Pressure pad calibration method based on simulated tire lip pressure distribution

Abstract

The present application relates to the technical field of tire test research, and particularly relates to a pressure piece calibration method based on simulation of tire lip pressure distribution. The method comprises the following steps: S1, setting the pressure piece on a calibration structure, and calibrating the pressure piece through the calibration structure; S2, placing a pressure calibration block on the pressure piece, and applying loads to the pressure calibration block multiple times through a standard pressure machine; S3, calculating the contact area S between the pressure piece and the pressure calibration block when each load is applied, and calculating the original electric signal Rawsum corresponding to the contact area S, and performing multiple variable regression analysis based on the load, the contact area S and the original electric signal Rawsum. The pressure calibration block provided by the present application is made of a tire sub-port rubber block, the contact area changes with the increase of pressure, and the change trend is close to the actual stress condition of the tire sub-port, and the calibration regression equation obtained is more accurate.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of tire test research, and particularly relates to a pressure piece calibration method based on simulation of tire lip pressure distribution. BACKGROUND

[0002] The tire lip, also known as a bead, refers to a part of a tire in contact with two side wings of a rim of a wheel hub after the tire and the wheel hub are assembled. The tire lip needs to withstand the stretching force caused by the internal pressure and overcome the lateral force suffered by the tire during the steering of the automobile, so that the bead will not slide out of the two side wings of the rim. Therefore, the tire lip should have high strength, impact resistance and bending resistance.

[0003] At present, there are two methods for calibrating the pressure piece used for the tire lip: one is to use the direct pressure method, which does not calibrate the pressure piece, directly tests the pressure, obtains the original electric signal, and compares the electric signals; and the other is to use a fixed area calibration block to calibrate and obtain a fitting formula. In the first method, only the original electric signals can be compared horizontally, and the real pressure and pressure intensity of the object under test cannot be obtained. In the second method, the value of the measured area S is a fixed value, and the fitting formula is obtained through the formula P=N / S. However, in the more practical tire lip pressure distribution situation, the measured area S should be a variable. Therefore, there is a large error between the measured pressure P obtained from the fitting formula and the actual pressure value.

[0004] Therefore, how to provide a pressure piece calibration method based on simulation of tire lip pressure distribution is a technical problem urgently to be solved by those skilled in the art. SUMMARY

[0005] The purpose of the present application is to provide a pressure piece calibration method based on simulation of tire lip pressure distribution. The pressure calibration block provided by the present application tests the tire lip pressure distribution based on the applied load, and obtains a calibration regression equation. The pressure calibration block of the present application is made of a tire bead, and the contact area changes with the increase of the pressure, and the change trend is close to the actual stress condition of the tire bead. The calibration regression equation obtained is more accurate.

[0006] Compared with the direct pressure method, the pressure piece is arranged on the calibration structure in the present application, and the pressure piece is calibrated by the calibration structure, so that the real pressure and pressure intensity of the object under test can be effectively obtained, and the accuracy of the detection result is improved. Compared with the method of using a fixed area calibration block to calibrate and obtain a fitting formula, the pressure calibration block is used to perform multiple variable regression analysis based on parameters such as load and deformation contact area, and a calibration regression equation is obtained. The pressure distribution of the tire lip is accurately obtained based on the calibration regression equation.

[0007] In order to achieve the above purpose, the present application provides the following technical solutions:

[0008] A pressure piece calibration method based on simulation of tire bead pressure distribution, comprising:

[0009] Step S1: setting the pressure piece on the calibration structure, and calibrating the pressure piece through the calibration structure;

[0010] Step S2: placing the pressure calibration block on the pressure piece, and applying multiple loads Load to the pressure calibration block through the standard press;

[0011] Step S3: calculating the contact area S between the pressure piece and the pressure calibration block when each load is applied, and calculating the original electric signal Rawsum corresponding to the contact area S, and performing multiple variable regression analysis based on the load Load, the contact area S and the original electric signal Rawsum.

[0012] In some embodiments of the present application, the pressure calibration block is made of a rubber block at the tire bead, the contact area S between the pressure calibration block and the pressure piece changes based on the increase of the multiple loads Load applied to the pressure calibration block by the standard press, and the change trend of the contact area S is close to the actual stress condition of the tire bead.

[0013] In some embodiments of the present application, further comprising:

[0014] In step S3, the contact area S between the pressure piece and the pressure calibration block when each load is applied is detected and calculated in real time by the control unit;

[0015] A preset contact area matrix T0 between the pressure piece and the pressure calibration block and a preset load matrix A are set in the control unit, for the preset load matrix A, set A(A1, A2, A3, A4), wherein A1 is the first preset load, A2 is the second preset load, A3 is the third preset load, and A4 is the fourth preset load, and Load0

[0016] For the preset contact area matrix T0 between the pressure piece and the pressure calibration block, set T0(T01, T02, T03, T04), wherein T01 is the first preset contact area between the pressure piece and the pressure calibration block, T02 is the second preset contact area between the pressure piece and the pressure calibration block, T03 is the third preset contact area between the pressure piece and the pressure calibration block, and T04 is the fourth preset contact area between the pressure piece and the pressure calibration block, and T01

[0017] The control unit is configured to select a corresponding load as the load applied by the standard press to the pressure calibration block in the next time according to a relationship between S and a contact area matrix T0 between the preset pressure sheet and the pressure calibration block;

[0018] When S < T01, a fourth preset load A4 is selected as the load applied by the standard press to the pressure calibration block in the next time;

[0019] When T01≤S < T02, a third preset load A3 is selected as the load applied by the standard press to the pressure calibration block in the next time;

[0020] When T02≤S < T03, a second preset load A2 is selected as the load applied by the standard press to the pressure calibration block in the next time;

[0021] When T03≤S < T04, a first preset load A1 is selected as the load applied by the standard press to the pressure calibration block in the next time.

[0022] In some embodiments of the present application, in step S3, a multivariate regression analysis is performed based on the load Load, the contact area S and the original electrical signal Rawsum, including:

[0023] A parameter model containing a plurality of explanatory variables based on the tire lip is obtained, and the plurality of explanatory variables are independent of each other;

[0024] The plurality of explanatory variables are respectively converted by a preset function to obtain a plurality of converted explanatory variables;

[0025] The plurality of converted explanatory variables are randomly combined according to the parameter model to obtain a plurality of candidate linear regression formulas;

[0026] The plurality of candidate linear regression formulas are respectively subjected to linear regression analysis to determine the regression formula of the tire lip.

[0027] In some embodiments of the present application, the plurality of candidate linear regression formulas are respectively subjected to linear regression analysis to determine the regression formula of the tire lip, including:

[0028] The plurality of candidate linear regression formulas are respectively subjected to linear regression analysis by a linear regression function in R language to determine the regression formula of the tire lip;

[0029] The candidate linear regression formula includes a plurality of parameter regression terms based on the tire lip.

[0030] In some embodiments of the present application, the plurality of candidate linear regression formulas are respectively subjected to linear regression analysis by the linear regression function in R language to determine the regression formula of the tire lip, including:

[0031] estimate a coefficient corresponding to a parameter regression term of the tire lip based on a linear regression function of R language;

[0032] based on the estimation result, a T test is used to determine the regression formula of the tire lip, and a calibration regression equation is obtained.

[0033] In some embodiments of the present application, the calibration regression equation is: Load=A*Rawsum+B*S+C.

[0034] Wherein, Load is the applied load, Rawsum is the original electrical signal, and S is the contact area between the pressure pad and the pressure calibration block.

[0035] In some embodiments of the present application, based on the estimation result, a T test is used to determine the regression formula of the tire lip, comprising:

[0036] Based on the estimation result, a T test is performed on the plurality of candidate linear regression formulas to obtain a T test result;

[0037] Remove the parameter regression term based on the tire lip in the T test result with a P value greater than 0.01 in the plurality of candidate linear regression formulas;

[0038] Calculate the average value of T in the T test result of the remaining parameter regression term based on the tire lip in each candidate linear regression formula;

[0039] The largest estimation result corresponding to the average value of T is fitted to obtain the target regression formula.

[0040] In some embodiments of the present application, the linear regression function of R language includes any one of the lm function and the glm function of R language.

[0041] The present application provides a pressure pad calibration method based on simulated tire lip pressure distribution, which has the beneficial effects compared with the prior art:

[0042] The present application sets the pressure pad on the calibration structure, calibrates the pressure pad through the calibration structure, places the pressure calibration block on the pressure pad, and applies load to the pressure calibration block multiple times through the standard pressure machine. The contact area between the pressure pad and the pressure calibration block when each load is applied is calculated, and the original electrical signal corresponding to the contact area is calculated. Based on the load, the contact area and the original electrical signal, multiple variable regression analysis is performed to obtain a calibration regression equation. Based on the calibration regression equation, the pressure distribution of the tire lip is obtained. The pressure distribution of the tire lip obtained by the method has very high accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1is a flow chart of a pressure piece calibration method based on analog tire lip pressure distribution of the present application;

[0044] Figure 2 is a schematic diagram of calibrating a pressure piece by a calibration structure of the present application;

[0045] Figure 3 is a physical diagram of a pressure calibration block of the present application;

[0046] Figure 4 is a schematic diagram of applying a load to the pressure calibration block by a standard press of the present application;

[0047] Figure 5 is a structural schematic diagram of the pressure calibration block of the present application. DETAILED DESCRIPTION

[0048] The specific embodiments of the present application will be further described in conjunction with the drawings and examples. The following examples are used to illustrate the present application, but are not used to limit the scope of the present application.

[0049] In the description of the present application, it should be understood that the terms "center", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only used to facilitate the description of the present application and simplify the description, and therefore cannot be understood as indicating or implying that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application.

[0050] The terms "first", "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the technical features indicated. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the present application, unless otherwise specified, the meaning of "a plurality of" is two or more.

[0051] In the description of the present application, it should be noted that, unless otherwise specified and limited, the terms "mounting", "connecting", "connection" should be understood broadly, for example, it can be fixedly connected, or detachably connected, or integrally connected; it can be mechanically connected, or electrically connected; it can be directly connected, or indirectly connected through an intermediate medium, or it can be the communication between the inside of two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0052] The calibration method of the pressure sheet used for the tire lip in the prior art has the following two methods: one is to use the direct pressure method, which does not calibrate the pressure sheet, directly tests the pressure, obtains the original electric signal, and compares the electric signals; the other is to use the fixed area calibration block to calibrate, and obtain the fitting formula; however, the method one can only compare the original electric signals horizontally, and cannot obtain the real pressure and pressure of the object to be pressed; the method two can obtain the fitting formula through the formula P=N / S, but the area S is fixed, and in the actual tire lip pressure distribution test process, the area is a variable, and the fitting formula has large errors and the like.

[0053] Therefore, the present application provides a pressure sheet calibration method based on simulated tire lip pressure distribution, the present application tests the tire lip pressure distribution based on the applied load through the provided pressure calibration block, and obtains the calibration regression equation, the pressure calibration block of the present application is made through the rubber block at the tire bead, the contact area changes with the increase of the pressure, and the change trend is close to the actual stress condition of the tire bead, and the calibration regression equation obtained is more accurate.

[0054] Referring to Figure 1 The disclosed embodiments of the present application provide a pressure sheet calibration method based on simulated tire lip pressure distribution, which comprises:

[0055] Step S1: setting the pressure sheet on the calibration structure, and calibrating the pressure sheet through the calibration structure;

[0056] Step S2: placing the pressure calibration block on the pressure sheet, and applying multiple loads Load to the pressure calibration block through the standard pressure machine;

[0057] Step S3: calculating the contact area S between the pressure sheet and the pressure calibration block when each load is applied, and calculating the original electric signal Rawsum corresponding to the contact area S, and performing multiple variable regression analysis based on the load Load, the contact area S and the original electric signal Rawsum.

[0058] In a specific embodiment of the present application, the pressure calibration block is made through the rubber block at the tire bead, the contact area S between the pressure calibration block and the pressure sheet changes based on the increase of the multiple loads Load applied to the pressure calibration block by the standard pressure machine, and the change trend of the contact area S is close to the actual stress condition of the tire bead.

[0059] In a specific embodiment of the present application, it further comprises:

[0060] In step S3, the control unit detects the contact area S between the pressure sheet and the pressure calibration block when each load is applied in real time;

[0061] The contact area matrix T0 between the preset pressure sheet and the pressure calibration block and the preset load matrix A are set in the control unit, and for the preset load matrix A, A (A1, A2, A3, A4) is set, wherein A1 is the first preset load, A2 is the second preset load, A3 is the third preset load, and A4 is the fourth preset load, and Load0

[0062] For the contact area matrix T0 between the preset pressure sheet and the pressure calibration block, T0 (T01, T02, T03, T04) is set, wherein T01 is the contact area between the first preset pressure sheet and the pressure calibration block, T02 is the contact area between the second preset pressure sheet and the pressure calibration block, T03 is the contact area between the third preset pressure sheet and the pressure calibration block, and T04 is the contact area between the fourth preset pressure sheet and the pressure calibration block, and T01

[0063] The control unit is configured to select a corresponding load as the load applied by the standard press to the pressure calibration block next time according to the relationship between S and the contact area matrix T0 between the preset pressure sheet and the pressure calibration block;

[0064] When S

[0065] When T01≤S

[0066] When T02≤S

[0067] When T03≤S

[0068] In an embodiment of the present application, in step S3, multiple variable regression analysis is performed based on the load Load, the contact area S and the original electric signal Rawsum, including:

[0069] A parameter model containing a plurality of explanatory variables based on the tire lip is obtained, and the plurality of explanatory variables are independent of each other;

[0070] The plurality of explanatory variables are respectively converted by a preset function to obtain a plurality of converted explanatory variables;

[0071] randomly combining the plurality of converted explanatory variables according to the parameter model to obtain a plurality of candidate linear regression formulas;

[0072] performing linear regression analysis on the plurality of candidate linear regression formulas respectively to determine the regression formula of the tire lip.

[0073] In an embodiment of the present application, performing linear regression analysis on the plurality of candidate linear regression formulas respectively to determine the regression formula of the tire lip includes:

[0074] performing linear regression analysis on the plurality of candidate linear regression formulas respectively to determine the regression formula of the tire lip by using a linear regression function in R language;

[0075] The candidate linear regression formula includes a plurality of parameter regression terms based on the tire lip.

[0076] In an embodiment of the present application, performing linear regression analysis on the plurality of candidate linear regression formulas respectively to determine the regression formula of the tire lip by using a linear regression function in R language includes:

[0077] estimating a coefficient corresponding to each of the plurality of parameter regression terms based on the tire lip in the plurality of candidate linear regression formulas by using the linear regression function in R language;

[0078] determining the regression formula of the tire lip based on the estimation result by using a T test, and obtaining a calibration regression equation.

[0079] In an embodiment of the present application, the calibration regression equation is Load=A*Rawsum+B*S+C.

[0080] wherein Load is the applied load, Rawsum is the original electrical signal, and S is the contact area between the pressure pad and the pressure calibration block.

[0081] In an embodiment of the present application, determining the regression formula of the tire lip based on the estimation result by using a T test includes:

[0082] performing a T test on the plurality of candidate linear regression formulas based on the estimation result to obtain a T test result;

[0083] removing, from the plurality of candidate linear regression formulas, a parameter regression term based on the tire lip whose P value in the T test result is greater than 0.01;

[0084] calculating an average value of T in the T test result of each of the remaining parameter regression terms based on the tire lip in each of the candidate linear regression formulas;

[0085] fitting the maximum estimation result corresponding to the average value of T to obtain a target regression formula.

[0086] In one embodiment of the present application, the linear regression function of the R language includes any one of the lm function and the glm function of the R language.

[0087] Referring to Figure 2 As shown, the pressure sheet is calibrated by the calibration structure, and the pressure sheet is placed on the calibration structure, so that the real pressure and pressure intensity of the object under pressure can be effectively obtained, and the accuracy of the detection result is improved.

[0088] Referring to Figure 3 As shown, it is a schematic diagram of the pressure calibration block, and the pressure calibration block is made by a rubber block at the tire sub-port, the contact area changes with the increase of pressure, and the change trend is close to the actual stress condition of the tire sub-port.

[0089] Referring to Figure 4 As shown, it is a schematic diagram of applying load to the pressure calibration block by a standard pressure machine.

[0090] Referring to Figure 5 As shown, the pressure calibration block provided by the present application is made by a rubber block at the tire sub-port, the contact area changes with the increase of pressure, and the change trend is close to the actual stress condition of the tire sub-port, so that the calibration regression equation is more accurate, and in the multiple variable regression analysis process, the determination parameters are as follows:

[0091] The parameter "Adjusted R Square" is 0.998657, which meets the requirement of "Adjusted R Square";

[0092] The "Significance F" in the variance analysis is 8.484*10 －20 , which is much smaller than the alternative hypothesis determination value 0.05, indicating that the variables "electric signal Rawsum" and "contact area S" are closely related to the load "test Load";

[0093] The variable regression coefficients are "electric signal Rawsum: -0.12126" and "contact area S: 0.029435", and the "P-value" values are "6.99599*10 －6 " and "4.73984*10 －14 " respectively, both of which are less than 0.05, so the two variables have a great influence on the load "test Load".

[0094] The above parameter determination meets the requirements, indicating that the pressure calibration block and the calibration method of the present application can meet the calibration requirements, and the calibration regression equation can be used as a standardized equation, and the pressure distribution test of the tire lip has very high accuracy.

[0095] According to the first concept of the present application, the present application can effectively obtain the real pressure and pressure intensity of the object to be pressed by setting the pressure sheet on the calibration structure and calibrating the pressure sheet by the calibration structure, and improve the accuracy of the detection result.

[0096] According to the second concept of the present application, the present application can accurately obtain the pressure distribution of the tire lip based on the calibration regression equation by using the pressure calibration block, performing multiple variable regression analysis based on the load, deformation contact area and other parameters, and obtaining the calibration regression equation.

[0097] Multiple regression analysis refers to a statistical analysis method in which one variable is regarded as a dependent variable and one or more variables are regarded as independent variables in related variables, a linear or nonlinear mathematical model quantity relationship between multiple variables is established, and sample data is analyzed. The present application can effectively obtain the real pressure and pressure intensity of the object to be pressed by setting the pressure sheet on the calibration structure and calibrating the pressure sheet by the calibration structure, and improve the accuracy of the detection result.

[0098] The above description is only one embodiment of the present application, but cannot limit the scope of the present application. Any structural changes made according to the present application, as long as the essence of the present application is not lost, should be considered to fall within the scope of the present application.

[0099] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process and related description of the system described above can refer to the corresponding process in the foregoing method embodiment, which will not be described here.

[0100] It should be noted that the system provided in the above embodiments is only exemplified by the division of the above functional modules. In actual application, the above functions can be completed by different functional modules according to needs, that is, the modules or steps in the embodiments of the present application can be further divided or combined, for example, the modules in the above embodiments can be combined into one module, or can be further divided into multiple sub-modules to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of the present application are only for distinguishing the modules and steps, and should not be considered as an improper limitation of the present application.

[0101] Those skilled in the art should clearly understand that the modules and method steps of each example described in combination with the embodiments disclosed herein can be realized by electronic hardware, computer software or a combination of both. The programs corresponding to the software modules and method steps can be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. In order to clearly illustrate the interchangeability of electronic hardware and software, the components and steps of each example have been described in the above description in general terms. Whether the functions are performed by electronic hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0102] The term "comprising" or any other similar word is intended to encompass a non-exclusive inclusion, so that a process, method, article, or equipment / device including a series of elements includes not only those elements, but also other elements not explicitly listed, or inherent to the process, method, article, or equipment / device.

[0103] So far, the technical solution of the present application has been described in combination with the preferred embodiments shown in the drawings, but those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to the related technical features without departing from the principles of the present application, and the technical solutions after such changes or replacements will all fall within the protection scope of the present application.

[0104] The above description is only for the preferred embodiments of the present application and is not intended to limit the protection scope of the present application.

Claims

1. A pressure plate calibration method based on simulated tire bead pressure distribution, characterized in that, The method comprises the following steps: S1: placing the pressure sheet on a calibration structure to calibrate the pressure sheet by the calibration structure; S2: placing a pressure calibration block on the pressure sheet and applying loads to the pressure calibration block by a standard pressure machine for multiple times; S3: calculating the contact area S between the pressure sheet and the pressure calibration block when each load is applied and calculating the original electric signal Rawsum corresponding to the contact area S, and performing multiple variable regression analysis based on the load Load, the contact area S and the original electric signal Rawsum; The pressure calibration block is made of a rubber block at a tire bead, the contact area S between the pressure calibration block and the pressure sheet changes based on the increase of the loads applied to the pressure calibration block by the standard pressure machine for multiple times, and the change trend of the contact area S is close to the actual stress condition of the tire bead.

2. A method of calibrating pressure strips based on simulated tire lip pressure distribution as claimed in claim 1, wherein, The method further comprises the following steps: In the step S3, the contact area S between the pressure sheet and the pressure calibration block when each load is applied is detected and calculated in real time by a control unit; A preset contact area matrix T0 between the pressure sheet and the pressure calibration block and a preset load matrix A are set in the control unit, for the preset load matrix A, A(A1, A2, A3, A4) is set, wherein A1 is a first preset load, A2 is a second preset load, A3 is a third preset load, A4 is a fourth preset load, and Load0 For the preset contact area matrix T0 between the pressure sheet and the pressure calibration block, T0(T01, T02, T03, T04) is set, wherein T01 is a first preset contact area between the pressure sheet and the pressure calibration block, T02 is a second preset contact area between the pressure sheet and the pressure calibration block, T03 is a third preset contact area between the pressure sheet and the pressure calibration block, T04 is a fourth preset contact area between the pressure sheet and the pressure calibration block, and T01 The control unit is used to select a corresponding load as the load applied to the pressure calibration block by the standard pressure machine next time according to the relationship between S and the preset contact area matrix T0 between the pressure sheet and the pressure calibration block; When S When T01≤S When T02≤S When T03≤S 3. A method of calibrating pressure strips based on simulated tire lip pressure distribution as claimed in claim 1, wherein, In the step S3, a multivariate regression analysis is performed based on the load Load, the contact area S and the original electrical signal Rawsum, comprising: obtaining a parameter model containing a plurality of explanatory variables based on the tire lip, and the plurality of explanatory variables are independent of each other; transforming a plurality of the explanatory variables by a preset function respectively to obtain a plurality of transformed explanatory variables; randomly combining a plurality of the transformed explanatory variables according to the parameter model to obtain a plurality of candidate linear regression formulas; performing linear regression analysis on a plurality of the candidate linear regression formulas respectively to determine the regression formula of the tire lip.

4. A method of calibrating pressure strips based on simulated tire lip pressure distribution as claimed in claim 3, wherein, performing linear regression analysis on a plurality of the candidate linear regression formulas respectively to determine the regression formula of the tire lip, comprising: performing linear regression analysis on a plurality of the candidate linear regression formulas respectively by a linear regression function in R language to determine the regression formula of the tire lip; the candidate linear regression formula includes a plurality of parameter regression terms based on the tire lip.

5. A method of calibrating pressure strips based on simulated tire lip pressure distribution as claimed in claim 4, wherein, the performing linear regression analysis on a plurality of the candidate linear regression formulas respectively by a linear regression function in R language to determine the regression formula of the tire lip, comprising: estimating the coefficient corresponding to each parameter regression term based on the tire lip in a plurality of the candidate linear regression formulas by a linear regression function in R language; based on the estimation result, using T test to determine the regression formula of the tire lip, and obtaining a calibration regression equation.

6. The pressure pad calibration method based on the simulation of the pressure distribution of the tire lip according to claim 5, characterized in that, the calibration regression equation is: Load=A*Rawsum+B*S+C; wherein Load is the applied load, Rawsum is the original electrical signal, and S is the contact area between the pressure pad and the pressure calibration block.

7. A method of calibrating a pressure strip based on simulated tire lip pressure distribution according to claim 5, wherein, based on the estimation result, using T test to determine the regression formula of the tire lip, comprising: based on the estimation result, performing T test on a plurality of the candidate linear regression formulas to obtain a T test result; removing the parameter regression term based on the tire lip in the T test result with a P value greater than 0.01 in a plurality of the candidate linear regression formulas; calculating the average value of T in the T test result of the remaining parameter regression term based on the tire lip in each of the candidate linear regression formulas; fitting the maximum estimation result corresponding to the average value of T to obtain a target regression formula.

8. The pressure pad calibration method based on the simulation of the pressure distribution of the tire lip according to claim 4, characterized in that, the linear regression function in R language includes any one of the lm function and the glm function in R language.

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