Numerical analysis on tractive performance of off-road tire on gravel road using a calibrated finite element method–discrete element method model and experimental validation

Xu, Wenjie; Zeng, Haiyang; Yang, Peng; Miao, Zhuang

doi:10.1177/0954407020930175

Cited by 15 publications

(12 citation statements)

References 61 publications

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“…3 The behaviour of tyres in contact with various ground interfaces (dry, wet, sand, dirt, snow) has been studied for automotive vehicle tyres, 4–8 truck tyres 9–15 and off-road tyres. 16,17 NASA, specifically, has also carried out extensive testing and parameterisation of aircraft tyres. 18…”

Section: Introductionmentioning

confidence: 99%

“…3 The behaviour of tyres in contact with various ground interfaces (dry, wet, sand, dirt, snow) has been studied for automotive vehicle tyres, [4][5][6][7][8] truck tyres [9][10][11][12][13][14][15] and off-road tyres. 16,17 NASA, specifically, has also carried out extensive testing and parameterisation of aircraft tyres. 18 One of the first attempts to model tyre responses with FEA was conducted by Kilner to study the vertical ground interaction and the drag load.…”

Section: Introductionmentioning

confidence: 99%

“…The FEA approaches mostly reported in literature include composite layup 16,17,21,27 and rebar element 7,[28][29][30] methods. Composite layup is usually used to model the plies as layers of a composite laminate defining material, direction and thickness through integration points for each layer.…”

Section: Introductionmentioning

confidence: 99%

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Implementation of a finite element modelling strategy for the prediction of aircraft tyre response

Ramji

Grasso

Chase³

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part G:

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This paper presents the finite element modelling (FEM) strategy to identify the structural response of aircraft tyres under quasi-static and taxiing load conditions. The tyre FEM was developed to simulate the aircraft tyre/ground interaction for a range of inflation pressures under vertical, lateral, longitudinal, torsional, yawed and un-yawed rolling. A thorough comparison for validation purposes is made between the test and simulation data extracted from the FEM. The reinforcement plies of the tyres are modelled in a computationally efficient manner whilst also considering the variable fibre volume fractions and ply discontinuities within the tyre. The accurate material characterisation at coupon level combined with the overall modelling approach allowed most simulated responses to match the experimental stiffness within 12% against best fit curves of similar tyre types and within 5% for the majority of test comparisons.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Implementation of a finite element modelling strategy for the prediction of aircraft tyre response

Ramji

Grasso

Chase³

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part G:

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“…The terramechanics characteristics have a significant impact on the traction performance of the vehicle when the vehicle is running on soft road. The current research methods of terramechanics include finite element method, 17 discrete element method, 18 discrete element-finite element coupling method, 19 other simulation methods and numerical analysis methods. 20,21 The researchers established a wheel-terrain interaction model between a single tire and sandy soil based on terramechanics and simulation theory.…”

Section: Introductionmentioning

confidence: 99%

Vertical load distribution strategy of amphibious wheel-track vehicle using neural network and particle swarm optimization

Gao

Tang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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Amphibious wheel-track vehicle (AWTV) can change the vertical load of the wheels and the tracks through the active hydro-pneumatic suspension system, which shows significant advantages in terms of maneuverability and road passing ability. However, AWTV is a strong nonlinear system. The irregularity of the road, and coupling characteristics between the vertical load of the wheel-tracks and the terrain will greatly affect the tractive efficiency of the whole vehicle. Therefore, how to effectively distribute the vertical load between the wheel and the track to improve the tractive efficiency of the whole vehicle is still a huge challenge. To address the above problems, based on the neural network (NN) and particle swarm optimization (PSO) algorithm, vertical load distribution strategy of the AWTV is proposed to improve its traction efficiency under different driving road in this paper. Firstly, the coupling dynamics model of AWTV with road and hydraulic system dynamics model of active suspension is established; Secondly, the wheel-track terrain model is built in EDEM-Recurdyn to collect data of vertical load and traction efficiency under the different soils and speeds, and the coupling function is obtained through NN; Then, the optimal vertical load of each axle is optimized through PSO; Finally, the feasibility and effectiveness of the strategy are verified by the simulation analysis under different road conditions and distribution strategies. The simulation and test results demonstrate that the proposed vertical load distribution strategy based on NN-PSO can effectively improve the traction performance of the AWTV in complex terrain environment, and have relatively superior control characteristics.

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“…A similar DEM-FEM method has been used to investigate the tractive performance of off-road tyres on a cobble pavement. 22,23 Nakashima et al used two-dimensional (2D) FEM to establish the model of the tyre and bottom of the soil, and a 2D DEM to establish the model of the soil surface layer. By coupling finite elements and discrete elements, the driving behavior of the tyre on sand was simulated using the DEM-FEM.…”

Section: Introductionmentioning

confidence: 99%

Tractive performance prediction for wheeled unmanned vehicles based on dynamics and discrete element method

Wang

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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Tractive performance is a key factor affecting the field mobility of unmanned vehicles. Presently, studies on the tractive performance of unmanned vehicles mainly focus on the tractive performance of a single wheel, but few studies have used the discrete element method to predict the tractive performance of vehicles. In this paper, a method based on dynamics and discrete elements is proposed to predict the traction performance of a vehicle. Based on the proposed method, the tractive performance of an unmanned vehicle in various field environments is obtained. Firstly, a numerical method for calculating the dynamic tractive performance of the vehicle on a flat road surface is proposed based on vehicle dynamics theory and terramechanics. According to the corresponding soil parameters, the tractive performance of the vehicle on three different sandy loams and three different clays is calculated. The mechanism of action between the wheels and the soil on sloped road is different from that on flat road, and the numerical calculation method is no longer suitable for predicting the tractive performance of vehicles on sloped roads. To predict the tractive performance of unmanned vehicles on various slope roads, the dynamic and discrete element method was used to simulate a sandy loam flat road, sandy loam pitch slope, sandy loam roll slope, light clay flat road, light clay pitch slope, and light clay roll slope. The vehicle dynamics model was established using dynamics software, and the tractive performance of the vehicle on six different roads was obtained through the coupling simulation of dynamics and discrete elements.

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Numerical analysis on tractive performance of off-road tire on gravel road using a calibrated finite element method–discrete element method model and experimental validation

Cited by 15 publications

References 61 publications

Implementation of a finite element modelling strategy for the prediction of aircraft tyre response

Implementation of a finite element modelling strategy for the prediction of aircraft tyre response

Vertical load distribution strategy of amphibious wheel-track vehicle using neural network and particle swarm optimization

Tractive performance prediction for wheeled unmanned vehicles based on dynamics and discrete element method

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