Parameter-Matching Algorithm and Optimization of Integrated Thermal Management System of Aircraft
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 subsyst...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Aerospace |
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| Online Access: | https://www.mdpi.com/2226-4310/9/2/104 |
| _version_ | 1797483889344643072 |
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| author | Ri Wang Sujun Dong Hongsheng Jiang Peiru Li Hainan Zhang |
| author_facet | Ri Wang Sujun Dong Hongsheng Jiang Peiru Li Hainan Zhang |
| author_sort | Ri Wang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T22:54:33Z |
| format | Article |
| id | doaj.art-c34be5380ab244528106c55f13b00b02 |
| institution | Directory Open Access Journal |
| issn | 2226-4310 |
| language | English |
| last_indexed | 2024-03-09T22:54:33Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Aerospace |
| spelling | doaj.art-c34be5380ab244528106c55f13b00b022023-11-23T18:14:46ZengMDPI AGAerospace2226-43102022-02-019210410.3390/aerospace9020104Parameter-Matching Algorithm and Optimization of Integrated Thermal Management System of AircraftRi Wang0Sujun Dong1Hongsheng Jiang2Peiru Li3Hainan Zhang4School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, ChinaSchool of Aeronautic Science and Engineering, Beihang University, Beijing 100191, ChinaSchool of Aeronautic Science and Engineering, Beihang University, Beijing 100191, ChinaTechnical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, ChinaTechnical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, ChinaThe 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.https://www.mdpi.com/2226-4310/9/2/104aircraftthermal management systemparameter matchingsensitivity analysisoptimization |
| spellingShingle | Ri Wang Sujun Dong Hongsheng Jiang Peiru Li Hainan Zhang Parameter-Matching Algorithm and Optimization of Integrated Thermal Management System of Aircraft Aerospace aircraft thermal management system parameter matching sensitivity analysis optimization |
| title | Parameter-Matching Algorithm and Optimization of Integrated Thermal Management System of Aircraft |
| title_full | Parameter-Matching Algorithm and Optimization of Integrated Thermal Management System of Aircraft |
| title_fullStr | Parameter-Matching Algorithm and Optimization of Integrated Thermal Management System of Aircraft |
| title_full_unstemmed | Parameter-Matching Algorithm and Optimization of Integrated Thermal Management System of Aircraft |
| title_short | Parameter-Matching Algorithm and Optimization of Integrated Thermal Management System of Aircraft |
| title_sort | parameter matching algorithm and optimization of integrated thermal management system of aircraft |
| topic | aircraft thermal management system parameter matching sensitivity analysis optimization |
| url | https://www.mdpi.com/2226-4310/9/2/104 |
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