A State-of-Health Estimation Method for Lithium Batteries Based on Fennec Fox Optimization Algorithm–Mixed Extreme Learning Machine

A reliable and accurate estimation of the state-of-health (SOH) of lithium batteries is critical to safely operating electric vehicles and other equipment. This paper proposes a state-of-health estimation method based on fennec fox optimization algorithm–mixed extreme learning machine (FFA-MELM). Fi...

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Vydáno v:	Batteries (Basel) Ročník 10; číslo 3; s. 87
Hlavní autoři:	Sun, Chongbin, Qin, Wenhu, Yun, Zhonghua
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 01.03.2024
Témata:	Accuracy Aging Algorithms Analysis Artificial neural networks Content analysis Datasets Deep learning Electric vehicles extreme learning machine Failure fennec fox optimization algorithm grey relational analysis Health Lithium Lithium batteries Lithium cells Machine learning Mathematical optimization Methods Neural networks Optimization Optimization algorithms Partial differential equations Reliability (Engineering) state-of-health Temperature China
ISSN:	2313-0105, 2313-0105
On-line přístup:	Získat plný text
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