JP7359627B2 - Tire model evaluation method and tire model creation method - Google Patents

Description

The present invention relates to a tire model evaluation method and a tire model creation method .

When a tire rolls on a road surface, the tire vibrates due to the force generated by contact with the road surface. Such tire vibrations propagate through propagation paths such as axles and suspensions and generate noise within the vehicle interior, or radiate noise from the tires.

Therefore, in Cited Document 1, the distribution of strain energy during vibration in the second mode of the tire cross section is analyzed by eigenvalue analysis using the finite element method, and locations with large strain energy are identified as those that have a large impact on improving tire performance. , it has been proposed to take measures to suppress strain energy at the relevant part to reduce noise.

Japanese Patent Application Publication No. 2002-205515

However, in the method described above, a plurality of natural frequencies are obtained by eigenvalue analysis, but the parts that greatly influence the improvement of tire performance may differ depending on the obtained natural frequencies. Therefore, it is necessary to identify parts that have a large effect on improving tire performance for each natural frequency and take measures for the identified parts, which increases the number of work steps. In addition, countermeasures taken for one natural frequency may affect other natural frequencies, and it may be difficult to determine which natural frequency should be prioritized for countermeasures among multiple natural frequencies. . In particular, since the number of eigenmodes increases as the frequency increases, the above-mentioned problems become more noticeable in high frequency regions.

In view of the above points, the present invention aims to identify parts that have a large influence on tire performance improvement comprehensively for a plurality of natural frequencies, without specifying each natural frequency acquired by eigenvalue analysis individually. The purpose of this invention is to provide a method for evaluating tire models and a method for manufacturing tires.

The tire model evaluation method of the present invention is a method for evaluating a tire model consisting of a finite element model divided into a plurality of elements, in which a computer performs an eigenvalue analysis using the finite element method using the tire model, a first step of acquiring a plurality of natural frequencies, and acquiring each node set in each element of the tire model or a first physical quantity of each element for each of the plurality of acquired natural frequencies; The method includes a second step in which the computer aggregates the first physical quantities at each natural frequency obtained in the first step for each node or each element to obtain a physical quantity distribution.

Further, the method for creating a tire model of the present invention includes a third step in which a computer identifies a region for improving tire performance from the physical quantity distribution obtained using the tire model evaluation method described above, and a region identified in the third step. and a fourth step of modifying the tire model by changing material properties of the parts.

In the present invention, since it is possible to specify a portion that greatly influences the improvement of tire performance comprehensively with respect to a plurality of natural frequencies obtained by eigenvalue analysis, it is possible to specify the portion while reducing the number of work steps.

Flow diagram showing the method of the first embodiment Diagram showing an example of physical quantity distribution of the first physical quantity Flow diagram showing the method of the second embodiment

(First embodiment)
Hereinafter, a first embodiment of the present invention will be described with reference to the drawings.

FIG. 1 is a flowchart illustrating a method for identifying areas effective for improving tire performance using a tire model evaluation method according to an embodiment of the present invention.

The method of this embodiment is a method that can be implemented using a computer, and uses vibration characteristic information obtained by eigenvalue analysis using a tire finite element model (hereinafter referred to as tire FE model) to The distribution of the first physical quantity in the FE model is determined.

First, in step S1, a reference tire FE model is created or prepared for the target tire. Specifically, we use the tire cross-sectional area in a natural equilibrium state as a reference shape, create a model using finite elements to represent the tire cross-sectional shape including the internal structure, and divide it into multiple elements using mesh division. Create or prepare a tire FE model.

Next, in step S2, eigenvalue analysis is performed. Specifically, the tire FE model is mounted on the virtual rim, and boundary conditions are set. Boundary conditions include the internal pressure of the tire and the load applied to the axis of the virtual rim. Then, an eigenvalue analysis using the finite element method using the tire FE model is performed to obtain vibration characteristic information including multiple natural frequencies and modes, and each node of the tire FE model is Alternatively, the first physical quantity is acquired for each element.

The first physical quantity is a physical quantity that is the basis for determining tire performance, and is, for example, a physical quantity calculated using stress, strain, or at least one of stress and strain (for example, strain energy, (strain energy density divided by the volume of the element, etc.), vibration velocity, acceleration, displacement, etc. Stress and strain are acquired for each element, and physical quantities calculated using at least one of stress and strain are also acquired for each element. The vibration velocity, acceleration, and displacement amount are acquired for each node. Note that in this embodiment, strain energy density is acquired for each element of the tire FE model as the first physical quantity.

Next, in step S3, the first physical quantities obtained for each natural frequency in step S2 are aggregated for each node or element to obtain a physical quantity distribution. For example, when N natural frequencies (N is an integer of 2 or more) are acquired in step S2, and the strain energy density of the i-th element at the n-th natural frequency is F(i, n), A physical quantity distribution function A(i) in which strain energy densities obtained for each natural frequency are aggregated for each element is expressed by the following equation (1).

Formula 1

なお、固有振動数毎に取得した第１物理量を節点毎又は要素毎に集約する場合、上記のように単に加算してもよく、上記のように加算したものを固有振動数の個数で除して平均値を求めてもよい。また、固有振動数毎に重み係数を第１物理量に乗じてから節点毎又は要素毎に加算したり、その加算値を固有振動数の個数で除して平均値を求めたりしてもよい。

Note that when the first physical quantities obtained for each natural frequency are aggregated for each node or element, they may be simply added as described above, or the added value may be divided by the number of natural frequencies. You can also calculate the average value. Alternatively, the first physical quantity may be multiplied by a weighting coefficient for each natural frequency and then added for each node or element, or the added value may be divided by the number of natural frequencies to obtain an average value.

Next, in step S4, it is determined whether the obtained physical quantity distribution of the first physical quantity achieves the target performance. Various methods can be used for this determination. For example, it is possible to identify a region in the physical quantity distribution where the strain energy density exceeds a predetermined range, and make the region a region where changing material properties is effective in improving tire performance.

Next, if there is a part in the physical quantity distribution where the first physical quantity exceeds the predetermined range (No in step S4), it is determined that the tire FE model has not achieved the target performance, and the process proceeds to step S5, where the material of the part identified in step S4 is Modify the tire FE model to change its characteristics.

Regarding the physical quantity distribution of the first physical quantity acquired in step S3, the gradation of the dynamic range (for example, 256 levels) is displayed linearly from the minimum value to the maximum value of the first physical quantity of each node or each element in the tire FE model. As illustrated in FIG. 2, the physical quantity distribution of the first physical quantity may be visualized by assigning a gradation to each gradation (gradation). Thereby, it is possible to easily specify a location that is effective for improving tire performance.

After modifying the tire FE model, return to step S2 to obtain the natural frequency, first physical quantity, etc. of the modified tire FE model, and obtain the physical quantity distribution (steps S2 to S3). It is determined whether or not this has been achieved (step S4). Such modification of the tire FE model (step S5), acquisition of the physical quantity distribution of the modified tire FE model (steps S2 to S3), and determination whether the acquired physical quantity distribution achieves the target performance (step S4) ) are repeatedly executed until the tire FE model achieves the target performance.

Then, when the physical quantity distribution achieves the target performance, the above control is ended, and a tire is manufactured based on the obtained tire FE model.

In this embodiment, a plurality of natural frequencies are acquired by eigenvalue analysis using a tire FE model, and the first physical quantities at the plurality of natural frequencies are aggregated for each node or element to obtain a physical quantity distribution. By using the acquired physical quantity distribution, tire performance can be comprehensively evaluated for multiple natural frequencies.
In addition, by identifying areas that are effective for improving tire performance based on the physical quantity distribution obtained in this embodiment, it is necessary to identify areas that have a large effect on improving tire performance for each of multiple natural frequencies. It is possible to identify areas that have a large impact on tire performance improvement comprehensively with respect to multiple natural frequencies, and it is possible to design and manufacture tires with improved tire performance at low cost.

(Second embodiment)
A second embodiment of the present invention will be described based on FIG. 3.

In this embodiment, a weighting coefficient W is calculated for each natural frequency based on a second physical quantity that is a physical quantity different from the first physical quantity, and the first physical quantity is multiplied by the weighting coefficient W calculated for each natural frequency. This embodiment differs from the first embodiment described above in that the first physical quantities are aggregated for each element or for each element.

Specifically, as shown in FIG. 3, in step S11, the tire cross-sectional area of the target tire in a natural equilibrium state is set as a reference shape, and a model is created using finite elements to create a model of the tire as a reference tire. Create or prepare an FE model.

Next, in step S12, the tire FE model is mounted on the virtual rim, boundary conditions are set, and then an eigenvalue analysis is performed using the finite element method using the tire FE model to calculate multiple natural frequencies and natural Vibration characteristic information including the mode is acquired, and a first physical quantity and a second physical quantity are acquired for each node or each element of the tire FE model for each acquired natural frequency.

The first physical quantity is a physical quantity that is the basis for determining tire performance, and is the first physical quantity of the first embodiment described above, such as stress, strain, and a physical quantity calculated using at least one of stress and strain. Examples include physical quantities similar to . Note that in this embodiment, strain energy density is acquired for each element of the tire FE model as the first physical quantity.

The second physical quantity is a physical quantity used to calculate the weighting coefficient W, and examples thereof include physical quantities such as vibration velocity, vibration displacement, acceleration, axial displacement, and velocity. Note that the vibration velocity, vibration displacement, acceleration, axial displacement, and velocity are acquired for each node.

Next, in step S13, a weighting coefficient W of each natural frequency is calculated from the second physical quantity acquired in step S12. In calculating the weighting coefficient W, the second physical quantities of all nodes or elements of the tire FE model may be used, but the second physical quantities of some nodes or elements may be used, or the second physical quantities of some nodes or elements may be used. The weighting coefficient of each natural frequency may be calculated using predetermined direction components of the two physical quantities, or using predetermined direction components of the second physical quantities of all nodes or elements.

Here, as an example of calculating the weighting coefficient W of each natural frequency from the second physical quantity, the vibration velocity of each node is obtained as the second physical quantity, and the vibration velocity of the node located on the outer surface of the tire of the tire FE model is calculated. A case will be described in which the weighting coefficient W of each natural frequency is calculated using the linear direction component.

Specifically, the natural frequency, the reciprocal of the point group density of each node (the number of nodes included in a unit area centered on the reference node), and the normal direction at the nodes located on the outer surface of the tire. The weighting coefficient W to be applied to each natural frequency is obtained by adding up the vectors multiplied by the natural vector for all nodes located on the outer surface of the tire for each natural frequency. In other words, if there are J nodes (J is an integer greater than or equal to 2) on the tire outer surface, the nth natural frequency is ωn, and the normal direction of the jth node located on the tire outer surface to the tire outer surface is ωn. Assuming that the eigenvector Ej is the eigenvector Ej, and the point group density ρj of the j-th node, the weighting coefficient Wn applied to the n-th natural frequency is expressed by the following equation (2).

Formula 2

次いで、ステップＳ１４において、ステップＳ１２で取得した第１物理量にステップＳ１３で算出した重み係数Ｗｎを固有振動数毎に乗じ、固有振動数毎に重み係数Ｗｎを乗じた第１物理量を節点毎又は要素毎に集約して物理量分布を取得する。

Next, in step S14, the first physical quantity obtained in step S12 is multiplied by the weighting coefficient Wn calculated in step S13 for each natural frequency, and the first physical quantity obtained by multiplying the weighting coefficient Wn for each natural frequency is calculated for each node or element. The physical quantity distribution is obtained by aggregating each time.

For example, when N natural frequencies (N is an integer of 2 or more) are obtained in step S12, the strain energy density of the i-th element at the n-th natural frequency is F(i, n), the n-th When the weighting coefficient applied to the natural frequency of is Wn, the physical quantity distribution A(i) in which the strain energy density, which is obtained by multiplying each natural frequency by the weighting coefficient Wn, is aggregated for each node or element is given by the following formula (3). It is expressed as follows.

Formula 3

なお、第１物理量を節点毎又は要素毎に集約する場合、上記のように固有振動数毎に重み係数を第１物理量に乗じてから節点毎又は要素毎に加算してもよく、あるいはまた、その加算値を固有振動数の個数で除して平均値を求めてもよい。

Note that when the first physical quantity is aggregated for each node or element, the first physical quantity may be multiplied by a weighting coefficient for each natural frequency as described above and then added for each node or element, or alternatively, The average value may be obtained by dividing the added value by the number of natural frequencies.

Next, in step S15, it is determined whether the obtained physical quantity distribution of the first physical quantity has achieved the target performance. Various methods can be used for this determination. For example, it is possible to identify a region in the physical quantity distribution where the strain energy density exceeds a predetermined range, and make the region a region where changing material properties is effective in improving tire performance.

If there is a part in the physical quantity distribution where the first physical quantity exceeds the predetermined range (No in step S15), it is determined that the tire FE model has not achieved the target performance, and the process proceeds to step S16, where the material of the part identified in step S15 is Modify the tire FE model to change its characteristics.

After modifying the tire FE model, the process returns to step S12 to obtain the physical quantity distribution of the modified tire FE model (steps S12 to S14), and again determines whether the physical quantity distribution achieves the target performance (step S15). ). Such modification of the tire FE model (step S16), acquisition of the physical quantity distribution of the modified tire FE model (steps S12 to S14), and determination whether the acquired physical quantity distribution achieves the target performance (step S15) ) are repeatedly executed until the tire FE model achieves the target performance.

Then, when the physical quantity distribution achieves the target performance, the above control is ended, and a tire is manufactured based on the obtained tire FE model.

In this embodiment, a weighting coefficient W is calculated for each natural frequency based on a second physical quantity obtained from the same model as the finite element model from which the first physical quantity was obtained, and the calculated weighting coefficient W is calculated for each natural frequency. After multiplying by one physical quantity, it is aggregated for each node or element to obtain a physical quantity distribution. Therefore, it is possible to reflect the influence of each natural frequency on the physical quantity distribution according to its contribution to tire performance, and it is possible to more accurately identify areas that have a large impact on improving tire performance, thereby improving tire performance. tires can be designed and manufactured at low cost.

In addition, by calculating the weighting coefficient of each natural frequency using the second physical quantity of some nodes of the tire FE model or using the predetermined direction component of the second physical quantity, it is possible to Therefore, the weighting coefficient W can reflect the influence of the parts that make a large contribution to the tire performance. As a result, based on the physical quantity distribution obtained using the weighting coefficient W, it is possible to more accurately identify a region that has a large influence on improving tire performance.

In particular, as in this embodiment, the weighting coefficient W of each natural frequency is calculated using the normal direction component of the vibration velocity of the node located on the tire outer surface of the tire FE model, and the weighting coefficient W is used to obtain the By identifying areas that are effective for improving tire performance based on the physical quantity distribution of It is possible to design and manufacture tires that suppress noise generation at low cost.

(Modification example 1 of the second embodiment)
In the second embodiment, the vibration velocity of each node is acquired as the second physical quantity, and the weighting coefficient W of each natural frequency is calculated using the normal direction component of the vibration velocity of the node located on the tire outer surface of the tire FE model. Although the calculation case has been described, various methods can be used to calculate the weighting coefficient W of each natural frequency from the second physical quantity.

For example, instead of acquiring the vibration velocity of each node as the second physical quantity, the vibration displacement and acceleration of each node are acquired, and the normal direction component of the vibration velocity of the node located on the tire outer surface of the tire FE model is obtained. The weighting coefficient W of each natural frequency may be calculated using

In addition, the vibration velocity, vibration displacement, and acceleration of each node are acquired as second physical quantities, and the tire FE model's tire outer surface shoulder area (centered on the maximum width of the tire, 1/ The weighting coefficient W of each natural frequency may be calculated using the normal direction component or the tire width direction component of the second physical quantity of the node located within the tire radial direction region whose length is multiplied by 2.

In addition, the vibration velocity, vibration displacement, and acceleration of each node are acquired as second physical quantities, and the weight of each natural frequency is calculated using the in-plane direction component of the second physical quantity of the node located on the inner surface of the tire in the tire FE model. The coefficient W may also be calculated. By obtaining the physical quantity distribution using the weighting coefficient W calculated in this way, it is possible to identify the parts that contribute highly to the generation of tire cavity resonance noise, and to reduce the tire cavity resonance noise generation. Can be designed and manufactured at low cost.

(Modification example 2 of the second embodiment)
In the second embodiment, a case will be described in which the second physical quantity is a physical quantity obtained by eigenvalue analysis using the same model as the first physical quantity, but the present invention is not limited to this.

For example, the air around the tire FE model is modeled, and the sound pressure and acoustic parameters at a predetermined target position obtained by eigenvalue analysis using the model are used as the second physical quantities, or the rim attached to the tire FE model is modeled. , and the displacement, velocity, acceleration, or jerk obtained by eigenvalue analysis using the model is used as the second physical quantity, or at least a part of the vehicle is modeled, and a predetermined location of the model is obtained by eigenvalue analysis using the model. For example, a region adjacent to the tire FE model may be modeled, and a physical quantity obtained by eigenvalue analysis using the model may be used as the second physical quantity, such as by setting the reaction force generated in the tire FE model as the second physical quantity.

(Other embodiments)
In each of the embodiments described above, a case has been described in which a portion effective for improving tire performance is specified based on the acquired first physical quantity distribution, but the present invention is not limited thereto. The present invention provides tire performance based on the acquired first physical quantity distribution, such as comparing the performance of a plurality of tires with different structures or acquiring the degree of contribution of the members constituting the tire to the tire performance. Various evaluations of the model can be performed.

The embodiments described above are presented as examples and are not intended to limit the scope of the invention. This novel embodiment can be implemented in various other forms, and various omissions, substitutions, and changes can be made without departing from the gist of the invention.

Claims (7)

In a method for evaluating a tire model consisting of a finite element model divided into multiple elements,
A computer performs an eigenvalue analysis using the finite element method using the tire model to obtain a plurality of natural frequencies, and sets each element of the tire model for each of the obtained plurality of natural frequencies. a first step of acquiring a first physical quantity of each node or each element;
a second step in which the computer aggregates the first physical quantities at each natural frequency obtained in the first step for each node or each element to obtain a physical quantity distribution;
How to evaluate tire models, including: Evaluation of the tire model according to claim 1 , wherein the computer calculates the physical quantity distribution by weighting each natural frequency and aggregating the first physical quantity for each node or each element in the second step. Method. 3. The computer acquires a second physical quantity different from the first physical quantity from the tire model from which the first physical quantity has been acquired, and calculates a weighting coefficient for each natural frequency from the acquired second physical quantity. How to evaluate tire models. The method for evaluating a tire model according to claim 3, wherein the second physical quantity is a physical quantity obtained by an eigenvalue analysis using the same tire model as the first physical quantity. The computer calculates a weighting coefficient for each natural frequency from the second physical quantity of some of the nodes or the elements, or a predetermined directional component of the second physical quantity of some or all of the nodes or the elements. The tire model evaluation method according to claim 3 or 4. 6. The first physical quantity is a physical quantity including any one of stress, strain, and physical quantity calculated using at least one of stress and strain of each element. How to evaluate tire models. a third step in which the computer specifies a region for improving tire performance from the physical quantity distribution obtained using the tire model evaluation method according to any one of claims 1 to 6;
A method for creating a tire model, comprising: a fourth step of modifying the tire model by changing material properties of the portions identified in the third step.

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