Indirect Prediction for Lithium-Ion Batteries RUL Using Multi-Objective Arithmetic Optimization Algorithm-Based Deep Extreme Learning Machine

Lithium-ion batteries (LIBs) experience aging degradation during long-term operation. Accurate prediction of the remaining useful life (RUL) in advance is crucial to ensure continuous and reliable energy supply of the battery management system (BMS). Aiming at the problem of limited robustness of de...

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Vydané v:	IEEE access Ročník 11; s. 110400 - 110416
Hlavní autori:	Li, Linna, Huang, Zhong, Ding, Guorong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Aging Algorithms Arithmetic Artificial neural networks Batteries Correlation coefficients health indexes Indexes Integrated circuit modeling Lithium-ion batteries Lithium-ion batteries SOH estimation Machine learning Mathematical models MOAOA-DELM Multiple objective analysis Optimization Optimization algorithms Optimization methods Parameters Prediction algorithms Predictive models Rechargeable batteries Robustness RUL prediction Stability
ISSN:	2169-3536, 2169-3536
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