RMPC-Based Directional Stability Control for Electric Vehicles Subject to Tire Blowout on Curved Expressway

2018 ◽  
Vol 141 (4) ◽  
Author(s):  
Lu Yang ◽  
Ming Yue ◽  
Jie Wang ◽  
Wenbin Hou
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Stability Control ◽  
Simulation Platform ◽  
Vertical Force ◽  
Directional Stability ◽  
Stability Performance ◽  
Switch Control ◽  
Exogenous Disturbances ◽  
Vehicle Dynamic Simulation

This paper presents a directional stability control based on robust tube-based model predictive control (RMPC) approach for an overactuated electric vehicle after tire blowout on curved expressway, in the presence of the exogenous disturbances, such as cross wind and road variation. To begin with, the vehicle dynamic simulation platform allowing for the tire vertical force redistribution after tire blowout is presented, and the reliability of the platform is further analyzed by comparing with the existing experimental test results. After that, a RMPC-based controller is designed to enhance the directional stability performance of the vehicle on curved expressway after tire burst. Also, a pseudo inverse switch control allocator is developed to realize the allocation of the desired resultant signal for the remained effective wheels at the last stage. In the end, the simulation results conducting on the depicted simulation platform demonstrate the favorable maneuverability of the proposed method over the conventional model predictive control (MPC) in enhancing directional stability performance of the vehicle after a tire blowout on curved expressway.

Path tracking framework synthesizing robust model predictive control and stability control for autonomous vehicle

2020 ◽  
Vol 234 (9) ◽  
pp. 2330-2341
Author(s):  
Jiaxing Yu ◽  
Xiaofei Pei ◽  
Xuexun Guo ◽  
JianGuo Lin ◽  
Maolin Zhu
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Stability Control ◽  
Robust Model Predictive Control ◽  
Direct Yaw Moment Control ◽  
Robust Model ◽  
Yaw Moment Control ◽  
Moment Control ◽  
The Stability ◽  
Yaw Moment

This paper proposes a framework for path tracking under additive disturbance when a vehicle travels at high speed or on low-friction road. A decoupling control strategy is adopted, which is made up of robust model predictive control and the stability control combining preview G-vectoring control and direct yaw moment control. A vehicle-road model is adopted for robust model predictive control, and a robust positively invariant set calculated online ensures state constraints in the presence of disturbances. Preview G-vectoring control in stability control generates deceleration and acceleration based on lateral jerk, later acceleration, and curvature at preview point when a vehicle travels through a cornering. Direct yaw moment control with additional activating conditions provides an external yaw moment to stabilize lateral motion and enhances tracking performance. A comparative analysis of stability performance of stability control is presented in simulations, and furthermore, many disturbances are considered, such as varying wind, road friction, and bounded state disturbances from motion planning and decision making. Simulation results show that the stability control combining preview G-vectoring control and direct yaw moment control with additional activating conditions not only guarantees lateral stability but also improves tracking performance, and robust model predictive control endows the overall control system with robustness.

The Research of Wheel Drive Vehicle Yaw Stability Controller Based on Model Predictive Control

2014 ◽  
Vol 998-999 ◽  
pp. 735-740 ◽  
Author(s):  
Chen Guo Zou ◽  
Hong Liang Zhou ◽  
Zhen He
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Method ◽  
Stability Control ◽  
Safety Control ◽  
Yaw Rate ◽  
Wheel Drive ◽  
Yaw Stability ◽  
Braking Torque ◽  
Driving Torque

As an important active safety control method, vehicle yaw stability control guarantees the dynamic stability of vehicle. A wheel drive vehicle yaw stability controller based on model predictive control theory is designed to plan the longitudinal forces of the four wheels online to control the driving torque or braking torque of each wheel. With the designed controller, the vehicle is able to track the desired yaw rate in the process of turning. The yaw stability and longitudinal characteristics of the vehicle are guaranteed at the same time.

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 Yaw Stability Control at the Handling Limits Based on Model Predictive Control

2020 ◽  
Vol 21 (2) ◽  
pp. 361-370 ◽  
Author(s):  
Shaosong Li ◽  
Guodong Wang ◽  
Bangcheng Zhang ◽  
Zhixin Yu ◽  
Gaojian Cui
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Stability Control ◽  
Yaw Stability
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