Tire fatigue life prediction method

Abstract

To provide a tire fatigue life prediction method high in prediction accuracy.SOLUTION: This tire fatigue life prediction method comprises: a generation step of generating a fatigue life estimation line representing a relationship between breaking energy of a vulcanized rubber material and a repetition number using a strain energy density function of the vulcanized rubber material constituting a tire, a cracking progress speed, tear energy, and a strain energy density; an acquisition step of acquiring the strain amplitude of one round of a tire model during grounding for the tire model constituted by an element which can be numerically analyzed by a computer representing the tire; and an estimation step of estimating a fatigue life by applying a value of the strain amplitude acquired in the acquisition step to the fatigue life estimation line.SELECTED DRAWING: Figure 6

Description

[Technical field]

[0001] The present invention relates to a tire fatigue life prediction method using material test data and computer-based numerical analysis, and more particularly to a tire fatigue life prediction method using a fatigue life estimation curve and strain amplitude obtained by numerical analysis. [Background technology]

[0002] Conventionally, the fatigue life (durability) of a tire has been evaluated by actually manufacturing a tire and running a test run using a drum testing machine or the like until the tire breaks down. In this case, it is difficult to predict in advance at what mileage a tire will break down and in which part of the tire. In addition, running a tire through a test run until it breaks down takes a lot of time and requires a lot of effort. For this reason, a method for predicting the fatigue life (durability) of a tire has been proposed.

[0003] For example, Patent Document 1 proposes a tire durability performance prediction method including the steps of inputting first time series data of the rolling conditions of a tire rolling on a road surface into a computer, inputting representative rolling conditions identified from the first time series data based on a predetermined criterion into the computer, inputting a tire model in which the tire is discretized into a finite number of elements into the computer, and inputting a first element for which durability performance is to be predicted and identified from the tire model into the computer, in which the computer executes the steps of calculating a temperature distribution of the tire model rolling under the representative rolling conditions, calculating physical quantities including stress or strain acting on the first element based on the tire model having the temperature distribution and the rolling conditions at least at one time point identified from the first time series data, and acquiring a first function showing the relationship between the rolling conditions and the physical quantities using the rolling conditions at least at one time point and the physical quantities. Patent Document 1 describes that an SN curve or an ε-N curve is used to predict the fatigue life. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2022-073699 A Summary of the Invention [Problem to be solved by the invention]

[0005] In the above-mentioned Patent Document 1, the SN curve or ε-N curve is used to predict fatigue life. The method of obtaining the tensile fatigue properties of these vulcanized rubber materials is standardized as JIS K 6270:2018 Vulcanized rubber and thermoplastic rubber - Method of determining tensile fatigue properties (constant strain method). In order to obtain the SN curve or ε-N curve using this method, it is recommended to perform constant strain tensile fatigue tests at least four levels. However, it takes a lot of time to perform tensile fatigue tests with test strains at least four levels. In addition, when fatigue failure is predicted using only the SN curve or ε-N curve, the prediction accuracy is insufficient, and further improvement in accuracy is required. An object of the present invention is to provide a tire fatigue life prediction method that predicts the fatigue life of a tire with high accuracy. [Means for solving the problem]

[0006] In order to achieve the above-mentioned object, the invention [1] is a method for predicting fatigue life of a tire, comprising the steps of: creating a fatigue life estimation line that expresses the relationship between the fracture energy and the number of cycles of a vulcanized rubber material using the strain energy density function, crack growth rate, and tear energy of the vulcanized rubber material that constitutes the tire, as well as the strain energy density; acquiring the strain amplitude for one revolution of a tire model at the time of contact with the ground, the tire model being composed of elements that represent a tire and can be numerically analyzed by a computer; and estimating the fatigue life by applying the strain amplitude value acquired in the acquiring step to the fatigue life estimation line.

[0007] Invention [2] is a tire fatigue life prediction method according to invention [1], in which the preparation step includes a step of performing a tensile test on a sample of vulcanized rubber material to obtain the relationship between tensile stress and tensile strain, and calculating a strain energy density function using the relationship between tensile stress and tensile strain, a step of measuring a crack growth rate on the sample of vulcanized rubber material using a crack growth rate measuring device to calculate the crack growth rate and tear energy, and a step of performing a constant strain tensile fatigue test at one level of test strain to obtain the tensile strain and the number of times the tensile force was applied, and calculating the strain energy density. Invention [3] is a method for predicting the fatigue life of a tire as described in Invention [1] or [2], in which an aged vulcanized rubber material is used as the vulcanized rubber material that constitutes the tire.

[0008] Invention [4] is a tire fatigue life prediction method described in any one of Inventions [1] to [3], in which the creation process of creating a fatigue life estimation line includes a process of modifying the fatigue life estimation line based on the tire structure to create a modified fatigue life estimation line, and the estimation process applies the strain amplitude value acquired in the acquisition process to the modified fatigue life estimation line to estimate the fatigue life. Invention [5] is a tire fatigue life prediction method described in any one of Inventions [1] to [4], in which the creation process of creating a fatigue life estimation line includes a process of correcting the fatigue life estimation line based on the median value of the strain amplitude obtained in the acquisition process to create a corrected fatigue life estimation line, and the estimation process applies the value of the strain amplitude obtained in the acquisition process to the corrected fatigue life estimation line to estimate the fatigue life. Invention [6] is a tire fatigue life prediction method according to any one of Inventions [1] to [5], in which the creation process of creating a fatigue life estimation line includes a process of correcting the fatigue life estimation line based on a safety factor to create a corrected fatigue life estimation line, and the estimation process applies the strain amplitude value acquired in the acquisition process to the corrected fatigue life estimation line to estimate the fatigue life.

[0009] Invention [7] is a tire fatigue life prediction method according to any one of Inventions [1] to [6], wherein the acquisition step includes a first step of performing contact analysis on a tire model to obtain stress and strain waveforms in the tire circumferential direction for each element of the tire model, a second step of Fourier transforming the stress and strain waveforms in the tire circumferential direction for each element of the tire model obtained in the first step to obtain a strain spectrum for each element of the tire model, and a third step of obtaining a strain amplitude from the strain spectrum obtained in the second step. Invention [8] is a tire fatigue life prediction method according to any one of Inventions [1] to [7], wherein the tire model has component elements corresponding to multiple components constituting the tire, and the component elements are composed of elements that can be numerically analyzed by a computer, the acquisition process is a process of acquiring a maximum value of strain amplitude in at least one component element among the multiple component elements of the tire model, and the estimation process is a process of applying the maximum value of strain amplitude acquired in the acquisition process to a fatigue life estimation line to estimate the fatigue life. Effect of the Invention

[0010] According to the present invention, the fatigue life of a tire can be predicted with high accuracy. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a schematic diagram showing a fatigue life prediction device used in a tire fatigue life prediction method according to an embodiment of the present invention. [Diagram 2] 1 is a graph showing the relationship between tensile stress and tensile strain of a vulcanized rubber material. [Diagram 3] 1 is a graph showing the relationship between strain energy density and tensile strain of a vulcanized rubber material. [Figure 4] 1 is a graph showing the relationship between the crack growth rate and the tear energy of a vulcanized rubber material. [Diagram 5] FIG. 2 is a schematic diagram showing an example of a device for measuring the crack growth rate of a vulcanized rubber material. [Figure 6] 1 is a graph showing an example of a fatigue life estimation line for a vulcanized rubber material. [Figure 7] FIG. 2 is a schematic perspective view showing a state in which a tire model and a road surface model are in contact with each other according to the embodiment of the present invention. [Figure 8] 4 is a graph showing an example of a strain amplitude of a tire model according to an embodiment of the present invention. [Figure 9] 1 is a graph showing an example of a fatigue life prediction line of a vulcanized rubber material after aging. [Figure 10] 1 is a graph showing an example of a corrected fatigue life prediction line for a vulcanized rubber material. [Figure 11] 10(a) is a graph showing another example of the strain amplitude of the tire model according to the embodiment of the present invention, and (b) is a graph showing another example of the strain amplitude of the tire model according to the embodiment of the present invention. [Figure 12] 1 is a graph showing an example of a modified fatigue life prediction line based on the strain amplitude of a vulcanized rubber material. [Figure 13] 1 is a graph showing an example of a modified fatigue life estimation line based on a safety factor of a vulcanized rubber material. [Figure 14] FIG. 2 is a schematic diagram showing an example of a configuration of a tire model according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The tire fatigue life prediction method of the present invention will be described in detail below with reference to the preferred embodiments shown in the accompanying drawings. It should be noted that the drawings described below are illustrative for explaining the present invention, and the present invention is not limited to the drawings shown below. In the following, the range of values ​​indicated by "~" includes the values ​​on both sides. For example, if ε is the number ε α ~number ε β That is, the range of ε is the number ε α and the number ε β The range includes ε α ≦ε≦ε β It is. In addition, unless otherwise specified, the terms "perpendicular" and "parallel" include the generally accepted error range in the relevant technical field. Unless otherwise specified, the term "temperature" also includes the generally accepted error range. Furthermore, unless otherwise specified, the terms "value" and "parallel" include the generally accepted error range in the relevant technical field.

[0013] [Fatigue life prediction device] FIG. 1 is a schematic diagram showing a fatigue life prediction device used in a tire fatigue life prediction method according to an embodiment of the present invention. The tire fatigue life prediction method of the present embodiment aims to predict the fatigue life of a tire with high accuracy. Hereinafter, a tire refers to a tire whose fatigue life is to be predicted, unless otherwise specified. The tire fatigue life prediction method of this embodiment is implemented, for example, by using a fatigue life prediction device 10 shown in Fig. 1. The tire fatigue life prediction method is implemented, for example, by using the fatigue life prediction device 10 shown in Fig. 1, but is not limited to the fatigue life prediction device 10 as long as the tire fatigue life prediction method can be executed using hardware and software such as a computer, and may be a program for causing a computer or the like to execute each step of the tire fatigue life prediction method as a procedure. Furthermore, the fatigue life prediction device 10 is not limited to the configuration shown in Fig. 1.

[0014] The fatigue life prediction device 10 includes a processing unit 12 , an input unit 14 , and a display unit 16 . The processing unit 12 has a condition setting section 20, an estimated line creation section 22, a model creation section 24, a calculation section 26, an estimation section 27, a memory 28, a display control section 30, and a control section 32. The fatigue life prediction device 10 also has a ROM (Read Only Memory) and the like, which are not shown in the figure. The processing unit 12 is controlled by a control unit 32. In the processing unit 12, the condition setting unit 20, the estimated line creation unit 22, the model creation unit 24, the calculation unit 26, and the estimation unit 27 are connected to a memory 28, and data of the condition setting unit 20, the estimated line creation unit 22, the model creation unit 24, the calculation unit 26, and the estimation unit 27 are stored in the memory 28. In the tire fatigue life prediction method described below, various processes are performed in each part of the processing unit 12. In the following description, a description of the various processes performed in each part of the processing unit 12 by the control unit 32 is omitted, but a series of processes in each part is controlled by the control unit 32. Memory 28 stores the strain energy density function, crack growth rate, tear energy, and strain energy density of the vulcanized rubber material constituting the tire described below, the fatigue life estimation line created by the estimation line creation unit 22, the strain amplitude value, etc.

[0015] In the tire fatigue life prediction method described below, various processes are performed in each part of the processing unit 12. In the following description, a description of the various processes performed in each part of the processing unit 12 by the control unit 32 is omitted, but a series of processes in each part are controlled by the control unit 32.

[0016] The fatigue life prediction device 10 may be configured using hardware such as a computer that functionally forms each of the condition setting unit 20, estimated line creation unit 22, model creation unit 24, and calculation unit 26 by executing a program (computer software) stored in ROM or the like in the control unit 32, or it may be a dedicated device in which each part is composed of a dedicated circuit, or it may be configured as a server to be executed on the cloud. Memory 28 is not particularly limited, and may be a physical storage medium such as a hard disk drive (HDD), a solid state drive (SSD), and a dynamic random access memory (DRAM), or may be a storage area located on a cloud connected via the Internet.

[0017] In the fatigue life prediction device 10 described below, various processes are performed in each part of the processing unit 12. In the following description, a description of the various processes performed in each part of the processing unit 12 by the control unit 32 is omitted, but a series of processes in each part are controlled by the control unit 32.

[0018] The input unit 14 is a variety of input devices such as a mouse and a keyboard for inputting various information according to instructions from an operator. The display unit 16 displays, for example, information input to the condition setting unit 20, results obtained by the tire fatigue life prediction method such as the fatigue life estimation line created by the estimation line creation unit 22, and the strain amplitude results obtained by the contact analysis of the tire model by the calculation unit 26, and various known displays are used. The display unit 16 also includes a device such as a printer for displaying various information on an output medium.

[0019] The condition setting unit 20 sets the specifications of a tire to be predicted for fatigue life by the tire fatigue life prediction method. The specifications of the tire to be predicted include the cross-sectional shape of the tire, the tire groove shape (pattern), the tire structure, the tire components and arrangement, and the tire size. The tire is made of vulcanized rubber material. The type of vulcanized rubber material is not particularly limited, and may be one type or multiple types.

[0020] The estimation line creation unit 22 creates a fatigue life estimation line that represents the relationship between the fracture energy and number of cycles of the vulcanized rubber material using the strain energy density function, crack growth rate, tear energy, and strain energy density of the vulcanized rubber material that constitutes the tire. Here, Fig. 2 is a graph showing the relationship between tensile stress and tensile strain of a vulcanized rubber material, Fig. 3 is a graph showing the relationship between strain energy density and tensile strain of a vulcanized rubber material, and Fig. 4 is a graph showing the relationship between crack growth rate and tear energy of a vulcanized rubber material. FIG. 5 is a schematic diagram showing an example of a device for measuring the crack growth rate of a vulcanized rubber material.

[0021] The strain energy density function of the vulcanized rubber material that constitutes a tire is calculated using the relationship between the tensile stress and tensile strain of the vulcanized rubber material shown in Figure 2. The strain energy density W is in an area 35 surrounded by the SS curve 34 and the horizontal axis (tensile strain ε) shown in Fig. 2. Therefore, for example, the strain energy density W can be obtained by integrating the SS curve 34. The SS curve 34 is a stress-strain curve. The relationship between the tensile stress and the tensile strain of the vulcanized rubber material is obtained by a tensile test, and the strain energy density W is generated by, for example, the estimated line generating unit 22. For example, the relationship between strain energy density W and tensile strain ε is shown by curve 36 in Figure 3. The strain energy density W and tensile strain ε are expressed, for example, as a function shown in the following formula (1) in which W is a power of tensile strain ε. The following formula (1) represents curve 36 shown in Figure 3. In the following formula (1), a and b are values ​​(fitting parameters) specific to the vulcanized rubber material. The function of the following equation (1) which expresses the relationship between the strain energy density W and the tensile strain ε is called the strain energy density function. W=a ε b (1) The strain energy density function is not limited to the above formula (1), and a material constitutive law called a hyperelastic model, such as the Yeoh model or the Ogden model, may be used.

[0022] A tensile test is performed on a sample of the vulcanized rubber material to measure the tensile stress and tensile strain. This results in an SS curve 34 shown in Figure 2. The tensile test is, for example, the tensile test specified in JIS K 6251:2017 "Vulcanized rubber and thermoplastic rubber - Determination of tensile properties."

[0023] The crack growth rate and the tear energy are shown, for example, by a straight line 37 in a log-log graph as shown in Fig. 4. The crack growth rate and the tear energy are calculated by an estimation line creating unit 22, for example, by measuring the crack growth rate of a vulcanized rubber material sample 41 using a crack growth rate measuring device 40 shown in Fig. 5. In this case, for example, a tensile strain ε (constant strain) is repeatedly applied from zero to a maximum value under predetermined conditions with a predetermined crack 41c formed in a vulcanized rubber material sample 41. The predetermined conditions include the application pattern, frequency, test temperature, etc., for repeatedly applying the tensile strain ε. The crack growth rate measuring device 40 holds both ends of a vulcanized rubber material sample 41 with chucks 42a, 42b arranged opposite each other. One chuck 42a is repeatedly moved up and down by a driving unit 43, while the other chuck 42b is fixed in a fixed position. A tensile strain ε is repeatedly applied to the vulcanized rubber material sample 41. The driving unit 43 is controlled by a control and calculation unit 45. The crack 41c is photographed by an imaging unit 44, and the change in the crack length c is calculated by the control and calculation unit 45 based on the photographed image data.

[0024] The vulcanized rubber material sample 41 is, for example, in the shape of a strip (width 10 mm, length 100 mm, thickness 2 mm) or in the shape of a dumbbell (sizes 3, 5, and 6) as defined in JIS K 6251:2017. The pattern of repeatedly applying tensile strain ε to sample 41 of the vulcanized rubber material is, for example, a sine wave shape, and the frequency is appropriately selected, for example, in the range of 1 Hz to 10 Hz. The test temperature is appropriately selected, for example, in the range of 25°C to 40°C. The maximum value of tensile strain ε is, for example, 0.03 to 0.3 (elongation equivalent: 3% to 30%). The initial shape of crack 41c is, for example, a wedge shape, and the initial value of crack length c is preferably about 1 mm to 3 mm, sufficiently smaller than the width of sample 41 of the vulcanized rubber material.

[0025] The crack growth rate v is calculated by the control calculation unit 45 based on the following formula (2) using the number of times n that the tensile strain ε is applied. Crack growth rate v = dc / dn (2)

[0026] In the case of vulcanized rubber materials, the relationship between the crack growth rate (dc / dn) and the tear energy T is expressed by the following formula (3). In the double logarithmic graph shown in FIG. 4, the crack growth rate (dc / dn) and the tear energy T are represented by a straight line 37. dc / dn=(1 / G)·Tβ (3) Here, in formula (3), β is the slope and G is the energy release rate, each of which is an inherent value of this vulcanized rubber material. The energy release rate G is the ratio of the energy input to the vulcanized rubber material sample 41 to the area of ​​the developed crack 41c. The slope β and tear energy T of this vulcanized rubber material sample 41 are calculated by the crack growth rate measuring device 40 (control calculation unit 45), and the straight line 37 shown in FIG. 4 is obtained.

[0027] When the vulcanized rubber material sample 41 is in the form of a strip, the tear energy T is expressed by the following formula (4). T = 2 kcW (4) Here, in equation (4), k is a function of the stretch ratio λ of sample 41, k=π / λ 1 / 2 , W is the strain energy density.

[0028] By substituting equation (4) into equation (3), the following equation (5) is obtained. dc / dn=(1 / G)·(2kcW)β···(5) By transforming equation (5), the following equation (6) is obtained. dn=dc / [(1 / G)·(2kcW)β]···(6)

[0029] Tensile strain ε is applied n times (n=0→b), and the crack length c becomes the initial value c 0 If sample 41 advances from cb to cb just before it breaks (c=c 0 →c b ), integrating equation (6) gives the following equation (7). Nb=[1 / [(1 / G)·(2kW)β]]·[1 / (1-β)]·(c b (1-β) -c 0 (1-β) ) · · · (7) In the formula (7), Nb is the number of times that the tensile strain ε is applied until the vulcanized rubber sample 41 breaks, and c 0 Compared to c bAssuming that is sufficiently large and β is greater than 2, the following equation (8) is derived. (c b (1-β) -c 0 (1-β) )=-c 0 (1-β) (8)

[0030] By substituting equation (8) into equation (7), the following equation (9) is obtained. Nb=[1 / [(1 / G)·(2kW)β]]·[1 / (β-1)]·(c 0 (1-β) ) · · · (9) From equation (9), the tensile fatigue life Nb of this vulcanized rubber material is calculated by the characteristic value of this vulcanized rubber material, the initial defect (c 0 ) and the strain energy density W.

[0031] By converting both sides of equation (9) into common logarithms and rearranging them, we obtain the following equation (10). log(Nb) = -βlogW + log[(c 0 (1-β) ) / [(1 / G) (β-1) (2kβ)]] (10)

[0032] Further rearrangement of equation (11) gives the following equation (11). logW = -(1 / β)log(Nb) + log[(c 0 (1-β) ) / [(1 / G) (β-1) (2kβ)]] (11)

[0033] Equation (11) can be expressed on a double logarithmic graph with the ordinate representing the strain energy density W and the abscissa representing the number of times n that tensile strain ε is applied. This double logarithmic graph is the fatigue life estimation line for vulcanized rubber materials. The β in the above formula (11) is obtained by formula (3). Therefore, (c 0 (1-β) By specifying the strain energy density W of the vulcanized rubber material, a fatigue life prediction line can be obtained for any strain energy density W of the vulcanized rubber material.0 (1-β) ) / [(1 / G)·(β-1)·(2kβ)] is difficult to determine.

[0034] Therefore, in a double logarithmic graph with the ordinate representing the strain energy density W and the abscissa representing the number of times n that a tensile strain ε is applied, a point is identified through which equation (11) with a slope of (-1 / β) passes. By identifying this point, a fatigue life estimation line can be obtained. In order to identify the point through which equation (11) passes, a constant strain tensile fatigue test is performed on a vulcanized rubber material sample 41 at one level of test strain εc, and the tensile strain εb at the time of breakage of the vulcanized rubber material sample 41 and the number of times n that a tensile force f is applied to the vulcanized rubber material sample 41 until it breaks are identified. In addition, since the constant strain tensile fatigue test can avoid the influence of temperature, it is preferable to carry out the test under the same temperature conditions as those for measuring the crack growth rate.

[0035] By performing a constant strain tensile fatigue test at one level of test strain εc, the above-mentioned tensile strain εb and the number of times n that the tensile force f is applied can be specified. Based on the test strain εc and the strain energy density function shown in FIG. 3, the strain energy density Wc at the test strain εc can be determined. Here, the determined number of times n and the strain energy density W c The value of P on a log-log graph shown in Figure 6, where the vertical axis is strain energy density W and the horizontal axis is the number of times a constant strain is applied n, is 1 Therefore, as shown in FIG. 6, the fatigue life estimation line 38 is 1 In this case, the strain energy density Wc is expressed as Wc=a·εc b The slope of the fatigue life prediction line 38 is (Wc / Nc) (-1 / β) It is.

[0036] As described above, a constant strain tensile fatigue test was performed at one test strain level εc, and P 1 Once the coordinates of P are specified, 1are the results of an actual tensile fatigue test. This is advantageous for estimating the tensile fatigue life of vulcanized rubber materials with high accuracy. It is preferable to use the constant strain tensile fatigue test specified in JIS K 6270:2018 as the constant strain tensile fatigue test. The tensile fatigue test method is a well-known method and is highly objective.

[0037] In order to break the vulcanized rubber material sample under test earlier, the test strain εc in the constant strain tensile fatigue test is preferably set to 1 / 3 or more, more preferably 1 / 2 or more, of the elongation at break (Eb) specified in JIS K 6251: 2017. Accordingly, the above-mentioned tensile strain εb and the number of times n of application of the tensile force f can be determined more quickly, and the tensile fatigue life of the vulcanized rubber material can be estimated more quickly.

[0038] When a tensile test is used to specify the above-mentioned tensile strain εb and the number of times n that the tensile force f is applied, the tensile strain at the time of breakage of the vulcanized rubber material sample in the tensile test is the tensile strain εb. In this case, the number of times n that the tensile force f is applied to the vulcanized rubber material sample until it breaks is one.

[0039] Based on the identified tensile strain εb and the strain energy density function shown in FIG. 3, the strain energy density W at the tensile strain εb can be identified. Here, the identified number of times n applied and the value of the strain energy density W are P of the fatigue life estimation line 38 shown in FIG. 0 The coordinates are:

[0040] It should be noted that the tensile strain εb and the number of times n that the tensile force f is applied can be determined when measuring the tensile strain ε and the tensile stress σ shown in Fig. 2. Apart from determining the SS curve 34 shown in Fig. 2, a tensile test can be performed on a sample of the vulcanized rubber material to determine the tensile strain εb and the number of times n that the tensile force f is applied.

[0041] As described above, the relationship between the tensile strain ε and the strain energy density W of the vulcanized rubber material constituting the tire, and the relationship between the crack growth rate v and the tear energy T are specified, and a constant strain tensile fatigue test is performed at one level of test strain εc to specify the tensile strain εb and the number of times n that the tensile force f is applied, and a fatigue life estimation line is calculated. Therefore, the time required to obtain the necessary data can be significantly reduced compared to when a constant strain tensile fatigue test is performed at four or more levels of test strain εc. As a result, the fatigue life of the tire can be predicted in a shorter period of time.

[0042] Here, FIG. 7 is a schematic perspective view showing a state in which the tire model and the road surface model according to the embodiment of the present invention are in contact with each other. The model creation unit 24 of the fatigue life prediction device 10 creates a tire model 46 (see FIG. 7) that represents a tire and is composed of elements that can be numerically analyzed by a computer. The model creation unit 24 also creates a road surface model (see FIG. 7) that represents a road surface and is composed of elements that can be numerically analyzed by a computer. The tire model 46 is not particularly limited as long as it is composed of elements that can be numerically analyzed by a computer, and may be, for example, a finite element model that is divided into a mesh of a finite number of elements. There are no particular limitations on the road surface model 47 as long as it is made up of elements that can be numerically analyzed by a computer, and it may be, for example, a finite element model that is divided into a finite number of mesh elements.

[0043] A known method can be used to create the tire model and the road surface model. For example, the tire model and the road surface model are each divided into a finite number of elements each consisting of a plurality of nodes to create the tire model and the road surface model. In the case of graphic data, the data is converted into data modeled with elements that can be numerically analyzed by a computer. The tire model and the road surface model modeled with elements that can be numerically analyzed by a computer may be discrete models that can be numerically calculated, and may be, for example, mesh data used in numerical simulations such as FEM, or design data such as CAD data.

[0044] The tire model 46 is not particularly limited as long as it is composed of elements that can be numerically analyzed by a computer, and is, for example, a three-dimensional finite element model that is mesh-divided into a finite number of elements. There are no particular limitations on the road surface model 47 as long as it is made up of elements that can be numerically analyzed by a computer, and it may be, for example, a finite element model that is divided into a finite number of mesh elements. The elements constituting the tire model or road surface model are elements that can be analyzed by a computer, such as solid elements such as tetrahedral solid elements, pentahedral solid elements, and hexahedral solid elements, shell elements such as triangular shell elements and quadrilateral shell elements, and membrane elements.

[0045] The tire model may have member elements corresponding to a plurality of members constituting the tire. The member elements are composed of elements that can be numerically analyzed by a computer. Elasticity or viscoelasticity may be imparted to each element, or rubber having a predetermined viscoelastic property may be modeled as a tire model. In this case, the model creation unit 24 imparts elasticity or viscoelasticity to each element of the tire model. The method of imparting elasticity and viscoelasticity to the tire model is not particularly limited, and any method used in numerical analysis software can be used as appropriate. Viscoelasticity includes, for example, the Prony series and parallel rheology frameworks. As for elasticity, it is preferable to use a material constitutive law called a hyperelastic model (Neo-Hookean, Mooney-Rivlin, Yeoh, Arruda-Boyce, Ogden model, etc.).

[0046] The tire model may have component elements corresponding to a plurality of components constituting the tire. In this case, the component elements are composed of elements that can be numerically analyzed by a computer. It is preferable to provide information on the physical properties of the vulcanized rubber material of the tire for each component element, which makes it possible to more clearly identify the defective part of the tire and to predict the fatigue life of the tire with higher accuracy. The information on the physical properties is, for example, viscoelasticity and elasticity properties according to the composition of the vulcanized rubber material of the multiple components constituting the tire. The components constituting the tire contain, for example, a rubber component, silica, carbon black, and a silane coupling agent. Examples of the rubber component include natural rubber (NR), isoprene rubber (IR), butadiene rubber (BR), styrene butadiene rubber (SBR), acrylonitrile-butadiene copolymer rubber (NBR), butyl rubber (IIR), halogenated butyl rubber (Br-IIR, Cl-IIR), and chloroprene rubber (CR).

[0047] More specifically, both natural and synthetic rubbers are used as vulcanized rubber materials for tires, but the blends or blend ratios of the materials vary depending on the parts of the tire. Examples of each part include tread rubber, side rubber, inner liner, bead filler, etc. Also included is coating rubber for reinforcing members such as carcass or belt. As an example of the composition of the tire, the tread rubber, which corresponds to the part that comes into contact with the road surface, is made of styrene-butadiene rubber, polybutadiene rubber, and natural rubber, with the ratio of these varying depending on the required performance. As another example, the side rubber applied to the sidewall often contains isoprene-based rubber or polybutadiene rubber, which provides good flex crack growth resistance. In addition, the inner liner, a layer of rubber attached to the inside of the tire, is required to prevent a drop in internal pressure and ensure airtightness, so it is made of isobutylene-isoprene rubber (butyl rubber), which has extremely low gas permeability.

[0048] In addition to the differences in the vulcanized rubber materials mentioned above, there are also differences in the materials used; for example, carbon black is blended to increase the strength of the rubber through vulcanization, or silica is blended for the purposes of reducing fuel consumption or heat generation, and the blending ratios of these materials also vary depending on the product and the location of use. For example, in order to increase the rigidity of the bead portion of the tire while also providing excellent flexural resistance, a rubber composition having high hardness is used for the rubber used in the bead filler, which is made by increasing the amount of carbon black or compounding a resin. As described above, since a wide variety of vulcanized rubber materials are used in tires, it is essential to use the results of properly evaluating the materials used in the tire to be predicted in order to improve the accuracy of life prediction. For this reason, in the tire model as well, it is essential to properly assign physical property values ​​such as elastic modulus of the materials used in the tire to be predicted to the component elements in order to improve the accuracy of life prediction.

[0049] Since an actual road surface is considered to be harder than rubber and less likely to deform, it is preferable that the road surface model has physical characteristics in which the entire model or the portion in contact with the tire model is a rigid body. Here, a rigid body means that when the tire model comes into contact with the road surface model and the tire model and the road surface model are subsequently moved relatively, the deformation of the road surface model is zero. The actual road surface means the actual road surface.

[0050] In the road surface model 47, the surface 47a may be, for example, a flat surface, a curved surface, or a model having projections and recesses that reproduce an actual road surface. By making the surface 47a of the road surface model 47 a curved surface, for example, a drum test machine can be reproduced. For example, a part of the road surface model 47 may be modeled using a curved line. By modeling the surface 47a of the road surface model 47 using a curved line, the surface 47a of the road surface model 47 becomes smooth, the contact with the tire model 46 becomes stable, and numerical calculations such as FEM can be efficiently performed. The modeled curve is not particularly limited, and examples include a circular arc, a sine wave, a cosine wave, a spline curve, and a Bezier curve.

[0051] When the road surface model 47 is a model having projections and recesses that reproduces an actual road surface, it is possible to model it using displacement or coordinate values ​​obtained by measuring the surface shape of the actual road surface. The method of modeling using the displacement or coordinate values ​​obtained by measuring the surface shape of the actual road surface is not particularly limited, and examples thereof include the following methods. For example, first, the surface shape of the actual road surface to be modeled into the road surface model 47 is measured by a laser displacement meter. Next, the surface shape data measured by the laser displacement meter is Fourier transformed to calculate the spectrum of the road surface irregularity amplitude and the irregularity period (road surface period), thereby obtaining a road surface model 47.

[0052] For the tire model, data on the shape and size of the tire and the viscoelastic properties are input to a model creation unit 24 via the input unit 14, for example, and a tire model is created in the model creation unit 24. For the road surface model, data representing the shape, size, and surface of the road surface, as well as physical property data indicating that it is a rigid body, are input, for example, to the model creation unit 24 via the input unit 14, and the road surface model is created in the model creation unit 24. The tire model and the road surface model may be stored in advance in the memory 28 via, for example, the input unit 14. In this case, the model creation unit 24 reads out the tire model and the road surface model stored in the memory 28 from the memory 28, and sets the tire model and the road surface model.

[0053] The calculation unit 26 performs a contact analysis (numerical analysis) between the tire model and the road surface model in order to obtain the strain amplitude for one revolution of the tire model. The contact analysis is not particularly limited as long as it can obtain the stress and strain waveform in the tire circumferential direction in each element (not shown) of the tire model 46. For example, a static contact analysis is used in which the tire model is brought into contact with the road surface model with a predetermined load. In addition, for example, a dynamic rolling analysis is used in which the tire model and the road surface model are moved relatively at a predetermined speed while in contact with each other, and the tire model is rolled on the road surface model for one revolution. Steady-state transportation analysis is also used. The contact analysis is performed in a virtual space such as within a computer by a numerical analysis (simulation) such as the finite element method using a general-purpose analysis software program such as Abaqus. Furthermore, prior to the contact analysis, the calculation unit 26 determines analysis conditions such as the load and the relative movement speed in the contact analysis between the tire model and the road surface model.

[0054] In the contact analysis, for example, a tire model is brought into contact with a road surface model under a prescribed load while the internal pressure of the tire model is at a prescribed internal pressure. In addition, in the contact analysis, an internal pressure filling process is performed on the tire model. The internal pressure filling process reproduces the process of assembling a tire onto a rim of a rim size specified by JATMA, ETRTO, TRA, etc. and filling the tire with internal pressure, and indicates a process of applying a pressure equivalent to the internal pressure of the tire model to the inner surface of the tire model facing the tire cavity region, or a process of modeling the tire cavity region with elements that can be analyzed by a computer and applying internal pressure.

[0055] Here, the specified internal pressure refers to the "maximum air pressure" specified by JATMA, the maximum value of the "TIRE LOAD LIMITS A TVARIOUS COLD DINFLATION PRESSURES" specified by TRA, or the "INFLATION PRESSURES" specified by ETRTO. The specified load refers to the "maximum load capacity" specified by JATMA, the maximum value of the "TIRE LOAD LIMITS AT VARIOUS COLLIDING PRESSURES" specified by TRA, or the "LOAD CAPACITY" specified by ETRTO. However, in JATMA, for passenger car tires, the specified internal pressure is 180 kPa, and the specified load is 88% of the maximum load capacity. The relative movement speed is not particularly limited, and is appropriately determined depending on the predicted fatigue life of the tire to be evaluated. In addition, when the tire model and the road surface model are moved relatively, either the tire model or the road surface model may be moved. Furthermore, the direction of the relative movement of the tire model and the road surface model is not particularly limited, but may be, for example, the rolling direction DL. The tire model 46 is rotated one rotation around the rotation axis C of the tire model.

[0056] The load and relative movement speed in the contact analysis between the tire model 46 and the road surface model 47, as well as which of the tire model 46 and the road surface model 47 is to be moved and the movement direction, are stored, for example, in the memory 28. The calculation unit 26 may store the load and relative movement speed, and which of the tire model 46 and the road surface model 47 is to be moved and the movement direction in the memory 28, and read them out from the memory 28. Furthermore, the load and relative movement speed in a contact analysis between the tire model and the road surface model may be input from the input unit 14 and set in the calculation unit 26 . The tire model 46 and the road surface model 47 that are to be moved and the direction of movement may be input from the input unit 14 and set in the calculation unit 26 . Moreover, in the memory 28, simulation conditions such as contact analysis in the calculation unit 26 are set. The strain amplitude (principal value / each component) for one revolution of the tire model when in contact with the ground is obtained, but this may be in a rolling state or in a static contact analysis. If in a rolling state, it is preferable to obtain values ​​for one revolution of the tire model in a steady state. When reproducing a rolling state using a static contact analysis, it is preferable to apply a centrifugal force equivalent to a specified speed.

[0057] After performing a contact analysis between the tire model and the road surface model, the calculation unit 26 obtains stress and strain waveforms (see FIG. 8) in the tire circumferential direction (not shown) in each element (not shown) of the tire model 46. The stress and strain waveforms in the tire circumferential direction described above are obtained by the above-mentioned contact analysis and are stored in the memory 28, for example. The calculation unit 26 then performs a Fourier transform on the obtained stress and strain waveforms in the tire circumferential direction for each element of the tire model to obtain the stress and strain spectrum for each element of the tire model. The stress and strain spectrum for each element of the tire model is stored in, for example, the memory 28. The computing unit 26 further derives strain amplitudes from the acquired stress and strain spectra, which are then stored in the memory 28, for example.

[0058] As described above, when a contact analysis is performed on a tire model and the tire model is brought into contact with a road surface model or the tire model is rotated once on the road surface model, the elements of the tire model receive a force in the tire circumferential direction from the road surface model, causing deformation, etc. For each element of the tire model at this time, a stress waveform in the tire circumferential direction and a strain waveform 39 shown in Fig. 8 are obtained. The process of obtaining the stress and strain waveforms in the tire circumferential direction for each element of the tire model described above is referred to as the first process. Then, the stress and strain waveforms in the tire circumferential direction for each element of the tire model obtained in the first step are Fourier transformed. This allows the stress and strain spectrum to be obtained for each element of the tire model. The step of obtaining the strain spectrum for each element of the tire model described above is called the second step. As described above, the stress amplitude, stress phase difference, strain amplitude Aε (see Fig. 8), strain phase difference, and phase lag are obtained for each Fourier order by Fourier transforming the stress and strain waveforms of each element obtained in the second step. The step of obtaining the strain amplitude from the strain spectrum obtained in the second step is called the third step.

[0059] The strain amplitude Aε (see FIG. 8) obtained in the above-mentioned third step can be, for example, the sum of each strain component in each direction, the sum of the normal components of the strain, the sum of the shear components of the strain, or the amplitude of the maximum principal strain. The method of acquiring the strain amplitude is not limited to the above-mentioned method. For example, the strain amplitude may be acquired by using the fluctuation history of the normal and shear components in the tire meridian direction, tire circumferential direction, and tire thickness direction for one tire revolution for the stress and strain of each element of the tire model in a static contact state or rolling state. The order of the Fourier transform is preferably 10 or more, more preferably 10 to 100, and even more preferably 20 to 50. If the order is 10 to 100, the accuracy is good.

[0060] The estimation unit 27 performs an estimation step of estimating a fatigue life by applying the value of the strain amplitude obtained by the numerical analysis to a fatigue life estimation line. Specifically, the strain amplitude obtained by numerical analysis is expressed as ε 2 and the strain amplitude value ε 2 is fitted to the strain energy density function shown in FIG. 3, i.e., curve 36 shown in FIG. 3, to obtain the strain energy density W 2 The strain energy density W 2 Applying this to the fatigue life prediction line 38 shown in Figure 6, P 2 Coordinates of (N 2 ,W 2 ) is determined. This gives the strain energy density W 2 Number of times given in N 2 This grant count N 2 is estimated to be the fatigue life of the tire being predicted.

[0061] The display control unit 30 causes the display unit 16 to display information on the load and relative moving speed of the tire model determined by the condition setting unit 20, the object being moved and the moving direction, the fatigue life estimation line created by the estimation line creation unit 22, the tire model and road surface model created by the model creation unit 24, and the fatigue life estimation results, etc. The display control unit 30 can also cause the display unit 16 to display various types of information input via the input unit 14.

[0062] [Tire fatigue life prediction method] In the tire fatigue life prediction method, for example, as described above, the estimation line creation unit 22 carries out a creation process of creating a fatigue life estimation line 38 (see Figure 6) that shows the relationship between the fracture energy and the number of cycles of the vulcanized rubber material using the strain energy density function, crack growth rate, tear energy, and strain energy density of the vulcanized rubber material that constitutes the tire. The fatigue life estimation line 38 (see FIG. 6) is created as described above.

[0063] The model creation unit 24 creates a tire model that represents the tire to be predicted and is composed of elements that can be numerically analyzed by a computer. Next, the calculation unit 26 carries out an acquisition step of acquiring the strain amplitude Aε (see FIG. 8) for one revolution of the tire model when it is in contact with the ground. The strain amplitude Aε (see FIG. 8) for one revolution of the tire model when in contact with the ground is obtained as described above.

[0064] Next, the estimation unit 27 performs an estimation step of estimating a fatigue life by applying the value of the strain amplitude acquired in the acquisition step to a fatigue life estimation line 38 (see FIG. 6). Specifically, as described above, the strain amplitude value ε 2 is fitted to the curve 36 shown in Figure 3, and the strain energy density W 2 The strain energy density W 2 Applying this to the fatigue life prediction line 38 shown in Figure 6, the strain energy density W 2 Number of times given in N 2 This grant count N 2is estimated to be the fatigue life of the tire being predicted. In the fatigue life prediction method, the strain amplitude value obtained by the numerical analysis as described above is applied to a fatigue life estimation line created from actual measured values ​​of the vulcanized rubber material to estimate the fatigue life, thereby making it possible to predict the fatigue life of a tire with high accuracy. In addition, the fatigue life prediction method is suitable for identifying the initial occurrence position of a crack inside a tire, which is difficult to confirm until it appears on the outside of the actual tire, or the running distance (number of revolutions) at which the crack occurs.

[0065] In addition, in the tire fatigue life prediction method, the vulcanized rubber material constituting the tire may be an aged vulcanized rubber material, which allows for consideration of the decrease in fracture energy or the change in strain energy density in the aged vulcanized rubber material, thereby enabling highly accurate life prediction. The aged vulcanized rubber material is, for example, aged by heat. In this case, it is preferable to use the aging method according to "JIS K 6257:2017 Vulcanized rubber and thermoplastic rubber - Determination of heat aging characteristics". When the aged vulcanized rubber material is used, the fatigue life estimation line 50 shown in Fig. 9 is generated by the estimation line generating unit 22. Fig. 9 is a double logarithmic graph. In the fatigue life estimation line 38 before aging, the energy density W 2 The number of times it is granted is N 2 After aging, as shown by the fatigue life prediction line 50, the energy density W 2 The number of times the item is given is N 3 That is, the fatigue life becomes shorter.

[0066] In the tire fatigue life prediction method, the creating step of creating a fatigue life estimation line preferably includes a step of creating a corrected fatigue life estimation line by correcting the fatigue life estimation line based on the tire structure, and the estimating step preferably estimates the fatigue life by applying the strain amplitude value acquired in the acquiring step to the corrected fatigue life estimation line. This makes it possible to predict the fatigue life of the tire that is the prediction target, reflecting the effect of improving durability due to differences in the number of carcass layers or reinforcing layers called reinforcements. Examples of reinforcing layers called reinforcements include a composite material layer formed by topping a rubber sheet with a metal or fiber reinforcing material, or a composite material layer formed by blending a resin into a rubber sheet, and further examples include a rubber layer alone blended with a resin. The term "based on the structure" refers to differences in the number of carcass layers, the presence or absence of a reinforcing layer such as a reinforcement, and the angle of a reinforcing material. FIG. 10 is a graph showing an example of a corrected fatigue life prediction line for a vulcanized rubber material. As shown in Fig. 10, fatigue life estimation line 38, which is expressed by a double logarithmic graph, is expressed as a straight line connecting the strain energy density when the number of applied cycles is 1 and the strain energy density when the number of applied cycles is 1 at the time of break. In this case, the fatigue life estimation line 38 is modified to create a modified fatigue life estimation line by multiplying the strain energy density when the number of applied cycles is 1 by a coefficient based on the tire structure and translating the fatigue life estimation line parallel to the vertical axis (strain energy density) while maintaining the slope. In addition, the change in strain energy density when the strain energy is applied once indicates that the number of times the strain energy can be applied until fracture, i.e., the fatigue life, changes even with the same strain energy.

[0067] It has been confirmed that the durability of a tire increases as the number of reinforcing layers in the structure increases. Therefore, the number of times the tire can be damaged (lifespan) increases by increasing the number of carcass layers and adding reinforcing layers containing metal, fiber, or resin arranged from the side portion to the bead portion. The coefficient increases as the number of reinforcing layers increases. In other words, the number of times the tire can be damaged increases. As shown in FIG. 10, compared to the fatigue life estimation line 38 before modification, the first modified fatigue life estimation line 51 has a coefficient larger than 1, and when the strain energy density is Wb, the number of times of application is N 4 It is. In addition, the second modified fatigue life estimation line 52 has a coefficient smaller than 1, and when the strain energy density is Wb, the number of times of application is N 5 It is. The fatigue life estimation line 38 is the line where the strain energy density is Wb and the number of times of application is N. b Number of times given N 5 , N b and N 4 is N 5 <N b <N 4 This is in a relationship.

[0068] Fig. 11(a) is a graph showing another example of the strain amplitude of the tire model according to the embodiment of the present invention. (b) is a graph showing another example of the strain amplitude of the tire model according to the embodiment of the present invention. Fig. 12 is a graph showing an example of a corrected fatigue life estimation line based on the strain amplitude of a vulcanized rubber material. In the tire fatigue life prediction method, the creation step of creating a fatigue life estimation line performed by the estimation line creation unit 22 includes a step of creating a corrected fatigue life estimation line by correcting the fatigue life estimation line based on the median value of the strain amplitude obtained in the acquisition step. Then, the estimation step performed by the estimation unit 27 preferably applies the value of the strain amplitude obtained in the acquisition step to the corrected fatigue life estimation line to estimate the fatigue life.

[0069] The strain amplitude is obtained by contact analysis using a tire model as described above. Even if the strain amplitude is the same, the median value may differ. For example, in the strain waveform 39a shown in FIG. 11(a), the median value Cv of the strain amplitude Aε is zero. The strain amplitude Aε includes positive and negative values. The strain amplitude Aε shown in FIG. 11(a) is also called double-ended. In the strain waveform 39b shown in Fig. 11(b), the median value Cv of the strain amplitude Aε exceeds zero and is a positive value. The strain amplitude Aε shown in Fig. 11(b) is also called pulsating. In the case of the strain amplitude Aε (pulsating) shown in FIG. 11(b), the average strain is large, and therefore the fatigue limit is lower than that in the case of the strain amplitude Aε (reversible) shown in FIG. 11(a).

[0070] A coefficient is assigned so that the number of times the strain amplitude Aε can be applied until fracture occurs varies depending on the median Cv of the strain amplitude Aε. This makes it possible to estimate the fatigue life taking into account not only the magnitude of the strain amplitude, but also the average strain, as described above. For example, when the strain amplitude Aε (double swing) is as shown in Fig. 11(a), the fatigue life estimation line 53 shown in Fig. 12 results. The fatigue life estimation line 53 is the fatigue life estimation line 38 shown in Fig. 6. On the other hand, the strain amplitude Aε (pulsating) shown in FIG. 11(b) results in a fatigue life estimation line 54 shown in FIG. Fatigue life estimation line 54 is a modified fatigue life estimation line obtained by modifying fatigue life estimation line 53 by multiplying the strain energy density when the strain energy is applied once by a coefficient. The fatigue life estimation line 53 is when the strain energy density is Wb and the number of times of application is N. b The fatigue life estimation line 54 is when the strain energy density is Wb and the number of times of application is N. a Number of times given N a and N b is N a <N a In other words, the strain amplitude Aε (pulsating) has a shorter life. In addition, when the maximum or minimum value of the strain amplitude is taken into consideration, the maximum or minimum value can be obtained from the median and the strain amplitude. In addition, a modified fatigue life prediction line may be created using the coefficient based on the tire structure and the coefficient based on the strain amplitude.

[0071] In the tire fatigue life prediction method, the creation process of creating a fatigue life estimation line performed by the estimation line creation unit 22 modifies the fatigue life estimation line based on a safety factor to create a modified fatigue life estimation line, and the estimation process performed by the estimation unit 27 can also estimate the fatigue life by applying the strain amplitude value acquired in the acquisition process to the modified fatigue life estimation line. FIG. 13 is a graph showing an example of a corrected fatigue life prediction line based on the safety factor of a vulcanized rubber material. As described above, a modified fatigue life estimation line may be created by modifying the fatigue life estimation line 38 shown in Fig. 13 based on a safety factor. In this case, for example, a modified fatigue life estimation line 55 is created by modifying the fatigue life estimation line 38 by multiplying the strain energy density when the number of times of application is one by a coefficient based on the safety factor. The modified fatigue life estimation line 55 is created by translating the fatigue life estimation line 38 along the vertical axis (strain energy density). The modified fatigue life estimation line 55 takes into account the safety factor in the fatigue life (number of cycles) as well as the strain energy density on the vertical axis.

[0072] Also, for example, the fatigue life estimation line 38 is modified so that the strain energy density when the number of applications is 1 becomes smaller while maintaining the number of applications when the strain energy density is 0.1, to generate a modified fatigue life estimation line 56. The modified fatigue life estimation line 56 is obtained by modifying the slope ((Wc / Nc)) of the fatigue life estimation line 38. (-1 / β) ) is changed. The modified fatigue life prediction line 56 is based on the assumption that the fatigue life (number of cycles) obtained from the fatigue test results and the test strain smaller than the test conditions are approximately correct, and takes into account the variation in fatigue life at test strains larger than the test conditions. It is useful for designs with a high safety factor, assuming that crack growth will begin early due to a latent defect.

[0073] As shown in FIG. 13, compared to the fatigue life estimation line 38 before modification, the modified fatigue life estimation line 55 has a coefficient based on the safety factor that is smaller than 1, and when the strain energy density is Wb and the number of times of application is N 6 It is. In comparison with the fatigue life estimation line 38 before modification, the modified fatigue life estimation line 56 is a line in which the coefficient based on the safety factor is smaller than 1, the strain energy density is Wb, and the number of times of application is N 7 It is. Number of times given: N 6 , N b and N 7 is N 6 <N 7 <N b This is in a relationship.

[0074] Also, for example, it is preferable to expand the circumferential stress and strain in each finite element of the tire into a Fourier series and use the strain amplitude for each order obtained to perform the evaluation. In this case, by extracting and using only the dominant strain amplitude, it becomes possible to predict the fatigue life with higher accuracy. As an example of the strain amplitude used to estimate the fatigue life, the largest value of the strain amplitude among the Fourier orders may be used, or a higher order value such as the first to third orders may be used. When using multiple orders such as the first to third orders, it is preferable to use the sum of the strain amplitudes in each order. In addition, the order of the Fourier series expansion is preferably at least 10. As a calculation condition for the tire model to be acquired, a strain history obtained when the tire is rotated at a predetermined speed until it becomes steady may be acquired, or a strain history for one revolution of the tire model may be acquired from a static contact state.

[0075] In the tire fatigue life prediction method, the tire model created by the model creation unit 24 may have member elements corresponding to a plurality of members constituting the tire. The member elements are composed of elements that can be numerically analyzed by a computer. In this case, the acquisition step performed by the calculation unit 26 is a step of acquiring the maximum value of the strain amplitude in at least one member element among the plurality of member elements of the tire model. The estimation step performed by the estimation line creation unit 22 estimates the fatigue life by applying the maximum value of the strain amplitude acquired in the acquisition step to a fatigue life estimation line.

[0076] FIG. 14 is a schematic diagram showing an example of a configuration of a tire model according to an embodiment of the present invention. The tire model 60 shown in FIG. 14 has a cap tread element 62 which is a member element corresponding to the cap tread of the tire, an undertread element 63 which is a member element corresponding to the undertread, a sidewall element 64 which is a member element corresponding to the sidewall, a bead filler element 65 which is a member element corresponding to the bead filler, a rim cushion element 66 which is a member element corresponding to the rim cushion, an inner liner element 67 which is a member element corresponding to the inner liner, a carcass element 68 which is a member element corresponding to the carcass, and a belt element 69 which is a member element corresponding to the belt layer. The belt element 69 is provided in, for example, four layers. The maximum value of the strain amplitude in at least one member element among the multiple member elements of the tire model is obtained. In this case, the strain amplitude is obtained for each member element of the tire model, and the maximum value of the strain amplitude among them is extracted. Specifically, the strain amplitude is obtained for all elements of at least one of the component elements shown in Figure 14, namely the cap tread element 62, the undertread element 63, the sidewall element 64, the bead filler element 65, the rim cushion element 66, the inner liner element 67, the carcass element 68, and the belt element 69, and the maximum value of the strain amplitudes of all the elements is extracted. Since each member element of the tire model is assigned an element number, the position of the maximum value of the strain amplitude can be easily identified.

[0077] Also, as shown in Table 1 below, among the elements shown in Fig. 14, for example, the maximum strain amplitude is obtained for each of the member elements of the cap tread element 62, under tread element 63, sidewall element 64, bead filler element 65, rim cushion element 66, and inner liner element 67. Each element shown in Table 1 below is a rubber layer without a reinforcing layer. In order to predict the occurrence and propagation of cracks in the rubber portion of a tire, for example, among the multiple member elements of the tire model, only elements corresponding to rubber layers without reinforcing layers are extracted as shown in Table 1 below, since these have a relatively low strength compared to the reinforcing layers. In addition, the elements to be extracted in order to predict the occurrence and progression of cracks in the rubber portion of a tire are not particularly limited to the elements shown in Table 1 below, and the rubber in the reinforcing layer may also be evaluated. Of the multiple component elements of the tire model, the fatigue life is predicted for the component element with the maximum strain amplitude. Specifically, in Table 1 below, of the multiple component elements of the tire model, the rim cushion element has the maximum strain amplitude. In this case, the tire fatigue life prediction method estimates the fatigue life of the rim cushion element. In this way, by predicting the fatigue life of the component element that has the maximum strain amplitude among the multiple component elements of the tire model, it is possible to clarify which components of the tire are at high risk of failure due to crack propagation, and then predict the tire's life. It is also possible to identify the initial location of cracks inside the tire from the component element where the strain shows the maximum value.

[0078] In addition, when the approximate location of the failure can be identified in advance, such as by post-mortem analysis of a failure in an actual tire, the fatigue life is estimated for the specific component element corresponding to the failure location, rather than the component element showing the maximum strain among the multiple component elements of the tire model, for example, the rim cushion element described above. In this case, the strain amplitude is obtained for all elements in the specific component element corresponding to the failure location, and the maximum value is extracted from the strain amplitudes of all elements. This maximum value is used to estimate the fatigue life of the specific component element corresponding to the failure location. This makes it possible to efficiently predict the fatigue life of a tire with high accuracy.

[0079] [Table 1]

[0080] The present invention is basically configured as described above. Although the tire fatigue life prediction method of the present invention has been described in detail above, the present invention is not limited to the above-mentioned embodiment, and various improvements and modifications may be made without departing from the spirit and scope of the present invention. EXAMPLES

[0081] Hereinafter, examples of the tire fatigue life prediction method of the present invention will be specifically described. In this example, using samples A, B, and C shown below, the effect of the tire fatigue life prediction method of the present invention was evaluated by comparing the running distance at failure in an indoor durability test with the predicted value of the failure occurrence distance using the tire fatigue life prediction method of the present invention. In this example, the tire size of sample A was 285 / 85R22.5, the tire size of sample B was 275 / 70R22.5, and the tire size of sample C was 265 / 60R22.5. The tires of samples A, B, and C all had the same configuration except for the tire size, and the components of each configuration were also made of the same vulcanized rubber material.

[0082] [Indoor durability test] In the indoor durability test of actual tires, samples A, B, and C were mounted on standard rims of the JATMA standard, and then internal pressure was applied. Then, the tires of samples A, B, and C to which internal pressure was applied were placed on a rotating drum, and a load equivalent to the load capacity corresponding to the specified air pressure specified in the JATMA standard shown in Table 2 below was applied. The drum was rotated and the tires were rolled at a speed of 50 km / h, and the distance at the time of destruction was calculated from the number of tire revolutions until destruction occurred. The tire sizes of samples A, B, and C are shown in Table 2 below. In the indoor durability test, the distance at breakage of sample A was set as 100, and samples B and C were evaluated. The results are shown in Table 3 below. In the tires of samples A, B, and C, destruction occurred in the region (rim cushion portion) near the carcass end where destruction due to crack propagation occurred in the indoor durability test.

[0083] [Table 2]

[0084] [Fatigue life prediction] As described above, in the tires of samples A, B, and C, destruction occurred in the region (rim cushion portion) near the carcass end where destruction due to crack propagation occurred in the indoor durability test. For this reason, in predicting the fatigue life of the tire, the strain amplitude of each element was calculated in the rim cushion element 66 of the tire model 60 shown in Figure 14, and the fatigue life was predicted using the maximum value among them. The predicted running distance was calculated by counting one application (one cycle) on the fatigue life estimation line as one rotation. The number of applications on the fatigue life estimation line was taken as the distance at the time of fracture. In predicting the fatigue life of the tires, the distance at breakage of sample A was set as 100, and samples B and C were evaluated. The results are shown in Table 3 below.

[0085] The fatigue life prediction was carried out as follows. The vulcanized rubber material used was the same as that used for the rim cushion. The following three tests were carried out on the material used for the rim cushion: a tensile test, a crack growth test, and a constant strain tensile fatigue test. The tensile test was carried out on the material used in the rim cushion, as specified in JIS K 6251:2017 "Vulcanized rubber and thermoplastic rubber - Determination of tensile properties". From this, a stress-strain curve was obtained and a strain energy density function was created. A crack growth test was carried out on the material used for the rim cushion portion using a crack growth rate measuring device 40 shown in FIG. 5, and the crack growth rate and tear energy were obtained. A constant strain tensile fatigue test, as specified in JIS K 6270:2018, was conducted on the material used in the rim cushion to obtain the fatigue life at one specified test strain level. This fatigue life was applied to the strain energy density function created from the results of the tensile test to calculate the corresponding strain energy density. A fatigue life estimation line was then created for the material (vulcanized rubber material) used in the rim cushion.

[0086] The simulation conditions for obtaining the strain amplitude were as follows: A tire model (see Fig. 14) was created that corresponds to the above-mentioned tire samples A, B, and C and is composed of elements that can be numerically analyzed by computer. A rolling analysis (simulation) was carried out under the same load and air pressure conditions as the indoor durability test. In the rolling analysis, the tire model was rolled at a speed of 50km / h, and the strain history for one revolution of the tire model at the steady state was obtained.The maximum strain amplitude was then obtained for the rim cushion element. In the rolling analysis, the tire model was subjected to an internal pressure filling process based on the air pressure conditions. The internal pressure filling process reproduced the above-mentioned situation in which a tire was mounted on a rim of a specific rim size specified by JATMA and the tire was filled with internal pressure. The rolling analysis (simulation) was performed using the general-purpose simulation software Abaqus. Among the rim cushion elements, the maximum value of the strain amplitude was applied to the fatigue life estimation line for the material (vulcanized rubber material) used in the rim cushion part described above, and the fatigue life of the tire model corresponding to tire samples A, B, and C was predicted.

[0087] [Table 3]

[0088] As shown in Table 3 above, the fatigue life prediction results for tire samples A, B, and C tended to match the results of the indoor durability tests, and the numerical values ​​were also roughly consistent, demonstrating that the tire fatigue life prediction method has high prediction accuracy. [Explanation of symbols]

[0089] 10 Fatigue life prediction device 12 Processing Unit 14 Input section 16 Display 20 Condition setting section 22 Estimation Line Creation Department 24 Model Creation Department 26 Arithmetic section 27 Estimation part 28 Memory 30 Display control unit 32 Control section 34 SS curve 35 areas 38 Fatigue life prediction line 39, 39a, 39b waveform 40 Crack Growth Rate Measurement Device 41 Samples 41c Crack 42a, 42b chuck 43 Drive unit 44 Imaging unit 45 Control and calculation section 46 Tire Models 47 Road surface model 47a surface 50 Fatigue life prediction line 51 First revised fatigue life line 52 Second revised fatigue life line 53 Fatigue life prediction line 54 Fatigue life prediction line 55 Modified fatigue life prediction line 56 Modified fatigue life prediction line 60 Tire Models 62 Cap tread element 63 Undertread elements 64 Sidewall Elements 65 Bead filler element 66 Rim cushioning element 67 Inner Liner Elements 68 Carcass Elements 69 Belt element Aε amplitude C Rotational Axis DL Rolling direction β Slope

Claims

1. A creation step of creating a fatigue life estimation line showing a relationship between the fracture energy and the number of cycles of a vulcanized rubber material constituting a tire, using a strain energy density function, a crack growth rate, a tear energy, and a strain energy density of the vulcanized rubber material constituting the tire; an acquisition step of acquiring a strain amplitude for one revolution of a tire model when the tire is in contact with the ground, the tire model being constituted by elements that can be numerically analyzed by a computer and that represent the tire; and an estimation step of applying the strain amplitude value acquired in the acquisition step to the fatigue life estimation line to estimate a fatigue life.

2. The creating step includes a step of performing a tensile test on a sample of the vulcanized rubber material to obtain a relationship between a tensile stress and a tensile strain, and calculating the strain energy density function using the relationship between the tensile stress and the tensile strain. performing a crack growth rate measurement on a sample of the vulcanized rubber material using a crack growth rate measurement device and calculating the crack growth rate and the tear energy; 2. The tire fatigue life prediction method according to claim 1, further comprising a step of: conducting a constant strain tensile fatigue test at one level of test strain, acquiring the tensile strain and the number of times the tensile force is applied, and calculating the strain energy density.

3. The tire fatigue life prediction method according to claim 1 , wherein an aged vulcanized rubber material is used as the vulcanized rubber material constituting the tire.

4. The creation step of creating the fatigue life estimation line includes a step of creating a corrected fatigue life estimation line by modifying the fatigue life estimation line based on a structure of the tire, The tire fatigue life prediction method according to claim 1 , wherein the estimation step estimates the fatigue life by applying the strain amplitude value acquired in the acquisition step to the corrected fatigue life estimation line.

5. The creation step of creating the fatigue life estimation line includes a step of creating a corrected fatigue life estimation line by correcting the fatigue life estimation line based on the median value of the strain amplitude obtained in the acquisition step, The tire fatigue life prediction method according to claim 1 , wherein the estimation step estimates the fatigue life by applying the strain amplitude value acquired in the acquisition step to the corrected fatigue life estimation line.

6. The creation step of creating the fatigue life estimation line includes a step of creating a corrected fatigue life estimation line by correcting the fatigue life estimation line based on a safety factor, The tire fatigue life prediction method according to claim 1 , wherein the estimation step estimates the fatigue life by applying the strain amplitude value acquired in the acquisition step to the corrected fatigue life estimation line.

7. The obtaining step includes a first step of performing a contact analysis on the tire model to obtain stress and strain waveforms in a tire circumferential direction for each element of the tire model; a second step of performing a Fourier transform on the stress and strain waveforms in the tire circumferential direction of each of the elements of the tire model obtained in the first step, and acquiring a strain spectrum for each of the elements of the tire model; The method for predicting a fatigue life of a tire according to claim 1 , further comprising a third step of obtaining the strain amplitude from the spectrum of the strain obtained in the second step.

8. the tire model has member elements corresponding to a plurality of members constituting the tire, the member elements being composed of the elements that can be numerically analyzed by the computer, the obtaining step is a step of obtaining a maximum value of the strain amplitude in at least one member element among a plurality of member elements of the tire model, 2 . The tire fatigue life prediction method according to claim 1 , wherein the estimation step estimates the fatigue life by applying the maximum value of the strain amplitude acquired in the acquisition step to the fatigue life estimation line.

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