannan, M. A., Hussain, A., Hoque, M. M., Ker, P. J., Saad, M. H. M., & Ayob, A.
- Affiliations
- University of Asia Pacific (BD)
- Universiti Tenaga Nasional (MY)
- National University of Malaysia (MY)
- University of Chittagong (BD)
- Corresponding author
- Hannan, M.A.
- Venue
- Journal of Cleaner Production
- Publisher
- Elsevier BV
- Published
- 2018-12
- Volume
- 205
- Pages
- 115-133
- ISSN
- 0959-6526 (ISSN-L)
- OpenAlex
- W2890169947
- Cited by
- 755
- References
- 114
- Citations by year
- 2026: 72 · 2025: 94 · 2024: 110 · 2023: 124 · 2022: 106 · 2021: 115 · 2020: 83 · 2019: 51
- FWCI
- 31.74
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Cleaner Production (publishedVersion)
- Funders
- Universiti Kebangsaan Malaysia (DIP-2015-012)
- Universiti Tenaga Nasional (RJO10289176/D/1/2018/J40 to J50)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Keywords
- lithium-ion batteries, electric vehicles, state of health estimation, remaining useful life prediction, battery degradation, battery health monitoring
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