State of Health Estimation for Lithium-Ion Batteries Using Enhanced Whale Optimization Algorithm for Feature Selection and Support Vector Regression Model

Evaluating the state of health (SOH) of lithium-ion batteries (LIBs) is essential for their safe deployment and the advancement of electric vehicles (EVs). Existing machine learning methods face challenges in the automation and effectiveness of feature extraction, necessitating improved computationa...

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Veröffentlicht in:	Processes Jg. 13; H. 1; S. 158
Hauptverfasser:	Wang, Rui, Xu, Xikang, Zhou, Qi, Zhang, Jingtao, Wang, Jing, Ye, Jilei, Wu, Yuping
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.01.2025
Schlagworte:	Accuracy Aging Algorithms Automation Batteries Cetacea Datasets Electric vehicles Feature extraction Feature selection Gaussian process Health Lithium Lithium-ion batteries Machine learning Mathematical optimization Methods Neural networks Noise threshold Optimization Optimization algorithms Parameter identification Random noise Regression models Root-mean-square errors Support vector machines Technology application Temperature
ISSN:	2227-9717, 2227-9717
Online-Zugang:	Volltext
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