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Predictive Fast Charging of Lithium-ion Battery with Electro-Thermal Constraints

  • Beijing Institute of Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

Lithium-ion batteries (LIBs) are widely used in electric vehicles (EVs) attributed to their advantages of high energy density and long cycle life. In this vision, fast charging of the LIB system has been a crucial technology to promote the large-scale penetration of EVs in the existing automotive market. Motivated by this, a thermal-constrained fast charging method is proposed based on the model predictive control (MPC) concept in this paper. A coupled electro-Thermal model is established, based on which two model-based observers are devised to estimate the state of charge (SOC) and internal temperature of LIB. On this premise, an MPC-based controller is exploited to trade-off smartly the charging fastness and the physical constraints. Comparative results show that the proposed method can optimize the charging towards high speed while keep the terminal voltage and battery internal temperature both within the safety region, which forms an obvious superiority over the traditionally-used constant-current-constant-voltage (CC-CV) protocol.

源语言英语
主期刊名Proceedings - 2020 IEEE 18th International Conference on Industrial Informatics, INDIN 2020
出版商Institute of Electrical and Electronics Engineers Inc.
页615-620
页数6
ISBN(电子版)9781728149646
DOI
出版状态已出版 - 20 7月 2020
活动18th IEEE International Conference on Industrial Informatics, INDIN 2020 - Virtual, Warwick, 英国
期限: 21 7月 2020 → 23 7月 2020

丛书

姓名IEEE International Conference on Industrial Informatics (INDIN)
卷2020-July
ISSN(印刷版)1935-4576

会议

会议18th IEEE International Conference on Industrial Informatics, INDIN 2020
国家/地区英国
市Virtual, Warwick
时期21/07/20 → 23/07/20

联合国可持续发展目标

此成果有助于实现下列可持续发展目标:

  1. 可持续发展目标 7 - 经济适用的清洁能源
    可持续发展目标 7 经济适用的清洁能源

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