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.
Skip Nav Destination
Article navigation
December 2017
Research-Article
Handling Delays in Yaw Rate Control of Electric Vehicles Using Model Predictive Control With Experimental Verification
Milad Jalali,
Milad Jalali
Mechanical Engineering Department,
University of Waterloo,
Waterloo, ON N2L 3G1, Canada
e-mail: mjalaliy@uwaterloo.ca
University of Waterloo,
Waterloo, ON N2L 3G1, Canada
e-mail: mjalaliy@uwaterloo.ca
Search for other works by this author on:
Amir Khajepour,
Amir Khajepour
Mechanical Engineering Department,
University of Waterloo,
Waterloo, ON N2L 3G1, Canada
University of Waterloo,
Waterloo, ON N2L 3G1, Canada
Search for other works by this author on:
Shih-ken Chen,
Shih-ken Chen
Global Research and Development Center,
General Motors Company,
Warren, MI 48090-9055
General Motors Company,
Warren, MI 48090-9055
Search for other works by this author on:
Bakhtiar Litkouhi
Bakhtiar Litkouhi
Global Research and Development Center,
General Motors Company,
Warren, MI 48090-9055
General Motors Company,
Warren, MI 48090-9055
Search for other works by this author on:
Milad Jalali
Mechanical Engineering Department,
University of Waterloo,
Waterloo, ON N2L 3G1, Canada
e-mail: mjalaliy@uwaterloo.ca
University of Waterloo,
Waterloo, ON N2L 3G1, Canada
e-mail: mjalaliy@uwaterloo.ca
Amir Khajepour
Mechanical Engineering Department,
University of Waterloo,
Waterloo, ON N2L 3G1, Canada
University of Waterloo,
Waterloo, ON N2L 3G1, Canada
Shih-ken Chen
Global Research and Development Center,
General Motors Company,
Warren, MI 48090-9055
General Motors Company,
Warren, MI 48090-9055
Bakhtiar Litkouhi
Global Research and Development Center,
General Motors Company,
Warren, MI 48090-9055
General Motors Company,
Warren, MI 48090-9055
1Corresponding author.
Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received September 4, 2015; final manuscript received June 20, 2017; published online August 9, 2017. Assoc. Editor: Azim Eskandarian.
J. Dyn. Sys., Meas., Control. Dec 2017, 139(12): 121001 (8 pages)
Published Online: August 9, 2017
Article history
Received:
September 4, 2015
Revised:
June 20, 2017
Citation
Jalali, M., Khajepour, A., Chen, S., and Litkouhi, B. (August 9, 2017). "Handling Delays in Yaw Rate Control of Electric Vehicles Using Model Predictive Control With Experimental Verification." ASME. J. Dyn. Sys., Meas., Control. December 2017; 139(12): 121001. https://doi.org/10.1115/1.4037166
Download citation file:
Get Email Alerts
Offline and online exergy-based strategies for hybrid electric vehicles
J. Dyn. Sys., Meas., Control
Optimal Control of a Roll-to-Roll Dry Transfer Process With Bounded Dynamics Convexification
J. Dyn. Sys., Meas., Control (May 2025)
In-Situ Calibration of Six-Axis Force/Torque Transducers on a Six-Legged Robot
J. Dyn. Sys., Meas., Control (May 2025)
Active Data-enabled Robot Learning of Elastic Workpiece Interactions
J. Dyn. Sys., Meas., Control
Related Articles
Vehicle Dynamics Control of eAWD Hybrid Electric Vehicle Using Slip Ratio Optimization and Allocation
J. Dyn. Sys., Meas., Control (September,2018)
Linear Vehicle Dynamics of the TowPlow, a Steerable Articulated Snowplow, and Its Kinematics-Based Steering Control
J. Dyn. Sys., Meas., Control (August,2015)
Integrated Vehicle Dynamics Control Via Torque Vectoring Differential and Electronic Stability Control to Improve Vehicle Handling and Stability Performance
J. Dyn. Sys., Meas., Control (July,2018)
Optimal Torque Distribution for the Stability Improvement of a Four-Wheel Distributed-Driven Electric Vehicle Using Coordinated Control
J. Comput. Nonlinear Dynam (September,2016)
Related Proceedings Papers
Related Chapters
Practical Applications
Robust Control: Youla Parameterization Approach
Real Time Control Solution for Nonlinear Position System
International Conference on Future Computer and Communication, 3rd (ICFCC 2011)
Design and Analysis of a Double-Half-Revolution Mechanism Exploration Rover
Proceedings of the 2010 International Conference on Mechanical, Industrial, and Manufacturing Technologies (MIMT 2010)