This paper presents a novel vehicle lateral stability control method based on an estimated lateral stability region on the phase plane of vehicle yaw rate and lateral speed, which is obtained through a local linearization method. Since the estimated stability region does not only describe vehicle local stability, but also define the oversteering and understeering characteristics, the proposed control method can achieve both local stability and vehicle handling stability. Considering the irregular geometric shape of the estimated stability region, a stability analysis algorithm is designed to determine the distance between vehicle states and stability region boundaries. State estimation or measurement errors are also incorporated in the distance calculation. Based on the calculated shortest distance between vehicle states and stability boundaries, a direct yaw moment controller is designed to maintain vehicle states stay within the stability region. CarSim® and Simulink® co-simulation is applied to verify the control design through a cornering maneuver. The simulation results show that the proposed control method can make the vehicle stay within the stability region successfully and thus always operate in a safe manner.
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ASME 2017 Dynamic Systems and Control Conference
October 11–13, 2017
Tysons, Virginia, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-5827-1
PROCEEDINGS PAPER
Vehicle Lateral Motion Control Based on Estimated Stability Regions
Yiwen Huang,
Yiwen Huang
Arizona State University, Tempe, AZ
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Yan Chen
Yan Chen
Arizona State University, Mesa, AZ
Search for other works by this author on:
Yiwen Huang
Arizona State University, Tempe, AZ
Yan Chen
Arizona State University, Mesa, AZ
Paper No:
DSCC2017-5152, V001T45A006; 8 pages
Published Online:
November 14, 2017
Citation
Huang, Y, & Chen, Y. "Vehicle Lateral Motion Control Based on Estimated Stability Regions." Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Volume 1: Aerospace Applications; Advances in Control Design Methods; Bio Engineering Applications; Advances in Non-Linear Control; Adaptive and Intelligent Systems Control; Advances in Wind Energy Systems; Advances in Robotics; Assistive and Rehabilitation Robotics; Biomedical and Neural Systems Modeling, Diagnostics, and Control; Bio-Mechatronics and Physical Human Robot; Advanced Driver Assistance Systems and Autonomous Vehicles; Automotive Systems. Tysons, Virginia, USA. October 11–13, 2017. V001T45A006. ASME. https://doi.org/10.1115/DSCC2017-5152
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