Remaining useful life estimation – A review on the statistical data driven approaches

Si, Xiao-Sheng; Wang, Wenbin; Hu, Chang-Hua; Zhou, Dong-Hua

doi:10.1016/j.ejor.2010.11.018

Cited by 2,162Reliability and Maintenance OptimizationMachine Fault Diagnosis TechniquesTechnical Engine Diagnostics and Monitoring

Remaining useful life estimation – A review on the statistical data driven approaches

Si, Xiao-Sheng, Wang, Wenbin, Hu, Chang-Hua, Zhou, Dong-Hua·2011·European Journal of Operational Research

DOI 10.1016/j.ejor.2010.11.018

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Work in battery ML has focused on predicting battery state, degradation, and remaining lifetime using supervised learning, fuzzy logic, and clustering.
“Work in this area has focused on predicting battery state, degradation, and remaining lifetime using supervised learning techniques, fuzzy logic, and clustering [42,104,218,358,414,725,735,819,854].”
From Tackling climate change with machine learning (2023) · cites this paper as [735]
Many academic battery models are based on laboratory data that do not account for real-world factors such as environmental conditions.
“However, many models developed in academia are based on laboratory data that do not account for real-world factors such as environmental conditions [735,819,854].”
From Tackling climate change with machine learning (2023) · cites this paper as [735]

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Authors: Si, X.-S., Wang, W., Hu, C.-H., & Zhou, D.-H.
Affiliations: City University of Hong Kong (HK)
Tsinghua University (CN)
Corresponding author: Wang, Wenbin
Zhou, Dong-Hua
ORCID: Wang, Wenbin
Venue: European Journal of Operational Research
Publisher: Elsevier BV
Published: 2011-08
Volume: 213
Issue: 1
Pages: 1-14
ISSN: 0377-2217 (ISSN-L)
DOI: 10.1016/j.ejor.2010.11.018
OpenAlex: W2055873761
Cited by: 2,162
References: 190
Citations by year: 2026: 181 · 2025: 140 · 2024: 143 · 2023: 154 · 2022: 178 · 2021: 226 · 2020: 204 · 2019: 200 · 2018: 147 · 2017: 172 · 2016: 106 · 2015: 97 · 2014: 99 · 2013: 63 · 2012: 41
FWCI: 122.11
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: European Journal of Operational Research (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
Topics: Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Reliability and Maintenance Optimization
Physical Sciences › Engineering › Control and Systems Engineering › Machine Fault Diagnosis Techniques
Physical Sciences › Engineering › Automotive Engineering › Technical Engine Diagnostics and Monitoring
Keywords: remaining useful life prediction, prognostics and health management, condition-based maintenance, condition monitoring, health monitoring

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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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Remaining useful life estimation – A review on the statistical data driven approaches

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