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April 26, 2026Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering0 citations

Simulation and experimental analysis of transient response of cross-country vehicle tire traversing a cleat based on a high-precision finite element model

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YLYue LiuBeijing Institute of TechnologyJXJunqiang XiBeijing Institute of Technology

Key Points

  • The aim is to develop a high-fidelity finite element model to predict the behavior of vehicle tires on complex terrains.
  • Developed a finite element model incorporating Rayleigh damping for dynamic simulation.
  • Characterized hyperelastic parameters through material testing and reverse engineering.
  • Validated the model under static and dynamic conditions, achieving high correlation coefficients.
  • Predictions for static stiffness exceeded 95% correlation with experimental data on flat ground and cleat tests.
  • Dynamic cleat traversal showed global accuracy consistently above 95% in force response simulations.

Abstract

This study develops a high-fidelity finite element (FE) model to predict the mechanical behavior of cross-country vehicle tires on complex terrains. Through reverse engineering and material testing, the hyperelastic parameters of the rubber compounds were characterized, and the cord-rubber composites were accurately modeled using rebar elements with orthotropic elasticity. The established 3D tire model incorporates Rayleigh damping to enhance dynamic simulation stability. Extensive validation under static and dynamic conditions demonstrates high accuracy. The correlation coefficients between predictions and experiments exceed 95% for static stiffness on flat ground and cleat loading tests. For dynamic cleat traversal, a hybrid simulation strategy was employed. The simulated vertical force responses show excellent agreement with experimental measurements across various operating conditions, with a global accuracy consistently above 95%. This validated model provides a reliable digital tool for tire performance prediction and design optimization.

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Cite This Study

Liu et al. (2026) studied this question.

synapsesocial.com/papers/69edacbd4a46254e215b47a2https://doi.org/10.1177/09544070261430078
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