Remaining Useful Life Prediction of Lithium-Ion Batteries Using Neural Networks with Adaptive Bayesian Learning

With smart electronic devices delving deeper into our everyday lives, predictive maintenance solutions are gaining more traction in the electronic manufacturing industry. It is imperative for the manufacturers to identify potential failures and predict the system/device’s remaining useful life (RUL)...

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Hlavní autoři:	Karkulali Pugalenthi, Hyunseok Park, Shaista Hussain, Nagarajan Raghavan
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2022-05-01
Edice:	Sensors
Témata:	lithium-ion batteries particle filters neural networks remaining useful life prognostics
On-line přístup:	https://www.mdpi.com/1424-8220/22/10/3803
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