Advancing Lithium-Ion Battery Health Prognostics With Deep Learning: A Review and Case Study

Advancing Lithium-Ion Battery Health Prognostics With Deep Learning: A Review and Case Study

<p dir="ltr">Lithium-ion battery prognostics and health management (BPHM) systems are vital to the longevity, economy, and environmental friendliness of electric vehicles and energy storage systems. Recent advancements in deep learning (DL) techniques have shown promising results in...

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Bibliographic Details
Main Author: Mohamed Massaoudi (16888710) (author)
Other Authors: Haitham Abu-Rub (16855500) (author), Ali Ghrayeb (16864266) (author)
Published: 2024
Subjects:
Engineering
Electrical engineering
Information and computing sciences
Artificial intelligence
Deep learning (DL)
health and life-cycle analysis
lithium-ion battery (LIB) management system
prognostics and health management (PHM)
remaining useful life (RUL) prediction
state of charge (SOC) estimation
Batteries
Data models
Estimation
Mathematical models
Aging
Integrated circuit modeling
State of charge
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