Tire wear degree identification method and device

Abstract

The embodiment of the invention provides a tire wear degree identification method and device. The method comprises the steps that the circumferential acceleration sequence and the radial accelerationsequence of a tire in the driving process are acquired, and the sequences are normalized according to the vehicle speed square of the same moment; the normalized circumferential acceleration sequenceand radial acceleration sequence form a sample to be predicted in the form of a two-dimensional matrix; and the sample to be predicted is inputted to a preset convolutional neural network model, and the wear degree of the tire is determined according to the output result of the convolutional neural network model. According to the method, modeling of the complex mechanism of tire wear can be avoided, and wear degree identification can be realized by analyzing the circumferential and radial acceleration response of the tire so that the method is simpler and more convenient and higher in precision and online real-time prediction can be realized. End-to-end wear degree prediction is performed on the recombined acceleration signal matrix by using the powerful feature extraction function of theconvolutional neural network without too much early pretreatment so as to have robustness for the change of the driving condition.

Description

technical field [0001] The invention relates to the technical field of vehicle engineering, in particular to a tire wear degree identification method and device. Background technique [0002] Tire wear is an unavoidable problem during vehicle driving. Excessive wear will affect the stability of the vehicle during driving and pose a great threat to driving safety. Identifying the degree of tire wear can provide effective information for the driver to judge the current tire health status. [0003] At present, the tire wear degree identification method mainly includes the tread depth estimation method based on the tire acceleration response. The vertical acceleration signal is analyzed to obtain the resonance frequency, and the recursive least square method is used to estimate the parameters to obtain the tread depth. However, this method requires a long time. The estimation time of , and the estimation accuracy depends heavily on the model between the pattern depth and the re...

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Problems solved by technology

[0004] Embodiments of the present invention provide a tire wear degree identification method and device that are robust and can accurately identify the tire wear degree, so as to solve the defects in the prior art

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