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

Nonlinear Model Predictive Tracking Control for Nonholonomic AGV Based on Bio-Inspired Neurodynamics

2013 ◽  
Author(s):  
Xiao-Hong Yin ◽  
Can Yang
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Nonlinear Model ◽  
Control Method ◽  
Kinematic Model ◽  
Input Saturation ◽  
Stability Control ◽  
Control Approach ◽  
Velocity Jump ◽  
Control Principle

Considering nonholonomic constraint and input saturation of the Automatic Guided Vehicle (AGV) kinematic model, in the present work the nonlinear model predictive control was applied and a combined tracking/stability control approach was proposed. In addition, the bio-inspired neurodynamics model was applied to generate smooth forward velocities so that the sharp velocity jump can be overcome by the proposed controller. Specifically, an optimal sub-control method consisting of cost function and constraints were obtained based on the model predictive control principle, and a terminal sub-control method was designed to make the control system stable. Finally, the effectiveness of the proposed control strategy was demonstrated through comparison studies with simulations.

scholarly journals Lateral Stability Control of Four-Wheel Independent Drive Electric Vehicles Based on Model Predictive Control

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Bin Huang ◽  
Sen Wu ◽  
Song Huang ◽  
Xiang Fu
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Algorithm ◽  
Control Method ◽  
Integrated Control ◽  
Stability Control ◽  
Lateral Stability ◽  
Integrated Simulation ◽  
Consumption Rates ◽  
Experiment Verification

Four-wheel independent drive electric vehicle was used as the research object to discuss the lateral stability control algorithm, thus improving vehicle stability under limit conditions. After establishing hierarchical integrated control structure, we designed the yaw moment decision controller based on model predictive control (MPC) theory. Meanwhile, the wheel torque was assigned by minimizing the sum of consumption rates of adhesion coefficients of four tires according to the tire friction ellipse theory. The integrated simulation platform of Carsim and Simulink was established for simulation verification of yaw/rollover stability control algorithm. Then, we finished road experiment verification of real vehicle by integrated control algorithm. The result showed that this control method can achieve the expectation of effective vehicle tracking, significantly improving the lateral stability of vehicle.

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