Aerodynamic Shape Optimization of the Pantograph Fairing of a High-Speed Train

In order to improve the aerodynamic performance of the pantograph fairing of a high-speed train, an aerodynamic shape optimization design approach of the pantograph fairing was proposed based on a multi-objective genetic algorithm and the theory of computational fluid dynamics (CFD). The aerodynamic drag force and the acoustic power level of the fairing were set to be the optimization objectives. A three-dimensional (3D) parametric model of the pantograph fairing was established and 4 optimization design variables were extracted. The script files of the software of CATIA and STAR-CCM+ were integrated into the optimization design software ISIGHT, and then the automatic deformation of the pantograph fairing and the automatic calculation of the train aerodynamics could be obtained. The design variables were automatically updated by non-dominated sorting genetic algorithm-II (NSGA-II) to achieve the automatic optimization of the pantograph fairing. After optimization, the correlations between the optimization objectives and the design variables were analyzed, and the most important design variables which influenced the optimization objectives were obtained. The optimization results show that the correlations between the optimization design variables and the two optimization objectives are the same, and only the values of the correlation coefficients are different. Compared with the prototype, the aerodynamic drag force of the middle coach with the optimized fairing has been reduced up to 4.21%, and the maximum acoustic power level of the optimized fairing has been reduced up to 7.38%.