JP2022091029A - Tire designing method, program, and tire designing device - Google Patents

Abstract

To provide a tire designing method capable of calculating characteristic values and costs for a plurality of tires different in layout with less labor.SOLUTION: The tire designing method includes the steps of: acquiring an initial finite element model representing the section of a tire composed of a plurality of tire components; generating a plurality of morphing models different in layout through morphing on the basis of the initial finite element model; executing finite element analysis for the morphing models to calculate tire characteristic values; and calculating a tire cost for each morphing model on the area of each tire component appearing in the morphing model and the material cost of each tire component.SELECTED DRAWING: Figure 5

Description

The present invention relates to a tire design method, a program and a tire design device.

Conventionally, there has been known a method of acquiring a tire characteristic value by performing a finite element analysis using a finite element model of a tire in which a design variable is set (see, for example, Patent Document 1).

Conventionally, when designing a tire, a plurality of finite element models with different design variables have been created, and each finite element model has been subjected to finite element analysis to obtain characteristic values. Then, the tire was designed by adopting the design variable that optimizes the characteristic value.

Japanese Unexamined Patent Publication No. 2017-91007

However, it is troublesome to create a finite element model from scratch for each tire with different design variables. There is also a request to consider the cost of tires when designing tires.

The present invention has been made in view of such circumstances, and provides a tire design method, a program, and a tire design device capable of calculating characteristic values and costs with little effort for a plurality of tires having slightly different layouts. The challenge is to provide.

The tire design method of the embodiment includes a step of acquiring an initial finite element model representing a cross section of a tire composed of a plurality of tire components in a tire design method including a step of calculating a tire characteristic value by a computer based on design variables. , A step of generating a plurality of morphing models having different layouts by morphing based on the initial finite element model, a step of performing a finite element analysis for each of the morphing models, and a step of calculating the characteristic value of the tire. It includes a step of calculating the cost of each tire of the morphing model based on the area of each tire component appearing in the morphing model and the material cost of each tire component.

The program of the embodiment is a program that executes the above method.

Further, the tire design device of the embodiment acquires an initial finite element model representing a cross section of a tire composed of a plurality of tire components in a tire design device including a characteristic value calculation unit that calculates a tire characteristic value based on design variables. An initial model acquisition unit, a morphing unit that generates a plurality of morphing models having different layouts by morphing based on the initial finite element model, a characteristic value calculation unit that calculates characteristic values for each of the morphing models, and the above. It includes a cost calculation unit that calculates the cost of each tire of the morphing model based on the area of each tire component appearing in the morphing model and the material cost of each tire component.

According to the above-mentioned tire design method, program, and tire design device, it is possible to calculate characteristic values and costs for a plurality of tires having slightly different layouts with little effort.

The figure which shows the tire design apparatus. The figure which shows the database. The figure which shows the table. The figure which shows the tire 2D model. Flowchart of tire design method. The figure of the tire model of an Example. (A) is an initial finite element model. (B) is the optimum model. The figure which shows the tire design apparatus of the modification example. A plot of the relationship between characteristic values and costs. The figure which plotted the data which the cost of a tire falls within a desired range. Flowchart of tire design method of modification example.

The embodiment will be described with reference to the drawings. It should be noted that the embodiments described below are merely examples, and those appropriately modified without departing from the spirit of the present invention shall be included in the scope of the present invention.

In the following description, the tire axis direction is the extension direction of the tire rotation axis.

The tire design device 10 of the embodiment generates a plurality of morphing models having different layouts based on an initial finite element model representing a cross section of a tire, performs finite element analysis on each morphing model, and performs characteristic values of each tire ( It is a device that calculates the cost of each tire based on a plurality of morphing models while calculating (hereinafter referred to as "tire characteristic value"). The calculation results are used for optimizing the tire layout.

The layout is, for example, the dimensions of various parts of the tire constituent members and the amount of overlap of the two tire constituent members. Examples of the dimensions of the tire component include the thickness of the tire component. Here, the tire constituent member is a member such as a tread rubber 25 or a sidewall rubber 26 (see FIG. 4) constituting the tire. Further, the thickness is a length in a direction perpendicular to the surface on the inner surface side of the tire from the surface on the inner surface side of the tire to the surface on the outer surface side of the tire of the tire constituent member. In the present embodiment, a plurality of thicknesses are used. As the morphing model, it is assumed that a plurality of morphing models having different tire layouts, more specifically, a plurality of morphing models having different thicknesses of tire components are generated. It can be said that generating a plurality of morphing models is a kind of tire design method because a plurality of tires are simply designed.

As shown in FIG. 1, the tire design device 10 of the embodiment is a computer system including a processing device (CPU) 11, a storage device 12, and the like. An input device 13 such as a keyboard and a mouse and an output device 14 such as a display are connected to the tire design device 10.

The storage device 12 generates a program 15 for executing the method of the present embodiment, a database 16 in which data necessary for finite element analysis and cost calculation are stored, and a group of design variables used in morphing described later. Table 17 and the like for this purpose are stored. By reading and executing the program 15 of the storage device 12, the processing device 11 reads and executes the initial model acquisition unit 30, the morphing unit 31, the characteristic value calculation unit 32, the member volume calculation unit 33, the cost calculation unit 34, and the response curved surface generation unit. 35, functions as an optimization calculation unit 36.

As shown in FIG. 2, in the database 16, the material numbers of the tire components (hereinafter referred to as “blending numbers”) and the data such as the physical property values, densities, and material costs of each material are linked and stored. There is. Here, the physical property values include physical property values required for simulation by a finite element model, such as Poisson's ratio and elastic modulus. The material cost is the price per unit mass of the material. Further, as the material, various rubbers having different formulations are assumed. Density and material cost data are used to calculate tire costs, and physical property values are used for finite element analysis.

Further, as shown in FIG. 3, the table 17 defines the amount of change in the design variable from the initial finite element model. In the present embodiment, it is assumed that at least a plurality of morphing models in which the thickness of the tire constituent member is changed are generated. Therefore, the table 17 has at least a reference thickness of a tire component such as a tread rubber 25 (see FIG. 4) (in other words, the thickness of the tire component in the initial finite element model. An initial finite such as this thickness. The amount of change from the numerical value of the design variable in the element model is defined as the "reference value"). By adding or subtracting the numerical values in Table 17 with respect to the reference value, a group of design variables used in morphing is generated.

When trying to generate a morphing model in which design variables other than the thickness of the tire component are also changed, the table 17 defines the amount of change in the design variable to be changed in addition to the thickness of the tire component. ing.

It should be noted that the design variables that are changed for the generation of the plurality of morphing models include design variables related to the layout of the tire, for example, the dimensions of various parts of the tire component. The thickness of the tire component is one of the design variables related to the layout. In addition, tread width and the like are also design variables related to layout.

The initial model acquisition unit 30 acquires a tire model. The tire model acquired here is a finite element model in which the tire is divided into a finite number of elements. Element numbers, node numbers, node coordinates, material property values (density, Young's modulus, Poisson's ratio, yield stress, maximum strength, linear expansion coefficient, etc.) are set for each element.

The finite element model in this embodiment is a two-dimensional model of the axial cross section of the tire as shown in FIG. 4 (hereinafter referred to as “tire two-dimensional model 20”). Further, the tire two-dimensional model 20 is a model on one side in the tire axial direction. However, as a two-dimensional tire model, a model in which both sides in the tire axial direction are aligned may be acquired.

In the tire two-dimensional model 20, tire components such as a bead 21, a carcass ply 22, an inner liner 23, a belt 24, a tread rubber 25, a sidewall rubber 26, and a rim strip 27 appear. Further, the main groove 28 appears in the tread rubber 25. In an actual tire, the main groove 28 makes one round in the tire circumferential direction.

Such a tire two-dimensional model 20 is created by dividing the shape of the two-dimensional CAD drawing of the tire into a mesh and is stored in advance in the storage device 12. The mesh division is to divide the tire into a large number of elements, and can be performed by a known method.

The tire two-dimensional model 20 at the time acquired by the initial model acquisition unit 30 is referred to as an initial finite element model.

The morphing unit 31 generates a morphing model whose layout is changed from the initial finite element model. In the present embodiment, as a morphing model, it is assumed that a plurality of models in which the layout of the tire constituent members, in detail, at least the thickness of the tire constituent members is changed, are generated.

Therefore, the region whose thickness is to be changed is selected in the initial finite element model. Here, the area is a part or all of the tire constituent members. By this selection, all the nodes (or some nodes satisfying a predetermined condition) in the selected area are set as control points. The selection of the area will be described later.

The morphing unit 31 displaces the set control points based on the table 17. The morphing unit 31 generates a plurality of new coordinates by applying the respective values of the table 17 to the coordinates of the set control points (that is, adding or subtracting the values of the table 17), and those new coordinates are generated. The thickness of the tire component is generated as a design variable based on the coordinates. Further, the morphing unit 31 also generates design variables (for example, tread width) other than the thickness of the tire constituent member, if necessary.

The morphing unit 31 generates a morphing model group by morphing based on the generated design variables. The plurality of morphing models included in the morphing model group have slightly different thicknesses of tire components. Further, when the morphing unit 31 also generates design variables other than the thickness of the tire constituent member, the design variables are also slightly different in the plurality of morphing models. The plurality of morphing models are all finite element models, but the nodes of the tire components are displaced with respect to the initial finite element model, and the mesh shape is changed.

The morphing portion 31 includes only an element having a length in the thickness direction of the tire component in the initial finite element model of a predetermined value or less (for example, 0.2 mm or less) in the direction of increasing the thickness of the tire component. Change.

The characteristic value calculation unit 32 executes finite element analysis using the morphing model generated by the morphing unit 31 and calculates the tire characteristic value. Since there are a plurality of morphing models generated by the morphing unit 31, the characteristic value calculation unit 32 executes finite element analysis for each morphing model to calculate the tire characteristic value. Examples of the calculated tire characteristic values include vertical rigidity, lateral rigidity, front-rear rigidity, rolling resistance, ground contact pressure distribution, ground contact length, ground contact width, cornering power, peak μ, and the like of the tire.

When a model other than the tire (for example, a road surface model) is required for the finite element analysis, the model is acquired by the initial model acquisition unit 30 and used for the finite element analysis by the characteristic value calculation unit 32.

Depending on the tire characteristic value to be calculated, the characteristic value calculation unit 32 can execute the finite element analysis by using the two-dimensional morphing model (finite element model) as it is. However, depending on the tire characteristic value to be calculated, the characteristic value calculation unit 32 needs to execute the finite element analysis using the three-dimensional finite element model. In that case, the three-dimensional model creation unit (not shown) creates a three-dimensional finite element model before the characteristic value calculation unit 32 executes the finite element analysis.

Specifically, the three-dimensional model creation unit creates a three-dimensional finite element model by copying and developing the two-dimensional morphing model generated by the morphing unit 31 in the tire circumferential direction around the tire rotation axis. The three-dimensional finite element model is created for each of the plurality of morphing models generated by the morphing unit 31.

The member volume calculation unit 33 and the cost calculation unit 34 execute the calculation of the tire cost separately from the calculation of the characteristic value by the characteristic value calculation unit 32.

The member volume calculation unit 33 calculates the volume of each tire component for each morphing model generated by the morphing unit 31. For example, the member volume calculation unit 33 calculates the volume of each element in three dimensions by making each element of the morphing model make one revolution around the tire rotation axis. Then, the member volume calculation unit 33 calculates the volume of the tire constituent member by adding the volumes of all the elements constituting the tire constituent member. Specifically, first, using Pappus-Guldin's theorem, the volume when each element of the morphing model is made to make one round around the tire rotation axis is calculated by the following equation.

Here, R _m is the distance from the tire rotation axis to the center of gravity of the m-th element, S _m is the area of the m-th element, and v _m is the volume of the m-th element. The distance R from the tire rotation axis to the center of gravity of the element is obtained from the coordinates of the center of gravity, and the coordinates of the center of gravity are obtained from the coordinates of the node. By adding the volumes v _m of each element obtained in this way by the following equation, the volume of the tire constituent member can be obtained.

Here, j is the number of elements constituting the tire constituent member.

When the morphing model is a model having only one side in the tire axial direction, the volume of the tire component can be calculated by doubling the volume V calculated by the equation of Equation 2. Further, when the morphing model is a model in which both sides in the tire axial direction are aligned, the volume V calculated by the equation of Equation 2 is the volume of the tire constituent member.

In this way, the member volume calculation unit 33 calculates the volume of each tire component of the three-dimensional tire based on each morphing model.

The cost calculation unit 34 calculates the tire cost from the material cost of each tire component read from the database 16 and the volume of each tire component calculated by the member volume calculation unit 33. Specifically, the cost calculation unit 34 calculates the cost of the tire component by multiplying the volume of the tire component by the material density and the material cost of the tire component, and adds the costs of all the tire components. The cost of the tire is calculated by. That is, the tire cost is calculated by the following formula.

Here, Y is the cost of the tire (yen), V _n is the volume of the nth tire component (m ³ ), ρ _n is the material density of the nth tire component (kg / m ³ ), and cn is the material density of the _nth tire component. The material cost (yen / kg) and i are the number of tire components constituting one tire.

If the database 16 stores only the data of the material of the rubber member and does not include the data of the material of the member other than the rubber member such as the steel cord and the organic fiber cord, the formula of Equation 3 alone is used for the tire. The exact cost cannot be calculated. In that case, a more accurate cost of the tire can be calculated by adding the cost of the member other than the rubber member to the cost Y calculated by the equation 3.

On the other hand, when the database 16 includes data on materials for members other than rubber members such as steel cords and organic fiber cords, the more accurate cost of the tire can be calculated by the formula of Equation 3.

In this way, the costing unit 34 calculates the cost of the tires of each morphing model.

The response curved surface generation unit 35 generates a response curved surface showing the relationship between any one of the tire characteristic values calculated by the characteristic value calculation unit 32 or the tire cost calculated by the cost calculation unit 34 and the design variable. The design variable here includes the thickness of the tire component. If only the thickness of the tire component is considered as a design variable, the response surface is actually a curve. However, when considering factors other than the thickness of the tire component as design variables, the response curved surface is literally a curved surface.

The response curved surface generation unit 35 generates a plurality of response curved surfaces. For example, a plurality of response curves such as a response curve between the design variable and the cost of the tire, a response curve between the design variable and the longitudinal rigidity of the tire, and a response curve between the design variable and the rolling resistance are generated.

By generating the response curved surface by the response curved surface generation unit 35, the data of the relationship between the design variable and the tire characteristic value, which was discrete data, becomes a continuous curved surface showing the relationship between the two.

In the optimization calculation unit 36, as the setting for performing the optimization calculation, the range of the design variable is set, the constraint of the characteristic value is set, and the objective function is set. The constraint of the characteristic value is, for example, an upper limit value and a lower limit value of the characteristic value.

The objective function in this embodiment is a function to be minimized or maximized, including the tire characteristic value and the cost of the tire. For example, when trying to obtain a design variable in which the vertical rigidity of the tire is large and the cost of the tire is small, the following objective function F is set in the optimization calculation unit 36.

Here, X is the rate of decrease in the vertical rigidity of the tire of the morphing model with respect to the vertical rigidity of the tire of the initial finite element model, Y is the rate of decrease in the cost of the tire of the morphing model with respect to the cost of the tire of the initial finite element model, a and b. Are weighting coefficients, respectively.

The optimization calculation unit 36 executes the optimization calculation after setting the range of design variables, the constraint of the characteristic value, and the objective function. Specifically, the optimization calculation unit 36 is designed to repeatedly calculate the objective function using the response curved surface generated by the response curved surface generation unit 35 while changing the design variables, and to minimize or maximize the objective function. Find the combination of variables. An optimization algorithm such as the Nelder-Mead method is used for this calculation.

For example, when the objective function F of the above equation 4 is set as the objective function, the optimum design variable in which the vertical rigidity of the tire is large and the cost of the tire is small is obtained by the optimization calculation by the optimization calculation unit 36. I want it. The design variable obtained at this time includes the thickness of the tire component.

The design variables obtained by the optimization calculation unit 36 in this way are output to the output device 14. Further, the calculation results by the morphing unit 31, the characteristic value calculation unit 32, the member volume calculation unit 33, the cost calculation unit 34, and the response curved surface generation unit 35 are also output to the output device 14, respectively.

The tire design method using the tire design device 10 will be described with reference to the flowchart of FIG.

First, the initial model acquisition unit 30 acquires the tire two-dimensional model 20 as the initial finite element model (S1).

Next, in the morphing unit 31, a tire component whose thickness or the like is changed in the initial finite element model and a region where the thickness or the like is changed in the tire component member are selected (S2).

Here, as the tire component whose thickness is changed, a tire component having an area equal to or larger than a predetermined area is selected in the initial finite element model. For example, a tire component having an occupancy of 3% or more with respect to the total area of the initial finite element model is selected. Examples of such a tire component include a tread rubber 25 and a sidewall rubber 26. Further, it is preferable that the fiber material (fiber cord or the like) and the inner liner 23 are excluded from the tire constituent members whose thickness is changed.

Further, in order to select a region for changing the thickness, first, the tire constituent members are divided into a plurality of regions arranged in the longitudinal direction thereof on the cross section in the tire axial direction. However, if the tire component does not have a sufficient length on the cross section in the tire axial direction, the tire component is not divided into a plurality of regions.

As a specific example, when the length of the tire component on the cross section in the tire axial direction is 30 mm or more, the tire component is divided into three regions in the longitudinal direction. When the length of the tire component on the cross section in the tire axial direction is 20 mm or more and less than 30 mm, the tire component is divided into two regions in the longitudinal direction. Further, when the length of the tire constituent member on the cross section in the tire axial direction is less than 20 mm, the tire constituent member is not divided into regions.

The length of the tire constituent member is the longer of the lengths of the tire inner surface side surface and the tire outer surface side surface on the tire axial cross section. Further, the longitudinal direction of the tire component is the direction of a line in which the length of the tire component is defined on the cross section in the tire axial direction.

After the tire component is divided into a plurality of regions, one or more regions whose thickness is to be changed are selected from the plurality of regions. At this time, all areas of the tire components may be selected.

The selection of the member whose thickness is to be changed, the division of the member into the area, and the selection of the area whose thickness is to be changed may be performed by the operator via the input device 13, but the processing device 11 executes the program 15. It may be automatically performed by the area setting unit realized by reading and executing.

When the region whose thickness is to be changed is selected, the morphing unit 31 sets all the nodes (or some nodes satisfying a predetermined condition) in the selected region as control points.

Next, the morphing unit 31 generates a design variable group (S3). Design variables include numerical values for tire layout, and more specifically for tire component thickness.

Next, the morphing unit 31 generates a morphing model group based on the design variables (S4). In the plurality of generated morphing models, the thickness of the region selected in step S2 is slightly different.

Next, for the morphing model, which is a finite element model, the formulation number is acquired from the database 16 (S5). Specifically, a compounding number stored in the database 16 is assigned to each element of the morphing model, which is a finite element model, through an input operation by the operator in the input device 13. As a result, each element is associated with the physical property value, density, and material cost associated with the compounding number. Since there are a plurality of elements for one tire component, the same compounding number is assigned to the plurality of elements belonging to the same tire component.

The morphing model can be used for simulation by assigning physical property values to each element. In addition, the morphing model can be used to calculate the cost of tires by assigning density and material cost to each element.

Next, the characteristic value calculation unit 32 executes finite element analysis for each of the generated plurality of morphing models, and calculates the tire characteristic value in each morphing model (S6). The characteristic value calculation unit 32 reads the physical characteristic value of the material from the database 16 based on the compounding number assigned in step S5 and uses it for the finite element analysis.

When a three-dimensional finite element model is required for finite element analysis, a three-dimensional model creation unit (not shown) performs a two-dimensional morphing model before the characteristic value calculation unit 32 executes the finite element analysis. Create a three-dimensional finite element model based on.

Next, the cost of the tire is calculated based on each morphing model. Specifically, first, the member volume calculation unit 33 calculates the volume of each tire component member based on the morphing model (S7).

Next, the cost calculation unit 34 calculates the cost of the tire based on the volume, density, and material cost of each tire component (S8). At this time, the cost calculation unit 34 reads the cost of the material from the database 16 based on the compounding number assigned in step S5 and uses it for the calculation.

Next, the response curved surface generation unit 35 generates a response curved surface of the tire characteristic value calculated in step S6 and the design variable, and a response curved surface of the tire cost calculated in step S8 and the design variable (S9). ). The design variable here includes the thickness of the tire component.

Next, in the optimization calculation unit 36, the range of the design variable is set, the constraint of the characteristic value is set, and the objective function is set (S10). Next, the optimization calculation unit 36 performs an optimization calculation to obtain a combination of design variables that minimizes or maximizes the objective function (S11). The combination of design variables obtained in step S11 (one of which is the thickness of the tire component) is a combination of design variables that realizes an optimum solution in which the tire characteristic value and the cost of the tire are compatible.

By designing the tire based on the design variable obtained in step S11, it is possible to design an optimum tire, for example, a tire having a large vertical rigidity of the tire and a low cost of the tire.

Next, the effect of this embodiment will be described. In the tire design method of the present embodiment, a step of acquiring a tire two-dimensional model 20, a step of generating a plurality of morphing models having different layouts based on the tire two-dimensional model 20, and a finite element analysis for each morphing model are executed. This includes a step of calculating the characteristic value of the tire and a step of calculating the cost of the tire of each morphing model based on the area and material cost of each tire component appearing in the morphing model.

In this way, since a plurality of morphing models are generated using the morphing technique based on the tire two-dimensional model 20, it is possible to generate (in other words, design) a plurality of tire models having different layouts with little effort.

Further, in the tire design method of the present embodiment, since the tire characteristic value is calculated for a plurality of morphing models and the tire cost is calculated, the characteristic value and the cost are calculated for a plurality of tires having slightly different layouts. Can be done.

Then, since the characteristic values and the costs are calculated for a plurality of tires having slightly different layouts, the tire design device 10 can obtain the optimum tire design variables based on the calculation results, or calculate them. The results can be used by humans as a reference for optimal tire design.

In addition, design variables related to the layout of the tire and objective functions including the cost of the tire and tire characteristic values are set, and the design variables that minimize or maximize the objective function are calculated by the optimization calculation. It is possible to obtain a design variable in which both the cost and the tire characteristic value are compatible.

Further, as a member whose layout (particularly thickness) is changed by morphing, a tire component having an area equal to or larger than a predetermined value (for example, an occupancy rate of 3% or more with respect to the total area of the initial finite element model) is selected in the initial finite element model. Therefore, it is possible to select a tire component that has sufficient room for design change and has a large contribution to cost as a target to be changed. In addition, since the fiber material (fiber cord, etc.) and the inner liner 23 are excluded from the members whose layout (especially the thickness) is changed by morphing, the tire components whose design cannot be actually changed due to the nature of the material and the thickness. It can be prevented from being selected, and the calculation cost can be suppressed.

Further, the calculation cost can be suppressed by selecting only a part of the selected tire constituent member as a region to be changed by morphing. Further, a tire component having a longer length in a cross section in the tire axial direction is divided into more regions, and a region to be changed by morphing is selected from these regions, so that the tire component can be actually manufactured. The controllable range is changed in morphing, and there is no waste of calculation.

Further, as described above, when the thickness of the selected region is changed by morphing, the region including an element having a length in the thickness direction of a predetermined value or less (for example, 0.2 mm or less) in the initial finite element model is used. In morphing, change only in the direction of increasing the thickness. Thereby, it is possible to prevent the generation of tire components that are too thin in morphing, and it is possible to prevent the generation of a morphing model that cannot be manufactured.

Further, the cost of the tire as a finished product is calculated based on the volume of each tire component obtained based on the morphing model which is a finite element model and the material cost of each tire component stored in the database 16. Thereby, the tire cost can be calculated by utilizing the managed material cost data and the finite element model created for the simulation.

Further, in the present embodiment, the volume of each tire component in one tire is calculated by calculating the volume of each tire component when the two-dimensional morphing model is deployed once in the tire circumferential direction. Can be calculated. Then, the cost of the tire can be calculated using the volume. Therefore, when it is not necessary to create a three-dimensional finite element model for calculating tire characteristics, calculate the tire cost without creating a three-dimensional model just for calculating the tire cost. Can be done.

Further, the tire design device 10 of the embodiment includes an initial model acquisition unit 30 that acquires an initial finite element model, a morphing unit 31 that generates a plurality of morphing models having different layouts based on the initial finite element model, and each morphing model. Based on the characteristic value calculation unit 32 that calculates the tire characteristic value based on the design variables, the area of each tire component appearing in the morphing model, and the material cost of each tire component, the cost of the tire of each morphing model is calculated. It has a cost calculation unit 34 for calculation.

As described above, since the tire design device 10 generates a plurality of morphing models by the morphing technique, it is possible to generate a plurality of tire models having slightly different layouts with less effort. Then, the tire design device 10 can calculate the tire characteristic value and the cost for those tires by the characteristic value calculation unit 32 and the cost calculation unit 34.

Next, an embodiment will be described. As an example, the method of the above embodiment was actually executed. FIG. 6A is an initial finite element model. Further, FIG. 6B is an optimum model designed based on the design variables obtained in step S11 by executing the above steps 1 to S11. Comparing FIG. 6 (a) and FIG. 6 (b), it can be seen that the sidewall rubber and the bead filler are thinner in the optimum model of FIG. 6 (b).

Table 1 shows the values of the tire cost, longitudinal rigidity, and rolling resistance in the optimum model when the value in the initial finite element model is 1. As for the cost of tires, the smaller the number, the cheaper it is. As for the vertical rigidity and rolling resistance, the smaller the value, the better the performance.

As can be seen from Table 1, it was confirmed that the optimum model based on the design variables obtained by the method of the above embodiment has smaller values and is superior to the initial finite element model in terms of cost, longitudinal rigidity and rolling resistance.

Various changes can be made to the above embodiments. An example of the change will be described below.

<Change example 1>
FIG. 7 shows a modified example tire design device 110. The tire design device 110 has a cluster analysis unit 135 and an optimum design variable identification unit 136 instead of the response curved surface generation unit 35 and the optimization calculation unit 36 in the tire design device 10 of the above embodiment. The cluster analysis unit 135 and the optimum design variable identification unit 136 are realized by the processing device 11 reading and executing the program 15.

The cluster analysis unit 135 acquires data of characteristic values and costs for a plurality of morphing models. Here, the characteristic value is any one of the characteristic values of the tire (vertical rigidity of the tire, rolling resistance, etc.) calculated by the characteristic value calculation unit 32. The cost is the cost of the tire calculated by the cost calculation unit 34. Since there are multiple morphing models, there are as many relationships between characteristic values and costs as there are morphing models.

The relationship between the characteristic value and the cost can be plotted as shown in FIG. One plot point shows the relationship between characteristic values and costs for one morphing model. The number of plot points matches the number of morphing models.

The cluster analysis unit 135 extracts data in which the tire cost falls within a desired range from the data shown in FIG. Here, the desired range of the tire cost is input and set by the operator from the input device 13. In FIG. 8, the data in the range between the two horizontally extending broken lines is the data to be extracted. The extracted data is shown in FIG.

The cluster analysis unit 135 executes a cluster analysis on the extracted data, and classifies the extracted data into groups according to plot points (relationship between the characteristic value and the cost) in which the characteristic values of the tires are close to each other. As a method of cluster analysis, various methods such as hierarchical clustering by Ward's method can be used.

In FIG. 9, the data in the range sandwiched by the two vertically extending broken lines belong to the same group. In FIG. 9, seven groups of G1 to G7 are formed. G1 to G7 are in order of magnitude of tire characteristic value, G1 is the group having the smallest tire characteristic value, and G7 is the group having the largest tire characteristic value.

The optimum design variable specifying unit 136 determines the relationship between the magnitude of the characteristic values of the plurality of groups G1 to G7 classified by the cluster analysis unit 135 and the magnitude of the design variable that is the basis for calculating the characteristic values of the groups G1 to G7. organize. Then, the optimum design variable specifying unit 136 specifies a design variable having the same magnitude relation as the magnitude relation of the characteristic value, and the design variable is specified as the optimum design variable.

For example, when the thickness of the tread rubber 25 is the smallest in the group G1 and the largest in the group G7, the design variable used as the basis for calculating the magnitude relationship between the characteristic values of the groups G1 to G7 and the characteristic values of the groups G1 to G7. The magnitude relationship (that is, the thickness of the tread rubber 25) is the same. Therefore, the optimum design variable specifying unit 136 specifies the thickness of the tread rubber 25 as the optimum design variable.

The cluster analysis unit 135 and the optimum design variable identification unit 136 follow the flowchart of FIG. First, the cluster analysis unit 135 acquires data of characteristic values and costs for a plurality of morphing models (S1). Next, the cluster analysis unit 135 extracts data in which the tire cost falls within a desired range from the acquired data (S2). Next, the cluster analysis unit 135 executes a cluster analysis on the extracted data, and classifies the extracted data into groups according to data (relationship between the characteristic value and the cost) having similar tire characteristic values (S3).

Next, the optimum design variable identification unit 136 organizes the relationship between the magnitude of the characteristic values of a plurality of groups classified by the cluster analysis unit 135 and the magnitude of the design variable on which the characteristic values of those groups are calculated. (S4). Then, the optimum design variable specifying unit 136 specifies a design variable having the same magnitude relation as the magnitude relation of the characteristic value, and the design variable is specified as the optimum design variable (S5).

The optimum design variable identified in this way is an effective design variable for improving the characteristics of the tire while keeping the cost of the tire within a desired range. Therefore, by designing the tire using optimal design variables. Tires with optimized cost and characteristic values can be designed.

<Change example 2>
The finite element model acquired by the initial model acquisition unit 30 may be a three-dimensional model of the entire tire. In that case, the member volume calculation unit 33 can calculate the volume of each tire component from the three-dimensional model without performing the calculation of expanding the two-dimensional model in the tire circumferential direction as described above.

<Change example 3>
The specific usage pattern of the tire design device 10 is not limited. For example, even if the above tire design device 10 is provided on the server and a plurality of client computers are connected to the server via a network, the above method can be executed on each client computer. good.

10 ... tire design device, 11 ... processing device, 12 ... storage device, 13 ... input device, 14 ... output device, 15 ... program, 16 ... database, 17 ... table, 20 ... tire two-dimensional model, 21 ... bead, 22 ... carcass ply, 23 ... inner liner, 24 ... belt, 25 ... tread rubber, 26 ... sidewall rubber, 27 ... rim strip, 28 ... main groove, 30 ... initial model acquisition part, 31 ... morphing part, 32 ... characteristic value Calculation unit, 33 ... Member volume calculation unit, 34 ... Cost calculation unit, 35 ... Response curved surface generation unit, 36 ... Optimization calculation unit, 110 ... Tire design device, 135 ... Cluster analysis unit, 136 ... Optimal design variable identification unit

Claims (6)

In a tire design method that includes a step in which a computer calculates a tire characteristic value based on design variables.
A step to obtain an initial finite element model representing a cross section of a tire consisting of multiple tire components,
Based on the initial finite element model, morphing is used to generate multiple morphing models with different layouts.
A step of performing a finite element analysis for each of the morphing models to calculate the characteristic value of the tire, and
A step of calculating the cost of each tire of the morphing model based on the area of each tire component appearing in the morphing model and the material cost of each tire component.
Tire design methods, including. The tire according to claim 1, wherein a design variable relating to the layout of the tire, an objective function including the cost and the characteristic value are set, and a design variable for minimizing or maximizing the objective function is calculated. Design method. In the initial finite element model, a step of selecting a tire component having an area equal to or larger than a predetermined area, and
Including a step in which some or all of the selected tire components are selected as areas to be altered by morphing.
The tire design method according to claim 1 or 2, wherein a plurality of morphing models in which the selected regions are changed are generated by morphing. The thickness of the selected area is changed by the morphing.
In the morphing, the region including the element whose length in the thickness direction is equal to or less than a predetermined value in the initial finite element model is changed only in the direction of increasing the thickness.
The tire design method according to claim 3. A program that executes any of the methods of claims 1 to 4. In a tire design device that includes a characteristic value calculation unit that calculates the characteristic value of a tire based on design variables.
An initial model acquisition unit that acquires an initial finite element model that represents a cross section of a tire composed of a plurality of tire components, and an initial model acquisition unit.
Based on the initial finite element model, a morphing unit that generates a plurality of morphing models with different layouts by morphing,
A characteristic value calculation unit that calculates characteristic values for each of the morphing models,
A cost accounting unit that calculates the cost of each tire of the morphing model based on the area of each tire component appearing in the morphing model and the material cost of each tire component.
Including tire design equipment.

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