Journal of Terramechanics最新文献

Traditional plowing efficiency control methods are difficult to balance the tillage efficiency and uniform plowing depth, and the impact of the motor temperature rise on the control accuracy cannot be ignored during electric tractor operations. Therefore, a plowing drag-adaptive operation control method considering the motor temperature rise was proposed for an electric tractor equipped with a sliding battery pack. Firstly, a field-oriented control model with temperature compensation for the PMSM was developed based on the obtained winding resistances and flux links at different temperatures. Then, the driving torque and battery displacement were regulated to adapt the drag variation by the fuzzy neural network algorithm, allowing joint control of the speed and slip rate, and the simulation analysis was performed. Finally, a field plowing test was conducted. The results showed that the traction efficiency is increased by 23.33 % compared with those without control, and when the motor temperature rises, it can be compensated for temperature to output the required torque accurately, and the average relative errors in both speed and slip rate are reduced. The proposed method can improve the slip and greatly enhance the plowing operational stability, which provided technical support for the automatic precision operation of electric tractors.

The working parameters of vibratory rollers have an important effect on the compaction quality. The traditional method of obtaining the best working parameters through field tests is time-consuming and laborious. In order to determine the best working parameters more conveniently and accurately, a mechanical-hydraulic-finite element co-simulation method is proposed in this paper. This method considers the effect of the hydraulic system on vibration compaction and makes the simulation result as close to the actual condition as possible. By analyzing the change of soil stress and settlement, the effect regulation of working parameters on compaction quality is obtained. The results show that the proposed co-simulation method can accurately reflect the real conditions, and the best compaction quality can be achieved when the walking speed is 3 km/h, the vibration frequency is 24 Hz, and the amplitude is 2.5 mm. The research provides a reference for improving the compaction quality and compacting-related simulation.

Planetary surface exploration rovers are required to have the ability to travel over uneven ground such as sandy or rocky terrain. In addition, to maintain long-term functionality under severe mass constraints, the rover must be highly reliable with a simple configuration. The reduction in the number of actuators will also contribute to a reduction in the number of electrical components involved and improve reliability. This paper proposes a lightweight and simple traveling and steering mechanism that combines a path-following system based on the difference in rotational speed of the left and right wheels when traveling in a curve and a passive Ackermann mechanism without an actuator, assuming a small exploration rover of a size and mass that can be mounted on a Japanese launch vehicle. We also propose a correction method to improve the path-following performance. We also developed a prototype wheeled rover of the target size and weight, and tested and evaluated the effectiveness of the proposed method in following the target path and overcoming obstacle on simulated soil.

Instrumented single tire soil bin testing was conducted on a rigid surface and artificial soil by vertically loading a radial tire (LT235/75R15) to two tire vertical loads (6 kN and 8 kN) inflated to three levels of tire inflation pressure (179, 241, and 283 kPa). Lowering the tire inflation pressure by 37 % resulted in 26 % (6 kN vertical load) and 39 % (8 kN vertical load) greater contact lengths (P < 0.05). The 2-D contact area on artificial soil (initial bulk density of 1.51 Mg/m³) was significantly affected (P < 0.05) by tire inflation pressure for each load case. Increasing the load significantly affected the tire’s contact length on soil (P = 0.0010); however, tire inflation pressure did not significantly affect the contact length on soil (P = 0.0609). Soil rut depth and tire-soil deformed volume were not significantly affected by vertical load and tire inflation pressure. Measured tire contact area on soil surface was 3.3 times the contact area on the rigid surface, suggesting tire-soil interaction interface properties on deformable soil are better than using the gross flat plate for evaluating low ground pressure tire technology effects on traction and reducing soil compaction.

Rubber tracked running gears are widely used in high-mobility Unmanned Ground Vehicles (UGV) to increase obstacle negotiation possibility in urban and rural terrain. The paper proposes a method of assessing the mobility level of the light UGV‘s tracked running gears in terms of their ability to overcome terrain obstacles. A model of rubber track system was created in the MSC ADAMS environment. A track-ground contact was also modeled, defining the traction force based on the Wong equations. For four different chassis models (rigid construction, bogies solution – rigid and elastically mounted to the frame and rocker-bogie construction), with two track tension variants, the ability to overcome five terrain obstacles was checked, taking into account three different types of soil. The solutions were accessed on the basis of parameters of general efficiency of overcoming obstacles, driving force and slip values, as well as the distribution of track pressures on the ground. The best solutions for each criterion were indicated. The simulation results showed an improvement in the driving properties with the use of elastically suspended elements. The results also emphasized the negative impact of increased track tension on overcoming obstacles and the impact of ground characteristics on the slip values of the running gear.

Modeling the force interaction between a wheel and the ground is necessary when evaluating the effectiveness of a vehicle’s mobility on challenging terrain. Soft soils with low bearing strength are a particularly difficult medium for wheeled vehicles. Helical scrolls have shown promise as an alternative to wheels which can work across a range of terrains, warranting a detailed terramechanics study to model their capabilities. Most of the existing terramechanics literature is limited to wheels and often employs an apparatus to study single wheels in a fixed geometry.

This paper describes the design and implementation of a novel apparatus capable of housing a range of scroll geometries and configurations. The apparatus is comprised of a soil container, carriage to drive the scroll in two operating configurations, and a surrounding frame that enables both vertical and horizontal motions of the carriage. The carriage is outfitted with a drive system and instrumentation to measure the sinkage, stress, and drawbar pull values required for a terramechanics characterization. Initial stress-sinkage curves for three different scroll configurations align with expected results and provide a proof of concept that the proposed apparatus can successfully measure differing geometric parameters and can be used for further terramechanics characterizations.

The study of deformable soils is one of the key factors in determining the tire, vehicle and/or agricultural tool design parameters. This literature review provides a brief overview of soil classification, soil testing, soil constitutive models, and numerical approaches utilized to model soil-tire/tool interaction. In the past, empirical, semi-empirical, and analytical soil models were used in these studies. However, some limitations occurred in terms of characterization of soil-tire/tool interaction in detail due to a large number of variables such as cohesion, moisture content, etc. In the last few decades, the finite element (FE) method was used with different formulations such as Lagrangian, Eulerian, and Arbitrary Lagrangian Eulerian to simulate the soil-tire/tool interaction. Recently, particle-based methods based on continuum mechanics and discrete mechanics started to be employed and showed good capability in terms of modeling of soil deformation and separation. Overall, this literature review provides simulation researchers insights into soil interaction modeling with tires and agricultural tools.

Distinct physical properties of red clay soil in hilly and mountainous regions of southwest China, including high adhesiveness and density, challenge the operation of agricultural machinery. A scarcity of accurate discrete element simulation parameters for this soil type restricts computational modeling. The study was focused on red clay soil with a moisture content of 12.50% ± 1% and a measured repose angle of 35.54°. The soil's inherent physical properties were identified through experimental assessments. Soil contact mechanical parameters were obtained from the GEMM database, and optimal contact parameter ranges were determined using Steepest Ascent Experiments, with the simulated soil particle repose angle serving as the response value. A second-order regression model was developed using a quadratic regression rotation orthogonal combination test. By taking the actual repose angle as the optimization criterion, parameters were optimized. The optimal contact mechanical parameters in EDEM simulations were identified as: JKR surface energy at 8.981 J/m², recovery coefficient at 0.474, dynamic friction coefficient at 0.196, and static friction coefficient at 0.45. The model yielded a repose angle of 36.21°, closely corresponding with the observed value, with a relative error of 1.80%. The parameters calibrated in this study offer a valuable reference for future soil-tool interaction studies and tillage implement optimization in these regions.

The dynamic behavior of the vibratory drum of a soil compactor for earthworks is known to be affected by soil stiffness. Real-time monitoring techniques measuring the acceleration of vibratory drums have been widely used for soil compaction quality control; however, their accuracy can be affected by soil type and conditions. To resolve this problem, a novel deep learning-based technique is developed. The method allows the regression estimation of soil stiffness from vibration drum acceleration responses. By expanding the range of applicability and improving accuracy, the proposed method provides a more reliable and robust approach to evaluate soil compaction quality. To train the estimation model, numerous datasets of noise-free waveform data are numerically generated by solving the equations of motion of the mass–spring–damper system of a vibratory roller. To validate the effectiveness of the proposed technique, a field experiment is conducted. A good correlation between the estimated and measured values is demonstrated by the experimental results. The correlation coefficient is 0.790, indicating the high potential of the proposed method as a new real-time monitoring technique for soil compaction quality.