JP7006174B2 - Simulation method, its equipment and program - Google Patents

Description

The present invention relates to a method for simulating a tire using a computer, a device and a program thereof, and in particular, a tire simulation with improved analysis results in a contact problem having a large difference in rigidity such as between a tire and a road surface such as rolling analysis. With respect to the method, its equipment and program.

Currently, a method of creating a tire model or the like that can be analyzed by a computer and simulating the performance of the tire or the like by the finite element method (FEM) has been proposed. In performance simulation of tires and the like, a tire model obtained by dividing a tire into a finite number of elements is created, and the tire model composed of the finite elements is rolled on a virtual road surface imitating a road surface. When designing a tire using tire performance simulation, simulations are performed for multiple tire shapes based on an optimized design method.

In the simulation of the finite element method of a tire, the penetration of the contact surface may become a problem in the contact problem of a tire and an object having a large rigidity difference such as a road surface such as rolling analysis. Therefore, the accuracy of the analysis result is improved by applying a contact reaction force to adjust the intrusive amount or prevent the intrusive. For example, Patent Document 1 describes repetition such as shape optimization calculation including contact analysis with a road surface model or the like by preventing the road surface model from penetrating into the tire model before contact, which occurs due to a change in tire size. In the calculation, a suitable tire simulation method has been proposed in order to prevent the calculation from breaking due to the placement position of the model.

JP-A-2015-125461

In the above-mentioned Patent Document 1, it is proposed to prevent the road surface model from penetrating the tire model in advance. However, the amount of penetration after contact depends on the tread shape, material properties, mesh size, etc., but these are not taken into consideration. Therefore, when trying to obtain higher reliability and higher analysis accuracy, there is a concern that the calculation method is not sufficient.

An object of the present invention is to provide a tire simulation method, an apparatus and a program thereof, which solves the above-mentioned problems based on the prior art, sets an appropriate penetration amount at the time of contact, and can obtain highly reliable calculation results. There is something in it.

In order to achieve the above object, the present invention is a tire simulation method executed by numerical analysis by a computer, and is a tire model creation process for creating a tire model that can be numerically analyzed by a computer, and a tire. For the road surface in contact, the road surface model creation process that creates a road surface model that can be numerically analyzed by a computer and the contact analysis between the tire model and the road surface model by a computer are performed, and the penalty rigidity value at a predetermined penetration amount is obtained. It has a step and a rolling analysis step of performing a rolling analysis of a tire model and a road surface model using a penalty rigidity value obtained in the contact analysis step by a computer, and a plurality of contact analysis steps are set in advance. In addition, for the penalty rigidity defined based on the contact force proportional to the penetration amount between the tire model and the road surface model, the process of obtaining the penetration amount specified by the position of the tire model and the position of the road surface model, respectively. The present invention provides a method for simulating a tire having a step of obtaining a regression curve representing the relationship between the penalty rigidity and the penetration amount, and a step of obtaining a penalty rigidity value at a predetermined penetration amount using the regression curve.

The predetermined penetration amount is preferably 1.0 × 10 ^-5 to 5.0 × 10 ^-1 (mm).
Penalty stiffness is defined by an equation that includes at least the element area, element volume, and penalty factor, and the penetration amount is adjusted by changing at least one of the element area, element volume, and penalty coefficient. Can be done.
The number of levels of penalty rigidity set in the contact analysis step is preferably at least 3 levels.
The tire model is divided into a plurality of regions in the tire cross-sectional width direction, and it is preferable that the penalty rigidity value is adjusted for each of the plurality of regions to determine the penetration amount.

The present invention provides a tire model that can be numerically analyzed by a computer for a tire, a model creation unit that creates a road surface model that can be numerically analyzed by a computer for a road surface that the tire contacts, and contact analysis between the tire model and the road surface model. It has an analysis unit that performs rolling analysis between the tire model and the road surface model using the obtained penalty rigidity value, and has a plurality of analysis units in advance. For the set penalty rigidity defined based on the contact force proportional to the penetration amount between the tire model and the road surface model, the penetration amount specified by the position of the tire model and the position of the road surface model is obtained. Provided is a tire simulation device for obtaining a regression curve showing the relationship between a penalty rigidity and a penetration amount, and using the regression curve to obtain a penalty rigidity value at a predetermined penetration amount.

The predetermined penetration amount is preferably 1.0 × 10 ^-5 to 5.0 × 10 ^-1 (mm).
Penalty stiffness is defined by an equation that includes at least the element area, element volume, and penalty coefficient, and the analyzer changes the penetration amount by changing at least one of the element area, element volume, and penalty coefficient. Can be adjusted.
The number of levels of penalty rigidity set by the analysis unit is preferably at least 3 levels.
It is preferable that the model creating unit creates a tire model divided into a plurality of regions in the tire cross-sectional width direction, and the analysis unit adjusts the penalty rigidity value for each of the plurality of regions to determine the penetration amount.

The present invention provides a program for causing a computer to execute each step of the tire simulation method of the present invention as a procedure.

According to the present invention, it is possible to provide a tire simulation method, a tire simulation device, and a program for tire simulation that can set an appropriate penetration amount and obtain highly reliable calculation results.

It is a schematic diagram which shows the simulation apparatus used in the simulation method of embodiment of this invention. It is a schematic diagram which shows an example of the tire model used in the simulation method of embodiment of this invention. It is a schematic diagram which shows the main part of the example of the tire model used in the simulation method of embodiment of this invention. It is a flowchart which shows the simulation method of embodiment of this invention. It is a graph which shows the relationship between the penetration amount and the penalty rigidity in the contact center part. It is a schematic diagram which shows an example of the wear energy of a tire model. It is a schematic diagram which shows another example of the wear energy of a tire model. It is a schematic diagram which shows the other example of the tire model used in the simulation method of embodiment of this invention. It is a graph which shows the relationship between the penetration amount and the penalty rigidity of Example 1 and Comparative Examples 1-5. It is a schematic diagram which shows the result of the wear energy of the tire model of Example 1. FIG. It is a schematic diagram which shows the result of the wear energy of the tire model of the comparative example 3. FIG. It is a graph which shows the result of the wear energy of the tire model of Example 1. FIG. It is a graph which shows the result of the wear energy of the tire model of the comparative example 3. FIG.

Hereinafter, the simulation method, the apparatus and the program thereof of the present invention will be described in detail based on the preferred embodiments shown in the accompanying drawings.
FIG. 1 is a schematic diagram showing a simulation device used in the simulation method of the embodiment of the present invention. FIG. 2 is a schematic diagram showing an example of a tire model used in the simulation method of the embodiment of the present invention.

The simulation device 10 shown in FIG. 1 (hereinafter, simply referred to as a processing device 10) is an example of a device that implements the tire simulation method of the present invention. The processing device 10 is configured by using hardware such as a computer. The processing device 10 shown in FIG. 1 is used for the tire simulation method of the present invention. However, if the tire simulation method can be executed by numerical analysis using hardware or software such as a computer, the processing device 10 can be used. Not limited.

The processing device 10 has a processing unit 12, an input unit 14, and a display unit 16. The processing unit 12 includes a condition setting unit 20, a model creation unit 22, an analysis unit 24, a memory 28, a display control unit 30, and a control unit 32. In addition to this, although not shown, it has a ROM and the like.
The processing unit 12 is controlled by the control unit 32. Further, in the processing unit 12, the condition setting unit 20, the model creation unit 22, the analysis unit 24, and the display control unit 30 are connected to the memory 28, and the data of the condition setting unit 20, the model creation unit 22, and the analysis unit 24 are connected to the memory 28. It is stored in the memory 28.

The input unit 14 is various input devices for inputting various information such as a mouse and a keyboard according to an operator's instruction. The display unit 16 displays, for example, the results obtained by the tire simulation method of the present invention, and various known displays are used. Further, the display unit 16 also includes a device such as a printer for displaying various information on an output medium.

The processing device 10 functionally forms each part of the condition setting unit 20, the model creation unit 22, and the analysis unit 24 by executing the program (computer software) stored in the memory 28 or the like by using the control unit 32. do. As described above, the processing device 10 may be configured by a computer in which each part functions by executing a program, or may be a dedicated device in which each part is configured by a dedicated circuit.
In the tire simulation method of the present embodiment, since the tire contact analysis and the tire rolling analysis are performed, the processing device 10 has a function of performing the tire contact analysis and the tire rolling analysis.

The condition setting unit 20 inputs and sets various conditions and information necessary for the tire simulation method of the present embodiment. The condition setting unit 20 inputs and sets various conditions and information such as the size of the tire, the size of each member constituting the tire, the arrangement position, and the physical characteristics such as the elastic modulus. Various conditions and information are input via, for example, the input unit 14. Various conditions and information set by the condition setting unit 20 are stored in the memory 28.

The characteristic value set in the condition setting unit 20 is a physical quantity to be evaluated. The objective function is a function for finding the physical quantity to be evaluated.
In the case of a tire, the characteristic value is the characteristic value of the tire. The characteristic values are, for example, a physical quantity to be evaluated as tire performance, CP (cornering power) which is a lateral force near zero slip angle which is an index of steering stability, and 1 of a tire which is an index of riding comfort. Next natural frequency, rolling resistance as an index of fuel efficiency, lateral rigidity as an index of steering stability, vertical rigidity, amount of deflection, ground pressure distribution, cornering force, friction coefficient and tire tread as an index of wear resistance Examples include wear energy of members.

In addition, information such as tire load, running conditions such as tire rolling speed, road surface conditions on which the tire runs, such as uneven shape, friction coefficient, and vehicle specifications for use in vehicle running simulation, etc. Set.

The model creation unit 22 creates a tire model in which the tire can be numerically analyzed by a computer and a road surface model in which the road surface in contact with the tire can be numerically analyzed by a computer, and the road surface is a target for rolling the tire.
As the tire model, a tire model that reproduces the rim on which the tire is mounted, the wheel, and the axis of rotation of the tire may be used. Further, if necessary, a model that reproduces the vehicle on which the tire is mounted may be incorporated into the tire model. At this time, it is also possible to create a model in which the tire model, the rim model, the wheel model, and the tire rotation axis model are integrated based on the preset boundary conditions.
The form of the tire model used for the analysis is not particularly limited, and for example, the tire model 40 shown in FIG. 2 is exemplified. As shown in FIG. 2, the tire model 40 is composed of a plurality of elements 41. Further, the form of the tire model used for the analysis may be a smooth tire without a groove, a tire with only a main groove, or a pattern.

A known creation method can be used to create the tire model created by the model creation unit 22. For example, a tire model 40 is created by dividing a tire into a finite number of elements composed of a plurality of nodes.
The road surface model 42 may be created in the same manner as the tire model 40, may be analytically modeled as an elastic body, or may be analytically modeled as a rigid body. Further, the road surface model 42 may be a three-dimensional discretized model or an analysis model as a surface.
The elements constituting the tire model 40 or the road surface model 42 are, for example, a quadrilateral element in a two-dimensional plane, a tetrahedral solid element in a three-dimensional body, a pentahedron solid element, a solid element such as a hexahedral solid element, a triangular shell element, and a quadrangle. Shell elements such as shell elements and elements such as surface elements that can be numerically analyzed by a computer. In the process of analysis, the elements divided in this way are identified one by one using the three-dimensional coordinates in the three-dimensional model and the two-dimensional coordinates in the two-dimensional model.

The tire model and the road surface model created by the model creation unit 22 may be discretized models that can be numerically calculated for numerical analysis, and are, for example, finite element models for use in the known finite element method (FEM). Consists of.
If the tire model is used to obtain tire performance such as tire wet performance, for example, if a model that reproduces inclusions existing on the road surface is generated in addition to the road surface model and the tire model. good. For example, as an inclusion model, various models that reproduce water, snow, mud, sand, gravel, ice, etc. on the road surface may be generated by a discretized model that can be calculated numerically.
The road surface model is not limited to a model that reproduces a road surface having a flat surface, and may be a model that reproduces a road surface shape having irregularities on the surface, if necessary.

The analysis unit 24 performs contact analysis between the tire model 40 and the road surface model 42, obtains a penalty rigidity value at a predetermined penetration amount, and uses the obtained penalty rigidity value to roll the tire model and the road surface model. The analysis is carried out.
In the analysis unit 24, the penetration amount defined by the position of the tire model and the position of the road surface model is determined for each of a plurality of preset penalty rigidity defined based on the contact force between the tire model and the road surface model. Ask. As a result, a plurality of pairs of penalty rigidity data and penetration amount data are obtained.

Next, a regression curve showing the relationship between the penalty stiffness and the penetration amount is obtained by using a set of a plurality of penalty rigidity data and the penetration amount data. Using this regression curve, the penalty stiffness value at a predetermined penetration amount is obtained. The obtained plurality of penalty rigidity data and the penetration amount data are stored in the memory 28 as a set.
The analysis unit 24 obtains a relationship with the penetration amount for each of a plurality of preset penalty rigidity. Specifically, a regression curve between the penalty rigidity and the penetration amount is obtained. The analysis unit 24 uses a regression curve to obtain a penalty stiffness value at a predetermined penetration amount.

The regression curve can be obtained by a known method using a plurality of sets of penalty rigidity data and penetration amount data, and the method for obtaining the regression curve is not particularly limited, and the regression curve is a power. Alternatively, it is preferable to use a non-linear function such as an exponential model.
For example, a program for obtaining a regression curve is stored in the memory 28. The analysis unit 24 calls the program and the set of the penalty rigidity data and the penetration amount data from the memory 28, and obtains a regression curve by using a plurality of sets of the penalty rigidity data and the penetration amount data.
Further, it is preferable that the number of levels of the penalty rigidity set by the analysis unit 24 is set to at least three levels in order to improve the accuracy of the regression curve.

Next, the contact analysis will be described including the penalty rigidity.
FIG. 3 is a schematic view showing a main part of an example of a tire model used in the simulation method of the embodiment of the present invention, and FIG. 3 shows an enlarged part of FIG.
The penalty method is generally used as a method for solving a contact problem by the FEM (finite element method). The penalty method is a method of allowing the intrusion of objects in contact with each other and applying a force according to the amount of intrusion to the objects as a contact force. That is, it is a method of numerically simulating contact by making a virtual spring stretch between objects that come into contact with each other.

FIG. 3 shows the element 41 of the tire model 40 shown in FIG. 2 that is in contact with the road surface model 42. In FIG. 3, the surface 41a of the element 41 invades the surface 42a of the road surface model 42. Further, a contact reaction force f is applied to the surface 41a of the element 41.
The contact reaction force f is represented by f = −kL. k is the penalty rigidity and L is the penetration amount. As shown in FIG. 3, the penetration amount L is the distance between the surface 41a of the element 41 and the surface 42a of the road surface model 42. Note that FIG. 3 shows a state in which the tire model 40 has invaded the road surface model 42.

Taking LS-DYNA, which is one of the general-purpose finite element method software, as an example, the penalty rigidity k is defined by the following equation when the element is a solid element. F _si in the following equation is a scale factor (penalty coefficient). K is a bulk modulus and is represented by K = E / (3 (1-2ν)). E is Young's modulus and ν is Poisson's ratio. Further, A is an element area and V is an element volume.
When the element is a shell element, V (element volume) in the following equation is the diagonal length.

From the above equation, the penalty rigidity k can adjust the penetration amount by changing at least one of the element area A, the element volume V, and the penalty coefficient (scale factor) f _si . As a result, the tuning parameter of the penalty rigidity is not limited to the penalty coefficient, and the mesh size can be taken into consideration, so that the parameter can be selected according to the analysis target and the constraint condition.
Further, when the mesh size of the tire model is changed to adjust the penalty rigidity, the larger the number of divisions of the element, the longer the calculation time, but the higher the calculation accuracy. Therefore, it is preferable to increase the number of element divisions as much as possible in consideration of the balance with the calculation time.
Further, since it is generally known that the change in wear energy is large at the end of the land portion of the tread, it is preferable to increase the number of divisions at the end of the block to suppress a decrease in evaluation accuracy. Therefore, for the purpose of wear energy analysis, when the mesh size changes depending on the widthwise cross-sectional position of the tread, the penalty rigidity should be adjusted so that the penetration amount does not change significantly depending on the widthwise cross-sectional position of the same cross section. Is preferable.

In addition, static grounding analysis is preferable for contact analysis in order to acquire data efficiently. Further, in the static grounding analysis, when viscoelasticity is used as the material constitutive law, it is preferable to give a damping term to a sufficient time or an equation of motion in order to obtain a stable intrusion amount in a steady state.
Further, the penetration amount is preferably the same value in the ground contact region in the tire width direction on the same cross section, and it is desirable that the error from at least a predetermined value is within 50%. For example, if the penetration amount at the center of contact is set as a predetermined value of the penetration amount and the value is 0.01 mm, the penetration amount at each position of the cross section in the tire width direction including the contact center is 0.005 mm to 0.015 mm. It is desirable to fit in.

As described above, the analysis unit 24 performs rolling analysis between the tire model and the road surface model using the obtained penalty rigidity value. For example, it acts on the behavior of the tire model or the tire model when the simulation condition for reproducing the rolling of the tire rolling on the road surface is given to the tire model generated by the model creation unit 22, the road surface model, or the like. Obtain physical quantities such as forces in chronological order. The analysis unit 24 functions, for example, by executing a subroutine by a known finite element solver.
Further, the analysis unit 24 calculates the above-mentioned characteristic value. As the characteristic value, for example, wear energy is calculated. The rolling analysis is not particularly limited, and a known method can be appropriately used.
Further, the analysis target of the rolling analysis is not particularly limited, and in addition to the straight running state and the turning state such as cornering, the braking state and the driving state to which the acceleration is applied are analyzed.

After the contact analysis, the analysis unit 24 can also analyze physical quantities such as wear energy, contact pressure, tire rigidity, and rolling characteristics.
In the above-mentioned contact analysis and rolling analysis, for example, a tire model may be used after applying a predetermined internal pressure to the tire model to perform an internal pressure filling process (also referred to as an inflatable process). A tire model simulating a state in which the internal pressure is removed after the internal pressure filling process, that is, a state in which the tire is punctured may be used. Further, the tire model may be a tire model that can be numerically analyzed by a computer fitted to the rim, but may be, for example, a model without a rim that constrains the rim contact portion.
In the analysis unit 24, for example, in the state shown in FIG. 2, contact analysis is performed by constraining either the rotation axis (not shown) of the tire model 40 or the road surface model 42. Further, the analysis unit 24 calculates characteristic values using various models created by the model creation unit 22.

The display control unit 30 displays the tire model, the road surface model, the result of the numerical calculation, and the optimum solution on the display unit 16. For example, the tire model and the road surface model are read from the memory 28 and displayed on the display unit 16. ..

Next, a tire simulation method of the present embodiment will be described.
FIG. 4 is a flowchart showing a simulation method according to an embodiment of the present invention. FIG. 5 is a graph showing the relationship between the penetration amount and the penalty rigidity at the center of contact with the ground.
In this embodiment, for example, a tire having a size of 195 / 65R15 is targeted for simulation.
Before the simulation, the tire shape, the tire size, the tire pattern, and the like are set in the condition setting unit 20. In the present embodiment, for example, the wear energy is set as a characteristic value (objective function) in order to obtain the wear energy defined by the product of the shear force and the slip amount of the tire block at the contact portion. The tire shape parameter is set in the condition setting unit 20. Determine the nonlinear response used to obtain the characteristic value (objective function).

In the simulation method, the model creating unit 22 creates a tire model 40 (see FIG. 2) such as a mesh model using the information set in the condition setting unit 20 (step S10). Step S10 is a tire model creating process.
Next, the model creation unit 22 creates a road surface model 42 (see FIG. 2) using the information set in the condition setting unit 20 (step S12). Step S12 is a road surface model creation process.
Next, in order to obtain a regression curve, a plurality of penalty stiffnesses are set in the condition setting unit 20 (step S14). It is desirable that the set values of the plurality of penalty rigidity set in step S14 are set discretely with respect to an arbitrary value in which the change in the penalty rigidity is set in advance. Or set to approach a predetermined value.

Next, the analysis unit 24 performs contact analysis between the tire model 40 (see FIG. 2) and the road surface model 42 (see FIG. 2) using the plurality of penalty rigidity set in step S14 (step S16). Step S16 is a contact analysis step, and in step S16, either one of the tire model 40 and the road surface model 42 is restrained, and the contact process is performed in that state. As the contact analysis, for example, a static grounding analysis is performed as described above.
The penetration amount L is acquired by the contact analysis in step S16 (step S18). In step S18, the penetration amount for the penalty rigidity is obtained, and the set of the penalty rigidity data and the penetration amount data is obtained and stored in the memory 28. In addition, if the mesh size and material properties of the area in contact with the road surface are the same in the tread portion of the tire model, the intrusive amount to be acquired is a judgment condition that targets only the intrusive amount at a typical position, for example, the center of ground contact. It may be set as a program.

In step S14, a plurality of penalty stiffnesses are set. It is determined whether all the corresponding penetration amounts have been acquired for the set penalty rigidity (step S20), and the above-mentioned steps S14 to S18 are repeatedly executed until the penetration amounts of all the penalty rigidity are obtained (step S20). As a result, a combination of the penalty rigidity data and the penetration amount data can be obtained for all the set penalty rigidity.

In order to obtain the regression curve, it is preferable that there are at least three pairs of the penalty stiffness data and the penetration amount data at the same location. Therefore, it is preferable that the number of levels of the penalty rigidity set in advance is at least three levels. If there are at least three pairs of penalty stiffness data and penetration amount data, an accurate regression curve can be obtained.
The combination of the above-mentioned penalty rigidity data and the penetration amount data, that is, the upper limit of the number of preset penalty rigidity is not particularly limited, but is appropriate from the calculation time, the required accuracy of the penetration amount, and the like. It will be decided.
Further, for example, a setting may be incorporated in the program to set a change in the regression coefficient or the residual sum of squares as a determination condition and to stop repeating the above-mentioned steps S14 to S18 if the value does not change.

Next, a regression curve 50 is obtained as shown in FIG. 5 by regression analysis using a plurality of pairs of the obtained penalty rigidity data and the penetration amount data (step S22). The method for obtaining the regression curve 50 is as described above. The reference numeral 51 shown in FIG. 5 is a data point represented by a set of the penalty rigidity data and the penetration amount data.

Next, the regression curve obtained in step S22 is used to obtain a penalty stiffness value at a predetermined penetration amount (step S24). In step S24, for example, the regression curve 50 shown in FIG. 5 is used to obtain a penalty rigidity value at a predetermined penetration amount D.
Next, using the penalty rigidity value obtained in step S24, the analysis unit 24 performs rolling analysis between the tire model 40 (see FIG. 2) and the road surface model 42 (see FIG. 2) (step S26). .. Step S26 is a rolling analysis step, and in the rolling analysis of step S26, for example, wear energy is obtained as a characteristic value. The result of the wear energy obtained in step S26 is stored in, for example, the memory 28.

The result of the tire wear energy obtained in step S26 is shown in FIG. The distribution of wear energy in the tread portion 60 shown in FIG. 6 of the tire model varies in the tire circumferential direction in any of the first region 61a, the second region 61b, the third region 62a, and the fourth region 62b. There is almost no. That is, it is shown that the rolling analysis was performed in a state where an appropriate penetration amount was set and the tire model 40 (see FIG. 2) and the road surface model 42 (see FIG. 2) were in uniform contact with each other.

On the other hand, when the method of the present invention is not used, the distribution of wear energy in the tread portion 100 shown in FIG. 7 of the tire model is the first region 101a, the second region 101b, and the third region 101b as compared with FIG. In both the region 102a and the fourth region 102b, the wear energy in the tire circumferential direction varies. Originally, in the case of the tire model as shown in FIGS. 6 and 7 in which the mesh division in the circumferential direction is uniform and does not have a lug groove or the like, even if there is a response delay of the viscoelastic material or vibration of the main groove edge portion. The wear energy under steady state should be distributed almost uniformly in the circumferential direction. The variation in wear energy is largely due to the fact that the penalty rigidity is too large or too small, that is, an appropriate penetration amount is not set. By setting an appropriate penetration amount as in the present invention, a distribution of wear energy with small variation can be obtained as shown in FIG. 6, and highly reliable calculation results can be obtained.
The physical property value is not limited to the wear energy, but can be estimated by using the above-mentioned method when combining the wear energy test result and the calculation result with the friction coefficient between the tire and the road surface as a parameter. be.

The predetermined penetration amount D for obtaining the penalty rigidity value is preferably 1.0 × 10 ^-5 to 5.0 × 10 ^-1 (mm). As the predetermined penetration amount D, the above range is a practical range, and a more accurate tire rolling analysis result can be obtained.
In the above-mentioned simulation method, one predetermined penetration amount is set for one tire model, but the present invention is not limited to this. For example, in the tire model 40 shown in FIG. 8, the tread portion 44 is divided into a plurality of regions 44a to 44c in the tire cross-sectional width direction W. The penalty rigidity may be adjusted for each of the plurality of regions 44a to 44c to determine the penetration amount. This makes it possible to finely control the penetration amount for each region, and it is possible to efficiently obtain highly accurate tire rolling analysis results without modifying the mesh size of the tire model.

As the division of the region, for example, it may be classified into a land portion (shoulder portion, center portion, etc.) with the circumferential groove of the tire as a boundary. The region 44a and the region 44b shown in FIG. 8 are regions called a center portion, and the region 44c is a region called a shoulder portion.
Even in the case of the tire model 40 shown in FIG. 8, it is desirable that the penetration amount is the same value in the width direction region of the same cross section. If the amount of penetration is greatly changed for each land area, the contact pressure and slip amount will be affected, so an accurate wear energy distribution cannot be evaluated. Therefore, it is preferable that the intrusive amount in the width direction region of the same cross section has an error of at least 50% or less from the value of the predetermined intrusive amount.

In the present embodiment, an appropriate penetration amount can be set and a highly reliable calculation result can be obtained. In addition, the performance of the tire can be evaluated more accurately without being affected by the mesh size of the tire model, the material physical characteristics of the tire, and the like.
The tire simulation method described above can be performed by the processing device 10 described above. Further, the above-mentioned simulation method can also be executed by using a program for causing a computer to execute each step of the above-mentioned simulation method as a procedure.

In the present embodiment, a three-dimensional finite element model created by expanding the tire model 40 of the two-dimensional tire cross-section model shown in FIG. 2 in the circumferential direction has been described as an example, but the present invention is not limited thereto. For example, when using a pattern design in an actual product, the nodes of the finite element model may not be aligned on the same cross section due to the complicated groove shape. In that case, a node or element group having a predetermined cross section, for example, a node closest to the ground contact center and having a circumferential distance from the width direction cross section is extracted, and evaluated using the penetration amount thereof. Such a program may be given to the processing apparatus 10.

The present invention is basically configured as described above. Although the simulation method, the apparatus and the program of the present invention have been described in detail above, the present invention is not limited to the above embodiment, and various improvements or changes may be made without departing from the gist of the present invention. Of course.

Hereinafter, the effect of the simulation method of the present invention will be specifically described.
In this embodiment, the contact analysis and rolling analysis between the tire model and the road surface model are performed by the simulation methods of Example 1 and Comparative Examples 1 to 5, the wear energy of the tire is calculated, and the simulation method of the present invention is used. The effect was confirmed.

In this embodiment, a tire model having a tire size of 195 / 65R15 was used, the penetration amount was adjusted, and the wear energy at the time of cornering was calculated by using the finite element method (FEM). In addition, the wear energy of the actual tire was obtained for comparison.
In the tire model and the actual tire, the air pressure was 230 kPa, the load was 4.0 kN, and the cornering speed was 20 km / hour.

Hereinafter, Example 1 and Comparative Examples 1 to 5 will be described.
FIG. 9 is a graph showing the relationship between the penetration amount and the penalty rigidity of Examples 1 and Comparative Examples 1 to 5.
In this embodiment, using a tire model having the same mesh, regression analysis is performed from the analysis results of five cases having different penalty rigidity, a regression curve 50 is obtained, and as Example 1, the penalty rigidity having a desired penetration amount is obtained. I got the value. The analysis was performed using the obtained penalty stiffness value. Since the difference between the penetration amount in the cross-sectional width direction in the tire model and the average value of the penetration amount in the same cross-sectional width direction position was within ± 50%, FIG. 9 is a comparison using the value at the center of contact as a representative value. Is going.

Further, in order to obtain a regression curve, the set value of the penalty rigidity was set in 5 cases, and the set of the penetration amount and the penalty rigidity in the 5 cases was set as Comparative Example 1 to Comparative Example 5 as shown in FIG. Further, from the regression curve 50 shown in FIG. 9, Example 1 having a predetermined penetration amount was obtained.
The rolling analysis of the tire model and the road surface model was carried out in a turning state in which a turning force (lateral force) of 0.2 G was applied. At this time, the output interval was set to 1000 Hz, and the shear force and the slip amount at each node in the contact region were calculated for 1.0 second for each minute time step. That is, 1000 pieces of data were obtained. Then, the wear energy of Example 1 and Comparative Examples 1 to 5 was calculated by multiplying the obtained value of the shearing force and the value of the slip amount.

The measured values were measured by measuring a real tire with the same tire size of 195 / 65R15 as the tire model under the same running conditions as the above-mentioned tire model (pneumatic pressure 230 kPa, load 4.0 kN, cornering speed 20 km / hour). The results were used. In a turning state in which a real tire was rolled and a turning force (lateral force) of 0.2 G was applied, the shear force and the slip amount were measured, and the shear force and the slip amount were obtained. The measured value of wear energy was obtained by multiplying the value of shear force and the value of slip amount.
Table 1 below shows the wear energies of Example 1 and Comparative Examples 1 to 5, as well as the measured values. In Table 1 below, the measured wear energy is standardized as 100.

As shown in Table 1 above, in Example 1, the wear energy was closer to the measured value than in Comparative Examples 1 to 5, and highly reliable calculation results were obtained.
Here, FIG. 10 is a schematic diagram showing the result of the wear energy of the tire model of the first embodiment, and FIG. 11 is a schematic diagram showing the result of the wear energy of the tire model of the comparative example 3. FIG. 12 is a graph showing the results of wear energy of the tire model of Example 1, and FIG. 13 is a graph showing the results of wear energy of the tire model of Comparative Example 3. In FIG. 12, reference numeral 70 indicates an overall average value of 1000 data numbers, and reference numeral 72 indicates a peak value in 1000 data numbers. In FIG. 13, reference numeral 110 indicates an overall average value of 1000 data numbers, and reference numeral 112 indicates a peak value in 1000 data numbers.

10 and 12 show the results of the wear energy of Example 1, and FIGS. 11 and 13 show the results of the wear energy of Comparative Example 3. FIG. 10 shows the distribution of wear energy in the tread portion 64. The region 65a of the tread portion 64 of the first embodiment shown in FIG. 10 corresponds to the reference numeral 73a in FIG. 12, the region 65b corresponds to the reference numeral 73b in FIG. 12, and the region 65c corresponds to the reference numeral 73c in FIG. Corresponds to reference numeral 73d in FIG.
FIG. 11 shows the distribution of wear energy in the tread portion 105 of Comparative Example 3. The region 106a of the tread portion 105 shown in FIG. 11 corresponds to the reference numeral 114a in FIG. 13, the region 106b corresponds to the reference numeral 114b in FIG. 13, the region 106c corresponds to the reference numeral 114c in FIG. 13, and the region 106d corresponds to the reference numeral 114c in FIG. It corresponds to the reference numeral 114d.

As shown in FIG. 12, in Example 1, the total average value of 1000 data and the peak value of 1000 data were almost the same. On the other hand, in Comparative Example 3, the deviation between the total average value of 1000 data and the peak value of 1000 data was large, that is, the variation between the data was large. By suppressing the variation in the value of the intrusion amount in the width direction of the same cross section and optimizing the intrusion amount in this way, it is possible to obtain a result with high analysis accuracy and small variation in the value in each land area. did it.

10 Simulation equipment (processing equipment)
12 Processing unit 14 Input unit 16 Display unit 20 Condition setting unit 22 Model creation unit 24 Analysis unit 28 Memory 30 Display control unit 32 Control unit 40 Tire model 42 Road surface model 50 Regression curve

Claims (11)

It is a tire simulation method executed by numerical analysis by a computer.
A tire model creation process for creating a tire model that can be numerically analyzed by the computer for the tire,
A road surface model creation process for creating a road surface model that can be numerically analyzed by the computer for the road surface with which the tires come into contact.
A contact analysis step of performing contact analysis between the tire model and the road surface model by the computer and obtaining a penalty rigidity value at a predetermined penetration amount.
The computer has a rolling analysis step of performing rolling analysis between the tire model and the road surface model using the penalty rigidity value obtained in the contact analysis step.
The contact analysis step is
The position of the tire model and the position of the road surface model are defined for each of a plurality of preset penalty rigidity defined based on the contact force proportional to the penetration amount between the tire model and the road surface model. The process of determining the amount of penetration and
A step of obtaining a regression curve representing the relationship between the penalty rigidity and the penetration amount,
A method for simulating a tire, which comprises a step of obtaining the penalty rigidity value at the predetermined penetration amount using the regression curve. The tire simulation method according to claim 1, wherein the predetermined penetration amount is 1.0 × 10 ^-5 to 5.0 × 10 ^-1 (mm). The penalty rigidity is defined by an equation including at least an element area, an element volume, and a penalty coefficient, and the penetration is performed by changing at least one of the element area, the element volume, and the penalty coefficient. The method for simulating a tire according to claim 1 or 2, wherein the amount is adjusted. The tire simulation method according to any one of claims 1 to 3, wherein the number of levels of the penalty rigidity set in the contact analysis step is at least three levels. The tire model is divided into a plurality of regions in the tire cross-sectional width direction, and the penetration amount is determined by adjusting the penalty rigidity value for each of the plurality of regions according to any one of claims 1 to 4. Tire simulation method. A tire model that can be numerically analyzed by a computer for tires, and a model creation unit that creates a road surface model that can be numerically analyzed by the computer for the road surface with which the tires come into contact.
Contact analysis between the tire model and the road surface model is performed, a penalty rigidity value at a predetermined penetration amount is obtained, and the rolling analysis between the tire model and the road surface model is performed using the obtained penalty rigidity value. Has an analysis unit to carry out
The analysis unit determines the position of the tire model and the road surface model, respectively, with respect to a plurality of preset penalty rigidity defined based on a contact force proportional to the penetration amount between the tire model and the road surface model. The penetration amount defined by the position is obtained, a regression curve representing the relationship between the penalty rigidity and the penetration amount is obtained, and the regression curve is used to obtain the penalty rigidity value at the predetermined penetration amount. Simulation device. The tire simulation apparatus according to claim 6, wherein the predetermined penetration amount is 1.0 × 10 ^-5 to 5.0 × 10 ^-1 (mm). The penalty rigidity is defined by an equation including at least an element area, an element volume, and a penalty coefficient, and the analysis unit changes at least one of the element area, the element volume, and the penalty coefficient. The tire simulation apparatus according to claim 6 or 7, wherein the penetration amount is adjusted accordingly. The tire simulation apparatus according to any one of claims 6 to 8, wherein the number of levels of the penalty rigidity set by the analysis unit is at least three levels. The model creating unit creates the tire model divided into a plurality of regions in the tire cross-sectional width direction, and the analysis unit adjusts a penalty rigidity value for each of the plurality of regions to determine the penetration amount. The tire simulation apparatus according to any one of 6 to 9. A program for causing a computer to execute each step of the tire simulation method according to any one of claims 1 to 5 as a procedure.

Images