Hybrid dynamic modeling and optimization control method for longitudinal dynamic system of intelligent automobile

Abstract

The hybrid dynamic modeling and optimization control method for the intelligent automobile longitudinal dynamics system comprises the steps of establishing a whole automobile longitudinal dynamics model, and conducting segmented affine approximation on a nonlinear part existing in the model; based on hybrid dynamic model of the longitudinal dynamic system of the whole vehicle and a prediction control method, converting an intelligent vehicle longitudinal motion control problem into a mixed integer quadratic programming problem for solving to achieve the integration of a system optimization control law, and determining the optimal values of the driving torque and the braking torque and the optimal switching sequence between the driving mode and the braking mode in the intelligent vehicle longitudinal motion control process. The method solves the problems that an existing automobile longitudinal motion control method cannot accurately describe hybrid dynamic characteristics existing in asystem and a driving mode and a braking mode are smoothly switched in the automobile speed adjusting process.

Description

technical field [0001] The invention relates to a hybrid dynamic modeling and optimization control method for a longitudinal dynamics system of an intelligent vehicle, in particular to the longitudinal dynamics control of an intelligent vehicle by using the hybrid system modeling and its optimization control theory, and belongs to the field of motion control of an intelligent vehicle. Background technique [0002] As an important part of the intelligent transportation system, a smart car is a high-tech carrier integrating functions such as environmental perception, planning decision-making, and motion control. It can realize autonomous driving in different road environments and represents an important direction for the future development of automobiles. . Motion control is one of the key links to realize autonomous driving of smart cars. Its research content mainly includes lateral motion control and longitudinal motion control. Among them, longitudinal motion control is of ...

AI Technical Summary

Problems solved by technology

[0003] In order to track the target vehicle speed, the longitudinal motion control process of the smart car must involve the discrete switching between the driving mode and the braking mode. The previous control methods cannot accurately describe the coupling between the continuous dynamic process and the discrete event in the system when modeling. Therefore, in the control strategy design, most of them can only set a fixed threshold as the logical judgment condition for switching the working mode, which will not only reduce the system's adaptive ability, but also cannot avoid the possibility Oscillating behavior, which causes a large longitudinal impact in the process of autonomous driving of smart cars

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