Dynamic characteristics of rack vehicle-track coupled system on large slope line: theoretical modelling and experimental validation

Abstract

Rack railway is a rail transportation that utilizes the gear-rack engagement to supply the traction forces on large-slope lines, primarily employed in mountainous regions where the conventional trains cannot operate due to the wheel-rail adhesion limitations. However, there is limited research on this system dynamics and further analysis is required to understand the interaction mechanism between the rack vehicle and track. Based on the typical vehicle-track coupled dynamics theory, the rack vehicle-track spatially coupled dynamics model is developed in this paper to evaluate the dynamic behaviours of the rack vehicle and the track system running on large-slope line with a detailed modeling of the longitudinal motion for the rack and sleeper, where the time-varying gear-rack mesh stiffness and the rail geometrical irregularity are incorporated. The excellent agreement observed between simulated and field-test results serves as strong validation for developed dynamics model. The results demonstrate that the vibration responses of the wheelset and the rack are dominated by the gear-rack mesh excitations. It should be noticed that the wheel loads are reduced by the presence of the gear-rack engagement. Furthermore, the vibration of the sleeper can explicitly reflect the gear-rack mesh characteristics through the transfer of the rack fastener.

KEYWORDS:

• Rack vehicle
• vehicle-track coupled dynamics
• gear-rack engagement
• time-varying mesh stiffness
• large slope line

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 52022083], the Project of Science and Technology of Sichuan Province [grant number 2021YFG0065], and the Fundamental Research Funds for the State Key Laboratory of Rail Transit Vehicle System of Southwest Jiaotong University [grant number 2023TPL-T11].