Interpretable Deep Learning Using Temporal Transformers for Battery Degradation Prediction

Interpretable Deep Learning Using Temporal Transformers for Battery Degradation Prediction

Accurate modelling of lithium-ion battery degradation is a complex problem, dependent on multiple internal mechanisms that can be affected by a multitude of external conditions. In this study, a transformer-based approach, capable of leveraging historical conditions and known-future inputs is introd...

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Bibliographic Details
Main Authors: James Sadler, Rizwaan Mohammed, Kotub Uddin
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Batteries
Subjects:
lithium-ion batteries
transformers
interpretable
deep learning
Online Access:https://www.mdpi.com/2313-0105/11/7/241
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