Open Access

ARTICLE

Effect of Streamline Length on Aerodynamic Performance of 600 km/h Maglev Trains

Yan Li¹, Bailong Sun², Tian Li^2,*, Weihua Zhang²

1 Technical Center, Southwest Jiaotong University Chengdu Design Institute Co., Ltd., Chengdu, 610031, China
2 State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu, 610031, China

* Corresponding Author: Tian Li. Email:

Computer Modeling in Engineering & Sciences 2025, 144(2), 1957-1970. https://doi.org/10.32604/cmes.2025.069159

Received 16 June 2025; Accepted 31 July 2025; Issue published 31 August 2025

Abstract

High-speed maglev trains represent a key direction for the future development of rail transportation. As operating speeds increase, they face increasingly severe aerodynamic challenges. The streamlined aerodynamic shape of a maglev train is a critical factor influencing its aerodynamic performance, and optimizing its length plays a significant role in improving the overall aerodynamic characteristics of the train. In this study, a numerical simulation model of a high-speed maglev train was established based on computational fluid dynamics (CFD) to investigate the effects of streamline length on the aerodynamic performance of the train operating on an open track. The results show that the length of the streamlined section has a pronounced impact on aerodynamic performance. When the streamline length increases from 8.3 to 14.3 m, the aerodynamic drag of the head and tail cars decreases by 16.2% and 32.1%, respectively, with reductions observed in both frictions drag and pressure drag—the latter showing the most significant decrease in the tail car. Moreover, the extended streamline length effectively suppresses flow separation on the train body surface. The intensity of the positive pressure region on the upper surface of the head car streamlined section is reduced, directly leading to a 38.2% reduction in lift. This research provides a theoretical basis for the parametric design of aerodynamic shapes for high-speed maglev trains and offers guidance and recommendations for drag and lift reduction optimization.

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Keywords

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