Improved SOH Prediction of Lithium-Ion Batteries Based on Multi-Dimensional Feature Analysis and Transformer Framework

Improved SOH Prediction of Lithium-Ion Batteries Based on Multi-Dimensional Feature Analysis and Transformer Framework

Data-driven state-of-health (SOH) prediction is increasingly critical for the effective management of lithium-ion batteries; however, challenges remain in practical applications. Traditional methods that rely on a single health indicator often fail to capture the complexity and multi-dimensional nat...

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Bibliographic Details
Main Authors: Tianfeng Long, Pengcheng Zhang, Xiaoqi Liu, Huaqing Shang, Meiling Yue, Xuesong Shen, Jianwen Meng
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Open Journal of Vehicular Technology
Subjects:
Feature extraction
lithium-ion battery
SOH prediction
Transformer
Online Access:https://ieeexplore.ieee.org/document/11015565/
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https://ieeexplore.ieee.org/document/11015565/

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