Comparing Hybrid Approaches of Deep Learning for Remaining Useful Life Prognostic of Lithium-Ion Batteries

Comparing Hybrid Approaches of Deep Learning for Remaining Useful Life Prognostic of Lithium-Ion Batteries

Many published journals used hybrid deep learning methods to predict batteries’ remaining useful life by adopting different rationales to select and combine deep learning methods aiming to propose the most accurate prediction model possible. The main contribution of this article consists...

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Bibliographic Details
Main Authors: Anas Tiane, Chafik Okar, Mohamad Alzayed, Hicham Chaoui
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Lithium-ion battery
remaining useful life
deep neural network
machine learning
Online Access:https://ieeexplore.ieee.org/document/10510289/

Internet

https://ieeexplore.ieee.org/document/10510289/

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