Model predictive control based vehicle stability control via active front steering

2017 ◽  
Author(s):  
Shunhang Zheng ◽  
Bangcheng Zhang ◽  
Shaosong Li ◽  
Guodong Wang ◽  
Xiaoquan Zhu ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Stability Control ◽  
Vehicle Stability ◽  
Active Front Steering ◽  
Vehicle Stability Control

Handling Delays in Yaw Rate Control of Electric Vehicles Using Model Predictive Control With Experimental Verification

2017 ◽  
Vol 139 (12) ◽  
Author(s):  
Milad Jalali ◽  
Amir Khajepour ◽  
Shih-ken Chen ◽  
Bakhtiar Litkouhi
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Rear Wheel ◽  
Stability Control ◽  
Vehicle Stability ◽  
Control Loop ◽  
Yaw Rate ◽  
Vehicle Stability Control ◽  
Wheel Drive ◽  
Rear Wheel Drive

In this paper, a new approach is proposed to deal with the delay in vehicle stability control using model predictive control (MPC). The vehicle considered here is a rear-wheel drive electric (RWD) vehicle. The yaw rate response of the vehicle is modified by means of torque vectoring so that it tracks the desired yaw rate. Presence of delays in a control loop can severely degrade controller performance and even cause instability. The common approaches for handling delays are often complex in design and tuning or require an increase in the dimensions of the controller. The proposed method is easy to implement and does not entail complex design or tuning process. Moreover, it does not increase the complexity of the controller; therefore, the amount of online computation is not appreciably affected. The effectiveness of the proposed method is verified by means of carsim/simulink simulations as well as experiments with a rear-wheel drive electric sport utility vehicle (SUV). The simulation results indicate that the proposed method can significantly reduce the adverse effect of the delays in the control loop. Experimental tests with the same vehicle also point to the effectiveness of this technique. Although this method is applied to a vehicle stability control, it is not specific to a certain class of problems and can be easily applied to a wide range of model predictive control problems with known delays.

Vehicle Stability Control Based on Generalized Predictive Contol

2013 ◽  
Vol 774-776 ◽  
pp. 448-454
Author(s):  
Wei Qiao Yin ◽  
Jing Li ◽  
You De Li ◽  
Qing Wei
Keyword(s):  
Predictive Control ◽  
Vehicle Dynamics ◽  
State Space Model ◽  
Stability Control ◽  
Vehicle Stability ◽  
Vehicle Stability Control ◽  
Vehicle Systems ◽  
Braking Control ◽  
Vehicle Chassis ◽  
Two Degree Of Freedom

For the uncertain environmental factors existing in the vehicle systems, in this paper we established linear two degree-of-freedom vehicle dynamics state-space model which considering lateral interference, and designed the vehicle chassis coordination controller based on generalized predictive control, utilized combined steering and braking control to strengthen the vehicle yaw and lateral stability. Simulation and Analysis for the controller in MATLAB/Simulink environment were conducted, the results verified the feasibility and effectiveness of the control methods.

An Analytical Transient Tire Model

2001 ◽  
Vol 29 (2) ◽  
pp. 108-132 ◽  
Author(s):  
A. Ghazi Zadeh ◽  
A. Fahim
Keyword(s):  
Transient Behavior ◽  
Stability Control ◽  
Vehicle Stability ◽  
Tire Model ◽  
Steering Angle ◽  
First Order ◽  
Vehicle Stability Control ◽  
Proposed Model ◽  
Depth Study ◽  
And Performance

Abstract The dynamics of a vehicle's tires is a major contributor to the vehicle stability, control, and performance. A better understanding of the handling performance and lateral stability of the vehicle can be achieved by an in-depth study of the transient behavior of the tire. In this article, the transient response of the tire to a steering angle input is examined and an analytical second order tire model is proposed. This model provides a means for a better understanding of the transient behavior of the tire. The proposed model is also applied to a vehicle model and its performance is compared with a first order tire model.

Vehicle Stability Control Through Predictive and Optimal Tire Saturation Management

2012 ◽  
Author(s):  
Justin Sill ◽  
Beshah Ayalew
Keyword(s):  
Stability Control ◽  
Vehicle Stability ◽  
Distribution Problem ◽  
Scale Separation ◽  
Torque Distribution ◽  
Hydraulic Hybrid ◽  
Time Scale Separation ◽  
Vehicle Stability Control ◽  
Natural Time ◽  
Set Up

This paper presents a predictive vehicle stability control (VSC) strategy that distributes the drive/braking torques to each wheel of the vehicle based on the optimal exploitation of the available traction capability for each tire. To this end, tire saturation levels are defined as the deficiency of a tire to generate a force that linearly increases with the relevant slip quantities. These saturation levels are then used to set up an optimization objective for a torque distribution problem within a novel cascade control structure that exploits the natural time scale separation of the slower lateral handling dynamics of the vehicle from the relatively faster rotational dynamics of the wheel/tire. The envisaged application of the proposed vehicle stability strategy is for vehicles with advanced and emerging pure electric, hybrid electric or hydraulic hybrid power trains featuring independent wheel drives. The developed predictive control strategy is evaluated for, a two-axle truck featuring such an independent drive system and subjected to a transient handling maneuver.

Mixed H∞/H2 Output Feedback Stability Control for Dual-Motor Independent Drive Electric Vehicle

2013 ◽  
Vol 658 ◽  
pp. 602-608 ◽  
Author(s):  
Cheng Lin ◽  
Chun Lei Peng
Keyword(s):  
Electric Vehicle ◽  
Output Feedback ◽  
Stability Control ◽  
Vehicle Stability ◽  
Robust Performance ◽  
Output Feedback Controller ◽  
Vehicle Stability Control ◽  
Feedback Stability ◽  
Simulation Results ◽  
Yaw Moment

This paper presents the design of mixed H∞/H2Output Feedback Controller for Independent Drive Electric Vehicle Stability Control. It generates yaw moment by applying driving intervention at front Independent driving wheels according to the vehicle states. The performance of the proposed controller is evaluated through a series of simulations under different velocity and different mass. The simulation results show that the controller can help vehicle against a certain range of uncertainty (speeds and loads) and get excellent robust performance.

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