Remaining Useful Life Prediction of Lithium-Ion Batteries by Using a Denoising Transformer-Based Neural Network
In this study, we introduce a novel denoising transformer-based neural network (DTNN) model for predicting the remaining useful life (RUL) of lithium-ion batteries. The proposed DTNN model significantly outperforms traditional machine learning models and other deep learning architectures in terms of...
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| Principais autores: | , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
MDPI AG
2023-08-01
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| Series: | Energies |
| Assuntos: | |
| Acceso en liña: | https://www.mdpi.com/1996-1073/16/17/6328 |
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