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Remaining useful life prediction of Lithium-ion batteries using spatio-temporal multimodal attention networks

Autor: Suh, Sungho, Mittal, Dhruv Aditya, Bello, Hymalai, Zhou, Bo, Jha, Mayank Shekhar, Lukowicz, Paul

Lithium-ion batteries are widely used in various applications, including electric vehicles and renewable energy storage. The prediction of the remaining useful life (RUL) of batteries is crucial for ensuring reliable and efficient operation, as well

Externí odkaz: http://arxiv.org/abs/2310.18924

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Two-stage Early Prediction Framework of Remaining Useful Life for Lithium-ion Batteries

Autor: Mittal, Dhruv, Bello, Hymalai, Zhou, Bo, Jha, Mayank Shekhar, Suh, Sungho, Lukowicz, Paul

Early prediction of remaining useful life (RUL) is crucial for effective battery management across various industries, ranging from household appliances to large-scale applications. Accurate RUL prediction improves the reliability and maintainability

Externí odkaz: http://arxiv.org/abs/2308.03664

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Akademický článek

Degradation Tolerant Optimal Control Design for Stochastic Linear Systems

Autor: Kanso Soha, Jha Mayank Shekhar, Theilliol Didier

Publikováno v: International Journal of Applied Mathematics and Computer Science, Vol 34, Iss 1, Pp 5-14 (2024)

Safety-critical and mission-critical systems are often sensitive to functional degradation at the system or component level. Such degradation dynamics are often dependent on system usage (or control input), and may lead to significant losses and a po

Externí odkaz: https://doaj.org/article/0839b8fdf98748e8bda2dc98c8316119