Method for improving steering control precision of driving front wheel under limited conditions

Abstract

Disclosed is a method for improving the steering control precision of a driving front wheel under limited conditions. The method is characterized in that a reference model, a tire lateral force and cornering stiffness processor, an MPC and an automobile model are involved. The reference model is used for determining the expected yaw velocity and centroid side slip angle of an automobile; the tirelateral force and cornering stiffness processor is used for determining the side slip angle, lateral force and cornering stiffness of a tire; the automobile model is used for outputting actual motionstate information of the automobile, and the information comprises the longitudinal velocity, yaw velocity, centroid slip angle and road adhesion coefficient of the automobile; the MPC combines the expected yaw velocity and centroid slip angle of the automobile and the actual motion state information of the automobile to optimally calculate the front-wheel additional rotation angle of the automobile, superimposes the front-wheel additional rotation angle with a front-wheel rotation angle generated according to steering input of a driver and outputs a superimposition result to the automobile model to achieve stability control under the extreme conditions.

Description

technical field [0001] The invention relates to the field of vehicle lateral stability control, in particular to a method for improving the control precision of active front wheel steering under extreme working conditions. Background technique [0002] As people pay more and more attention to the safety of automobiles, the active safety systems of automobiles have been developed rapidly, among which the active front steering (Active Front Steering, AFS) technology is widely used as an effective lateral stability control system. At present, the control methods used by AFS mainly include PID control, sliding mode variable structure control and model predictive control (Model Predictive Control, MPC) and other methods, among which model predictive control can better deal with multi-objective tasks and system constraints. The field of stability control has been widely used. [0003] According to different prediction models and optimization methods used, MPC can be divided into ...

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Problems solved by technology

[0004] In order to solve the problems that the existing linear MPC method cannot fully characterize the nonlinear characteristics of tires, the control accuracy of the AFS controller is low and the stability domain is narrow under extreme conditions, the present invention provides an improved active front wheel steering control under extreme conditions When the tire lateral force reaches saturation, the linear time-varying method is used to convert the nonlinear predictive control problem into a linear predictive control problem, which reduces the calculation burden of the system while characterizing the nonlinear characteristics of the tire, and improves the active front. The control accuracy of wheel steering ensures the stability of the car under extreme conditions

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