A hybrid data-driven method for voltage state prediction and fault warning of Li-ion batteries
As the extensive application of electrochemical energy storage (EES), Li-ion battery fault is a key factor reference to the reliable operation and system security, influencing by the environment temperature and battery voltage. To address distinct challenges in lithium-ion battery fault prediction,...
Tallennettuna:
| Päätekijät: | , , , |
|---|---|
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
Elsevier
2024-12-01
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| Sarja: | Case Studies in Thermal Engineering |
| Aiheet: | |
| Linkit: | http://www.sciencedirect.com/science/article/pii/S2214157X24014515 |
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