State of health estimation for lithium-ion battery based on the coupling-loop nonlinear autoregressive with exogenous inputs neural network

•Coupling loop NARX neural network has better time series prediction accuracy.•Principal component feature extraction eliminates redundant variables effectively.•BR algorithm speeds up the convergence rate of neural network weights. In order to solve the problem of low accuracy of traditional artifi...

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Veröffentlicht in:	Electrochimica acta Jg. 393; S. 139047
Hauptverfasser:	Cui, Zhiquan, Wang, Chunhui, Gao, Xuhong, Tian, Shushan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Elsevier Ltd 10.10.2021 Elsevier BV
Schlagworte:	Algorithms Artificial neural networks Back propagation networks Bayesian analysis Bayesian regularization algorithm Coupling Coupling-loop Error reduction Feature extraction Functional approximation Independent variables Indicators Lithium Lithium batteries Lithium-ion batteries Lithium-ion battery Machine learning Neural networks Rechargeable batteries Regularization State of health Lithium-ion battery Coupling-loop Functional approximation State of health Bayesian regularization algorithm
ISSN:	0013-4686, 1873-3859
Online-Zugang:	Volltext
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