Analysis of the nonlinear dynamic behavior of longitudinal systems in heavy-haul trains

Leiting Wang; Yang Jin; Wangxiang Li; Chenyang Tang; Leiting Wang; Yang Jin; Wangxiang Li; Chenyang Tang

doi:10.3934/era.2025027

Electronic Research Archive

2025, Volume 33, Issue 2: 582-599. doi: 10.3934/era.2025027

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Analysis of the nonlinear dynamic behavior of longitudinal systems in heavy-haul trains

1.
School of Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
2.
National Key Laboratory of Rail Transit Carrying Systems, Southwest Jiaotong University, Chengdu 610031, China

Received: 03 November 2024 Revised: 19 December 2024 Accepted: 02 January 2025 Published: 08 February 2025

The payload, coupler slack, and buffer device performance in heavy-haul trains substantially affect their longitudinal dynamic systems under operational conditions. These factors result in the bifurcation of the system, consequently leading to chaos. To study this phenomenon in depth, a two-degrees-of-freedom longitudinal dynamics model of the train is established. The system is analyzed using the fourth-order Runge–Kutta (R-K_4) numerical integration method, incorporating bifurcation diagrams, phase planes, Poincaré mapping, and time-domain analysis to elucidate the trajectory of the system as it transitions into a chaotic state of motion via period-doubling bifurcations and quasi-periodic motions. A comprehensive analysis of the complex nonlinear dynamics of the train's longitudinal system can establish a theoretical foundation for forecasting and regulating the chaotic motion of the train system.
- heavy-haul trains,
- coupler buffer device,
- periodic motion,
- bifurcation,
- chaos
Citation: Leiting Wang, Yang Jin, Wangxiang Li, Chenyang Tang. Analysis of the nonlinear dynamic behavior of longitudinal systems in heavy-haul trains[J]. Electronic Research Archive, 2025, 33(2): 582-599. doi: 10.3934/era.2025027

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Abstract

The payload, coupler slack, and buffer device performance in heavy-haul trains substantially affect their longitudinal dynamic systems under operational conditions. These factors result in the bifurcation of the system, consequently leading to chaos. To study this phenomenon in depth, a two-degrees-of-freedom longitudinal dynamics model of the train is established. The system is analyzed using the fourth-order Runge–Kutta (R-K_4) numerical integration method, incorporating bifurcation diagrams, phase planes, Poincaré mapping, and time-domain analysis to elucidate the trajectory of the system as it transitions into a chaotic state of motion via period-doubling bifurcations and quasi-periodic motions. A comprehensive analysis of the complex nonlinear dynamics of the train's longitudinal system can establish a theoretical foundation for forecasting and regulating the chaotic motion of the train system.

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