4.7 Article

Novel Constrained Nonlinear Control of Vehicle Dynamics Using Integrated Active Torque Vectoring and Electronic Stability Control

Journal

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 68, Issue 10, Pages 9564-9572

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2019.2933229

Keywords

Wheels; Torque; Friction; Vehicle dynamics; Engines; Tires; Stability analysis; Optimal integrated control; input and state constraints; active torque vectoring; electronic stability control; continuous

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This study deals with a new integrated control sys-tem using active torque vectoring (ATV) and electronic stability control (ESC) for enhancement of vehicle directional stability and steerability. In this system, the stabilizing yaw moment is calculated using a novel constrained nonlinear controller with both input and state constraints. The proposed controller is designed using the prediction of continuous nonlinear vehicle model. It guarantees the vehicle directional stability by restricting the side slip angle in the admissible range when the yaw rate tracks its desired response for improved steerability. The calculated yaw moment is generated as driving and braking forces by integrated ATV and ESC systems. According to the integration policy, the required yaw moment is initially generated by ATV in the rear wheels to keep the vehicle driving performance. Because of limitation of ATV, if more yaw moment is required, the ESC system applies asymmetric braking pressure to front wheels to compensate the scarcity of ATV. By the proposed strategy, the small reduction of vehicle velocity is achieved and the vehicle drivability performance is maintained. In order to determine the full capacity of ATV, the active differential dynamics is considered in this paper. Simulation studies are conducted to evaluate the efficiency of proposed constrained controller in comparing with the unconstrained controller and a conventional nonlinear model predictive controller (NMPC) developed in the recent papers using 14-DOF vehicle model. By analyzing the results, it is clear that the proposed controller is much faster and easy to solution and implementation.

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