|
In order to solve the stability problem of intelligent vehicles, which is that high-adhesion roads are prone to rollover accidents and low-adhesion roads are prone to side-slip accidents under sharp turning conditions, the vehicle adaptive control model that considers vehicle yaw and roll stability is proposed. The vehicle dynamics model was constructed by comprehensively considering many factors that cause vehicle instability such as yaw, sideslip, and roll during the operation of the smart car. At the same time, the vehicle dynamics model is optimized to realize adaptive control of the model's time domain parameters, which significantly improves the tracking accuracy and the calculation efficiency of the controller. In order to further verify the performance of the controller, a vehicle dynamics model predictive controller was built based on the vehicle dynamics simulation software Carsim, and the effectiveness of the adaptive predictive control model was verified through J-turn test and fishhook test analysis. And The simulation results is show that the adaptive model predictive controller proposed in this article can effectively improve the calculation efficiency and control accuracy of the model, and the average single calculation time is shortened by approximately 16.76%. Compared with traditional rolling prediction methods, the adaptive simulation model proposed in this paper has a faster response speed and higher control accuracy, which can effectively ensure the safe and stable operation of intelligent connected vehicles without collision in complex environments such as time-varying curvature and roll slope.
|
