In-vehicle noise control method, device and electronic equipment
By using VAone software to establish an SEA subsystem model in the development of in-vehicle noise in commercial vehicles, obtaining engine sound excitation and simulating a semi-infinite fluid environment, the problems of long development cycle and high cost of in-vehicle noise in commercial vehicles are solved, and accurate in-vehicle noise prediction and control are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- FAW JIEFANG AUTOMOTIVE CO
- Filing Date
- 2026-04-03
- Publication Date
- 2026-07-31
AI Technical Summary
Existing technologies for developing in-vehicle noise control in commercial vehicles suffer from long development cycles, high costs, and delayed problem resolution, making it difficult to accurately predict and control in-vehicle noise in the early stages of vehicle development.
Engine acoustic excitation was obtained by measuring the sound power of the engine in a semi-anechoic chamber under full vehicle conditions. Based on VAone software, the SEA subsystem and acoustic cavity of the commercial vehicle cab were modeled, a separate external acoustic cavity was established, a semi-infinite fluid environment was simulated, the body panel materials and acoustic wrapping were assigned, the sound transfer function from the outside to the inside of the vehicle was calculated, and an equivalent leakage was established through airtightness test. The modeling method of the inner protective panel was corrected, and the sound pressure level inside the vehicle at different engine speeds was calculated.
It enables accurate prediction of in-vehicle noise in the early stages of testing, shortens the development cycle, reduces costs, achieves an error of less than 2dB, and improves model accuracy.
Smart Images
Figure CN122491093A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of automotive noise control technology, and in particular to in-vehicle noise control methods, devices and electronic equipment. Background Technology
[0002] With the development of the automotive industry and the increasing demands of users for driving comfort, in-vehicle noise (NVH) performance has become one of the key indicators for evaluating vehicle quality. Especially for commercial vehicles, excessive in-vehicle noise not only seriously affects driving comfort but also interferes with speech clarity. Therefore, accurately predicting and controlling in-vehicle noise in the early stages of vehicle development is of great significance for enhancing product market competitiveness. Currently, the development of in-vehicle noise control for commercial vehicles mainly relies on physical prototype testing. In the traditional "design-prototype-testing-improvement" development process, companies typically need to manufacture multiple prototypes, obtain in-vehicle noise data through field testing, and optimize the structure based on the test results. However, this method has significant shortcomings: First, the development cycle is long, with prototype manufacturing and test preparation often taking several months, which cannot meet the needs of rapid iteration in modern automobiles; second, the cost is high, with each prototype manufacturing and test representing a huge financial investment, especially for commercial vehicles with complex structures and high modification difficulty; third, problems are often discovered late in the testing phase, leaving little room for design modifications and leading to a surge in rectification costs.
[0003] The patent document discloses a fixed-position vehicle interior noise modeling and test benchmarking method based on energy statistics. The simulation modeling method is simplified by using the engine sound power as the excitation input, reducing the number of microphones required, establishing the relationship between the engine sound power and the interior noise under the whole vehicle condition, and benchmarking the sound transfer function from the outside to the inside of the vehicle through experiments and simulations. The modeling is refined by considering the sound cavity between the inner panel and the sheet metal, and setting the equivalent leakage area for the actual leakage location, improving the accuracy to 2 dB. It can balance modeling efficiency and high simulation accuracy, shorten the development cycle and reduce costs. Summary of the Invention
[0004] The purpose of this invention is to provide a method, device, electronic device and storage medium for predicting in-vehicle noise, which can accurately calculate the in-vehicle sound pressure level under a fixed state and establish an accurate correspondence between engine sound power and in-vehicle noise.
[0005] This invention provides the following solution:
[0006] According to one aspect of the present invention, a method for predicting in-vehicle noise is provided, the method comprising:
[0007] Engine acoustic excitation was obtained by testing the engine's acoustic power in a semi-anechoic chamber under full vehicle conditions.
[0008] Based on VAone, the SEA subsystem and acoustic cavity model of the commercial vehicle cab were completed, a separate external acoustic cavity was established, the connection was improved and a semi-infinite fluid simulation semi-anechoic chamber environment was established, and the body panel material, thickness and acoustic wrapping were given.
[0009] The sound transmission function from outside the vehicle to inside the vehicle is calculated by modeling, and the sound transmission function of the anechoic chamber cab is tested. The test and simulation results are compared, the modeling method of the inner protective panel is corrected, the internal structure of the cab is refined, and the equivalent leakage is established through air tightness test.
[0010] Based on the revised model, the in-vehicle sound pressure level at different engine speeds was calculated and compared with the results of the whole vehicle test to verify the accuracy of the model.
[0011] Optionally, the engine acoustic excitation can be obtained through sound power testing of the engine in a semi-anechoic chamber under full vehicle conditions, including:
[0012] Engine sound power was obtained using the nine-point method in a semi-anechoic chamber environment;
[0013] The key parameters of sound absorption coefficient and flow resistance are obtained through loss transmission bench testing.
[0014] Optionally, the test conditions for obtaining engine power output per unit volume include: engine idle speed and rated speed.
[0015] Optionally, based on VAone, complete the modeling of the SEA subsystem and acoustic cavity of the commercial vehicle cab, establish a separate external acoustic cavity, perfect the connection and establish a semi-infinite fluid, simulate a semi-anechoic chamber environment, and assign material, thickness, and acoustic enclosure to the body panels, including:
[0016] The cab SEA subsystem was modeled using VAone. The model materials and thickness were set. Based on the obtained flow resistance parameters, a new acoustic package material was created in the software. The material was assigned to the corresponding subsystem according to the actual thickness and coverage area. The in-vehicle acoustic cavity was refined and established, and a separate external acoustic cavity was established.
[0017] On the top of the driver's cab, semi-infinite fluids are created in the front, back, left, and right sides to simulate a semi-anechoic chamber environment.
[0018] Optionally, the sound transfer function from outside the vehicle to inside the vehicle is calculated using a model, and the sound transfer function of the anechoic chamber cab is tested simultaneously. The test and simulation results are compared to correct the modeling method of the inner lining panel, refine the internal structure of the cab, and establish an equivalent leakage through airtightness testing, including:
[0019] Add 1W of sound power to the right ear cavity of the driver in the cab, calculate the sound pressure level response of the acoustic cavity at the bottom of the cab, and obtain the acoustic transfer function of the simulated cab.
[0020] The test driver placed a sound source to excite the driver's right ear, and a microphone was placed on the engine to measure the ratio of the sound pressure at the frequency response point under this excitation to the volume acceleration at the center of the sound source. The sound pressure level was obtained by converting the signal using a formula.
[0021] Experimental simulation of transfer function comparison.
[0022] Optionally, the sound transfer function from outside the vehicle to inside the vehicle is calculated using a model, and the sound transfer function of the anechoic chamber cab is tested simultaneously. The test and simulation results are compared to correct the modeling method of the inner lining panel, refine the internal structure of the cab, and establish an equivalent leakage through airtightness testing. This also includes:
[0023] After comparing the experimental simulation transfer functions, the model was optimized.
[0024] Optionally, the model can be optimized, including:
[0025] Optimize the modeling method of the inner lining panel, establish the inner lining panel SEA subsystem, and consider the acoustic cavity between it and the sheet metal.
[0026] Establish a model of the SEA subsystem of the metal structural components of the sleeper berth and overhead luggage rack, considering its segmentation and coupling of the acoustic cavity;
[0027] The test method obtains the leakage amount in the cab, converts it into an equivalent leakage area, and sets up leakage points in key locations such as doors, glass, pressure relief vents, air conditioning, and steering column.
[0028] Optionally, based on the modified model, the in-vehicle sound pressure level at different engine speeds is calculated and compared with the results of whole-vehicle tests to verify the model accuracy, including:
[0029] The engine excitation is applied to the external acoustic cavity to calculate the driver's right ear acoustic cavity response at 400-8000Hz under the rated idle speed;
[0030] A microphone was placed in the driver's right ear in a semi-anechoic chamber environment. With the engine running stably, the A-weighted sound pressure level of the driver's right ear was measured.
[0031] Compare simulation and experimental results.
[0032] According to two aspects of the present invention, an in-vehicle noise prediction device is provided, the in-vehicle noise prediction device comprising:
[0033] The acquisition module is used to acquire engine acoustic excitation through sound power testing of the engine in a semi-anechoic chamber under full vehicle conditions.
[0034] A module is established to model the SEA subsystem and acoustic cavity of a commercial vehicle cab based on VAone, establish a separate external acoustic cavity, improve the connection and establish a semi-infinite fluid simulation semi-anechoic chamber environment, and assign material, thickness and acoustic wrapping to the body panels.
[0035] The correction module is used to calculate the sound transmission function from outside the vehicle to inside the vehicle through the model, and at the same time conduct sound transmission function tests of the anechoic chamber and the cab. By comparing the test and simulation results, the modeling method of the inner protective panel is corrected, the internal structure of the cab is refined, and the equivalent leakage is established through airtightness test.
[0036] The calculation module is used to calculate the in-vehicle sound pressure level at different engine speeds based on the corrected model, and compare it with the results of whole vehicle tests to verify the accuracy of the model.
[0037] According to three aspects of the present invention, an electronic device is provided, the electronic device comprising:
[0038] The memory, the processor, and the program stored in the memory for implementing the in-vehicle noise prediction method.
[0039] The memory is used to store the program that implements the in-vehicle noise prediction method;
[0040] The processor is used to execute a program that implements the in-vehicle noise prediction method to carry out the steps of the in-vehicle noise prediction method described above.
[0041] The above solution achieves the following beneficial technical effects:
[0042] To address the shortcomings of long development cycles, high costs, and delayed problem-solving in experimental methods, this invention establishes a commercial vehicle cab SEA subsystem and acoustic cavity model based on VAone in the early stages of testing. Engine acoustic power is obtained through whole-vehicle engine acoustic power testing as the excitation input, and key parameters such as cab leakage, body panel thickness, flow resistance, and sound absorption coefficient are subsequently improved and controlled. The in-vehicle-engine acoustic transfer function is tested, and based on the energy transfer path analysis results, a refined model is created, considering losses at the inner lining panel based on the actual connection method, until the transfer function error within the target frequency band is within 2dB. Based on the corrected model, the in-vehicle sound pressure level under stationary conditions is calculated, establishing the correspondence between engine acoustic power and in-vehicle noise, with an error of less than 2dB. Attached Figure Description
[0043] Figure 1 This is a flowchart of an in-vehicle noise prediction method provided by one or more embodiments of the present invention;
[0044] Figure 2 This is a flowchart of the acquisition operation in the in-vehicle noise prediction method provided by one or more embodiments of the present invention;
[0045] Figure 3 This is a flowchart of the establishment operation in the in-vehicle noise prediction method provided by one or more embodiments of the present invention;
[0046] Figure 4This is a flowchart of the correction operation in the in-vehicle noise prediction method provided by one or more embodiments of the present invention;
[0047] Figure 5 This is a flowchart of the correction operation in the in-vehicle noise prediction method provided by one or more embodiments of the present invention;
[0048] Figure 6 This is a flowchart of the calculation operation in the in-vehicle noise prediction method provided by one or more embodiments of the present invention;
[0049] Figure 7 This is a flowchart of an in-vehicle noise prediction method provided by one or more embodiments of the present invention;
[0050] Figure 8 This is a model diagram of the in-vehicle SEA subsystem and the in-vehicle and external acoustic cavities provided in one or more embodiments of the present invention;
[0051] Figure 9 This is a comparison diagram of experimental and simulation transfer functions before and after model correction provided by one or more embodiments of the present invention;
[0052] Figure 10 These are simulation comparison diagrams of in-vehicle noise tests at the target frequency band during idling, provided by one or more embodiments of the present invention.
[0053] Figure 11 This is a simulation comparison chart of in-vehicle noise test at engine speeds of 800 rpm to 1800 rpm provided by one or more embodiments of the present invention;
[0054] Figure 12 This is a structural diagram of an in-vehicle noise prediction device provided in one or more embodiments of the present invention;
[0055] Figure 13 This is a structural diagram of an electronic device provided in one or more embodiments of the present invention. Detailed Implementation
[0056] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. 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.
[0057] Figure 1 This is a flowchart of an in-vehicle noise prediction method provided in one or more embodiments of the present invention. See also... Figure 1 The in-vehicle noise prediction method includes the following steps:
[0058] S11 obtains engine sound excitation through sound power testing of the engine in a semi-anechoic chamber under full vehicle conditions.
[0059] S12, based on VAone, completes the modeling of the SEA subsystem and acoustic cavity of the commercial vehicle cab, establishes a separate external acoustic cavity, improves the connection and establishes a semi-infinite fluid simulation semi-anechoic chamber environment, and assigns material, thickness and acoustic wrapping to the body panels.
[0060] S13, calculate the sound transmission function from outside the vehicle to inside the vehicle through the model, and at the same time test the sound transmission function of the anechoic chamber and the driver's cab. Compare the test and simulation results, correct the modeling method of the inner protective plate, refine the internal structure of the driver's cab, and establish the equivalent leakage through airtightness test.
[0061] S14. Based on the modified model, the in-vehicle sound pressure level under different engine speeds is calculated and compared with the vehicle test results to verify the model accuracy.
[0062] In the technical solution provided in this embodiment, it is first necessary to obtain the acoustic excitation of the engine. The method for obtaining the engine acoustic excitation is through acoustic power testing.
[0063] The sound power test in this embodiment is a sound power test of the engine in the whole vehicle state. Moreover, the above-mentioned sound power test is carried out in a semi-anechoic chamber.
[0064] After the above sound power test, the sound excitation of the engine was obtained.
[0065] In the process of acquiring acoustic excitation described above, it is also necessary to obtain a series of key parameters in the prediction process. These key parameters include: sound absorption coefficient and flow resistance. Typically, these key parameters are obtained through transmission loss bench testing.
[0066] Next, using VA one software, we completed the modeling of the SEA subsystem and acoustic cavity of the commercial vehicle cab.
[0067] It should be understood that the above modeling operations yield the SEA subsystem model of the commercial vehicle cab, as well as the acoustic cavity model.
[0068] Furthermore, through the above modeling operations, an independent external acoustic cavity can be established.
[0069] After completing the modeling of the SEA subsystem and acoustic cavity, the next step is to complete the connection of the semi-infinite fluid. This connection is necessary to simulate the semi-anechoic chamber environment.
[0070] Furthermore, the above modeling operations also require assigning materials, thickness, and acoustic properties to the vehicle body.
[0071] After completing the above modeling operations, the acoustic transfer function from outside the vehicle to inside the vehicle can be calculated using the completed model.
[0072] In addition, while calculating the acoustic transmission function from outside the vehicle to inside the vehicle, the acoustic transmission function test of the anechoic chamber and driver's cab is carried out simultaneously.
[0073] After completing the above acoustic transmission function test, the experimental results are compared with the simulation results, and the modeling method is further modified and optimized based on the comparison results.
[0074] The main changes are to the modeling method for interior trim panels, which has been changed from creating interior trim panels using an acoustic package mode to using separate materials, as well as more detailed modeling, including the roof rack, metal panels dividing the rear sleeper berth, etc.
[0075] In addition to revising and optimizing the modeling method, it is also necessary to conduct airtightness tests on the vehicle body to establish the equivalent leakage of the vehicle body.
[0076] After the aforementioned corrections, the SEA model should be more accurate and better reflect the actual acoustic parameters of the vehicle body compared to its initial state. Therefore, the corrected SEA model can be used to calculate the in-vehicle sound pressure level.
[0077] It is important to note that the calculation of the in-vehicle sound pressure level needs to be performed separately for different engine speeds. This is mainly because the calculated sound pressure level results need to be compared with the experimental results under different test conditions to improve the accuracy of the modeling. In other words, the modeling accuracy of the vehicle body SEA model needs to be verified under different engine speeds.
[0078] After the above series of operations, an accurate cab SEA model is obtained. The vehicle body SEA model established in this way can accurately calculate the in-vehicle sound pressure level under stationary conditions and establish an accurate correspondence between engine sound power and in-vehicle noise.
[0079] Figure 2 This is a flowchart of the acquisition operation in the in-vehicle noise prediction method provided in one or more embodiments of the present invention. See also Figure 2 Engine acoustic excitation was obtained through acoustic power testing of the engine in a semi-anechoic chamber under full vehicle conditions, including:
[0080] S21, in a semi-anechoic chamber environment, the engine sound power is obtained by the nine-point method.
[0081] S22 obtains key parameters such as sound absorption coefficient and flow resistance through loss transmission bench testing.
[0082] This embodiment, based on the foregoing embodiments of the present invention, focuses on describing the process of obtaining engine sound excitation.
[0083] The process of obtaining engine sound power uses the nine-point method, and this nine-point method is performed in a semi-anechoic chamber environment.
[0084] In addition to obtaining the engine sound power, it is also necessary to obtain some key parameters. These key parameters include: sound absorption coefficient and flow resistance.
[0085] It should be noted that the operating conditions for obtaining engine sound power include multiple speed conditions from engine idle speed to rated speed.
[0086] Figure 3 This is a flowchart of the setup operation in the in-vehicle noise prediction method provided in one or more embodiments of the present invention. See also Figure 3 Based on VAone, the SEA subsystem and acoustic cavity modeling of the commercial vehicle cab were completed, a separate external acoustic cavity was established, connections were perfected and a semi-infinite fluid was established to simulate a semi-anechoic chamber environment, and the body panel materials, thicknesses, and acoustic enclosures were assigned, including:
[0087] S31, based on VAone, complete the modeling of the cab SEA subsystem, set the model material and thickness, and create a new acoustic package material in the software based on the obtained parameters such as flow resistance. The material is assigned to the corresponding subsystem according to the actual thickness and coverage area, and the in-vehicle acoustic cavity is refined and established, and a separate external acoustic cavity is established.
[0088] S32, semi-infinite fluid is created on the top of the cab, front, back, left and right, to simulate a semi-anechoic chamber environment.
[0089] This embodiment, based on the foregoing embodiments of the present invention, focuses on illustrating the process of establishing the SEA model.
[0090] In this embodiment, the SEA model building process uses VA one software. That is, VA one software is used to perform SEA subsystem modeling operations.
[0091] Within the VA One software, set the model materials and thickness.
[0092] Next, based on the flow resistance parameters obtained in the acoustic excitation acquisition step, a new acoustic package material is created in VA One software. After creating the acoustic package material, it is assigned to the corresponding subsystem according to the actual thickness and coverage area, and then further refined to establish an in-vehicle acoustic cavity model.
[0093] Furthermore, a separate external acoustic cavity model needs to be established.
[0094] Figure 4 This is a flowchart of the correction operation in the in-vehicle noise prediction method provided by one or more embodiments of the present invention. See also Figure 4The sound transfer function from outside the vehicle to inside was calculated using a model, and the sound transfer function of the anechoic chamber cab was tested simultaneously. The experimental and simulation results were compared to refine the modeling method of the inner lining panel, detail the internal structure of the cab, and establish an equivalent leakage through airtightness testing, including:
[0095] S41, add 1W of sound power to the right ear cavity of the driver in the cab, calculate the sound pressure level response of the acoustic cavity at the bottom of the cab, and obtain the acoustic transfer function of the simulated cab.
[0096] S42, a sound source is placed to excite the driver's right ear, and a microphone is placed on the engine to measure the ratio of the sound pressure at the frequency response point under this excitation to the volume acceleration at the center of the sound source. The sound pressure level is obtained by converting the result using a formula.
[0097] S43, experimental simulation of transfer function comparison.
[0098] This embodiment, based on the foregoing embodiments of the present invention, focuses on describing the detailed operation of the model correction process.
[0099] Specifically, this embodiment focuses on the process of obtaining the basic parameters for model correction. In this embodiment, the basic parameters mainly refer to the sound pressure level transfer function ratio.
[0100] Specifically, the simulated transfer function ratio is first calculated using simulation. Then, the experimental transfer function ratio is calculated using experiments. Finally, the simulated and experimental transfer function ratios are compared to obtain the comparison results.
[0101] Specifically, the calculation process of the simulated transfer function ratio is as follows: 1W of sound power is added to the right ear cavity of the driver in the cab, the sound pressure level response of the cavity at the bottom of the cab is calculated, and the simulated cab sound transfer function is obtained.
[0102] The calculation process of the experimental transfer function ratio is as follows: a sound source is placed to the right ear of the test driver for excitation, and a microphone is placed on the engine to measure the ratio of the sound pressure at the response point in the frequency domain under this excitation to the volume acceleration at the center of the sound source. The sound pressure level is obtained by conversion using a formula.
[0103] After calculating the simulated transfer ratio and the experimental transfer ratio respectively, the two calculation results were compared to obtain the basic parameters of the correction process.
[0104] Figure 5 This is a flowchart of the correction operation in the in-vehicle noise prediction method provided by one or more embodiments of the present invention. See also Figure 5 The sound transfer function from outside the vehicle to inside was calculated using a model, and the sound transfer function of the anechoic chamber cab was tested simultaneously. The experimental and simulation results were compared to refine the modeling method of the inner lining panel, detail the internal structure of the cab, and establish an equivalent leakage through airtightness testing, including:
[0105] S51, add 1W of sound power to the right ear cavity of the driver in the cab, calculate the sound pressure level response of the bottom cavity of the cab, and obtain the sound transfer function of the simulated cab.
[0106] S52, a sound source is placed to excite the driver's right ear, and a microphone is placed on the engine to measure the ratio of the sound pressure at the frequency response point under this excitation to the volume acceleration at the center of the sound source. The sound pressure level is obtained by converting the result using a formula.
[0107] S53, experimental simulation comparison of transfer functions.
[0108] S54, optimize the modeling method of the inner lining, establish the inner lining SEA subsystem, and consider the acoustic cavity between it and the sheet metal.
[0109] S55. Establish a model of the SEA subsystem of the metal structure of the sleeper berth and overhead luggage rack, considering its segmentation and coupling of the acoustic cavity.
[0110] S56, the test method obtains the leakage amount in the cab, converts it into an equivalent leakage area, and sets leakage points in key locations such as doors, glass, pressure relief vents, air conditioning, and steering column.
[0111] This embodiment, based on the foregoing embodiments of the present invention, uses the basic parameters obtained from the process described in the foregoing embodiments to modify the established SEA model.
[0112] The correction process begins with establishing the inner lining SEA subsystem and considering the acoustic cavity between the inner lining and the sheet metal.
[0113] Next, a subsystem model of the SEA (Self-Effect Acoustic Aspect) of the sleeper berth and overhead luggage rack metal structures is established. This model is primarily designed to account for the segmentation and coupling effects of the metal structures on the acoustic cavity.
[0114] Finally, the leakage amount in the cab was obtained through experiments. The cab leakage amount obtained from the experiments was then converted into an equivalent leakage area, and leakage was simulated at some key locations such as doors, windows, pressure relief vents, air conditioning, and steering column.
[0115] Through the series of operations described above, the correction of the SEA model is completed, resulting in a more accurate and realistic vehicle body SEA model.
[0116] Figure 6 This is a flowchart of the calculation operations in the in-vehicle noise prediction method provided in one or more embodiments of the present invention. See also Figure 6 Based on the corrected model, the in-vehicle sound pressure level at different engine speeds was calculated and compared with the results of whole-vehicle tests to verify the model's accuracy, including:
[0117] S61 applies engine excitation to the external acoustic cavity to calculate the driver's right ear acoustic cavity response at 400-8000Hz under rated idle speed.
[0118] S62, a microphone for the driver's right ear was placed in a semi-anechoic chamber environment. With the engine running stably, the A-weighted sound pressure level of the driver's right ear was measured.
[0119] S63, comparing simulation and experimental results.
[0120] Similar to the aforementioned correction process, the model verification stage also involves comparing the simulation results with the experimental results to verify the model's accuracy.
[0121] Specifically, the simulation results were obtained through the following process: the engine excitation was applied to the external acoustic cavity to calculate the driver's right ear acoustic cavity response at 400-8000Hz under the rated idle speed.
[0122] The test results were obtained through the following process: a microphone for the driver's right ear was placed in a semi-anechoic chamber environment, the engine was running stably, and the A-weighted sound pressure level of the driver's right ear was measured.
[0123] The model is considered to meet the accuracy requirements only if the difference between the simulation results and the experimental results is within the set range; otherwise, the established model is considered not to meet the accuracy requirements.
[0124] Figure 7 This is a flowchart of an in-vehicle noise prediction method provided in one or more embodiments of the present invention. See also... Figure 7 The in-vehicle noise prediction method includes the following steps:
[0125] S701, Start the modeling process.
[0126] S702, obtain model parameters.
[0127] S703, obtain material parameters.
[0128] S704, vehicle body leaks obtained.
[0129] S705, obtain the modeling method.
[0130] S706 performs simulation modeling based on the acquired material parameters, vehicle body leakage, and modeling methods.
[0131] S707 compares the simulated and experimental acoustic transfer functions.
[0132] S708: If, after comparison, the model does not meet the accuracy requirements, the model shall be corrected.
[0133] S709. If the model meets the accuracy requirements after comparison, obtain the corrected model.
[0134] S710 uses the modified model to calculate the in-vehicle response.
[0135] Figure 8 This refers to the in-vehicle SEA subsystem and the model of the interior and exterior acoustic cavities. See also... Figure 8 1 is the cab SEA subsystem and in-vehicle acoustic cavity model; 2 is the external acoustic cavity, used to add engine sound excitation.
[0136] Figure 9 This is a comparison graph of experimental and simulation transfer functions before and after model correction.
[0137] Figure 10 This is a comparison chart of in-vehicle noise simulation tests at the target frequency band during idling.
[0138] Figure 11 A simulated comparison of in-vehicle noise levels during engine speed tests ranging from 800 rpm to 1800 rpm.
[0139] Figure 12 This is a structural diagram of an in-vehicle noise prediction device provided in one or more embodiments of the present invention. See also... Figure 12 The in-vehicle noise prediction device includes:
[0140] The acquisition module 1201 is used to acquire engine sound excitation through sound power testing of the engine in a semi-anechoic chamber under full vehicle conditions.
[0141] Module 1202 is used to complete the modeling of the SEA subsystem and acoustic cavity of the commercial vehicle cab based on VAone, establish a separate external acoustic cavity, improve the connection and establish a semi-infinite fluid simulation semi-anechoic chamber environment, and assign material, thickness and acoustic wrapping to the body panel.
[0142] The correction module 1203 is used to calculate the sound transmission function from outside the vehicle to inside the vehicle through the model, and at the same time conduct sound transmission function tests of the anechoic chamber and the driver's cab, compare the test and simulation results, correct the modeling method of the inner protective panel, refine the internal structure of the driver's cab, and establish an equivalent leakage through airtightness test.
[0143] The calculation module 1204 is used to calculate the in-vehicle sound pressure level at different engine speeds based on the modified model, and compare it with the vehicle test results to verify the accuracy of the model.
[0144] It is worth noting that although only some basic functional modules are disclosed in the embodiments of this invention, it does not mean that the composition of this system is limited to the above-mentioned basic functional modules. On the contrary, what this embodiment intends to express is that, based on the above-mentioned basic functional modules, those skilled in the art can arbitrarily add one or more functional modules in combination with existing technology to form an infinite number of embodiments or technical solutions. That is to say, this system is open rather than closed. The fact that this embodiment only discloses a few basic functional modules should not be considered as the scope of protection of the claims of this invention being limited to the disclosed basic functional modules. At the same time, for the convenience of description, the above device is described separately according to its functions as various units and modules. Of course, in implementing this invention, the functions of each unit and module can be implemented in one or more software and / or hardware.
[0145] like Figure 13 As shown, the present invention also provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the in-vehicle noise prediction method.
[0146] Figure 13 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. For example... Figure 13 The structure shown in this embodiment of the invention includes an electronic device comprising one or more processors 1310 and a memory 1320; the processors 1310 in this electronic device may be one or more. Figure 13 Taking a processor 1310 as an example; memory 1320 is used to store one or more programs; the one or more programs are executed by the one or more processors 1310, so that the one or more processors 1310 implement the in-vehicle noise prediction method as described in any one of the embodiments of the present invention.
[0147] The electronic device may also include an input device 1330 and an output device 1340.
[0148] The processor 1310, memory 1320, input device 1330, and output device 1340 in this electronic device can be connected via a bus or other means. Figure 13 Taking the example of a connection between China and Israel via a bus.
[0149] The memory 1320 in this electronic device serves as a computer-readable storage medium, which can be used to store one or more programs. These programs can be software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the in-vehicle noise prediction method provided in this embodiment of the invention. The processor 1310 executes various functional applications and data processing of the electronic device by running the software programs, instructions, and modules stored in the memory 1320, thereby implementing the in-vehicle noise prediction method described in the above embodiment.
[0150] Memory 1320 may include a program storage area and a data storage area, wherein the program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the electronic device, etc. Furthermore, memory 1320 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, memory 1320 may further include memory remotely located relative to processor 1310, and these remote memories may be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.
[0151] Input device 1330 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the electronic device. Output device 1340 may include display devices such as a display screen.
[0152] The present invention also provides a computer-readable storage medium comprising: a computer program executable by a vehicle, wherein when the computer program is run on the vehicle, the vehicle performs the steps of the in-vehicle noise prediction method.
[0153] Specifically, the computer storage medium in this embodiment of the invention can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. For example, a computer-readable storage medium can be—but is not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.
[0154] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.
Claims
1. A method of predicting in-vehicle noise, characterized by, The in-vehicle noise prediction method includes: Engine acoustic excitation was obtained by testing the engine's acoustic power in a semi-anechoic chamber under full vehicle conditions. Based on VAone, the SEA subsystem and acoustic cavity model of the commercial vehicle cab were completed, a separate external acoustic cavity was established, the connection was improved and a semi-infinite fluid was established to simulate a semi-anechoic chamber environment, and the body panel material, thickness and acoustic wrapping were given. The sound transmission function from outside the vehicle to inside the vehicle is calculated by modeling, and the sound transmission function of the anechoic chamber cab is tested. The test and simulation results are compared, the modeling method of the inner protective panel is corrected, the internal structure of the cab is refined, and the equivalent leakage is established through air tightness test. Based on the revised model, the in-vehicle sound pressure level at different engine speeds was calculated and compared with the results of the whole vehicle test to verify the accuracy of the model.
2. The method of claim 1, wherein, Engine acoustic excitation was obtained through acoustic power testing of the engine in a semi-anechoic chamber under full vehicle conditions, including: Engine sound power was obtained using the nine-point method in a semi-anechoic chamber environment; The key parameters of sound absorption coefficient and flow resistance are obtained through loss transmission bench testing.
3. The method of claim 2, wherein, The test conditions for obtaining engine power output include: engine idle speed and rated speed.
4. The method of claim 1, wherein, Based on VAone, we completed the modeling of the SEA subsystem and acoustic cavity of the commercial vehicle cab, established a separate external acoustic cavity, perfected the connection and established a semi-infinite fluid, simulated a semi-anechoic chamber environment, and assigned material, thickness, and acoustic enclosure to the vehicle body panels, including: The cab SEA subsystem was modeled using VAone. The model materials and thickness were set. Based on the obtained flow resistance parameters, a new acoustic package material was created in the software. The material was assigned to the corresponding subsystem according to the actual thickness and coverage area. The in-vehicle acoustic cavity was refined and established, and a separate external acoustic cavity was established. On the top of the driver's cab, semi-infinite fluids are created in the front, back, left, and right sides to simulate a semi-anechoic chamber environment.
5. The method of claim 1, wherein, The sound transfer function from outside the vehicle to inside was calculated using a model, and the sound transfer function of the anechoic chamber cab was tested simultaneously. The experimental and simulation results were compared to refine the modeling method of the inner lining panel, detail the internal structure of the cab, and establish an equivalent leakage through airtightness testing, including: Add 1W of sound power to the right ear cavity of the driver in the cab, calculate the sound pressure level response of the acoustic cavity at the bottom of the cab, and obtain the acoustic transfer function of the simulated cab. The test driver placed a sound source to excite the driver's right ear, and a microphone was placed on the engine to measure the ratio of the sound pressure at the frequency response point under this excitation to the volume acceleration at the center of the sound source. The sound pressure level was obtained by converting the signal using a formula. Experimental simulation of transfer function comparison.
6. The method of claim 5, wherein, The sound transfer function from outside the vehicle to inside is calculated using a model, and the sound transfer function of the anechoic chamber cab is tested simultaneously. The experimental and simulation results are compared to refine the modeling method of the inner lining panel, detail the internal structure of the cab, and establish an equivalent leakage through airtightness testing. Other aspects include: After comparing the experimental simulation transfer functions, the model was optimized.
7. The method of claim 6, wherein, The model is optimized, including: Optimize the modeling method of the inner lining panel, establish the inner lining panel SEA subsystem, and consider the acoustic cavity between it and the sheet metal. Establish a model of the SEA subsystem of the metal structural components of the sleeper berth and overhead luggage rack, considering its segmentation and coupling of the acoustic cavity; The test method obtains the leakage amount in the cab, converts it into an equivalent leakage area, and sets up leakage points in key locations such as doors, glass, pressure relief vents, air conditioning, and steering column.
8. The method of claim 1, wherein, Based on the revised model, the in-vehicle sound pressure level at different engine speeds was calculated and compared with the results of whole-vehicle tests to verify the model's accuracy, including: The engine excitation is applied to the external acoustic cavity to calculate the driver's right ear acoustic cavity response at 400-8000Hz under the rated idle speed; A microphone was placed in the driver's right ear in a semi-anechoic chamber environment. With the engine running stably, the A-weighted sound pressure level of the driver's right ear was measured. Compare simulation and experimental results.
9. A vehicle interior noise prediction device, characterized in that, The in-vehicle noise prediction device includes: The acquisition module is used to acquire engine acoustic excitation through sound power testing of the engine in a semi-anechoic chamber under full vehicle conditions. A module is established to model the SEA subsystem and acoustic cavity of a commercial vehicle cab based on VAone, establish a separate external acoustic cavity, improve the connection and establish a semi-infinite fluid simulation semi-anechoic chamber environment, and assign material, thickness and acoustic wrapping to the body panels. The correction module is used to calculate the sound transmission function from outside the vehicle to inside the vehicle through the model, and at the same time conduct sound transmission function tests of the anechoic chamber and the cab. By comparing the test and simulation results, the modeling method of the inner protective panel is corrected, the internal structure of the cab is refined, and the equivalent leakage is established through airtightness test. The calculation module is used to calculate the in-vehicle sound pressure level at different engine speeds based on the corrected model, and compare it with the results of whole vehicle tests to verify the accuracy of the model.
10. An electronic device, characterized in that, The electronic device includes: The memory, the processor, and the program stored in the memory for implementing the in-vehicle noise prediction method. The memory is used to store the program that implements the in-vehicle noise prediction method; The processor is configured to execute a program that implements the in-vehicle noise prediction method to implement the steps of the in-vehicle noise prediction method according to any one of claims 1 to 8.