The dynamics at the tire road contact have an immense effect on the vehicle’s handling and stability characteristics as the majority of the forces and moments acting on the vehicle chassis are generated at the tire contact patch. Sudden changes at this contact patch results in abrupt variations in vehicle characteristics which may lead to lose of control for the inexperienced driver. The active safety systems available today seek to prevent such unintended vehicle behavior by assisting drivers in maintaining control of their vehicles. Nevertheless, the lack of knowledge about the tire-road interactions highly limits their effectiveness. Motivated by this opportunity and necessity in the field, this study develops a tire slip-angle estimation algorithm and an adaptive control strategy to improve vehicle stability. The estimator uses a sensor fusion approach that integrates feedback from a concept technology, namely the intelligent tire with a model based nonlinear observer to provide information on tire forces and slip-angle. The proposed control and observer algorithms are evaluated using numerical analysis under a double lane change maneuver. To get a better measure of possible improvements in vehicle performance, the tests are executed together with baseline algorithm inspired by a conventional system. The results demonstrate that the proposed algorithms can successfully negotiate the given tasks as well as promising considerable improvements over the baseline system.
- Dynamic Systems and Control Division
An Adaptive Vehicle Stability Control Strategy Using Tire Slip-Angle Feedback
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Arat, MA, & Taheri, S. "An Adaptive Vehicle Stability Control Strategy Using Tire Slip-Angle Feedback." Proceedings of the ASME 2014 Dynamic Systems and Control Conference. Volume 3: Industrial Applications; Modeling for Oil and Gas, Control and Validation, Estimation, and Control of Automotive Systems; Multi-Agent and Networked Systems; Control System Design; Physical Human-Robot Interaction; Rehabilitation Robotics; Sensing and Actuation for Control; Biomedical Systems; Time Delay Systems and Stability; Unmanned Ground and Surface Robotics; Vehicle Motion Controls; Vibration Analysis and Isolation; Vibration and Control for Energy Harvesting; Wind Energy. San Antonio, Texas, USA. October 22–24, 2014. V003T49A005. ASME. https://doi.org/10.1115/DSCC2014-6271
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