Tire noise evaluation method

Abstract

To provide a tire noise evaluation method that allows for quick, highly accurate estimation of noise levels at operating temperatures during tire acceleration, while also reducing the effort and cost required for noise evaluation at operating temperatures. [Solution] The tire noise evaluation method of this disclosure evaluates tire noise during vehicle acceleration. The tire noise evaluation method of this disclosure estimates the driving force sensitivity based on the change in noise when the vehicle's driving force changes, divided by the change in the driving force, based on the characteristics of the tire and the temperature characteristics of the tire, and evaluates the noise during acceleration based on the estimated driving force sensitivity.

Description

Technical Field

[0001] The present disclosure relates to a method for evaluating tire noise.

Background Art

[0002] Conventionally, as a method for evaluating tire noise during tire rotation, as disclosed in Patent Document 1, a method of measuring the noise of a tire generated by bringing the tire into contact with and running on a rotating drum having a simulated road surface on its outer peripheral surface with a noise measuring instrument is known.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the tire noise evaluation method of Patent Document 1, after the tire is prototyped, the prototyped tire has to be installed on a test machine to collect noise, and the noise evaluation of the tire cannot be performed in a short time, and the labor and cost required for the noise evaluation of the tire also increase. Also, it is known that tire noise increases during acceleration when a driving force acts. Therefore, there is a demand to accurately evaluate the acceleration noise during the acceleration running of a vehicle. Furthermore, as will be described in detail below, the inventor of the present case has found through numerous tests that acceleration noise may have temperature dependence. In such a background, it is preferable if tire noise can be accurately evaluated for each use temperature. Therefore, an object of the present disclosure is to provide a tire noise evaluation method that can accurately estimate, in a short time and with ease, the noise evaluation at the use temperature during tire acceleration running, and can also reduce the labor and cost required for the noise evaluation at the use temperature.

Means for Solving the Problems

[0005] To solve the above problems, the tire noise evaluation method according to this disclosure is a method for evaluating tire noise during acceleration of a vehicle, wherein the method estimates a driving force sensitivity based on the characteristics of the tire and the temperature characteristics of the tire, which is obtained by dividing the amount of change in noise when the driving force of the vehicle changes by the amount of change in the driving force, and evaluates the noise during acceleration based on the estimated driving force sensitivity.

[0006] The driving force sensitivity at operating temperature may be evaluated based on tire characteristics having a temperature dependence of 1 or more, or it may be mechanically calculated based on data on the contribution of each tire characteristic to the driving force sensitivity at operating temperature, which has been determined in advance by prior testing.

[0007] According to this disclosure, noise at operating temperatures during tire acceleration is evaluated based on the driving force sensitivity estimated based on tire characteristics and tire temperature characteristics. Therefore, it is easier to accurately estimate noise at operating temperatures during tire acceleration.

[0008] Furthermore, according to this disclosure, tire noise during acceleration is estimated and evaluated based on the driving force sensitivity estimated without conducting tests. Therefore, the noise at the operating temperature during tire acceleration can be estimated in a short time, and the effort and cost required for noise evaluation at that operating temperature can be significantly reduced.

[0009] A tire noise evaluation method according to claim 1, wherein a third noise is estimated as the noise when the vehicle is accelerating with the driving force, by adding a second noise obtained by multiplying the driving force sensitivity by the driving force to a first noise generated when the vehicle is coasting.

[0010] With this configuration, when estimating the third noise (corresponding to tire noise during acceleration) for a specific driving force, the third noise for that driving force can be instantly estimated simply by substituting the driving force into a linear equation for calculating the third noise, where the driving force is the variable.

[0011] Furthermore, the tire noise evaluation method according to claim 1 or 2, wherein the driving force sensitivity is estimated based on one or more design factors.

[0012] This configuration makes it easier to systematically and objectively estimate driving force sensitivity using design factors.

[0013] Alternatively, the temperature characteristics of the driving force sensitivity may be estimated based on a plurality of design factors, and the contribution of each design factor to the temperature characteristics of the driving force sensitivity may be evaluated based on experimental design.

[0014] This configuration makes it easy to efficiently and accurately evaluate the contribution of each tire design factor to driving force sensitivity at different operating temperatures. Therefore, by focusing on design factors that have a high contribution to driving force sensitivity, it becomes easier to accurately estimate tire noise at operating temperatures during acceleration. [Effects of the Invention]

[0015] According to the tire noise evaluation method described herein, it is possible to estimate the noise level at the operating temperature during tire acceleration driving in a short time with high accuracy, and the effort and cost required for noise evaluation at said operating temperature can also be reduced. [Brief explanation of the drawing]

[0016] [Figure 1] This is an L8 orthogonal array of the four design factors in a noise test conducted on a test bench. [Figure 2] This graph shows the relationship between driving force and noise for each tire. [Figure 3] This graph shows the slope of the linear equation applied to each tire and the coefficient of determination R². [Figure 4] This is an analysis of variance (ANOVA) table based on tests conducted by the inventor, and is an example of an ANOVA table when the design factors are A, B, C, D, A and B, and A and C. [Figure 5] This graph shows the change in the slope of the linear equation when each design factor is changed from its baseline value. [Figure 6]It is a graph showing an analysis of variance table regarding the noise of tires with other basic specifications in actual vehicle tests. [Figure 7] It is a graph corresponding to FIG. 5 in the tires of the basic specifications showing the analysis of variance table of noise in FIG. 6. [Figure 8] It is an orthogonal table of two design factors in the noise test which is a bench test. [Figure 9] It is a graph showing the relationship between the driving force and the overall noise level of the outside vehicle noise in the actual vehicle test in winter. [Figure 10] It is a graph showing the relationship between the driving force and the overall noise level of the outside vehicle noise in the actual vehicle test in summer. [Figure 11] It is a graph showing the comparison of the slopes of the solid line, dotted line, and dashed-dotted line in FIGS. 9 and 10. [Figure 12] It is a graph showing the relationship between the air temperature and the driving force sensitivity in three tires. [Figure 13] It is a graph showing the relationship between the temperature and the driving force sensitivity in three tires in the actual vehicle test.

Modes for Carrying Out the Invention

[0017] Hereinafter, embodiments according to the present disclosure will be described in detail with reference to the accompanying drawings. In the following, when a plurality of embodiments, modification examples, etc. are included, it is assumed from the beginning that new embodiments can be constructed by appropriately combining their characteristic parts. Also, in the following examples, the same components are denoted by the same reference numerals in the drawings, and overlapping explanations are omitted. Further, in this specification, coasting noise refers to the noise of the tire when the vehicle is coasting, and acceleration noise refers to the noise of the tire when the vehicle is accelerating. Also, among the components described below, components not described in the independent claims indicating the highest-level concept are arbitrary components and not essential components.

[0018] [Method for Evaluating Acceleration Noise Without Considering Environmental Temperature] First, we will explain a method for evaluating acceleration noise without considering ambient temperature, and without conducting tests that evaluate acceleration noise using a test machine including a simulated road surface (hereinafter simply referred to as a bench test) or tests that evaluate acceleration noise by driving a vehicle with actual tires (hereinafter simply referred to as a real vehicle test).

[0019] The inventors investigated the relationship between vehicle driving force and tire noise by conducting numerous bench tests and actual vehicle tests on a large number of tires with varying design factors (design elements, design variables, and design factors). Some of these tests will now be described. A bench test, as disclosed in Patent Document 1, is a test in which tire noise is measured using a noise meter by running a tire on a rotating drum with a simulated road surface on its outer circumference.

[0020] Figure 1 shows the L8 orthogonal array of the four design factors in a noise test conducted on a test bench. By using the L8 orthogonal array, it is possible to identify the combination of design factors that contributes significantly to noise using only 8 tires, without having to test 24 tires with different combinations of the four design factors, while significantly reducing the amount of work required. In the example shown in Figure 1, the identification of each tire is determined by the four design factors (design elements) A, B, C, and D.

[0021] Design factors include the effective contact area [contact area excluding grooves] (the area of ​​regions divided axially is also acceptable, and their ratios are also design factors). Examples of regions divided axially include the center, quarter, and shoulder. Other design factors include, for example, the area ratio of the land portion of the contact area to the total area including grooves (the area of ​​regions divided axially is also acceptable, and their ratios are also design factors), the effective contact ratio of the ribs, the number of pitches [the number of circumferential blocks around the circumference of the tire], the hardness of the tread rubber, the belt width [the axial width of the belt when viewed in cross-section], the belt angle [the angle of the belt ply relative to the circumferential direction], the number of belt ends [the number of cords per inch of the belt ply], the Young's modulus of the tread rubber, the elastic modulus of the tread rubber, the tanδ (loss tangent) of the tread rubber, the carcass ply material, the Young's modulus of the carcass ply, the number of carcass ply ends, the hardness of the bead filler, the Young's modulus of the bead filler, and the bead filler height [the radial length of the bead filler].

[0022] Figure 1 shows the results of an analysis of four of the design factors listed above. In Figure 1, each design factor is presented as one of two options. In the design factor column, "base" indicates that the design factor is at the baseline value, "+" indicates that the design factor is greater than the baseline value, and "-" indicates that the design factor is less than the baseline value. As shown in Figure 1, tire 1 is a tire in which all four design factors are at the baseline value. Tire 2 is a tire in which design factors A and B are at the baseline value, while design factor C is less than the baseline value and design factor D is greater than the baseline value.

[0023] Tire 3 is a tire in which design factors A and C are at the standard values, while design factor B is smaller than the standard value and design factor D is larger than the standard value. Tire 4 is a tire in which design factors A and D are at the standard values, while design factor B is smaller than the standard value and design factor C is smaller than the standard value. Tire 5 is a tire in which design factors B and C are at the standard values, while design factor A is larger than the standard value and design factor D is larger than the standard value.

[0024] Tire 6 is a tire in which design factors B and D are at the standard value, while design factor A is greater than the standard value and design factor C is smaller than the standard value. Tire 7 is a tire in which design factors C and D are at the standard value, while design factor A is greater than the standard value and design factor B is smaller than the standard value. Tire 8 is a tire in which design factor A is greater than the standard value, design factor B is smaller than the standard value, design factor C is smaller than the standard value, and design factor D is greater than the standard value.

[0025] Figure 2 is a graph showing the relationship between driving force and noise for each tire. The noise on the vertical axis of Figure 2 is the noise measured by a microphone, and is the sum of the power of the power spectrum in the frequency band between 500 kHz and 1500 Hz of the measured sound pressure. Based on the measured values ​​for each tire, the inventors applied the relationship between driving force and noise to the linear equation Y = aX + b for each tire. The application to the linear equation was performed using the least squares method. To determine whether this application was appropriate, the inventors calculated the coefficient of determination R2 shown in equation (1) below for each tire using the calculated linear equation.

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[0026] In Equation 1, yi is the measured noise level, and the yi hat is the noise level in a linear equation at the same driving force as yi. The y bar is the average of the measured noise levels. The coefficient of determination R² is an index with a maximum value of 1, and is used to determine whether the fit is appropriate or not. The closer the R² value is to 1, the better the fit is indicated, and roughly speaking, if the value is greater than about 0.7, it can be judged that the fit is appropriate.

[0027] In Equation 1, if all measured values ​​lie on the fitted linear equation, then for each i, the value obtained by subtracting the yi-hat from yi becomes 0. Therefore, the coefficient of determination R² shown in Equation (1) is 1. From this, it can be seen that the closer the coefficient of determination R² is to 1, the more appropriate the fit can be judged to be.

[0028] Figure 3 is a graph showing the slope of the linear equation fitted to each tire and the coefficient of determination R2. As shown in Figure 3, R2 was the maximum value of 1 for 6 of the 8 tires tested, representing 75%. In addition, the R2 values ​​for the remaining 2 tires were 0.98 and 0.99, respectively, which are close to 1. Therefore, from the tests of these 8 tires, it became clear that there is a proportional relationship between the change in driving force and the change in noise for tires, and that noise can be expressed as a linear function with driving force as the variable. Furthermore, the inventors also confirmed the proportional relationship between the change in driving force and the change in noise in actual vehicle tests, and confirmed that noise can be expressed as a linear function with driving force as the variable.

[0029] Figure 4 shows an analysis of variance (ANOVA) table based on tests conducted by the inventor, and is an example of an ANOVA table when the design factors are A, B, C, D, A and B, and A and C. In the ANOVA table shown in Figure 4, SS (Sum of Squares) is the sum of squares, df (Degrees of Freedom) is the degrees of freedom, which is the rank of the variation. MS (Mean square) is the mean sum of squares, and F is the variance ratio, which is the value obtained by dividing the MS of the factor variation by the MS of the error. P-value is the significance level obtained from the probability function of the F distribution, which is the probability that the judgment was wrong. A P-value of 5% or less is usually judged to be significant. ρ is the coefficient of determination, which is calculated as (SS - df × mean sum of squares of errors) / (total sum of squares × 100).

[0030] The analysis of variance (ANOVA) table is a well-known technique and will not be described in detail here. It is a method for analyzing the mean value for each design factor using variance, and is used to analyze whether or not a design factor has an effect when that factor is varied. By performing ANOVA, it is possible to analyze how the variability due to the design factor compares to the variability due to measurement error, and to determine whether the variability is greater when the design factor is varied than the measurement error, or whether the effect of varying the design factor remains within the range of the measurement error.

[0031] In an analysis of variance (ANOVA) table, the variance ratio is an indicator that shows how large the variance of the design factors is compared to the variance of the error. The contribution rate is an indicator that represents the relative strength of the design factors, and roughly speaking, it is an indicator that shows the contribution of the sum of squares of each design factor to the total sum of squares. The contribution rate is an indicator used in the field of statistics or statistical data analysis, and in an analytical model, when there are multiple variables, it shows the proportion that each variable contributes to a certain criterion. The contribution rate takes a value from 0 to 1, and a contribution rate of 1 means that all the information represented by the original feature is represented. In the example shown in Figure 4, the contribution rate of design factor D is 77%, which is outstanding compared to the other design factors. From this, it can be seen that in this case, among A, B, C, and D, design factor D has the largest contribution to noise.

[0032] Figure 5 is a graph that investigates the change in the slope of the linear equation when only each design factor is changed from the reference value. In each graph, the slopes at A1, B1, C1, and D1, subscripted with 1, represent the slope at the reference value. In each graph, the slopes at A2, B2, C2, and D2, subscripted with 2, represent the slope when the values ​​of design factors A and D are increased above the reference value, and when the values ​​of design factors B and C are increased above the reference value.

[0033] As shown in Figure 5, the change in the slope is greater when design factor D is changed than when the other design factors A, B, and C are changed. This is consistent with the fact that in Figure 4, the contribution rate of design factor D is 77%, which is outstandingly larger than the contribution rates of the other design factors A, B, and C. From this, we can conclude that, in this test example, for tires with identical basic specifications, design factor D contributes significantly to noise.

[0034] Therefore, for tires with identical basic specifications, focusing on design factor D and evaluating tire design and estimated acceleration noise in terms of driving force allows for the efficient design of quieter tires, and also enables accurate and efficient evaluation of estimated noise in terms of driving force for the designed tires. More specifically, by focusing on design factor D and conducting multiple further tests with varying values, it is possible to grasp the trend of the change in driving force sensitivity (slope of the linear equation) when design factor D is changed for tires with the same basic concept and specifications. As a result, it becomes easier to accurately estimate the change in driving force sensitivity when design factor D is changed for other tires with the same basic concept and specifications, and to accurately estimate the noise value in relation to driving force.

[0035] Figure 6 is a graph showing the analysis of variance table for noise of tires with other basic specifications in actual vehicle tests, and Figure 7 is a graph corresponding to Figure 5 for the tires with the basic specifications for which the noise analysis of variance table in Figure 6 is shown. As shown in Figure 6, in this basic specification tire, design factor A is outstanding with a contribution rate of 56%, and consistent with this, the slope is steeper when the value of design factor A is increased above the reference value. In this example, the contribution rate of design factor D is 28%, which is a value that cannot be ignored. Therefore, by focusing on design factors A and D, and especially on design factor A, and conducting multiple further tests with varying values, it is easier to accurately estimate the change in noise when at least one of design factors A and D is changed for tires with the same basic concept and basic specifications. Thus, it is possible to efficiently design tires with low noise, and it is also easier to accurately and efficiently evaluate the estimated noise at the driving force of the designed tire.

[0036] In this way, by analyzing and investigating the relationship between design factors and acceleration noise using experimental design methods, such as orthogonal arrays, analysis of variance tables, D-optimal design, full factorial design, partially factorial design, Latin hypersquare, Fischer's three principles, and factor effect diagrams, it becomes easier to efficiently design tires with low noise, and to accurately and efficiently estimate the acceleration noise at a specific driving force for the designed tire.

[0037] In summary, regarding the design specifications of the tire, we were able to calculate the quantitative sensitivity (driving force sensitivity) to the slope of the linear equation representing noise and driving force from the relationship between the amplitude of design factors and the effect of those factors, and we confirmed and discovered that it is possible to estimate the acceleration noise [dB(A)] at an arbitrary acceleration (driving force) using this linear equation. The estimation formula can be given as equation (2) below, and the estimation of acceleration noise at driving force can be performed in the following procedure. (Estimate formula)

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[0038] (Specific steps) (1) For tires conforming to design standards, the driving force sensitivity = noise increase [dB(A)] / driving during acceleration (rotation shaft torque [Nm]) and the tire coasting noise shall be obtained using at least one of bench tests and actual vehicle tests. (2) Evaluate the impact of specification changes on coasting noise and driving force sensitivity (the range of change in coasting noise and driving force sensitivity) and create a database. In this case, it is preferable to use experimental design to evaluate the range of change in coasting noise and driving force sensitivity in relation to design factors. The database may store functions for calculating the range of change (amount of change) in coasting noise and driving force sensitivity. (3) Based on the changes in specifications between the design standard tire and the quoted tire, the change in coasting noise and driving force sensitivity is calculated using the above database. (4) The acceleration noise at the target acceleration (driving force) is calculated using the above equation (2).

[0039] The noise level to be evaluated may be the overall level, or it may be a partial overall level including the 1kHz band, for example, a partial overall level of the frequency bands included in the frequency range from 500Hz to 1.5kHz. The overall level is the sum of the power of each frequency band in the analyzed power spectrum, while the partial overall level is the sum of the power of each frequency band in the power spectrum within any frequency range.

[0040] Through numerous tests, the inventors have found that the contribution of acceleration noise is particularly pronounced in noise within the frequency range of 500 Hz to 1.5 kHz. Therefore, by performing a partial overall analysis of noise within the frequency range of 500 Hz to 1.5 kHz, acceleration noise can be evaluated effectively and with high accuracy.

[0041] The noise level in the test can be evaluated using the following method. Coasting noise evaluation method = JASO C 606:1981, ISO 10844:1994 Acceleration noise evaluation method = ISO362, UN-ECE R51-03, JIS D 1024, ISO 10844:1994

[0042] The tire noise evaluation method described herein is a method for evaluating tire noise during vehicle acceleration, which involves estimating a driving force sensitivity based on the characteristics of the tire, which is obtained by dividing the amount of noise change when the vehicle's driving force changes by the amount of change in the driving force, and evaluating the noise during acceleration based on the estimated driving force sensitivity.

[0043] According to this disclosure, tire noise during acceleration is estimated and evaluated without testing, based on the driving force sensitivity estimated without testing due to the characteristics of the tire. Therefore, noise evaluation during acceleration can be performed in a short time, and the effort and cost required for such noise evaluation can also be reduced.

[0044] Alternatively, a third noise, which is obtained by adding a second noise (calculated by multiplying the driving force sensitivity by the driving force) to the first noise generated when the vehicle is coasting, may be estimated as the noise generated when the vehicle is accelerating using the driving force.

[0045] With this configuration, when estimating the third noise (corresponding to tire noise during acceleration) for a specific driving force, the third noise for that driving force can be instantly estimated simply by substituting the driving force into a linear equation for calculating the third noise, where the driving force is the variable.

[0046] Alternatively, the driving force sensitivity may be estimated based on one or more design factors.

[0047] This configuration makes it easier to systematically and objectively estimate driving force sensitivity using design factors.

[0048] Alternatively, the driving force sensitivity may be estimated based on multiple design factors, and the contribution of each design factor to the driving force sensitivity may be evaluated based on experimental design.

[0049] This configuration makes it easier to efficiently and accurately evaluate the contribution of each tire design factor to the driving force sensitivity, and consequently, to accurately estimate tire noise during acceleration.

[0050] [Method for evaluating acceleration noise while considering ambient temperature] Next, we will explain the method for evaluating acceleration noise when it fluctuates with ambient temperature. Even when evaluating acceleration noise while considering ambient temperature, the noise evaluation during the test can be performed using the method described above in "[Method for evaluating acceleration noise without considering ambient temperature]".

[0051] For example, as explained below, the evaluation of noise in tests is based on the design factors mentioned above, specifically the effective contact area [contact area excluding grooves] (the area of ​​regions divided axially is also acceptable, and their ratios are also design factors). Here, examples of regions divided axially include the center, quarter, and shoulder. Other design factors can also be used, for example, the area ratio of the contact area to the total area including the grooves on the land portion (the area of ​​regions divided axially is also acceptable, and their ratios are also design factors), the effective contact ratio of the ribs, the number of pitches [number of circumferential blocks around the circumference of the tire], the hardness of the tread rubber, the belt width [the axial width of the belt when viewed in cross-section], the belt angle [the angle of the belt ply with respect to the circumferential direction], the number of belt ends [the number of cords per inch of the belt ply], the Young's modulus of the tread rubber, the elastic modulus of the tread rubber, the tanδ (loss tangent) of the tread rubber, the carcass ply material, the Young's modulus of the carcass ply, the number of carcass ply ends, the hardness of the bead filler, the Young's modulus of the bead filler, and the bead filler height [the radial length of the bead filler].

[0052] Furthermore, coasting noise evaluation and acceleration noise evaluation can be performed using the following method described in [Method for evaluating acceleration noise without considering ambient temperature]. Coasting noise evaluation method = JASO C 606:1981, ISO 10844:1994 Acceleration noise evaluation method = ISO362, UN-ECE R51-03, JIS D 1024, ISO 10844:1994

[0053] Furthermore, as explained below, the evaluation of acceleration noise can also be performed using at least one of the experimental design methods described in [Methods for Evaluating Acceleration Noise Without Considering Ambient Temperature], such as orthogonal arrays, analysis of variance tables, D-optimal design, full factorial design, partial factorial design, Latin hypersquare, Fischer's three principles, and factor effect diagrams. Alternatively, the evaluation of acceleration noise may also be performed using other methods described in [Methods for Evaluating Acceleration Noise Without Considering Ambient Temperature].

[0054] The inventors of this case have discovered that, as will be explained below, one or more design factors (design elements, design variables) of a tire may include design factors that have a large temperature dependence. Furthermore, through numerous tests, the inventors have also discovered that design factors related to the rubber material of a tire often have a large temperature dependence. In this case, the acceleration noise of a tire related to such a design factor with a large temperature dependence is temperature-dependent, and the driving force sensitivity (slope) changes significantly with temperature.

[0055] Figure 8 is an orthogonal array of two design factors in a bench test, specifically a noise test. Figure 8 shows the results of an analysis of two design factors E and F from the design factors listed above. By using an orthogonal array, 2 2 =By testing only three tires, without having to test four tires, it is possible to identify combinations of design factors that significantly contribute to noise.

[0056] In Figure 8, each design factor is set to select one of two values. Furthermore, "base" in the design factor column indicates that the design factor is at the baseline value, while "-" in each design factor column indicates that the design factor is smaller than the baseline value. As shown in Figure 8, tire 9 is a tire where both design factors are at the baseline value. Tire 10 is a tire where design factor F is at the baseline value, while design factor E is smaller than the baseline value. Similarly, tire 11 is a tire where design factor E is at the baseline value, while design factor F is smaller than the baseline value.

[0057] Figure 9 is a graph showing the relationship between driving force [kN] and the overall noise level [dB(A)] of external noise in winter vehicle testing, and Figure 10 is a graph showing the relationship between driving force [N] and the overall noise level [dB(A)] of external noise in summer vehicle testing. In Figures 9 and 10, the solid line is the optimal straight line obtained by the least squares method based on the measured points at tire 9, the dotted line is the optimal straight line obtained by the least squares method based on the measured points at tire 10, and the dashed line is the optimal straight line obtained by the least squares method based on the measured points at tire 11. In addition, in Figures 9 and 10, a and b on the horizontal axis are the same positive constants evaluated in [kN], and c and d on the vertical axis are the same positive constants evaluated in [dB(A)].

[0058] As shown in Figures 9 and 10, for example, tire 11, indicated by the dashed line, measured a large external noise level exceeding (c+12d) in summer, while in winter, only external noise levels below (c+11d) were measured. Furthermore, for the other tires 9 and 10, the external noise level in summer was higher than that in winter. This confirms that acceleration noise can be temperature-dependent. Figure 11 is a graph comparing the slopes of the solid, dotted, and dashed lines in Figures 9 and 10, and Figure 12 is a graph showing the relationship between temperature and driving force sensitivity for the three tires. As shown in Figures 11 and 12, the slope representing driving force sensitivity increased to 1.24 times for tire 11, and the rate of increase in the slope representing driving force sensitivity increased to 1.31 times for tire 10. Furthermore, for tire 9, the slope representing driving force sensitivity increased significantly to 1.40 times.

[0059] Figure 13 is a graph showing the relationship between temperature and driving force sensitivity for three tires in actual vehicle testing. In Figure 13, the solid line is the optimal straight line obtained by the least squares method based on the measured points for tire 9, the dotted line is the optimal straight line obtained by the least squares method based on the measured points for tire 10, and the dashed line is the optimal straight line obtained by the least squares method based on the measured points for tire 11.

[0060] The horizontal axis values ​​e and f are identical positive constants evaluated in [°C], and the vertical axis values ​​g and h are identical positive constants evaluated in terms of driving force sensitivity. As shown in Figure 13, it was confirmed that the driving force sensitivity increased linearly (like a first-order function) with increasing temperature for all three tires 9-11. Therefore, from the results shown in Figure 13, it was confirmed that the predicted driving force sensitivity can sometimes be estimated using the following equation (3).

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[0061] In equation (3) above, (predicted driving sensitivity at the reference temperature) represents a point on the solid, dotted, or dashed line in the graph shown in Figure 13. Therefore, by adding to this the temperature correction slope, which is the slope on the solid, dotted, or dashed line, multiplied by (noise estimation temperature - reference temperature), the predicted driving sensitivity at the noise estimation temperature on the solid, dotted, or dashed line can be calculated with high accuracy. Here, the temperature correction slope is the slope that serves as a measure of the temperature dependence of the driving force sensitivity.

[0062] Here, the calculation of predictive drive sensitivity in the [method for evaluating acceleration noise without considering ambient temperature] can also be used. In equation (3), N is the number of different design factors in the tire model, design factor sensitivity i is the slope in the i-th design factor, and design variation i is the change range (amount of change) indicating the degree of change in the i-th design factor. The value of [temperature correction slope × (noise estimate temperature - reference temperature)] in equation (3) may be further analyzed and the predictive drive sensitivity may be calculated using the following equation (4).

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[0063] In equation (4) above, the value of [temperature correction slope × (noise estimate temperature - reference temperature)] in equation (3) is calculated as the sum of the temperature changes for each design factor. In equation (4), the design factor sensitivity i at the reference temperature is the driving force sensitivity (slope) at the reference temperature for the i-th design factor, and the design factor-specific temperature correction slope i is the value obtained by dividing the change in driving force sensitivity for the i-th design factor by the temperature change value.

[0064] In equations (3) and (4), the temperature correction slope, design factor sensitivity i, design variation i, design factor sensitivity i at reference temperature, and design factor specific temperature correction slope i are determined, for example, for a test tire by performing bench tests and actual vehicle tests on the driving force sensitivity = noise increase [dB(A)] / driving during acceleration (rotating shaft torque [Nm]) and the coasting noise of the tire. For one or more specific design factors, at least one of the design factor sensitivity i, design factor sensitivity i at reference temperature, and design factor sensitivity i at reference temperature may be evaluated as zero (0) or approximately zero.

[0065] The impact of specification changes on coasting noise and driving force sensitivity (the range of change in coasting noise and driving force sensitivity) will be evaluated and compiled into a database. In this process, it is preferable to evaluate the range of change in coasting noise and driving force sensitivity in relation to design factors using experimental design. The database may also store functions for calculating the range of change (amount of change) in coasting noise and driving force sensitivity.

[0066] Based on the specification changes between the design standard tire and the quoted tire, the change in coasting noise and driving force sensitivity is calculated using the above database without conducting actual vehicle tests or bench tests. Then, using equation (2) and equation (3) or (4) above, the noise-estimated temperature and acceleration noise at the target acceleration (driving force) are calculated. The noise level to be evaluated may be the overall level. Alternatively, the noise level to be evaluated may be a partial overall level including the 1kHz band, for example, a partial overall level of the frequency band included in the frequency range of 500Hz to 1.5kHz.

[0067] By using experimental design methods to calculate the contribution rate, etc., design factors that significantly change the driving force sensitivity with temperature changes can be identified, making it easier to accurately evaluate acceleration noise at ambient temperatures. If the reference driving force sensitivity is temperature-dependent, the reference driving force sensitivity in equations (3) and (4) may be determined using equation (5) below. Here, the reference sensitivity temperature correction slope is determined in advance by bench tests and actual vehicle tests. It is preferable that the reference sensitivity temperature correction slope is determined in advance for multiple types of tire models and stored in a database.

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[0068] The tire noise evaluation method described herein is a method for evaluating tire noise during vehicle acceleration, which involves estimating a driving force sensitivity based on the change in noise when the vehicle's driving force changes, divided by the change in driving force, based on the tire characteristics and tire temperature characteristics, and evaluating the noise during acceleration based on the estimated driving force sensitivity.

[0069] The driving force sensitivity at operating temperature may be evaluated based on tire characteristics having a temperature dependence of 1 or more, or it may be mechanically calculated based on data on the contribution of each tire characteristic to the driving force sensitivity at operating temperature, which has been determined in advance by prior testing.

[0070] According to this disclosure, noise at operating temperatures during tire acceleration is evaluated based on the driving force sensitivity estimated based on tire characteristics and tire temperature characteristics. Therefore, it is easier to accurately estimate noise at operating temperatures during tire acceleration.

[0071] Furthermore, according to this disclosure, tire noise during acceleration is estimated and evaluated based on the driving force sensitivity estimated without conducting tests. Therefore, the noise at the operating temperature during tire acceleration can be estimated in a short time, and the effort and cost required for noise evaluation at that operating temperature can be significantly reduced.

[0072] The third noise, which is obtained by adding the second noise (calculated by multiplying the driving force sensitivity by the driving force) to the first noise generated when the vehicle is coasting, can be estimated as the noise when the vehicle is accelerating using the driving force.

[0073] With this configuration, when estimating the third noise (corresponding to tire noise during acceleration) for a specific driving force, the third noise for that driving force can be instantly estimated simply by substituting the driving force into a linear equation for calculating the third noise, where the driving force is the variable.

[0074] Alternatively, the driving force sensitivity may be estimated based on one or more design factors.

[0075] This configuration makes it easier to systematically and objectively estimate driving force sensitivity using design factors.

[0076] Alternatively, the temperature characteristics of the driving force sensitivity may be estimated based on multiple design factors, and the contribution of each design factor to the temperature characteristics of the driving force sensitivity may be evaluated based on experimental design.

[0077] This configuration makes it easy to efficiently and accurately evaluate the contribution of each tire design factor to driving force sensitivity at different operating temperatures. Therefore, by focusing on design factors that have a high contribution to driving force sensitivity, it becomes easier to accurately estimate tire noise at operating temperatures during acceleration. [Explanation of symbols]

[0078] A,B,C,D,E,F Design factors

Claims

1. A method for evaluating tire noise during vehicle acceleration, A tire noise evaluation method comprising: estimating a driving force sensitivity based on the change in noise when the driving force of the vehicle changes, divided by the change in the driving force, based on the characteristics of the tire and the temperature characteristics of the tire; and evaluating the noise during acceleration based on the estimated driving force sensitivity.

2. The tire noise evaluation method according to claim 1, wherein a third noise is estimated as the noise when the vehicle is accelerating with the driving force, by adding a second noise obtained by multiplying the driving force sensitivity by the driving force to a first noise generated when the vehicle is coasting.

3. A tire noise evaluation method according to claim 1 or 2, wherein driving force sensitivity is estimated based on one or more design factors.

4. The temperature characteristics of the driving force sensitivity are estimated based on a plurality of design factors. The tire noise evaluation method according to claim 3, wherein the contribution of each design factor to the temperature characteristics of the driving force sensitivity is evaluated based on the experimental design method.

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