Remaining life prediction of lithium-ion batteries based on vmd decomposition and cascaded bilstm-transformer network
Abstract Accurate prediction of battery capacity, a key indicator of State of Health (SOH), is of significant engineering value for ensuring system safety, optimizing maintenance strategies, and extending equipment lifespan. However, the battery degradation process exhibits complex characteristics s...
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| 主要な著者: | , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Springer
2026-01-01
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| シリーズ: | Journal of King Saud University: Computer and Information Sciences |
| 主題: | |
| オンライン･アクセス: | https://doi.org/10.1007/s44443-025-00349-z |
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