Modelling and prediction of tyre–snow interaction using finite element analysis–smoothed particle hydrodynamics techniques

Abstract

This paper focuses on the modelling and prediction of truck tyre–snow interaction to compute tyre motion resistance coefficient. The off-road truck tyre size 315/80R22.5 is modelled using finite element analysis and validated in static and dynamic response against published measured data. The snow is modelled using smoothed particle hydrodynamics technique and hydrodynamic-elastic-plastic material and then calibrated against physical measurements provided by published terramechanics data. The contact algorithm implemented is the node-symmetric node-to-segment contact with edge treatment. The rolling resistance coefficient is also known as the motion resistance coefficient of the truck tyre–snow interaction and is computed for several operating conditions including the vertical load, inflation pressure, tyre longitudinal speed, and snow depth. The influence of the above-mentioned operating conditions on the truck tyre motion resistance coefficient is examined and discussed.

Rolling resistance prediction of off-road tire using advanced simulation and analytical techniques

“…The rolling resistance coefficient, f r , is The performed simulation to predict rolling resistance is repeated at several terrains including flooded surface, snow, dry and moist sand, clayey soil, dense sand, and snow. The obtained results are validated and published [10,11,17]. The simulations are repeated at different operating conditions such as; inflation pressures (379 kPa, 586 kPa and 758 kPa); applied vertical loads (13 kN, 27 kN, and 40 kN); and tire speed ranging between 10 and 100 km/h.…”

“…1 A model presenting the artificial neuron [9] Fig. 2 315/80R22.5 FEA truck tire dimensions [10] translational and rotational directions apart from the vertical translational direction. The vertical rest starts by applying a low rate ramp vertical load to the center of the tire resulting in deformation.…”

“…In this research, several terrains are modeled and calibrated to predict the tire-terrain interaction. The terrain modeled include soils such as dry and moist sand, clayey soil, dense sand and snow which are modeled using the isotropic-elastic-plastic-hydrodynamic relationship [10,11,14], while other terrains includes the water to model flooded surface [15][16][17]. Furthermore, the moisture effect of the soils is also taken into account by modeling moist sand and sandy loam with different moisture content [18].…”

Review of compressed snow mechanics: Testing methods

“…The goal of computational modeling of compressed snow is to provide an accurate and stable material model to be used in simulating tire-snow interaction. Both classical Finite Element Method (FEM) (Cresseri et al, 2010;Cresseri and Jommi, 2005;Meschke et al, 1996) and eXtended Finite Element Method (XFEM) (Bobillier et al, 2020;El-Sayegh and El-Gindy, 2019;Seta et al, 2003) were applied to simulate the tire-snow interaction. While good results were obtained, especially in the validation of simple compression and shear characterization tests, current state-of-the-art snow material models show poor performance in predicting tire traction (Terziyski, 2010).…”

Development of an HLFS agricultural tire model using FEA technique

“…To this aim, they developed a three dimensional element model for track tire using Pam-Crash and represented a three-layered membrane element for the carcass and belt plies. Recently in 2018, Zeinab et al [14][15][16] modeled tires for on-road and off-road operations to determine tire characteristics such as rolling resistance, traction, and cornering on different terrains.…”