Paper
7 September 2022 Research on stability control of multi-axle special vehicle based on active steering
Jianfu Yang, Zhihao Liu, Hongjie Cheng, Lei Gao
Author Affiliations +
Proceedings Volume 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022); 1232936 (2022) https://doi.org/10.1117/12.2646772
Event: Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 2022, Changsha, China
Abstract
In order to improve the maneuverability and stability of a certain type of multi-axle special vehicle under low adhesion coefficient and high-speed conditions, an active steering controller is designed with this type of multi-axle special vehicle as the research object. Firstly, the dynamic model of this type of special vehicle is built based on Trucksim, and the accuracy of the model is verified by real vehicle experiments, which lays a foundation for the research on active steering control. Then, an active steering controller is designed based on the Ackerman steering principle with the zero centroid slip angle as the control objective. Finally, the model of the controller is built through simulink, and the cosimulation with the vehicle dynamics model of Trucksim is carried out to verify the designed active steering controller. The simulation results show that the designed active steering controller has an ideal control effect on the roll stability and handling stability of the vehicle under high speed conditions and low adhesion road coefficient.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jianfu Yang, Zhihao Liu, Hongjie Cheng, and Lei Gao "Research on stability control of multi-axle special vehicle based on active steering", Proc. SPIE 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 1232936 (7 September 2022); https://doi.org/10.1117/12.2646772
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KEYWORDS
Motion models

Roads

Chlorine

Lawrencium

Autoregressive models

Sensors

Vehicle control

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