State-of-Health Prediction of Lithium-Ion Batteries Using Exponential Smoothing Transformer With Seasonal and Growth Embedding

State-of-Health Prediction of Lithium-Ion Batteries Using Exponential Smoothing Transformer With Seasonal and Growth Embedding

In the world of modern energy, Lithium-Ion batteries reign supreme, offering rechargeability, sustainability, and long-term energy storage. However, their lifespan is not infinite, calling for accurate prediction of remaining life under various conditions. Deep learning shines in this domain, with t...

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Bibliographic Details
Main Authors: Muhammad Rifqi Fauzi, Novanto Yudistira, Wayan Firdaus Mahmudy
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Time series forecasting
lithium-ion battery
seasonal embedding
growth embedding
transformer
state-of-health (SoH)
Online Access:https://ieeexplore.ieee.org/document/10412053/

Internet

https://ieeexplore.ieee.org/document/10412053/

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