Lithium-ion battery RUL prediction based on optimized VMD-SSA-PatchTST algorithm
Abstract Accurate prediction of lithium-ion batteries’ remaining useful life (RUL) is critical for system reliability and safety. This study proposes a novel forecasting framework that fuses modal decomposition with the advanced PatchTST model. Initially, the Spearman correlation coefficient is empl...
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| Main Authors: | Pei Tang, Zetao Qiu, Zhongran Yao, Jiahao Pan, Dashuai Cheng, Xiaoyong Gu, Changcheng Sun |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-11934-7 |
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