Intelligent electric vehicle trajectory tracking and motion control method

Abstract

The invention discloses an intelligent electric vehicle trajectory tracking and motion control method which comprises the following steps: judging whether a vehicle can work in a lateral stable rangeor not according to a given target trajectory and a current road condition; if the vehicle works in the stable area, executing the step 2; if the lateral stability range is exceeded, executing the step 3; 2, executing a working mode 1, and performing vehicle trajectory tracking and stability control by adopting vehicle trajectory tracking and yawing stability double closed-loop control: calculating an expected course angle of a vehicle according to an expected driving trajectory and a vehicle kinematics model; establishing a three-degree-of-freedom vehicle dynamic model, designing a trajectorytracking controller, inputting the difference between the expected course angle of the vehicle and the course angle of the previous moment into the trajectory tracking controller, and solving to obtain a front wheel rotation angle and a longitudinal speed; designing a yaw stability controller by adopting a model predictive control algorithm and then carrying out moment distribution; and 3, executing a working mode 2, and carrying out drifting control on vehicle trajectory tracking.

Description

technical field [0001] The invention relates to a control method belonging to the field of optimal control of the chassis of a four-wheel hub-driven electric vehicle. More specifically, the invention relates to a smart vehicle trajectory tracking and stability control method based on switching control, involving the kinematics of the vehicle With dynamic control, it can improve the handling, stability and comfort of the vehicle. Background technique [0002] With the society's demand for intelligent, low-carbon and lightweight vehicles, the development of smart electric vehicles has become an important way to improve vehicle safety, reduce environmental pollution and save energy. Traditional active safety control systems have been unable to meet the current complex traffic conditions. environment, so it is particularly important for the development of the electronic control system of smart electric vehicles. The traditional control method mainly considers separately the tra...

AI Technical Summary

Problems solved by technology

[0004] 1. Trajectory tracking controllers and motion controllers at this stage can better track the desired trajectory to ensure the stability of the vehicle under certain conditions, but there are few studies on the factors affecting the adhesion conditions and vehicle speed. It is difficult to ensure the stability and ride comfort of the vehicle on complex road surfaces

[0005] 2. Most of the current research on trajectory tracking and dynamics control of smart vehicles adopts a separate design of the trajectory tracking controller and the vehicle yaw stability controller, and the two controllers have a common actuator (such as steering motor and drive motor) , will cause control conflicts, especially in complex road conditions or high-speed driving, which will reduce the driving safety of the vehicle

[0006] 3. Trajectory tracking control and vehicle dynamics control at the present stage are mainly based on model-based controller design, which is highly dependent on the environment and parameter selection, that is, when the environment changes suddenly, it cannot adapt well to the new state conditions. Tracking

However, in real life, it cannot be guaranteed that the vehicle can simply work in simple or complex working conditions. Obviously, the trajectory tracking controller at this stage cannot meet the vehicle trajectory tracking under all working conditions.

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