Wheel Angle Research Articles

The Control of Handling Stability for Four-Wheel Steering Distributed Drive Electric Vehicles Based on a Phase Plane Analysis

For the sake of enhancing the handling and stability of distributed drive electric vehicles (DDEVs) under four-wheel steering (4WS) conditions, this study proposes a novel hierarchical control strategy based on a phase plane analysis. This approach involves a meticulous comparison of the stable region in the phase plane to thoroughly analyze the intricate influence of the front wheel angle, rear wheel angle, road adhesion coefficient, and longitudinal speed on the complex dynamic performances of DDEVs and to accurately determine the critical stable-state parameter. Subsequently, a hierarchical control strategy is presented as an integrated solution to achieve the coordinated control of maneuverability and stability. On the upper control level, a model predictive control (MPC) motion controller is developed, wherein the real-time adjustment of the control weight matrix is ingeniously achieved by incorporating the crucial vehicle stable-state parameter. The lower control level is responsible for the optimal torque allocation among the four wheel motors to minimize the tire load rate, thereby ensuring a sufficient tire grip margin. The optimal torque distribution for the four wheel motors is achieved using a sophisticated two-level allocation algorithm, wherein the friction ellipse is employed as a judgement condition. Finally, this developed control strategy is thoroughly validated through co-simulation utilizing the CarSim 2019 and Simulink 2020b commercial software, demonstrating the validity of the developed control strategy. The comparative results indicate that the presented controller ensures a better tracking capability to the desired vehicle state while exhibiting improved handling stability under both the double lane shifting condition and the serpentine working condition.

Performance materials with variations of tractor drive wheel fin angle and low-cost manufacturing analysis

Nowadays, the demand for workers in the agriculture industry has decreased and there is a need for rising mechanization in the agriculture process. The agriculture process that requires mechanization is cultivating. The rice cultivator has to be as light as possible, so requires a lighter material but is also strong enough. The correlation between the rice transplanter tool and the wheels is closely related to soil conditions. The selection of wheel materials is considered based on the characteristics of the planting area. In addition, another influence variable is the angle of the fin in the rice transplanter wheel. Material of rice transplanter wheel has been established, these are 1023 carbon steel sheet, AISI 1020 steel cold rolled, AISI 316 stainless steel. The angle of the fin was varied, these are 30, 35, and 40, this fin will give an effect on the traction result of rice transplanter wheel movement. The combination of lightweight material and the appropriate fin angle of the rice transplanter wheel has the best traction result. As a result of this research, the suitable material for the rice transplanter wheel was carbon steel and the fin’s angle was 30. This research involved a comparison and analysis of material strength under various fin angles. The evaluation of stress criteria was conducted using design values to determine the most reliable final product design. The paper contributes by illustrating how to represent the final decision on the combination of design and materials, incorporating a cost index assessment.

RELATIONSHIP BETWEEN TRANSITION CURVES (CLOTHOIDS) AND CIRCULAR CURVES IN ROAD ALIGNMENT

<p style="text-align: justify;"><span lang="EN-GB" style="font-size: 12pt; line-height: 200%; font-family: arial, helvetica, sans-serif;">The transition from a straight line to a circular curve is always abrupt, even if this is not readily noticeable at very large radii or low driving speeds. On the straight section the steering wheel angle is zero, on the arc section the steering wheel angle must have a certain value, as stated above, which is greater the tighter the curve. This in turn would mean that you would have to turn the steering wheel jerkily at the transition between the straight section and the circular curve section. Otherwise you would go off track. Even in the case of large radii without transition curves, the lines of a road appear inelastic and can satisfy neither aesthetically nor driving psychologically down to the last detail. In perspective foreshortening - how the road is seen by the driver - sudden kinks appear despite the large curve radii.</span></p>

A Novel Robust H∞ Control Approach Based on Vehicle Lateral Dynamics for Practical Path Tracking Applications

This paper proposes a robust lateral control scheme for the path tracking of autonomous vehicles. Considering the discrepancies between the model parameters and the actual values of the vehicle and the fluctuation of parameters during driving, the norm-bounded uncertainty is utilized to deal with the uncertainty of model parameters. Because some state variables in the model are difficult to measure, an H∞ observer is designed to estimate state variables and provide accurate state information to improve the robustness of path tracking. An H∞ state feedback controller is proposed to suppress system nonlinearity and uncertainty and produce the desired steering wheel angle to solve the path tracking problem. A feedforward control is designed to deal with road curvature and further reduce tracking errors. In summary, a path tracking method with H∞ performance is established based on the linear matrix inequality (LMI) technique, and the gains in observer and controller can be obtained directly. The hardware-in-the-loop (HIL) test is built to validate the real-time processing performance of the proposed method to ensure excellent practical application potential, and the effectiveness of the proposed control method is validated through the utilization of urban road and highway scenes. The experimental results indicate that the suggested control approach can track the desired trajectory more precisely compared with the model predictive control (MPC) method and make tracking errors within a small range in both urban and highway scenarios.

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.

Chassis concept of the individually steerable five-link suspension: a novel approach to maximize the road wheel angle to improve vehicle agility

The Institute of Vehicle Systems Engineering at Ulm University of Applied Sciences is currently developing the autonomous concept vehicle Nimbulus-e in the strategic field “Intelligent Commercial Vehicles” with the aim of maneuvering as agilely as possible in confined spaces. To achieve high agility under the conditions mentioned, large road wheel steering angles are necessary. As part of the basic vehicle concept, the first step is to select a suitable chassis for this purpose. Conventional suspensions cannot be applied due to the mechanical connection of the tie rod to the steering knuckle limiting the road wheel angles. Therefore, the approaches published so far for individual chassis concepts with large steering angles are analyzed and evaluated for use. In this paper, the concept of a novel individually steerable five-link suspension is described. The concept includes a vehicle body mounted steering actuator connected to the chassis via a self-locking worm gear. Due to the body mounted connection of the steering actuator, it does not contribute to the unsprung mass. An analysis of the kinematic and elastokinematic properties and the achievable road wheel steering angle is presented. In the Nimbulus e concept vehicle, the individually steerable corner module is used on both the front and the rear axle. The system is driven by four wheel hub motors. This means that eight control variables are available for the vehicle.

Comparison of modeling methods and mitigation measures for curve squealing

Predicting and mitigating curve squealing has always been difficult. This study employed various modeling methods to unify the existing models and establish three finite element models (FEMs) of wheelset–track systems to predict curve squealing. The FEMs of the wheelset–track systems, which incorporated solid fasteners, negative friction–velocity slopes, and multiple wheelsets, were examined using complex eigenvalue analysis to determine their relative capacity to predict curve squeal. The inhibitory effects of damping treatments on curve squeal in both wheels and rails were also studied. The results indicate that, in an improvement on the initial model, the FEMs developed in this study can effectively predict curve squeal with frequencies of 482, 1,205, and 2154 Hz. The wheelset–track system was more likely to produce frictional self-excited vibrations under negative damping and interference from multiple wheelsets, but the impact was small. In addition, the rubber block angle of the resilient wheel was set at 15°. Increasing the damping of the rail vibration absorbers and selecting a continuous–discrete under-rail vibration absorber effectively suppressed the generation of curve squeal.

On integrated lateral and longitudinal control of brain-controlled vehicles

A brain-controlled vehicle (BCV) is a vehicle that uses the Brain–Computer interface (BCI) to analyze the driver’s electroencephalogram (EEG) to obtain human control commands, which can help disabled people extend movement range and improve their self-independence. At this stage, research on the control of BCVs usually focuses only on the lateral control or longitudinal control, and few studies have focused on the problem of integrated lateral and longitudinal control. Given this situation, this paper investigates the integrated control of brain-controlled vehicles (BCV) in both lateral and longitudinal directions, and proposes a control method that utilizes speed as the coupling point. Firstly, the vehicle’s speed is determined by the provided road information. To control the vehicle’s longitudinal speed, a hierarchical control method based on model predictive control (MPC) is implemented. This method introduces a threshold σ to speed up the calculation process and reduce resource consumption. Then, a global controller is developed to conduct the motion control. This controller utilizes three local ANFIS intelligent controllers, employing soft-switching combinations, to generate the steering wheel angle signal. The generated steering wheel angle signal is combined with the cornering command issued by the driver. This fusion process produces the final command, which is responsible for the vehicle’s motion control. Finally, a simulation model is developed to test the integrated control of the BCV in terms of both lateral and longitudinal movements. Multiple experiments are conducted under varying conditions, and the results prove that the proposed method is able to complete the integrated control of the BCV well, which fully illustrates its effectiveness.

Design of four-wheel steering system based on automotive electronic control technology

Abstract With the rapid development of the automobile industry, people’s requirements for automobile handling performance and driving safety are getting higher and higher. As an important automobile power system, four-wheel steering technology can improve the maneuverability, stability, and safety of vehicles by controlling the steering angles of front and rear wheels. Therefore, the design and research of the four-wheel steering system has become one of the hotspots in the field of automotive engineering. In this paper, a two-degree-of-freedom dynamics model is established, and based on the PID control strategy of joint feedback of center-of-mass lateral deflection and traverse angular velocity, the vehicle model of a four-wheeled steering vehicle is constructed by using TruckSim, and the minimum turning radius test, serpentine test, and steering wheel angle step test project are carried out. The results show that compared with the two-wheel steering vehicle, the minimum turning diameter of the four-wheel steering vehicle is reduced by 1/3, which effectively improves the maneuverability at low speeds as well as the safety and stability at high speeds, and has better transient response.

Research on Stability Control of Distributed Drive Vehicle with Four-Wheel Steering

The four-wheel steering distributed drive vehicle is a novel type of vehicle with independent control over the four-wheel angle and wheel torque. A method for jointly controlling the distribution of the wheel angle and torque is proposed based on this characteristic. Firstly, the two-degrees-of-freedom model and ideal reference model of four-wheel steering vehicle are established; then, the four-wheel steering controller and torque distribution controller are designed. The rear wheel angle is controlled by the feedforward controller and the feedback controller. The feedforward controller takes the side slip angle of the center of mass as the control target, and the feedback controller takes the yaw angle as the control target. Torque is controlled by two control layers, the additional yaw moment of the upper layer is calculated by the vehicle motion state and fuzzy control theory, and the lower layer distributes wheel torque through the road adhesion coefficient and wheel load. Finally, a simulation platform is established to verify the effectiveness of the proposed control algorithm.

Design Method of Cam Steering Mechanism Based on Path Fitting

In order to improve the accuracy of a solar-powered punch card car’s movement on a designated route and reduce positional deviations during its operation, a solar-powered punch card car with a single cam as the steering guidance mechanism was designed. The car adopts a three-wheel structure. The transmission mechanism, steering mechanism, driving mechanism, and regulating mechanism of the car were analyzed. The kinematics model of the car was established and the motion characteristics of the car were obtained. By analyzing the relationship between the steering angle of the car and the curvature radius of its travel route, the front wheel angle of the car at each position was calculated using MATLAB R2020a. This allowed us to establish the relationship between the front wheel angle and the displacement of the steering push rod, which was further converted into the theoretical contour line of the cam. Subsequently, the theoretical contour line of the cam was completed and envelope correction was performed. Finally, through mechanical analysis and experimental verification using a prototype, the results indicated that the single-cam steering guidance mechanism calculated using this fast path fitting method exhibited excellent mechanical performance and a smooth and accurate trajectory, and the traveling path of the theoretical cam contour curve was basically consistent with the actual trajectory route.

Conceptualization and development of a semi-automatic vegetable transplanter prototype for small landholdings

The process of seedling transplantation has significant importance within the realm of mechanical vegetable production in contemporary agriculture. A prototype of a two-row tractor-mounted semi-automatic vegetable seedling transplanter (SVT) was conceptualized and developed for small agricultural holdings. The functional behaviour of the prototype was examined with computer-aided design tools, and the various units of the prototype have been finalized. To develop the prototype, the feeding, metering, transplanting, drive train, and soil compacting/covering unit of the machine were developed and constructed using materials readily accessible locally. The machine has a set row-to-row spacing of 600 mm, and it may alter the plant-to-plant spacing when the machine's forward speed changes. The pace was customized to achieve the required 450 mm plant-to-plant spacing. A 12:1 speed reduction gearbox was used for the proper metering of seedlings. The effect of independent factors, namely tray cell type, feeding mechanism, soil covering/compacting wheel angle, and age of seedling, on the machine's actual field capacity (AFC) was examined. The prototype underwent preliminary field testing to assess the functional viability, and the functioning was satisfactory. The main effect of the feeding mechanism and soil covering/compacting wheel angle on AFC was statistically significant at 5 % for tomato and brinjal whereas their first-order interaction was found statistically significant on AFC for tomatoes. The findings demonstrate that this study's prototype can be marketed or used to further vegetable production studies.

Research on layered control of path tracking for unmanned industrial vehicles based on fully hydraulic steering leakage compensation

Industrial vehicles work in complex terrain, the variable centre of mass position, leakage nonlinearity of full hydraulic steering and other issues lead to poor path tracking stability and accuracy. In this paper, an intelligent hierarchical controller for industrial vehicles’ path tracking is designed with full hydraulic steering leakage compensation, including an upper decision layer and a lower execution layer. The upper decision layer observes the pavement-tyre adhesion coefficients through an extended Kalman filter algorithm, and uses the real-time observations of the adhesion coefficients to establish a variable constraint control for the linear time-varying MPC, and thus performs the path tracking control. The lower actuator layer receives the upper layer’s target steering wheel angle output and performs steering operations. Based on the establishment of a mathematical model of full hydraulic steering considering the leakage characteristics, it analyses the leakage disturbance factors and constructs a fuzzy feed-forward steering leakage compensation controller to compensate for the leakage disturbances in real time for path tracking steering. Simulation and experimental results show that the lateral acceleration, sideslip angle, tyre side slip angle and tracking error of intelligent industrial vehicles under different loads and working conditions are improved by more than 32.4%, 35.8%, 40.2% and 45.8% respectively, and the designed hierarchical controller for the path tracking of intelligent industrial vehicles, which considers the compensation of all-hydraulic steering leakage, can effectively improve the path tracking stability and tracking accuracy of intelligent industrial vehicles under different loads and working conditions.

FGO-MFI: factor graph optimization-based multi-sensor fusion and integration for reliable localization

Reliable and precise information pertaining to the position, velocity, and attitude is essential for automated driving. This paper proposes FGO-MFI, a cost-effective and robust multi-sensor fusion and integration localization framework that utilizes factor graph optimization. Firstly, a tightly coupled Global Navigation Satellite Systems (GNSS)/on-board sensor fusion localization framework is established to estimate vehicle states, including position, velocity, and attitude. To address the large drift rate of the Inertial Measurement Unit (IMU), this study introduces a novel IMU/Dynamics pre-integration method based on the vehicle dynamics model. We establish a two-degree-of-freedom vehicle dynamics model utilizing measurements from the wheel speed sensor and steering wheel angle sensor. The IMU/Dynamics factor is devised through a close integration of the model output and IMU pre-integration, enabling the construction of precise odometry with low-cost on-board sensors. Then, to address the issue of the non-Gaussian distribution of GNSS pseudorange error, this paper employs a Gaussian Mixture Model (GMM) to characterize the pseudorange noise, which is then applied to further sensor fusion. Given the time-varying nature of pseudorange noise, the expectation maximization algorithm is utilized to estimate GMM parameters online, leveraging the pseudorange residuals within a sliding window. Comprehensive experiments, inclusive of challenging scenarios such as urban canyons, tunnels, and wooded areas, have been carried out. They affirm the superior performance of the proposed method. Experiments have shown that our method demonstrates reliable localization across different statuses of GNSS signal, exhibiting a 39.4% improvement in the root mean square error of position error when compared to the state-of-the-art. Additionally, this FGO-MFI is a general sensor data fusion framework and is able to incorporate diverse sensor measurements, for example, from cameras and LiDARs to provide more reliable and accurate localization information.

Impact of freeway slope photovoltaic panels on drivers: A study based on driving simulator

Aiming at the impact of freeway slope photovoltaic construction on driving safety, a driving simulator experiment was carried out. By designing eight slope photovoltaic schemes under varying sunlight conditions and road alignment parameters, we recruited 35 drivers to collect detailed driving behavior data. Seven driving indicators were selected to develop an evaluation index system. Statistical analysis was conducted to compare driver behavioral performance under eight slope photovoltaic schemes. The findings reveal that the installation of photovoltaic panels on freeway slopes significantly affects driving behavior. Specifically, the driver's speed and degree of steering wheel angle decreased significantly, while acceleration increased significantly on straight alignment. The standard deviation of driver speed, acceleration and standard deviation of acceleration significantly reduced, while the degree of steering wheel angle and the depth of the gas pedal significantly increased when photovoltaic panels were laid on the side slopes on curved road sections. In addition, different curve radius, the impact of photovoltaic panels on acceleration and degree of steering wheel turning angle were different. There is a significant effect of installing side slope photovoltaic panels on driver acceleration, standard deviation of acceleration and degree of steering wheel turning angle in curved sections with different curve radius. Under different sunlight conditions, the impact of photovoltaic panels on the degree of steering wheel angle were also different. The actual setup needs to take into account the impact of different road alignments on drivers. The is study provided theoretical support for the installation of freeway slope photovoltaic panels.

Hierarchical extension H2/H∞ control approach for active front steering system of vehicle

Aiming at improving the vehicle handling stability and vehicle control performance by conventional H2/H∞ control, this paper investigates the active front steering (AFS) system by proposing a hierarchical extension H2/H∞ control strategy. Considering uncertainties and the vehicle handling stability, a mixed H2/H∞ control method is presented to generate the additional front wheel angle through tracking the desired vehicle yaw rate in the upper level. Furthermore, to enhance the H2/H∞ control effect, the novel extension control is proposed to adjust the H2/H∞ control signal dynamically according to different domains defined by the vehicle states. To track front wheel angle from the upper level, this study puts forward the fractional-order proportional-integral-derivative (FOPID) controller for driving the electro-hydraulic steering actuators. The hardware-in-the-loop experiments are performed to demonstrate the hierarchical control theory. The test results indicate that the proposed hierarchical extension H2/H∞ control strategy improves the vehicle cornering stability well, as well as can make the vehicle have better handling stability than conventional H2/H∞ and sliding mode control.

Trajectory Tracking Control Design for 4WS Vehicle Based on Particle Swarm Optimization and Phase Plane Analysis

With the rapid development of today’s society, the traffic environment has become more and more complex. As an essential part of intelligent vehicles, trajectory tracking has attracted significant attention for its stability and safety. It is prone to poor accuracy and instability in extreme working conditions like high speed. In this paper, a trajectory tracking control strategy to ensure lateral stability at a high speed and low attachment limit conditions is proposed for distributed drive vehicles. The model predictive controller (MPC) was used to control the front wheel angle, and the particle swarm optimization (PSO) algorithm was designed to optimize the MPC control parameters adaptively. The sliding mode controller controls the rear wheel angle, and the vehicle instability degree is judged by analyzing the β − β˙ phase plane. The controllers of different instability degrees are designed herein. Finally, a torque divider is designed to consider the actuation anti-slip. The designed controller is verified by Carsim and MATLAB-Simulink co-simulation. The results show that the trajectory tracking controller designed in this paper effectively improves the tracking accuracy under the premise of ensuring stability.

Analysis and regulation of driving behavior in the entrance zone of freeway tunnels: Implementation of visual guidance systems in China

In China, visual guidance systems are commonly used in tunnels to optimize the visual reference system. However, studies focusing specifically on visual guidance systems in the tunnel entrance zone are limited. Hence, a driving simulation test is performed in this study to quantitatively evaluate the effectiveness of (i) visual guidance devices at different vertical positions (pavement and roadside) and (ii) a multilayer visual guidance system for regulating driving behavior in the tunnel entrance zone. Furthermore, the characteristics of driving behavior and their effects on traffic safety in the tunnel entrance zone are examined. Data such as the vehicle position, area of interest (AOI), throttle position, steering wheel angle, and lane center offset are obtained using a driving simulation platform and an eye-tracking device. As indicators, the first fixation position (FP), starting deceleration position (DP), average throttle position (TPav), number of deceleration stages (N|DS), gradual change degree of the vehicle trajectory (G|VT), and average steering wheel angle (SWAav) are derived. The regulatory effect of visual guidance devices on driving performance is investigated. First, high-position roadside visual guidance devices effectively reduce decision urgency and significantly enhance deceleration and lane-keeping performance. Specifically, the advanced deceleration performance (AD), smooth deceleration performance (SD), trajectory gradualness (TG), and trajectory stability (TS) in the tunnel entrance zone improve by 63%, 225%, 269%, and 244%, respectively. Additionally, the roadside low-position visual guidance devices primarily target the trajectory gradualness (TG), thus resulting in improvements by 80% and 448% in the TG and TS, respectively. Meanwhile, the pavement visual guidance devices focus solely on enhancing the TS and demonstrates a relatively lower improvement rate of 99%. Finally, the synergistic effect of these visual guidance devices facilitates the multilayer visual guidance system in enhancing the deceleration and lane-keeping performance. This aids drivers in early detection and deceleration at the tunnel entrance zone, reduces the urgency of deceleration decisions, promotes smoother deceleration, and improves the gradualness and stability of trajectories.

A form-grinding wheel optimization method for helical gears based on a PSO-SVM model

A gear form-grinding optimization method is proposed to obtain an optimal profile of a form-grinding wheel by solving a transcendental equation of the contact line between a form-grinding wheel and a helical gear workpiece. Since the equation of the contact line is transcendental, the relationship between the installation angle of the form-grinding wheel and the shape of the contact line cannot be represented by explicit functions, which makes it difficult to obtain the optimal profile of the form-grinding wheel. An optimization method of the contact line between the form-grinding wheel and the gear is proposed using three evaluation parameters that are the overrun, the shift, and the offset. Some gear form-grinding performances, such as machining stroke, tooth deviation, and grinding chatter, can be quantitatively described using those evaluation parameters. Further, a method for optimizing evaluation parameters is proposed, which uses a particle swarm optimization-support vector machine (PSO-SVM) model with the advantage of small-sample robustness to solve evaluation parameters. The PSO-SVM model is trained under the condition of different installation angles of the form-grinding wheel as the input and the evaluation function as the output. The R-squared value of the overrun is 0.986 that vilidate the high accuracy of the PSO-SVM model. Gear form-grinding test results show the proposed method can effectively improve grinding accuracy.

Lateral Stability Control for Intelligent Commercial Vehicle Based on Reconstructed Objective Function Method

In this paper, a novel electric-hydraulic power steering (EHPS) system and a vehicle stability coordination control algorithm are proposed which can not only ensure the accuracy of the trajectory tracking but also solve the coordination control problem between the stability of the lateral control and the stability of the roll in the extreme condition. Firstly, the EHPS system is designed to provide accurate control input of front wheel angle for vehicle lateral dynamics control. Secondly, on the basis of optimal preview theory, a new trajectory tracking fusion controller combined with sliding mode control is proposed to improve the accuracy and stability of the system in the process of vehicle lateral trajectory tracking control. Then, the stability domain boundary function of the phase plane is determined according to the phase plane of the sideslip angle-yaw rate, and the stability margin of the phase plane is calculated during the steering process. Finally, considering the tracking accuracy, lateral stability and roll stability performance in the process of trajectory tracking, the linear weighted algorithm is used to coordinate above three objectives, and the HIL bench test and real vehicle experiment verify that the proposed algorithm has good reliability and effectiveness.