CN112084682A - TBR tire noise testing method and low-noise tire preparation - Google Patents
TBR tire noise testing method and low-noise tire preparation Download PDFInfo
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- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M17/00—Testing of vehicles
- G01M17/007—Wheeled or endless-tracked vehicles
- G01M17/02—Tyres
- G01M17/025—Tyres using infrasonic, sonic or ultrasonic vibrations
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Abstract
The invention discloses a method for detecting the noise of an all-steel radial (TBR) tire and a low-noise tire prepared by the method. A tire noise flow-solid coupling simulation method is adopted, weighting is carried out by combining a point sound source model base and a line sound source model base to establish a tire noise mixed propagation model related to propagation distance, the noise sound pressure level of a TBR tire near-far field measuring point is calculated, parameters are calibrated, acceleration and uniform rotation of the tire are simulated through a computer, and information of the tire is extracted, wherein the information comprises grid information and node information. The result shows that in the range of 1-8m, the influence of the height of the measuring point on the measuring result is small, the influence of the distance of the measuring point on the measuring result is large, the transmission rule goodness fit between the method and the simulation measuring point is high, the errors of the prediction result are all lower than 0.85dB (A), and the average error is 7.55%. According to the simulation working condition, designing a semi-anechoic chamber drum noise transmission test of 4 types of different tires, and comparing the test result with the detection method disclosed by the invention, the tire noise flow-solid coupling simulation analysis method can accurately simulate the tire noise rule, and the maximum error of a measuring point is less than 10%.
Description
Technical Field
The invention belongs to the field of noise propagation simulation detection, and particularly relates to noise detection of an all-steel radial (TBR) tire, and a low-noise tire prepared by using the noise detection.
Background
The tire noise is one of the main noise sources of the automobile noise, the TBR tire has the characteristics of high tire pressure, heavy load and large impact, the noise pollution is particularly serious, the existing tire noise test comprises an indoor test and an outdoor test, the outdoor test acceptance site environment influence is large, and the cost is high and the precision is low; the indoor test condition has high dependency, and the judgment of near-far field noise combination is lacked, so that the far field noise value cannot be accurately predicted. For tire noise propagation performance, existing research includes virtual prediction using a boundary element method by analyzing tire vibration and noise propagation; the contribution of tread parameters, road surface access phase, and the like to noise was studied (document 1), but the test conditions were highly required, the implementation process was complicated, and there was no good correlation. In the face of tire noise limit regulations successively issued by countries in the world, particularly noise limit requirements of European Union label law, how to reduce the dependence of tire noise detection on tests and relate near far field noise needs a low-cost high-precision detection method, and a low-noise TBR tire is prepared on the basis, so that the quality and the production benefit of the tire product are improved.
Disclosure of Invention
The invention aims to provide a tire noise near-far field hybrid propagation model for detecting tire noise, and the method is accurate and efficient, has low dependence on test conditions, can simulate near-far field noise propagation within a limited distance, and has higher industrial application value.
According to the testing method, finite element analysis is firstly carried out on the tire, the tire is an all-steel radial tire, sound pressure levels of measuring points at different distances and different heights on the front side of the tire are respectively calculated by adopting tire noise flow-solid coupling simulation analysis, and the result shows that within the range of 1-8m, the influence of the height of the measuring point on the measuring result is small, the influence of the distance of the measuring point on the measuring result is large, and the propagation rule is not described by a common point sound source or a line sound source. And simulating the acceleration and the uniform rotation of the tire by the computer, and extracting the information of the tire, wherein the information comprises grid information and node information. Extracting pressure fluctuation data after the flow-solid coupling simulation, introducing the pressure fluctuation data into a Virtual Lab and setting the pressure fluctuation data as a dipole source, wherein the rolling tire continuously generates thrust to fluid to cause the speed of a fluid mass point to be continuously changed, so that the fluid around the tire vibrates to generate sound waves, an automatic matching layer technology in the Virtual Lab is adopted, an envelope surface grid is arranged outside a tire structure grid and defined as an acoustic grid, and a propagation medium and corresponding material properties are set.
In the invention, the complexity of a tire noise sounding mechanism is considered, the key parameters are calibrated through the detection of a mixed propagation model, and the predicted result and the measurement result of a laboratory drum transmission method are compared and analyzed, so that the analysis shows that: the propagation rule matching degree between the TBR tire noise mixed propagation model and the simulation measuring points is high, the errors of prediction results are all lower than 0.85dB, the average error is 7.55%, and the maximum prediction error of the ideal point sound source and line sound source model on the tire noise propagation rule is close to 50%. In order to further verify the effectiveness of a TBR tire noise mixed propagation measurement model, a semi-anechoic chamber drum noise test of a tire is designed according to simulation working condition conditions, and the result shows that the tire noise flow-solid coupling simulation analysis method accurately simulates the propagation rule of tire noise, the detection method is effective and accurate in result, well establishes the correlation of near-far field noise of the tire, and has a great engineering application value. According to the detection result, the pattern, the material and the like of the tire are improved, and the TBR tire with lower noise is prepared.
Drawings
FIG. 1 is an axisymmetric finite element model.
FIG. 2 is a tire wall model extracted from a database of results of computer Abaque software analysis.
Fig. 3 is a tire structure grid with an envelope grid disposed outside the tire structure grid, defined as an acoustic grid.
Fig. 4 is a field point grid arrangement provided in the tire positive side direction.
FIG. 5 is a sound pressure level curve of a simulation test point under the condition that the rolling speed of a TBR tire is 70 km/h.
FIG. 6 is a comparison of simulation and model predicted noise attenuation values.
FIG. 7 is a TBR test tire of the same gauge with a different pattern.
FIG. 8 is a test sensor layout, in which (a) is a structural layout and (b) is a test site.
FIG. 9 is a comparison of noise attenuation values for a TBR tire noise mixture propagation model test and a semi-anechoic indoor noise test.
Detailed Description
Firstly, establishing a point sound source model and a line sound source model, assuming that the radius of the point sound source is a, if the propagation medium of noise only considers the influence of air, solving a sound field by using a wave equation of sound waves in a fluid medium, wherein a Laplace operator in the wave equation of the sound waves adopts a spherical coordinate form, the wave equation is changed into the spherical coordinate form, all points on the surface of a spherical source vibrate in the same amplitude and the same phase along the radial direction, the vibration speed of the surface of the spherical source is irrelevant to polar angle and azimuth angle, the sound field caused by the point sound source is centrosymmetric, the sound pressure in the sound field is a function of time and distance, r is the distance from a receiving point to the center of the sound source, and P is the sound atAnd (6) pressing. In formula 1: 1 and 2 respectively denote two different measuring point positions, PrefThe reference sound pressure in the air is generally 2X 10-5Pa。
Formula 1:
the linear sound source is established based on a point sound source model and consists of countless incoherent point sound sources, in a free field radiation environment, the radiation sound energy of the linear sound source is uniformly distributed on a cylindrical surface taking the sound source as the center, the linear sound source model is supposed to be infinitely long, the sound wave meets the cylindrical surface divergence rule, the geometric attenuation rule formula is shown as formula 2, the propagation distance is doubled, and the sound pressure level is attenuated by 3dB (A).
Selecting a specification tire to perform finite element analysis, such as a certain brand 315/80R22.5 specification tire, establishing an axisymmetric finite element model, and as shown in fig. 1, completing the finite element analysis of radial vertical loading and static balancing processes in computer software, wherein the computer software can be an Abaqus/Standard solver, the inflation pressure can be 400-800KPa, preferably 600KPa, and the vertical preloading F is performedz26.75 KN; introducing the analysis result into computer (such as Abaqus/Standard solver) for simulating acceleration and uniform motion of tireThe speed can be selected to be 40-120km/h, preferably 70km/h, and the uniform rotation is ensured for 3 weeks or more until stable output data is obtained; as shown in fig. 2, the tire mesh information obtained from the Abaqus software analysis result database (ODB) file may be used to generate an IPN file, the IPN file is set as a wall boundary condition in an import software (e.g., FlowVision software), the unit mesh and node information on the fluid-solid coupling surface are extracted from the analysis result file, the unit information on the fluid-solid coupling surface is extracted and written into a computer software (e.g., a reboot file of Abaqus), and the analysis result of the external flow field simulation software is called to implement joint simulation. The calling external flow field Simulation software can use corresponding commands, such as a 'Co-Simulation' keyword.
The pressure fluctuation data after the flow-solid coupling simulation is extracted, and software can be introduced to be set as a dipole source, wherein the software includes but is not limited to Virtual Lab. The rolling tire continuously generates thrust to the fluid, so that the mass point speed of the fluid is continuously changed, and the fluid around the tire vibrates to generate sound waves. As shown in fig. 3, the auto-matching layer technique in Virtual Lab sets an envelope grid, defined as an acoustic grid, outside the tire structure grid, and sets a propagation medium and corresponding material properties. A plurality of sound field test points are arranged in the front side direction of the tire, the test points can be divided into two groups of equal-height test points and unequal-height test points, as shown in FIG. 4, 29 sound field test points are arranged in the front side direction of the tire, 15 equal-height test points are uniformly distributed on a central line on the front side of the tire, the horizontal distance interval of the test points is 0.5m, the height of the test points is 0.2m, the other test points are arranged with equal height difference of 0.055m, and sound pressure level data of all the field points are output.
Because the distance of a far-field test point of the current tire passing through the noise test regulation method is 7.5m, the invention selects data within 8m from the center, and a simulation result under the working condition that the rolling speed of a certain 315/80R22.5 specification TBR tire is 70km/h is shown in figure 5. The result shows that the influence of the height of the measuring point in the range of 1-8m on the noise measurement result of the TBR tire is small, so that the changes of the propagation rule along with the increase of the test distance in the same plane are mainly considered, the noise sound pressure levels of the tires at the positions of 2m, 4m and 8m in the plane are predicted by using a point sound source and a line sound source respectively on the basis of the noise simulation result at the position of 1m away from the tire, and the results are compared with the simulation result, and are shown in the table 1.
TABLE 1 comparison of predicted and simulated results for point and line sources
The equivalent distance is the horizontal projection of the distance from the measuring point to the center of the tire, and the measuring point P1 is taken as a reference point.
As can be seen from table 1, in a propagation distance of 8m, both an ideal line sound source and a point sound source model cannot predict a tire noise propagation rule well, the absolute value of a prediction error of the point sound source model decreases with the increase of the distance, and the prediction error of the line sound source model increases with the increase of the distance, that is, the characteristics of the line sound source are significant in a tire approach range, and the characteristics of the point sound source play a major role in a far field range. And constructing a TBR tire noise mixed propagation model based on the bounding property of the arctan function and the propagation characteristics of the point sound source and the linear sound source by integrating the weighted results of the point sound source and the linear sound source. As shown in formula 3
ΔLp＝α(r)ΔLps+β(r)ΔLp1 r1＞r2
Wherein Δ LPsPropagation attenuation value, DeltaLP, for ideal point source model1Propagation attenuation values of an ideal line sound source model are obtained; alpha is alpha(r)β(r)Weight coefficients for point and line sources, respectively, both as a function of propagation distance, and alpha(r)+β(r)＝1。
According to table 1, when the propagation distance is 8m, the prediction error of the point sound source model is close to 0, i.e. alpha(r)≈1，β(r)0 is approximately distributed; when the propagation distance is 2m, the prediction error of the linear sound source model is 0, namely alpha(r)≈0，β (r)1. Therefore, the function can be boundedBased on the (arctan function f (x) ═ arctan (x)), f (x) ∈ (-pi/2, pi/2), and using the above boundary condition to calibrate the key parameters in the model, and determining the weight function alpha under different propagation distances(r)And beta(r)As shown in formula 4:
formula 4:
where r is the distance from the center point of the calculated interval to the noise source, and is generally taken as (r ═ r)1+r2)/2。r1、r2Respectively the distance of the two measuring points to the noise source.
Combining the formula, the calculation formula of the mixed propagation detection of the noise of the TBR tire is deduced as shown in formula 5:
The noise propagation attenuation values of 15 simulation measurement points of the tire noise are predicted by adopting the formula, and the result is shown in table 2. Based on the data in table 2, a graph is drawn (as shown in fig. 6), and it can be seen from table 2 that the absolute error between the predicted value and the simulation result at the measured point is lower than 0.85db (a), and the average error is 7.55%. The result shows that the prediction result of the TBR tire noise hybrid propagation model is well matched with the simulation, and the model provides a quantitative method for the propagation rule of the TBR tire near-far field noise.
TABLE 2 comparison of measured Point Acoustic attenuation values of simulation results and model prediction results
Example (b):
in order to verify the accuracy of the TBR tire noise mixed propagation simulation detection method, an indoor rotary drum noise test is designed according to simulation conditions, the influence of pattern forms on the prediction result of a mixed propagation model is considered, four tires with the same specification and different patterns are selected as research objects in the test (as shown in figure 7), and the TBR tire noise mixed simulation detection result is compared with the noise test value of a semi-anechoic laboratory test rotary drum method.
The semi-anechoic indoor noise test can better control the test environment, the comparability of the test result is strong, and due to the limitation of indoor space, the positions of the test points in the test are only arranged at the positions with the distances of 1m, 2m and 4m from the center of the tire (as shown in figure 8)
Test results referring to Table 3, a graph of the difference between the simulated predicted value of the mixed noise propagation of the TBR tire and the test results is plotted (as shown in FIG. 9)
TABLE 3 test and model prediction of noise attenuation values
The units of the difference data in the table are Db (A), absolute error values are in parentheses below the tires, and average error percentages are in parentheses below the average errors. The method can be seen that the prediction curve and the test result curve have good consistency, the prediction errors are all lower than 0.85dB (A), the average error is 8.2%, and the accuracy of the detection method is further verified. The method can be effectively applied to the field of industrial manufacturing.
The drawings and examples are not to be construed as limiting the scope of the invention, which is intended to be covered by the claims and that various modifications and applications of the invention will be suggested to persons skilled in the art based on the description.
Claims (9)
1. A method for detecting all-steel radial tire noise is characterized in that finite element analysis is carried out on a tire, and a near-far field tire noise mixed propagation model constructed by a propagation distance is combined for detection.
2. The method of claim 1, wherein said detecting is a weighted propagation model of a synthetic point/line source constructed by calculating noise pressure level at near-far field survey points by tire noise flow-solid coupling simulation analysis method, as described by the following equation(r)ΔLPs+β(r)ΔLP1 r1>r2In the formula,. DELTA.LPsPropagation attenuation value, DeltaLP, for ideal point source model1Propagation attenuation values of an ideal line sound source model are obtained; alpha is alpha(r)、β(r)Are the weight coefficients of a point source and a line source, respectively, both as a function of the propagation distance, and alpha(r)+β(r)＝1。
3. A method as claimed in claim 2, wherein the information extracted from the tyre comprises mesh information and node information by computer simulation of tyre acceleration and constant rotation.
4. The method as claimed in claim 3, characterized in that the pressure fluctuation data after the flow-solid coupling simulation is extracted, introduced into a Virtual Lab and set as a dipole source, the rolling tire continuously generates thrust on the fluid to cause the speed of the fluid mass point to continuously change, so that the fluid around the tire vibrates to generate sound waves, an automatic matching layer technology in the Virtual Lab is adopted, an envelope surface grid is arranged outside the tire structure grid, defined as an acoustic grid, and a propagation medium and corresponding material properties are arranged.
5. The method of claim 2, wherein the sound field test points are arranged in a direction normal to the tire, uniformly distributed on a center line normal to the tire, and sound pressure level data is outputted for all the field points.
6. The method of claim 5, wherein the stations are spaced apart horizontally by 0.5m, have a height of 0.2m, or are arranged with a height difference of 0.055m, etc.
7. The method of claim 1, wherein the finite elements comprise radial vertical loading and static balancing processes.
8. The method of claim 5, wherein the inflation pressure is 600kpa, the velocity is 70km/h, and the vertical preload Fz is 26.75KN
9. A method for producing a low-noise tire, characterized in that a test is performed based on the detection method according to any one of claims 1 to 8, and a tire pattern is designed based on the test result to obtain the tire.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116579932A (en) * | 2023-03-29 | 2023-08-11 | 山东华勤橡胶科技有限公司 | Method and system for predicting and optimizing tire pattern noise |
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| JP2007230458A (en) * | 2006-03-02 | 2007-09-13 | Toyo Tire & Rubber Co Ltd | Method for simulating noise radiated from tire |
| US20100305746A1 (en) * | 2008-01-09 | 2010-12-02 | Masaki Shiraishi | Simulation method of noise performance of tire and method of producing tire |
| US20140019103A1 (en) * | 2012-07-11 | 2014-01-16 | Sumitomo Rubber Industries, Ltd. | Method for estimating noise performance of rolling tire |
| CN110059364A (en) * | 2019-03-26 | 2019-07-26 | 江苏大学 | A kind of tire cavity resonance noise Simulation test method |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007230458A (en) * | 2006-03-02 | 2007-09-13 | Toyo Tire & Rubber Co Ltd | Method for simulating noise radiated from tire |
| US20100305746A1 (en) * | 2008-01-09 | 2010-12-02 | Masaki Shiraishi | Simulation method of noise performance of tire and method of producing tire |
| US20140019103A1 (en) * | 2012-07-11 | 2014-01-16 | Sumitomo Rubber Industries, Ltd. | Method for estimating noise performance of rolling tire |
| CN110059364A (en) * | 2019-03-26 | 2019-07-26 | 江苏大学 | A kind of tire cavity resonance noise Simulation test method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116579932A (en) * | 2023-03-29 | 2023-08-11 | 山东华勤橡胶科技有限公司 | Method and system for predicting and optimizing tire pattern noise |
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