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dc.contributor.author |
Belfetni, Isra/ Moussa, Sakina /Encadré par Djeddi, Abdelghani |
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dc.date.accessioned |
2025-07-23T02:44:19Z |
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dc.date.available |
2025-07-23T02:44:19Z |
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dc.date.issued |
2025-06 |
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dc.identifier.uri |
http//localhost:8080/jspui/handle/123456789/12951 |
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dc.description.abstract |
This work presents a comprehensive study on electric batteries, with a particular focus on Lithium-Ion batteries due to their high efficiency. Various modeling methods (electrical, electrochemical, and artificial intelligence-based) have been discussed, along with techniques for estimating the State of Charge (SOC) and regulating temperature, given their direct impact on the battery’s performance and lifespan. A state feedback control method was employed, offering greater accuracy and stability, especially in the presence of operational disturbances. The study highlights the importance of an integrated Battery Management System (BMS) to ensure safe and sustainable energy usage in modern applications. |
en_US |
dc.language.iso |
fr |
en_US |
dc.publisher |
Université Echahid Cheikh Larbi Tebessi - Tebessaa |
en_US |
dc.subject |
Batterie, Li-ion, EDC, SDG, température. |
en_US |
dc.title |
Commande robuste des systèmes non- linéaires pour la gestion de l’état de charge (EDC) et de la température des batteries électriques |
en_US |
dc.type |
Thesis |
en_US |
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