A co-estimation framework of state of health and remaining useful life for lithium-ion batteries using the semi-supervised learning algorithm
To ensure the safe operation of lithium-ion batteries, it is crucial to accurately predict their state of health (SOH) and remaining useful life (RUL). Addressing the issue of high costs and time consumption due to the reliance on large amounts of labeled data in existing models, this paper proposes...
| Main Authors: | , , , , |
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| Formato: | Artigo |
| Idioma: | English |
| Publicado: |
Elsevier
2025-01-01
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| Series: | Energy and AI |
| Subjects: | |
| Acceso en liña: | http://www.sciencedirect.com/science/article/pii/S2666546824001241 |