JP4763261B2 - Tire performance prediction method, tire design method, tire performance prediction program, and recording medium - Google Patents

Description

  The present invention relates to a tire performance prediction method, a tire design method, a tire performance prediction program, and a recording medium, and predicts performance of a tire having a tread pattern used for an automobile or the like, particularly tire performance such as drainage performance or performance on snow. The present invention relates to a tire performance prediction method, a tire design method, a tire performance prediction program, and a recording medium.

  Conventionally, in the development of pneumatic tires, tire performance is obtained by actually designing and manufacturing tires, mounting them on automobiles, and performing performance tests. I have taken the steps of starting over. Due to the development of numerical analysis methods such as the finite element method (FEM) and the computer environment, for example, the tire performance for paved road surfaces is predicted by performing load analysis and rolling analysis on the rigid road surface of the tires with a computer. It has become possible, and several performance predictions can be made from here (for example, see Non-Patent Document 1).

  The present applicant has proposed a technique relating to tire performance prediction when the tire is used via a fluid, such as tire drainage performance (see Patent Documents 1, 2, 3, and 4). These technologies enable performance prediction by numerical analysis of complex phenomena that require coupled analysis of water and tires, as typified by drainage analysis of tread patterns.

  In addition, the present applicant has developed a technology for predicting tire performance when the tire is used on a road surface on snow, and is a complicated model for modeling a road surface as an elasto-plastic body, represented by snow performance analysis of a tread pattern. Performance prediction by mathematical analysis using a road surface material model has also become possible (see Patent Document 5).

  Also, with current tire performance prediction technology based on numerical analysis, dry road surfaces and icy road surfaces are generally modeled by considering the road surface as a rigid body and appropriately setting the friction coefficient. The tire noise can also be predicted by performing acoustic analysis using the boundary element method (BEM) and finite element method (FEM) as noise analysis using the road surface and air around the tire as acoustic elements. (For example, refer nonpatent literature 2).

  Also, for tire vibration analysis on uneven road surfaces, FEM vibration analysis is performed by modeling the road surface with rigid elements including unevenness and evaluating the axial force when the tire model rolls on the uneven road surface. Thus, performance prediction is possible (for example, see Non-Patent Document 3).

Based on these, dry performance that can assume the road surface is rigid, performance on ice, wet performance on the road via water and snow, performance on snow, noise performance determined by tires and road surface through air, and road surface unevenness With regard to the performance of a single unit such as vibration performance, a part of the tire development cycle for design, manufacturing, and performance evaluation can be replaced by numerical analysis, and the development period has been shortened.
JP 2000-141509 A JP 2000-352549 A JP 2001-009838 A JP 2001-305022 A JP 2003-159915 A Koidg, M., Heguri, H., Kamegawa, T., Nakajima, Y., And Ogawa, H., "Optimization for Motorcyc1e Tire using Explicit FEM," Tire Science and Technology, TSTCA, Vo1.29, No.4 , October-December 2001, pp.230-243. Nakajima, Y., Inoue, Y, and Ogawa, H., "Application of the Boundary Element Method and, Modal Analysis to Tire Acoustic Prob1ems," Tire Science and Technology, TSTCA, Vol.21, No.2, April-June , 1992, pp. 66-90, or ADVirmalwar, Swati M. Athavale, PRSajanpawar, "APPLICATION OF FEM AND EXPERIMENTAL TECHNIQUES FOR SIMULATION OF TYPE / ROAD AIR PUMPING NOISE, HORN EFFECT AND VIBRATION OF TYRE SIDEWALLS," Proceeding Inter-noise , Vol.3.1999, pp.1817-1825 Sobnanie, M., "Road Load Analysis," Tire Science and Technology, TSTCA, Vol.31, No.1, January-March 2003, pp.19-38

  However, in tire design, there is almost no need to satisfy only a single performance, and it is generally necessary to simultaneously satisfy a plurality of performances that are contradictory to each other. For example, there is a contradiction that when the negative rate of the tread pattern is increased to improve the performance on snow, the performance on ice is decreased. In designing tires, it is necessary to create an optimum design plan in consideration of these contradictions. However, a single tire performance prediction technology cannot consider the trade-off between performances, and there is a limit to shortening the development period by replacing a part of the development cycle with numerical analysis. For this reason, the present situation is that the design, manufacturing, and evaluation cycle using numerical analysis technology has not been made efficient.

  In consideration of the above facts, the present invention is a tire performance prediction method, a tire design method, a tire performance prediction program, and a record that can efficiently develop a tire while considering a plurality of tire performances and obtain a tire with good performance. The purpose is to obtain a medium.

  To achieve the above object, the present invention predicts a plurality of tire performances through gas (for example, air), liquid (for example, water), soil and snow, etc., evaluates the tire from a plurality of prediction results, The development has been streamlined to facilitate the provision of tires with good performance.

Specifically, the tire performance prediction method of the present invention includes the following steps (a) to (f). (A) A tire comprising a pair of a tire model having a pattern shape that can be deformed by at least one of ground contact and rolling and a road surface model that is in contact with the tire model and models a road surface state A step of determining a plurality of performance prediction models; (b) for each of a plurality of tire performance prediction models including road models having different road surface states, at least one of a tire model and a road surface model in a state where the tire model is in contact with the road surface model (C) a step of predicting each of the tire performances corresponding to each of the determined physical quantities, and (d) an initial value of each of the plurality of tire performances and the predicted plurality of tire performances. A weight that is proportional to the difference between a predetermined target value for each tire performance and the initial value. Steps and the evaluation value weighted sum subjected to the ratio, the evaluation criteria to determine the evaluation value to evaluate the tire performance from the evaluation criteria based on the plurality of tire performance predicted.

  In the tire performance prediction method of the present invention, first, in order to evaluate the performance of a design plan of a tire to be evaluated (change of tire shape, structure, material, pattern, etc.), a plurality of target performances to be predicted are selected, Apply tire design proposals to numerical analysis models for each target performance. That is, a tire model (numerical analysis model) capable of numerical analysis is created. In addition, a road surface model (numerical analysis model) is created by modeling the target road surface for each target performance. A plurality of combined tire performance prediction models of a road surface model and a tire model for each target performance are determined. These tire performance prediction models are subjected to numerical analysis considering tires and road surfaces at the same time, and numerical prediction of tire performance is performed. The tire model at this time may share a model with respect to a different road surface model, and may use a different tire model. Predict tire performance for each target performance, determine the possibility of a tire design plan from the prediction results of these multiple tire performances, and if the result is good, adopt the design plan, or manufacture a tire of the design plan and evaluate the performance If the result is satisfactory, the design plan is adopted. If one or more predicted performances (or actually measured performances) based on the design plan are insufficient, the design plan is corrected, and the process returns to the creation of the numerical analysis model. With this procedure, the tire development can be made more efficient because the number of times of manufacturing and evaluating the performance is extremely small.

  Therefore, in order to develop a tire based on a plurality of performance predictions, an efficient and accurate numerical analysis model for predicting tire performance is indispensable. Therefore, in the present invention, in order to predict tire performance, in step (a), a tire model having a pattern shape that can be deformed by at least one of ground contact and rolling, and a road surface that is in contact with the tire model and that is in contact with the tire model. A plurality of tire performance prediction models are defined in which a road surface model that models a state is a pair of combinations. In step (b), for each of a plurality of tire performance prediction models including a road surface model having a different road surface state, a physical quantity generated in at least one of the tire model and the road surface model in a state where the tire model is in contact with the road surface model is obtained. . In step (c), each tire performance corresponding to each of the determined physical quantities is predicted. In step (d), the tire performance is evaluated from the estimated tire performances and the respective evaluation criteria for the plurality of predetermined tire performances.

  In the present invention, the tire performance prediction model having a pair of a tire model and a road surface model has a plurality of combinations in which a road surface model having a different road surface state and a corresponding tire model are a pair, and the plurality of tire performances. Each tire performance is predicted from at least two physical quantities obtained from the prediction model, and the tire performance is evaluated based on the prediction. Therefore, in the present invention, by using a plurality of tire performance prediction methods, the design plan change can be evaluated from the tire performance prediction results before performing the actual measurement evaluation. As a result, it is possible to reduce design plan changes made through actual measurement evaluation, and to shorten and improve tire development.

  In the present invention, for the purpose of further shortening and improving the tire development, it is possible to omit the design plan change made through the actual measurement evaluation and replace it with the design plan change made by evaluating the tire performance prediction result. In the present invention, the tire performance evaluation / design plan change / performance prediction calculation portion can be automated and integrated for the purpose of further improving the efficiency of the design change performed by evaluating the tire performance prediction result. When automating or integrating, mathematical methods, exploratory methods, empirical methods, optimization methods such as trade-off analysis, approximation methods such as response surface methodology, experimental design, Employing a sampling method such as the Monte Carlo method, a robust design method such as the Tacti method, and a reliability evaluation / optimization method that takes into account variations in the design plan are effective in improving efficiency and improving tire performance.

  Invention of Claim 2 is a tire performance prediction method of Claim 1, Comprising: In the said step (a), the fluid model which modeled the fluid which at least one part contacts with at least one of a tire and a road surface In step (b), a deformation calculation of the tire model is executed, a flow calculation of the fluid model is executed, and the tire model and the flow after the deformation calculation are determined. Recognizing and recognizing the boundary surface with the fluid model after the calculation, the boundary condition related to the recognized boundary surface is applied to the tire model and the fluid model, and the deformation calculation and the flow calculation are performed on the tire model and the fluid model after the boundary condition is applied. The calculation is repeated until the fluid model is in a pseudo-flow state.

  When a load is applied to soil, snow, etc., the internal structure (structure formed by cavities and soil or structure formed by cavities and ice crystals) changes and deforms. There are cases where the initial shape does not return. Therefore, in order to express soil and snow as a numerical model, fluid such as soil and snow is used as a plastic body as a fluid model. In addition, characteristics as an elastic body are given as necessary, and modeling is performed so as to generate an appropriate reaction force when a load is applied. As described above, by modeling a fluid such as soil or snow as an elasto-plastic body or a plastic body (rigid plastic body), the tire performance can be predicted with high accuracy.

  Thus, the fluid model included in the road model of the snow road surface needs to be coupled with the tire model. This coupled calculation is described in more detail in Japanese Patent Application Laid-Open No. 2000-141509, Japanese Patent Application Laid-Open No. 2000-352549, Japanese Patent Application Laid-Open No. 2001-009838, and Japanese Patent Application Laid-Open No. 2001-305002. Are listed.

  In addition, the present invention is a development of the previous invention, and a plurality of tire performances (for at least one tire performance, the previous invention related to the water-tire coupled calculation method is used from a single tire performance target). Can be predicted with high accuracy up to a relationship in which a plurality of tire performances contradict the design plan, thereby improving tire development efficiency.

  The invention according to claim 3 is the tire performance prediction method according to claim 2, wherein the road surface model includes a fluid model in which a wet road surface is targeted and the liquid is modeled as the road surface state. And

  The road surface model of the tire performance prediction model includes a fluid model (for example, a water model) in which a road surface state is a wet road surface and a liquid such as water is modeled, so that at least one of the tire performances is a tire. Of wet performance can be included.

  Invention of Claim 4 is the tire performance prediction method of Claim 2, Comprising: The said road surface model makes the snow road surface object as the said road surface state, and the snow model which modeled the elastic-plastic body or the plastic body As a fluid model.

  As the road surface model of the tire performance prediction model, at least one of the tire performances includes the on-snow performance of the tire by modeling the snow surface as a elasto-plastic material or a plastic material for the road surface condition. be able to.

  The invention according to claim 5 is the tire performance prediction method according to claim 2, wherein the road surface model targets a sherbet road surface as the road surface state, and models an elastic-plastic body or a plastic body containing liquid. The sherbet model is included as a fluid model.

  As a road surface model of the tire performance prediction model, the road surface state is a sherbet road surface, and an elastic-plastic body containing liquid or a sherbet model in which a plastic body is modeled is included as a fluid model. One can include the sherbet performance of the tire.

  In the present invention, for example, coupled calculation of water and tires, and coupled calculation of snow and tires, for example, are developed, and the subject is a sherbet road surface that is snow containing a large amount of moisture. By doing so, the running ability on the sherbet road surface can be predicted.

  Specifically, the characteristics of the water model are that the bulk modulus of water is very high in order to express incompressibility, the shear modulus is considered to be “0”, and water is considered as an elastoplastic material. The yield stress is considered to be “0”. On the other hand, the feature of the snow model relates to a method for calculating snow and tire coupling. Snow can be regarded as an elasto-plastic material (yield stress needs to be considered), the bulk modulus is very low compared to the water model, and the shear modulus needs to be considered. Since the feature of the sherbet road surface is snow that contains a large amount of water, in the present invention, the characteristics of the sherbet road surface are considered to be intermediate between the characteristics of the snow model and the water model, and the snow model and the water model are included in the material characteristics of the sherbet model. A numerical value obtained by internally dividing the material characteristics at a certain ratio is used. The material properties that are internally divided at a certain ratio include at least one of bulk modulus, shear modulus, Poisson's ratio, and yield stress. In this case, the fixed ratio may be obtained by actually measuring the material properties of the sherbet to obtain an optimum ratio, or may be obtained by trial and error in accordance with the moisture content contained in the sherbet.

  In order to evaluate the tire performance on the sherbet road surface, the dynamic pressure generated by the collision between the tire and the sherbet at the traveling speed reduces the force (fluid reaction force) that pushes up the tire, as in the water-tire coupled calculation. It can be considered that sherbet road running performance is high. Therefore, in order to reduce the fluid reaction force, it is only necessary to design the tire so that the dynamic pressure becomes small.

  A sixth aspect of the present invention is the tire performance prediction method according to the second aspect, wherein the road surface model targets a road surface on ice as the road surface state, and selects a predetermined friction coefficient of the road surface on ice. It includes an on-ice road surface model modeled by

  As the road surface model of the tire performance prediction model, the road surface condition is on the ice surface, and by including a predetermined on-ice road surface friction coefficient model, the tire performance includes: At least one can include the on-ice performance of the tire. As for the calculation method, the road surface model may be modeled with a rigid element, and the friction coefficient measured on the road surface on ice may be used as the road surface model.

  The invention according to claim 7 is the tire performance prediction method according to claim 2, wherein the road surface model targets a dry road surface as the road surface state, and selects a predetermined dry road friction coefficient. A dry road surface model modeled by

  As a road surface model of the tire performance prediction model, the road surface condition targets a dry road surface, and includes a dry road surface model that is modeled by selecting a friction coefficient of a predetermined dry road surface. At least one can include the performance of the tire on the dry road surface. Regarding the calculation method, a road surface model may be modeled with rigid elements, and a friction coefficient measured on a dry road surface may be used as the road surface model.

  The invention according to claim 8 is the tire performance prediction method according to claim 2, wherein the road surface model is an elastoplasticity that includes soil as a target for a soil road surface representing an agricultural field or an unpaved land as the road surface state. A soil model obtained by modeling a body or a plastic body is included as a fluid model.

  As a road surface model of the tire performance prediction model, including a soil model that models an elastoplastic body or a plastic body including soil as a fluid model, where a road surface state represents an agricultural field or an unpaved land. In addition, at least one of the tire performances can include the performance on the soil road surface of the tire.

  The invention according to claim 9 is the tire performance prediction method according to claim 2, wherein the road surface model includes a noise analysis model in which a road surface including a gas in the vicinity where the tire contacts the road surface is modeled. It is characterized by.

  The road surface model of the tire performance prediction model includes a noise analysis model that models a road surface including a gas in the vicinity where the tire is in contact with the road surface. Can be included. That is, the road surface state is a road surface including air in the vicinity of the ground contact surface, and the road surface model can be motelized using air as a tire noise performance analysis model. Thereby, the noise performance of the tire can be included in at least one of the tire performances. As for the calculation method, the air around the tire model may be modeled with acoustic elements, and a general BEM or FEM acoustic analysis may be performed as a noise analysis. When FEM is used as an acoustic element around the tire model, an infinite element is used to consider the distance from the tire surface to infinity, or to a sufficiently far distance where noise performance can be evaluated. The road surface model has a total reflection condition or a sound absorption characteristic, and is set so that tire surface vibrations are appropriately reflected on the road surface.

  The tire analysis using the finite element method can adopt a technique already proposed by the present applicant, and the acoustic analysis is performed using a standard acoustic analysis method such as Nakajima, Y, Inoue, Y. Ogawa, H., "App1ication of the Boundary Element Method and Modal Analysis to Tire Acoustic Problems," Tire Sience and Technology, TSTCA, Vol.21, No.2, April-June, 1992, pp.66 / 90, or AD Virmalwar, Swati M. Athavale, PRSajanpawar, "APPLICATION OF FEM AND EXPERIMENTAL TECHNIQUES FOR SIMULATION OF TYPE / ROAD AIR PUMPING NOISE, HORN EFFECT AND VIBRATION OF TIRE SIDEWALLS," Proceeding Inter-noise 99, Vol.3 1999, pp1817-1825 Can be adopted.

  The invention according to claim 10 is the tire performance prediction method according to claim 2, wherein the road surface model is an uneven road surface model that targets uneven road surfaces as the road surface state and models road surfaces including unevenness. It is characterized by including.

  The road surface model of the tire performance prediction model includes an uneven road surface model in which the road surface condition is an uneven road surface and the road surface including the unevenness is modeled, so that at least one of the tire performance is an uneven road surface of the tire. Top performance can be included.

The pneumatic tire designing method according to the eleventh aspect includes the following steps (1) to (7). (1) A tire having a pair of a tire model having a pattern shape that can be deformed by at least one of contact and rolling and a road surface model that is in contact with the tire model and models a road surface state A step of determining a plurality of performance prediction models; (2) for each of a plurality of tire performance prediction models including road surface models having different road surface conditions, at least one of a tire model and a road surface model in a state where the tire model is in contact with the road surface model (3) a step of predicting each of the tire performances corresponding to each of the determined physical quantities, and (4) an initial value of each of the plurality of tire performances and the predicted plurality of tire performances. A weight that is proportional to the difference between a predetermined target value for each tire performance and the initial value. An evaluation value weighted sum subjected to the ratio, the evaluation criteria to determine the evaluation value, evaluating the tire performance from the evaluation criteria based on the plurality of tire performances expected, (5) of the tire performance A step of correcting each tire model of the tire performance prediction model based on the evaluation result; (6) the step (2) to the step (5) for the tire performance prediction model based on the corrected tire model; And (7) repeating until the evaluation value reaches the maximum value or the minimum value so that the evaluation result becomes a predetermined target performance , and (7) a tire based on the tire model of the calculation result of step (6) Step to design .

  When designing a tire, if the steps are sequentially executed, the tire performance of the tire can be evaluated from a plurality of tire performances, and the design can be made while predicting the tire performance. .

When the tire performance is predicted by a computer, the tire performance can be evaluated easily and simply by causing the computer to execute the following tire performance prediction program. Specifically, the tire performance prediction program according to the twelfth aspect of the invention includes the following steps (A) to (D). (A) A tire comprising a pair of a tire model having a pattern shape that can be deformed by at least one of ground contact and rolling and a road surface model that is in contact with the tire model and models a road surface state (B) at least one of a tire model and a road surface model in a state where the tire model is in contact with the road surface model, for each of a plurality of tire performance prediction models including road surface models having different road surface states; (C) predicting each of the tire performances corresponding to each of the determined physical quantities, and (D) initial values of the plurality of tire performances and the predicted plurality of tire performances. A weight that is proportional to the difference between a predetermined target value for each tire performance and the initial value. Steps and the evaluation value weighted sum subjected to the ratio, the evaluation criteria to determine the evaluation value to evaluate the tire performance from the evaluation criteria based on the plurality of tire performance predicted.

In addition, when predicting tire performance by a computer, if the following tire performance prediction program is stored and executed in a storage medium and data is collected, it will be useful for comparison with past performance evaluation and future data accumulation. be able to. Specifically, the invention described in claim 13 is a recording medium on which a tire performance prediction program for predicting tire performance by a computer is recorded, and includes the following steps. (I) A tire comprising a pair of a tire model having a pattern shape that can be deformed by at least one of contact with the ground and rolling, and a road surface model that is in contact with the tire model and models a road surface state (B) at least one of a tire model and a road surface model in a state where the tire model is in contact with the road surface model, for each of a plurality of tire performance prediction models including road surface models having different road surface conditions; (B) predicting each of the tire performances corresponding to each of the obtained plurality of physical quantities, ( i ) initial values of the plurality of tire performances and the predicted plurality of tire performances A weight that is proportional to the difference between a predetermined target value for each tire performance and the initial value. Steps and the evaluation value weighted sum subjected to the ratio, the evaluation criteria to determine the evaluation value to evaluate the tire performance from the evaluation criteria based on the plurality of tire performance predicted.

  As described above, according to the present invention, the tire is evaluated by predicting or analyzing a plurality of tire performances, so that the efficiency of tire development can be improved and a tire with good performance can be obtained. There is an effect that.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. In this embodiment, the present invention is applied to performance prediction of a pneumatic tire.

  FIG. 1 shows an outline of a personal computer for performing performance prediction of the pneumatic tire of the present invention. The personal computer includes a keyboard 10 for inputting data and the like, a computer main body 12 that predicts tire performance according to a pre-stored processing program, and a CRT 14 that displays calculation results of the computer main body 12 and the like.

  The computer main body 12 includes a flexible disk unit (FDU) into which a flexible disk (FD) as a recording medium can be inserted and removed. Note that processing routines and the like described later can be read from and written to the flexible disk FD using the FDU. Therefore, a processing routine to be described later may be recorded in the FD in advance and the processing program recorded in the FD may be executed via the FDU. Further, a mass storage device (not shown) such as a hard disk device is connected to the computer main body 12, and the processing program recorded on the FD is stored (installed) in the mass storage device (not shown) and executed. Also good. Recording media include optical discs such as CD and DVD, and magneto-optical discs such as MD and MO. When these are used, instead of or in addition to the FDU, a CD-ROM device, a CD-RAM device, a DVD- A ROM device, DVD-RAM device, MD device, MO device, or the like may be used.

(Performance prediction evaluation)
FIG. 2 shows a processing routine of the performance prediction evaluation program of the present embodiment. In step 100, a design plan (change of tire shape, structure, material, pattern, etc.) of the tire to be evaluated is determined. In step 100, a plurality of target performances to be predicted are selected in order to evaluate the performance of the design plan of the tire to be evaluated (change of tire shape, structure, material, pattern, etc.). The target performance includes the performance on snow, the performance on a sherbet in which a part of the liquid such as water is crystallized, the performance on the ice in the frozen state in which all of the liquid such as water is frozen, and the dry road surface by selecting the friction coefficient. There are performance (dry performance), performance on wet road surface (wet performance), performance on soil in a field or non-paved land, noise performance, performance on uneven road surface and the like. As an example of the target performance to be set, it is possible to define a contradictory performance evaluation value of improving the performance on snow and improving the performance on ice, with the performance on snow and the performance on ice as target performance.

  Next, tire performance prediction is executed for each target performance selected in step 100 above. That is, in steps 101-1, 101-2,..., 101-N (N is a natural number greater than or equal to 2 and the total number of target performances) corresponding to each target performance selected in step 100, prediction calculation of tire performance is performed. Executed. In the next step 101A, tire performance is evaluated from a plurality of prediction results obtained by the prediction calculation in steps 101-1 to 101-N.

  Next, in step 124, it is determined from the evaluation of the prediction result whether or not the prediction performance is good. The determination in step 124 may be made by inputting from the keyboard. Moreover, when an allowable range is set in advance in the evaluation value and the evaluation value of the prediction result is within the allowable range, the prediction performance is good. You may make it judge.

  As a result of the evaluation of the predicted performance, if the target performance is insufficient, the result is negative in step 124, the design plan is changed (corrected) in the next step 134, the process returns to step 102, and the processing so far is repeated. On the other hand, if the performance is sufficient, the result is affirmative in step 124, and in the next step 126, the tire of the design plan set in step 100 is manufactured, and in the next step 128, the tire actual performance evaluation is performed on the manufactured tire. I do. When the result of the tire actual performance evaluation in step 128 is satisfactory performance (good performance), the result in step 130 is affirmative, and in the next step 132, the design plan modified in step 100 or step 134 is determined as good. Adopt as performance, and end this routine. The adoption of the design plan in step 132 outputs (displays or prints) that the design plan has good performance, and stores the data of the design plan.

  In the above embodiment, the case where the tire performance prediction and evaluation for one design plan is repeated while correcting the design plan and the design plan to be adopted is obtained is described, but the present invention is limited to this. Instead, a design plan to be adopted from a plurality of design plans may be obtained. For example, tire performance prediction and evaluation may be performed for a plurality of design plans, and the best design plan may be selected from each evaluation result. Further, the best design plan can be obtained by executing the above embodiment for the selected best design plan.

  Thus, in the present embodiment, a plurality of tire performance predictions are performed. Previously, single tire performance prediction and evaluation were performed using actual evaluation or numerical analysis assuming a single road surface, so it was not possible to improve the efficiency of tire development using numerical analysis in areas where multiple tire performances contradict each other. The draft change was forced to be made after actual evaluation. In the present embodiment, as shown in FIG. 2, the design plan can be changed by performing a plurality of tire performance predictions, by evaluating the tire performance prediction results before performing the actual measurement evaluation. As a result, it is possible to reduce design plan changes made through actual measurement evaluation, and to shorten and improve tire development.

(Performance evaluation standard)
Here, the processing of step 101A will be described. In step 101A, the tire performance is evaluated from the tire performance prediction processing result for each target performance selected in the above step. In the present embodiment, a plurality of different prediction results are evaluated according to the following evaluation criteria.

  The prediction result of step 101-i (1 ≦ i ≦ N: i is a number for identifying tire performance), which is the tire performance prediction process, differs depending on the target tire performance (target performance). For example, traction on snow predicts longitudinal force, whereas slash performance predicts fluid reaction force (vertical force etc.).

  Therefore, in this embodiment, in order to evaluate the predicted values of different tire performances in a unified manner, the fluctuation ratio of the tire performance predicted values with respect to the initial design plan in the tire performance prediction model (specifically, the tire model) (hereinafter referred to as performance). Fluctuation rate P (i)) is adopted.

P (i) = Ca (i) / Cb (i)
However, i is a number representing the target performance, Ca is the tire performance after correcting the tire performance prediction model (specifically, the tire model), and Cb is the tire performance of the initial design plan.

  Using this performance fluctuation rate P, the prediction results of a plurality of tire performances are evaluated in an integrated manner by a mathematical formula that obtains an evaluation value Q shown in the following formula.

Q = W ₁ · P (1) + ... + W _N · P (N)
Here, N is the total number of target performances, and W is a weighting factor. The weighting factor W can be arbitrarily set, but is preferably selected so as to be proportional to the difference between the design target and the initial design plan as follows.

W _i = {Cc (i) −Cb (i)} / Cb (i) · α
ΣW _i = 1 (i = 1 to N)
However, Cc is a design target of tire performance. Α is a constant for normalization so that the sum of the weighting factors W becomes “1”.

  As a result, the evaluation standard value of the initial design plan is “1” and the evaluation standard value of the modified design plan is “1” or more, whatever the evaluation standard of each tire performance. Further, the farther the initial design plan is from the design target, the higher the priority of the tire performance. Therefore, a plurality of tire performance predictions are performed in steps 101-1 to 101-N, and the design plan modification (step 134) is repeatedly executed so that the evaluation value Q in step 101A is maximized.

(Tire performance prediction)
Next, details of step 101-i (1 ≦ i ≦ N), which is a tire performance prediction process for each target performance selected in the above step, will be described. FIG. 3 shows a typical processing routine of the tire performance prediction program. Here, as an example of the tire performance prediction, a case where the tire performance prediction is performed with respect to the performance on the sherbet road surface will be described.

  First, when considering an elastoplastic body containing liquid or a sherbet model modeling a plastic body, a fluid model using water as a fluid (hereinafter referred to as a water model) and a tire model, and a fluid using snow as a fluid It is necessary to consider both a model (hereinafter referred to as a snow model) and a tire model. That is, the sherbet model is considered to be a combination of a water model and a snow model.

  The characteristics of the water model are that the bulk modulus of water is very high to express incompressibility, the shear modulus is considered to be “0”, and the yield stress is high when water is considered an elastoplastic material. To be considered “0”. On the other hand, the characteristics of the snow model are that snow can be regarded as an elasto-plastic material (yield stress needs to be considered), the bulk modulus is much lower than the water model, and the shear modulus needs to be considered There is. And since the feature of the sherbet road surface is snow containing a lot of moisture, in this embodiment, the characteristic of the sherbet road surface is considered to be intermediate between the characteristics of the snow model and the water model, and the snow model A numerical value obtained by internally dividing the characteristics of the water model at a fixed ratio is used. The characteristic of internal division at a constant ratio includes at least one of bulk modulus, shear modulus, Poisson's ratio, and yield stress. The constant ratio of the material characteristics may be obtained by actually measuring the material physical properties of the sherbet to obtain an optimum ratio, or may be obtained by trial and error in accordance with the moisture content contained in the sherbet.

  Therefore, the tire performance prediction processing for the performance on the sherbet road surface is performed by the tire and the sherbet in accordance with a technique related to a water model and tire coupled calculation method (for example, Japanese Patent Application Laid-Open No. 2001-305002 already proposed by the applicant). It can be considered that the sherbet road running performance is higher as the force (fluid reaction force) that pushes up the tire by the dynamic pressure generated by the collision at the traveling speed is smaller. Thus, in order to reduce the fluid reaction force, it is only necessary to design the tire so that the dynamic pressure becomes small.

  In the present embodiment, tire performance prediction of sherbet road surface performance is described as an example, but the present invention is not limited to this. For example, as shown in FIG. 7, there is a contradiction that when the negative rate of the tread pattern is increased to improve the performance on snow, the performance on ice is decreased. In designing tires, it is necessary to create an optimum design plan in consideration of these contradictions. For this reason, as described in the present embodiment, it is very effective to obtain a plurality of tire performances simultaneously.

  Details of the tire performance prediction process will be described below. In step 101-i of FIG. 2, that is, in the tire performance prediction process, the processing routine of FIG. 3 is executed. First, in step 102 of FIG. 3, a tire design plan is dropped into a numerical analysis model for each target performance selected in step 100 in the tire performance prediction model.

  That is, in step 102, a tire model is created in order to drop the tire design plan into a numerical analysis model. The creation of the tire model differs slightly depending on the numerical analysis method used. In this embodiment, a finite element method (FEM) is used as a numerical analysis method. The tire model in this case is divided into a plurality of elements by element division corresponding to the finite element method (FEM), for example, mesh division, and the tire is input to a computer program created based on a numerical / analytical method. This is the data format. This element division refers to dividing an object such as a tire, a fluid, and a road surface into several small (finite) small parts. After calculating every small part and calculating all the small parts, the whole response can be obtained by adding all the small parts. The numerical analysis method may be a difference method, a finite volume method, or a discrete element method (DEM).

  In the creation of the tire model in step 102, a pattern can be modeled after a tire cross-section model is created. Specifically, a tire radial section model is created, that is, tire section data is created. The tire cross-section data is collected from a design drawing or measured by measuring the outer shape of the tire with a laser shape measuring instrument or the like. Also, the exact structure of the tire is taken from the design drawings and actual tire cross-section data. Rubber and reinforcing materials (belts, plies, etc., which are bundles of reinforcing cords made of iron / organic fibers, etc., bundled in a sheet shape) in the tire cross section are modeled according to the modeling method of the finite element method. Next, the tire cross-section data (tire radial cross-section model), which is two-dimensional data, is developed by one turn in the circumferential direction to create a three-dimensional (3D) model of the tire. 4A and 4B show the process of creating a tire model, where FIG. 4A is a tire cross-section model, FIG. 4B is an image diagram of the tire cross-section model being developed in the circumferential direction, and FIG. 4C is a tire developed one round (360 degrees). 3 shows a three-dimensional (3D) model. In FIG. 4C, a part of the tire in the circumferential direction is finely divided, but it is needless to say that 360 degrees may be equally divided.

  It should be noted that the creation of the tire model can be omitted in the case of the other tire performance prediction process when the same tire model is employed for predicting the tire performance for each target performance.

  In the next step 104, a road surface model of the tire performance prediction model is created as a main process. Specifically, step 104 includes creation of a fluid model, creation of a road surface model, and setting of a road surface state. First, the fluid model is located between the tire and the road surface, and is a gas such as air, a liquid such as water, an elastic plastic or plastic body such as snow (including a sherbet body such as snow containing a large amount of moisture), A fluid such as soil is modeled as an example. In the present embodiment, a sherbet-like fluid containing a large amount of moisture in snow is assumed. In creating a fluid model, first, a part (or all) of a tire, a ground contact surface, and a fluid region including a region where the tire moves and deforms are divided and modeled. When the creation of the fluid model is completed, the environment construction that can be evaluated is completed by inputting the road surface state together with the creation of the road surface model.

  Here, the road surface is modeled and input to set the modeled road surface to an actual road surface state. The road surface is modeled by dividing the road surface shape into elements and selecting the road surface friction coefficient μ and inputting the road surface state. That is, since there is a road friction coefficient μ corresponding to dry (DRY), wet (WET), on ice, snow, non-paved, etc., depending on the road surface condition, by selecting an appropriate value for the friction coefficient μ, The road surface condition can be reproduced. Further, the road surface model only needs to be in contact with at least a part of the fluid model, and can be arranged inside the fluid model. Further, the road surface model can express an uneven road surface. In this case, the road surface can be easily created not by flattening but by providing unevenness.

  In the next step 108, boundary conditions are set. That is, since a part of the tire model is interposed in a part of the fluid model, it is necessary to simulate the behavior of the tire and the fluid by giving analytical boundary conditions to the fluid model and the tire model. This procedure is different when the tire is rolling and when the tire is not rolling. The selection of when the tire is rolling and when the tire is not rolling may be input in advance, or may be selected at the beginning of the execution of this process, and both are executed and selected after obtaining each. Anyway.

  As shown in FIG. 5A, the setting of the boundary conditions at the time of tire rolling in step 108 gives boundary conditions regarding inflow / outflow to the fluid model (fluid region) 20 in step 400. As shown in FIG. 6A, the boundary condition regarding the inflow / outflow is that the upper surface 20A of the fluid model (fluid region) 20 flows freely, and the other front surface 20B, rear surface 20C, side surface 20D, and lower surface 20E are Treat as a wall (no inflow / outflow). In the next step 402, internal pressure is applied to the tire model, and in the next step 404, at least one of rotational displacement and straight displacement (displacement may be force or speed) and a predetermined load load are applied to the tire model. In addition, when considering friction with the road surface, only one of rotational displacement (or force or speed) or straight displacement (or force or speed) may be used.

  As shown in FIG. 5B, the setting of the boundary condition at the time of tire non-rolling in step 108 gives the boundary condition regarding inflow / outflow to the fluid model in step 410. Here, since the analysis is performed in a steady state, the tire model is stationary in the traveling direction, and a fluid model in which the fluid flows toward the tire model at the traveling speed is considered. That is, in step 412, a flow velocity is given to the fluid in the fluid model (fluid region). As shown in FIG. 6B, the boundary conditions regarding inflow / outflow are the same as those at the time of rolling, with the front surface of the fluid model (fluid region) 20 flowing in at the advancing speed, the rear surface flowing out, and the upper surface, side surface, and lower surface. . In step 414, an internal pressure is applied to the tire model, and in the next step 416, a load is applied to the tire model.

  When the setting of the boundary condition is completed in step 108, the tire model is deformed in step 110, and it is determined in the next step 112 whether the elapsed time is within 1 msec. If the determination in step 112 is affirmative, the process returns to step 110 and the tire model deformation calculation is performed again. Here, the deformation calculation of the tire model is performed based on the finite element method from the tire model and the given boundary conditions. In order to obtain a transient state, the tire model deformation calculation is repeated while the elapsed time (single elapsed time) is 1 msec or less, and when 1 msec elapses, the next calculation (fluid calculation) is started.

  If the result is negative in step 112, the flow proceeds to step 114 to perform fluid calculation. In the next step 116, it is determined whether or not the elapsed time is within 1 msec. If the result is affirmative, the process returns to step 114, the fluid calculation is performed again, and if the result in step 116 is negative, the process proceeds to step 118. Here, the fluid calculation is performed based on the finite element method from the fluid model and the given boundary conditions. In order to obtain a transient state, the fluid calculation is repeated while the elapsed time (single elapsed time) is 1 msec or less, and when 1 msec elapses, the next calculation is started.

  In this manner, the tire model deformation calculation and fluid calculation (flow calculation) are performed based on the numerical model created or set up to step 108. In order to obtain a transient state, the deformation calculation of the tire model and the fluid calculation of the fluid model are each performed within 1 msec, and the boundary conditions of both are updated every 1 msec.

  Note that either the tire model deformation calculation or the fluid calculation may be calculated first, or may be calculated in parallel. That is, steps 110 and 112 and steps 114 and 116 may be exchanged.

  In the above description, the case where the calculation is repeatedly performed during the preferable elapsed time in which the elapsed time (single elapsed time) is 1 msec or less has been described. However, in the present invention, the elapsed time is not limited to 1 msec, and 10 msec or less. The elapsed time can be employed, preferably 1 msec or less, and more preferably 1 μsec or less. Further, the elapsed time may be determined individually.

  In the next step 118, the tire model deformation calculation and the fluid calculation are performed separately for 1 msec and then coupled to each other. Therefore, the boundary surface of the fluid model is recognized according to the deformation of the tire model, and the boundary condition is set. In step 119, the surface pressure is applied to the tire model.

  In step 118, first, in order to determine which part of the fluid model is hidden in the tire model, an interference part between the fluid model and the tire model is calculated. Next, it is determined whether or not the fluid element is completely hidden in the tire model. If the fluid element is completely hidden in the tire model, this element is inside the tire model, and the inflow and outflow of fluid are performed. Since it is not broken, a boundary condition as a wall is added. On the other hand, when a part of the fluid element is hidden in the tire model, a cut surface that divides the fluid element is calculated on the surface of the tire model, and the fluid element is further divided on the cut surface. Next, a region that is not hidden by the tire model among the divided fluid elements is newly defined as a fluid model (fluid region), and this portion is used for fluid calculation. Further, since the cut surface of the new fluid element is in contact with the tire model, a boundary condition as a wall is added. Thereby, the surface shape of the tire model can be taken into the fluid calculation as a boundary condition.

  In step 119, the pressure calculated by the fluid calculation is added to the tire model as a boundary condition (surface force) of the tire model, and the deformation of the tire model due to the fluid force is calculated by the deformation calculation of the next tire model. On the fluid side, the surface shape of the deformed tire model is taken into the boundary condition as a new wall, and on the tire model side, the fluid pressure is taken into the boundary condition as a surface force acting on the tire model. By repeating this every 1 msec, a transient flow related to tire performance prediction can be created in a pseudo manner. Here, 1 msec is a time that can sufficiently express the process in which the pattern in the contact surface is deformed by rolling the tire.

  In the above, the repetition time (single elapsed time) taken into the boundary condition is set to 1 msec. However, the present invention is not limited to 1 msec, and a time of 10 msec or less can be adopted, preferably 1 msec or less. Yes, and more preferably, a time of 1 μ · sec or less can be employed.

  In the next step 120, it is determined whether or not the calculation is completed. If the result in step 120 is affirmative, the process proceeds to step 122. If the result in step 120 is negative, the process returns to step 110, and the tire model deformation calculation and fluid calculation are performed again. A single calculation is performed every 1 msec. In addition, as a specific determination method, there are the following examples.

  If the tire model is a non-rolling model or a rolling model with an all-round pattern, the target physical quantity (fluid reaction force, pressure, flow rate, etc.) can be regarded as a steady state (can be regarded as the same as the previously calculated physical quantity) State) until the calculation is completed. Or, it is repeated until the deformation of the tire model can be regarded as a steady state. Furthermore, it is also possible to end the process when a predetermined time is reached. The predetermined time in this case is preferably 100 msec or more, more preferably 300 msec or more.

  In this way, after changing the tire model deformation calculation, fluid calculation, and adding boundary conditions (surface force) for the coupling of both, the tire model deformation calculation was returned to and changed again. Perform calculations with boundary conditions. This is repeated until the calculation is completed. When the calculation is completed, the result is affirmative in step 120, the process proceeds to step 122, the calculation result is output as the prediction result, the prediction result is evaluated, and then this routine is ended. FIG. 8 shows a dynamic pressure distribution by sherbet, which is an example of an output as a prediction result.

  The output of the calculation result and the evaluation of the prediction result may be performed during the repeated calculation by outputting the calculation result at that time and evaluating the output or sequentially evaluating the output. In other words, output and evaluation may be performed during the calculation.

  As the output of the prediction result, values or distributions of shear force, shear stress, fluid force, flow velocity, flow rate, pressure, energy, etc. can be adopted. Specific examples of the output of the prediction result include output of fluid reaction force, output and visualization of fluid flow, and output and visualization of stress distribution. The fluid reaction force is a force by which fluid (for example, snow) moves the tire forward and stops but pushes it upward. The flow of the fluid can be calculated from the velocity vector of the fluid, and can be visualized by representing both the flow and the periphery of the tire model and the periphery of the pattern with a diagram or the like. To visualize the stress distribution of the fluid, the tire model periphery and pattern periphery may be created as a diagram, and the stress value may be displayed on the figure corresponding to the color or pattern.

  In addition, the evaluation includes an evaluation of whether the traction is an acceptable value, a subjective evaluation (whether it is flowing smoothly, judgment of turbulence depending on the direction of flow, etc.), and pressure / energy is rising locally. It is possible to adopt whether there is no flow rate, a necessary flow rate is obtained, a fluid force is not increased, a flow is not stagnated, or the like. Moreover, in the case of a pattern, it can also be adopted whether it is flowing in the groove. Also, in the case of a tire model, when the tire rotates, the tire sandwiches fluid such as water near the ground contact surface and the ground contact surface, and there is a large amount of forward spray pushed forward, or whether it is flowing sideways on the road surface, Can be adopted.

  The evaluation of the prediction result is expressed numerically by using the output value of the prediction result and the distribution of the output value, and how well the predetermined allowable value and the allowable characteristic are adapted to each output value and the distribution of the output value. By doing so, an evaluation value can be determined.

  In the above embodiment, the case where the tire performance prediction and evaluation for one design plan is repeated while correcting the design plan and the design plan to be adopted is obtained is described, but the present invention is limited to this. Instead, a design plan to be adopted from a plurality of design plans may be obtained. For example, tire performance prediction and evaluation may be performed for a plurality of design plans, and the best design plan may be selected from each evaluation result. Further, the best design plan can be obtained by executing the above embodiment for the selected best design plan.

  As described above, in the present embodiment, when evaluating tire performance, prediction performance evaluation by prediction calculation of a tire model and measurement performance evaluation of a manufactured tire are performed. These predicted performance evaluation and actual performance evaluation are used to confirm the obtained tire performance.

  First, in the prediction performance evaluation based on the tire model prediction calculation, which is the main part of the present embodiment, a plurality of performance evaluations are calculated for each design plan change. In the past, tires were prototyped and tested every time the design plan was changed, so waiting time was a bottleneck in development efficiency. Time can be reduced by substituting this for prediction. Further, when a plurality of tire performance prediction evaluations are not performed, actual evaluations must be performed for performances that cannot be predicted every time the design plan is changed, which does not lead to elimination of bottlenecks in trial production and experiments. If all necessary performance can be predicted and evaluated, the tire performance evaluation cycle can be accelerated from the change of the design plan.

  By the way, since there is a prediction error in the prediction evaluation, there is a difference in evaluation between the predicted value and the actually measured value. However, it has been confirmed that this prediction error is within an acceptable range when establishing a prediction evaluation method. However, it is usually preferable to confirm that the prediction error is within an allowable range at the end of the actual measurement evaluation after the tire design plan is finalized. The allowable range means whether it is within the design target range.

  Therefore, in the present embodiment, the tire performance of the design plan is finally confirmed by the actual performance evaluation of the manufactured tire.

  Therefore, in the past, it was necessary to carry out many times for each design plan change, but in this embodiment, it is for confirming that the error between the prediction evaluation and the actual measurement evaluation is within an allowable range. It only needs to be done once. That is, the actual measurement evaluation is a final check, and it is usually only necessary to confirm that the actual measurement result matches the prediction result. This is not to reflect the actual measurement result in the prediction. Therefore, only when the actual measurement result and the prediction result are true beyond the allowable range, the examination is repeated from the prediction evaluation loop with another design plan.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. In this embodiment, the present invention is applied to performance prediction of a radial tire.

  As a tire standard, the load is a standard load, and the standard load is a maximum load (maximum load capacity) of a single wheel in an application size described in the following standard. The internal pressure at this time is the air pressure corresponding to the maximum load (maximum load capacity) of the single wheel in the applicable size described in the following standard. The rim is a standard rim (or “Approved Rim” or “Recommended Rim”) in an applicable size described in the following standard. The standard is determined by an industrial standard effective in the region where the tire is produced or used. For example, in the United States, “The Tire and Rim Association Inc. Year Book”, in Europe “The European Tire and Rim Technical Organization Standards Manual”, and in Japan, the Japan Automobile Tire Association “JATMA Year Book”. ing.

  After modeling for performance prediction based on this tire, performance prediction of the tire model was performed, and the prediction results and actual measurement results were shown together.

  The tire modeled and prototyped as this example has a tire size of 195 / 65R15, and the tread pattern has a structure without sipes.

  In the actually measured performance evaluation test, the above tire was assembled to a 6J-15 rim at an internal pressure of 200 kPa and mounted on a passenger car, and various running tests were performed.

  FIG. 9A shows the tread pattern of the tire of the first example, and FIG. 9B shows the tread pattern of the tire of the second example. In Table 1 below, wet performance evaluation, on-snow performance evaluation, on-shelve performance evaluation, on-ice performance evaluation, dry performance evaluation, off-road performance evaluation, noise performance evaluation for the tires of the first and second examples, The result of vibration performance evaluation is shown.

(Wet performance evaluation)
In the hydroplaning performance test for wet performance evaluation, the tire was mounted on a passenger car and entered a pool with a water depth of 10 mm at a different speed, and the hydroplaning generation speed was evaluated by a test driver. The result is expressed as an index of the hydroplaning rate.

(Performance evaluation on snow)
The acceleration test on the snow was evaluated by the time (acceleration time) until the accelerator was fully opened from a stationary state and traveled 50 m. The result is expressed as an index of acceleration time.

(Performance evaluation on sherbet)
In the sherbet road surface running performance test, a sherbet with a moisture content of 95% was prepared on the asphalt road surface, entered the pool with a sherbet depth of 40 mm at different speeds, and the hydroplaning generation speed was evaluated by a test driver. The result is expressed as an index of the hydroplaning rate.

(Performance evaluation on ice)
The acceleration test on ice was evaluated by the time (acceleration time) until the accelerator was fully opened from a stationary state and traveled 50 m. The result is expressed as an index of acceleration time.

(Dry performance evaluation)
In the dry performance test, the feeling score by the test driver is expressed as an index.

(Off-road performance evaluation / Uneven road performance evaluation)
In the off-road acceleration performance test, the evaluation was performed based on the time (acceleration time) until the accelerator was fully opened from a stationary state on an unpaved ground and traveled 50 m. The result is expressed as an index of acceleration time.

(Noise performance evaluation)
In the noise performance test, a noise drum test was performed at a speed of 70 km / h, and the sound pressure spectrum (overall value at a frequency of 100 to 500 Hz) measured with a microphone located 1 m away from the tire center line at a height of 25 cm was used as an index. expressing.

(Vibration performance evaluation)
In the vibration performance test, the feeling score of the test driver when driving on the uneven road surface is expressed as an index.

  As can be seen from Table 1, all the performance test results have good exponential values. From this, it can be seen that the superiority or inferiority of the performance between the patterns is consistent between the performance evaluation by the actual vehicle test and the performance prediction result by the embodiment of the present invention. Therefore, the tire performance prediction according to the embodiment of the present invention is effective for the performance prediction of the design plan, and even when a plurality of tire performances are contradictory to the design plan change, the prediction technology is utilized to improve the efficiency. An optimal design plan can be created.

  That is, by using the performance prediction method according to the embodiment of the present invention, it is possible to replace a part of the tire development cycle of design / manufacturing / performance evaluation with numerical analysis. By utilizing this, the efficiency of tire development can be improved.

It is the schematic of the personal computer for implementing tire performance prediction concerning embodiment of this invention. It is a flowchart which shows the flow of a process of the program concerning this Embodiment and predicting several tire performance in the case of tire performance evaluation. It is a flowchart which shows the flow of a process of the program which estimates single tire performance. The tire model is shown in the course of creation. (A) is a tire cross-section model, (B) is an image of the tire cross-section model being developed in the circumferential direction, and (C) is a three-dimensional tire developed one round (360 degrees). It is a diagram which shows a model. (A) is a flowchart showing a flow of boundary condition setting processing at the time of rolling, and (B) is a flowchart showing a flow of boundary condition setting processing at the time of non-rolling. (A) is explanatory drawing for demonstrating the setting of the boundary condition at the time of rolling, (B) is explanatory drawing for demonstrating the setting of the boundary condition at the time of non-rolling. It is explanatory drawing of the contradiction of performance on ice and performance on snow. It is an image figure which shows the dynamic pressure distribution by a sherbet. It is an image figure which shows the tread pattern of an Example, (A) shows 1st Example, (B) shows 2nd Example.

Explanation of symbols

10 Keyboard 12 Computer body 14 CRT
20 Fluid model 30 Tire model FD Flexible disk (recording medium)

Claims (13)

A tire performance prediction method including the following steps.
(A) A tire comprising a pair of a tire model having a pattern shape that can be deformed by at least one of ground contact and rolling and a road surface model that is in contact with the tire model and models a road surface state A step of determining a plurality of performance prediction models.
(B) For each of a plurality of tire performance prediction models including road surface models having different road surface conditions, a step of obtaining a physical quantity generated in at least one of the tire model and the road surface model when the tire model is in contact with the road surface model.
(C) predicting each tire performance corresponding to each of the determined physical quantities.
(D) A ratio between each initial value of the plurality of tire performances and each value of the predicted plurality of tire performances is obtained, and a weight proportional to a difference between a predetermined target value of each tire performance and the initial value is set. A step of evaluating the tire performance from the evaluation criteria based on a plurality of predicted tire performances , using the weighted sum given to the ratio as an evaluation value and obtaining the evaluation value as an evaluation criterion. In the step (a), a road surface model that expresses a road surface state is defined including a fluid model that models a fluid in which at least a part of at least one of the tire and the road surface is in contact,
In the step (b), deformation calculation of the tire model is executed, flow calculation of the fluid model is executed, and a boundary surface between the tire model after the deformation calculation and the fluid model after the flow calculation is recognized and recognized. The boundary condition related to the boundary surface is given to the tire model and the fluid model, and the tire model and the fluid model after the boundary condition is given are calculated until the fluid model becomes a pseudo-fluid state by repeating the deformation calculation and the flow calculation. Let
The tire performance prediction method according to claim 1.   The tire performance prediction method according to claim 2, wherein the road surface model includes a fluid model in which a wet road surface is targeted as the road surface state and a liquid is modeled.   3. The tire performance prediction method according to claim 2, wherein the road surface model includes a snow model that models a snow road surface as the road surface state and models an elastic-plastic body or a plastic body as a fluid model. 4.   3. The tire performance prediction method according to claim 2, wherein the road surface model includes a sherbet model that models an elasto-plastic body containing liquid or a plastic body as a fluid model for the sherbet road surface as the road surface state. .   3. The tire performance prediction according to claim 2, wherein the road surface model includes an on-ice road surface model that is modeled by selecting a predetermined friction coefficient of the on-ice road surface as an object on the ice surface as the road surface state. Method.   The tire performance prediction according to claim 2, wherein the road surface model includes a dry road surface model that is modeled by selecting a predetermined dry road surface friction coefficient for a dry road surface as the road surface state. Method.   3. The road surface model includes a soil model obtained by modeling an elastoplastic body including soil or a plastic body as a fluid model, the soil surface representing an agricultural field or an unpaved land as the road surface state. The tire performance prediction method described in 1.   The tire performance prediction method according to claim 2, wherein the road surface model includes a noise analysis model in which a road surface including a gas in the vicinity where the tire contacts the road surface is modeled.   The tire performance prediction method according to claim 2, wherein the road surface model includes an uneven road surface modeled on an uneven road surface as the road surface state, and a road surface including unevenness is modeled. A pneumatic tire design method including the following steps.
(1) A tire having a pair of a tire model having a pattern shape that can be deformed by at least one of contact and rolling and a road surface model that is in contact with the tire model and models a road surface state A step of determining a plurality of performance prediction models.
(2) A step of obtaining a physical quantity generated in at least one of a tire model and a road surface model in a state where the tire model is in contact with the road surface model for each of a plurality of tire performance prediction models including road surface models having different road surface conditions.
(3) A step of predicting each of the tire performances corresponding to each of the obtained plurality of physical quantities.
(4) A ratio between each initial value of the plurality of tire performances and each value of the predicted plurality of tire performances is obtained, and a weight proportional to a difference between a predetermined target value of each tire performance and the initial value is set. A step of evaluating the tire performance from the evaluation criteria based on a plurality of predicted tire performances , using the weighted sum given to the ratio as an evaluation value and obtaining the evaluation value as an evaluation criterion.
(5) A step of correcting each tire model of the tire performance prediction model based on the evaluation result of the tire performance.
(6) for the tire performance prediction model by tire model described above modification, the evaluating step (2) to step (5), in order to become a target performance evaluation of the step (4) is predetermined Repeating until the value reaches the maximum or minimum value .
(7) A step of designing a tire based on a tire model obtained as a result of the calculation in step (6). A tire performance prediction program comprising the following steps for predicting tire performance by a computer.
(A) A tire comprising a pair of a tire model having a pattern shape that can be deformed by at least one of ground contact and rolling and a road surface model that is in contact with the tire model and models a road surface state A step of determining a plurality of performance prediction models.
(B) For each of a plurality of tire performance prediction models including road surface models having different road surface conditions, a step of obtaining a physical quantity generated in at least one of a tire model and a road surface model in a state where the tire model is in contact with the road surface model.
(C) Predicting each of the tire performances corresponding to each of the determined physical quantities.
(D) A ratio between each initial value of the plurality of tire performances and each value of the predicted plurality of tire performances is obtained, and a weight proportional to a difference between a predetermined target value of each tire performance and the initial value is set. A step of evaluating the tire performance from the evaluation criteria based on a plurality of predicted tire performances , using the weighted sum given to the ratio as an evaluation value and obtaining the evaluation value as an evaluation criterion. A recording medium recording a tire performance prediction program for predicting tire performance by a computer, the recording medium recording a tire performance prediction program characterized by including the following steps.
(I) A tire comprising a pair of a tire model having a pattern shape that can be deformed by at least one of contact with the ground and rolling, and a road surface model that is in contact with the tire model and models a road surface state A step of determining a plurality of performance prediction models.
(B) obtaining a physical quantity generated in at least one of a tire model and a road surface model in a state where the tire model is in contact with the road surface model, for each of a plurality of tire performance prediction models including road surface models having different road surface conditions;
(Ha) predicting each of the tire performances corresponding to each of the determined physical quantities.
( Ii ) A ratio between each initial value of the plurality of tire performances and each predicted value of the plurality of tire performances is obtained, and a weight proportional to a difference between a predetermined target value of each tire performance and the initial value is determined. A step of evaluating the tire performance from the evaluation criteria based on a plurality of predicted tire performances , using the weighted sum given to the ratio as an evaluation value and obtaining the evaluation value as an evaluation criterion.