The invention discloses a BMS (Battery Management System) balanced linkage refrigeration method based on adaptive model predictive control, which can process temperature control and strong nonlinearity and time-varying characteristics of MOS (Metal Oxide Semiconductor) tube heat production through online adaptive model predictive control based on unscented Kalman filtering, thereby obtaining a better control effect. Comprehensive energy loss, heat dissipation time, real-time temperature and maximum equalization voltage are incorporated into a cost function, and power consumption of a passive equalization circuit is combined with a semiconductor refrigeration chip, so that accurate temperature control of a high-power MOS tube is realized, the temperature intensity is obviously reduced, the overall service life of a system is prolonged, the safety of the system is guaranteed, the risk of thermal runaway is reduced, and the efficiency of the system is improved. Further, the cost of the new energy vehicle management system is reduced, the safety performance of the system is greatly improved, the optimal control quantity, the optimal reference equalizing current Icell and the reference input current Imos of the second semiconductor refrigeration chip covering the MOS tube can be quickly solved through a model prediction control algorithm by converting a cost function into a convex optimization problem, and the optimal control quantity, the optimal reference equalizing current Icell and the reference input current Imos of the second semiconductor refrigeration chip covering the MOS tube can be quickly solved. Therefore, the method can be applied to online real-time control through PI control.

    本发明公开了一种基于自适应模型预测控制的BMS均衡联动制冷方法,通过基于无迹卡尔曼滤波的在线自适应模型预测控制可以处理温度控制和MOS管产热的强非线性和时变特性,从而取得更好的控制效果,通过将综合能量损失、散热时常、实时温度、最大均衡电压纳入成本函数,通过被动均衡电路的耗电与半导体制冷芯片相结合,实现大功率MOS管的精准控温,温度强度显著减小,延长系统整体寿命、保障系统安全,减少热失控风险并提高系统效率,进而降低新能源车辆管理系统的成本并大幅度提高系统安全性能,通过将成本函数转化为凸优化问题,通过模型预测控制算法可以快速地求解得到最优控制量及最优参考均衡电流Icell和覆盖于MOS管上的第二半导体制冷芯片的参考输入电流Imos,进而可以通过PI控制应用于在线的实时控制。


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    Titel :

    BMS balanced linkage refrigeration method based on adaptive model predictive control


    Weitere Titelangaben:

    基于自适应模型预测控制的BMS均衡联动制冷方法


    Beteiligte:
    WANG LI (Autor:in) / TAN CHANGPENG (Autor:in) / WU JI (Autor:in) / WU MUYAO (Autor:in) / LUO GANG (Autor:in)

    Erscheinungsdatum :

    2024-04-26


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    F25B Kältemaschinen, Kälteanlagen oder Kälteverfahren , REFRIGERATION MACHINES, PLANTS, OR SYSTEMS / B60L PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES , Antrieb von elektrisch angetriebenen Fahrzeugen




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