Data-driven modeling of lithium-ion battery degradation using XGBoost with extended Kalman filter-based internal resistance correction
Accurate prediction of battery degradation is essential for the reliability and cost-effectiveness of lithium-ion batteries in energy storage. Previous degradation prediction methods such as model-based methods provide interpretability but rely on simplifications, whereas data-driven approaches capt...
Salvato in:
| Autori principali: | , , , |
|---|---|
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Elsevier
2025-12-01
|
| Serie: | Results in Engineering |
| Soggetti: | |
| Accesso online: | http://www.sciencedirect.com/science/article/pii/S2590123025041465 |
| Tags: |
Nessun Tag, puoi essere il primo ad aggiungerne!!
|