Abstracts:Energy saving has been a prominent concern of ground vehicle Original Equipment Manufacturers and research agencies for decades. The search for technological advances that can increase energy efficiency of vehicles has been a relentless quest. The framework of research on energy efficiency improvements has been considerably extended after the introduction of fully electric vehicles with electric motors that individually drive each wheel, i.e., In-Wheel Motors (IWM). Although incoming IWM vehicles can significantly decrease driveline power losses and, thus, improve vehicle energy efficiency compared to conventional mechanical driveline systems, one technical problem related to the vehicle-tire-terrain interaction needs to be addressed in fully electric terrain vehicles. These vehicles are still lacking strategies to manage power distribution between the drive wheels, which are not connected by a driveline system anymore, with the purpose to minimize slip power losses at all tires and maximize vehicle slip energy efficiency. Inappropriate power delivered to each of the wheels, which run in different stochastic terrain conditions, can deteriorate slip energy efficiency of a vehicle with four individually driven wheels. The research work presented in this article addresses the problem of wheel power distribution for an unmanned ground vehicle (UGV) with four IWMs.

Abstracts:Vehicle traction between the wheel and the ground surface is a critical design element for on-road and off-road mobility. Adequate traction in dry sand relates to the vehicle’s ability to negotiate deserts, sand dunes, climb slopes, and ingress/egress along beaches. The existing traction equations predict values for only one mode of operation (braked, towed, or powered). In this article, we propose a unified algorithm for continuous prediction of traction over a range of braked, towed, and powered operations for wheels operating on sand. A database of laboratory and field records for wheeled vehicles, entitled Database Records for Off-road Vehicle Environments (DROVE), was used to develop the proposed algorithm. The algorithm employs the ratio of contact pressure to cone index as a primary variable to develop fitting parameters for a relationship between slip and traction. The performance of the algorithm is examined versus the measured data and is also compared against two alternative equations. The new equation showed higher correlation and lower error compared to the existing equations for powered wheels. The proposed equation can be readily implemented into off-road mobility models, eliminating the need for multiple traction equations for different modes of operation.

Abstracts:In the geotechnical and terramechanical engineering applications, precise understandings are yet to be established on the off-road structures interacting with complex soil profiles. Several theoretical and experimental approaches have been used to measure the ultimate bearing capacity of the layered soil, but with a significant level of differences depending on the failure mechanisms assumed. Furthermore, local displacement fields in layered soils are not yet studied well. Here, the bearing capacity of a dense sand layer overlying loose sand beneath a rigid beam is studied under the plain-strain condition. The study employs using digital particle image velocimetry (DPIV) and finite element method (FEM) simulations. In the FEM, an experimentally characterised constitutive relation of the sand grains is fed as an input. The results of the displacement fields of the layered soil based DPIV and FEM simulations agreed well. From the DPIV experiments, a correlation between the slip surface angle and the thickness of the dense sand layer has been determined. Using this, a new and simple approach is proposed to predict theoretically the ultimate bearing capacity of the layered sand. The approach presented here could be extended more easily for analysing other complex soil profiles in the ground-structure interactions in future.

Abstracts:This paper presents the establishment and validation of an improved model predicting tractive parameters of a lugged wheel under multiple operating conditions. During the basic straight driving wheel-soil interaction, the common-used equivalent radius theory and the bulldozing theory are combined to calculate the lug effects referring the traditional theories of soil stress distribution, while the bulldozing effect is reconsidered according to the work conservation. On the basis of the further prediction under multiple conditions including the inclination in three degrees of freedom and the turning driving, the numerical model using the discrete element method under each operating condition is separately established. Under such circumstances, the validation and analysis are conducted differing in sizes and driving parameters of the wheel. It is indicated that the improved model displays the better reasonability and precision in predicting lug effects of a heavy off-road wheel. This model is mostly accurate and sensitive to the variation of parameters under straight and inclining driving conditions, but demands further correction during low slipping of the turning condition. Generally, the improved model in this paper focuses on the prediction of drawbar pull and driving torque, but lacks precision in the tendency of sinkage.