Comfortable and healthy aircraft cabin environment is required as more and more people choose to travel by air. The cabin environment is optimized by searching the optimal control parameters such as air supply velocity, angle and temperature. The optimal solutions are obtained by combining a multi-objective particle swarm optimization (MOPSO) with the simulation of computational fluid dynamics (CFD). It is found that different combinations of optimal air supply parameters can build an optimal cabin environment and the locations of the obtained optimal solutions are isolated in their value spaces. To achieve a stable engineering control operation, the determination of a stable range of optimal air supply parameters is required. Therefore, a method by using cluster analysis is developed to obtain stable ranges of optimal air supply parameters. Results show that the proposed method can obtain the ranges of optimal air supply parameters successfully.Keywords cabin environment, multi-objective optimization, particle swarm optimization, cluster analysis, stable range, optimal air supply parameters Article History

Pilot’s thermal comfort and performance are directly affected by air flow field and temperature field in cockpit. A three-dimensional cockpit model of a certain civil aircraft is established, and the distribution of air velocity and temperature is obtained with the method of computational fluid dynamics (CFD). Aiming at the problems of high local air speed and uneven temperature distribution in the cockpit, two new supply air grilles are proposed. The results show that one of the grilles can obviously optimize air flow field and temperature in the cockpit and improve the thermal comfort of the pilots.