Method for rapidly predicting tire cornering stiffness, computer equipment, storage medium and program product

Abstract

The invention relates to the technical field of tire simulation design, in particular to a method for rapidly predicting tire cornering stiffness, computer equipment, a storage medium and a program product. According to the method, common tire structure factors including apex height, tread groove bottom rubber thickness, steel wire belt angle, steel wire belt width and cushion rubber thickness are selected, an experiment scheme is generated by utilizing an experiment design tool, and a tire cornering stiffness experiment result is recorded. And establishing a function relationship between the structure factor and the cornering stiffness through data analysis. And calculating an undetermined coefficient through data processing, and finally generating an expression for predicting the tire cornering stiffness. According to the method, the cornering stiffness under different tire designs can be quickly and accurately predicted, the prediction efficiency and precision are remarkably improved, tedious calculation of traditional finite element analysis is avoided, and time and cost in the experiment and simulation process are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of tire simulation design, and particularly to a method for quickly predicting the cornering stiffness of a tire, a computer device, a storage medium, and a program product. Background Art

[0002] With the continuous development of the automotive industry, vehicle handling stability and safety have become crucial considerations in the design and manufacturing processes. Among them, as a key component in direct contact with the ground, the performance of the tire has a direct impact on the handling and safety of the vehicle. The cornering stiffness of a tire is an important index for evaluating the tire's response to lateral forces, and it is the ratio between the lateral force and the cornering angle. The cornering stiffness (C_P) reflects the tire's response ability to external forces during driving, and is usually defined as (where F is the lateral force and α is the cornering angle, with the unit of N / degree), and the magnitude of its value directly affects the steering performance, stability, and handling feel of the vehicle.

[0003] Currently, there are mainly two methods for testing the cornering stiffness of a tire: one is to obtain the cornering stiffness value through experimental measurement, and the other is to predict it through simulation methods such as finite element analysis (FEA). However, traditional experimental methods usually require a large amount of time and resources, and the cost is extremely high when conducting a large number of tests under different vehicle models and different design schemes; while the finite element analysis method requires the establishment of complex models and cumbersome rolling simulations, with a large amount of calculation and a long simulation time. These methods often cannot meet the actual development requirements due to the excessive calculation burden during the tire design and optimization processes.

[0004] In addition, existing tire designs usually need to consider the interaction of multiple design factors, and there are numerous structural design factors for tires, and the influence of each factor on the cornering stiffness is also non-linear. Traditional simulation calculations often cannot efficiently and accurately reflect the changes in the cornering stiffness of the tire when dealing with these complex relationships. This makes it necessary for designers to continuously adjust design parameters in multiple rounds of experiments and simulations during the actual tire design process in order to find the optimal design scheme. Summary of the Invention

[0005] In order to solve the above technical problems, the purpose of the present invention is to provide a method for quickly, accurately, and efficiently predicting the cornering stiffness of a tire, which is of great significance for tire design optimization. It can directly obtain the predicted value of the cornering stiffness of the tire through simple parameter input, avoiding the cumbersome simulation and testing processes, not only reducing the design verification cycle, but also accelerating the R & D process of the tire, thereby improving the efficiency and reliability of tire design.

[0006] In order to achieve the above purpose, the present invention adopts the following technical solutions:

[0007] A method for quickly predicting the cornering stiffness of a tire, which uses the following functional expression to quickly predict the cornering stiffness of the tire:

[0008] CP = (1 + 0.002 * Δa - 0.07 * Δb - 0.005 * Δc - 0.001 * Δd - 0.01 * Δe) * CP r ;

[0009] where CP is the predicted cornering stiffness value of the tire, and CP r is the cornering stiffness value of the reference tire, and Δa to Δe are the change amounts of the structural parameters of the height a of the chafer, the rubber thickness b at the bottom of the tread groove, the angle c of the steel belt layer, the width d of the steel belt layer, and the thickness e of the cushion rubber in sequence.

[0010] Preferably, the designed change in the height a of the chafer is ±10 mm; the designed change in the rubber thickness b at the bottom of the tread groove is ±0.6 mm; the designed change in the angle c of the steel belt layer is ±5°; the designed change in the width d of the steel belt layer is ±8 mm; the designed change in the thickness e of the cushion rubber is ±0.8 mm.

[0011] Furthermore, the present invention also provides a method for establishing the functional expression of the method, which is characterized in that the method includes the following steps:

[0012] 1) Select the structural factors affecting the cornering stiffness of the tire, and define at least five structural variables, where the structural variables include the height a of the chafer, the rubber thickness b at the bottom of the tread groove, the angle c of the steel belt layer, the width d of the steel belt layer, and the thickness e of the cushion rubber;

[0013] 2) Use an experimental design tool to determine the change range of each structural variable through experimental design, and record the corresponding experimental results of the cornering stiffness;

[0014] 3) Analyze the influence trend of each structural factor, and construct the functional relationship between each factor and the cornering stiffness;

[0015] 4) Through data processing, calculate the undetermined coefficients affecting each structural factor, and establish the functional expression of each factor on the cornering stiffness;

[0016] 5) Use the obtained functional expression to predict the cornering stiffness under different tire structures.

[0017] Preferably, the experimental design tool is Minitab software, and the design tool generates an experimental plan and conducts changes in structural factors at at least five levels.

[0018] Preferably, the functional relationship includes a linear relationship, a parabolic relationship, a logarithmic relationship, or other function types obtained through experiments.

[0019] Preferably, the undetermined coefficients are calculated through Matlab data processing, and the coefficients affecting the structure factor are obtained by solving; preferably, the undetermined coefficients are solved by the least squares method.

[0020] Preferably, the method further includes predicting the tire cornering stiffness according to the generated function expression and comparing and verifying it with the measured result.

[0021] Furthermore, the present invention also provides a computer device, including a memory, a processor, and a computer program stored on the memory, and the processor executes the computer program to implement the method.

[0022] Furthermore, the present invention also provides a computer-readable storage medium, on which a computer program or instruction is stored, and when the computer program or instruction is executed by a processor, the method is implemented.

[0023] Furthermore, the present invention also provides a computer program product, including a computer program or instruction, and when the computer program or instruction is executed by a processor, the method is implemented.

[0024] Due to the adoption of the above technical solution, the present invention simplifies the traditional experimental measurement and simulation calculation processes, and significantly improves the efficiency and accuracy of tire cornering stiffness prediction. Compared with the existing finite element analysis method and the cumbersome experimental test, the technical solution of the present invention has the following remarkable technical effects:

[0025] 1. High prediction accuracy: The present invention selects common tire structure factors and combines with a polynomial regression model to establish a functional relationship between the structure factor and the cornering stiffness. Through experimental design and data analysis, it can accurately reflect the influence of different design factors on the tire cornering stiffness, thereby effectively predicting the tire cornering stiffness. The experimental results show that the error between the predicted cornering stiffness of the present invention and the measured value is within 8.36%, and the prediction effect on different tire models is good, verifying the high accuracy of the method.

[0026] 2. High calculation efficiency: Compared with the traditional finite element analysis method, the polynomial prediction method based on the change of the structure factor adopted by the present invention avoids complex rolling simulation calculations, significantly reduces the calculation amount. Using the pre-constructed polynomial expression, the cornering stiffness of different tire design schemes can be quickly calculated, greatly shortening the prediction time. This method can achieve real-time prediction and is suitable for the rapid iteration and optimization of tire design.

[0027] 3. Easy to operate: The prediction method of the present invention can be calculated by simply inputting tire structure factors (such as the height of the apex rubber, the thickness of the rubber at the bottom of the tread groove, the angle of the steel belt layer, etc.) and experimental data, without the need for complex simulation software or high-performance computing resources, and has strong operational convenience. Designers can quickly obtain the prediction results of the cornering stiffness without relying on large-scale simulation tools, improving the work efficiency in the design process.

[0028] 4. Wide applicability: The method and system of the present invention are applicable to various types of radial tires and can predict the cornering stiffness for different tire structures and design requirements. By selecting appropriate design factors and experimental parameters, accurate prediction data can be provided for tires of different models and specifications, with good generality and scalability.

[0029] 5. Cost reduction: Since the method of the present invention can reduce the need for complex simulations and a large number of experiments, it saves time and costs in the development process. Designers do not need to conduct comprehensive tests and simulation analyses for each design scheme, and the tire design verification cycle can be significantly shortened through rapid prediction, reducing the R & D cost.

[0030] In summary, the method and system for quickly predicting the cornering stiffness of tires provided by the present invention provide an efficient and reliable new tool for tire design and optimization by simplifying the process, improving the prediction accuracy, accelerating the calculation speed, and reducing the cost, with significant technical advantages and broad application prospects. Brief Description of the Drawings

[0031] Figure 1 Schematic diagram of tire design factors. a, b, c, d, e;

[0032] Figure 2 Main effect diagram of each factor in Taguchi design;

[0033] Figure 3 Prediction and measured results prediction for different tire models. Detailed Embodiment

[0034] The following combines the embodiments of the present invention, and clearly and completely describes the technical solutions in the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0035] This embodiment is implemented on the premise of the technical solution of the present invention. Taking the tire 205 / 55R16 as an example (the reference structure corresponds to the cornering stiffness CP under the conditions of air pressure 230 kPa and load 6750 N) r=1600N / degree is known), and detailed implementation methods are given, but the protection scope of the present invention is not limited to the following embodiments.

[0036] The first step is to select the commonly used tire structural factors. Considering the standardization of the design and the factors affecting the cornering stiffness reported in the literature, the selected tire structural variables are: apex height (a), rubber thickness at the bottom of the groove (b), steel belt layer angle (c), steel belt layer width (d), cushion rubber thickness (e). Figure 1 .

[0037] In the second step, the experimental design was done using Minitab software. Five structural variables were selected with a range of five levels, namely experimental plan L25. The range of variation of each factor needs to be identified according to the actual limitations of the project. The design variation of the apex height a is ±10mm. The design variation of the rubber thickness b at the bottom of the groove is ±0.6mm. The design variation of the steel belt layer angle c is ±5°, the design variation of the steel belt layer width d is ±8mm, and the design variation of the cushion rubber thickness e is ±0.8mm. Then, the corresponding tire cornering stiffness test results are recorded. See Table 1 for details.

[0038] Table 1 Taguchi design and experimental results

[0039]

[0040]

[0041] The third step is to extract the main effect of each factor on the tire cornering stiffness according to the analysis results of Minitab software. See the figure for details. Considering the influence of experimental error and the graphical trend of the main effect, the relationship between the tire cornering stiffness and each factor is constructed to be a linear change and has the following relationship:

[0042] CP=(1+k 1 *Δa+k 2 *Δb+k 3 *Δc+k 4 *Δd+k 5 *Δe)*CP r (0.1)

[0043] In the fourth step, according to the relationship between each test scheme and the corresponding result data (Table 1) and the constructor, there are 25 equations as follows:

[0044]

[0045] The above equations can be expressed as a matrix of X*k=b, where X is a matrix of 25 rows and 5 columns:

[0046]

[0047] The vector k [k 1 , k 2 , k 3 , k 4 , k 5 ’ is an unknown column vector. It can be obtained by left-multiplying the inverse matrix X on both sides of the equation. -1 Since the number of equations is greater than the number of unknowns, it is an overdetermined system of equations. Use the least squares method of the built-in function pinv in Matlan to solve, k = Pinv(X)*b; obtain k 1 = 0.002, k 2 = -0.07, k 3 = -0.005, k 4 = -0.001, k 5 = -0.01. Substitute k 1 ~k 5 into the constructor expression, that is:

[0048] CP = (1 + 0.002*Δa - 0.07*Δb - 0.005*Δc - 0.001*Δd - 0.01*Δe)*CP r (0.4)

[0049] Fifth step, adjust the design values of the 5 factors and use the expression obtained in the 4th step to predict and measure the cornering stiffness of the tire model 205 / 55R16, as shown in Table 2; in addition, select tire models 235 / 45R18 (model 2), 255 / 45R20 (model 3), 235 / 55R19 (model 4), 215 / 65R16 (model 5) respectively for the prediction and measurement of the tire cornering stiffness, see Figure 3 .

[0050] Table 2 Prediction results and experimental results of the cornering stiffness of tire model 205 / 55R16

[0051]

[0052] From Table 2, Figure 3 it can be seen that the error between the cornering stiffness of the tire predicted (predicted) by the method of this patent and the measured result is within 8.36%, and there is also a good corresponding trend in the applications of different tire models, which proves the effectiveness of the method of this patent.

[0053] The foregoing is a description of embodiments of the present invention. Through the above description of the disclosed embodiments, those skilled in the art can implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for quickly predicting tire cornering stiffness, characterized in that: This method uses the following function expression to quickly predict the tire cornering stiffness: ； Where CP is the predicted tire cornering stiffness value, CP r is the cornering stiffness of the reference tire, ∆a~∆e are the changes in structural parameters of the apex rubber height a, the rubber thickness at the bottom of the tread groove b, the steel belt layer angle c, the steel belt layer width d, and the cushion rubber thickness e.

2. A method for rapidly predicting tire cornering stiffness according to claim 1, characterized in that: The design variation of the apex rubber height a is ±10mm; the design variation of the rubber thickness b at the bottom of the groove is ±0.6mm; the design variation of the steel belt layer angle c is ±5°; the design variation of the steel belt layer width d is ±8mm; the design variation of the pad rubber thickness e is ±0.8mm.

3. The method for establishing the function expression of the method according to claim 1, characterized in that: The method comprises the following steps: 1) selecting structural factors that affect the cornering stiffness of the tire and defining at least five structural variables, wherein the structural variables include apex rubber height a, rubber thickness b at the bottom of the tread groove, steel belt layer angle c, steel belt layer width d, and cushion rubber thickness e; 2) using an experimental design tool to determine the variation range of each structural variable through experimental design, and recording the corresponding cornering stiffness experimental results; 3) analyzing the influence trend of each structural factor, and constructing a functional relationship between each factor and the cornering stiffness; 4) calculating the undetermined coefficients that affect each structural factor through data processing, and establishing a functional expression of each factor on the cornering stiffness; 5) using the obtained functional expression to predict the cornering stiffness under different tire structures.

4. The method according to claim 3, characterized in that The experimental design tool is Minitab software, and the design tool generates an experimental plan to perform structural factor changes at least at five levels.

5. The method according to claim 3, characterized in that: The functional relationship includes a linear relationship, a parabolic relationship, a logarithmic relationship or other function types obtained through experiments.

6. The method according to claim 3, characterized in that The undetermined coefficients are calculated by Matlab data processing, and the coefficients affecting the structure factor are solved; preferably, the undetermined coefficients are solved by the least square method.

7. The method according to claim 3, characterized in that The method also includes predicting the tire cornering stiffness based on the generated function expression and comparing and verifying it with the actual measured results.

8. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the method according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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