Rolling Optimization Control Method Of Multiple Time Scales Vehicle Stability Based On Vehicle State Parameter Estimation

Nowadays,there are many traffic accidents around us.With the rapid development of automobile industry,the focus of people's attention is how to improve the security and comfort of automobile and reduce the occurrence of accidents.Many domestic and foreign researchers have developed more and more research into autonomous driving,at the same time,they worked out many effective electronic control systems to achieve vehicle intelligentization.Vehicle yaw stability control is critical for the automobile active safety.In order to improve the overall performance of vehicle,the identification of vehicle state parameters is great significance to vehicle stability control.the focus of people's attention is how to identify vehicle state parameters and control vehicle yaw stability in this paper.This paper on the major projects of national natural science fund(61790564)“Extreme coordinated control of the vehicle movement under the condition of integration ”,the national natural science foundation of key projects of international(regional)cooperation and the exchange(61520106008)“ For safety of electric cars rolling optimization of energy efficiency ” and national natural science foundation of China youth fund project(61703176)“ Fast calculation method of nonlinear model predictive control research and application” of funding,the following research and analysis.Aiming at the yaw stability control problem,a rolling optimal control method for vehicle yaw stability with multi-time scales is proposed.Considering the different time scales of steering driving behavior and lateral stability integrated controller are established respectively.Driver behavior and lateral active safety control belong to different time scales,so that the controller can meet the comprehensive control of different time scales.In this paper,the model predictive control algorithm is used to transform the control problem into a constrained nonlinear programming problem with constraints.The additional yaw moment is applied to the vehicle through the braking force distribution strategy.The effectiveness of the controller is verified through a variety of simulation conditions.Vehicle yaw stability control can further improve vehicle stability and driving comfort.The identification of vehicle state parameters is of great significance to the improvement of vehicle safety.The most important problem is how to obtain the realtime and accurate driving status information of the vehicle.It is impossible for all the driving state information of vehicles to be realized by sensors,so the estimation theory is introduced.In view of the problem of how to obtain vehicle state parameters,this paper proposes vehicle quality estimation and road slope estimation methods.In the process of vehicle driving,the road changes and the precision of sensors lead to the inaccuracy of vehicle driving state information,which limits the development of vehicle active safety technology.The longitudinal velocity and yaw velocity of vehicle are very important in active safety control of vehicle.In this paper,vehicle quality estimation by least square quality identification estimator and road slope estimation by full dimensional state observer are studied.Based on the full dimensional state observer theory,a road slope estimator is established for vehicle longitudinal speed,side speed and yaw velocity.Based on the vehicle longitudinal dynamics model,the vehicle mass estimator is established by using the least square estimation method.Due to the complex internal system and the strong coupling between static volumes,in this thesis,according to the dynamic equation of vehicle,the quality of vehicles and road grade are estimated by multiple time scales method,and a vehicle dynamic model established to replace the real vehicle.Then make use of the vehicle dynamics simulation software ve DYNA to operate joint simulation.Finally,the estimator and control algorithm is verified in several typical working conditions and for the result,this estimator and controller has certain accuracy and validity.