Publication news

Estimation of terramechanics parameters of wheel-soil interaction model using particle filtering

Shamrao, Chandramouli Padmanabhan, Sayan Gupta, Annadurai Mylswamy

Journal of Terramechanics, Volume 79, 2018, Pages 79-95, ISSN 0022-4898,

https://doi.org/10.1016/j.jterra.2018.07.003.

(http://www.sciencedirect.com/science/article/pii/S0022489817302720)

Abstract: Accurate estimation of the parameters affecting the wheel-soil interaction terramechanics of an extraterrestrial rover is key to the success of its mission. Traditional approaches to estimating the relevant parameters based on laboratory tests lead to predictions that show significant deviation from experimental observations. The objective of this article is to apply dynamic Bayesian estimation techniques on the measurements from simple single wheel tests to estimate the terramechanics parameters. This ensures that the parameter estimation takes into account the scatter that invariably exists in physical measurements. A mathematical model for a rigid wheel driven on a dry (0% moisture content) granular soil medium is considered to model the planetary regolith. It is demonstrated that adopting Bayesian techniques for terramechanics parameter estimation leads to good predictions for the drawbar pull, torque and the wheel sinkage. This bypasses the need for using more complex models which in turn require additional parameters to be estimated.

Keywords: Wheel-soil interaction; Dynamic Bayesian estimation; Particle filter; Single wheel test; Bevameter

Determination of in-situ engineering properties of soil using an inverse solution technique and limited field tests

Qingsong Zhang, Shrini K. Upadhyaya, Qingxi Liao, Xuan Li

Journal of Terramechanics, Volume 79, 2018, Pages 69-77, ISSN 0022-4898,

https://doi.org/10.1016/j.jterra.2018.07.001.(http://www.sciencedirect.com/science/article/pii/S0022489817302203)

Abstract: The goal of this research is to develop a response surface based inverse solution technique to determine in-situ engineering properties of soil for use in mobility and traction prediction models from the force displacement data generated by a cone penetrometer device. The nonlinear elasto-plastic behavior of soil was characterized by a six-parameter constitutive model – two elastic parameters (i.e., bulk modulus, K and the Poisson’s ratio, υ), three plastic parameters (i.e., angle of internal friction φ, cohesion c, and soil hardening parameter λ), and one soil physical condition parameter (i.e. initial void ratio, e∗). Soil failure was represented by the Drucker-Prager yield criterion and associated flow rule. LS-DYNA FEM software package was used to model the soil-cone interaction problem. FEM simulations were conducted for a set of soil properties properly selected within the defined parameter space. The analysis of FEM simulations indicated that the cone penetration force-displacement curves could be represented by two piecewise smooth functions – a parabola followed by a straight line. The coefficients of these two curves were used to create fourth order response surfaces using a stepwise multiple linear regression technique. The results showed both cohesion and soil hardening parameter could be predicted using this methodology.

Keywords: Finite element modeling; Machine-soil interaction; Nonlinear behavior; Optimization

Assessment of the side thrust for off-road tracked vehicles based on the punching shear theory

Sung-Ha Baek, Gyu-Beom Shin, Choong-Ki Chung,

Journal of Terramechanics, Volume 79, 2018, Pages 59-68, ISSN 0022-4898,

https://doi.org/10.1016/j.jterra.2018.07.002.

(http://www.sciencedirect.com/science/article/pii/S0022489817302306)

Abstract: The track system is generally applied for heavy off-road vehicles. While moving on the off-road, the track system horizontally transmits an engine torque to the soil-track interface, resulting in slip displacement and an associated soil thrust acting as a traction force. As soil thrust is developed on the bottom and the side of the track system (hereinafter referred to as “bottom thrust” and “side thrust”, respectively), it is imperative to evaluate both the bottom thrust and the side thrust to assess the off-road tracked vehicle’s performance. Unlike the bottom thrust, however, the mechanisms of the side thrust have not been fully understood. To address this, this study aimed to evaluate the side thrust for off-road tracked vehicles. A new mechanism for the side thrust was theoretically investigated based on the punching shear theory. A series of model track experiments were conducted on a model track system with silty sand. From the experiment results, the shapes of the failure surface were observed, and the side thrust was measured for verification purposes. Particular attention was given to the development of a side thrust prediction model for the heavy off-road tracked vehicles based on the proposed mechanism.

Keywords: Off-road tracked vehicle; Track system; Tractive performance; Side thrust; Model track experiment; Soil-track interaction; Punching shear theory

Development and numerical validation of an improved prediction model for wheel-soil interaction under multiple operating conditions

Yonghao Du, Jingwei Gao, Lehua Jiang, Yuanchao Zhang
Journal of Terramechanics, Volume 79, 2018, Pages 1-21, ISSN 0022-4898, 
https://doi.org/10.1016/j.jterra.2018.04.005.

Abstract: 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.

Keywords: Wheel-soil interaction; Prediction model; Lug effects; Multiple operating conditions; Discrete element method
 

Interaction of a rigid beam resting on a strong granular layer overlying weak granular soil: Multi-methodological investigations

Zuhair Kadhim Jahanger, S. Joseph Antony, Elaine Martin, Lutz Richter
Journal of Terramechanics, Volume 79, 2018, Pages 23-32, ISSN 0022-4898,
https://doi.org/10.1016/j.jterra.2018.05.002.

Abstract: 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.

Keywords: Granular mechanics; Bearing capacity; Layered soil; FEM; DPIV; Failure mechanism

A unified equation for predicting traction for wheels on sand over a range of braked, towed, and powered operations

George L. Mason, James M. Williams, Farshid Vahedifard, Jody D. Priddy
Journal of Terramechanics, Volume 79, 2018, Pages 33-40, ISSN 0022-4898,
https://doi.org/10.1016/j.jterra.2018.05.005.

Abstract: 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.

Keywords: Off-road mobility; Sand; Traction; Vehicle Terrain Interface (VTI) model; Database Records for Off-road Vehicle Environments (DROVE)

UGV with a distributed electric driveline: Controlling for maximum slip energy efficiency on stochastic terrain

Mostafa A. Salama, Vladimir V. Vantsevich, Thomas R. Way, David J. Gorsich]

Journal of Terramechanics, Volume 79, October 2018, Pages 41-57, ISSN 0022-4898, https://doi.org/10.1016/j.jterra.2018.06.001.

Abstract: 
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.

Keywords: In-Wheel Motor UGV; Optimal wheel power distribution; Stochastic terrain condition; Slip energy efficiency; Inverse dynamics control

Performance of combined offset disc harrow (front active and rear passive set configuration) in soil bin

Ganesh Upadhyay, Hifjur Raheman

Journal of Terramechanics, Volume 78, 2018, Pages 27-37, ISSN 0022-4898,
https://doi.org/10.1016/j.jterra.2018.04.002.

Abstract: Soil bin investigations were initiated with combined offset disc harrow (CODH) which unites the benefits of powered discs and combination tillage together through a front active-rear passive set configuration. The proposed configuration may help to achieve timeliness in sowing, better crop residue handling with reduced tillage passes and improved engine power utilization of tractor. The effects of speed ratio (u/v), front gang angle (α), operating depth and cone index (CI) on its draft, torque and power requirement were studied and compared with its traditional passively driven mode at an average soil moisture of 9–10% (db) in sandy-clay loam soil. Optimum system settings were found out before further performance evaluation in the field. The substantially reduced draft requirement with CODH might help to reduce the wheel slippage and improve field productivity while increased power requirement might prevent the under-loading of tractor engine. Tillage quality was assessed considering CI values and found to be far superior compared to traditional mode. Optimum system settings were found at α of 35° and u/v ratio of 3.6 in terms of lowest power expenditure and better work quality with torque power expenditure of 60–70% in total power indicating improved utilization of engine power if operated with tractor power take-off (PTO).

Keywords: Draft; Torque; Passively driven mode; Speed ratio; Front gang angle
 

Probabilistic self-tuning approaches for enhancing performance of autonomous vehicles in changing terrains

Alvaro Javier Prado, Fernando A. Auat Cheein, Saso Blazic, Miguel Torres-Torriti,

Journal of Terramechanics, Volume 78, 2018, Pages 39-51, ISSN 0022-4898,
https://doi.org/10.1016/j.jterra.2018.04.001.

Abstract: Motion controllers usually require a tuning stage to ensure an acceptable performance of the vehicle during operation in challenging scenarios. However, such tuning stage is a time consuming process for the programmer and often is based on intuition or heuristic approaches. In addition, once tuned, the vehicle performance varies according to the nature of the terrain. In this work, we study the use of well-known probabilistic techniques for self-tuning trajectory tracking controllers for service units based on the idea of saving both vehicle’s resources and human labour force time. The proposed strategies are based on Monte Carlo and Bayesian approaches to find the best set of gains to tune the controller both off-line and on-line, thus enhancing the controller performance in the presence of changing terrains. The approaches are implemented and validated on a skid-steer mini-loader vehicle usually used for mining purposes. Implementation details and both simulation and empirical results are included in this work, showing that when using our approaches, effort can be saved up to 30% and tracking errors reduced up to 75%.

Keywords: Trajectory tracking control; Auto-tuning; Industrial machinery; Wheel-terrain interaction