Detailed Architectural Design of a Multi-Head Self-Attention Model for Lithium-Ion Battery Capacity Forecasting
As the adoption of lithium-ion batteries increases, concerns over safety incidents and replacement costs have become increasingly pressing. Accurate battery state prediction is thereby vital for reducing costs and ensuring safety. This paper introduces a novel system based on a transformer encoder a...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10916651/ |
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