Steering Wheel Research Articles

Development of Electro-Mechanical Actuator for Wheel Steering of Railway Vehicles

Development of Electro-Mechanical Actuator for Wheel Steering of Railway Vehicles

Comparative Research on Landing and Rollout Characteristics of Skid-Equipped and Wheeled Aircraft

Skid landing gear is a specialized landing device known for its compact structure and lightweight. However, current research on the dynamic characteristics of skid-equipped aircraft on concrete runways is limited, which raises uncertainties about its practical applications. To address this gap, a general aircraft model based on a modular concept is first constructed, considering the coupling effects of aerodynamic, buffer, and ground forces. On this basis, the differences in motion characteristics between skid-equipped and wheeled aircraft are compared in detail. Then, the impact of various factors on the landing characteristics of skid-equipped aircraft is analyzed, such as initial longitudinal velocity, pitching angle, and friction coefficient of skid. Simulation results show that the lack of buffering capability provided by tires results in a 10.57% increase in overload for skid-equipped aircraft and a 15.39% decrease in the efficiency of the main landing gear buffer. Notably, the initial pitching angle has a critical impact on the landing overload of skid-equipped aircraft. Due to the significant differences in the mechanical properties of the landing gears, the skid-equipped aircraft without nose wheel steering ability is a statically unstable system during the rollout phase. The intervention of asymmetric disturbances would pose a serious threat to the rollout safety.

СОГЛАСОВАНИЕ ГЕОМЕТРИЧЕСКИХ ХАРАКТЕРИСТИК ФАКТИЧЕСКОГО ПОВОРОТА КОЛЁСНОЙ МАШИНЫ

Based on the above calculation scheme of controlled curvilinear motion of a wheeled vehicle, it was revealed that the steering trapezoid causes some discrepancy between the kinematics of real and correct rotation. It is established that when adjusting the track width of the machine, the kinematic mismatch between the optimal rolling conditions of the wheels increases, and, consequently, the calculated dependences of the parameters of the ideal turn will not give a satisfactory result when analyzing the actual turn. The minimum theoretical turning radius is taken as an estimated indicator of the turnability of a wheeled vehicle. The conclusion of a multifunctional analytical dependence for determining the theoretical minimum turning radius of a wheeled vehicle, the wheels of which are controlled by a steering trapezoid, is presented. The resulting formula includes the longitudinal base of the machine, the pin track, the angles of rotation of the inner and outer steerable wheels. A comparison of the calculation results according to the developed and known formulas is given, which confirmed the complete convergence. It was found that, for example, an increase in the pivot track of the machine by 0.2 m leads to an increase in the theoretical minimum radius of the actual turn by 16.5%, and the distance from the continuation of the rear axle to the instantaneous center of rotation by 45.07...98.02% when the angle of rotation of the inner steering wheel changes from 20° to 40°.

The impact of camera-monitor system viewing angles on drivers’ distance perception: A simulated driving study

Camera-monitor systems (CMS) are increasingly used in driving. CMS separates the driver's sight line from the camera view, due to the lack of mirror reflection, only changing the camera's visual axis angle may affect the driver's rear view perception. While previous research has explored camera height and field of view, the effects of horizontal and vertical viewing angles alone remain unclear. This study aimed to evaluate how the horizontal viewing angle and vertical viewing angle of CMS camera affect distance estimation and car-following tasks. By changing the horizontal and vertical viewing angle, different self-vehicle references and horizon positions were formed in the image. Two experiments were conducted with the CMS around the steering wheel (Experiment 1) and at the bottom of the A-pillar (Experiment 2). Independent variables were the horizontal viewing angle (reference scale: 1/4, 1/3, 1/2) and vertical viewing angle (horizon position: 1/2, 1/3). Dependent variables included distance estimation error ratio and following distance. Experiment 1 demonstrated a significant interaction effect: a smaller reference scale and higher horizon position reduced distance underestimation. Additionally, a smaller reference scale for the participants' self-vehicle resulted in shorter following distances. In Experiment 2, the distance estimation outcomes on the left display aligned with those of Experiment 1; however, the influence of the viewing angle was diminished on the right display. The study suggests CMS design should balance vehicle reference inclusion with environmental cues, enhancing distance perception and driving safety. The consistency between CMS design and driver familiarity also needs to be considered.

Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology

Despite advancements in ergonomic comfort assessments in automotive design, optimizing seat dimensions within the constrained spaces of micro-electric cars presents a substantial challenge. In this study, response surface methodology (RSM) is utilized for the ergonomics design of a micro electric car in the conceptual design phase. Specifically, five critical seat dimensions are analyzed: Seatback Angle, Seat Base Angle, Steering Wheel Height from Car Base, Distance from Seat Base to Pedals, and Distance from Seat Base to Steering Wheel. The analysis took place using a 2-level full factorial design L32 orthogonal array. The optimal dimensions are determined using RSM, such as the mean comfort level and signal-to-noise ratio are maximized, and the standard deviation for multiple drivers is minimized. Three regression models are formulated for the three responses, and their adequacy is checked using different methods. The optimal dimensions are obtained and verified through digital human modeling simulation. This research offers practical guidelines for the ergonomic seating design in micro-electric vehicles, enhancing comfort without compromising space efficiency.

Artificial Intelligence (AI) and Workplace Communication: Promises, Perils, and Recommended Policy

Communication sits at the heart of any coordination within organization. Yet, what are the consequences when employes use Artificial Intelligence (AI) to copilot, i.e., support, their communication? While AI support in human interactions holds much promise for improving communication quality at work, it also fundamentally challenges how much people trust that communication. We, therefore, ask how organizations should introduce AI. In particular, we focus on the responsibility of leaders as stewards of workplace communication. Accordingly, we offer a set of specific hands-on recommendations on how employes should be guided to use AI copiloting effectively so that they do not give in to the temptation of letting go of the “steering wheel” (i.e., allowing AI to [auto]pilot intraorganizational communication).

The Effects of Adding TiO2 and CuO Nanoparticles to Fuel on Engine and Hand–Arm Driver Vibrations

Occupant comfort is a key consideration in automobile dynamics, with vibrations potentially causing long-term physical discomfort, especially for drivers. This study investigates the impact of adding TiO2 and CuO nanoparticles to fuel on engine-induced vibrations. Experiments were conducted at various nanoparticle concentrations (0, 50, 100, and 150 ppm) and engine speeds (1000, 2000, and 3000 rpm). Key performance metrics, including kinematic viscosity, density, heating value, thermal conductivity, and brake power (BP), were analyzed. The results indicated that increasing nanoparticle concentration led to a rise in BP. The highest reduction in root mean square (RMS) vibration accelerations occurred at 3000 rpm and 150 ppm, with vibration reductions of 30.33% for CuO and 28.61% for TiO2. Additionally, 8–10% of engine vibrations were transmitted to the steering wheel. The use of 150 ppm CuO nanoparticles resulted in reduced vibration transmission to the steering wheel at all tested speeds. These findings suggest that nanoparticle-enhanced fuels can significantly reduce engine vibrations, potentially improving driver comfort and reducing wear on vehicle components.

Development of a Mathematical Model of a Highly Maneuverable Robot for Simulation of Robots with Different Types of Designs

The article presents the results of developing a mathematical model and simulation modeling of a three-wheeled highly maneuverable mobile robot. A mathematical model of the robot in the state space has been developed. The possibility of using this robot with rotary modules for analyzing and testing control algorithms for robots of various designs has been considered. The relevance of the study is justified by the high costs of creating physical models of robots for experimental verification of control algorithms. The proposed three-wheeled mobile robot with rotary modules, where each wheel is simultaneously both a driving and a steering wheel, allows reducing these costs, while maintaining the ability to simulate part of the real operating conditions. Simplified diagrams of the robot are given, the main parameters and equations characterizing the change in linear and angular velocity are described. Particular attention is paid to modeling various types of robot drives: automotive type and with a differential drive. In the discrete state space, equations describing the dynamics of the robot were presented, which allows them to be used in software products for modeling. The results of simulation modeling obtained in the SimInTech software environment confirm the effectiveness of the proposed model. The analysis of the obtained results showed that the use of a three-wheeled robot with rotary modules allows successfully simulating the behavior of robots with other types of drives and creating conditions close to real ones for testing control algorithms. The proposed model can be used to improve the quality of design and testing of control algorithms in robotics, while reducing the costs of creating physical models of robots, as well as in the educational process.

An Investigation of Classical Model Predictive Controller Path Tracking Performance of a Two-Wheel and Four-Wheel Steering Vehicle

Studies on self-driving vehicles have become a trend in recent years, and many systems have been developed to enable autonomous manoeuvre. Various methods have been used to improve path-tracking algorithms which increase vehicle performance, including tracking accuracy and stability. Path tracking is one of the primary problems for autonomous vehicles where the vehicle deviates from target paths, which leads to unnecessary counter-correction. Conventional front wheel steering is unable to satisfy the manoeuvre with a high lateral acceleration since the front steering angle is limited in accurately responding to vehicle dynamics. Moreover, the characteristics of front wheel steering vehicles affect handling stability due to the fact that the turning radius is larger than the vehicle itself. This disadvantageous can compromise safety during under-steer and over-steer situations. The main objective of this preliminary study is to investigate the performance of a four-wheel steering system (4WS) in path tracking for autonomous vehicles using a classical model predictive controller (MPC). Conventional two-wheel steering (2WS) tracking performance following the desired driving system with the same MPC controller is compared with 4WS vehicles. The driving system is developed using Driving Scenario Designer to extract the desired yaw angle and lateral position for controller references constructed in Matlab Simulink. Fixed MPC constraint, prediction, control horizon, yaw angle and lateral position weights were used to compare the performance between 2WS and 4WS vehicles. The simulation results show that 4WS is three times better than 2WS vehicles in tracking predetermined paths. 4WS vehicle show 74.55% better performance in lateral position tracking and 68.75% better performance in trailing predetermined yaw angle value. The simulation data from the preliminary study will be used as a guideline to develop an advanced controller of 4WS vehicles.

Effect of multi-modal input to the perception of sound quality

The perception of sound quality of car interior noise is treated. The decisive factor of sound quality is car interior noise itself but our percetion varies also by the symultaneous exposure of seat and steenring wheel vibrations and the moving seanary from the window screen. We have conducted subjective experiments on the perception of car interior noise unsing car simulator located inside the sound proof room to see the effect of seat and steering wheel vibration and moving sceenary to our perception on sound quality such as pleasantness, booming sensation and powefulness. As the results, the addition of moving sceenary and seat-floor vibration together with the steering wheel viration have significant effect to our perception of sound quality.

Analysis of the perceived intensity of vibratory stimuli driven by the Modal Overlap Factor

The vibro-tactile perception experiment reported in this paper aims to investigate correlations between the perceived vibratory intensity and the Modal Overlap Factor (MOF) of vibratory stimuli. The MOF is often used to physically characterise the vibratory behavior of a structure and can be estimated from the product of frequency, modal density and modal loss factor. In this experiment, stimuli are applied to the participant's hands by means of a steering wheel set in vibration by a shaker. The vibratory stimuli are synthesized from filtered white noise convolved with an impulse response defined as a sum of damped sine waves. The MOF can be controlled by selecting the number of sine waves, their frequency and damping ratio. A set of 100 stimuli, with MOF values ranging from 2 to 200%, in the 5-305Hz range, and equalized in acceleration, is used. Each of the 80 participants is asked to rate twice the perceived intensity of 10 stimuli, pseudo-randomly chosen among the 100 stimuli. Data are analyzed to establish trends between perceived vibratory intensity and the physical parameters of the stimuli.

Fabrication of Novel Polyurethane matrix-based Functional Composites with Enhanced Mechanical Performance

Thermoplastic polyurethane (TPU) has gained significant interest in several fields, including automobile steering wheels, and the electronics sector due to their easier processability, abrasive resistance, and self-lubricating performances. However, their strong inherent flammability and significant smoke and heat production during burning limit their industrial applications. Therefore, its applicability can be enhanced with the addition of high-strength reinforcement and making them antibacterial and flame-retardant. This research is designed to examine the influence of zirconium phosphate (ZrP) and zinc oxide (ZnO) nanoparticles on the novel polyurethane/glass fiber reinforced composites for flame retardant and antibacterial applications with improved mechanical performance. Three different types of novel polyurethane (PU1, PU2, PU3) matrices were prepared using different recipes, and 7% ZrP and 5% ZnO nanoparticles were added to the polyurethane matrices separately, and their corresponding composite samples were fabricated using glass reinforcement. Mechanical i.e., Charpy impact, hardness and tensile, and functional i.e., flame retardancy (FR) and antibacterial tests were performed to compare their performance. Mechanical testing results showed that PU3-based composite samples showed the highest values of impact force, hardness, and tensile strength in both ZrP and ZnO nanoparticle-based composite samples. Furthermore, 7% ZrP-PU3 composite exhibited the best performance of flame retardancy due to the presence of hexamethylene diisocyanates (HDI) content. Likewise, the 5% ZnO-PU3-based composite exhibited the highest antibacterial activity along with enhanced mechanical performance.

Manual steering and robust adaptive constrained control of ship autopilot

This study proposes two schemes for ship autopilot: the first is a follow-up mode, applying manual dynamics to the state-space-based underactuated large merchant ship (ULMS) model, using a steering wheel and joystick to emulate manual operation; the second is a Nav mode developed by path-following control. In this mode, a novel path-following control strategy is developed for ULMS with input saturation and delay, two novel auxiliary systems are employed to stabilize the plant with input constraints. The input delay auxiliary system (IDAS) effectively tackles the design challenges posed by input delay, while the input saturation auxiliary system (ISAS) is dedicated to generating actual control inputs under the constraint of saturation. Furthermore, the dynamic surface control (DSC) technique and the roust neural damping technique are introduced to mitigate the computational burden and simplify the controller structure, thereby enhancing the efficiency and performance of the entire control system. Lyapunov stability analysis proves the ship motion system is semi-globally uniformly ultimately bounded (SGUUB). Finally, the effectiveness of these two schemes is verified through turning experiment, comparative simulations and a semi-physical simulation platform that integrates physical models with computer simulation technology.

Interlimb coordination is not strictly controlled during walking

In human walking, the left and right legs move alternately, half a stride out of phase with each other. Although various parameters, such as stride frequency and length, vary with walking speed, the antiphase relationship remains unchanged. In contrast, during walking in left-right asymmetric situations, the relative phase shifts from the antiphase condition to compensate for the asymmetry. Interlimb coordination is important for adaptive walking and we expect that interlimb coordination is strictly controlled during walking. However, the control mechanism remains unclear. In the present study, we derived a quantity that models the control of interlimb coordination during walking using two coupled oscillators based on the phase reduction theory and Bayesian inference method. The results were not what we expected. Specifically, we found that the relative phase is not actively controlled until the deviation from the antiphase condition exceeds a certain threshold. In other words, the control of interlimb coordination has a dead zone like that in the case of the steering wheel of an automobile. It is conjectured that such forgoing of control enhances energy efficiency and maneuverability. Our discovery of the dead zone in the control of interlimb coordination provides useful insight for understanding gait control in humans.

Synthesis of a dynamic positioning algorithm for wheeled boats

The work analyzes the controllability indicators of a vessel with a wheeled propulsion-steering complex and an azimuth thruster in order to identify the possibility of developing high-precision control algorithms, such as the dynamic positioning task. The influence of the parameters of the wheel-propulsion steering complex and the azimuth thruster on the dynamics of the vessel is considered, and the areas of controllability of the vessel are identified for various propulsion parameters. The influence on the dynamics of the vessel of external wind influence, which has a great influence on the dynamics of the vessel due to its design features (shallow draft, flat bottom, large windage), has been studied. The areas of controllability of the vessel under conditions of external influence when changing wind parameters (force and direction) and parameters of propulsors with separate and joint use of propulsors are determined. An algorithm has been synthesized for dynamically holding a vessel at a given point under wind influence while maintaining a given hull position. The dynamic positioning algorithm consists of two parallel processes. The first is the return of the center of mass of the vessel, which has shifted under the influence of external influences, to a given point due to the wheeled propulsion and steering complex. The second is maintaining a given orientation of the ship's hull using an azimuth thruster. Computer simulation confirmed the high quality indicators of the proposed control algorithm.

Coordinated Control of Differential Drive-Assist Steering and Direct Yaw Moment Control for Distributed-Drive Electric Vehicles

Direct yaw moment control (DYC) and differential drive-assist steering (DDAS) for distributed-drive vehicles are both realized by allocating the in-wheel motor torque. To address the interference caused by overlapping control objectives, this paper proposes a multilayer control strategy that integrates DYC and DDAS, consisting of an upper controller, a coordinated decision layer, and a torque distribution layer. The upper controller, designed based on the vehicle’s dynamic characteristics, incorporates an adaptive fuzzy control DYC system and a dual PID control DDAS system. The coordinated decision layer is developed utilizing a phase-plane dynamic weighting method, delineating region boundaries by applying the double-line and limit cycle methods. The torque distribution strategy is formulated considering motor peak torque and road adhesion conditions. Multi-condition joint simulation experiments indicate that the proposed multilayer control strategy, integrating the advantages of DYC and DDAS, reduces peak steering wheel torque by approximately 10%, peak yaw rate by around 25%, peak sideslip angle by roughly 29%, and peak sideslip angle rate by about 19%, significantly improving driving stability and maneuvering flexibility.

Correlation between Muscular Activity and Vehicle Motion during Double Lane Change Driving.

The aim of this study was to compare the correlation between electromyography (EMG) activity and vehicle motion during double lane change driving. This study measured five vehicle motions: the steering wheel angle, steering wheel torque, lateral acceleration, roll angle, and yaw velocity. The EMG activity for 19 muscles and vehicle motions was applied for envelope detection. There was a significantly high positive correlation between muscles (mean correlation coefficient) for sternocleidomastoid (0.62) and biceps brachii (0.71) and vehicle motions for steering wheel angle, steering wheel torque, lateral acceleration, and yaw velocity, but a negative correlation between the muscles for middle deltoid (-0.75) and triceps brachii long head (-0.78) and these vehicle motions. The ANOVA test was used to analyze statistically significant differences in the main and interaction effects of muscle and vehicle speed. The mean absolute correlation coefficient exhibited an increasing trend with the increasing vehicle speed for the muscles (increasing rate%): upper trapezius (30.5%), pectoralis major sternal (38.7%), serratus anterior (13.3%), and biceps brachii (11.0%). The mean absolute correlation coefficient showed a decreasing trend with increasing vehicle speed for the masseter (-9.6%), sternocleidomastoid (-12.9%), middle deltoid (-5.5%), posterior deltoid (-20.0%), pectoralis major clavicular (-13.4%), and triceps brachii long head (-6.3%). The sternocleidomastoid muscle may decrease with increasing vehicle speed as the neck rotation decreases. As shoulder stabilizers, the upper trapezius, pectoralis major sternal, and serratus anterior muscles are considered to play a primary role in maintaining body balance. This study suggests that the primary muscles reflecting vehicle motions include the sternocleidomastoid, deltoid, upper trapezius, pectoralis major sternal, serratus anterior, biceps, and triceps muscles under real driving conditions.

Adaptive Curve Passing Control in Autonomous Vehicles with Integrated Dynamics and Camera-Based Radius Estimation

Autonomous vehicles frequently encounter performance degradation during high-speed cornering due to excessive speed and lateral acceleration, potentially leading to collisions or rollovers. This paper proposes a novel curve-passing control approach that first estimates the curve radius and then controls the steer and speed for smooth and comfortable handling. In particular, the curve radius is innovatively estimated using a combination of a camera-based lane detection model and a steering wheel dynamic model. The curve-passing control approach is validated on high-speed ramps and curves, demonstrating its robustness and intelligence to adapt to dynamic changes in curve curvature. The model effectively prevents vehicles from entering curves at dangerously high speeds from straight roads and mitigates sudden accelerations or decelerations when entering curves. Experimental results indicate that the vehicle speed is reduced to around 50 km/h and the corresponding acceleration is −0.6 m/s2 upon entering curves with a minimum radius of 150 m. This demonstrates that the proposed control model can ensure a comfortable and safe driving experience by autonomously decelerating the vehicle before entering various types of curves.

Dynamic Measurement Method for Steering Wheel Angle of Autonomous Agricultural Vehicles

Steering wheel angle is an important and essential parameter of the navigation control of autonomous wheeled vehicles. At present, the combination of rotary angle sensors and four-link mechanisms is the main sensing approach for steering wheel angle with high measurement accuracy, which is widely adopted in autonomous agriculture vehicles. However, in a complex and challenging farmland environment, there are a series of prominent problems such as complicated installation and debugging, spattered mud blocking the parallel four-bar mechanism, breakage of the sensor wire during operation, and separate calibrations for different vehicles. To avoid the above problems, a novel dynamic measurement method for steering wheel angle is presented based on vehicle attitude information and a non-contact attitude sensor. First, the working principle of the proposed measurement method and the effect of zero position error on measurement accuracy and path tracking are analyzed. Then, an optimization algorithm for zero position error of steering wheel angle is proposed. The experimental platform is assembled based on a 2ZG-6DM rice transplanter by software design and hardware modification. Finally, comparative tests are conducted to demonstrate the effectiveness and priority of the proposed dynamic sensing method. Experimental results show that the average absolute error of the straight path is 0.057° and the corresponding standard deviation of the error is 0.483°. The average absolute error of the turning path is 0.686° and the standard deviation of the error is 0.931°. This implies the proposed dynamic sensing method can accurately realize the collection of the steering wheel angle. Compared to the traditional measurement method, the proposed dynamic sensing method greatly improves the measurement reliability of the steering wheel angle and avoids complicated installation and debugging of different vehicles. The separate calibrations for different vehicles are not needed since the proposed measurement method is not dependent on the kinematic models of the vehicles. Given that the attitude sensor can be installed at a higher position on the wheel, sensor damage from mud blocking and the sensor wire breaking is also avoided.

Implementing Model Predictive Control (MPC) in Steer-by-Wire Systems for Future Automated Vehicles

Abstract The need for future green sustainable transportation represents a motivation for the researchers in order to create a better society. In this paper a proposed Steer-by-Wire system for future automated vehicles is analysed by implementing model predictive control (MPC) controller that would optimise the desired behaviour of the vehicle. By using MATLAB/Simulink, a bicycle vehicle model is simulated in standardised test manoeuvres according to standard ISO:7401. These results are used as referent data for the desired trajectory of the vehicle and as input data for the MPC controller. The idea of using these results for the controller is generated by the desire of creating a shared information intelligent systems. Shared information and control in the future intelligent systems would be crucial for creating the desired sustainable transport. By traveling, the vehicle would collect data of the desired measured variables and those data would be send to every other vehicle. Therefore, the next vehicle would possess the previous data and would try to improve the vehicle response and safety. Every optimised trajectory would be shared with the rest of the vehicles and this cycle would result in further optimization and in creation of a safer, more comfortable and more sustainable transport. The optimisation is done by the MPC controller which is responsible for defining the steering wheel angle and therefore creating the Steer-by-Wire system that is entirely defined by the MPC controller without driver commands. By comparing the trajectory of the automated vehicle and the desired trajectory gained from the previous simulations, the desired steering wheel angle is defined. This results in creation of a Steer-by-Wire system that improves the vehicle dynamics, safety and dynamic response of the vehicle. The mathematical modelling, results of the simulations and advantages of using the MPC controller for the Steer-by-Wire system in automated vehicle are presented.