Search Results (157)

In railways, problems in braking and traction can be caused by so-called low-adhesion conditions. Adhesion is increased by sanding, where sand grains are blasted towards the wheel–rail contact. Despite the successful use of sanding in practice and extensive experimental studies, the physical mechanisms of adhesion increase are poorly understood. This study combines experimental work with a DEM model to aim at a deeper understanding of adhesion increase during sanding. The experimentally observed processes during sanding involve repeated grain breakage, varying sand fragment spread, formation of clusters of crushed sand powders, plastic deformation of the steel surfaces due to the high load applied and shearing of the compressed sand fragments. The developed DEM model includes all these processes. Two types of rail sand are analysed, which differ in adhesion increase in High-Pressure Torsion tests under wet contact conditions. This study shows that higher adhesion is achieved when a larger proportion of the normal load is transferred through sand–steel contacts. This is strongly influenced by the coefficient of friction between sand and steel. Adhesion is higher for larger sand grains, higher sand fragment spread, and higher steel hardness, resulting in less indentation, all leading to larger areas covered by sand. Full article

With the rise of vehicle automation, accurate estimation of driving dynamics has become crucial for ensuring safe and efficient operation. Vehicle dynamics control systems rely on these estimates to provide necessary control variables for stabilizing vehicles in various scenarios. Traditional model-based methods use wheel-related measurements, such as steering angle or wheel speed, as inputs. However, under low-traction conditions, e.g., on icy surfaces, these measurements often fail to deliver trustworthy information about the vehicle states. In such critical situations, precise estimation is essential for effective system intervention. This work introduces an AI-based approach that leverages perception sensor data, specifically camera images and lidar point clouds. By using relative kinematic relationships, it bypasses the complexities of vehicle and tire dynamics and enables robust estimation across all scenarios. Optical and scene flow are extracted from the sensor data and processed by a recurrent neural network to infer vehicle states. The proposed method is vehicle-agnostic, allowing trained models to be deployed across different platforms without additional calibration. Experimental results based on real-world data demonstrate that the AI-based estimator presented in this work achieves accurate and robust results under various conditions. Particularly in low-friction scenarios, it significantly outperforms conventional model-based approaches. Full article

This study investigates the operational performance of fruit-picking robots under varying terrain slopes and soil moisture conditions, with a focus on comparing wheeled and tracked locomotion systems. A modular robot platform was designed and tested in both controlled environments and actual mountainous orchards in Shandong, China. The experiments assessed key performance metrics—average speed, slip rate, and path deviation—under combinations of four slope levels (0°, 8°, 18°, 28°) and three soil moisture levels (dry 10%, moderate 20%, wet 35%). Results reveal that wheeled robots perform optimally on dry and flat terrain but experience significant slippage and path deviation under steep and wet conditions. In contrast, tracked robots maintain better stability and terrain adaptability, demonstrating lower slip rates and more consistent trajectories across a wide range of conditions. A synergistic deterioration effect was observed when high slope and high soil moisture co-occur, significantly degrading the performance of wheeled systems, while tracked systems mitigated these effects. Complementary semi-structured interviews with 20 orchard stakeholders—including farmers, growers, and hired pickers—highlighted key user expectations: robust traction, terrain adaptability, reduced physical labor, and operational safety. The findings suggest that future agricultural robots should adopt adaptive hybrid mobility systems and integrate environmental perception capabilities to enhance performance in complex agricultural scenarios. These insights contribute practical and theoretical guidance for the design and deployment of intelligent fruit-picking robots in diverse field environments. Full article

This study develops a real-time energy-efficient control strategy for distributed-drive electric tractors (DDETs) to minimize electrical energy consumption during traction operations. Taking a four-wheel independently driven DDET as the research object, we conduct dynamic analysis of draft operations and establish dynamic models of individual components in the tractor’s drive and transmission system. A backpropagation (BP) neural network-based operational speed prediction model is constructed to forecast operational speed within a finite prediction horizon. Within the model predictive control (MPC) framework, a real-time energy-efficient control strategy is formulated, employing a dynamic programming algorithm for receding horizon optimization of energy consumption minimization. Through plowing operation simulation with comparative analysis against a conventional equal torque distribution strategy, the results indicate that the proposed real-time energy-efficient control strategy exhibits superior performance across all evaluation metrics, providing valuable technical guidance for future research on energy-efficient control strategies in agricultural electric vehicles. Full article

Friction behaviour at the wheel–rail interface is of critical importance for railway operations and maintenance and is generally characterised by creep curves. The V-Track test rig was used in this study to measure both the lateral and longitudinal creep curves with uncontaminated dry interface conditions, utilising contact pressures representative of operational railway wheel–rail systems. The novelties of this study are threefold. 1. With proper representations of train/track components, the V-Track tests revealed the effects of structural dynamics on measuring wheel–rail creep curves in real life. 2. Pure lateral and longitudinal creepage conditions were produced with two distinct experimental principles—displacement- and force-controlled—on the V-Track, i.e., by carefully controlling the angle of attack and the traction/braking torque, respectively, and thus the coefficient of friction from lateral and longitudinal creep curves measured on the same platform could be cross-checked. 3. The uncertainties in the measured creep curves were analysed, which was rarely addressed in previous studies on creep curve measurements. In addition, the measured creep curves were compared against the theoretical creep curves obtained from Kalker’s CONTACT. The influence of wheel rolling speed and torque direction on the creep curve characteristics was then investigated. The measurement results and findings demonstrate the reliability of the V-Track to measure wheel–rail creep curves and study the wheel–rail frictional rolling contact. Full article

To improve the traction performance of mobile mechanisms on soft ground, such as paddy fields, tidal flats, and swamps, a mallard (Anas platyrhynchos) foot was adopted as a bionic prototype to explore the influence and contribution of the plantar morphology of the toes and webbing on the anti-subsidence function during its locomotion on wet and soft substrates and to apply this to the bionic design of high-traction wheel grousers. A handheld three-dimensional laser scanner was used to scan the main locomotion postures of a mallard foot during ground contact, and the Geomagic Studio software was utilized to repair the scanned model. As a result, the main three-dimensional geometric models of a mallard foot during the process of touching the ground were obtained. The plantar morphology of a mallard foot was divided into three typical parts: the plantar irregular edge curve, the lateral webbing surface, and the medial webbing surface. The main morphological feature curves/surfaces were extracted through computer-aided design software for the fitting and construction of a mathematical model to obtain the fitting equations of the three typical parts, and the mathematical model construction of the plantar irregular morphology of the mallard foot was completed. In order to verify the sand-fixing and flow-limiting characteristics of this morphological feature, based on the discrete element method (DEM), the numerical simulation of the interaction between the plantar surface of the mallard foot and sand particles was carried out. The simulation results show that during the process of the mallard foot penetration into the loose medium, the lateral and medial webbing surfaces cause the particles under the foot to mainly move downward, effectively preventing the particles from spreading around and significantly enhancing the solidification effect of the particles under the sole. Based on the principle and technology of engineering bionics, the plantar morphology and movement attitude characteristics of the mallard were extracted, and the characteristics of concave middle and edge bulge were applied to the wheel grouser design of paddy field wheels. Two types of bionic wheel grousers with different curved surfaces were designed and compared with the traditional wheel grousers of the paddy field wheel. Through pressure-bearing simulation and experiments, the resistance of different wheel grousers during the process of penetrating into sand particles was compared, and the macro–micro behaviors of particle disturbance during the pressure-bearing process were analyzed. The results show that a bionic wheel grouser with unique curved surfaces can well encapsulate sand particles at the bottom of the wheel grouser, and it also has a greater penetration resistance, which plays a crucial role in improving the traction performance of the paddy field wheel and reducing the disturbance to the surrounding sand particles. This paper realizes the transformation from the biological model to the mathematical model of the plantar morphology of the mallard foot and applies it to the bionic design of the wheel grousers of the paddy field wheels, providing a new solution for improving the traction performance of mobile mechanisms on soft ground. Full article

Autonomous navigation in mining environments is challenged by complex wheel–terrain interaction, traction losses caused by slip dynamics, and sensor limitations. This paper investigates the effectiveness of Deep Reinforcement Learning (DRL) techniques for the trajectory tracking control of skid-steer mobile robots operating under terra-mechanical constraints. Four state-of-the-art DRL algorithms, i.e., Proximal Policy Optimization (PPO), Deep Deterministic Policy Gradient (DDPG), Twin Delayed DDPG (TD3), and Soft Actor–Critic (SAC), are selected to evaluate their ability to generate stable and adaptive control policies under varying environmental conditions. To address the inherent partial observability in real-world navigation, this study presents an original approach that integrates Long Short-Term Memory (LSTM) networks into DRL-based controllers. This allows control agents to retain and leverage temporal dependencies to infer unobservable system states. The developed agents were trained and tested in simulations and then assessed in field experiments under uneven terrain and dynamic model parameter changes that lead to traction losses in mining environments, targeting various trajectory tracking tasks, including lemniscate and squared-type reference trajectories. This contribution strengthens the robustness and adaptability of DRL agents by enabling better generalization of learned policies compared with their baseline counterparts, while also significantly improving trajectory tracking performance. In particular, LSTM-based controllers achieved reductions in tracking errors of 10%, 74%, 21%, and 37% for DDPG-LSTM, PPO-LSTM, TD3-LSTM, and SAC-LSTM, respectively, compared with their non-recurrent counterparts. Furthermore, DDPG-LSTM and TD3-LSTM reduced their control effort through the total variation in control input by 15% and 20% compared with their respective baseline controllers, respectively. Findings from this work provide valuable insights into the role of memory-augmented reinforcement learning for robust motion control in unstructured and high-uncertainty environments. Full article

Modern powertrain configurations for electric vehicles introduce the possibility to actuate the wheel directly by means of in-wheel motors. These machines enable stiffer and more efficient traction, with the possibility of introducing pitch motion control due to the intrinsic coupling between longitudinal, vertical, and pitch dynamics. This paper proposes a pitch rate attenuation control exploiting a Lyapunov function that attempts to cancel the pitch rate dynamics from the model. Unlike previous works, this pitch control is performed exclusively with the traction machine; it does not rely on controllable suspension systems. The controller formulation guarantees global stability of the vehicle. Furthermore, it considers the nonlinearity of the plant introduced by the dependency on the pitch angle. To facilitate the feedback of the road profile needed by the Lyapunov controller, two Kalman filters are included in the control law. This work implements the described strategy on a half car model. Simulations examine different speed and road conditions. It is demonstrated that the control strategy can blend longitudinal and pitch rate attenuation torque commands using a rear in-wheel motor, attaining a reduction of up to $41\%$ for chassis pitch rate and $36\%$ for pitch acceleration. Full article

Increasing developments in the offshore energy sector have led to demand for robotics use in inspection, maintenance, and repair maintenance tasks, particularly for the service life extension of structures. These robots experience slippage due to varying surface conditions caused by environmental factors and marine growth, leading to inconsistent traction forces and potential mission failures in single-drive systems. This paper explores control strategies and mechanical configurations both in simulation and on the physical industrial robot to mitigate slippage in offshore robotic operations, improving reliability and reducing costs. This study examines mechanical and control modifications such as multi-wheel drive (MWD), PID velocity control, and a feedback-linearized slip control system with an individual wheel disturbance observer to detect surface variations. The results indicate that a 3 WD setup with slip control handles the widest range of conditions but suffers from high control effort due to chattering effects. The simulations show potential for slip control; practically, challenges arise from low sampling rates compared to traction changes. In real-world conditions, a PID-controlled MWD system, combined with increased normal force, achieves better traction and stability. The findings highlight the need for further investigation into the mechanical design and sensor feedback, with the refinement of slip control strategies and observer design for the offshore environment. Full article

Open-pit mining involves the use of vehicles with high load capacity and satisfactory mobility. As experience shows, these requirements are fully met by pneumatic wheeled dump trucks, the traction drives of which can be made using thermal or electric machines. The latter are preferable due to their environmental friendliness. Unlike dump trucks with thermal engines, which require fuel to be injected into them, electric trucks can be powered by various options of a power supply: centralized, autonomous, and combined. This paper highlights the advantages and disadvantages of different power supply systems depending on their schematic solutions and the quarry parameters for all the variants of the power supply of the dumper. Each quantitative indicator of each factor was changed under conditions consistent with the others. The steepness of the road elevation in the quarry and its length were the factors under study. The studies conducted show that the energy consumption for dump truck movement for all variants of a power supply practically does not change. Another group of factors consisted of electric energy sources, which were accumulator batteries and double electric layer capacitors. The analysis of energy efficiency and the regenerative braking system reveals low efficiency of regeneration when lifting the load from the quarry. In the process of lifting from the lower horizons of the quarry to the dump and back, kinetic energy is converted into heat, reducing the efficiency of regeneration considering the technological cycle of works. Taking these circumstances into account, removing the regenerative braking systems of open-pit electric dump trucks hauling soil or solid minerals from an open pit upwards seems to be economically feasible. Eliminating the regenerative braking system will simplify the design, reduce the cost of a dump truck, and free up usable volume effectively utilized to increase the capacity of the battery packs, allowing for longer run times without recharging and improving overall system efficiency. The problem of considering the length of the path for energy consumption per given gradient of the motion profile was solved. Full article

In order to explore the influence of wheel surface structure on the trafficability of planetary rovers on soft ground, three kinds of wheels with different rigid wheel surface structures were selected for research. The basic performance parameters of the wheel on simulated planetary soil are measured and tested to explore the law of the wheel’s sinkage, slip rate and traction coefficient. The results show that the wheel grouser increases the sinkage and slip rate of the wheel. The tread reduces the sinkage of the wheel, but it also reduces the traction performance of the wheel at a higher slip rate. Considering the complex working conditions of the planetary rover on the soft ground, the six-wheeled three-rocker-arm planetary rover is used to carry out passability tests in three terrains: obstacle crossing, out of sinkage and climbing. The results show that the grousers can cause disturbance and damage to the soft soil and have significant passing advantages. There may also be a slip phenomenon when crossing the obstacle, but it does not affect passing. The completely closed tread structure will cause soil accumulation between the tread and the grouser, affecting the wheel’s ability to escape sinkage. This study provides a reference for the design of a rigid wheel surface structure for planetary rovers from the perspective of passing performance. Full article

This paper addresses the issue of wheelset slip in trains caused by low-adhesion track surfaces and proposes an active anti-slip tracking control strategy. Considering the wide operational range of trains and the complex adhesion conditions between wheels and rails, a comprehensive model of the train, incorporating adhesion effects, is developed and then transformed into a mathematical model with perturbations. To tackle the slip phenomenon on low-adhesion track surfaces, a robust adhesion observer with high dynamic accuracy is designed. Building on this, an active anti-slip strategy is proposed to ensure that the control command does not exceed the maximum traction force available from the track surface. To further enhance controller performance, higher-order sliding mode control is integrated with a saturation compensation law. Finally, a Hardware-in-the-Loop (HIL) platform is constructed using a Digital Signal Processor (DSP) controller and a Modular Test (MT) PXI real-time simulator. The simulator loads the adhesion model, while the DSP controller executes the designed anti-slip control algorithm. Experimental results demonstrate that the proposed controller effectively prevents wheelset slip under low-adhesion conditions and significantly reduces tracking errors along the target speed-displacement curve. Full article

Tires are important for the transmission of forces, good traction of the vehicle, and safety of the passengers. Tires also influence vehicle fuel consumption and cause tire and road wear pollution to the environment in the form of microplastics. In the United States, the Uniform Tire Quality Grading (UTQG) for tread wear is reported on the tire sidewall and is used as an indicator of the expected service life of a tire. In Europe, a similar approach that applies tread depth reduction measurements and projection to the minimum tread depth is under discussion. Tread depth measurements will be carried out in parallel with abrasion measurements over the recently introduced abrasion rate test in the United Nations regulation 117. Testing is carried out with an on-road convoy method accompanied by a vehicle fitted with reference tires to minimize the influence of external parameters. In this brief review, we start with a short historical overview of the methods that have been applied so far for the measurement of tire service life. Based on the limited publicly available data, we calculate the average tread depth reduction per distance driven for summer and winter tires fitted both in the front and rear axles of passenger cars (1–1.2 mm for front wheels and 0.5–0.6 mm for rear wheels per 10,000 km). We theoretically estimate the tread mass loss per mm of tread depth reduction (250 g per 1 mm tread depth reduction, depending on the tire size) and we compare the values to experimental data obtained in recent campaigns. We give estimations of the tire service life as a function of the tread wear UTQG (100 times the indicated tread wear rating). We also discuss the projected service life using tread depth reduction and mass loss. Full article

Traction motors in electric transport are most often synchronous permanent magnet motors (PMSMs). Induction motors (IMs) have large dimensions and stator current amplitudes under comparable loads. Traditional IM control methods do not solve these problems. Recent studies have shown that by changing the main magnetic flux in the IM in accordance with the load, these characteristics of the asynchronous electric drive can be significantly improved. Standard frequency converters do not allow for the implementation of these algorithms. But it makes sense to conduct a potential assessment of the capabilities of this algorithm to reduce the total stator currents of traction IMs. This article analyzes the results of real tests of a special vehicle for transporting rock inside mines, conducted several years ago at a mining equipment plant and in several mines in Russia. The prototype of the special transport vehicle has a load capacity of 15 tons, and its traction electric drive is based on four motor wheels with a total power of 100 kW and a frequency converter from the company “Vacon” (Vaasa, Finland). The tests were conducted at the plant’s testing ground and in real mine conditions. These tests allowed us to obtain information about the operation of the asynchronous electric drive under dynamically changing loads in a wide range, which is very difficult to obtain on laboratory benches or in industrial enterprise conditions. The experiments confirmed the efficiency of the optimization algorithm for asynchronous electric drives with frequency control. At the same time, the weight, size, and electrical parameters of the drive are as close as possible to those of direct current drives. Full article

Gearboxes used in electric locomotives are a critical unit, especially in freight rolling stock. The article presents the calculation of the main parameters of the two-way oblique traction transmission of the VL-80s electric locomotive (which is operated on the railways of Uzbekistan) based on a comprehensive analysis of the diagnostic parameters obtained using the Poisson normal distribution method for the identified failures according to the Uzbekistan depot data. Also, a Pareto diagram was constructed for the chassis of 3VL-80s electric locomotives based on the data of the Locomotive Operation Department of JSC Uzbekistan Temir Yollari, and probabilistic and statistical analyses of the failures and breakdowns of the wheel pair and the large gear wheel of the traction gearbox of the VL-80s electric locomotives were carried out. An algorithm and methodology for assessing the reliability of the large gear wheel of the traction gearbox of an electric locomotive are presented. As a result of a numerical calculation of the coefficients of the empirical regression equations using approximation and spline interpolation methods, a regression equation was obtained for the dependence of the standard deviation of the wear of the tooth of the large gear wheel of the traction reducer of the VL80s electric locomotive on the mileage. Full article