Browse Topic: Four wheel steering
The pursuit of maintaining a zero-sideslip angle has long driven the development of four-wheel-steering (4WS) technology, enhancing vehicle directional performance, as supported by extensive studies. However, strict adherence to this principle often leads to excessive understeer characteristics before tire saturation limits are reached, resulting in counter-intuitive and uncomfortable steering maneuvers during turns with variable speeds. This research delves into the phenomenon encountered when a 4WS-equipped vehicle enters a curved path while simultaneously decelerating, necessitating a reduction in steering input to adapt to the increasing road curvature. To address this challenge, this paper presents a novel method for dynamically regulating the steady-state yaw rate of 4WS vehicles. This regulation aims to decrease the vehicle's sideslip angle and provide controlled understeer within predetermined limits. As a result, the vehicle can maintain a zero-sideslip angle during turns with
Vehicular automation in the form of a connected and automated vehicle platoon is demanding as it aims to increase traffic flow and driver safety. Controlling a vehicle platoon on a curved path is challenging, and most solutions in the existing literature demonstrate platooning on a straight path or curved paths at constant speeds. This article proposes an algorithmic solution with leader-following (LF) communication topology and constant distance (CD) spacing for platooning homogeneous position-controlled vehicles (PCVs) on a curved path, with each vehicle capable of cornering at variable speeds. The lead vehicle communicates its reference position and orientation to all the follower vehicles. A follower vehicle stores this information as a virtual trail of the lead vehicle for a specific period. An algorithm uses this trail to find the follower vehicle’s reference path by solving an optimization problem. This algorithm is feasible and maintains a constant inter-vehicle distance. The
This work investigates the steering and wheel speed control of a completely custom built 8x8 scaled electric combat vehicle (SECV) which has been constructed to meet the Ackermann condition at low speeds. During remote control operation the scaled vehicle is capable of continuously maintaining and varying the individual wheel speed and individual wheel steering angles of all eight wheels in real time. Several steering scenarios have been developed including traditional (front 2-axle steering), fixed third axle (first, second and fourth axle steering), all wheel steering and crab steering (all wheels are parallel with same steering angle). The traditional, two axle steering scenario is experimentally tested for accuracy in this work with planned future research for experimental analysis of the other steering configurations. This work is conducted using Arduino software to control the physical SECV and TruckSim software to simulate the dynamics of the vehicle. The results obtained from
The purpose of this specification is to provide airplane operators and tow vehicle manufacturers with: a General design and operating requirements pertinent to test and evaluation of towbarless tow vehicles. Specific design requirements are provided in ARP4852 and ARP4853. b Test and evaluation requirements. The results of these test evaluations will determine if the loads induced by the tow vehicle will exceed the design loads of the nose gear, or are within the aircraft manufacturer’s limits so that they do not affect the certified safe limit of the nose gear. The results of these test evaluations will also determine if a stability problem may occur during pushback and/or maintenance towing operations with the tested airplane/tow vehicle combination. This document specifies general test requirements and a test evaluation procedure for towbarless tow vehicles (TLTV) intended for pushback and maintenance towing only. It is not meant for dispatch (operational) towing (see definitions in
This research aims to model and assess autonomous vehicle controller while including a four-wheel steering and longitudinal speed control. Such a modeling process simulates human driver behavior with consideration of real vehicle dynamics’ characteristics during standard maneuvers. However, a four-wheel steering control improves vehicle stability and maneuverability as well. A three-degree of freedom bicycle model, lateral deviation, yaw angle, and longitudinal speed is constructed to describe vehicle dynamics’ behavior. Moreover, a comprehensive traction model is implemented which includes an engine, automatic transmission, and non-linear magic formula tire model for simulation of vehicle longitudinal dynamics. A combination of proportional integral derivative (PID) longitudinal controller and fuzzy lateral controller are implemented simultaneously to track the desired vehicle path while minimizing lateral deviation and yaw angle errors. Then, A linear quadratic regulator (LQR) based
Lane-changing is a typical traffic scene effecting on road traffic with high request for reliability, robustness and driving comfort to improve the road safety and transportation efficiency. The development of connected autonomous vehicles with V2V communication provide more advanced control strategies to research of lane-changing. Meanwhile, four-wheel steering is an effective way to improve flexibility of vehicle. The front and rear wheels rotate in opposite direction to reduce the turning radius to improve the servo agility operation at the low speed while those rotate in same direction to reduce the probability of the slip accident to improve the stability at the high speed. Hence, this paper established Four-Wheel-Steering(4WS) vehicle dynamic model and quasi real lane-changing scenes to analyze the motion constraints of the vehicles. Then, the polynomial function was used for the lane-changing trajectory planning and the extended rectangular vehicle model was established to get
Steering movement is the most basic movement of the vehicle, in the car driving process, the driver through the steering wheel has always been to control the direction of the car, in order to achieve their own driving intention. Four Wheel Steering (4WS) is an advanced vehicle control technique which can markedly improve vehicle steering characteristics. Compared with traditional front wheel steering vehicles, 4WS vehicles can steer the front wheels and the rear wheels individually for cornering, according to the vehicle motion states such as the information of vehicle speed, yaw velocity and lateral acceleration. Therefore, 4WS can enhance the handling stability and improve the active safety for vehicles. Based on the theory of Vehicle Dynamics and Sliding Mode Control, this paper investigates the following issues, Firstly, a 2DOF 2WS vehicle model is built up by using the state-space equations, which will be used to compare the 4WS vehicle model containing vehicle lateral and yaw
This paper presents an integrated chassis controller with multiple hierarchical layers for 4WID/4WIS electric vehicle. The proposed systematic design consists of the following four parts: 1) a reference model is in the driver control layer, which maps the relationship between the driver's inputs and the desired vehicle motion. 2) a sliding mode controller is in the vehicle motion control layer, whose objective is to keep the vehicle following the desired motion commands generated in the driver control layer. 3) By considering the tire adhesive limits, a tire force allocator is in the control allocation layer, which optimally distributes the generalized forces/moments to the four wheels so as to minimize the tire workloads during normal driving. 4) an actuator controller is in the executive layer, which calculates the driving torques of the in-wheel motors and steering angles of the four wheels in order to finally achieve the distributed tire forces. Experimental verification is made to
Four-wheel independent control electric vehicle is a new type of x-by-wire EV with four wheels independent steering and four wheels independent drive/brake systems. In order to take full advantage of the vehicle's performance potential, this paper presents a novel integrated chassis control strategy. In the paper, the strategy is designed by the hierarchical control structure and divided into integrated control layer and allocation layer. By this method, the control logical can be modularized and simplified. In the integrated control layer, Model Prediction Control (MPC) is adopted to design the integrated control unit, which belongs to be a kind of local optimization algorithm with feedback correction features. Using this method could avoid the system performance degradation caused by the control model mismatch. The control allocation layer is to optimally distribute the vehicle control forces to the steering/driving/brake actuators on each wheel. In order to maximize the use of the
The main characteristic of vehicle moving on road is related to its response to the drivers command and to environmental factors affecting the direction of motion of vehicle. The two basic problems in handling the vehicle are control of vehicle along the desired path and stabilization of the direction of motion of vehicle against external disturbances. The vehicle with best handling characteristics is the vehicle which can always be controlled by the driver. While parking the vehicle and doing sharp turnings the vehicle with two wheel steering cannot be more significant. The two wheel steering system takes large radius of turning and requires more space to take turn. Hence four wheel steering is preferable than two wheel steering systems. A multi-function four wheel steering system could improve directional stability at high speeds, sharp turning performance at low speeds, and parking performance of a vehicle. Generally there are three types of steering systems which include front
This paper describes the use of a designed Fuzzy Logic Control for the purpose of integrating the driver’s steering input together with the four-wheel steering system (4WS) in order to improve the vehicle’s dynamic behavior with respect to yaw rate and body sideslip angle. The control objective is to obtain zero body sideslip angle by a two-dimensional rule table, which is created based on the error and on the change in the error of sideslip angle that is to be minimized. The dynamics of the model is developed with a three-degree of freedom nonlinear vehicle model including roll dynamics. The Magic Formula is applied in order to formulate the nonlinear characteristics of the tires. A lane change and steady state cornering simulations are performed to show the effectiveness of the control on transient motion body sideslip angle and yaw rate response time behaviors. During simulations, comparisons are done with the two-wheel steered vehicle and the control techniques studied previously
The tow vehicle should be designed for towbarless push-back and/or maintenance towing of regional type aircraft as specified in 1.3. The design will ensure that the unit will safely secure the aircraft nose landing gear within the coupling system for any operational mode. The purpose of this towing procedure is to achieve a safer and faster operation than is possible with conventional towing equipment
The dynamics of a four wheel steering(4WS) system inherently has model uncertainties, resulting in degradation in performance. As a way to compensate the model uncertainties of the vehicle system, a nonlinear neural network control scheme is proposed and evaluated. The control scheme is composed of a conventional model reference control term and a compensator term. The compensator term is generated by an unsupervised neural network whose teaching signal is just error information between the actual plant and the reference model. This control scheme does not require an inverse dynamics of the plant or a Jacobian information of the learned plant, so that an on-line learning can be carried out. Since the teaching signal of this scheme is simple to compute in the control process, the fast convergence can be realized. The validity and effectiveness of the proposed control scheme for a vehicle four wheel steering are verified by computer simulations
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