STOCHASTIC MODELING AND UNCERTAINTY CASCADE OF SOIL BEARING AND SHEARING CHARACTERISTICS FOR LIGHT-WEIGHT VEHICLE APPLICATIONS

This paper investigates the validity of commonly used terramechanics models for light-weight vehicle applications while accounting for experimental variability. This is accomplished by means of cascading uncertainty up to the terminal point of operations measurement. Vehicle-terrain interaction is extremely complex, and thus models and simulation methods for vehicle mobility prediction are largely based on empirical test data. Analytical methods are compared to experimental measurements of key operational parameters such as drawbar force, torque, and sinkage. Models of these operational parameters ultimately depend on a small set of empirically determined soil parameters, each with an inherent uncertainty due to test variability. The soil parameters associated with normal loads are determined by fitting the dimensionless form of Bekker’s equation to the data given by the pressure-sinkage test. In a similar approach, the soil parameters associated with shear loads are determined by fitting Janosi and Hanamoto’s equation to the data given by the direct shear test. An uncertainty model is used to propagate the soil parameter variability through to the wheel performance based on Wong and Reece. The commonly used analytical model is shown to be inaccurate as the envelope of model uncertainty does not lie within the experimental measures, suggesting that model improvements are required to accurately predict the performance of light-weight vehicles on deformable terrain.

[1]  A. R. Reece,et al.  Prediction of rigid wheel performance based on the analysis of soil-wheel stresses , 1967 .

[2]  K. Terzaghi,et al.  Soil mechanics in engineering practice , 1948 .

[3]  Lin Li,et al.  On the impact of cargo weight, vehicle parameters, and terrain characteristics on the prediction of traction for off-road vehicles , 2007 .

[4]  A. R. Reece,et al.  Prediction of rigid wheel performance based on the analysis of soil-wheel stresses part I. Performance of driven rigid wheels , 1967 .

[5]  M. G. Bekker,et al.  Off-the-Road Locomotion: Research and Development in Terramechanics , 1960 .

[6]  Matthew Spenko,et al.  A modified pressure–sinkage model for small, rigid wheels on deformable terrains , 2011 .

[7]  Jo Yung Wong,et al.  Terramechanics and Off-Road Vehicle Engineering: Terrain Behaviour, Off-Road Vehicle Performance and Design , 2009 .

[8]  Karl Iagnemma,et al.  Investigation of Stress and Failure in Granular Soils for Lightweight Robotic Vehicle Applications , 2012 .

[9]  J. Y. Wong,et al.  Data processing methodology in the characterization of the mechanical properties of terrain , 1980 .

[10]  Carmine Senatore,et al.  Direct shear behaviour of dry, granular soils for low normal stress with application to lightweight robotic vehicle modelling , 2011 .

[11]  Hammad Mazhar,et al.  Investigating the Mobility of Light Autonomous Tracked Vehicles using a High Performance Computing Simulation Capability , 2012 .

[12]  R. Anderson,et al.  Mojave Martian Simulant: A New Martian Soil Simulant , 2007 .

[13]  B. Hanamoto,et al.  The analytical determination of drawbar pull as a function of slip for tracked vehicles in deformable soils , 1961 .

[14]  Karl Iagnemma,et al.  A polynomial chaos approach to the analysis of vehicle dynamics under uncertainty , 2012 .

[15]  Barry N. Taylor,et al.  Guidelines for Evaluating and Expressing the Uncertainty of Nist Measurement Results , 2017 .

[16]  Karl Iagnemma,et al.  A Laboratory Single Wheel Testbed for Studying Planetary Rover Wheel-Terrain Interaction , 2005 .