Physics-Informed Fractional-Order Recurrent Neural Network for Fast Battery Degradation with Vehicle Charging Snippets

To handle and manage battery degradation in electric vehicles (EVs), various capacity estimation methods have been proposed and can mainly be divided into traditional modeling methods and data-driven methods. For realistic conditions, data-driven methods take the advantage of simple application. How...

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Vydáno v:	Fractal and fractional Ročník 9; číslo 2; s. 91
Hlavní autoři:	Wang, Yanan, Wei, Min, Dai, Feng, Zou, Daijiang, Lu, Chen, Han, Xuebing, Chen, Yangquan, Ji, Changwei
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 01.02.2025
Témata:	Accuracy Algorithms Back propagation Back propagation networks backpropagation Batteries battery degradation Big Data Calculus Charging Datasets Degradation Electric vehicles Forecasts and trends fractional-order gradient incremental capacity analysis Information management Machine learning Methods Neural networks Physics physics-informed machine learning Recurrent neural networks Wavelet transforms China
ISSN:	2504-3110, 2504-3110
On-line přístup:	Získat plný text
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