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Parameter-Matching Algorithm and Optimization of Integrated Thermal Management System of Aircraft

机译:飞机综合热管理系统的参数匹配算法及优化

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摘要

The integrated thermal management system of aircraft is essential to maintain a suitable environment for the cabin crew and devices. The system is composed of the air-cycle refrigeration subsystem, the vapor-compression refrigeration subsystem, the liquid-cooling subsystem and the fuel-cycle subsystem, which are coupled with each other through heat exchangers. Due to the complex structure and large number of components in the system, it is necessary to design a corresponding parameter-matching algorithm for its special structure and to select the appropriate optimization design method. In this paper, the structure of an integrated thermal management system is analyzed in depth. A hierarchical matching algorithm of system parameters was designed and realized. Meanwhile, a sensitivity analysis of the system was performed, where key parameters were selected. Besides, a variety of optimization algorithms was used to optimize the design calculations. The results show that the particle swarm optimization and genetic algorithm could effectively find the global optimal solution when taking the fuel penalty as the objective function. Furthermore, the particle swarm optimization method took less time.
机译:飞机的集成热管理系统对于为机组人员和设备保持合适的环境至关重要。该系统由空气循环制冷子系统、蒸汽压缩制冷子系统、液冷子系统和燃料循环子系统组成,它们通过热交换器相互耦合。由于系统结构复杂,组件数量多,需要针对其特殊结构设计相应的参数匹配算法,并选择合适的优化设计方法。本文深入分析了一体化热管理系统的结构。设计并实现了系统参数的分层匹配算法。同时,对系统进行了灵敏度分析,选择了关键参数。此外,还利用多种优化算法对设计计算进行优化。结果表明,当以燃料损失为目标函数时,粒子群优化和遗传算法能够有效地找到全局最优解。此外,粒子群优化方法花费的时间更少。

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