NVH performance determination method, apparatus and device, and computer readable storage medium

Abstract

The invention discloses an NVH performance determination method, apparatus and device, and a computer readable storage medium. The method comprises the steps that working condition data, road condition data and NVH signals of a vehicle in the automatic testing process are obtained, in the automatic testing process, the vehicle is controlled to run according to a preset path through a robot according to a preset driving action, and the preset driving action and the preset path are formulated based on testing requirements; determining a signal characteristic based on the NVH signal; the signal features are input into a recognition model, a recognition result output by the recognition model is obtained, and the recognition result comprises distribution, intensity and source of noise and vibration; and generating an NVH performance report in combination with the working condition data, the road condition data and the identification result. Through the NVH performance evaluation method and device, human participation is avoided to a great extent, and the objectivity of an NVH performance evaluation result is ensured.

Description

Technical Field

[0001] This application relates to the technical field of vehicle testing, and particularly to a method, device, equipment and computer-readable storage medium for determining NVH performance. Background Art

[0002] The NVH performance of a vehicle is one of the important evaluation indicators of vehicle comfort. NVH of a vehicle refers to Noise, Vibration, and Harshness, and its essence is the vibration and noise problems of the vehicle.

[0003] Currently, the common vehicle NVH performance evaluation scheme is that a tester drives or rides in the vehicle to be tested and scores from the subjective feeling level according to the vibration and noise felt during the driving and riding process. Summary of the Invention

[0004] This application provides a method, device, equipment and computer-readable storage medium for determining NVH performance, which can solve the technical problem that the existing method for determining NVH performance is not objective enough.

[0005] In a first aspect, an embodiment of this application provides a method for determining NVH performance. The method for determining NVH performance includes:

[0006] Obtain the working condition data, road condition data and NVH signals of the vehicle during the automated test. During the automated test, a robot controls the vehicle to drive along a preset path according to preset driving actions, where the preset driving actions and the preset path are formulated based on test requirements;

[0007] Determine the signal characteristics based on the NVH signals;

[0008] Input the signal characteristics into an identification model to obtain an identification result output by the identification model. The identification result includes the distribution, intensity and source of noise and vibration;

[0009] Generate an NVH performance report by combining the working condition data, road condition data and the identification result.

[0010] Combined with the first aspect, in an implementation manner, before obtaining the working condition data, road condition data and NVH signals of the vehicle during the automated test, it further includes:

[0011] Perform time synchronization processing on the sensors for collecting NVH signals.

[0012] Combined with the first aspect, in an implementation manner, the determining the signal characteristics based on the NVH signals includes:

[0013] Denoise the NVH signal to obtain a new NVH signal;

[0014] Perform feature statistics on the new NVH signal to obtain signal features, where the signal features include the mean, variance, and peak value of the new NVH signal.

[0015] Combined with the first aspect, in one embodiment, after generating the NVH performance report by combining the working condition data, road condition data, and NVH problem identification result, it further includes:

[0016] Compare the standard NVH performance report corresponding to the working condition data and road condition data with the NVH performance report, and determine the problem items based on the comparison result;

[0017] Generate optimization suggestions based on the problem items.

[0018] Combined with the first aspect, in one embodiment, after generating the optimization suggestions based on the problem items, it further includes:

[0019] After improving the vehicle based on the optimization suggestions, re-perform an automated test on the vehicle, and return to execute the steps of obtaining the working condition data, road condition data, and NVH signal of the vehicle during the automated test.

[0020] In a second aspect, an embodiment of the present application provides an NVH performance determination device, where the NVH performance determination device includes:

[0021] An acquisition module for acquiring the working condition data, road condition data, and NVH signal of the vehicle during the automated test. During the automated test, the vehicle is controlled to travel along a preset path by a robot according to a preset driving action, where the preset driving action and the preset path are formulated based on the test requirements;

[0022] A determination module for determining signal features based on the NVH signal;

[0023] An identification module for inputting the signal features into an identification model to obtain an identification result output by the identification model, where the identification result includes the distribution, intensity, and source of noise and vibration;

[0024] A generation module for generating an NVH performance report by combining the working condition data, road condition data, and identification result.

[0025] Combined with the second aspect, in one embodiment, the NVH performance determination device further includes an optimization module for:

[0026] Compare the standard NVH performance report corresponding to the working condition data and road condition data with the NVH performance report, and determine problem items based on the comparison results;

[0027] Generate optimization suggestions based on the problem items.

[0028] Combined with the second aspect, in an implementation, the NVH performance determination device further includes a loop module for:

[0029] After improving the vehicle based on the optimization suggestions, re-perform an automated test on the vehicle, and notify the acquisition module to execute the steps of acquiring the working condition data, road condition data, and NVH signals of the vehicle during the automated test.

[0030] In a third aspect, an embodiment of the present application provides an NVH performance determination device, which includes a processor, a memory, and an NVH performance determination program stored on the memory and executable by the processor. When the NVH performance determination program is executed by the processor, the steps of the NVH performance determination method described in the first aspect are implemented.

[0031] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which an NVH performance determination program is stored. When the NVH performance determination program is executed by a processor, the steps of the NVH performance determination method described in the first aspect are implemented.

[0032] The beneficial effects brought by the technical solutions provided in the embodiments of the present application include:

[0033] In the embodiments of the present application, the working condition data, road condition data, and NVH signals of the vehicle during the automated test are acquired. Among them, during the automated test, the robot controls the vehicle to drive along a preset path according to preset driving actions, and the preset driving actions and preset path are formulated based on test requirements; the signal characteristics are determined based on the NVH signals; the signal characteristics are input into the recognition model to obtain the recognition results output by the recognition model, and the recognition results include the distribution, intensity, and source of noise and vibration; combined with the working condition data, road condition data, and recognition results, an NVH performance report is generated. Through the embodiments of the present application, the robot controls the vehicle to drive along a preset path according to preset driving actions, ensuring the consistency of the automated tests for the same test requirements. On this basis, an NVH performance report is generated through data processing, greatly avoiding human participation and ensuring the objectivity of the NVH performance evaluation results. Description of the Drawings

[0034] Figure 1 It is a schematic flowchart of the first embodiment of the NVH performance determination method of the present application;

[0035] Figure 2 It is a schematic flowchart of the second embodiment of the NVH performance determination method of the present application;

[0036] Figure 3 It is a schematic flowchart of the third embodiment of the NVH performance determination method of the present application;

[0037] Figure 4 It is a schematic diagram of the functional modules of an embodiment of the NVH performance determination device of the present application;

[0038] Figure 5 It is a schematic diagram of the hardware structure of the NVH performance determination device involved in the solution of the embodiment of the present application. Specific embodiments

[0039] In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0040] To make the purpose, technical solution and advantages of the present application clearer, the embodiments of the present application will be further described in detail below with reference to the accompanying drawings.

[0041] In a first aspect, an embodiment of the present application provides an NVH performance determination method.

[0042] In one embodiment, with reference to Figure 1 , Figure 1 It is a schematic flowchart of the first embodiment of the NVH performance determination method of the present application. As Figure 1 shown, the NVH performance determination method includes:

[0043] Step S10, obtaining the working condition data, road condition data, and NVH signals of the vehicle during the automated test. Among them, during the automated test, the robot controls the vehicle to travel along a preset path according to a preset driving action, and the preset driving action and the preset path are formulated based on the test requirements;

[0044] In this embodiment, taking the test requirement of testing the NVH performance of a vehicle traveling at 80 km / h on a bumpy road as an example, the preset driving actions include the throttle control action for controlling the vehicle to travel at 80 km / h, and the preset path includes Path 1, where the flatness of Path 1 is poor. Taking the test requirement of testing the NVH performance of a vehicle during the acceleration process (0 - 100 km / h) on a bumpy road as an example, the preset driving actions include the throttle control action for controlling the vehicle to accelerate from 0 to 100 km / h, and the preset path includes Path 1, where the flatness of Path 1 is poor. And so on, corresponding preset driving actions and preset paths are formulated based on the test requirements, so that the solution of this application is applicable to various test requirements.

[0045] Among them, the operating condition data includes vehicle speed, acceleration, engine speed, motor speed, transmission speed, and steering wheel angle; the road condition data includes the flatness and type of the road surface where the vehicle is located; the NVH signals include the signals collected by the accelerometer and the signals collected by the microphone.

[0046] It should be noted that the above is only a schematic description of the operating condition data and the road condition data. The specific composition of the operating condition data and the road condition data is formulated according to actual needs and is not limited here.

[0047] Further, in one embodiment, before step S10, it further includes:

[0048] Performing time synchronization processing on the sensors for collecting NVH signals.

[0049] In this embodiment, the sensors for collecting NVH signals include an accelerometer and a microphone. Performing time synchronization processing on the two sensors can eliminate invalid tests caused by asynchronous data sources and precisely match the time-frequency characteristics of the vibration / noise signals by unifying the time reference. Among them, the time synchronization processing can be implemented based on solutions such as PTP time synchronization, GPS time synchronization, or hardware time synchronization.

[0050] It should be noted that it can also be performing time synchronization processing on the sensors for collecting operating condition data, road condition data, and NVH signals. Thus, by unifying the time reference, the time-frequency characteristics of the vibration / noise signals can be precisely matched under the same operating conditions and road conditions.

[0051] Step S20, determining signal characteristics based on the NVH signals;

[0052] In this embodiment, the signal characteristics are the characteristic values of the NVH signals, which may include the peak value of the vibration signal, the peak value of the noise signal, the law of change of the vibration signal over time, the law of change of the noise signal over time, and so on. Based on the required characteristic values, the NVH signals are processed according to the corresponding characteristic extraction methods to obtain the signal characteristics.

[0053] Further, in one embodiment, step S20 includes:

[0054] Perform denoising processing on the NVH signal to obtain a new NVH signal;

[0055] Perform feature statistics on the new NVH signal to obtain signal features, where the signal features include the mean, variance, and peak value of the new NVH signal.

[0056] In this embodiment, there are various choices for denoising processing. For example, perform denoising processing on the NVH signal by means of wavelet threshold denoising. Its principle is to utilize the multi-resolution characteristic of wavelet transform to decompose the NVH signal into high-frequency and low-frequency components of different scales. According to the different intensity distribution characteristics of the noise and the wavelet coefficients of the NVH signal in different frequency bands, remove the wavelet coefficients corresponding to the noise, retain the wavelet decomposition coefficients of the NVH signal, and then perform wavelet reconstruction to obtain a new NVH signal.

[0057] Alternatively, perform denoising processing on the NVH signal by means of blind source separation (BSS). Its principle is to decouple the multi-channel mixed signal into independent source signals through independent component analysis (ICA) or non-negative matrix factorization (NMF), and separate the background noise and the target NVH component.

[0058] After the denoising processing is completed, extract the time-frequency characteristics of the new NVH signal through short-time Fourier transform (STFT) or wavelet transform, and then calculate statistics such as the mean, variance, and peak value of the new NVH signal.

[0059] Step S30: Input the signal features into the recognition model to obtain the recognition result output by the recognition model. The recognition result includes the distribution, intensity, and source of noise and vibration;

[0060] In this embodiment, the model basis of the recognition model can select the convolutional neural network CNN model. The recognition model is obtained by training the CNN model with multiple pre-constructed sample pairs. Among them, each sample pair consists of an input sample and a label. The input sample is the mean, variance, and peak value of the NVH signal in a scene, and the label is the distribution, intensity, and source of noise and vibration in this scene. Of course, other types of neural network models can also be selected, which are not limited here.

[0061] Referring to the above description, input the signal features into the recognition model, and the recognition result including the distribution, intensity, and source of noise and vibration output by the recognition model can be obtained.

[0062] Step S40: Generate an NVH performance report by combining the working condition data, road condition data, and recognition result.

[0063] In this embodiment, based on the recognition result and combining with the working condition data and road condition data that generate the NVH signal, an NVH performance report can be obtained. Exemplarily, an NVH performance report is as follows:

[0064] When the vehicle is driving on a bumpy road at a speed of 80 km / h, the noise distribution is at the driver's seat, the maximum decibel is 50 dB, and the source is the tire; the vibration distribution is at the door and chassis, the maximum amplitude is 7 μm, and the sources are the generator and the engine.

[0065] In the embodiment of the present application, the working condition data, road condition data, and NVH signal of the vehicle during the automated test are obtained. During the automated test, the robot controls the vehicle to drive along a preset path according to a preset driving action. The preset driving action and the preset path are formulated based on the test requirements; the signal characteristics are determined based on the NVH signal; the signal characteristics are input into the recognition model to obtain the recognition result output by the recognition model. The recognition result includes the distribution, intensity, and source of noise and vibration; the NVH performance report is generated by combining the working condition data, road condition data, and the recognition result. Through the embodiment of the present application, the robot controls the vehicle to drive along a preset path according to a preset driving action, which ensures the consistency of the automated test for the same test requirement. On this basis, the NVH performance report is generated by processing the data, greatly avoiding human participation and ensuring the objectivity of the NVH performance evaluation result.

[0066] Further, in one embodiment, referring to Figure 2 , Figure 2 is a schematic flowchart of the second embodiment of the NVH performance determination method of the present application. As Figure 2 shown, after step S40, the following steps are further included:

[0067] Step S50, comparing the standard NVH performance report corresponding to the working condition data and road condition data with the NVH performance report, and determining the problem items based on the comparison result;

[0068] Step S60, generating optimization suggestions based on the problem items.

[0069] In this embodiment, it is assumed that the NVH performance report generated in step S40 is as follows:

[0070] When the vehicle is driving on a bumpy road at a speed of 80 km / h, the noise distribution is at the driver's seat, the maximum decibel is 50 dB, and the source is the tire; the vibration distribution is at the door and chassis, the maximum amplitude is 7 μm, and the sources are the generator and the engine.

[0071] The standard NVH performance report corresponding to the vehicle driving on a bumpy road at a speed of 80 km / h is:

[0072] When the vehicle is driving on a bumpy road at a speed of 80 km / h, the noise distribution is mainly in the driver's seat, the maximum decibel is 30 dB - 45 dB, and the source is the tire. The vibration distribution is in the chassis, the maximum amplitude is 10 um, and the source is the generator.

[0073] Compare the generated NVH performance report with the standard NVH performance report, and use the inconsistent content as problem items. Combining the above example, after comparison, the problem items determined based on the comparison results include:

[0074] The maximum decibel of the noise exceeds the standard, the noise sources include the tire, the vibration distribution points increase the door, and the vibration sources increase the engine.

[0075] Based on the problem items, search for the solution table to generate optimization suggestions. Among them, the solution table is pre-constructed and can record the solutions corresponding to various abnormal situations based on actual experience. For example:

[0076] When the maximum decibel of the noise exceeds the standard, the solutions for various noise sources are as follows: when the maximum decibel of the noise exceeds the standard and the noise source includes the generator, the corresponding solution is Solution 1; when the maximum decibel of the noise exceeds the standard and the noise source includes the engine, the corresponding solution is Solution 2; when the maximum decibel of the noise exceeds the standard and the noise source includes the wheel, the corresponding solution is Solution 3.

[0077] Similarly, when the vibration distribution points include the door, the corresponding solution is Solution 4; when the vibration distribution points include the window, the corresponding solution is Solution 5; when the vibration distribution points include the chassis, the corresponding solution is Solution 6.

[0078] Similarly, when the vibration source includes the engine, the corresponding solution is Solution 7; when the vibration source includes the generator, the corresponding solution is Solution 8.

[0079] And so on, record the solutions corresponding to various abnormal situations in the solution table. The specific content of each solution can be optimized from the design level: put forward improvement suggestions for weak links (such as adding sound insulation materials); optimize from the control level: adjust the control strategy (such as engine speed control); optimize from the material level: recommend the use of high-performance materials (such as shock-absorbing rubber); optimize from the process level: improve the manufacturing process (such as welding accuracy, assembly process, etc.); specifically set according to the actual situation, and there is no limit here.

[0080] Combining the above description, when the problem items determined based on the comparison results include that the maximum decibel of the noise exceeds the standard, the noise sources include the tire, the vibration distribution points increase the door, and the vibration sources increase the engine, by searching the solution table, Solutions 3, 4, and 8 can be found. On this basis, optimization suggestions can be generated in combination with Solutions 3, 4, and 8.

[0081] Further, in one embodiment, referring to Figure 3 , Figure 3 which is a schematic flowchart of the third embodiment of the NVH performance determination method of the present application. As Figure 3 shown, after step S60, it further includes:

[0082] After improving the vehicle based on the optimization suggestions, re-perform an automated test on the vehicle, and return to execute step S10.

[0083] In this embodiment, it is assumed that the vehicle is improved based on Solutions 3, 4, and 8 included in the optimization suggestions. After the improvement, re-perform an automated test on the vehicle. Among them, preset driving actions and a preset path can be formulated based on the same test requirements as described above, and during the automated test, the robot controls the vehicle to travel along the preset path according to the preset driving actions, and then execute steps S10 to S40 again, thereby generating a new NVH performance report. Based on the new NVH performance report, it can be verified whether the optimization actions are effective.

[0084] The above process can be looped multiple times, so as to continuously optimize the NVH performance of the vehicle through a feedback mechanism. Among them, the loop can be stopped when there are no problem items or a stop instruction is received.

[0085] In a second aspect, an embodiment of the present application further provides an NVH performance determination device.

[0086] In one embodiment, referring to Figure 4 , Figure 4 which is a schematic diagram of the functional modules of an embodiment of the NVH performance determination device of the present application. As Figure 4 shown, the NVH performance determination device includes:

[0087] An acquisition module 10, configured to acquire the operating condition data, road condition data, and NVH signals of the vehicle during the automated test. During the automated test, the robot controls the vehicle to travel along the preset path according to the preset driving actions, where the preset driving actions and the preset path are formulated based on the test requirements;

[0088] A determination module 20, configured to determine the signal characteristics based on the NVH signals;

[0089] An identification module 30, configured to input the signal characteristics into an identification model to obtain an identification result output by the identification model, where the identification result includes the distribution, intensity, and source of noise and vibration;

[0090] A generation module 40, configured to generate an NVH performance report by combining the operating condition data, road condition data, and the identification result.

[0091] Further, in one embodiment, the NVH performance determination device further includes a time synchronization module for:

[0092] Performing time synchronization processing on the sensors for collecting NVH signals.

[0093] Further, in one embodiment, the determination module 20 is used for:

[0094] Performing denoising processing on the NVH signals to obtain new NVH signals;

[0095] Performing feature statistics on the new NVH signals to obtain signal features, where the signal features include the mean, variance, and peak value of the new NVH signals.

[0096] Further, in one embodiment, the NVH performance determination device further includes an optimization module for:

[0097] Comparing the standard NVH performance report corresponding to the working condition data and road condition data with the NVH performance report, and determining problem items based on the comparison result;

[0098] Generating optimization suggestions based on the problem items.

[0099] Further, in one embodiment, the NVH performance determination device further includes a loop module for:

[0100] After improving the vehicle based on the optimization suggestions, re-performing an automated test on the vehicle, and notifying the acquisition module to execute the steps of acquiring the working condition data, road condition data, and NVH signals of the vehicle during the automated test.

[0101] Wherein, the function implementation of each module in the above NVH performance determination device corresponds to each step in the above NVH performance determination method embodiment, and its function and implementation process will not be elaborated herein one by one.

[0102] In a third aspect, an embodiment of the present application provides an NVH performance determination device, and the NVH performance determination device can be a device with data processing functions such as a personal computer (PC), a laptop computer, a server, etc.

[0103] Referring to Figure 5 , Figure 5 is a schematic diagram of the hardware structure of the NVH performance determination device involved in the embodiment of the present application. In the embodiment of the present application, the NVH performance determination device may include a processor, a memory, a communication interface, and a communication bus.

[0104] Among them, the communication bus can be of any type and is used to interconnect the processor, memory, and communication interface.

[0105] The communication interface includes input / output (I / O) interfaces, physical interfaces, and logical interfaces, etc., which are used to interconnect the components inside the NVH performance determination device, and interfaces for interconnecting the NVH performance determination device with other devices (such as other computing devices or user devices). The physical interface can be an Ethernet interface, a fiber optic interface, an ATM interface, etc.; the user device can be a display, a keyboard, etc.

[0106] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical memory, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0107] The processor can be a general-purpose processor, and the general-purpose processor can call the NVH performance determination program stored in the memory and execute the NVH performance determination method provided by the embodiments of the present application. For example, the general-purpose processor can be a central processing unit (CPU).

[0108] Among them, when the NVH performance determination program is called, it executes the following method:

[0109] Obtain the working condition data, road condition data, and NVH signals of the vehicle during the automated test. During the automated test, the robot controls the vehicle to travel along a preset path according to preset driving actions, where the preset driving actions and the preset path are formulated based on the test requirements;

[0110] Determine the signal characteristics based on the NVH signals;

[0111] Input the signal characteristics into the recognition model to obtain the recognition result output by the recognition model. The recognition result includes the distribution, intensity, and source of noise and vibration;

[0112] Combine the working condition data, road condition data, and recognition result to generate an NVH performance report.

[0113] Further, in one embodiment, when the NVH performance determination program is called, the following method is also executed:

[0114] Perform time synchronization processing on the sensors for collecting NVH signals.

[0115] Further, in one embodiment, when the NVH performance determination program is called, the following method is also executed:

[0116] Denoise the NVH signals to obtain new NVH signals;

[0117] Perform feature statistics on the new NVH signals to obtain signal features, where the signal features include the mean, variance, and peak value of the new NVH signals.

[0118] Further, in one embodiment, when the NVH performance determination program is called, the following method is also executed:

[0119] Compare the standard NVH performance report corresponding to the working condition data and road condition data with the NVH performance report, and determine problem items based on the comparison result;

[0120] Generate optimization suggestions based on the problem items.

[0121] Further, in one embodiment, when the NVH performance determination program is called, the following method is also executed:

[0122] After improving the vehicle based on the optimization suggestions, re-perform automated testing on the vehicle, and return to execute the steps of obtaining the working condition data, road condition data, and NVH signals of the vehicle during the automated testing.

[0123] For specific embodiments of the method executed when the NVH performance determination program is called, reference can be made to the various embodiments of the NVH performance determination method of this application, which will not be elaborated here.

[0124] Those skilled in the art can understand that Figure 5 the hardware structure shown in does not constitute a limitation to this application, and may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0125] Fourthly, an embodiment of this application also provides a computer-readable storage medium.

[0126] The NVH performance determination program is stored on the computer-readable storage medium of this application. When the NVH performance determination program is executed by a processor, the steps of the NVH performance determination method as described above are implemented.

[0127] Among them, the method implemented when the NVH performance determination program is executed may refer to the various embodiments of the NVH performance determination method of the present application, which will not be elaborated here.

[0128] It should be noted that the serial numbers of the embodiments of the present application above are only for description and do not represent the superiority or inferiority of the embodiments.

[0129] The terms "including" and "having" and any variations thereof in the specification, claims and drawings of the present application are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally further include unlisted steps or units, or may optionally further include other steps or units inherent to these processes, methods, products or devices. The descriptions of terms such as "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit that "first", "second" and "third" are different types.

[0130] In the description of the embodiments of the present application, words such as "exemplary", "for example" or "for instance" are used to indicate examples, illustrations or explanations. Any embodiment or design solution described as "exemplary", "for example" or "for instance" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary", "for example" or "for instance" is intended to present relevant concepts in a specific manner.

[0131] In the description of the embodiments of the present application, unless otherwise specified, " / " means "or". For example, A / B may mean A or B; "and / or" in the text is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B may mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of the present application, "a plurality of" means two or more than two.

[0132] In some processes described in the embodiments of the present application, there are multiple operations or steps that appear in a specific order. However, it should be understood that these operations or steps may not be executed in the order in which they appear in the embodiments of the present application or may be executed in parallel. The serial numbers of the operations are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed in sequence or in parallel, and these operations or steps may be combined.

[0133] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation manner. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disc) as described above and includes several instructions for causing a terminal device to execute the methods described in various embodiments of the present application.

[0134] The above are only the preferred embodiments of the present application, and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present application.

Claims

1. A method for determining NVH performance, characterized in that The NVH performance determination method includes: Obtaining the working condition data, road condition data, and NVH signals of the vehicle during the automated test. During the automated test, a robot controls the vehicle to travel along a preset path according to a preset driving action, where the preset driving action and the preset path are formulated based on the test requirements; Determining the signal characteristics based on the NVH signals; Inputting the signal characteristics into an identification model to obtain the identification result output by the identification model, where the identification result includes the distribution, intensity, and source of noise and vibration; Generating an NVH performance report by combining the working condition data, road condition data, and the identification result.

2. The NVH performance determination method according to claim 1, characterized in that Before obtaining the working condition data, road condition data, and NVH signals of the vehicle during the automated test, it further includes: Performing time synchronization processing on the sensors used to collect NVH signals.

3. The NVH performance determination method according to claim 1, wherein The determining the signal characteristics based on the NVH signals includes: Performing denoising processing on the NVH signals to obtain new NVH signals; Performing feature statistics on the new NVH signals to obtain signal characteristics, where the signal characteristics include the mean, variance, and peak value of the new NVH signals.

4. The NVH performance determination method according to claim 1, wherein, After generating the NVH performance report by combining the working condition data, road condition data, and the NVH problem identification result, it further includes: Comparing the standard NVH performance report corresponding to the working condition data and the road condition data with the NVH performance report, and determining problem items based on the comparison result; Generating optimization suggestions based on the problem items.

5. The NVH performance determination method according to claim 4, wherein After generating the optimization suggestions based on the problem items, it further includes: After improving the vehicle based on the optimization suggestions, re-performing the automated test on the vehicle, and returning to execute the step of obtaining the working condition data, road condition data, and NVH signals of the vehicle during the automated test.

6. An NVH performance determination device, characterized in that, The NVH performance determination device includes: An acquisition module for obtaining the working condition data, road condition data, and NVH signals of the vehicle during the automated test. During the automated test, a robot controls the vehicle to travel along a preset path according to a preset driving action, where the preset driving action and the preset path are formulated based on the test requirements; A determination module for determining the signal characteristics based on the NVH signals; An identification module for inputting the signal characteristics into an identification model to obtain the identification result output by the identification model, where the identification result includes the distribution, intensity, and source of noise and vibration; A generation module for generating an NVH performance report by combining the working condition data, road condition data, and the identification result.

7. The NVH performance determination device according to claim 6, wherein, The NVH performance determination device further includes an optimization module for: Comparing the standard NVH performance report corresponding to the working condition data and the road condition data with the NVH performance report, and determining problem items based on the comparison result; Generating optimization suggestions based on the problem items.

8. The NVH performance determination device according to claim 7, wherein The NVH performance determination device further includes a loop module for: After improving the vehicle based on the optimization suggestions, re-performing the automated test on the vehicle, and notifying the acquisition module to execute the step of obtaining the working condition data, road condition data, and NVH signals of the vehicle during the automated test.

9. An NVH performance determination device, characterized in that, The NVH performance determination device includes a processor, a memory, and an NVH performance determination program stored on the memory and executable by the processor. When the NVH performance determination program is executed by the processor, the steps of the NVH performance determination method according to any one of claims 1 to 5 are implemented.

10. A computer-readable storage medium, characterized in that, An NVH performance determination program is stored on the computer-readable storage medium. When the NVH performance determination program is executed by a processor, the steps of the NVH performance determination method according to any one of claims 1 to 5 are implemented.

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