Applied Sciences (Nov 2024)
Efficient Wheel-Rail Stick-Slip Numerical Modeling for Railway Traction Vehicles
Abstract
Motor railway vehicles necessitate enhanced control of wheel-rail contact mechanics to ensure optimal adhesion. During train running, driving wheelsets exhibit torsional vibrations that compromise adhesion and potentially lead to axle damage. Consequently, the development of dynamic models for analyzing driving wheelset stick-slip phenomena and control strategies is an area of significant research interest for traction control, studies on rail corrugation, and locomotive drivetrain design. Despite their application in various railway vehicle problems, non-smooth models have not been explored as an alternative for analyzing stick-slip, and existing research has focused on extensive computations based on Kalker’s theory or simplified models using constitutive friction laws. This work demonstrates the efficacy of non-smooth models in studying motor wheelset stick-slip. The non-smooth approach is suited for control systems, prioritizes simplicity while capturing the essential friction characteristics, and enables efficient dynamic simulations. The proposed model incorporates a set-valued friction law, and the equations of motion are formulated as a switch model. Numerical integration is achieved through an event-driven algorithm. The paper showcases application examples for the model. A direct comparison with an equivalent model using a constitutive friction law shows that the non-smooth integration is an order of magnitude more efficient in the stick phase.
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