Active Steering Wheel System for Ultra-Compact Mobility Vehicles: Operability Evaluation with Steering Burden in Various Drivers

In ultra-compact electric vehicles, the satisfactory installation of an assist mechanism for steering operation is difficult. To address this problem, in this paper, we propose an active steering wheel system in which the steering wheel and tires are electrically connected, without a mechanical connection. Furthermore, in ultra-compact mobility vehicles where the driving position is restricted, steering burden is likely to occur depending on the physique of the driver. However, whether the effects of the steering reaction torque and the amount of steering increase the burden on the driver in such vehicles has not yet been clarified. Therefore, in this study, we developed an upper limb burden model using inverse kinematics and muscle activity to investigate the burden of steering on the driver by considering the driver physique.

An adaptive tracking control method for the all-wheel-driving and active-steering articulated vehicle with n-units

To achieve the running control of the all-wheel-driving and active-steering articulated vehicles (AWDASAVs) with n-units, an adaptive tracking control method is proposed in this paper, which includes a real-time target trajectory generation and an adaptive tracking control system. Firstly, the AWDASAV kinematics model is derived, and then the front-axle trace as the target trajectory is computed for all rear-axle steering by using data compressing and filtering, coordinate transformation, and local spline differences, which has small data storage and high computational efficiency and makes it easier to use in AWDASAV. Secondly, an adaptive tracking control system composed of an adaptive active steering controller and a differential distribution controller is designed to achieve accurate trajectory tracking and coordinated movement for AWDASAV. Finally, the AWDASAV simulation model with five-units was built in ADAMS by code development for cross-validation simulation, and the simulations with two cases at various speeds are carried out to verify the simulation model and control method. To further investigate the proposed method, the influence of three parameters on the tracking control performance and comparison with different control methods are carried out. The results exhibit excellent tracking control performance.

Path Tracking Control of Autonomous Vehicle Based on Nonlinear Tire Model

The tire forces of vehicles will fall into the non-linear region under extreme handling conditions, which cause poor path tracking performance. In this paper, a model predictive controller based on a nonlinear tire model is designed. The tire forces are characterized with nonlinear composite functions of the magic formula instead of a simple linear relation model. Taylor expansion is used to linearize the controller, the first-order difference quotient method is used for discretization, and the partial derivative of the composite function is used for matrix transformation. Constant velocity and variable velocity conditions are selected to compare the designed controller with the conventional controller in Carsim/Simulink. The results show that when the tire forces fall in the nonlinear region, two controllers have good stability, and the tracking accuracy of the controller designed in this paper is slightly better. However, after the tire forces become nonlinear, the controller with linear tire force becomes worse, the tracking accuracy is far worse than the controller with the nonlinear tire model, and the vehicle stability is also degraded. In addition, an active steering test platform based on LabVIEW-RT is established, and hardware-in-the-loop tests are carried out. The effectiveness of the designed controller is verified.

A novel tracking control method for the distributed-drive and active-steering articulated virtual rail train

To realize the running control of distributed-drive and active-steering articulated virtual rail trains travelling on urban roads under non-contact virtual rail constraints, target trajectory generation and active-steering control are crucial issues. In this article, a novel tracking control method is proposed, which includes a dynamic target trajectory generation and a new active-steering tracking control system. First, a distributed-drive and active-steering articulated virtual rail train kinematics model with n-sections is derived, and then a new target trajectory generation method is proposed using data filtering and compression, coordinate transformation and spline difference, and the simulation comparison shows that the proposed method has less data storage space and high computational efficiency. Second, a new active-steering tracking control system composed of a rear axle preview active-steering controller, a front axle coordinated steering controller, and a differential-distribution controller is designed to achieve tracking control and coordinated movement of distributed-drive and active-steering articulated virtual rail train. Finally, a distributed-drive and active-steering articulated virtual rail train simulation model was constructed in ADAMS, and then simulations are performed under three rail conditions and compared with the other two methods, which show that the proposed method has good tracking control accuracy, adaptability, and superiority under various rails and different speeds.

Active steering control based on preview theory for articulated heavy vehicles

This paper investigates the active steering control of the tractor and the trailer for the articulated heavy vehicle (AHV) to improve its high-speed lateral stability and low-speed path following. The four-degree-of-freedom (4-DOF) single track dynamic model of the AHV with a front-wheel steered trailer is established. Considering that the road information at the driver’s focus is the most clear and those away from the focus blurred, a new kind controller based on the fractional calculus, i.e., a focus preview controller is designed to provide the steering input for the tractor to make it travel along the desired path. In addition, the active steering controllers based on the linear quadratic regulator (LQR) and single-point preview controller respectively are also proposed for the trailer. However, the latter is designed on the basis of the articulation angle between the tractor and trailer, inspired by the idea of the driver’s single-point preview controller. Finally, the single lane change maneuver and 90o turn maneuver are carried out. And the simulation results show that compared with the single-point preview controller, the new kind preview controller for the tractor can have good high speed maneuvering stability and low speed path tracking ability by adjusting the fractional order of the controller. On this basis, three different AHVs with the same tractor are simulated and the simulation results show that the AHV whose trailer adopts the single-point preview controller has better high-speed lateral stability and low-speed path tracking than the AHV whose trailer adopts the LQR controller.

Trajectory Tracking Control in Real-Time of Dual-Motor-Driven Driverless Racing Car Based on Optimal Control Theory and Fuzzy Logic Method

To improve the accuracy and timeliness of the trajectory tracking control of the driverless racing car during the race, this paper proposes a track tracking control method that integrates the rear wheel differential drive and the front wheel active steering based on optimal control theory and fuzzy logic method. The model of the lateral track tracking error of the racing car is established. The model is linearized and discretized, and the quadratic optimal steering control problem is constructed. Taking advantage of the differential drive of dual-motor-driven racing car, the dual motors differential drive fuzzy controller is designed and integrated driving with active steering control. Simulation analysis and actual car verification show that this integrated control method can ensure that the car tracks different race tracks well and improve the track tracking control accuracy by nearly 30%.

A Review Paper on Electric Assisted Steering System for Automobiles

Electric Assisted Steering system is an Electric System, which reduces the amount of steering effort by directly applying the output from the electric motor to the steering system.In this system the mechanical link between the steering wheel and road wheels of an automobile are replaced by a control system consisting of sensors, actuators and controllers seem to offer great advantages such as enhanced system performance, simplified construction, design flexibility etc.It offers greater vehicle safety by adapting variable steering ratios to human needs, filtering drive train influences and even adjusting active steering torque in critical situations. In addition, it can make cars even lighter and more fuel efficient when compared to those using hydraulic steering systems. The central electronic elements of today’s steering systems are modern microcontrollers