An air filter cartridge acoustic transmission loss simulation method, system, device and medium

Abstract

This invention discloses a method, system, device, and medium for simulating acoustic transmission loss of air filter cartridges, relating to the field of air filter cartridge simulation technology. The method includes: determining the flow resistance and porosity of the filter cartridge in a target air filter; and generating a filter cartridge simulation curve for the target air filter based on the flow resistance, porosity, and a porous media model with determined coefficient parameters. The method for determining the coefficient parameters in the porous media model includes: conducting acoustic transmission loss experiments on the filter cartridge in a test air filter to obtain an experimental curve; determining the flow resistance and porosity of the filter cartridge in the test air filter; and determining the coefficient parameters in the porous media model using a multi-iteration method based on the experimental curve, the flow resistance, and the porosity of the filter cartridge in the test air filter. This invention significantly improves the simulation efficiency of air filter cartridges.

Description

Technical Field

[0001] This invention relates to the field of air filter element simulation technology, and in particular to a method, system, device and medium for simulating acoustic transmission loss of air filter elements. Background Technology

[0002] Filter elements are porous media materials that significantly contribute to acoustic transmission loss, with the contribution primarily related to the filter paper material and filter element structure. In the early stages of vehicle development, it's necessary to simulate the transmission loss of the engine intake system to address engine noise by optimizing the system structure. The raw data from this simulation serves as the basis for later optimizations. Without filter element simulation, the simulated transmission loss curve of the intake system differs significantly from the experimental data, particularly in the frequency range above 500Hz. Therefore, calculating the acoustic transmission loss of the filter element is crucial for early-stage vehicle noise optimization.

[0003] In existing technologies, when designing filter elements of different volumes using the same media material, the noise reduction effect must be simulated after each filter element of a certain volume is designed. The noise reduction performance of the filter element of that volume is judged by observing the changes in frequency and amplitude in the simulation curve. However, every time the volume of the filter element is changed, the simulation parameters corresponding to the current volume must be obtained again. This repetitive operation greatly reduces the simulation efficiency of air filter elements. Summary of the Invention

[0004] The purpose of this invention is to provide a method, system, device, and medium for simulating acoustic transmission loss of air filter elements, which greatly improves the simulation efficiency of air filter elements.

[0005] To achieve the above objectives, the present invention provides the following solution:

[0006] In a first aspect, the present invention provides a method for simulating acoustic transmission loss of an air filter element, comprising:

[0007] Determine the flow resistance and porosity of the filter element in the target air filter;

[0008] Based on the flow resistance, porosity, and porous media model with determined coefficient parameters of the filter element in the target air filter, a filter element simulation curve for the target air filter is generated; the filter element simulation curve is used to characterize the noise reduction effect of the filter element in the target air filter.

[0009] The methods for determining the coefficient parameters in the porous media model include:

[0010] An acoustic transmission loss experiment was conducted on the filter element in the test air filter to obtain the filter element experimental curve; the filter element experimental curve is used to characterize the noise reduction effect of the filter element in the test air filter.

[0011] Determine the flow resistance and porosity of the filter element in the test air filter;

[0012] Based on the filter element experimental curve, the flow resistance and porosity of the filter element in the test air filter, the coefficient parameters in the porous media model are determined by multiple iterations. The coefficient parameters include: tortuosity, viscous characteristic length and thermal characteristic length; the thermal characteristic length is a set multiple of the viscous characteristic length.

[0013] The process of the nth iteration is as follows:

[0014] Determine the coefficient parameters for the nth iteration;

[0015] Based on the flow resistance ratio and porosity of the filter element in the test air filter, the coefficient parameters of the nth iteration, and the porous media model, the filter element simulation curve for the nth iteration is generated.

[0016] Calculate the amplitude difference between the filter element simulation curve and the filter element experimental curve in the nth iteration;

[0017] When the magnitude difference in the nth iteration is less than the first set value, the coefficient parameter of the nth iteration is determined as the final coefficient parameter;

[0018] When the amplitude difference of the nth iteration is greater than or equal to the first set value and less than the second set value, the viscous feature length in the coefficient parameter of the nth iteration is changed by the first set amplitude, and the changed coefficient parameter of the nth iteration is used as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration; or the tortuosity in the coefficient parameter of the nth iteration is changed by the second set amplitude, and the changed coefficient parameter of the nth iteration is used as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration.

[0019] When the amplitude difference of the nth iteration is greater than or equal to the second set value, the viscosity feature length in the coefficient parameter of the nth iteration is changed by a third set amplitude, and the changed coefficient parameter of the nth iteration is used as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration; the second set value is greater than the first set value.

[0020] Optionally, the filter element is made of folded media material;

[0021] An acoustic transmission loss experiment was conducted on the filter element in the test air filter to obtain the filter element experimental curve, which specifically includes:

[0022] Filter elements are classified according to a first condition and a second condition; the first condition is the type of media material; the second condition is the height of the filter element.

[0023] The sorted filter elements were then installed into the corresponding test air filters.

[0024] Acoustic transmission loss experiments were conducted on filter elements of different models of test air filters to obtain filter element test curves.

[0025] Optionally, acoustic transmission loss experiments are conducted on filter elements of different models of test air filters to obtain filter element test curves, specifically including:

[0026] Acoustic transmission loss tests were conducted on filter elements of different models of test air filters using the impedance tube method or the two-load method, and the filter element experimental curves were obtained.

[0027] Optionally, the flow resistance of the filter element in the target air filter is determined, specifically including:

[0028] Obtain the height, cross-sectional area, and fluid flow rate of the filter element in the target air filter;

[0029] The intake resistance of the engine intake system is simulated to obtain the flow resistance value of the filter element in the target air filter;

[0030] The flow resistance ratio of the filter element in the target air filter is calculated based on the flow resistance value, the height, the cross-sectional area, and the fluid flow rate.

[0031] Optionally, the formula for calculating the flow resistance of the filter element in the target air filter is:

[0032]

[0033] In the formula, δ is the flow resistance of the filter element in the target air filter, Δp is the flow resistance value of the filter element in the target air filter, h is the height of the filter element in the target air filter, S is the cross-sectional area of ​​the filter element in the target air filter, and Q is the fluid flow rate of the filter element in the target air filter.

[0034] Optionally, an intake resistance simulation is performed on the engine intake system to obtain the flow resistance value of the filter element in the target air filter, specifically including:

[0035] Create a three-dimensional model of the automobile engine intake system;

[0036] The three-dimensional model is meshed to obtain a mesh model of the automobile engine intake system;

[0037] The mesh model is imported into the flow resistance simulation software to obtain the flow resistance simulation results; the flow resistance simulation results include the flow resistance value of the filter element in the target air filter.

[0038] Optionally, the filter element is made of folded media material;

[0039] Determining the porosity of the filter element in the target air filter specifically includes:

[0040] A three-dimensional model of the filter element in the target air filter is created to obtain a filter element simulation model;

[0041] Measure the length, width, and height of the filter element simulation model, and calculate the volume of the filter element simulation model;

[0042] Measure the surface area and thickness of the medium material, and calculate the volume of the medium material;

[0043] Based on the volume of the filter element simulation model, the volume of the media material, and the formula for calculating the filter element porosity, the porosity of the filter element in the target air filter is obtained; the formula for calculating the filter element porosity is:

[0044]

[0045] In the formula, V represents the porosity of the filter element in the target air filter. LX V represents the volume of the filter element simulation model. LZ For the volume of the dielectric material, Porosity is the porosity of the medium material.

[0046] Secondly, the present invention provides an acoustic transmission loss simulation system for air filter cartridges, comprising:

[0047] The flow resistance and porosity acquisition module is used to determine the flow resistance and porosity of the filter element in the target air filter;

[0048] The filter element simulation curve generation module is used to generate a filter element simulation curve for the target air filter based on the flow resistance, porosity, and a porous media model with determined coefficient parameters. The filter element simulation curve is used to characterize the noise reduction effect of the filter element in the target air filter.

[0049] The methods for determining the coefficient parameters in the porous media model include:

[0050] An acoustic transmission loss experiment was conducted on the filter element in the test air filter to obtain the filter element experimental curve; the filter element experimental curve is used to characterize the noise reduction effect of the filter element in the test air filter.

[0051] Determine the flow resistance and porosity of the filter element in the test air filter;

[0052] Based on the filter element experimental curve, the flow resistance and porosity of the filter element in the test air filter, the coefficient parameters in the porous media model are determined by multiple iterations. The coefficient parameters include: tortuosity, viscous characteristic length and thermal characteristic length; the thermal characteristic length is a set multiple of the viscous characteristic length.

[0053] The process of the nth iteration is as follows:

[0054] Determine the coefficient parameters for the nth iteration;

[0055] Based on the flow resistance ratio and porosity of the filter element in the test air filter, the coefficient parameters of the nth iteration, and the porous media model, the filter element simulation curve for the nth iteration is generated.

[0056] Calculate the amplitude difference between the filter element simulation curve and the filter element experimental curve in the nth iteration;

[0057] When the magnitude difference in the nth iteration is less than the first set value, the coefficient parameter of the nth iteration is determined as the final coefficient parameter;

[0058] When the amplitude difference of the nth iteration is greater than or equal to the first set value and less than the second set value, the viscous feature length in the coefficient parameter of the nth iteration is changed by the first set amplitude, and the changed coefficient parameter of the nth iteration is used as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration; or the tortuosity in the coefficient parameter of the nth iteration is changed by the second set amplitude, and the changed coefficient parameter of the nth iteration is used as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration.

[0059] When the amplitude difference of the nth iteration is greater than or equal to the second set value, the viscosity feature length in the coefficient parameter of the nth iteration is changed by a third set amplitude, and the changed coefficient parameter of the nth iteration is used as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration; the second set value is greater than the first set value.

[0060] Thirdly, the present invention provides an electronic device, including a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to perform the air filter cartridge acoustic transmission loss simulation method described in the first aspect.

[0061] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the acoustic transmission loss simulation method for air filter cartridges as described in the first aspect.

[0062] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0063] This invention provides a method, system, device, and medium for simulating acoustic transmission loss of air filter cartridges. Based on the experimental curves of the filter cartridges, the flow resistance and porosity of the filter cartridges in the test air filter, a multi-iteration method is used to determine the coefficient parameters in the porous medium model. By calculating and comparing the amplitude differences between the simulated curves and the experimental curves, the amplitudes of the tortuosity, viscous characteristic length, and thermal characteristic length in the coefficient parameters are continuously adjusted until the amplitude difference in the nth iteration is less than a first set value. The coefficient parameters of the nth iteration are then determined as the final coefficient parameters. When simulating acoustic transmission loss of filter cartridges of other volumes, the coefficient parameters determined after multiple iterations can be directly input. Only the flow resistance and porosity corresponding to different volumes of filter cartridges need to be calculated to directly obtain the filter cartridge simulation curves, greatly improving the simulation efficiency of air filter cartridges. Attached Figure Description

[0064] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0065] Figure 1 A flowchart of the acoustic transmission loss simulation method for air filter cartridges provided in an embodiment of the present invention;

[0066] Figure 2 A flowchart illustrating the method for determining coefficient parameters in a porous media model provided in this embodiment of the invention;

[0067] Figure 3 This is a photograph of an air filter with a filter element installed, provided as an embodiment of the present invention.

[0068] Figure 4 This is a physical image of a filter element made of folded media material, provided as an embodiment of the present invention.

[0069] Figure 5 A flowchart illustrating the process of the nth iteration provided in this embodiment of the invention;

[0070] Figure 6 A comparison chart of the filter element simulation curve and the filter element experimental curve provided in the embodiments of the present invention;

[0071] Figure 7 A schematic diagram of the module structure of the air filter cartridge acoustic transmission loss simulation system provided in an embodiment of the present invention. Detailed Implementation

[0072] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0073] The purpose of this invention is to provide a method, system, device, and medium for simulating acoustic transmission loss of air filter elements, which greatly improves the simulation efficiency of air filter elements.

[0074] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0075] Example 1

[0076] This embodiment provides a method for simulating the acoustic transmission loss of an air filter element, such as... Figure 1 As shown, the method includes:

[0077] Step S1: Determine the flow resistance and porosity of the filter element in the target air filter.

[0078] Step S2: Based on the flow resistance, porosity, and porous media model of the filter element in the target air filter with determined coefficients, generate the filter element simulation curve for the target air filter. The filter element simulation curve characterizes the noise reduction effect of the filter element in the target air filter; the horizontal axis of the filter element simulation curve represents frequency, and the vertical axis represents amplitude.

[0079] In one example, the porous media model is of type Johnson-Champoux-Allard.

[0080] In this embodiment, determining the flow resistance of the filter element in the target air filter specifically includes:

[0081] Step S11: Obtain the height, cross-sectional area, and fluid flow rate of the filter element in the target air filter.

[0082] Step S12: Simulate the intake resistance of the engine intake system to obtain the flow resistance value of the filter element in the target air filter.

[0083] Step S12 further includes:

[0084] Step S121: Establish a three-dimensional model of the car engine intake system.

[0085] Step S122: Mesh the 3D model to obtain the mesh model of the car engine intake system.

[0086] Step S123: Import the mesh model into the flow resistance simulation software to obtain the flow resistance simulation results. The flow resistance simulation results include the flow resistance value of the filter element in the target air filter and the flow resistance values ​​of other components.

[0087] In one example, a typical automotive engine intake system includes: an intake manifold, an upper housing, a filter element, a lower housing, an exhaust manifold, and a measuring tube. The intake manifold connects to the lower housing, the exhaust manifold connects to the upper housing, the filter element is positioned between the upper and lower housings, and the measuring tube connects to the exhaust manifold. When simulating the mesh model of an automotive engine intake system, Computational Fluid Dynamics (CFD) is generally used for flow resistance simulation, and Computer-Aided Engineering (CAE) is used for acoustic simulation. The flow resistance values ​​of other components in the flow resistance simulation results include, but are not limited to, the flow resistance values ​​of the intake manifold, the upper housing, and the exhaust manifold.

[0088] Step S13: Calculate the flow resistance ratio of the filter element in the target air filter based on its flow resistance value, height, cross-sectional area, and fluid flow rate. The formula for calculating the flow resistance ratio of the filter element in the target air filter is as follows:

[0089]

[0090] In the formula, δ is the flow resistance of the filter element in the target air filter, Δp is the flow resistance value of the filter element in the target air filter, h is the height of the filter element in the target air filter, S is the cross-sectional area of ​​the filter element in the target air filter, and Q is the fluid flow rate of the filter element in the target air filter.

[0091] In this embodiment, determining the porosity of the filter element in the target air filter specifically includes:

[0092] Step S14: Perform three-dimensional modeling of the filter element in the target air filter to obtain the filter element simulation model.

[0093] Step S15: Measure the length, width, and height of the filter element simulation model and calculate its volume.

[0094] Step S16: Measure the surface area and thickness of the medium material, and calculate the volume of the medium material.

[0095] Step S17: Based on the volume of the filter element simulation model, the volume of the media material, and the formula for calculating the filter element porosity, obtain the porosity of the filter element in the target air filter. The formula for calculating the filter element porosity is as follows:

[0096]

[0097] In the formula, V represents the porosity of the filter element in the target air filter.LX V represents the volume of the filter element simulation model. LZ For the volume of the dielectric material, Porosity is the porosity of the medium material.

[0098] like Figure 2 As shown, in this embodiment, the method for determining the coefficient parameters in the porous media model includes:

[0099] Step S21: Conduct an acoustic transmission loss experiment on the filter element in the test air filter to obtain the filter element experimental curve. The filter element experimental curve characterizes the noise reduction effect of the filter element in the test air filter; the horizontal axis of the filter element experimental curve represents frequency, and the vertical axis represents amplitude.

[0100] Step S22: Determine the flow resistance and porosity of the filter element in the test air filter.

[0101] In one example, the method for calculating the flow resistance of the filter element in the test air filter is consistent with the method for calculating the flow resistance of the filter element in the target air filter described in steps S11-S13. The method for calculating the porosity of the filter element in the test air filter is consistent with the method for calculating the porosity of the filter element in the target air filter described in steps S14-S17.

[0102] Step S23: Based on the filter element experimental curve, the flow resistance of the filter element in the test air filter, and the porosity of the filter element in the test air filter, the coefficient parameters in the porous media model are determined using a multi-iteration method. These coefficient parameters include: tortuosity, viscous characteristic length, and thermal characteristic length.

[0103] In one example, the thermal feature length is twice the viscous feature length.

[0104] Figure 3 An air filter structure with a filter element installed is shown. Figure 4 This illustration shows a filter element structure made of folded media material. The media material is typically filter paper or nonwoven fabric.

[0105] See Figure 3 and Figure 4 The structure shown in this embodiment involves conducting an acoustic transmission loss experiment on the filter element in the test air filter to obtain the filter element experimental curve, specifically including:

[0106] Step S211: Classify the filter elements according to the first condition and the second condition. The first condition is the type of media material, and the second condition is the height of the filter element.

[0107] Step S212: Install the sorted filter elements into the corresponding test air filters.

[0108] Step S213: Conduct acoustic transmission loss experiments on filter elements of different models of test air filters to obtain filter element test curves.

[0109] In one example, the acoustic transmission loss of filter elements in different models of air filters is tested using either the impedance tube method or the two-load method, resulting in experimental curves for the filter elements. Before conducting the acoustic transmission loss test on the filter elements, the corresponding testing equipment needs to be connected. This equipment mainly includes: a data acquisition unit, a power amplifier, a loudspeaker, a generator tube, a test piece, a microphone, a sound insulation expansion tube, a sound-absorbing tube, and a computer. The experimental process includes: connecting the testing equipment; opening the testing equipment software and adjusting the test parameters according to the test sample (the main test parameters are the diameter of the impedance tube and the sensor spacing, as well as the frequency range to be tested, such as 20Hz-4000Hz); calibrating the sensors (equivalent to error calibration, determining whether the sensors are in the calibrated state); installing the test sample; acquiring the test data of the sample; and processing and exporting the test data.

[0110] like Figure 5 As shown, in this embodiment, the process of the nth iteration is as follows:

[0111] Step S231: Determine the coefficient parameters for the nth iteration.

[0112] In one example, the initial coefficient parameters in the porous media model are set as follows: tortuosity = 1.5, viscous feature length = 0.05, and thermal feature length = 2 × viscous feature length.

[0113] Step S232: Based on the flow resistance ratio of the filter element in the test air filter, the porosity of the filter element in the test air filter, the coefficient parameters of the nth iteration, and the porous media model, generate the filter element simulation curve for the nth iteration.

[0114] Step S233: Calculate the amplitude difference between the filter element simulation curve and the filter element experimental curve in the nth iteration.

[0115] In one example, such as Figure 6 As shown, the simulated curve and the experimental curve of the filter element are presented in the same image. The difference in amplitude is determined by comparing whether the two curves match. When the two curves do not match, the difference in amplitude can be obtained by subtracting the amplitude of the vertical axis of the simulated curve from that of the experimental curve.

[0116] Step S234: When the amplitude difference of the nth iteration is less than the first set value, the coefficient parameter of the nth iteration is determined as the final coefficient parameter.

[0117] In one example, the first setting is 1dB.

[0118] Step S235: When the amplitude difference of the nth iteration is greater than or equal to the first set value and less than the second set value, change the viscosity feature length in the coefficient parameter of the nth iteration by the first set amplitude, and use the changed coefficient parameter of the nth iteration as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration; or change the tortuosity in the coefficient parameter of the nth iteration by the second set amplitude, and use the changed coefficient parameter of the nth iteration as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration.

[0119] In one example, the second setting is 5dB, the first setting amplitude is 0.05, and the second setting amplitude is 0.5. Changing the viscous feature length by the first setting amplitude increases / decreases the viscous feature length by 0.05, and changing the tortuosity by the second setting amplitude increases / decreases the tortuosity by 0.5.

[0120] Step S236: When the amplitude difference of the nth iteration is greater than or equal to the second set value, change the viscous characteristic length in the coefficient parameter of the nth iteration by the third set amplitude, and use the changed coefficient parameter of the nth iteration as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration. The second set value is greater than the first set value.

[0121] In one example, the third set amplitude is 0.1, and changing the viscous feature length by the third set amplitude means increasing / decreasing the viscous feature length by 0.1.

[0122] Example 2

[0123] This embodiment provides a simulation system for acoustic transmission loss of air filter cartridges, such as... Figure 7 As shown, the system specifically includes:

[0124] The flow resistance and porosity acquisition module 201 is used to determine the flow resistance and porosity of the filter element in the target air filter.

[0125] The filter element simulation curve generation module 202 is used to generate the filter element simulation curve of the target air filter based on the flow resistance ratio, porosity and porous media model of the filter element in the target air filter with determined coefficient parameters; the filter element simulation curve is used to characterize the noise reduction effect of the filter element in the target air filter.

[0126] The methods for determining the coefficient parameters in the porous media model include:

[0127] An acoustic transmission loss experiment was conducted on the filter element in the test air filter to obtain the filter element experimental curve; the filter element experimental curve is used to characterize the noise reduction effect of the filter element in the test air filter.

[0128] Determine the flow resistance and porosity of the filter element in the test air filter.

[0129] Based on the filter element experimental curve, the flow resistance and porosity of the filter element in the test air filter, the coefficient parameters in the porous media model are determined by multiple iterations. The coefficient parameters include: tortuosity, viscous characteristic length and thermal characteristic length; the thermal characteristic length is a set multiple of the viscous characteristic length.

[0130] The process of the nth iteration is as follows:

[0131] Determine the coefficient parameters for the nth iteration.

[0132] Based on the flow resistance ratio and porosity of the filter element in the test air filter, the coefficient parameters of the nth iteration, and the porous media model, the filter element simulation curve for the nth iteration is generated.

[0133] Calculate the amplitude difference between the filter element simulation curve and the filter element experimental curve in the nth iteration.

[0134] When the magnitude difference in the nth iteration is less than the first set value, the coefficient parameter of the nth iteration is determined as the final coefficient parameter.

[0135] When the amplitude difference of the nth iteration is greater than or equal to the first set value and less than the second set value, the viscosity feature length in the coefficient parameter of the nth iteration is changed by the first set amplitude, and the changed coefficient parameter of the nth iteration is used as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration. Alternatively, the tortuosity in the coefficient parameter of the nth iteration is changed by the second set amplitude, and the changed coefficient parameter of the nth iteration is used as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration.

[0136] When the amplitude difference of the nth iteration is greater than or equal to the second set value, the viscosity feature length in the coefficient parameter of the nth iteration is changed by the third set amplitude, and the coefficient parameter after the nth iteration is used as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration; the second set value is greater than the first set value.

[0137] Example 3

[0138] This embodiment provides an electronic device, including a memory and a processor. The memory is used to store computer programs, and the processor runs the computer programs to enable the electronic device to execute the acoustic transmission loss simulation method of the air filter element corresponding to Embodiment 1.

[0139] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the acoustic transmission loss simulation method for an air filter element as described in Embodiment 1.

[0140] In summary, the iterative calculation and acquisition of coefficient parameters in the porous media model can provide relatively accurate simulation calculation data for noise optimization design in the early stage of intake system noise research and development. At the same time, it also solves the problem of difficulty in obtaining simulation parameters of acoustic transmission loss of air filter element, further reduces the difference between the simulation calculation results and experimental results of acoustic transmission loss of air filter element, and greatly improves the simulation efficiency of air filter element.

[0141] In reality, the simulation model of the filter element used in the simulation is an equivalent model (it fills the voids formed by the folding or winding of the filter paper; if the filter paper folds have equal length, width, and height, then its equivalent model is a cube). To make the simulation results close to the experimental results, the simulation parameters need to be accurate enough. However, the parameters of the actual filter paper do not correspond to the parameters of the simulation model. Therefore, the concept of equivalent transformation is needed to solve this problem. Now, let's assume that the model used in the simulation is material B. The acoustic performance of material B is equivalent to the acoustic performance of a filter element made of material A. However, material B is a three-dimensional structure, or a three-dimensional slice. Therefore, when using it, we only need to change its length in various spatial directions. Among the five parameters of the model, tortuosity, viscous characteristic length, and thermal characteristic length are mainly related to the structure of the material's micropores. For the same material, making filter elements of different shapes will not change its parameters, but it will change the flow resistance and porosity. Therefore, we only need to determine the flow resistance and porosity first, and then use simulation comparison experiments to lock the three parameters of material B: tortuosity, viscous characteristic length, and thermal characteristic length. This will make it easy to determine the simulation parameters for making filter elements of different shapes from material B later (we do not need to change the three parameters of material B: tortuosity, viscous characteristic length, and thermal characteristic length later). We only need to calculate the two parameters of flow resistance and porosity that change due to structural changes using formulas. In other words, we can use the parameters of material B and its simulation model to approximate the acoustic effect of the actual model of material A.

[0142] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0143] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for simulating acoustic transmission loss of an air filter element, characterized in that, include: Determine the flow resistance and porosity of the filter element in the target air filter; Based on the flow resistance, porosity, and porous media model with determined coefficient parameters of the filter element in the target air filter, the filter element simulation curve of the target air filter is generated. The filter element simulation curve is used to characterize the noise reduction effect of the filter element in the target air filter; The methods for determining the coefficient parameters in the porous media model include: An acoustic transmission loss experiment was conducted on the filter element in the test air filter to obtain the filter element experimental curve; the filter element experimental curve is used to characterize the noise reduction effect of the filter element in the test air filter. Determine the flow resistance and porosity of the filter element in the test air filter; Based on the filter element experimental curve, the flow resistance and porosity of the filter element in the test air filter, the coefficient parameters in the porous media model are determined by multiple iterations. The coefficient parameters include: tortuosity, viscous characteristic length and thermal characteristic length; the thermal characteristic length is a set multiple of the viscous characteristic length. The process of the nth iteration is as follows: Determine the coefficient parameters for the nth iteration; Based on the flow resistance ratio and porosity of the filter element in the test air filter, the coefficient parameters of the nth iteration, and the porous media model, the filter element simulation curve for the nth iteration is generated. Calculate the amplitude difference between the filter element simulation curve and the filter element experimental curve in the nth iteration; When the magnitude difference in the nth iteration is less than the first set value, the coefficient parameter of the nth iteration is determined as the final coefficient parameter; When the amplitude difference of the nth iteration is greater than or equal to the first set value and less than the second set value, the viscosity feature length in the coefficient parameter of the nth iteration is changed by the first set amplitude, and the changed coefficient parameter of the nth iteration is used as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration; or the tortuosity in the coefficient parameter of the nth iteration is changed by the second set amplitude, and the changed coefficient parameter of the nth iteration is used as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration. When the amplitude difference of the nth iteration is greater than or equal to the second set value, the viscosity feature length in the coefficient parameter of the nth iteration is changed by a third set amplitude, and the changed coefficient parameter of the nth iteration is used as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration; the second set value is greater than the first set value.

2. The method for simulating acoustic transmission loss of an air filter element according to claim 1, characterized in that, The filter element is made of folded media material; An acoustic transmission loss experiment was conducted on the filter element in the test air filter to obtain the filter element experimental curve, which specifically includes: Filter elements are classified according to a first condition and a second condition; the first condition is the type of media material; the second condition is the height of the filter element. The sorted filter elements were then installed into the corresponding test air filters. Acoustic transmission loss experiments were conducted on filter elements of different models of test air filters to obtain filter element experimental curves.

3. The method for simulating acoustic transmission loss of an air filter element according to claim 2, characterized in that, Acoustic transmission loss experiments were conducted on filter elements of different models of test air filters to obtain filter element experimental curves, specifically including: Acoustic transmission loss tests were conducted on filter elements of different models of test air filters using the impedance tube method or the two-load method, and the filter element experimental curves were obtained.

4. The method for simulating acoustic transmission loss of an air filter element according to claim 1, characterized in that, Determining the flow resistance of the filter element in the target air filter specifically includes: Obtain the height, cross-sectional area, and fluid flow rate of the filter element in the target air filter; The intake resistance of the engine intake system is simulated to obtain the flow resistance value of the filter element in the target air filter; The flow resistance ratio of the filter element in the target air filter is calculated based on the flow resistance value, the height, the cross-sectional area, and the fluid flow rate.

5. The method for simulating acoustic transmission loss of an air filter element according to claim 4, characterized in that, The formula for calculating the flow resistance of the filter element in the target air filter is: In the formula, δ is the flow resistance of the filter element in the target air filter, Δp is the flow resistance value of the filter element in the target air filter, h is the height of the filter element in the target air filter, S is the cross-sectional area of ​​the filter element in the target air filter, and Q is the fluid flow rate of the filter element in the target air filter.

6. The method for simulating acoustic transmission loss of an air filter element according to claim 4, characterized in that, The intake resistance of the engine intake system is simulated to obtain the flow resistance value of the filter element in the target air filter, specifically including: Create a three-dimensional model of the automobile engine intake system; The three-dimensional model is meshed to obtain a mesh model of the automobile engine intake system; The mesh model is imported into the flow resistance simulation software to obtain the flow resistance simulation results; the flow resistance simulation results include the flow resistance value of the filter element in the target air filter.

7. The method for simulating acoustic transmission loss of an air filter element according to claim 1, characterized in that, The filter element is made of folded media material; Determining the porosity of the filter element in the target air filter specifically includes: A three-dimensional model of the filter element in the target air filter is created to obtain a filter element simulation model; Measure the length, width, and height of the filter element simulation model, and calculate the volume of the filter element simulation model; Measure the surface area and thickness of the medium material, and calculate the volume of the medium material; Based on the volume of the filter element simulation model, the volume of the media material, and the formula for calculating the filter element porosity, the porosity of the filter element in the target air filter is obtained; the formula for calculating the filter element porosity is: In the formula, V represents the porosity of the filter element in the target air filter. LX V represents the volume of the filter element simulation model. LZ For the volume of the dielectric material, Porosity is the porosity of the medium material.

8. A simulation system for acoustic transmission loss of an air filter element, characterized in that, include: The flow resistance and porosity acquisition module is used to determine the flow resistance and porosity of the filter element in the target air filter; The filter element simulation curve generation module is used to generate a filter element simulation curve for the target air filter based on the flow resistance, porosity, and a porous media model with determined coefficient parameters. The filter element simulation curve is used to characterize the noise reduction effect of the filter element in the target air filter. The methods for determining the coefficient parameters in the porous media model include: An acoustic transmission loss experiment was conducted on the filter element in the test air filter to obtain the filter element experimental curve; the filter element experimental curve is used to characterize the noise reduction effect of the filter element in the test air filter. Determine the flow resistance and porosity of the filter element in the test air filter; Based on the filter element experimental curve, the flow resistance and porosity of the filter element in the test air filter, the coefficient parameters in the porous media model are determined by multiple iterations. The coefficient parameters include: tortuosity, viscous characteristic length and thermal characteristic length; the thermal characteristic length is a set multiple of the viscous characteristic length. The process of the nth iteration is as follows: Determine the coefficient parameters for the nth iteration; Based on the flow resistance ratio and porosity of the filter element in the test air filter, the coefficient parameters of the nth iteration, and the porous media model, the filter element simulation curve for the nth iteration is generated. Calculate the amplitude difference between the filter element simulation curve and the filter element experimental curve in the nth iteration; When the magnitude difference in the nth iteration is less than the first set value, the coefficient parameter of the nth iteration is determined as the final coefficient parameter; When the amplitude difference of the nth iteration is greater than or equal to the first set value and less than the second set value, the viscous feature length in the coefficient parameter of the nth iteration is changed by the first set amplitude, and the changed coefficient parameter of the nth iteration is used as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration; or the tortuosity in the coefficient parameter of the nth iteration is changed by the second set amplitude, and the changed coefficient parameter of the nth iteration is used as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration. When the amplitude difference of the nth iteration is greater than or equal to the second set value, the viscosity feature length in the coefficient parameter of the nth iteration is changed by a third set amplitude, and the changed coefficient parameter of the nth iteration is used as the coefficient parameter of the (n+1)th iteration for the (n+1)th iteration; the second set value is greater than the first set value.

9. An electronic device, characterized in that, The device includes a memory and a processor, the memory being used to store a computer program, and the processor running the computer program to cause the electronic device to perform the air filter cartridge acoustic transmission loss simulation method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the method for simulating acoustic transmission loss of an air filter element as described in any one of claims 1 to 7.

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