Application of multi-modal temporal neural network based on enhanced sparrow optimization in lithium battery life prediction

This paper introduces the DeNet-Mamba-DC-SCSSA network, an advanced solution for predicting the Remaining Useful Life (RUL) of lithium-ion batteries, crucial for the safety and efficiency management of electric vehicles. Combining the robust Denoising Enhancement Network (DeNet), the Improved Sparro...

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Veröffentlicht in:	Scientific reports Jg. 14; H. 1; S. 27476 - 17
Hauptverfasser:	Liu, Zeyu, Du, Xiaofang, Shi, Yuhai
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 11.11.2024 Nature Publishing Group Nature Portfolio
Schlagworte:	639/4077 639/4077/4079/891 Algorithms Battery life degradation Denoising autoencoder Electric vehicles Health feature extraction Humanities and Social Sciences Lithium multidisciplinary Neural networks Science Science (multidisciplinary) Sparrow optimization algorithm Temporal neural network Sparrow optimization algorithm Temporal neural network Denoising autoencoder Health feature extraction Battery life degradation
ISSN:	2045-2322, 2045-2322
Online-Zugang:	Volltext
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