State of health estimation and remaining useful life prediction for lithium-ion batteries using FBELNN and RCMNN

This study proposes the novel method of lithium-ion battery state of health (SoH) estimation and remaining useful life (RUL) prediction to ensure the safety and reliability of the energy storage system. A fuzzy brain emotional learning neural network (FBELNN) is employed to estimate SoH and a recurr...

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Veröffentlicht in:	Journal of intelligent & fuzzy systems 2021-01, Vol.40 (6), p.10919-10933
Hauptverfasser:	Lin, Qiongbin, Xu, Zhifan, Lin, Chih-Min
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Discharge Discrete Wavelet Transform Energy storage Feature extraction Fuzzy logic Life prediction Lithium Lithium-ion batteries Neural networks Principal components analysis Rechargeable batteries Useful life Wavelet transforms
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