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作 者:董方旭 凡丽梅 段剑 王勇 孙岩 王飞[3] DONG Fang-xu;FAN Li-mei;DUAN Jian;WANG Yong;SUN Yan;WANG Fei(Shandong Nonmetallic Materials Institute,Jinan 250031,China;32103 Troops of the Chinese People’s Liberation Army,Weifang 261000,China;School of Mechatronics Engineering,Harbin Institute of Technology,Harbin 150001,China)
机构地区:[1]山东非金属材料研究所,山东济南250031 [2]中国人民解放军32103部队,山东潍坊261000 [3]哈尔滨工业大学机电工程学院,黑龙江哈尔滨150001
出 处:《节能技术》2025年第1期63-70,共8页Energy Conservation Technology
基 金:济南市“新高校20条”资助项目(2021GXRC054)。
摘 要:针对高超声速飞机的热管理系统,建立了一套综合热管理模型及其热沉调控策略,通过辨识控制和温度预测技术实现热沉利用率最大化,解决先进高速飞机散热困难问题。首先建立综合热管理模型,该模型考虑实际部件间的复杂耦合效应,可精确模拟高超声速飞行工况。其次提出基于能量守恒和温度反馈的燃油流量控制策略,分别利用径向基神经网络辨识飞机热载荷、利用灰色预测算法预测各节点温度,用于计算控制所需的冷热量差值。最后联合仿真,验证模型及算法的正确性和可靠性。研究表明,提出的辨识预测控制策略有效克服了热系统的惯性和时延问题,实现燃油热沉的精细化流量控制,提高了燃油热沉利用率。Aiming at the thermal management system of hypersonic aircraft,an integrated thermal management model and its heat sink control strategy are established.The identification control and temperature prediction technology are used to maximize the utilization rate of heat sink and solve the problem of heat dissipation of advanced hypersonic aircraft.Firstly,an integrated thermal management model is established,which considers the complex coupling effect between actual components and can accurately simulate hypersonic flight conditions.Secondly,a fuel flow control strategy based on energy conservation and temperature feedback is proposed.The radial basis neural network is used to identify the thermal load of the aircraft,and the gray prediction algorithm is used to predict the temperature of each node,which is used to calculate the difference between cold and heat required for control.Finally,the co-simulation is carried out to verify the correctness and reliability of the model and algorithm.The research shows that the proposed identification predictive control strategy effectively overcomes the inertia and time delay problems of the thermal system.The refined flow control of fuel heat sink is realized,and the fuel heat sink utilization is improved.
关 键 词:辨识控制 热管理系统 高超声速 燃油热沉 径向基神经网络
分 类 号:V245.3[航空宇航科学与技术—飞行器设计]
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