A method and system for testing the noise of electric drive assemblies in new energy vehicles

Abstract

This invention relates to the field of noise testing technology, and particularly to a method and system for testing the noise of electric drive assemblies in new energy vehicles. The method includes: constructing a test platform for electric drive noise; delineating a test area; drawing a traffic network distribution map within the test area; marking all road segments; acquiring real-world images of each road segment; and generating environmental data, wherein the environmental data includes at least: road condition information, type, and traffic flow. Through the test platform, the method obtains data reading permissions for the test vehicle; selects the deployment location of the audio pickup device at the electric drive assembly; collects audio data; locates the real-time position of the test vehicle; and uses a preset timestamp. This invention, by generating a test report, can intuitively display the road segments corresponding to the noise and perform correlation analysis between noise data and road attributes, thereby quickly identifying concentrated areas of abnormal noise and improving the accuracy and readability of noise test results.

Description

Technical Field

[0001] This invention relates to the field of noise testing technology, and in particular to a method and system for testing the noise of electric drive assemblies in new energy vehicles. Background Technology

[0002] The electric drive system is the core drive system of new energy vehicles. It typically includes components such as motors, reducers and inverters. To improve the overall comfort of new energy vehicles, noise tests are usually conducted on the electric drive system during vehicle use to evaluate its noise performance.

[0003] In existing technologies, such tests are usually conducted in laboratory test benches or rack environments. These environments offer good enclosure and load stability, which is beneficial for controlling variables and obtaining highly repeatable data. However, due to significant differences between the test environment and real road driving conditions, such as uneven road surfaces, vehicle acceleration and deceleration, ambient temperature changes, and the coupling between the electric drive system and the vehicle structure, laboratory tests cannot fully reflect the impact of these dynamic changes on noise. This results in a certain deviation between the noise data obtained and the noise generated during actual vehicle operation. This deviation makes it difficult to evaluate the noise of the electric drive assembly under actual operating conditions using laboratory test data.

[0004] Therefore, "how to conduct noise testing on the electric drive assembly of road vehicles" is the technical problem that this invention aims to solve. Summary of the Invention

[0005] The purpose of this invention is to provide a noise testing method and system for electric drive assemblies of new energy vehicles, so as to solve the problem of "how to test the noise of electric drive assemblies of vehicles on the road" mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for testing the noise of an electric drive assembly in a new energy vehicle, the method comprising:

[0008] Construct a test platform for electric drive noise, delineate the test area, draw a traffic network distribution map within the test area, mark all road segments, collect real-scene images of each road segment, and generate environmental data, wherein the environmental data includes at least: road condition information, type, and traffic flow.

[0009] Through the test platform, data reading permissions for the test vehicle are obtained, the deployment location of the audio pickup device at the electric drive assembly is selected, audio data is collected, the real-time location of the test vehicle is located, and a correspondence between the audio data and the real-time location is established through a preset timestamp.

[0010] Determine whether a sound source signal exists in the audio data. If so, traverse the road segment corresponding to the sound source signal through the correspondence and define it as the target road segment. Extract the audio data under the target road segment to obtain a segment. When the speed of the test vehicle is 0, write the segment to the preset verification pop-up window and send it to the central control device of the test vehicle. Play the segment, receive the verification result uploaded by the user, integrate the segment, verification result and target road segment, generate a test report, and synchronize the test report to the test platform.

[0011] Furthermore, the step of collecting real-scene images of each road segment and generating environmental data includes:

[0012] Using sensors pre-deployed in the test vehicle, sensor data is collected and driving behaviors are configured, including: rapid acceleration, rapid deceleration and rapid steering.

[0013] Establish a mapping between driving behaviors and segments.

[0014] Furthermore, the method also includes:

[0015] Based on the environmental data, standard segments are selected from the road segments, and the audio data corresponding to the standard segments are defined as feature data.

[0016] The feature data is clustered into several categories and then integrated to generate a feature set.

[0017] Furthermore, the steps of obtaining data reading permissions for the test vehicle via the test platform, selecting the deployment location of the audio pickup device at the electric drive assembly, and collecting audio data include:

[0018] An anomaly set consisting of several abnormal features is inserted into the feature set to determine whether there are abnormal features in the audio data, wherein the abnormal features include at least: electromagnetic noise, bearing failure and gear meshing abnormality;

[0019] Edit emergency rules that correspond one-to-one with the aforementioned abnormal features.

[0020] Furthermore, the step of extracting audio data from the target road segment to obtain a fragment includes:

[0021] Integrate all the microphones to build a microphone array;

[0022] Record the pickup times of different audio pickup devices and determine the approximate location where the segment was generated.

[0023] Furthermore, the step of extracting audio data from the target road segment to obtain a fragment includes:

[0024] Embed a community module into the testing platform and publish the fragment to the community module;

[0025] The system reads comment data from the community module, compares it with a pre-built semantic dictionary, generates a response strategy, and pushes the response strategy to the central control device.

[0026] Furthermore, the method also includes:

[0027] Traverse the correspondences and mappings to calculate the number of segments corresponding to each environmental data and driving behavior;

[0028] Based on the stated quantity, risk factors are defined, driving suggestions are generated, and sent to the central control device.

[0029] Furthermore, the system includes:

[0030] The generation module is used to construct a test platform for electric drive noise, delineate the test area, draw a traffic network distribution map within the test area, mark all road segments, collect real-scene images of each road segment, and generate environmental data, wherein the environmental data includes at least: road condition information, type, and traffic flow.

[0031] The module is used to obtain data reading permissions for the test vehicle via the test platform, select the deployment position of the audio pickup device at the electric drive assembly, collect audio data, locate the real-time position of the test vehicle, and establish a correspondence between the audio data and the real-time position via a preset timestamp.

[0032] The synchronization module is used to determine whether there is a sound source signal in the audio data. If so, it traverses the road segment corresponding to the sound source signal through the correspondence and defines it as the target road segment. It extracts the audio data under the target road segment to obtain a segment. When the speed of the test vehicle is 0, the segment is written to the preset verification pop-up window and sent to the central control device of the test vehicle. The segment is played, the verification result uploaded by the user is received, the segment, the verification result and the target road segment are integrated, a test report is generated, and the test report is synchronized to the test platform.

[0033] Furthermore, the generation module includes:

[0034] The configuration unit is used to collect sensor data using sensors pre-deployed in the test vehicle and configure driving behaviors, including: rapid acceleration, rapid deceleration and rapid steering.

[0035] The mapping unit is used to establish a mapping between driving behavior and segments.

[0036] Furthermore, the establishment module includes:

[0037] The judgment unit is used to insert an anomaly set consisting of several abnormal features into the feature set, and to determine whether there are abnormal features in the audio data, wherein the abnormal features include at least: electromagnetic noise, bearing failure and gear meshing abnormality;

[0038] The editing unit is used to edit emergency rules that correspond one-to-one with the abnormal features.

[0039] Compared with the prior art, the beneficial effects of the present invention are:

[0040] By identifying road segments and corresponding environmental data, the representativeness and comprehensiveness of test data can be improved, ensuring that test vehicles can cover a variety of real-world driving scenarios and obtain more comprehensive and realistic noise data. By deploying sound pickup devices, noise data of test vehicles during operation can be accurately collected, assisting in locating noise sources and improving the accuracy of noise testing in real-world scenarios. By pushing verification pop-ups to the central control device, noise data can be manually verified, further improving the efficiency of sound source signal identification. By generating test reports, road segments that frequently generate noise can be intuitively displayed. By correlating noise data with road attributes, concentrated areas of abnormal noise can be quickly identified, improving the accuracy and readability of noise test results. Attached Figure Description

[0041] Figure 1 A flowchart illustrating the noise testing method for electric drive assemblies of new energy vehicles provided in this embodiment of the invention;

[0042] Figure 2 This is a first sub-flowchart of the noise testing method for electric drive assemblies of new energy vehicles provided in an embodiment of the present invention;

[0043] Figure 3 This is a second sub-flowchart of the noise testing method for electric drive assemblies of new energy vehicles provided in an embodiment of the present invention;

[0044] Figure 4 This is a third sub-flowchart of the noise testing method for electric drive assemblies of new energy vehicles provided in an embodiment of the present invention;

[0045] Figure 5 This is a block diagram of the composition of the new energy vehicle electric drive assembly noise testing system provided in an embodiment of the present invention;

[0046] Figure 6 A block diagram of the generation module in the new energy vehicle electric drive assembly noise testing system provided in an embodiment of the present invention;

[0047] Figure 7 A block diagram of the module composition in the noise testing system for electric drive assemblies of new energy vehicles provided in an embodiment of the present invention;

[0048] Figure 8 This is a block diagram of the synchronization module in the noise testing system for electric drive assemblies of new energy vehicles provided in an embodiment of the present invention. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0050] In Example 1, Figure 1 The implementation flow of the noise testing method for electric drive assemblies of new energy vehicles provided in this embodiment of the invention is illustrated below, and is described in detail below:

[0051] S100: Construct a test platform for electric drive noise, delineate the test area, draw a traffic network distribution map within the test area, mark all road segments, collect real-world images of each road segment, and generate environmental data, wherein the environmental data includes at least: road condition information, type, and traffic flow.

[0052] A testing platform is constructed, primarily for processing noise data and managing test reports, similar to existing road test systems. A test area is defined, which can be an administrative region or a manually designated area. Traffic network information for the test area is collected from publicly available data, identifying environmental data such as main roads, auxiliary roads, intersections, tunnels, and bridges. Labeling environmental data not only provides detailed evidence for the correlation analysis between noise and the external environment but also assists in road segment classification, test condition division, abnormal condition screening, and noise cause tracing, thereby improving the data analysis accuracy of the testing platform.

[0053] Using traffic network information, a traffic network distribution map is drawn, and each road is divided into several segments on the map, with traffic lights and important facilities as intervals. The advantage of doing this is that it can refine the granularity of noise testing and determine the degree of impact of road conditions on noise testing. Real-world images of each road segment are collected from map service providers or using the onboard cameras of test vehicles. The image content is analyzed using image recognition and computer vision technologies to extract key environmental data, including road condition information (such as whether there are potholes, cracks, and slippery surfaces), road type (such as urban roads, highways, tunnels, bridges, and intersections), and traffic flow (through vehicle count statistics, speed estimation, etc.).

[0054] S200: Through the test platform, obtain data reading permission for the test vehicle, select the deployment position of the audio pickup device at the electric drive assembly, collect audio data, locate the real-time position of the test vehicle, and establish the correspondence between audio data and real-time position through a preset timestamp.

[0055] In the testing platform, drivers willing to participate in the electric drive assembly noise test are selected, and the corresponding vehicles are defined as test vehicles. Test vehicles should be new energy vehicles. Before the test, a sound pickup device needs to be installed in the test vehicle, and data reading permissions for the test vehicle need to be obtained. Furthermore, based on the structural layout of the electric drive system, the sound pickup device should be installed in a location close to the main noise source. The sound pickup device can be a magnetic microphone or an adhesive sound pickup device, etc. Specific installation locations can be: near the motor housing, the gearbox housing, the inverter side, or around the drive axle. The installation location should avoid overlapping with high-frequency vibration sources or areas of strong wind noise to reduce interference and improve the signal-to-noise ratio.

[0056] In actual deployment, the audio pickup devices are installed in structurally stable locations with short propagation paths to collect audio data from the test vehicle during its journey, pinpointing the vehicle's real-time location. A preset timestamp is then used to synchronize the real-time location with the collected audio data. Specifically, high-precision GPS is used to record the vehicle's latitude and longitude coordinates within the test area in real time. Simultaneously, a unified timestamp format is assigned to each audio pickup device, aligning the real-time location with the audio data in time, thus establishing a one-to-one correspondence in temporal sequence.

[0057] S300: Determine whether there is a sound source signal in the audio data. If so, traverse the road segment corresponding to the sound source signal through the correspondence and define it as the target road segment. Extract the audio data under the target road segment to obtain a segment. When the speed of the test vehicle is 0, write the segment to the preset verification pop-up window and send it to the central control device of the test vehicle. Play the segment, receive the verification result uploaded by the user, integrate the segment, verification result and target road segment, generate a test report, and synchronize the test report to the test platform. It should be noted that in this application, the user refers to the driver of the test vehicle.

[0058] Audio data is processed using spectrum analysis, short-time Fourier transform, or deep learning-based sound source identification algorithms to detect the presence of characteristic sound source signals (such as howling, electromagnetic noise, structural resonance, or rupture). If a sound source signal is identified, the road segment where the vehicle was located when the sound source signal was generated is determined based on the correspondence and defined as the target road segment. The audio data generated in the target road segment is defined as a segment.

[0059] When the test vehicle's speed is detected to be 0, indicating that the test vehicle is stationary, the previously identified and captured noise segment is written into a preset verification pop-up window and sent to the test vehicle's central control device via the vehicle communication module. Upon receiving the segment, the central control device immediately plays the corresponding audio, allowing the test vehicle driver to perform subjective auditory verification (whether or not the noise is heard) while the vehicle is stationary and safe. In addition, the test vehicle driver can also provide feedback on the specific noise perception through the verification pop-up window. The driver's subjective auditory verification and noise perception are uploaded to the test platform to obtain the verification results. The segment, verification results, and target road segment are written into a preset template to generate a test report, which is then synchronized to the test platform.

[0060] Professionals on the testing platform extract characteristic signals from the corresponding audio data by querying verification results and segments, determine the specific noise type, and formulate specific noise treatment methods based on environmental data of the target road section and practical experience.

[0061] In Example 2, Figure 2 The implementation flow of the noise testing method for the electric drive assembly of new energy vehicles provided by an embodiment of the present invention is shown. The steps of collecting real-scene images of each road segment and generating environmental data are described in detail below:

[0062] S101: Using sensors pre-deployed in the test vehicle, collect sensor data and configure driving behaviors, wherein the driving behaviors include: rapid acceleration, rapid deceleration and rapid steering.

[0063] In the testing platform, sensing devices pre-deployed in the test vehicle, such as accelerometers, gyroscopes, steering wheel angle sensors, and accelerator / brake pedal position sensors, are used to collect dynamic sensing data of the test vehicle in real time. Based on the changing trends of the sensing data, specific driving behaviors are configured, including rapid acceleration, rapid deceleration, and sharp steering.

[0064] S102: Establish a mapping between driving behavior and segments.

[0065] The audio data is used to extract segments of each driving action and establish a mapping; the advantage of this is that it captures environmental data that is most likely to trigger abnormal noise, thus improving the accuracy of sound source identification.

[0066] In Example 3, Figure 3 The implementation flow of the noise testing method for the electric drive assembly of a new energy vehicle provided by an embodiment of the present invention is shown below. The steps of obtaining data reading permissions for the test vehicle via the test platform, selecting the deployment position of the audio pickup device at the electric drive assembly, and collecting audio data are described in detail below:

[0067] S201: Insert an anomaly set consisting of several abnormal features into the feature set, and determine whether there are abnormal features in the audio data, wherein the abnormal features include at least: electromagnetic noise, bearing failure and gear meshing abnormality.

[0068] An anomaly set consisting of abnormal features is created and integrated into a feature set. The anomaly set can be obtained through historical test data, laboratory simulation tests, or driver annotations, and covers typical fault noise features. Among them, abnormal features include electromagnetic noise (such as periodic howling caused by stator eccentricity and electromagnetic force fluctuations), bearing failure (such as impact-type high-frequency noise caused by rolling element damage), gear meshing abnormalities (such as meshing periodic vibration sound caused by tooth surface wear or poor meshing), etc. These abnormal features usually have specific frequency domain, time domain, or envelope spectrum features.

[0069] S202: Edit emergency rules that correspond one-to-one with the aforementioned abnormal features.

[0070] When abnormal features are found in the audio data, the corresponding emergency rule is activated. The emergency rule is to trigger an alarm sound to remind the driver to stop immediately.

[0071] In Example 4, Figure 4 The implementation flow of the noise testing method for electric drive assemblies of new energy vehicles provided by the present invention is shown below. The steps of extracting audio data from the target road segment to obtain a segment are described in detail below:

[0072] S301: Integrates all microphones to build a microphone array.

[0073] Integrate all the audio pickup devices deployed in the test vehicle to build an audio pickup array. An audio pickup array is a collection of multiple audio pickup devices arranged in a preset geometric layout (such as a linear array, area array, or ring array). The audio pickup array should cover the key areas of the electric drive assembly, including the motor, gearbox, inverter, and their surrounding structures. The advantage of doing this is that it can achieve sound source localization, enhance the sound signal in the target direction, and suppress noise interference from other directions, thereby obtaining clearer and more stable audio data.

[0074] S302: Record the pickup time of different audio pickup devices and determine the approximate location where the segment was generated.

[0075] Since the various audio pickup devices are distributed in different locations on the test vehicle according to the pickup array, there will be slight differences in the time when each audio pickup device receives the audio data. Based on these time differences, the time difference positioning algorithm in the existing technology is applied to calculate the relative distance from the sound source to each audio pickup device. Combined with the known spatial coordinates of the audio pickup devices, the approximate location where the audio data is generated is deduced.

[0076] In Example 5, Figure 4 The implementation flow of the noise testing method for electric drive assemblies of new energy vehicles provided by the present invention is shown below. The steps of extracting audio data from the target road segment to obtain a segment are described in detail below:

[0077] S303: Embed the community module into the test platform and publish the fragment to the community module.

[0078] An embedded community module is added to the testing platform, and detected segments are published to this community module. The community module serves as an interactive and knowledge-sharing space within the platform, supporting test engineers, acoustic experts, and ordinary users to centrally browse, evaluate, comment on, and tag segments.

[0079] S304: Read the comment data in the community module, compare it with the pre-built meaning dictionary, generate a response strategy, and push the response strategy to the central control device.

[0080] Using natural language processing technology, semantic words are extracted from the comment data. These semantic words are words with practical meaning. They are then compared with a pre-built semantic dictionary, which contains a large number of phrases related to noise type, fault characteristics, user experience, and suggested measures. Semantic word groups are categorized according to their meaning. For example, words such as "harsh," "metallic friction," and "motor whistling" are classified as high-risk sound sources, while words such as "suggest adjusting gear meshing" and "reduce electromagnetic excitation frequency" are matched as coping strategy groups. Coping strategies are the methods for handling the faults corresponding to different semantic words. In practice, after a clip is published, the coping strategies corresponding to the semantic words in the comment data are read and pushed to the central control device to provide drivers with a reference for adjustments.

[0081] In Example 6, unlike Example 1, the method further includes:

[0082] Based on the environmental data, standard segments are selected from the road segments, and the audio data corresponding to the standard segments are defined as feature data.

[0083] The feature data is clustered into several categories and then integrated to generate a feature set.

[0084] A standard section refers to a typical road environment, such as a flat, dry urban road, a highway with low traffic flow, or a short or long uphill section. These road sections are defined as standard sections. When the test vehicle is in a standard section, the audio data from the electric drive assembly is defined as feature data. The feature data is then categorized and stored to obtain a feature set. For example, the feature data can be divided into smooth road types, bumpy road types, and long uphill road types. Each category represents a typical noise pattern or sound source type. This facilitates subsequent noise identification, model training, anomaly detection, or sound source information comparison.

[0085] In Example 7, unlike Example 1, the method further includes:

[0086] Traverse the correspondences and mappings to calculate the number of segments corresponding to each environmental data and driving behavior;

[0087] Based on the stated quantity, risk factors are defined, driving suggestions are generated, and sent to the central control device.

[0088] The number of segments under each type of environmental data and driving behavior is counted. The larger the number, the more likely the environment or driving behavior is to trigger noise from the electric drive assembly. When the number exceeds the threshold, the corresponding environmental data and driving behavior are defined as risk factors. Using these risk factors, driving suggestions are generated and sent to the central control device.

[0089] For example, a certain new energy vehicle's electric drive assembly recorded 420 audio data points on an uphill road, far more than the number on a downhill (170) and level road (230). The risk factor was the uphill section. By analyzing the audio data, it was determined that the motor output power increased, resulting in a more obvious electromagnetic whistling sound. The corresponding driving advice is: when going uphill, try to avoid rapid acceleration or pressing the accelerator pedal too hard, and use a smooth and linear acceleration method.

[0090] Figure 5 This invention illustrates a structural block diagram of a noise testing system for an electric drive assembly of a new energy vehicle, provided in an embodiment of the present invention. The noise testing system 1 for the electric drive assembly of a new energy vehicle includes:

[0091] The generation module 11 is used to construct a test platform for electric drive noise, delineate the test area, draw a traffic network distribution map within the test area, mark all road segments, collect real-scene images of each road segment, and generate environmental data, wherein the environmental data includes at least: road condition information, type, and traffic flow.

[0092] The module 12 is used to obtain data reading permissions for the test vehicle via the test platform, select the deployment position of the audio pickup device at the electric drive assembly, collect audio data, locate the real-time position of the test vehicle, and establish a correspondence between the audio data and the real-time position via a preset timestamp.

[0093] The synchronization module 13 is used to determine whether there is a sound source signal in the audio data. If so, it traverses the road segment corresponding to the sound source signal through the correspondence and defines it as the target road segment. It extracts the audio data under the target road segment to obtain a segment. When the speed of the test vehicle is 0, it writes the segment to the preset verification pop-up window and sends it to the central control device of the test vehicle. It plays the segment, receives the verification result uploaded by the user, integrates the segment, verification result and target road segment, generates a test report, and synchronizes the test report to the test platform.

[0094] Figure 6 This diagram illustrates the structural block diagram of a noise testing system for electric drive assemblies of new energy vehicles provided in an embodiment of the present invention. The generation module 11 includes:

[0095] Configuration unit 111 is used to collect sensing data using sensing devices pre-deployed in the test vehicle and configure driving behavior, wherein the driving behavior includes: rapid acceleration, rapid deceleration and rapid steering.

[0096] Mapping unit 112 is used to establish a mapping between driving behavior and segments.

[0097] Figure 7 This diagram illustrates the structural block diagram of a noise testing system for electric drive assemblies of new energy vehicles provided in an embodiment of the present invention. The establishment module 12 includes:

[0098] Judgment unit 121 is used to insert an anomaly set consisting of several abnormal features into the feature set, and to determine whether there are abnormal features in the audio data, wherein the abnormal features include at least: electromagnetic noise, bearing failure and gear meshing abnormality;

[0099] The editing unit 122 is used to edit emergency rules that correspond one-to-one with the abnormal features.

[0100] Figure 8 This diagram illustrates the structural block diagram of a noise testing system for electric drive assemblies of new energy vehicles provided in an embodiment of the present invention. The synchronization module 13 includes:

[0101] Integration unit 131 is used to integrate all the pickup devices and build a pickup array;

[0102] Unit 132 is used to record the pickup time of different pickup devices and determine the approximate location where the segment was generated;

[0103] Publishing unit 133 is used to embed a community module into the test platform and publish the fragment to the community module.

[0104] The push unit 134 is used to read the comment data in the community module, compare it with the pre-built meaning dictionary, generate a response strategy, and push the response strategy to the central control device.

[0105] The generation module 11 is mainly used to complete step S100, the establishment module 12 is mainly used to complete step S200, and the synchronization module 13 is mainly used to complete step S300.

[0106] Configuration unit 111 is mainly used to complete step S101, and mapping unit 112 is mainly used to complete step S102;

[0107] The judgment unit 121 is mainly used to complete step S201, and the editing unit 122 is mainly used to complete step S202;

[0108] The integration unit 131 is mainly used to complete step S301, the determination unit 132 is mainly used to complete step S302, the publishing unit 133 is mainly used to complete step S303, and the push unit 134 is mainly used to complete step S304.

[0109] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0110] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0111] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for testing the noise of an electric drive assembly in a new energy vehicle, characterized in that, The method includes: Construct a test platform for electric drive noise, delineate the test area, draw a traffic network distribution map within the test area, mark all road segments, collect real-scene images of each road segment, and generate environmental data, wherein the environmental data includes at least: road condition information, type, and traffic flow. Through the test platform, data reading permissions for the test vehicle are obtained, the deployment location of the audio pickup device at the electric drive assembly is selected, audio data is collected, the real-time location of the test vehicle is located, and a correspondence between the audio data and the real-time location is established through a preset timestamp. Determine whether there is a sound source signal in the audio data. If so, traverse the road segment corresponding to the sound source signal through the correspondence and define it as the target road segment. Extract the audio data under the target road segment to obtain a segment. When the speed of the test vehicle is 0, write the segment to the preset verification pop-up window and send it to the central control device of the test vehicle. Play the segment, receive the verification result uploaded by the user, integrate the segment, verification result and target road segment, generate a test report, and synchronize the test report to the test platform. The method further includes: Based on the environmental data, standard segments are selected from the road segments, and the audio data corresponding to the standard segments are defined as feature data. The feature data is clustered into several categories and integrated to generate a feature set; The steps of obtaining data reading permissions for the test vehicle via the test platform, selecting the deployment location of the audio pickup device at the electric drive assembly, and collecting audio data include: An anomaly set consisting of several abnormal features is inserted into the feature set to determine whether there are abnormal features in the audio data, wherein the abnormal features include at least: electromagnetic noise, bearing failure and gear meshing abnormality; Edit emergency rules that correspond one-to-one with the aforementioned abnormal features.

2. The noise testing method for electric drive assemblies of new energy vehicles according to claim 1, characterized in that, The steps of collecting real-scene images of each road segment and generating environmental data include: Using sensors pre-deployed in the test vehicle, sensor data is collected and driving behaviors are configured, including: rapid acceleration, rapid deceleration and rapid steering. Establish a mapping between driving behaviors and segments.

3. The noise testing method for electric drive assemblies of new energy vehicles according to claim 1, characterized in that, The step of extracting audio data from the target road segment to obtain a clip includes: Integrate all the microphones to build a microphone array; Record the pickup times of different audio pickup devices and determine the approximate location where the segment was generated.

4. The noise testing method for electric drive assemblies of new energy vehicles according to claim 1, characterized in that, The step of extracting audio data from the target road segment to obtain a clip includes: Embed a community module into the testing platform and publish the fragment to the community module; The system reads comment data from the community module, compares it with a pre-built semantic dictionary, generates a response strategy, and pushes the response strategy to the central control device.

5. The noise testing method for electric drive assemblies of new energy vehicles according to claim 2, characterized in that, The method further includes: Traverse the correspondences and mappings to calculate the number of segments corresponding to each environmental data and driving behavior; Based on the stated quantity, risk factors are defined, driving suggestions are generated, and sent to the central control device.

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