Wheel Velocity Research Articles

A bottom-up numerical model for wheel-rail contact to predict rail-way noise emission

Pass-by noise emission models are often based on measurement databases, yielding engineering models that are fast enough to calculate noise maps or to do predictions based on existing infrastructure. However, these cannot predict the effect of innovative components, either in the track or in the rolling stock. Changing properties of a single component, e.g. damping of rail pads or the profile of a wheel, leads to a chain of coupled effects including the dynamics of the individual component, the contact force, the vibrational velocity, and finally the emitted noise. These intricate interactions can only be captured by detailed numerical models. We present a step-by-step implementation that allows to predict the effect of changes on the component level on the pass-by noise emission. The model includes the finite element calculation of the mobility of track and wheel separately, and uses these to derive the contact force from the combined roughness and train speed. Next, the vibration velocities of rails, sleepers, and wheels are used as input for a boundary element calculation of the noise emission. Pass-by measurement results validate the models, and show good agreement if wheel-rail contact noise is dominant and secondary sources can be ignored.

An Enhanced GNSS/MINS Integrated Navigation System With a Wheel Velocity Predictor Based on Vehicle Dynamics Model

An Enhanced GNSS/MINS Integrated Navigation System With a Wheel Velocity Predictor Based on Vehicle Dynamics Model

Multiple Observer Adaptive Fusion for Uncertainty Estimation and Its Application to Wheel Velocity Systems.

Uncertainty estimation in real-world scenarios is challenged by complexities arising from peaking phenomena and measurement noises. This article introduces a novel scheme for practical uncertainty estimation to mitigate peaking dynamics and enhance overall dynamic behavior. A fusion estimation framework for lumped uncertainties using multiple extended state observers (ESOs) is constructed, and the low-frequency adaptive parameter learning technique is employed to approximate the optimal fusion. The adaptive fusion estimation not only attenuates transient peaks in uncertainty estimation but also attains fast convergence and high accuracy under the high-gain scheduling of ESOs. Furthermore, the robustness of uncertainty estimation against measurement noises is enhanced by cascading filters in the proposed adaptive fusion framework for multiple ESOs. Extensive theoretical analyses are executed to verify practical applicability in peak and noise rejection. Finally, simulations and experiments on the wheel velocity system of a mobile robot are conducted to test the validity and feasibility.

Optimal Synthesis of a Satellite Attitude Control System under Constraints on Control Torques and Velocities of Reaction Wheels

The problem of optimal synthesis of a nonlinear system’s control law parameters of satellite attitude control under constraints is considered. The maximum stability degree of a system is considered as an optimality criterion. The reaction wheels’ control moments and angular velocities achievable within the drives’ physical characteristics are considered as constraints. A linear model of the system converted from the original nonlinear model was used to solve the problem. The decomposition method, based on the transition from real time to relative time, is used to separate the tasks of optimality criterion maximization and constraints consideration. A method of synthesizing the optimal form of system transient process according to the maximum stability degree criterion is developed. An analytical method for determining the optimal values of control law parameters is proposed, based on the structural features of the linear differential equations system. A method that takes into account constraints on control moments and angular velocities of reaction wheels, based on transition scale from relative time to real time and its calculation algorithm, ensuring that conditions of all constraints are met, is developed. An example of solving the problem of optimal system synthesis is considered. The results demonstrate the effectiveness and simplicity of the proposed methods and algorithm for targeted selection of a system’s technical characteristics, taking into account constraints on reaction wheels’ maximum angular velocities and control moments values.

Modeling of Car-to-motorcycle Overtaking Maneuver Based on Comfort Zone Boundaries

Thailand has one of the world's highest road fatality rates, mainly on motorcycles. In mixed traffic, motorcycles coexist with other vehicles. The interaction between cars and motorcycles, such as overtaking due to speed differences, can lead to accidents. This scenario also has implications for autonomous vehicles interacting with motorcycles. To increase safety in such interactions, a model was developed that simulates overtaking maneuvers of car drivers with motorcycles, using the concept of comfort zone boundary and a four-phase classification. In a driving simulator, 648 overtaking maneuvers collected from 36 Thai drivers were recorded with different lateral positions and speeds of the motorcycles. A novel graphical method using steering wheel angle and steering wheel velocity signals facilitated the identification of the phases. Time-to-collision and lateral distance characterized driver comfort zones and served as an indicator for safety measures. The lateral position of the motorcycle has proven to be the most influential factor in the model. The results suggest that overtaking vehicles exhibit non-lane-bound driving characteristics and a risk for the sideswipe accident is identified. These results provide a foundational framework for advanced driver assistance systems and motion planning of autonomous vehicles, contributing to improved road safety.

Study on the grinding surface quality of CNTs/2009AL composite material based on minimum quantity lubrication

Carbon nanotube aluminum matrix (CNTs/AL) composites are ideal lightweight and high-strength materials due to their excellent properties. However, the research on CNTs/AL composites only stays in the simulation and preparation stages, and no grinding research has been carried out. Revealing the grinding mechanism of CNTs/AL composites has far-reaching significance for the development of high-end equipment industries such as aerospace. Taking CNTs/2009AL composites as the research object, a minimum quantity lubrication (MQL) flat grinding platform was built for comparing the surface quality and defects of dry grinding and MQL grinding. The experimental results show that grinding wheel velocity was the grinding parameter that had the greatest influence on surface roughness in dry grinding and MQL grinding. The subsurface defects of dry grinding mainly included microcracks, burrs, pits, coatings, cavities, etc., and the rebound phenomenon of agglomerated carbon nanotubes. The subsurface defects of MQL grinding were only burrs and pits. The surface coating phenomenon of dry grinding increased with the increase in grinding wheel velocity, and the surface quality was improved. MQL grinding could significantly reduce grinding heat, reduce friction, and make the machined surface smoother. In dry grinding and MQL grinding, the subsurface damage depth decreased obviously with the increase in grinding wheel velocity. When the grinding wheel velocity was 30 m/s, the minimum subsurface damage depth of dry grinding and MQL grinding was 40.091 and 26.906 μm, respectively. Mastering the grinding mechanism of grinding CNTs/AL composites and the influence of grinding parameters on surface quality provides a basis for the selection of parameters and methods in grinding in industry. MQL grinding of CNTs/AL composites reduces the formation of many surface defects and improves the surface quality of the workpiece. It is an efficient, clean, and environmentally friendly processing method.

IT-2 Fuzzy Control and Behavioral Approach Navigation System for Holonomic 4WD/4WS Agricultural Robot

In contemporary agriculture, researchers are focusing on precision farming and environmentally conscious techniques, leading to the advancement of autonomous agricultural mobile robots. Consequently, A navigation system using TSK Interval Type-2 fuzzy logic has been developed and, for the first time, applied to a holonomic mobile agricultural robot equipped with four-wheel drive and steer. This system employs a behavioral approach to accomplish the robot’s primary objective in unfamiliar environments. It comprises four controllers: one exclusively dedicated to goal-seeking behavior, with the remaining controllers responsible for obstacle avoidance. Supervision of these controllers is conducted through the Mandani fuzzy logic approach, which combines the outputs of all four controllers, robot wheel velocities and steering angles, using a proposed equations. Various case studies were examined and simulated utilizing MATLAB and VREP software platform to assess the navigator system’s performance. The simulation outcomes showcase the efficiency of the proposed equations and the system’s navigation capabilities. The stability of the entire system was thoroughly examined and confirmed, employing the Lyapunov function, in environments with and without obstacles.

The Effects of Si Substitution with C on the Amorphous Forming Ability, Thermal Stability, and Magnetic Properties of an FeSiBPC Amorphous Alloy

The industrialization of Fe-based amorphous alloys with high a saturation magnetic flux density (Bs) has been limited so far due to their inadequate amorphous forming ability (AFA). In this study, the effects of substituting Si with C on the AFA, thermal stability, and magnetic properties of Fe82Si6−xB9P3Cx (x = 0–6) alloys were systematically investigated. The experimental results demonstrate that the AFA, thermal stability, and soft magnetic properties can be significantly enhanced by the addition of C. Specifically, at a copper wheel velocity of 40 m/s, the Fe82Si6−xB9P3Cx (x = 2, 3, 4, 5 and 6) alloy ribbons exhibit a fully amorphous structure in the as-spun state. The activation energy required for the α-Fe phase crystallization process in Fe82Si6−xB9P3Cx (x = 0, 2, 4, and 6) alloys is determined to be 326.74, 390.69, 441.06, and 183.87 kJ/mol, respectively. Among all of the compositions studied, the Fe82Si4B9P3C2 alloy exhibits optimized soft magnetic properties, including a low coercivity (Hc) of 1.7 A/m, a high effective permeability (μe) of 10608 (f = 1 kHz), and a relatively high Bs of 1.61 T. These improvements may be attributed to a more homogeneous and optimized magnetic domain structure being achieved through proper C addition. This work holds significant implications for the advancement of Fe-based soft magnetic amorphous alloys with high Bs.

Experimental Evaluation of Effect of Leaves on Railroad Tracks in Loss of Braking

This study aims to comprehensively assess the lubrication effect of leaves on wheel–rail contact dynamics using the Virginia Tech-Federal Railroad Administration (VT-FRA) Roller Rig, which closely simulates field conditions with precision and repeatability. Railway operators grapple with the seasonally recurring challenge of leaf contamination, which can cause partial loss of braking and lead to undesired events such as station overruns. Better understanding the adhesion-reducing impact of leaf contamination significantly improves railway engineering practices to counter their effects on train braking and traction. This experimental study evaluates the reduction in traction and braking forces (collectively called “adhesion”) as a function of leaf volume, using two leaf species that commonly grow along U.S. railroad tracks. The test methods rely on the chosen leaves’ transpiration characteristics while ensuring the result’s reproducibility. Leaves were symmetrically positioned on the wheel surface, centered around the mid-rib area within the wear band, and taped on the edges far from the wear band. The critical test parameters (i.e., wheel load, wheel velocity, and percentage creepage) are kept constant among the tests. At the same time, leaf volume is reduced from a maximum amount that covers the entire wheel surface (100% coverage) to no leaves (0%). The latter is used as the baseline. The percentage creepage is kept constant at an exaggerated amount of 2% to accelerate the test time. The results indicate a nonlinear relationship between leaf volume and the loss of braking. Even a small amount of leaf contamination causes a significant reduction in adhesion by as much as 50% compared with no contamination (i.e., baseline). Increasing leaf volume results in contact saturation, beyond which adhesion is not reduced. The minimum adhesion observed in this study is 20% of the maximum adhesion that occurs when no leaf contamination is present.

Modeling the braking process for motorcycle with ABS

The project introduces the braking system for motorcycle with ABS and simulation the braking process using the Tire Hardware-In-The- Loop Simulator (Tire HILS). The ABS system includes electronic and hydraulic control units and wheel velocity sensors. The original pre-extreme algorithm is used to ABS control. The mathematical description of the pre-extreme control method is presented. Mathematical model has been developed for this method of anti-lock braking system operation during curvilinear motorcycle driving. This model was developed considering the possibility of obtaining the necessary data for the operation of the ABS without developing a new sensors base.

Wheel Velocity Based Cascade Driving Force Control for Electric Vehicles

Wheel Velocity Based Cascade Driving Force Control for Electric Vehicles

Deep Neural Network Model for Determination of Coal Cutting Resistance and Performance of Bucket-Wheel Excavator Based on the Environmental Properties and Excavation Parameters

In the present paper, we develop a new model, based on the implementation of deep neural networks, for the estimation of a series of excavation parameters, depending on the main environmental and excavation properties. The developed model, with high statistical accuracy (R > 0.79) and small RMSE (<17% of the actual output values), enables the simultaneous assessment of the following excavation parameters: effective capacity Qef, maximum current consumption Imax, maximum power consumption Nmax, maximum force consumption Pmax, maximum energy consumption Emax, and maximum linear and areal cutting resistance, KLmax and KFmax, respectively, based on the impact of the following environmental properties and excavation parameters: coal unit weight, coal compression strength, coal cohesion, friction angle, excavator movement angle in the left and right direction, slice height and thickness, and wheel velocity. The data analyzed in the present paper were previously collected from three neighboring open-pit coal mines in Serbia: Tamnava Western Field, Tamnava Eastern Field, and Field D. These mines have similar geological conditions and coal properties. Additionally, for each output factor, a complex analysis is provided on the impact of the examined input factors, by applying the multiple linear regression method. As far as we are aware, this is the first time such a comprehensive estimation model has been suggested for the operation of a bucket-wheel excavator in the Neogene coal basins. The deep neural network (DNN) model, trained over 300 epochs, shows an MSE range of 6.7–16.5% across various input factors, with distinct evaluations for Imax due to its unique values (4.8–12.5%).

Circumstances of falls among older adult walker users in long-term care and the associated walker design deficits

ABSTRACT Falls are the leading cause of fatal and non-fatal injuries in older adults. Walkers are often used by and prescribed to this population to reduce fall risk, however, walker users and walker non-users alike experience similar fall incidence rates. The role of walkers in preventing falls is unclear as some studies suggest walkers may be a fall-inciting factor. The purpose of this study was to analyze walker deficits by evaluating the circumstances and causes of falls in older adult walker users residing in long-term care facilities. Videos capturing 34 real-life falls involving wheeled walkers (rollators and two-wheeled walkers) in two retirement facilities were analyzed for 3 themes: walker type, fall direction, and activity at the time of fall. A frequency analysis of these themes was performed to determine common fall mechanisms. The results of this study suggest two-wheeled walker and rollator users most often fall sideways while turning and backward during weight transfer, respectively. Poor maneuverability, lateral stability, and wheel velocity control of the walkers contributed to the falls. Device improvements addressing these areas of deficiency may be necessary to mitigate falls occurring in older adult walker users.

AI-ACCIDENT DETECTION SYSTEM FOR FAST RESCUE ON FREEWAYS USING ON-BOARD CAR MOTION SENSORS FUSION

Continuous tracking and detecting position systems are significant services that can using in many applications such as detecting accident cars on Freeways. This paper introduces Artificial intelligent (AI) method to quick discover the accident and determine the position of car on Freeways that will reduce the rate of fatalities. Most tracking and detecting position systems are based on Global Navigation Satellite System (GNSS). But the GNSS signal in certain areas such as buildings and tunnel is unavailable which make a big problem for these systems. To solve this problem, most traditional methods are based on integrated GNSS with other navigation sensors such as accelerometers, gyroscopes, odometers and so on. But these integrated methods still high cost and need to long time processing. Today, most modern Vehicles are equipping with several On-board Car Motion Sensors (OVMS) such as Acceleration Sensors (AS), Wheel Velocity Sensor (WVS), Gravity Sensor (GS), Yaw Rate Sensor (YRS) and additional to GNSS that can improve the safety and also use to determine and detect the position of accident vehicle. This paper develops an approach AI-accident detection system based on integrating GNSS with On-board Vehicle Motion Sensors (OVMS) using Extended Kalman Filter (EKF) algorithm. During GPS outages, the three Acceleration Sensors (3-ASs) are processing to determine velocities and then position of vehicle on three x, y and z axes. While the YRS and GS sensors are using to determine velocities angles on three x, y and z axes, respectively. In same time the three WVS sensors are using to correct velocities errors of three acceleration sensors (3-ASs) until GNSS signal is return again. The proposed AI-accident detection system is tested in different scenarios during GPS outage signal. The results of proposed method can actually detect accident and determine the position of vehicle with high efficiency.

Roles of solidification rate and Co substitution for Cr on single phase ordered Fe2CrSi alloy formation

A comprehensive experimental and theoretical study on the structural, electronic, and magnetic properties of bulk Co-substituted Fe2CrSi Heusler alloys has been carried out. The impact of rapid solidification on the formation of phase pure Fe2CrSi alloy has also been explored. Bulk Fe2Cr1-xCoxSi (where x = 0, 0.1, 0.2, 0.3, and 0.5) alloy samples were prepared using arc melting, and melt-spinning was employed to prepare Fe2CrSi ribbons at two different wheel velocities (20 and 30 ms−1). Our investigation revealed that the Fe2CrSi Heusler alloys with a Co substitution in the range of 0.2 ≤ x ≤ 0.5 exhibited a single L21 phase structure. However, for x = 0 and 0.1, there were 27 % and 11 % A15 impurity phases, respectively, coexisting with the L21 phase. On the other hand, the sample melt-spun at 20 ms−1 contained only 7 % impurity phase, while the one melt-spun at 30 ms−1 was free of any impurity phase. First principles calculations using the GGA + U approach showed that the single phase ribbon sample exhibited 12.5 % DO3 type disorder, indicating a change in site preference resulting from a high solidification rate. All the experimental and calculated magnetic moments of the alloys were in agreement with the Slater-Pauling rule. Our results suggest that the Fe2Cr0.75Co0.25Si alloy is a promising candidate for spintronic device applications due to its half-metallic nature.

Analysis of soil compaction under different wheel applications using a dynamical cone penetrometer

Soil compaction is one of the major problems in modern agriculture. Thus, the workability of a soil reflects to its ability to accept the traffic of agricultural machinery and implements. Water content and compaction are factors that influence the rheological behavior of the soil. the representation of soil shows limitations regarding the behavior of the tire-soil interface and its resistance to deformation is both influenced by the different forms of loading application along a tire path on a soil particle. This paper presents a study of the impact of multiple wheel passage, the wheel velocity, and the weight applied to the wheel on the agricultural soil represented by the cone index. To do this, we were inspired to launch an investigation for soil compaction determination at three levels of wheel load, three levels of velocity and at tillage, first, second and third passages of wheel with three replications on clayey sandy mixed grain soil. The results of this study shows that the greatest soil compaction occurred at the highest wheel load (1000 N), the lowest speed (0.1 m/s) and the highest number of passes (third pass), this leads to minimize multiple passes and or follow the same path, also, keeping the load on the ground as low as possible (weight of the machines), and working at high speed in agricultural fields.

Soft Magnetic Properties and Electromagnetic Shielding Performance of Fe40Ni40B20 Microfibers

AbstractFe40Ni40B20 metallic glass is a key material among the many amorphous systems investigated thus far, owing to its high strength and appealing soft magnetic properties that make it suitable for use as transformer cores. In this study, Fe40Ni40B20 microfibers are fabricated down to 5 µm diameter. Three different melt–spinning wheel velocities: ≈51 m s−1, ≈59 m s−1, and ≈63 m s−1 (MG1, MG2, MG3) are used. Their fully amorphous structure is confirmed using X–ray diffraction, and differential scanning calorimetry (DSC) traces reveal a larger relaxation profile for the higher–quenched microfiber. Vibrating sample magnetometer measurements showed a higher saturation magnetization of 136 emug−1 for annealed metallic glass microfibers with a wheel velocity of 59.66 ms−1. Cylindrical magnetic field shields are obtained by aligning and wrapping the fibers around a cast. The observed anisotropic static field shielding behavior is in accordance with the microfibers' anisotropic nature. Composite samples are also produced by embedding the microfibers in an epoxy matrix to investigate their electromagnetic properties at GHz frequencies. Inclusion of the microfibers increase the composite's attenuation constant by 20 to 25 times, making it an ideal candidate for applications in the communications frequency range.

Modelling of washboard effect on unpaved roads experimental evidence on non-cohesive materials

Washboard or corrugation is a common phenomenon in unpaved roads. The washboard effect can be very uncomfortable for the driver, but it can also be very dangerous due to the loss of contact between the wheels and the road. There are few pieces of research about this topic, but undulations seem to emerge due to the caŕs velocity and mass. This work aims to identify the main physical variables controlling the appearance of the washboard effect. For this purpose, an experimental set-up of a multi-pass system was developed. This apparatus consists of a rotating wheel rolling over a sandy path. This model allows evaluation of the evolution of the undulations resulting from the washboard phenomenon and allows relating it to variables such as the dynamic forces and track profile. Different scenarios were evaluated, including wheel velocity, wheel mass, and soil density.

Unilateral frictional contact between a rigid wheel traversing on a flexible beam: An analytical investigation

This paper proposes a non-linear dynamic solver to simulate the dynamics of a rigid wheel traversing over a flexible beam involving a unilateral contact at the interface. Euler’s discretization scheme is extended incorporating Linear Complementary approach to perform explicit integration over time domain. The proposed solver is analytically designed to incorporate frictional force acting at the wheel-beam interface along with the possibility of generation of normal gap between the two bodies. Moreover, rotation of the wheel is also appended in the proposed algorithm and change in contact point between the wheel and beam is evaluated at every time step. After validation with existing literature, the solver is applied to study various dynamic responses of wheel and beam. Further, the technique is applied to moving oscillator model traversing over a flexible beam. The effect of initial wheel velocity, coefficient of friction, frequency of the oscillator on overall dynamic response of beam and wheel have been thoroughly investigated. The proposed algorithm delivers an exact solution based on the system’s fundamental mechanics, thus reducing the mesh reliance which amounts to high computational cost in finite element solver. The suggested method provides a broad future potential for solving rigid-flexible contact multibody dynamic problems.

Speed Control of Wheeled Mobile Robot by Nature-Inspired Social Spider Algorithm-Based PID Controller

Mobile robot is an automatic vehicle with wheels that can be moved automatically from one place to another. A motor is built in its wheels for mobility purposes, which is controlled using a controller. DC motor speed is controlled by the proportional integral derivative (PID) controller. Kinematic modeling is used in our work to understand the mechanical behavior of robots for designing the appropriate mobile robots. Right and left wheel velocity and direction are calculated by using the kinematic modeling, and the kinematic modeling is given to the PID controller to gain the output. Motor speed is controlled by the PID low-level controller for the robot mobility; the speed controlling is done using the constant values Kd, Kp, and Ki which depend on the past, future, and present errors. For better control performance, the integral gain, differential gain, and proportional gain are adjusted by the PID controller. Robot speed may vary by changing the direction of the vehicle, so to avoid this the Social Spider Optimization (SSO) algorithm is used in PID controllers. PID controller parameter tuning is hard by using separate algorithms, so the parameters are tuned by the SSO algorithm which is a novel nature-inspired algorithm. The main goal of this paper is to demonstrate the effectiveness of the proposed approach in achieving precise speed control of the robot, particularly in the presence of disturbances and uncertainties.