Numerical Simulation and Performance Prediction of Ejection Impact of Air Spring Based on Fluid–Structure Interaction

Author:

li yuru1ORCID,Xiao Shoune2,Xie Junke1,zhu Tao2

Affiliation:

1. Henan University of Science and Technology

2. Southwest Jiaotong University

Abstract

Abstract Air springs have found wide application in cushioning and shock absorption, but their use in ejection scenarios is still in its early stages. To address the challenges of applying air spring in high-speed ejections of rail vehicles, this study focuses on the ejection of the driver's cabin structure and investigates the elastic performance of air spring using a series-parallel combination. The study analyzes ejection characteristics for air spring in a series-parallel configuration by number simulation. A second-order response surface method is employed to establish a predictive model for the ejection performance of air spring in this configuration. The model's accuracy is verified through virtual collision analysis of the driver's cabin in a rail vehicle. The ejection velocity exhibits a relative error of only 9.1%. The test vehicle, driven by air spring, achieves a maximum kinetic energy of 415 kJ, meeting the initial target value of not less than 408 kJ. Additionally, the analysis of wheel-rail interaction reveals that the vertical lift and lateral displacement of the test vehicle are within acceptable limits, measuring 5.49 mm and 9.89 mm, respectively, without exceeding the wheel flange height and tread width. These results demonstrate that air spring with series-parallel combination can successfully propel the test vehicle to conduct driver's cabin collision tests, without any derailment or overturning. As a result, the study realizes ejection tests using air spring with series-parallel combination. The research on the ejection performance of air spring in this configuration offers a new driving and ejection method for applying air spring in rail vehicles, drones, and air-launched missiles, presenting promising prospects for future applications.

Publisher

Research Square Platform LLC

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