Robust stabilization of vehicle dynamics by active front wheel steering control

This article investigates the differential steering-based schema to control the lateral and rollover motions of the in-wheel motor-driven electric vehicles. Generated from the different torque of the front two wheels, the differential steering control schema will be activated to function the driver’s request when the regular steering system is in failure, thus avoiding dangerous consequences for in-wheel motor electric vehicles. On the contrary, when the vehicle is approaching rollover, the torque difference between the front two wheels will be decreased rapidly, resulting in failure of differential steering. Then, the vehicle rollover characteristic is also considered in the control system to enhance the efficiency of the differential steering. In addition, to handle the low cost measurement problem of the reference of front wheel steering angle and the lateral velocity, an [Formula: see text] observer-based control schema is presented to regulate the vehicle stability and handling performance, simultaneously. Finally, the simulation is performed based on the CarSim–Simulink platform, and the results validate the effectiveness of the proposed control schema.

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Comparison of Analytical and Empirical Models to Capture Variations in Off-Road Vehicle Dynamics

Design Engineering, Parts A and B ◽

10.1115/imece2005-81660 ◽

2005 ◽

Cited By ~ 4

Author(s):

Paul J. Pearson ◽

David M. Bevly

Keyword(s):

Empirical Data ◽

Vehicle Dynamics ◽

Experimental Validation ◽

Inertial Sensors ◽

Analytical Models ◽

Control Algorithms ◽

Model Parameters ◽

Steering Control ◽

Steering Angle ◽

Yaw Rate

This paper develops two analytical models that describe the yaw dynamics of a farm tractor and can be used to design or improve steering control algorithms for the tractor. These models are verified against empirical data. The particular dynamics described are the motions from steering angle to yaw rate. A John Deere 8420 tractor, outfitted with inertial sensors and controlled through a PC-104 form factor computer, was used for experimental validation. Conditions including different implements at varying depths, as would normally be found on a farm, were tested. This paper presents the development of the analytical models, validates them against empirical data, and gives trends on how the model parameters change for different configurations.

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Vehicle coupled bifurcation analysis of steering angle and driving torque

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering ◽

10.1177/0954407020985405 ◽

2021 ◽

pp. 095440702098540

Author(s):

Xianbin Wang ◽

Shuming Shi

Keyword(s):

Bifurcation Analysis ◽

Hybrid Method ◽

Vehicle Dynamics ◽

Front Wheel ◽

Steering Angle ◽

Driving Mode ◽

Vehicle System ◽

Autonomous Equation ◽

Real Coded Genetic Algorithm ◽

Driving Torque

The mechanism of vehicle dynamics steering bifurcation has almost been confirmed. But the present steering bifurcation mechanism cannot explain the bifurcation phenomena caused by the driving torque. As a result, the vehicle coupled bifurcation analysis of the steering angle and driving torque has not been studied. Based on the five degrees of freedom (5DOF) vehicle system dynamics model with driving torque involved, the vehicle dynamics equilibriums under different driving torque and driving mode were searched by a hybrid method in this paper. The hybrid method combined the real-coded Genetic Algorithm with Quasi-Newton gradient method. According to the definition of static bifurcation of nonlinear systems, the equilibrium bifurcation of 5DOF vehicle system was confirmed. Then, the 5DOF vehicle system model was transformed into autonomous equation with the front wheel steering angle as intermediate variable. From the two aspects of constant steering angle amplitude and constant driving torque, the bifurcation diagrams of different driving mode were calculated. The vehicle coupled bifurcation characteristics of steering angle and driving torque were analyzed. The results show that the values of the driving torque will directly affect the bifurcation characteristics of vehicle dynamics system. The coupled feature of the front wheel steering angle and driving torque effect on vehicle bifurcation is obvious.

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Experimental Validations on Vision-Based Path Tracking With Preview Four Wheel Steering Control

Volume 1: Advanced Driver Assistance and Autonomous Technologies; Advances in Control Design Methods; Advances in Robotics; Automotive Systems; Design, Modeling, Analysis, and Control of Assistive and Rehabilitation Devices; Diagnostics and Detection; Dynamics and Control of Human-Robot Systems; Energy Optimization for Intelligent Vehicle Systems; Estimation and Identification; Manufacturing ◽

10.1115/dscc2019-9159 ◽

2019 ◽

Author(s):

Yansong Peng ◽

Fengchen Wang ◽

Saikrishna Gurumoorthy ◽

Yan Chen ◽

Mutian Xin

Keyword(s):

Tracking Control ◽

Low Cost ◽

Experimental Tests ◽

Front Wheel ◽

Path Tracking ◽

Steering Control ◽

Tracking Errors ◽

The Road ◽

Experimental Validations ◽

Lateral Offset

Abstract In this paper, a vision-based path-tracking control strategy using four-wheel steering (4WS) is experimentally investigated via an automated ground vehicle (AGV). A low-cost monocular camera is used to continuously perceive the upcoming lane boundaries via capturing the preview road image frames. Based on the applied image processing algorithms, the vehicle lateral offset error with respect to the road center line and the heading angle error with respect to the road curvature are calculated in real time for the control purpose. The 4WS path-tracking controller is designed to minimize the two path-tracking errors of the AGV. The AGV with the 4WS system is utilized to perform the experimental tests on road to validate the path-tracking control design. For comparison, the road test is also conducted for the path-tracking control with only the front wheel steering. The experimental results show that the proposed 4WS is able to achieve better path-tracking performance.

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Vehicle Handling and Stability Enhancement With Active Steering Control Systems

Dynamic Systems and Control, Parts A and B ◽

10.1115/imece2004-61638 ◽

2004 ◽

Author(s):

Shih-Ken Chen ◽

William C. Lin ◽

Yuen-Kwok Steve Chin ◽

Xiaodi Kang

Keyword(s):

Rear Wheel ◽

Front Wheel ◽

Pole Placement ◽

Optimization Approach ◽

Steering Control ◽

Response Characteristics ◽

Active Steering ◽

Road Surfaces ◽

Response Optimization ◽

Stability Enhancement

This paper presents an analysis and comparison of a vehicle with active front steering and rear-wheel steering. Based on linear analysis of base vehicle characteristics under varying speed and road surfaces, desirable vehicle response characteristics are presented and a set of performance matrices for active steering systems is formulated. Using pole-placement approach, controllability issues under active front wheel steering and rear- wheel steering controls are discussed. A frequency response optimization approach is then used to design the closed-loop controllers.

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Robust stabilization of the vehicle dynamics by gain-scheduled H/sub ∞/ control

Proceedings of the 1999 IEEE International Conference on Control Applications (Cat. No.99CH36328) ◽

10.1109/cca.1999.801224 ◽

2003 ◽

Cited By ~ 2

Author(s):

E. Ono ◽

S. Hosoe ◽

K. Asano ◽

M. Sugai ◽

S. Doi

Keyword(s):

Vehicle Dynamics ◽

Robust Stabilization ◽

Gain Scheduled

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Vehicle Dynamics Control Based on Linear Quadratic Regulator

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.16-19.876 ◽

2009 ◽

Vol 16-19 ◽

pp. 876-880

Author(s):

Si Qi Zhang ◽

Tian Xia Zhang ◽

Shu Wen Zhou

Keyword(s):

Control Strategy ◽

Vehicle Dynamics ◽

Linear Quadratic Regulator ◽

Active Safety ◽

Vehicle Stability ◽

Steering Control ◽

Linear Quadratic ◽

Yaw Rate ◽

Vehicle Dynamics Control ◽

Yaw Moment

The paper presents a vehicle dynamics control strategy devoted to prevent vehicles from spinning and drifting out. With vehicle dynamics control system, counter braking are applied at individual wheels as needed to generate an additional yaw moment until steering control and vehicle stability were regained. The Linear Quadratic Regulator (LQR) theory was designed to produce demanded yaw moment according to the error between the measured yaw rate and desired yaw rate. The results indicate the proposed system can significantly improve vehicle stability for active safety.

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