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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| 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
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| Series: | IEEE Open Journal of Vehicular Technology |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11015565/ |
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