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A review on prognostics approaches for remaining useful life of lithium-ion battery
Open accessAbstract
Lithium-ion (Li-ion) battery is a core component for various industrial systems, including satellite, spacecraft and electric vehicle, etc. The mechanism of performance degradation and remaining useful life (RUL) estimation correlate closely to the operating state and reliability of the aforementioned systems. Furthermore, RUL prediction of Li-ion battery is crucial for the operation scheduling, spare parts management and maintenance decision for such kinds of systems. In recent years, performance degradation prognostics and RUL estimation approaches have become a focus of the research concerning with Li-ion battery. This paper summarizes the approaches used in Li-ion battery RUL estimation. Three categories are classified accordingly, i.e. model-based approach, data-based approach and hybrid approach. The key issues and future trends for battery RUL estimation are also discussed.
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References 36 · Cited by 64
Research works printed but not linked: 2
- Liu D, 2014, Instrumentation, 1, 59
- Wu Z Y, 2012, J. Seu Sci. Technol., 27, 65
Metadata
- Authors
- Su, C., & Chen, H. J.
- Affiliations
- Southeast University (CN)
- Corresponding author
- Su, C
- Venue
- IOP Conference Series: Earth and Environmental Science
- Publisher
- IOP Publishing
- Published
- 2017-11
- Volume
- 93
- Pages
- 012040
- ISSN
- 1755-1315 (ISSN-L)
- 1755-1307
- OpenAlex
- W2767278549
- Cited by
- 64
- References
- 36
- Citations by year
- 2026: 2 · 2025: 8 · 2024: 10 · 2023: 9 · 2022: 9 · 2021: 11 · 2020: 5 · 2019: 7 · 2018: 3
- FWCI
- 4.56
- Type
- conference paper
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- IOP Conference Series Earth and Environmental Science (publishedVersion, cc-by)
- Funders
- National Natural Science Foundation of China (71671035)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Battery Modeling and Management
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Reliability and Maintenance Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
- Keywords
- lithium-ion batteries, remaining useful life prediction, battery prognostics, performance degradation, model-based prognostics, data-driven prognostics, electric vehicles, maintenance decision-making, spare parts management
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