Design of Integrated Vehicle Chassis Control Based on LPV Methods

Author(s):  
Zoltán Szabó ◽  
Péter Gáspár ◽  
József Bokor
2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Bing Zhu ◽  
Yizhou Chen ◽  
Jian Zhao ◽  
Yunfu Su

An integrated vehicle chassis control strategy with driver behavior identification is introduced in this paper. In order to identify the different types of driver behavior characteristics, a driver behavior signals acquisition system was established using the dSPACE real-time simulation platform, and the driver inputs of 30 test drivers were collected under the double lane change test condition. Then, driver behavior characteristics were analyzed and identified based on the preview optimal curvature model through genetic algorithm and neural network method. Using it as a base, an integrated chassis control strategy with active front steering (AFS) and direct yaw moment control (DYC) considering driver characteristics was established by model predictive control (MPC) method. Finally, simulations were carried out to verify the control strategy by CarSim and MATLAB/Simulink. The results show that the proposed method enables the control system to adjust its parameters according to the driver behavior identification results and the vehicle handling and stability performance are significantly improved.


2018 ◽  
Vol 41 (9) ◽  
pp. 2428-2440 ◽  
Author(s):  
Jiaxu Zhang ◽  
Jing Li

This paper presents an integrated vehicle chassis control (IVCC) strategy to improve vehicle handling and stability by coordinating active front steering (AFS) and direct yaw moment control (DYC) in a hierarchical way. In high-level control, the corrective yaw moment is calculated by the fast terminal sliding mode control (FTSMC) method, which may improve the transient response of the system, and a non-linear disturbance observer (NDO) is used to estimate and compensate for the model uncertainty and external disturbance to suppress the chattering of FTSMC. In low-level control, the null-space-based control reallocation method and inverse tyre model are utilized to transform the corrective yaw moment to the desired longitudinal slips and the steer angle increment of front wheels by considering the constraints of actuators and friction ellipse of each wheel. Finally, the performance of the proposed control strategy is verified through simulations of various manoeuvres based on vehicle dynamic software CarSim.


Author(s):  
Ganesh Adireddy ◽  
Taehyun Shim

An integrated vehicle chassis control system was developed to improve vehicle handling (yaw) responses while maintain vehicle roll stability using an 8 DOF vehicle model, a simplified tire model, and a model predictive control method. The proposed control system incorporates active wheel torque distribution, active front steering, and active anti-rollbar to enhance vehicle handling and its ability to track the desired trajectory when the risk of vehicle rollover is low. As vehicle rollover risks increase, the proposed control system shifts its control focus from only handling enhancement to vehicle roll stabilization by adjusting the gains in the controller. The simulation results show that the proposed control system can improve vehicle handling responses while ensuring vehicle roll stability at high speed vehicle maneuvers.


Author(s):  
Carlos Villegas ◽  
Yin-Lam Chow ◽  
Martin Corless ◽  
Robert Shorten ◽  
Wynita Griggs

2008 ◽  
Vol 41 (2) ◽  
pp. 4677-4682
Author(s):  
V. Sankaranarayanan ◽  
Sinan Oncu ◽  
Dincer Ozcan ◽  
Levent Güvenç

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