A road noise analysis method, device, equipment and storage medium of a vehicle

Abstract

Embodiments of the present application disclose a vehicle road noise analysis method, device, equipment and storage medium, wherein the method comprises: obtaining road unevenness data of a target road and wheel arrangement data of a target vehicle; determining target road spectrum data according to the road unevenness data and the wheel arrangement data; inputting the target road spectrum data into a vehicle road noise analysis model corresponding to the target vehicle to obtain target vehicle road noise analysis data; wherein the number of wheels in the vehicle road noise analysis model is an even number and at least six. The technical scheme of the embodiments of the present application solves the technical problem that the prior art cannot perform road noise analysis on commercial vehicles, can perform road spectrum processing and road noise analysis on commercial vehicles, improves the accuracy of road noise analysis of commercial vehicles, shortens the development cycle of commercial vehicles, and improves the development efficiency of commercial vehicles.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of simulation analysis technology, and in particular to a method, apparatus, device and storage medium for analyzing road noise of vehicles. Background Technology

[0002] During vehicle operation, the interaction between tires and the ground (including impact and compression) generates radiated noise and structural excitation. Radiated noise is tire noise, while structural excitation is transmitted to the vehicle body through the suspension, causing vibration and noise issues, i.e., road noise. Road noise can be suppressed through tire design and selection, chassis vibration isolation design, and vehicle body structure design. Currently, OEMs conduct vehicle road noise assessments primarily in two ways: test-based assessments and simulation-based assessments. However, existing road noise analyses are generally only applicable to four-wheeled vehicles and lack road noise analysis methods for multi-axle, dual-tire commercial vehicles. Summary of the Invention

[0003] This invention provides a method, apparatus, device, and storage medium for road noise analysis of vehicles, which can perform road surface spectrum processing and road noise analysis on commercial vehicles, improve the accuracy of road noise analysis for commercial vehicles, shorten the development cycle of commercial vehicles, and improve the development efficiency of commercial vehicles.

[0004] In a first aspect, embodiments of the present invention provide a method for analyzing road noise in vehicles, the method comprising:

[0005] Acquire road surface roughness data and wheel arrangement data of the target vehicle;

[0006] The target road surface spectrum data is determined based on the road surface roughness data and wheel arrangement data;

[0007] The target road surface spectrum data is input into the vehicle road noise analysis model corresponding to the target vehicle to obtain the target vehicle road noise analysis data;

[0008] In the vehicle road noise analysis model, the number of wheels is even and at least six.

[0009] Secondly, embodiments of the present invention provide a road noise analysis device for vehicles, the device comprising:

[0010] The raw data acquisition module is used to acquire road surface roughness data of the target road surface and wheel arrangement data of the target vehicle;

[0011] The road surface spectrum data generation module is used to determine the target road surface spectrum data based on the road surface roughness data and wheel arrangement data;

[0012] The road noise analysis data generation module is used to input the target road surface spectrum data into the vehicle road noise analysis model corresponding to the target vehicle to obtain the target vehicle road noise analysis data.

[0013] In the vehicle road noise analysis model, the number of wheels is even and at least six.

[0014] Thirdly, embodiments of the present invention provide a computer device, the computer device comprising:

[0015] One or more processors;

[0016] Memory, used to store one or more programs;

[0017] When the one or more programs are executed by the one or more processors, the one or more processors implement the vehicle road noise analysis method described in any embodiment.

[0018] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the road noise analysis method for vehicles described in any embodiment.

[0019] The technical solution provided by this invention involves acquiring road surface roughness data of a target road surface and wheel arrangement data of a target vehicle; determining target road surface spectrum data based on the road surface roughness data and wheel arrangement data; and inputting the target road surface spectrum data into a vehicle road noise analysis model corresponding to the target vehicle to obtain target vehicle road noise analysis data. The number of wheels in the vehicle road noise analysis model is even and at least six. This invention solves the technical problem of existing technologies being unable to perform road noise analysis on commercial vehicles. It enables road surface spectrum processing and road noise analysis for commercial vehicles, improving the accuracy of commercial vehicle road noise analysis, shortening the commercial vehicle development cycle, and increasing commercial vehicle development efficiency. Attached Figure Description

[0020] Figure 1 This is a flowchart of a road noise analysis method for vehicles provided in an embodiment of the present invention;

[0021] Figure 2 This is a flowchart of another vehicle road noise analysis method provided in an embodiment of the present invention;

[0022] Figure 3 This is a schematic diagram of two-dimensional road surface scanning data provided in an embodiment of the present invention;

[0023] Figure 4 This is a schematic diagram of road surface unevenness data provided in an embodiment of the present invention;

[0024] Figure 5 This is a flowchart of determining road surface spectrum data provided in an embodiment of the present invention;

[0025] Figure 6This is a schematic diagram illustrating the determination of road surface spectrum data provided in an embodiment of the present invention;

[0026] Figure 7 This is a schematic diagram of a vehicle road noise analysis model provided in an embodiment of the present invention;

[0027] Figure 8 This is a flowchart of determining vehicle road noise analysis data provided in an embodiment of the present invention;

[0028] Figure 9 This is a schematic diagram of vehicle road noise analysis data provided in an embodiment of the present invention;

[0029] Figure 10 This is a flowchart of a diagnostic analysis of vehicle road noise data provided in an embodiment of the present invention;

[0030] Figure 11 This is a schematic diagram of the structure of a road noise analysis device for vehicles provided in an embodiment of the present invention;

[0031] Figure 12 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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, 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.

[0033] Figure 1 This is a flowchart of a road noise analysis method for vehicles provided by an embodiment of the present invention. The embodiment of the present invention can be applied to the scenario of road noise analysis for commercial vehicles. The method can be executed by a road noise analysis device for vehicles, which can be implemented by software and / or hardware.

[0034] like Figure 1 As shown, the road noise analysis method for vehicles includes the following steps:

[0035] S110. Obtain road surface unevenness data and wheel arrangement data of the target vehicle.

[0036] The target road surface can be the road surface on which the vehicle travels in the road noise simulation analysis. That is, this embodiment of the invention needs to simulate and analyze the road noise when the target vehicle travels on the target road surface. Road surface roughness data can be the roughness data of the target road surface. Specifically, the target road surface can be scanned based on a preset road surface roughness device to obtain the road surface roughness data. The target vehicle can be the vehicle used for road noise simulation analysis. For example, the target vehicle can be a multi-axle commercial vehicle with a dual-tire layout. Wheel arrangement data can be the arrangement data between the tires in the target vehicle. Specifically, the wheel arrangement data can be set based on the tire data of the target vehicle. The number of wheels on the same axle in the wheel arrangement data is even and at least two. By introducing...

[0037] S120. Determine the target road surface spectrum data based on the road surface roughness data and wheel arrangement data.

[0038] The target road surface spectrum data can be road surface spectrum data generated by the tires of the target vehicle driving on the target road surface. Specifically, the target road surface spectrum data can be determined based on road surface roughness data and wheel arrangement data. For example, based on a preset frequency resolution, the driving process of the target vehicle's tires on the target road surface can be simulated according to the road surface roughness data and wheel arrangement data, thereby obtaining the target road surface spectrum data in the simulation process. By introducing wheel arrangement data, the unique wheel-related data of commercial vehicles can be combined with road surface roughness data, providing a road surface spectrum analysis method applicable to commercial vehicles and improving the accuracy of road noise analysis for commercial vehicles.

[0039] S130. Input the target road surface spectrum data into the vehicle road noise analysis model corresponding to the target vehicle to obtain the target vehicle road noise analysis data.

[0040] The vehicle road noise analysis model can be a whole vehicle model of the target vehicle used to analyze road noise. Specifically, the initial vehicle road noise analysis model in this embodiment can be a computational model of the whole vehicle, not a neural network model. The number of wheels in the vehicle road noise analysis model is even and at least six. The target vehicle road noise analysis data can be road noise data generated when the target vehicle travels on the target road surface. Specifically, the target road surface spectrum data can be input into the target vehicle road noise analysis model to obtain the target vehicle road noise analysis data. By introducing the vehicle road noise analysis model, the unique whole vehicle model and road surface spectrum data of commercial vehicles can be combined, providing a road noise analysis method applicable to commercial vehicles, improving the accuracy of commercial vehicle road noise analysis, shortening the commercial vehicle development cycle, and improving the development efficiency of commercial vehicles.

[0041] The technical solution provided by this invention involves acquiring road surface roughness data of a target road surface and wheel arrangement data of a target vehicle; determining target road surface spectrum data based on the road surface roughness data and wheel arrangement data; and inputting the target road surface spectrum data into the vehicle road noise analysis model corresponding to the target vehicle to obtain target vehicle road noise analysis data. The number of wheels in the vehicle road noise analysis model is even and at least six. This invention solves the technical problem of existing technologies being unable to perform road noise analysis on commercial vehicles. It enables road surface spectrum processing and road noise analysis for commercial vehicles, improving the accuracy of commercial vehicle road noise analysis, shortening the commercial vehicle development cycle, and increasing commercial vehicle development efficiency.

[0042] Figure 2 This is a flowchart of another vehicle road noise analysis method provided by an embodiment of the present invention. The embodiments of the present invention can be applied to the scenario of road noise analysis for commercial vehicles. Based on the above embodiments, this embodiment further explains how to obtain the road surface roughness data of the target road surface; how to determine the target road surface spectrum data based on the road surface roughness data and wheel arrangement data; and how to obtain the vehicle road noise analysis model corresponding to the target vehicle. The device can be implemented by software and / or hardware and integrated into a computer device with application development capabilities.

[0043] like Figure 2 As shown, the road noise analysis method for vehicles includes the following steps:

[0044] S210. Obtain three-dimensional road surface scan data of the target road surface and wheel arrangement data of the target vehicle.

[0045] The target vehicle can be the vehicle used for road noise simulation analysis. For example, the target vehicle can be a multi-axle commercial vehicle with a dual-tire layout. The target road surface can be the road surface on which the vehicle travels in the road noise simulation analysis. That is, this embodiment of the invention requires simulation analysis of road noise when the target vehicle travels on the target road surface. The three-dimensional road surface scanning data can be three-dimensional scanning data of the target road surface. Specifically, the target road surface can be three-dimensionally scanned using a 3D road surface scanning instrument to obtain three-dimensional road surface scanning data. Further, the three-dimensional road surface scanning data includes multi-dimensional road surface data; for example, the three-dimensional road surface scanning data includes multi-dimensional road surface data such as length, width, and height. The wheel arrangement data can be the arrangement data between the tires in the target vehicle. Specifically, the wheel arrangement data can be set based on the tire data of the target vehicle. The number of co-axial wheels in the wheel arrangement data is even and at least two.

[0046] S220. The width dimension data in the three-dimensional road surface scanning data is fused to obtain two-dimensional road surface scanning data.

[0047] The two-dimensional road surface scan data can be the two-dimensional scan data of the target road surface. One dimension of the two-dimensional road surface scan data is the road surface length, and the other dimension is the road surface height. The road surface height can be unevenness. Specifically, since the width dimension data in the three-dimensional road surface scan data has little use in subsequent data analysis, in order to reduce the amount of data computation, the width dimension data in the three-dimensional road surface scan data can be fused to obtain the two-dimensional road surface scan data. For example, the width dimension data can be averaged, and only the average value of the width dimension data can be retained in subsequent analysis.

[0048] For example, Figure 3 This is a schematic diagram of two-dimensional road surface scanning data provided in an embodiment of the present invention. Figure 3 As shown, the first column of data in the figure represents road surface distances, with a maximum interval of 5mm and equal spacing. The distance unit in the table above is meters (m), while the road surface elevation information can be in mm or meters. The second column represents road surface unevenness data. The file format for 2D road surface scan data is csv (Comma-Separated Values). If there are multiple road surface data points, each road surface needs to be saved as a separate csv file. For example, Figure 4 This is a schematic diagram of road surface unevenness provided in an embodiment of the present invention.

[0049] S230. Obtain the vehicle speed setting command, and determine at least one candidate unevenness data based on the vehicle speed setting command and the road surface unevenness data.

[0050] The vehicle speed setting command can be a command to set the tire speed. Based on the vehicle speed setting command, the corresponding vehicle speed for road noise analysis of the target vehicle can be determined. Specifically, the value within the preset vehicle speed setting box can be used as the vehicle speed value. The relationship between vehicle speed and load is as follows: for the same road surface roughness (relationship between distance and elevation), the higher the vehicle speed, the higher the frequency of load coverage, and the lower the load amplitude. Candidate roughness data can be road surface roughness data with a corresponding format. Specifically, the data types of candidate roughness data include: amplitude and phase type and real part and imaginary part type. After determining the candidate roughness data, the required data type can be selected from the candidate roughness data for subsequent processing.

[0051] S240. Determine the target road surface spectrum data based on the candidate roughness data and the wheel arrangement data.

[0052] The target road surface spectrum data can be road surface spectrum data generated by the tires of the target vehicle driving on the target road surface. Specifically, the target road surface spectrum data can be determined based on candidate roughness data and wheel arrangement data.

[0053] For example, when determining the target pavement spectrum data based on candidate roughness data and wheel arrangement data, a roughness selection instruction can be obtained, and the target roughness data can be determined from the candidate roughness data in the roughness selection instruction; a Hanning window setting instruction can be obtained, and the target load frequency resolution can be determined based on the Hanning window setting instruction; based on the target load frequency resolution, the target roughness data and wheel arrangement data can be matched to obtain the target pavement spectrum data.

[0054] The roughness selection command can be a command to select candidate roughness data. Specifically, it can be based on interactive operations such as clicking and dragging candidate roughness data on a preset interactive interface. Based on the roughness selection command, roughness data for subsequent analysis can be determined from the candidate roughness data. The target roughness data can be the determined roughness data for subsequent analysis. Specifically, the candidate roughness data selected by the roughness selection command can be used as the target roughness data.

[0055] Furthermore, the Hanning window setting command can be used to set the size of the Hanning window. By setting the Hanning window size, the frequency resolution of the load can be determined; a larger window results in a higher frequency resolution and a smaller frequency interval. For example, when the Hanning window size is set to 8192, it means that one window contains 8192 data points. The target load frequency resolution can be determined based on the frequency resolution determined by the Hanning window setting command. Specifically, the target load frequency resolution can be determined based on the correspondence between the Hanning window size and the load frequency resolution, using the Hanning window size value in the Hanning window setting command.

[0056] The target load frequency resolution can be the frequency resolution of the final determined load. Specifically, based on the target load frequency resolution, target roughness data and wheel arrangement data can be matched to obtain target road surface spectrum data. Matching the target roughness data and wheel arrangement data can be understood as simulating the tires of the target vehicle driving on the target road surface, thereby obtaining the target road surface spectrum data during the simulation. By introducing wheel arrangement data, the unique wheel-related data of commercial vehicles can be combined with road roughness data, providing a road surface spectrum analysis method applicable to commercial vehicles and improving the accuracy of road noise analysis for commercial vehicles.

[0057] Specifically, the target road surface spectrum data includes the PSD (Power Spectral Density) data of each wheel and the CSD (Cross Power Spectral Density) data between them. Power spectral density describes how the power contained in each frequency component of a random vibration signal is distributed in the frequency domain; it is a statistical characteristic of random vibration in the frequency domain. In sinusoidal vibration tests, the frequency and amplitude of the vibration are fixed, so the power (energy) of the vibration is clear and easy to calculate. However, because the time history of random vibration is obviously non-periodic, power spectral density (mean square spectral density) must be used for calculation. A random vibration signal can be considered as composed of an infinite number of simple harmonic motions; therefore, the power spectrum of a random vibration signal is the sum of the power of simple harmonic motions within a given frequency range. The power of a simple harmonic motion is proportional to the square of its amplitude, and the power spectral density at a specified frequency is the average value of the mean square value of the signal in Δf. Ideally, the averaging time would be infinitely long and the filter bandwidth infinitely narrow, but this is practically impossible. Therefore, finite averaging time and finite bandwidth are usually used, resulting in (mean square value / unit interval frequency, hence also called mean square spectral density).

[0058] The variation of power spectral density over a frequency range, i.e., the graph of power spectral density against frequency, is called the spectrum of power spectral density. The spectrum of power spectral density can also be understood as follows: if a random vibration signal is divided into many small frequency bands Δf, and the mean square acceleration value is measured in each band, then divided by Δf, and Δf→0, the resulting function is called the spectrum of power spectral density. Since the unit of power spectral density is g... 2 / Hz represents the square of the acceleration value per unit frequency, hence it is also called the acceleration spectral density in random vibration tests. The spectrum of the power spectral density is also called the spectrum of the acceleration spectral density. The unit of power spectral density (acceleration spectral density) is g. 2 / Hz and m 2 / s 4 The two expression forms, / Hz, are related by a factor of 100, meaning 1g 2 / Hz=100m 2 / s 4 / Hz. In addition to providing information in the frequency domain, power spectral density can also be used to analyze the dynamic characteristics of products, study fatigue damage, and identify resonances. For example, power spectral density can be used to determine which vibrations experienced by a product installed on a vehicle are dominant and which are negligible, thus facilitating product design improvements.

[0059] Furthermore, the cross-power spectral density describes the frequency information between two random vibration processes. It not only provides the magnitude of energy distributed according to frequency but also the relationship between the two signals. From the cross-power spectral density, we can obtain the system's frequency response function and determine the relationship between the vibration response and its excitation time.

[0060] For example, Figure 5 This is a flowchart illustrating how to determine road surface spectrum data according to an embodiment of the present invention. Figure 5 As shown, the process for determining road surface spectrum data is as follows: First, the road surface spectrum of the target road surface is scanned or 3D road surface data is extracted to obtain 2D road surface roughness. Then, the vehicle speed is set, the 2D road surface roughness data is selected, the data export location is chosen, and then a wheel layout scheme is added to match the road surface data with the wheels, generating PSD data and CSD data, thus obtaining road surface spectrum data in CSV format. For example, Figure 6 This is a schematic diagram of determining road surface spectrum data provided by an embodiment of the present invention. Figure 6 These are the road surface spectrum data corresponding to a vehicle speed of 30 kph.

[0061] S250: Obtain preset indicator data and initial vehicle road noise analysis model.

[0062] The preset indicator data can be indicator data constrained by the vehicle road noise simulation scenario. Specifically, the preset indicator data includes at least one of the following: sweep frequency range, modal extraction range, damping, operating conditions, constraint settings, and output type. The initial vehicle road noise analysis model can be a whole vehicle model of the target vehicle capable of analyzing road noise. Specifically, in this embodiment of the invention, the initial vehicle road noise analysis model can be a computational model of the whole vehicle, not a neural network model. The number of wheels in the vehicle road noise analysis model is even and at least six. Furthermore, the preset indicator data and the initial vehicle road noise analysis model can be obtained through file upload or on-site creation, etc. For example, Figure 7 This is a schematic diagram of a vehicle road noise analysis model provided in an embodiment of the present invention. Figure 7 This is a vehicle road noise analysis model for a three-axle, dual-tire commercial vehicle.

[0063] S260. Adjust the parameters in the initial vehicle road noise analysis model according to the preset index data to obtain the target vehicle road noise analysis model.

[0064] The target vehicle road noise analysis model can be the final vehicle model used for road noise analysis. Specifically, the parameters in the initial vehicle road noise analysis model can be adjusted based on preset index data to obtain the target vehicle road noise analysis model. That is, the parameters in the initial vehicle road noise analysis model are adjusted to make the model conform to the constraints of the current road noise simulation.

[0065] S270. Input the target road surface spectrum data into the target vehicle road noise analysis model to obtain the target vehicle road noise analysis data.

[0066] The target vehicle road noise analysis data can be the road noise data generated by the target vehicle while driving on the target road surface. Specifically, the target road surface spectrum data can be input into the target vehicle road noise analysis model to obtain the target vehicle road noise analysis data. By introducing the vehicle road noise analysis model, the unique vehicle model of commercial vehicles and road surface spectrum data can be combined, providing a road noise analysis method applicable to commercial vehicles, improving the accuracy of commercial vehicle road noise analysis, shortening the commercial vehicle development cycle, and increasing the efficiency of commercial vehicle development.

[0067] For example, Figure 8 This is a flowchart illustrating how to determine vehicle road noise analysis data according to an embodiment of the present invention. Figure 8 As shown, the process for determining vehicle road noise analysis data is as follows: First, the whole vehicle calculation model and whole vehicle display model of the target vehicle are read in. Then, the road surface spectrum data determined above is read in. Further, the sweep frequency range, modal extraction range, damping are defined, working conditions are created, constraint settings are set, and output settings are configured. Finally, the calculation model is exported, which contains vehicle road noise analysis data. For example, Figure 9 This is a schematic diagram of vehicle road noise analysis data provided in an embodiment of the present invention.

[0068] In one optional implementation, to improve the accuracy of road noise analysis data, after obtaining the road noise analysis data of the target vehicle, further diagnostic analysis can be performed on the data. For example, upon receiving a road noise data diagnostic command, a diagnostic indicator setting interface can be displayed; based on the user's settings for preset diagnostic indicator items in the diagnostic indicator setting interface, the target indicator analysis range is determined; and based on the target indicator analysis range, diagnostic analysis is performed on the target vehicle road noise analysis data to obtain the target road noise diagnostic result.

[0069] This system allows for the configuration of a road noise data diagnostic activation control. When this control is triggered, indicating that the vehicle road noise analysis device has received a road noise data diagnostic command, the subsequent road noise data diagnostic process begins. Specifically, a diagnostic indicator setting interface can be displayed within a preset interactive interface. This interface offers multiple preset diagnostic indicator items for configuration, allowing users to determine the diagnostic scope of the road noise analysis data. These preset diagnostic indicator items can be pre-defined constraint indicators used to diagnose problems in the road noise analysis data. Specifically, the preset diagnostic indicator items include at least one of the following: diagnostic frequency, node contribution, transmission path contribution, modal contribution, design sensitivity, and optimization variable.

[0070] Furthermore, the target indicator analysis range can be the diagnostic range of road noise analysis data. Specifically, the target indicator analysis range can be determined by the settings of all preset diagnostic indicator items. The target road noise diagnostic result can be the result of data diagnosis of the target vehicle road noise analysis data. Specifically, diagnostic analysis of the target vehicle road noise analysis data can be performed based on the target indicator analysis range to obtain the target road noise diagnostic result.

[0071] For example, Figure 10 This is a flowchart illustrating the diagnostic analysis of vehicle road noise data provided in an embodiment of the present invention. Figure 10 As shown, the process for diagnosing and analyzing vehicle road noise data is as follows: After determining the target vehicle road noise analysis data, the user selects whether to perform a diagnosis. If no diagnosis is performed, the model is exported, and the target vehicle road noise analysis data obtained in the above steps is output. If road noise data diagnosis is performed, preset diagnostic indicators are set, specifically including setting the diagnostic frequency, GPA (Grid Participation Analysis) node contribution output, TPA (Transfer Path Analysis) transfer path contribution output, MPA (Modal Participation Analysis) modal contribution output, DSA (Design Sensitivity Analysis) design sensitivity output, and variable settings. In addition, diagnostic output settings can also be configured. Finally, the target vehicle road noise analysis data and the corresponding diagnostic results are output together.

[0072] The technical solution provided by this invention involves acquiring three-dimensional road surface scanning data of the target road surface and wheel arrangement data of the target vehicle; fusing the width dimension data in the three-dimensional road surface scanning data to obtain two-dimensional road surface scanning data; acquiring a vehicle speed setting command and determining at least one candidate roughness data based on the vehicle speed setting command and road surface roughness data; determining target road surface spectrum data based on the candidate roughness data and wheel arrangement data; acquiring preset index data and an initial vehicle road noise analysis model; adjusting the parameters in the initial vehicle road noise analysis model based on the preset index data to obtain the target vehicle road noise analysis model; and inputting the target road surface spectrum data into the target vehicle road noise analysis model to obtain the target vehicle road noise analysis data. This invention solves the technical problem of existing technologies being unable to perform road noise analysis on commercial vehicles, enabling road surface spectrum processing and road noise analysis for commercial vehicles, improving the accuracy of commercial vehicle road noise analysis, shortening the commercial vehicle development cycle, and increasing commercial vehicle development efficiency.

[0073] Figure 11 This is a schematic diagram of a road noise analysis device for vehicles provided in an embodiment of the present invention. The embodiment of the present invention can be applied to the scenario of road noise analysis for commercial vehicles. The device can be implemented by software and / or hardware and integrated into a computer device with application development capabilities.

[0074] like Figure 11 As shown, the vehicle road noise analysis device includes: a raw data acquisition module 310, a road surface spectrum data generation module 320, and a road noise analysis data generation module 330.

[0075] The system includes a raw data acquisition module 310 for acquiring road surface roughness data and wheel arrangement data of the target vehicle; a road surface spectrum data generation module 320 for determining target road surface spectrum data based on the road surface roughness data and wheel arrangement data; and a road noise analysis data generation module 330 for inputting the target road surface spectrum data into the vehicle road noise analysis model corresponding to the target vehicle to obtain target vehicle road noise analysis data. The number of wheels in the vehicle road noise analysis model is even and at least six.

[0076] The technical solution provided by this invention involves acquiring road surface roughness data of a target road surface and wheel arrangement data of a target vehicle; determining target road surface spectrum data based on the road surface roughness data and wheel arrangement data; and inputting the target road surface spectrum data into a vehicle road noise analysis model corresponding to the target vehicle to obtain target vehicle road noise analysis data. The number of wheels in the vehicle road noise analysis model is even and at least six. This invention solves the technical problem of existing technologies being unable to perform road noise analysis on commercial vehicles. It enables road surface spectrum processing and road noise analysis for commercial vehicles, improving the accuracy of commercial vehicle road noise analysis, shortening the commercial vehicle development cycle, and increasing commercial vehicle development efficiency.

[0077] In one optional implementation, the number of coaxial wheels in the wheel arrangement data is even and at least two. The road surface spectrum data generation module 320 is specifically used to: acquire a vehicle speed setting command, and determine at least one candidate roughness data based on the vehicle speed setting command and the road surface roughness data; wherein the data type of the candidate roughness data includes: amplitude phase type and real part imaginary part type; and determine the target road surface spectrum data based on the candidate roughness data and the wheel arrangement data.

[0078] In one optional implementation, the pavement spectrum data generation module 320 includes: a candidate roughness data analysis unit, configured to: acquire a roughness selection instruction, and determine target roughness data from the candidate roughness data according to the roughness selection instruction; acquire a Hanning window setting instruction, and determine a target load frequency resolution according to the Hanning window setting instruction; and match the target roughness data and the wheel arrangement data based on the target load frequency resolution to obtain the target pavement spectrum data.

[0079] In one optional implementation, the raw data acquisition module 310 is specifically used to: acquire three-dimensional road surface scanning data of the target road surface; fuse the width dimension data in the three-dimensional road surface scanning data to obtain two-dimensional road surface scanning data; wherein, one dimension of the two-dimensional road surface scanning data is the road surface length and the other dimension is the road surface height.

[0080] In one optional implementation, the road noise analysis data generation module 330 is specifically used for: acquiring preset index data and an initial vehicle road noise analysis model; adjusting the parameters in the initial vehicle road noise analysis model according to the preset index data to obtain a target vehicle road noise analysis model; and inputting the target road surface spectrum data into the target vehicle road noise analysis model to obtain the target vehicle road noise analysis data; wherein, the preset index data includes at least one of the following: sweep frequency range, modal extraction range, damping, operating conditions, constraint settings, and output type.

[0081] In an optional embodiment, the vehicle road noise analysis device further includes a road noise data diagnostic module, configured to: display a diagnostic indicator setting interface upon receiving a road noise data diagnostic instruction; determine a target indicator analysis range based on the user's setting operation of preset diagnostic indicator items in the displayed diagnostic indicator setting interface; and perform diagnostic analysis on the target vehicle road noise analysis data based on the target indicator analysis range to obtain a target road noise diagnostic result.

[0082] In one optional implementation, the preset diagnostic indicators include at least one of the following: diagnostic frequency, node contribution, transmission path contribution, modal contribution, design sensitivity, and optimization variable.

[0083] The vehicle road noise analysis device provided in this embodiment of the invention can execute the vehicle road noise analysis method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method execution.

[0084] Figure 12 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Figure 12 A block diagram of an exemplary computer device 12 suitable for implementing embodiments of the present invention is shown. Figure 12 The computer device 12 shown is merely an example and should not be construed as limiting the functionality or scope of the embodiments of the present invention. The computer device 12 can be any terminal device with computing capabilities and can be configured in the road noise analysis equipment of a vehicle.

[0085] like Figure 12 As shown, the computer device 12 is represented in the form of a general-purpose computing device. The components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, system memory 28, and a bus 18 connecting different system components (including system memory 28 and processing unit 16).

[0086] Bus 18 can be one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. For example, these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0087] Computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0088] System memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache 32. Computer device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 may be used to read and write non-removable, non-volatile magnetic media (…). Figure 12 Not shown; usually referred to as a "hard drive"). Although Figure 12 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 via one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0089] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 42 typically perform the functions and / or methods described in the embodiments of the present invention.

[0090] Computer device 12 can also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), and with one or more devices that enable a user to interact with the computer device 12, and / or with any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., network card, modem, etc.). This communication can be performed through input / output (I / O) interface 22. Furthermore, computer device 12 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) through network adapter 20. Figure 12 As shown, network adapter 20 communicates with other modules of computer device 12 via bus 18. It should be understood that, although... Figure 12 As not shown, it can be used in conjunction with computer device 12 with other hardware and / or software modules, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0091] Processing unit 16 executes various functional applications and data processing by running programs stored in system memory 28, such as implementing the road noise analysis method for vehicles provided in this embodiment, the method including:

[0092] Acquire road surface roughness data and wheel arrangement data of the target vehicle;

[0093] The target road surface spectrum data is determined based on the road surface roughness data and wheel arrangement data;

[0094] The target road surface spectrum data is input into the vehicle road noise analysis model corresponding to the target vehicle to obtain the target vehicle road noise analysis data;

[0095] In the vehicle road noise analysis model, the number of wheels is even and at least six.

[0096] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the vehicle road noise analysis method provided in any embodiment of the present invention, including:

[0097] Acquire road surface roughness data and wheel arrangement data of the target vehicle;

[0098] The target road surface spectrum data is determined based on the road surface roughness data and wheel arrangement data;

[0099] The target road surface spectrum data is input into the vehicle road noise analysis model corresponding to the target vehicle to obtain the target vehicle road noise analysis data;

[0100] In the vehicle road noise analysis model, the number of wheels is even and at least six.

[0101] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media 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 document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0102] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0103] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0104] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0105] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computing device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0106] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for analyzing road noise in vehicles, characterized in that, include: Obtain road surface roughness data and wheel arrangement data of the target vehicle; wherein, the number of coaxial wheels in the wheel arrangement data is even and at least two; Obtain a vehicle speed setting command, and determine at least one candidate roughness data based on the vehicle speed setting command and the road surface roughness data; wherein, the data type of the candidate roughness data includes: amplitude phase type and real part imaginary part type; Obtain the roughness selection instruction, and determine the target roughness data from the candidate roughness data in the roughness selection instruction; Obtain the Hanning window setting command and determine the target load frequency resolution based on the Hanning window setting command; Based on the target load frequency resolution, the target roughness data and the wheel arrangement data are matched to obtain the target road surface spectrum data; the target road surface spectrum data is then input into the vehicle road noise analysis model corresponding to the target vehicle to obtain the target vehicle road noise analysis data. The number of wheels in the vehicle road noise analysis model is even and at least six. The acquisition of the roughness data of the target road surface includes: Acquire 3D road surface scan data of the target road surface; The width dimension data in the three-dimensional road surface scanning data is fused to obtain two-dimensional road surface scanning data; wherein, one dimension of the two-dimensional road surface scanning data is the road surface length and the other dimension is the road surface height.

2. The method according to claim 1, characterized in that, The step of inputting the target road surface spectrum data into the vehicle road noise analysis model corresponding to the target vehicle to obtain the target vehicle road noise analysis data includes: Acquire data for preset indicator items and an initial vehicle road noise analysis model; Adjust the parameters in the initial vehicle road noise analysis model according to the preset index data to obtain the target vehicle road noise analysis model; The target road surface spectrum data is input into the target vehicle road noise analysis model to obtain the target vehicle road noise analysis data; The preset indicator data includes at least one of the following: sweep frequency range, modal extraction range, damping, operating conditions, constraint settings, and output type.

3. The method according to claim 1, characterized in that, The method further includes: Upon receiving a road noise data diagnostic command, the diagnostic indicator setting interface is displayed; The target indicator analysis range is determined based on the user's settings for preset diagnostic indicator items in the displayed diagnostic indicator settings interface. Based on the target index analysis range, the target vehicle road noise analysis data is analyzed for diagnosis to obtain the target road noise diagnosis result.

4. The method according to claim 3, characterized in that, The preset diagnostic indicators include at least one of the following: diagnostic frequency, node contribution, transmission path contribution, modal contribution, design sensitivity, and optimization variables.

5. A road noise analysis device for vehicles, characterized in that, The device includes: The raw data acquisition module is used to acquire road surface roughness data of the target road surface and wheel arrangement data of the target vehicle; wherein, the number of coaxial wheels in the wheel arrangement data is even and at least two. A road surface spectrum data generation module is used to acquire a vehicle speed setting instruction and determine at least one candidate roughness data based on the vehicle speed setting instruction and the road surface roughness data; wherein, the data types of the candidate roughness data include: amplitude-phase type and real-imaginary-part type; acquire an roughness selection instruction and determine target roughness data from the candidate roughness data based on the roughness selection instruction; acquire a Hanning window setting instruction and determine a target load frequency resolution based on the Hanning window setting instruction; and match the target roughness data and the wheel arrangement data based on the target load frequency resolution to obtain target road surface spectrum data; The road noise analysis data generation module is used to input the target road surface spectrum data into the vehicle road noise analysis model corresponding to the target vehicle to obtain the target vehicle road noise analysis data. The number of wheels in the vehicle road noise analysis model is even and at least six. When acquiring the unevenness data of the target road surface, the raw data acquisition module is used to: acquire three-dimensional road surface scanning data of the target road surface; fuse the width dimension data in the three-dimensional road surface scanning data to obtain two-dimensional road surface scanning data; wherein, one dimension of the two-dimensional road surface scanning data is the road surface length and the other dimension is the road surface height.

6. A computer device, characterized in that, The computer device includes: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the road noise analysis method for vehicles as described in any one of claims 1-4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the road noise analysis method for vehicles as described in any one of claims 1-4.

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