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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2404.04358 |
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| _version_ | 1866914966205890560 |
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| author | Lu, Zehui Tu, Hao Fang, Huazhen Wang, Yebin Mou, Shaoshuai |
| author_facet | Lu, Zehui Tu, Hao Fang, Huazhen Wang, Yebin Mou, Shaoshuai |
| contents | This paper presents an integrated control strategy for optimal fast charging and active thermal management of Lithium-ion batteries in extreme ambient temperatures, striking a balance between charging speed and battery health. A control-oriented thermal-NDC (nonlinear double-capacitor) battery model is proposed to describe the electrical and thermal dynamics, incorporating the effects of both an active thermal source and ambient temperature. A state-feedback model predictive control algorithm is then developed for optimal fast charging and active thermal management. Numerical experiments validate the algorithm under extreme temperatures, showing that the proposed algorithm can energy-efficiently adjust the battery temperature, thereby balancing charging speed and battery health. Additionally, an output-feedback model predictive control algorithm with an extended Kalman filter is proposed for battery charging when states are partially measurable. Numerical experiments validate the effectiveness under extreme temperatures. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_04358 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Integrated Optimal Fast Charging and Active Thermal Management of Lithium-Ion Batteries in Extreme Ambient Temperatures Lu, Zehui Tu, Hao Fang, Huazhen Wang, Yebin Mou, Shaoshuai Systems and Control Optimization and Control This paper presents an integrated control strategy for optimal fast charging and active thermal management of Lithium-ion batteries in extreme ambient temperatures, striking a balance between charging speed and battery health. A control-oriented thermal-NDC (nonlinear double-capacitor) battery model is proposed to describe the electrical and thermal dynamics, incorporating the effects of both an active thermal source and ambient temperature. A state-feedback model predictive control algorithm is then developed for optimal fast charging and active thermal management. Numerical experiments validate the algorithm under extreme temperatures, showing that the proposed algorithm can energy-efficiently adjust the battery temperature, thereby balancing charging speed and battery health. Additionally, an output-feedback model predictive control algorithm with an extended Kalman filter is proposed for battery charging when states are partially measurable. Numerical experiments validate the effectiveness under extreme temperatures. |
| title | Integrated Optimal Fast Charging and Active Thermal Management of Lithium-Ion Batteries in Extreme Ambient Temperatures |
| topic | Systems and Control Optimization and Control |
| url | https://arxiv.org/abs/2404.04358 |