Road feeling simulation method based on K-Medoids and classification regression tree

Abstract

The invention discloses a road feeling simulation method based on K-Medoids and a classification regression tree. The method comprises the steps of carrying out a real vehicle test, collecting data, carrying out the preprocessing of test data, carrying out the clustering of normalized test data, dividing training and testing data sets, training and testing a road feeling simulation model based on the K-Medoids and CART regression tree, judging whether the obtained road feeling model meets the requirements or not, and performing road feeling simulation according to the obtained road feeling simulation model based on the K-Medoids and CART regression tree. The input variables of the CART regression tree model are the vehicle longitudinal speed, the vehicle transverse acceleration, the vehicle yaw velocity, the vehicle vertical load, the steering wheel angle and the steering wheel angular velocity, and the output variable of the CART regression tree model is the steering wheel torque. Tests prove that the obtained road feeling simulation model based on the K-Medoids and CART regression tree is high in precision, the modeling process is easy to implement, and the defects in the prior art are overcome to a certain extent.

Description

technical field [0001] The invention relates to the field of vehicles, in particular to a road feeling simulation method based on K-Medoids and classification regression trees. Background technique [0002] Steering road feel, also known as steering force feeling or simply "road feel", refers to the driver's feeling of the movement and force of the vehicle and tires through the steering wheel feedback torque. Steering force sense can enable the driver to obtain the necessary vehicle driving status and driving environment information to a certain extent, so that the driver can make driving decisions in the most suitable way for the current driving conditions to ensure driving safety. For the vast majority of wheeled vehicles running on the road, there is a steering system of the car as a direct mechanical connection between the steering wheel and the steering wheel, and the reaction force of the road to the wheel can be transmitted to the steering wheel through the steering w...

AI Technical Summary

Problems solved by technology

[0004] The object of the present invention is to provide a kind of road feeling simulation method based on K-Medoids and classification regression tree, carry out modeling with real vehicle test data, K-Medoids clustering algorithm and CART regression tree algorithm, obtain based on K-Medoids and CART The road feeling simulation model of the regression tree solves the problems of complex model structure and low precision in traditional mechanism modeling

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