CN-122016350-A - Method and device for predicting tire wear, electronic equipment and computer program product

CN122016350ACN 122016350 ACN122016350 ACN 122016350ACN-122016350-A

Abstract

The application discloses a method and a device for predicting tire wear, electronic equipment and a computer program product. The method comprises the steps of obtaining longitudinal acceleration, slip angle and road spectrum excitation data of a tire to be detected of a vehicle, wherein the longitudinal acceleration is used for determining tire longitudinal force of the tire to be detected, the road spectrum excitation data is used for determining tire normal force of the tire to be detected, determining slip rates corresponding to the tire longitudinal force and the tire normal force according to a preset slip rate table, analyzing the slip angle and the slip rate by adopting a friction energy model under preset composite slip conditions to obtain friction energy density of a contact surface of the tire to be detected on a unit area, wherein the friction energy density is a direct physical representation of abrasion loss rate, and predicting abrasion of the tire to be detected according to the friction energy density. The application solves the technical problem of low prediction precision of the tire abrasion in the prior art.

Inventors

Pang Hongcheng
YAO BING

Assignees

赛轮集团股份有限公司

Dates

Publication Date: 20260512
Application Date: 20260120

Claims (10)

1. A method of predicting wear of a tire, comprising: acquiring longitudinal acceleration, slip angle and road spectrum excitation data of a tire to be detected of a vehicle, wherein the longitudinal acceleration is used for determining tire longitudinal force of the tire to be detected, the slip angle represents an angle between a contact surface of the tire to be detected and a running direction of the vehicle, and the road spectrum excitation data represents road surface unevenness and is used for determining tire normal force of the tire to be detected; Determining a slip rate corresponding to the tire longitudinal force and the tire normal force according to a preset slip rate table, wherein the preset slip rate table is used for representing the mapping relation between the tire longitudinal force, the tire normal force and the slip rate, and the slip rate is used for representing the relative movement of the contact surface of the tire to be detected and the ground; Analyzing the slip angle and the slip rate by adopting a friction energy model under a preset composite slip condition to obtain the friction energy density of the contact surface of the tire to be detected on a unit area, wherein the friction energy density is a direct physical representation of the abrasion loss rate; And predicting the abrasion of the tire to be detected according to the friction energy density.
2. The method according to claim 1, characterized in that before acquiring the longitudinal acceleration, slip angle and road spectrum excitation data of the tyre to be detected of the vehicle, the method further comprises: Acquiring a vehicle running state of the vehicle, wherein the vehicle running state comprises a straight line state, a general turning state and a violent turning state; Determining the slip angle of the tire to be detected on a steering shaft of the vehicle according to the running state of the vehicle; determining the slip angle of the tire to be detected on the non-steering shaft of the vehicle according to the slip angle of the tire to be detected on the steering shaft of the vehicle and a preset steering scaling coefficient between the steering shaft and the non-steering shaft, wherein the steering scaling coefficient is determined at least according to the geometric relationship between the steering shaft and the non-steering shaft on the vehicle and a pulling structure between the steering shaft and the non-steering shaft.
3. The method of claim 2, wherein the non-steering shaft includes a drive shaft and a trailing axle, and determining the slip angle of the tire to be detected on the non-steering shaft of the vehicle based on the slip angle of the tire to be detected on the steering shaft of the vehicle and a preset steering scaling factor between the steering shaft and the non-steering shaft includes: determining a first scaling factor based on a geometric relationship between the steering shaft and the drive shaft on the vehicle and a hitch structure between the steering shaft and the drive shaft, and determining the slip angle of the tire to be detected on the drive shaft of the vehicle based on a product of the first scaling factor and the slip angle of the tire to be detected on the steering shaft of the vehicle; And determining the slip angle of the tire to be detected on the trailing axle of the vehicle according to the product of the second scaling factor and the slip angle of the tire to be detected on the steering axle of the vehicle.
4. The method according to claim 1, wherein after acquiring longitudinal acceleration, slip angle and road spectrum excitation data of a tire to be detected of the vehicle, the method further comprises: Acquiring a vehicle running state of the vehicle, wherein the vehicle running state comprises a straight line state, a general turning state and a violent turning state; And determining a fluctuation standard deviation of random fluctuation of the slip angle according to the vehicle running state, wherein the fluctuation standard deviation is used for representing the random distribution degree of the slip angle under different vehicle running states, and the fluctuation standard deviation of the slip angle under the straight line state is smaller than the fluctuation standard deviation of the slip angle under the general turning state and smaller than the fluctuation standard deviation of the slip angle under the violent turning state.
5. The method according to claim 1, wherein after acquiring longitudinal acceleration, slip angle and road spectrum excitation data of a tire to be detected of the vehicle, the method further comprises: acquiring the whole vehicle quality of the vehicle; determining the tire longitudinal force of the tire to be detected on a drive shaft of the vehicle according to the product of the whole vehicle mass and the longitudinal acceleration; And determining the tire longitudinal force of the tire to be detected on a non-driving shaft of the vehicle according to the tire longitudinal force of the tire to be detected on the driving shaft of the vehicle and a preset normal scaling factor between the driving shaft and the non-driving shaft, wherein the normal scaling factor is determined at least according to the axle load ratio of the driving shaft and the non-driving shaft.
6. The method according to claim 1, wherein after acquiring longitudinal acceleration, slip angle and road spectrum excitation data of a tire to be detected of the vehicle, the method further comprises: and analyzing the road spectrum excitation data by adopting a preset vehicle dynamics model, and determining the normal force of the tire to be detected caused by road fluctuation, wherein the vehicle dynamics model is used for describing the stress influence of road surface unevenness, vehicle mass change and vehicle suspension dynamics on the tire to be detected.
7. The method according to claim 1, wherein after acquiring longitudinal acceleration, slip angle and road spectrum excitation data of a tire to be detected of the vehicle, the method further comprises: dividing the tread of the tire to be detected into a plurality of longitudinal rib pattern areas; and determining the tire normal force of each longitudinal rib pattern area according to the position of each longitudinal rib pattern area on the tread.
8. A tire wear prediction apparatus, comprising: The system comprises an acquisition module, a detection module and a detection module, wherein the acquisition module is used for acquiring longitudinal acceleration, a slip angle and road spectrum excitation data of a tire to be detected of a vehicle, wherein the longitudinal acceleration is used for determining tire longitudinal force of the tire to be detected, the slip angle represents an angle between a contact surface of the tire to be detected and a running direction of the vehicle, and the road spectrum excitation data represents road surface unevenness and is used for determining tire normal force of the tire to be detected; The determining module is used for determining the slip rate corresponding to the tire longitudinal force and the tire normal force according to a preset slip rate table, wherein the preset slip rate table is used for representing the mapping relation between the tire longitudinal force and the tire normal force and the slip rate, and the slip rate is used for representing the relative movement of the contact surface of the tire to be detected and the ground; The analysis module is used for analyzing the slip angle and the slip rate by adopting a friction energy model under a preset composite slip condition to obtain the friction energy density of the contact surface of the tire to be detected on a unit area, wherein the friction energy density is a direct physical representation of the abrasion loss rate; And the prediction module is used for predicting the abrasion of the tire to be detected according to the friction energy density.
9. An electronic device comprising a memory and a processor for executing a program stored in the memory, wherein the program is executed to perform the method of predicting tire wear as claimed in any one of claims 1 to 7.
10. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, carries out the steps of the method for predicting tyre wear as claimed in any one of claims 1 to 7.

Description

Method and device for predicting tire wear, electronic equipment and computer program product Technical Field The present application relates to the field of tire dynamics, and in particular, to a method, apparatus, electronic device, and computer program product for predicting tire wear. Background Tire wear is a key technical problem which cannot be ignored in the running process of heavy-duty vehicles, not only directly affects the service life of tires and the running economy of vehicles, but also becomes an important source of non-tail gas particulate matter emission in road traffic. Under the heavy load working condition, the vehicle often bears a larger axle load and a complex stress environment, and the abrasion strength is obviously higher than that of a passenger car scene, so that the abrasion prediction problem of the vehicle has important practical significance in engineering development. The current tire wear prediction method in the industry mainly comprises two major categories, namely an empirical regression model and a finite element simulation model. The empirical regression method relies on a large amount of test data, and establishes a correlation model between the abrasion loss and variables such as load, speed, tire pressure, temperature and the like in a statistical mode, and has low implementation cost and simple structure, but the application range of the model is limited, the sensitivity of the model to the vehicle structure, road condition change and randomized working condition is insufficient, and the differential abrasion behavior among the transverse rib of the tread is difficult to be described. The Finite Element (FEA) method can accurately solve tread contact pressure, shear stress and local slip distribution under static or quasi-static conditions, has higher precision on a theoretical level, but has complex modeling and huge calculation amount, is difficult to meet the prediction requirements under the conditions of long mileage, random excitation and multi-factor coupling, and is also difficult to realize real-time or quasi-real-time data interaction with a whole vehicle dynamics model. Aiming at the problem of low prediction precision of tire abrasion in the prior art, no effective solution is proposed at present. Disclosure of Invention The embodiment of the application provides a method, a device, electronic equipment and a computer program product for predicting tire wear, which are used for at least solving the technical problem of low prediction accuracy of the tire wear in the prior art. According to one aspect of the embodiment of the application, a prediction method of tire wear is provided, which comprises the steps of obtaining longitudinal acceleration, slip angle and road spectrum excitation data of a tire to be detected of a vehicle, wherein the longitudinal acceleration is used for determining the tire longitudinal force of the tire to be detected, the slip angle is used for indicating the angle between the contact surface of the tire to be detected and the running direction of the vehicle, the road spectrum excitation data is used for determining the tire normal force of the tire to be detected, the slip rate corresponding to the tire longitudinal force and the tire normal force is determined according to a preset slip rate table, the preset slip rate table is used for indicating the mapping relation between the tire longitudinal force and the tire normal force and the slip rate, the slip rate is used for indicating the relative movement between the contact surface of the tire to be detected and the ground, the slip rate is analyzed by adopting a friction energy model under a preset composite slip condition, and the friction energy density of the contact surface of the tire to be detected is obtained, and the friction energy density is the friction energy density to be predicted according to the physical wear is the direct wear. Optionally, before acquiring longitudinal acceleration, slip angle and road spectrum excitation data of a tire to be detected of a vehicle, the method further comprises acquiring vehicle driving states of the vehicle, wherein the vehicle driving states comprise a straight line state, a general turning state and a hard turning state, determining the slip angle of the tire to be detected on a steering shaft of the vehicle according to the vehicle driving states, determining the slip angle of the tire to be detected on the steering shaft of the vehicle according to a preset steering scaling factor between the steering shaft and a non-steering shaft, and determining the slip angle of the tire to be detected on the non-steering shaft of the vehicle according to at least a geometric relation between the steering shaft and the non-steering shaft on the vehicle and a pulling structure between the steering shaft and the non-steering shaft. Optionally, the non-steering shaft comprises a driving shaft and a trailing axle, the determining of