Vehicle Noise Performance Determination Method, Device and Storage Medium

Abstract

The present invention discloses a method, device and storage medium for determining the vehicle noise performance. The method includes: obtaining a noise evaluation index, and obtaining preset standard evaluation data constructed based on the noise evaluation index and subjective evaluation data; extracting index data from the in-vehicle noise data of the vehicle based on the noise evaluation index to obtain noise evaluation index data; assigning values to the noise evaluation index data based on the preset standard evaluation data to obtain a subjective evaluation value of the in-vehicle noise data, and determining the noise performance of the vehicle according to the target subjective evaluation value. The present invention assigns values to the noise evaluation index data in combination with the preset standard evaluation data to obtain a subjective evaluation value of the combined subjective and objective level. By predicting the subjective evaluation value through the objective value of the in-vehicle noise, the obtained subjective evaluation value of the level is highly matched with the actual subjective evaluation value of the consumer, providing an accurate basis for the design of the vehicle noise performance.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle performance research, and particularly relates to a method, device and storage medium for determining vehicle noise performance. Background Art

[0002] As consumers' requirements for vehicle ride comfort are getting higher and higher, in-vehicle sound comfort has become an important indicator for consumers to evaluate vehicle performance. The in-vehicle noise of a vehicle during high-speed driving on the road is mainly composed of road surface noise, wind noise, power noise, etc. There are many influencing factors. During the vehicle performance development period, how to correctly evaluate the in-vehicle noise performance has always been a difficult problem.

[0003] Currently, the evaluation methods for vehicle noise generally adopt objective evaluation methods or subjective evaluation methods. The objective evaluation method obtains relevant parameters of in-vehicle noise through analysis and measurement methods, and measures the vehicle noise performance through the relevant parameters of in-vehicle noise. The objective test value represents the result of engineering verification and is the ultimate expression of technology; subjective evaluation is to obtain subjective scores of relevant personnel on the vehicle noise level through forms such as questionnaire surveys or subjective evaluation tests. The subjective score represents the real-time feelings of passengers and is the actual experience of consumers. However, both of the above methods have limitations. The subjective evaluation method has different evaluation criteria for each person and does not combine the actual parameters of the vehicle, making it difficult to be used as the design basis for vehicle noise performance; the objective evaluation method is highly objective but ignores people's subjective feelings and cannot provide an accurate basis for the design of vehicle noise performance during the vehicle R & D stage. Summary of the Invention

[0004] The present invention provides a method, device and storage medium for determining vehicle noise performance to solve the problem that the existing noise evaluation methods have limitations and cannot provide an accurate basis for the design of vehicle noise performance.

[0005] A method for determining vehicle noise performance is provided, including:

[0006] Obtain noise evaluation indicators, and obtain preset standard evaluation data constructed based on the noise evaluation indicators and subjective evaluation data;

[0007] Extract index data from the in-vehicle noise data of the vehicle based on the noise evaluation indicators to obtain noise evaluation index data;

[0008] Assign values to the noise evaluation index data based on the preset standard evaluation data to obtain the target subjective evaluation value of the in-vehicle noise data;

[0009] Determine the noise performance of the vehicle according to the target subjective evaluation value.

[0010] Further, the in-vehicle noise data includes multiple sets of in-vehicle noise acquisition data. Based on the noise evaluation index, index data extraction is performed on the in-vehicle noise data to obtain noise evaluation index data, including:

[0011] Perform frequency-domain calculation on each set of in-vehicle noise acquisition data to obtain the auto-power spectrum corresponding to each set of in-vehicle noise acquisition data;

[0012] Perform energy averaging on the auto-power spectra corresponding to multiple sets of in-vehicle noise acquisition data to obtain the averaged target auto-power spectrum;

[0013] Based on the noise evaluation index, perform index data extraction on the target auto-power spectrum to obtain noise evaluation index data.

[0014] Further, the noise evaluation index includes sound pressure level and speech intelligibility. Based on the noise evaluation index, perform index data extraction on the target auto-power spectrum to obtain noise evaluation index data, including:

[0015] Perform sound pressure level calculation on the target auto-power spectrum to obtain the sound pressure level value;

[0016] Perform speech intelligibility calculation on the target auto-power spectrum to obtain the speech intelligibility value;

[0017] Take the sound pressure level value and the speech intelligibility value as the noise evaluation index data.

[0018] Further, performing frequency-domain calculation on each set of in-vehicle noise acquisition data to obtain the auto-power spectrum corresponding to each set of in-vehicle noise acquisition data includes:

[0019] Determine multiple sub-noise acquisition data within each set of in-vehicle noise acquisition data, and each sub-noise acquisition data corresponds to a collection location;

[0020] Perform frequency-domain calculation on each sub-noise acquisition data respectively to obtain the auto-power spectrum of each sub-noise acquisition data;

[0021] Perform averaging processing on the auto-power spectra of multiple sub-noise acquisition data within each set of in-vehicle noise acquisition data to obtain the average auto-power spectrum;

[0022] Take the average auto-power spectrum as the auto-power spectrum corresponding to the in-vehicle noise acquisition data.

[0023] Further, performing frequency-domain calculation on each sub-noise acquisition data respectively to obtain the auto-power spectrum of each sub-noise acquisition data includes:

[0024] Apply a window function to each sub-noise acquisition data to obtain the preprocessed data of each sub-noise acquisition data;

[0025] Perform a fast Fourier transform on the preprocessed data of each sub-noise acquisition data to obtain spectral data;

[0026] Perform a weighted conversion on the spectral data to obtain the auto-power spectrum of each sub-noise acquisition data.

[0027] Further, the noise evaluation index data includes the sound pressure level value and the speech intelligibility value. Based on the preset standard evaluation data, assign values to the noise evaluation index data to obtain the target subjective evaluation value of the vehicle interior noise data, including:

[0028] Based on the preset standard evaluation data, determine the target sound pressure level grade to which the sound pressure level value belongs, and determine the sound pressure level evaluation value according to the target sound pressure level grade;

[0029] Based on the preset standard evaluation data, determine the target speech intelligibility grade to which the speech intelligibility value belongs, and determine the speech intelligibility evaluation value according to the target speech intelligibility grade;

[0030] Take the sum of the sound pressure level evaluation value and the speech intelligibility evaluation value as the subjective evaluation value of the vehicle interior noise data.

[0031] Further, based on the preset standard evaluation data, determine the target sound pressure level grade to which the sound pressure level value belongs, and determine the sound pressure level evaluation value according to the target sound pressure level grade, including:

[0032] Obtain multiple sound pressure level grades in the preset standard evaluation data, and determine the sound pressure level value ranges corresponding to the sound pressure level grades;

[0033] Match the sound pressure level value with multiple sound pressure level value ranges, and record the sound pressure level grade corresponding to the matched sound pressure level value range as the target sound pressure level grade;

[0034] In the preset standard evaluation data, determine the subjective evaluation value corresponding to the target sound pressure level grade as the sound pressure level evaluation value.

[0035] Provide a vehicle noise performance determination device, including:

[0036] An acquisition module, configured to acquire noise evaluation indexes and acquire preset standard evaluation data constructed based on the noise evaluation indexes and subjective evaluation data;

[0037] An extraction module, configured to extract index data from the vehicle interior noise data of the vehicle based on the noise evaluation indexes to obtain noise evaluation index data;

[0038] An assignment module, configured to assign values to the noise evaluation index data based on the preset standard evaluation data to obtain the target subjective evaluation value of the vehicle interior noise data;

[0039] A determination module, configured to determine the noise performance of a vehicle according to a target subjective evaluation value.

[0040] Provided is a vehicle noise performance determination device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned vehicle noise performance determination method are implemented.

[0041] Provided is a readable storage medium storing a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned vehicle noise performance determination method are implemented.

[0042] In one solution provided by the above-mentioned vehicle noise performance determination method, device and storage medium, by obtaining a noise evaluation index, obtaining preset standard evaluation data constructed based on the noise evaluation index and subjective evaluation data, then extracting index data from the in-vehicle noise data of the vehicle based on the noise evaluation index to obtain noise evaluation index data, and then assigning values to the noise evaluation index data based on the preset standard evaluation data to obtain the subjective evaluation value of the in-vehicle noise data, and determining the noise performance of the vehicle according to the target subjective evaluation value; in the present invention, by analyzing, the noise evaluation index affecting the subjective perception of noise is obtained, then based on the preset standard evaluation data constructed from the noise evaluation index and subjective evaluation data, and then index data extraction is performed on the in-vehicle noise data, and further, in combination with the preset standard evaluation data, values are assigned to the noise evaluation index data to obtain an objective-subjective combined target subjective evaluation value. By predicting the subjective evaluation value through the objective value of the in-vehicle noise, the obtained target subjective evaluation value highly matches the actual subjective evaluation value of consumers, providing an accurate basis for the design of vehicle noise performance. Description of the Drawings

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments of the present invention. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained according to these drawings.

[0044] Figure 1 is a schematic structural diagram of a vehicle noise performance determination system in an embodiment of the present invention;

[0045] Figure 2 is a schematic flowchart of a vehicle noise performance determination method in an embodiment of the present invention;

[0046] Figure 3 is Figure 2 an implementation flowchart of step S20 in

[0047] Figure 4 isFigure 2 Schematic diagram of an implementation process of step S30 in

[0048] Figure 5 Schematic diagram of the structure of a vehicle noise performance determination device in an embodiment of the present invention;

[0049] Figure 6 Schematic diagram of another structure of a vehicle noise performance determination device in an embodiment of the present invention. Detailed implementation manners

[0050] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0051] The vehicle noise performance determination method provided by the embodiments of the present invention can be applied to a vehicle noise performance determination system as shown in Figure 1 The vehicle noise performance determination system includes a vehicle and a vehicle noise performance determination device. Among them, the vehicle communicates with the vehicle noise performance determination device through a network.

[0052] When it is necessary to evaluate the noise performance of a vehicle, such as when it is necessary to determine the noise performance of a vehicle during the vehicle R & D process to guide the vehicle performance optimization design, the vehicle noise performance determination device obtains noise evaluation indicators that affect the subjective perception of noise, and obtains preset standard evaluation data constructed based on the noise evaluation indicators and subjective evaluation data. Then, it obtains the actual in-vehicle noise data of the vehicle, and extracts index data from the in-vehicle noise data of the vehicle based on the noise evaluation indicators to obtain noise evaluation index data. Then, it assigns values to the noise evaluation index data based on the preset standard evaluation data to obtain the subjective evaluation value of the in-vehicle noise data, and determines the noise performance of the vehicle based on the target subjective evaluation value. In this embodiment, by analyzing the noise evaluation indicators that affect the subjective perception of noise, then constructing preset standard evaluation data based on the noise evaluation indicators and subjective evaluation data, and then extracting index data from the in-vehicle noise data, and further combining the preset standard evaluation data to assign values to the noise evaluation index data, a subjective evaluation value of the combination of subjective and objective levels is obtained. By predicting the subjective evaluation value through the objective value of the in-vehicle noise, the prediction standard is unified and accurate, so that the obtained subjective evaluation value of the level is highly matched with the actual subjective evaluation value of consumers, providing an accurate basis for the design of the vehicle noise performance.

[0053] In this embodiment, the vehicle noise performance determination system includes a vehicle and a vehicle noise performance determination device. For illustrative purposes only, in other embodiments, the vehicle noise performance determination system further includes a test device, which is used to conduct on-site noise tests on the vehicle to collect in-vehicle noise acquisition data during the test process of the vehicle as the in-vehicle noise data of the vehicle.

[0054] In one embodiment, as Figure 2 shown, a vehicle noise performance determination method is provided. Taking the vehicle noise performance determination device in Figure 1 as an example, the method includes the following steps:

[0055] S10: Obtain a noise evaluation index and obtain preset standard evaluation data constructed based on the noise evaluation index and subjective evaluation data.

[0056] When evaluating the noise of a vehicle, the vehicle noise performance determination device needs to obtain a noise evaluation index and preset standard evaluation data that affect the subjective perception of noise.

[0057] Among them, the noise evaluation index is based on a large number of in-vehicle noise samples during the driving process of the vehicle (especially at high speeds), as well as a large number of subjective evaluation data of users on these in-vehicle noise samples, and statistically analyzes and optimizes relevant parameters that mainly affect the subjective perception of in-vehicle noise, such as sound pressure level, speech intelligibility, etc. The preset standard evaluation data is standard unified evaluation data constructed through statistical analysis and optimization based on the noise evaluation index and a large number of subjective evaluation data of users on different noise evaluation index values.

[0058] S20: Extract index data from the in-vehicle noise data of the vehicle based on the noise evaluation index to obtain noise evaluation index data.

[0059] When evaluating the noise of a vehicle, the vehicle noise performance determination device also needs to obtain the in-vehicle noise data of the vehicle. Among them, the in-vehicle noise data includes data such as wind noise, road noise, and power system noise of the vehicle; the in-vehicle noise data is collected through sensors, and the collection position of the in-vehicle noise data is at the ear position of the vehicle occupants, such as the outer ear position of the driver, the outer ear of the co-pilot, and the outer ear positions of other passengers. The layout standard of the sensors can refer to the acoustic - measurement method for in-vehicle noise of motor vehicles with the standard number GB / T18697.

[0060] Among them, the in-vehicle noise data of the vehicle is collected through the following methods:

[0061] Determine the test environment and test road surface of the vehicle. To ensure that the acquisition environment of the in-vehicle noise data is consistent with the actual driving environment of the vehicle, it is necessary to conduct driving noise tests on the preset test road surface and test environment, so that the acquired in-vehicle noise data is a mixed noise composed of actual wind noise, road noise, power system noise, etc., making the acquired in-vehicle noise acquisition data closer to the noise environment where the occupants are located during vehicle driving. Among them, the preset test road surface needs to meet the standard GB / T 22157, that is, it needs to meet the technical specifications of the test lane for measuring the noise of road vehicles and tires in acoustics, and the preset test road surface needs to select a straight and open straight road surface as the test section. At the same time, when conducting vehicle tests, ensure that the weather of the test environment is rain-free and snow-free, and the wind speed of the test environment needs to be below 3 m / s.

[0062] Determine the acquisition positions of the in-vehicle noise data. The acquisition positions are at the ear positions of the vehicle occupants, such as the outer ear position of the driver, the outer ear of the co-driver, and the outer ear positions of other passengers, etc. Then, arrange sensors at the acquisition positions according to the preset standard. The arrangement standard of the sensors refers to the "Acoustics - Measurement Method for In-vehicle Noise of Motor Vehicles" with the standard number GB / T 18697.

[0063] After arranging the sensors at the acquisition positions according to the preset standard, control the vehicle to drive at a preset speed uniformly in the preset test environment and test road surface, so as to collect the in-vehicle noise acquisition data of the vehicle under stable driving conditions through the sensors as the in-vehicle noise data. Among them, the preset speed is determined according to the test requirements. For example, in the case of high-speed driving noise test, the preset speed is selected as 120 km / h for uniform driving.

[0064] The in-vehicle noise data collected through the above method can be consistent with the noise environment where the occupants are located during the actual driving process of the vehicle, improving the accuracy of the in-vehicle noise data and providing an accurate basis for subsequent subjective and objective evaluations based on the in-vehicle noise data.

[0065] After obtaining the in-vehicle noise data of the vehicle, the vehicle noise performance determination device extracts index data from the in-vehicle noise data of the vehicle based on the noise evaluation index to obtain the noise evaluation index data, that is, processes the in-vehicle noise data of the vehicle to obtain the index value corresponding to the noise evaluation index.

[0066] S30: Assign values to the noise evaluation index data based on the preset standard evaluation data to obtain the target subjective evaluation value of the in-vehicle noise data.

[0067] After obtaining the noise evaluation index data, that is, obtaining the index values corresponding to each noise evaluation index in the vehicle, the noise evaluation index data is assigned based on the preset standard evaluation data to obtain the target subjective evaluation value of the in-vehicle noise data. That is, according to the subjective evaluation value assignment standard of each noise evaluation index corresponding index value in the preset standard evaluation data, the subjective evaluation value corresponding to the noise evaluation index data is determined, and then the target subjective evaluation value of the in-vehicle noise data is obtained. Among them, the noise evaluation index data can be first classified according to the preset standard evaluation data, and then the noise evaluation index data is assigned according to the classified index level to obtain the target subjective evaluation value. That is, first, according to the index value range corresponding to each noise evaluation index in the preset standard evaluation data, the index level of the noise evaluation index data is determined, and then, according to the subjective evaluation value corresponding to each index level in the preset standard evaluation data, the subjective evaluation value corresponding to the index level of the noise evaluation index data is determined as the target subjective evaluation value of the in-vehicle noise data.

[0068] S40: Determine the noise performance of the vehicle based on the target subjective evaluation value.

[0069] After obtaining the target subjective evaluation value of the in-vehicle noise data, determine the noise performance of the vehicle based on the target subjective evaluation value.

[0070] Among them, a noise performance qualification threshold can be set. When the target subjective evaluation value is less than the noise performance qualification threshold, it is determined that the noise performance of the vehicle is unqualified; when the target subjective evaluation value is greater than or equal to the noise performance qualification threshold, it is determined that the noise performance of the vehicle is qualified, so as to guide the performance optimization design work of the vehicle according to whether the noise performance is qualified or not. For example, the noise performance qualification threshold is 2. When the target subjective evaluation value is less than 2, it is determined that the noise performance of the vehicle is unqualified, indicating that the noise performance of the vehicle fails to meet the design requirements and the vehicle performance-related structure needs to be redesigned; when the target subjective evaluation value is greater than or equal to 2, it is determined that the noise performance of the vehicle is qualified, indicating that the noise performance of the vehicle can meet the design requirements, and it can be considered whether the vehicle performance-related structure can be optimized according to the specific structure design and cost of the vehicle.

[0071] In other embodiments, different noise performance levels can be set in advance according to the magnitude of the target subjective evaluation value. Each noise performance level corresponds to a target subjective evaluation value range. After obtaining the target subjective evaluation value of the in-vehicle noise data, the noise performance level is determined according to the target subjective evaluation value range in which the target subjective evaluation value is located, so as to facilitate relevant personnel to guide the performance optimization design work of the vehicle based on the noise performance level of the vehicle. For example, the target subjective evaluation value is on a ten-point scale, and the noise performance levels include five levels, namely the first level, the second level, the third level, the fourth level, and the fifth level. The fifth level is the level where the noise performance is unqualified; among them, the target subjective evaluation value range of the first level is (8, 10), the target subjective evaluation value range of the second level is (6, 8), the target subjective evaluation value range of the third level is (4, 6), the target subjective evaluation value range of the fourth level is (2, 4), and the target subjective evaluation value range of the fifth level is (0, 2).

[0072] In this embodiment, the target subjective evaluation value is on a ten-point scale, and the noise performance levels include the first level, the second level, the third level, the fourth level, and the fifth level, and the target subjective evaluation value ranges of each noise performance level are only for illustrative purposes. In other embodiments, the target subjective evaluation value can be on a different scale, the specific number of levels of the noise performance levels can be other numbers, and the target subjective evaluation value ranges corresponding to each noise performance level can also be other numerical ranges, which will not be elaborated here.

[0073] In this embodiment, by obtaining the noise evaluation index that affects the subjective perception of noise, obtaining the preset standard evaluation data constructed based on the noise evaluation index and subjective evaluation data, then obtaining the actual in-vehicle noise data of the vehicle, extracting the index data from the in-vehicle noise data of the vehicle based on the noise evaluation index to obtain the noise evaluation index data, then assigning values to the noise evaluation index data based on the preset standard evaluation data to obtain the subjective evaluation value of the in-vehicle noise data, and determining the noise performance of the vehicle based on the target subjective evaluation value. By analyzing the noise evaluation index that affects the subjective perception of noise, then constructing the preset standard evaluation data based on the noise evaluation index and subjective evaluation data, then extracting the index data from the in-vehicle noise data, and then combining the preset standard evaluation data to assign values to the noise evaluation index data to obtain the combined subjective and objective level subjective evaluation value, predicting the subjective evaluation value through the objective value of the in-vehicle noise, with a unified and accurate prediction standard, making the obtained level subjective evaluation value highly match the actual subjective evaluation value of consumers, and providing an accurate basis for the design of the vehicle noise performance.

[0074] In one embodiment, the in-vehicle noise data includes multiple groups of in-vehicle noise acquisition data. Such as Figure 3As shown, in step S20, based on the noise evaluation index, the index data is extracted from the in-vehicle noise data to obtain the noise evaluation index data, which specifically includes the following steps:

[0075] S21: Perform frequency-domain calculation on each group of in-vehicle noise acquisition data to obtain the auto-power spectrum corresponding to each group of in-vehicle noise acquisition data.

[0076] In this embodiment, the in-vehicle noise data includes multiple groups of in-vehicle noise acquisition data. When, based on the noise evaluation index, the in-vehicle noise data is processed, that is, when performing the driving noise test on the vehicle, multiple tests need to be carried out. Each test acquires a group of in-vehicle noise acquisition data. The in-vehicle noise acquisition data acquired during multiple tests is combined into the in-vehicle noise data to reduce the data error caused by single acquisition and improve the accuracy of the in-vehicle noise data. Among them, when performing the driving noise test on the vehicle, the vehicle can be controlled to perform tests in two driving directions, forward and reverse. Multiple tests are carried out in each driving direction to obtain multiple groups of in-vehicle noise acquisition data, and then the multiple groups of in-vehicle noise acquisition data obtained from the tests in the two driving directions, forward and reverse, are combined into the in-vehicle noise data. For example, if 3 tests are carried out in each driving direction to obtain 3 groups of in-vehicle noise acquisition data, 3 groups of in-vehicle noise acquisition data for forward driving test and 3 groups of in-vehicle noise acquisition data for reverse driving test can be obtained, and a total of 6 groups of in-vehicle noise acquisition data are used as the in-vehicle noise data.

[0077] After obtaining the in-vehicle noise data composed of multiple groups of in-vehicle noise acquisition data, perform frequency-domain calculation on each group of in-vehicle noise acquisition data to obtain the auto-power spectrum corresponding to each group of in-vehicle noise acquisition data. Among them, the frequency-domain calculation usually adopts the Fourier transform algorithm. The Fourier transform algorithm includes continuous Fourier transform and discrete Fourier transform. In this embodiment, considering the vehicle noise characteristics, the discrete Fourier transform algorithm is used to perform frequency-domain calculation on the in-vehicle noise acquisition data to obtain the auto-power spectrum corresponding to the in-vehicle noise acquisition data.

[0078] For example, when performing frequency-domain calculation on each group of in-vehicle noise acquisition data, a window function can be applied to each group of in-vehicle noise acquisition data first to obtain the preprocessed data of each group of in-vehicle noise acquisition data, and then discrete Fourier transform is performed on the preprocessed data of each group of in-vehicle noise acquisition data to obtain the auto-power spectrum of each group of in-vehicle noise acquisition data.

[0079] S22: Perform energy averaging on the auto-power spectra corresponding to multiple groups of in-vehicle noise acquisition data to obtain the averaged target auto-power spectrum.

[0080] After obtaining the auto-power spectra corresponding to each set of in-vehicle noise acquisition data, perform energy averaging on the auto-power spectra corresponding to multiple sets of in-vehicle noise acquisition data to obtain the averaged target auto-power spectrum, that is, use the averaging algorithm to perform energy averaging on multiple sets of auto-power spectra, and take the averaged auto-power spectrum as the representative of all in-vehicle noise acquisition data, as the target auto-power spectrum of the in-vehicle noise data.

[0081] S23: Extract index data from the target auto-power spectrum based on the noise evaluation index to obtain the noise evaluation index data.

[0082] After performing energy averaging on the auto-power spectra corresponding to multiple sets of in-vehicle noise acquisition data to obtain the averaged target auto-power spectrum, extract index data from the target auto-power spectrum based on the noise evaluation index to obtain the noise evaluation index data. For example, perform sound pressure level curve extraction and / or speech intelligibility curve extraction on the target auto-power spectrum to obtain the sound pressure level curve extraction and / or speech intelligibility curve, and then calculate the sound pressure level value of the in-vehicle noise data based on the sound pressure level curve, and / or calculate the speech intelligibility value of the in-vehicle noise data based on the speech intelligibility curve. Finally, take the sound pressure level value and / or speech intelligibility value as the noise evaluation index data.

[0083] In other embodiments, the noise evaluation index data can be extracted by other means. For example, first perform frequency domain calculation on each set of in-vehicle noise acquisition data to obtain the auto-power spectrum corresponding to each set of in-vehicle noise acquisition data, and then perform sound pressure level curve extraction and / or speech intelligibility curve extraction based on the auto-power spectrum corresponding to each set of in-vehicle noise acquisition data to obtain the sound pressure level curve extraction and / or speech intelligibility curve corresponding to each set of in-vehicle noise acquisition data; then perform energy averaging on multiple sound pressure level curves to obtain the target sound pressure level curve, and / or perform energy averaging on multiple speech intelligibility curves to obtain the target speech intelligibility curve; then calculate the sound pressure level value of the in-vehicle noise data based on the target sound pressure level curve, and / or calculate the speech intelligibility value of the in-vehicle noise data based on the target speech intelligibility curve. Finally, take the sound pressure level value and / or speech intelligibility value as the noise evaluation index data.

[0084] In this embodiment, by performing frequency-domain calculation on each group of in-vehicle noise acquisition data, the auto-power spectrum corresponding to each group of in-vehicle noise acquisition data is obtained. Then, energy averaging is performed on the auto-power spectra corresponding to multiple groups of in-vehicle noise acquisition data to obtain the averaged target auto-power spectrum. Furthermore, based on the noise evaluation index, index data extraction is performed on the target auto-power spectrum to obtain the noise evaluation index data, which details the specific steps of extracting the noise evaluation index data from the in-vehicle noise data based on the noise evaluation index. By collecting multiple groups of in-vehicle noise acquisition data as the in-vehicle noise data, the accuracy of the in-vehicle noise data is improved. Then, after performing energy averaging on multiple groups of in-vehicle noise acquisition data, index data extraction is performed, thereby improving the accuracy of the noise evaluation index data.

[0085] In one embodiment, in step S21, that is, performing frequency-domain calculation on each group of in-vehicle noise acquisition data to obtain the auto-power spectrum corresponding to each group of in-vehicle noise acquisition data, specifically includes the following steps:

[0086] S211: Determine multiple sub-noise acquisition data within each group of in-vehicle noise acquisition data, and each sub-noise acquisition data corresponds to a collection position.

[0087] After obtaining the in-vehicle noise data composed of multiple groups of in-vehicle noise acquisition data, determine multiple sub-noise acquisition data within each group of in-vehicle noise acquisition data, and each sub-noise acquisition data corresponds to a collection position. In this embodiment, each group of in-vehicle noise acquisition data includes sub-noise acquisition data collected at multiple collection positions, where the multiple collection positions include at least two collection positions such as the driver's outer ear position, the co-driver's outer ear position, and the outer ear positions of other passengers. Since the vehicle noise heard at different positions within the vehicle is different, using the sub-noise acquisition data collected at different collection positions as a group of in-vehicle noise acquisition data can make the in-vehicle noise acquisition data more accurate, thereby improving the accuracy of the in-vehicle noise data.

[0088] S212: Perform frequency-domain calculation on each sub-noise acquisition data respectively to obtain the auto-power spectrum of each sub-noise acquisition data.

[0089] After determining multiple sub-noise acquisition data within each group of in-vehicle noise acquisition data, perform frequency-domain calculation on each sub-noise acquisition data respectively to obtain the auto-power spectrum of each sub-noise acquisition data.

[0090] S213: Perform averaging processing on the auto-power spectra of multiple sub-noise acquisition data within each group of in-vehicle noise acquisition data to obtain the average auto-power spectrum;

[0091] S214: Use the average auto-power spectrum as the auto-power spectrum corresponding to the in-vehicle noise acquisition data.

[0092] After performing frequency-domain calculations on each sub-noise acquisition data separately to obtain the auto-power spectrum of each sub-noise acquisition data, averaging the auto-power spectra of multiple sub-noise acquisition data within each set of in-vehicle noise acquisition data to obtain an average auto-power spectrum, and using the average auto-power spectrum as the auto-power spectrum corresponding to the in-vehicle noise acquisition data, the accuracy of the auto-power spectrum of each set of in-vehicle noise acquisition data can be improved, thereby improving the accuracy of the target auto-power spectrum of subsequent in-vehicle noise data, and providing an accurate customer data basis for subsequent extraction of index data and grading assignment.

[0093] In other embodiments, each set of in-vehicle noise acquisition data can be sub-noise acquisition data collected at the position of the driver's outer ear. Using the most representative sub-noise acquisition data collected at the position of the driver's outer ear as the in-vehicle noise acquisition data can reduce the number of acquisition devices and the subsequent data processing volume.

[0094] In this embodiment, by determining multiple sub-noise acquisition data within each set of in-vehicle noise acquisition data, each sub-noise acquisition data corresponds to a collection position, performing frequency-domain calculations on each sub-noise acquisition data separately to obtain the auto-power spectrum of each sub-noise acquisition data, then averaging the auto-power spectra of multiple sub-noise acquisition data within each set of in-vehicle noise acquisition data to obtain an average auto-power spectrum, and using the average auto-power spectrum as the auto-power spectrum corresponding to the in-vehicle noise acquisition data, the specific steps of performing frequency-domain calculations on each set of in-vehicle noise acquisition data to obtain the auto-power spectrum corresponding to each set of in-vehicle noise acquisition data are clarified. Using the sub-noise acquisition data collected at multiple collection positions as a set of in-vehicle noise acquisition data takes into account the different effects of the acquisition data at different collection positions, improves the accuracy of the in-vehicle noise acquisition data, thereby improving the accuracy of the target auto-power spectrum, and providing an accurate customer data basis for subsequent extraction of index data and grading assignment.

[0095] In one embodiment, in step S212, that is, performing frequency-domain calculations on each sub-noise acquisition data separately to obtain the auto-power spectrum of each sub-noise acquisition data, specifically includes the following steps:

[0096] S2121: Applying a window function to each sub-noise acquisition data to obtain preprocessed data of each sub-noise acquisition data;

[0097] S2122: Performing a fast Fourier transform on the preprocessed data of each sub-noise acquisition data to obtain spectral data;

[0098] S2123: Performing weighted conversion on the spectral data to obtain the auto-power spectrum of each sub-noise acquisition data.

[0099] After determining multiple sub-noise acquisition data within each set of in-vehicle noise acquisition data, a window function is first applied to each sub-noise acquisition data to reduce data leakage, thereby obtaining preprocessed data for each sub-noise acquisition data. Then, the fast Fourier transform is performed on the preprocessed data of each sub-noise acquisition data to obtain spectral data. Finally, the result of the fast Fourier transform, that is, the spectral data, is weighted and transformed to obtain the weighted auto-power spectrum for each sub-noise acquisition data. In this embodiment, using the fast Fourier transform can greatly reduce the number of multiplications required to calculate the discrete Fourier transform, significantly saving the data calculation amount and thus improving the calculation efficiency. In other embodiments, other Fourier transform algorithms can also be used, which will not be elaborated here.

[0100] Among them, the weighting method during the weighted transformation of the spectral data can be A-weighting, C-weighting, and linear weighting. Considering that the A-weighting method can better reflect the human ear's perception of the sound intensity, in this embodiment, during the weighted transformation, the fast Fourier transform is performed on the preprocessed data of each sub-noise acquisition data and A-weighting transformation is carried out to obtain the weighted auto-power spectrum based on A-weighting for each sub-noise acquisition data.

[0101] In this embodiment, by applying a window function to each sub-noise acquisition data, the preprocessed data for each sub-noise acquisition data is obtained. Then, the fast Fourier transform is performed on the preprocessed data of each sub-noise acquisition data and weighted transformation is carried out to obtain the auto-power spectrum for each sub-noise acquisition data, clarifying the specific steps of separately performing frequency-domain calculations on each sub-noise acquisition data to obtain the auto-power spectrum for each sub-noise acquisition data. By performing frequency-domain conversion on each sub-noise acquisition data through the fast Fourier transform algorithm, the data calculation amount can be significantly saved, thereby improving the calculation efficiency.

[0102] In one embodiment, the noise evaluation indicators include sound pressure level and speech intelligibility. In step S23, based on the noise evaluation indicators, index data extraction is performed on the in-vehicle noise data to obtain noise evaluation index data, which specifically includes the following steps:

[0103] S231: Calculate the sound pressure level of the target auto-power spectrum to obtain the sound pressure level value.

[0104] After obtaining the target auto-power spectrum of the in-vehicle noise data, calculate the sound pressure level of the target auto-power spectrum to obtain the sound pressure level curve, and then determine a sound pressure level value based on the sound pressure level curve as the sound pressure level value. For example, perform an averaging process on the sound pressure level curve, and take the obtained average value as the sound pressure level value. It is also possible to take the median or maximum value of the sound pressure level curve as the sound pressure level value.

[0105] S232: Calculate the speech intelligibility of the target auto-power spectrum to obtain the speech intelligibility value.

[0106] After obtaining the target auto-power spectrum of the in-vehicle noise data, perform speech intelligibility calculation on the target auto-power spectrum to obtain a speech intelligibility curve, and then determine a speech intelligibility value based on the speech intelligibility curve as the speech intelligibility numerical value. For example, perform an averaging process on the speech intelligibility curve, and take the obtained average value as the speech intelligibility numerical value. It is also possible to take the median or maximum value of the speech intelligibility curve as the speech intelligibility numerical value.

[0107] S233: Use the sound pressure level numerical value and the speech intelligibility numerical value as the noise evaluation index data.

[0108] After obtaining the sound pressure level numerical value and the speech intelligibility numerical value, jointly use the sound pressure level numerical value and the speech intelligibility numerical value as the noise evaluation index data.

[0109] In other embodiments, the noise evaluation index can also be the sound pressure level or speech intelligibility. Correspondingly, the noise evaluation index data can also be the sound pressure level numerical value or the speech intelligibility numerical value.

[0110] In this embodiment, by performing sound pressure level calculation on the target auto-power spectrum to obtain the sound pressure level numerical value, and performing speech intelligibility calculation on the target auto-power spectrum to obtain the speech intelligibility numerical value, and then jointly using the sound pressure level numerical value and the speech intelligibility numerical value as the noise evaluation index data, it clarifies the specific steps of extracting index data from the target auto-power spectrum based on the noise evaluation index to obtain the noise evaluation index data, providing an accurate basis for subsequent subjective scoring and assignment using the noise evaluation index data as objective data.

[0111] In one embodiment, the noise evaluation index data includes the sound pressure level numerical value and the speech intelligibility numerical value. As Figure 4 shown, in step S30, based on the preset standard evaluation data, assign values to the noise evaluation index data to obtain the target subjective evaluation value of the in-vehicle noise data, which specifically includes the following steps:

[0112] S31: Based on the preset standard evaluation data, determine the target sound pressure level grade to which the sound pressure level numerical value belongs, and determine the sound pressure level evaluation value according to the target sound pressure level grade.

[0113] In this embodiment, the noise evaluation index data includes the sound pressure level numerical value and the speech intelligibility numerical value. Correspondingly, the preset standard evaluation data includes multiple sound pressure level grades and multiple speech intelligibility grades. Each sound pressure level grade corresponds to a sound pressure level numerical value range, and each sound pressure level grade corresponds to a subjective evaluation value; each speech intelligibility grade corresponds to a speech intelligibility grade numerical value range, and each speech intelligibility grade corresponds to a subjective evaluation value.

[0114] After obtaining the noise evaluation index data including the sound pressure level value and the speech intelligibility value, based on the preset standard evaluation data, determine the target sound pressure level grade to which the sound pressure level value belongs, and determine the sound pressure level evaluation value according to the target sound pressure level grade.

[0115] Among them, based on the preset standard evaluation data, determine the target sound pressure level grade to which the sound pressure level value belongs, and determine the sound pressure level evaluation value according to the target sound pressure level grade, including: obtaining multiple sound pressure level grades in the preset standard evaluation data, and determining the sound pressure level value range corresponding to the sound pressure level grade; matching the sound pressure level value with multiple sound pressure level value ranges, and recording the sound pressure level grade corresponding to the matched sound pressure level value range as the target sound pressure level grade; in the preset standard evaluation data, determine the subjective evaluation value corresponding to the target sound pressure level grade as the sound pressure level evaluation value.

[0116] In other embodiments, after matching the sound pressure level value with multiple sound pressure level value ranges and recording the sound pressure level grade corresponding to the matched sound pressure level value range as the target sound pressure level grade, the subjective evaluation value corresponding to the target sound pressure level grade can be determined, and then the subjective evaluation values corresponding to the target sound pressure level grade and the sound pressure level grades below the target sound pressure level grade are accumulated, and the total subjective evaluation value obtained by accumulation is used as the sound pressure level evaluation value.

[0117] S32: Based on the preset standard evaluation data, determine the target speech intelligibility grade to which the speech intelligibility value belongs, and determine the speech intelligibility evaluation value according to the target speech intelligibility grade.

[0118] Meanwhile, based on the preset standard evaluation data, determine the target speech intelligibility grade to which the speech intelligibility value belongs, and determine the speech intelligibility evaluation value according to the target speech intelligibility grade.

[0119] Among them, based on the preset standard evaluation data, determine the target speech intelligibility grade to which the speech intelligibility value belongs, and determine the speech intelligibility evaluation value according to the target speech intelligibility grade, including: obtaining multiple speech intelligibility grades in the preset standard evaluation data, and determining the speech intelligibility value range corresponding to the speech intelligibility grade; matching the speech intelligibility value with multiple speech intelligibility value ranges, and recording the speech intelligibility grade corresponding to the matched speech intelligibility value range as the target speech intelligibility grade; in the preset standard evaluation data, determine the subjective evaluation value corresponding to the target speech intelligibility grade as the speech intelligibility evaluation value.

[0120] In other embodiments, after matching the speech intelligibility value with multiple speech intelligibility value ranges and recording the speech intelligibility level corresponding to the matched speech intelligibility value range as the target speech intelligibility level, the subjective evaluation value corresponding to the target speech intelligibility level can be determined, and then the subjective evaluation value corresponding to the target speech intelligibility level and the subjective evaluation values corresponding to each speech intelligibility level below the target speech intelligibility level are accumulated, and the accumulated total subjective evaluation value is used as the speech intelligibility evaluation value.

[0121] S33: Use the sum of the sound pressure level evaluation value and the speech intelligibility evaluation value as the subjective evaluation value of the in-vehicle noise data.

[0122] After obtaining the sound pressure level evaluation value and the speech intelligibility evaluation value, use the sum of the sound pressure level evaluation value and the speech intelligibility evaluation value as the subjective evaluation value of the in-vehicle noise data.

[0123] In one embodiment, the weight corresponding to the sound pressure level evaluation value and the weight corresponding to the speech intelligibility evaluation value can also be determined, where the weight corresponding to the sound pressure level evaluation value and the weight corresponding to the speech intelligibility evaluation value are different in size, and then based on the weight corresponding to the sound pressure level evaluation value and the weight corresponding to the speech intelligibility evaluation value, the sound pressure level evaluation value and the speech intelligibility evaluation value are weighted and summed to obtain the subjective evaluation value of the in-vehicle noise data.

[0124] In one embodiment, the noise evaluation index data can be a sound pressure level value or a speech intelligibility value. Correspondingly, the preset standard evaluation data includes multiple sound pressure level levels or multiple speech intelligibility levels. Each sound pressure level level corresponds to a sound pressure level value range, and each speech intelligibility level corresponds to a speech intelligibility level value range. After obtaining the noise evaluation index data, directly determine the sound pressure level value range to which the sound pressure level value belongs in the noise evaluation index data, and then determine the subjective evaluation value corresponding to the sound pressure level value range, and use the subjective evaluation value corresponding to the sound pressure level value range as the subjective evaluation value of the in-vehicle noise data; or directly determine the speech intelligibility value range to which the speech intelligibility value belongs in the noise evaluation index data, and then determine the subjective evaluation value corresponding to the speech intelligibility value range, and use the subjective evaluation value corresponding to the speech intelligibility value range as the subjective evaluation value of the in-vehicle noise data.

[0125] In other embodiments, the preset standard evaluation data may not include the sound pressure level level and / or multiple speech intelligibility levels, but only includes multiple sound pressure level value ranges and / or multiple speech intelligibility level value ranges. Each sound pressure level value range corresponds to a subjective evaluation value; each speech intelligibility level value range corresponds to a subjective evaluation value.

[0126] For example, the specific data of the preset standard evaluation data can be as shown in Table 1:

[0127] Table 1

[0128]

[0129] As shown in Table 1, the preset standard evaluation data includes 6 consecutive sound pressure level value ranges and 6 consecutive speech intelligibility level value ranges. Each sound pressure level value range corresponds to a subjective evaluation value, and the speech intelligibility level value range corresponds to a subjective evaluation value. After obtaining the sound pressure level value or the speech intelligibility value, the sound pressure level value range to which the sound pressure level value belongs can be directly determined, and then the subjective evaluation value corresponding to the sound pressure level value range is used as the sound pressure level evaluation value. At the same time, the speech intelligibility value range to which the speech intelligibility value belongs can be directly determined, and then the subjective evaluation value corresponding to the speech intelligibility value range is used as the speech intelligibility evaluation value. Then, the sum of the sound pressure level evaluation value and the speech intelligibility evaluation value is used as the target subjective evaluation value, which is simple and convenient.

[0130] In this embodiment, the noise evaluation index data includes the sound pressure level value and the speech intelligibility value. Based on the preset standard evaluation data, the target sound pressure level grade to which the sound pressure level value belongs is determined, and the sound pressure level evaluation value is determined according to the target sound pressure level grade. At the same time, based on the preset standard evaluation data, the target speech intelligibility grade to which the speech intelligibility value belongs is determined, and the speech intelligibility evaluation value is determined according to the target speech intelligibility grade. Finally, the sum of the sound pressure level evaluation value and the speech intelligibility evaluation value is used as the subjective evaluation value of the vehicle interior noise data, which refines the steps of assigning values to the noise evaluation index data based on the preset standard evaluation data to obtain the target subjective evaluation value of the vehicle interior noise data, and provides a basis for determining the noise performance of the vehicle based on the target subjective evaluation value.

[0131] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0132] In one embodiment, a vehicle noise performance determination device is provided, and the vehicle noise performance determination device corresponds one-to-one with the vehicle noise performance determination method in the above embodiment. As Figure 5 shown, the vehicle noise performance determination device includes module A, module B, module C, and module D. The detailed description of each functional module is as follows:

[0133] An acquisition module 501, configured to acquire a noise evaluation index and acquire preset standard evaluation data constructed based on the noise evaluation index and subjective evaluation data;

[0134] An extraction module 502 is configured to extract index data from the in-vehicle noise data of a vehicle based on a noise evaluation index to obtain noise evaluation index data;

[0135] An assignment module 503 is configured to assign values to the noise evaluation index data based on preset standard evaluation data to obtain a target subjective evaluation value of the in-vehicle noise data;

[0136] A determination module 504 is configured to determine the noise performance of the vehicle according to the target subjective evaluation value.

[0137] Further, the in-vehicle noise data includes multiple groups of in-vehicle noise acquisition data. Specifically, the extraction module 502 is configured to:

[0138] Perform frequency-domain calculation on each group of in-vehicle noise acquisition data to obtain the auto-power spectrum corresponding to each group of in-vehicle noise acquisition data;

[0139] Perform energy averaging on the auto-power spectra corresponding to multiple groups of in-vehicle noise acquisition data to obtain an averaged target auto-power spectrum;

[0140] Extract index data from the target auto-power spectrum based on the noise evaluation index to obtain noise evaluation index data.

[0141] Further, the noise evaluation index includes sound pressure level and speech intelligibility. Specifically, the extraction module 502 is further configured to:

[0142] Perform sound pressure level calculation on the target auto-power spectrum to obtain a sound pressure level value;

[0143] Perform speech intelligibility calculation on the target auto-power spectrum to obtain a speech intelligibility value;

[0144] Use the sound pressure level value and the speech intelligibility value as the noise evaluation index data.

[0145] Further, the extraction module 502 is further configured to:

[0146] Determine multiple sub-noise acquisition data within each group of in-vehicle noise acquisition data, and each sub-noise acquisition data corresponds to a collection position;

[0147] Perform frequency-domain calculation on each sub-noise acquisition data respectively to obtain the auto-power spectrum of each sub-noise acquisition data;

[0148] Perform averaging processing on the auto-power spectra of multiple sub-noise acquisition data within each group of in-vehicle noise acquisition data to obtain an average auto-power spectrum;

[0149] Use the average auto-power spectrum as the auto-power spectrum corresponding to the in-vehicle noise acquisition data.

[0150] Further, the extraction module 502 is further configured to:

[0151] Apply a window function to each sub-noise acquisition data to obtain the preprocessed data of each sub-noise acquisition data;

[0152] Perform a fast Fourier transform on the preprocessed data of each sub-noise acquisition data to obtain spectral data;

[0153] Perform weighted conversion on the spectral data to obtain the auto-power spectrum of each sub-noise acquisition data.

[0154] Further, the noise evaluation index data includes sound pressure level values and speech intelligibility values. The assignment module 503 is specifically used for:

[0155] Based on the preset standard evaluation data, determine the target sound pressure level grade to which the sound pressure level value belongs, and determine the sound pressure level evaluation value according to the target sound pressure level grade;

[0156] Based on the preset standard evaluation data, determine the target speech intelligibility grade to which the speech intelligibility value belongs, and determine the speech intelligibility evaluation value according to the target speech intelligibility grade;

[0157] Take the sum of the sound pressure level evaluation value and the speech intelligibility evaluation value as the subjective evaluation value of the vehicle interior noise data.

[0158] Further, the assignment module 503 is specifically also used for:

[0159] Obtain multiple sound pressure level grades in the preset standard evaluation data, and determine the sound pressure level value range corresponding to the sound pressure level grade;

[0160] Match the sound pressure level value with multiple sound pressure level value ranges, and record the sound pressure level grade corresponding to the matched sound pressure level value range as the target sound pressure level grade;

[0161] In the preset standard evaluation data, determine the subjective evaluation value corresponding to the target sound pressure level grade as the sound pressure level evaluation value.

[0162] For the specific limitations of the vehicle noise performance determination device, reference can be made to the limitations of the vehicle noise performance determination method in the above text, which will not be elaborated here. Each module in the above vehicle noise performance determination device can be implemented in whole or in part through software, hardware and their combination. The above modules can be embedded in the processor of the computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0163] In one embodiment, a vehicle noise performance determination device is provided, and the vehicle noise performance determination device may be a computer device. The vehicle noise performance determination device includes a processor, a memory, a network interface, and a database connected through a system bus. Among them, the processor of the vehicle noise performance determination device is used to provide computing and control capabilities. The memory of the vehicle noise performance determination device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the data used and generated by the vehicle noise performance determination method. The network interface of the vehicle noise performance determination device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a vehicle noise performance determination method is implemented.

[0164] In one embodiment, as Figure 6 shown, a vehicle noise performance determination device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0165] Obtain a noise evaluation index, and obtain preset standard evaluation data constructed based on the noise evaluation index and subjective evaluation data;

[0166] Extract index data from the in-vehicle noise data of the vehicle based on the noise evaluation index to obtain noise evaluation index data;

[0167] Assign a value to the noise evaluation index data based on the preset standard evaluation data to obtain the target subjective evaluation value of the in-vehicle noise data;

[0168] Determine the noise performance of the vehicle according to the target subjective evaluation value.

[0169] In one embodiment, a readable storage medium is provided, on which a computer program is stored. When the computer program is executed by the processor, the following steps are implemented:

[0170] Obtain a noise evaluation index, and obtain preset standard evaluation data constructed based on the noise evaluation index and subjective evaluation data;

[0171] Extract index data from the in-vehicle noise data of the vehicle based on the noise evaluation index to obtain noise evaluation index data;

[0172] Assign a value to the noise evaluation index data based on the preset standard evaluation data to obtain the target subjective evaluation value of the in-vehicle noise data;

[0173] Determine the noise performance of the vehicle according to the target subjective evaluation value.

[0174] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0175] Those skilled in the art can clearly understand that for the convenience and brevity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0176] The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. These modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention and should all be included in the protection scope of the present invention.

Claims

1. A method for determining the vehicle noise performance, characterized in that, it includes: Obtain the noise evaluation index, and obtain the preset standard evaluation data constructed based on the noise evaluation index and subjective evaluation data; Extract index data from the in-vehicle noise data of the vehicle based on the noise evaluation index to obtain noise evaluation index data; Assign values to the noise evaluation index data based on the preset standard evaluation data to obtain the target subjective evaluation value of the in-vehicle noise data; Determine the noise performance of the vehicle according to the target subjective evaluation value; The in-vehicle noise data includes multiple groups of in-vehicle noise acquisition data. The extraction of index data from the in-vehicle noise data of the vehicle based on the noise evaluation index to obtain noise evaluation index data includes: Perform frequency-domain calculation on each group of the in-vehicle noise acquisition data to obtain the auto-power spectrum corresponding to each group of the in-vehicle noise acquisition data; Perform energy averaging on the auto-power spectra corresponding to multiple groups of the in-vehicle noise acquisition data to obtain the averaged target auto-power spectrum; Extract index data from the target auto-power spectrum based on the noise evaluation index to obtain the noise evaluation index data.

2. The method for determining the vehicle noise performance according to claim 1, characterized in that, The noise evaluation index includes sound pressure level and speech intelligibility. The extraction of index data from the target auto-power spectrum based on the noise evaluation index to obtain the noise evaluation index data includes: Perform sound pressure level calculation on the target auto-power spectrum to obtain the sound pressure level value; Perform speech intelligibility calculation on the target auto-power spectrum to obtain the speech intelligibility value; Use the sound pressure level value and the speech intelligibility value as the noise evaluation index data.

3. The method for determining the vehicle noise performance according to claim 1, characterized in that, The performing frequency-domain calculation on each group of the in-vehicle noise acquisition data to obtain the auto-power spectrum corresponding to each group of the in-vehicle noise acquisition data includes: Determine multiple sub-noise acquisition data within each group of the in-vehicle noise acquisition data, and each sub-noise acquisition data corresponds to a collection position; Perform frequency-domain calculation on each sub-noise acquisition data respectively to obtain the auto-power spectrum of each sub-noise acquisition data; Perform averaging processing on the auto-power spectra of multiple sub-noise acquisition data within each group of the in-vehicle noise acquisition data to obtain the average auto-power spectrum; Use the average auto-power spectrum as the auto-power spectrum corresponding to the in-vehicle noise acquisition data.

4. The method for determining the vehicle noise performance according to claim 3, characterized in that, The performing frequency-domain calculation on each sub-noise acquisition data respectively to obtain the auto-power spectrum of each sub-noise acquisition data includes: Apply a window function to each sub-noise acquisition data to obtain the preprocessed data of each sub-noise acquisition data; Perform fast Fourier transform on the preprocessed data of each sub-noise acquisition data to obtain spectral data; Perform weighted conversion on the spectral data to obtain the auto-power spectrum of each sub-noise acquisition data.

5. The vehicle noise performance determination method according to any one of claims 1-4, characterized in that, the noise evaluation index data includes a sound pressure level value and a speech intelligibility value, and the step of assigning values to the noise evaluation index data based on the preset standard evaluation data to obtain the target subjective evaluation value of the in-vehicle noise data includes: Based on the preset standard evaluation data, determine the target sound pressure level grade to which the sound pressure level value belongs, and determine the sound pressure level evaluation value according to the target sound pressure level grade; Based on the preset standard evaluation data, determine the target speech intelligibility grade to which the speech intelligibility value belongs, and determine the speech intelligibility evaluation value according to the target speech intelligibility grade; Take the sum of the sound pressure level evaluation value and the speech intelligibility evaluation value as the target subjective evaluation value of the in-vehicle noise data.

6. The vehicle noise performance determination method according to claim 5, characterized in that, the step of determining the target sound pressure level grade to which the sound pressure level value belongs based on the preset standard evaluation data and determining the sound pressure level evaluation value according to the target sound pressure level grade includes: Obtain multiple sound pressure level grades in the preset standard evaluation data, and determine the sound pressure level value range corresponding to the sound pressure level grade; Match the sound pressure level value with multiple sound pressure level value ranges, and record the sound pressure level grade corresponding to the matched sound pressure level value range as the target sound pressure level grade; In the preset standard evaluation data, determine the subjective evaluation value corresponding to the target sound pressure level grade as the sound pressure level evaluation value.

7. A vehicle noise performance determination device, characterized in that, comprises: An acquisition module, configured to acquire noise evaluation indexes and acquire preset standard evaluation data constructed based on the noise evaluation indexes and subjective evaluation data; An extraction module, configured to extract index data from the in-vehicle noise data of the vehicle based on the noise evaluation indexes to obtain noise evaluation index data; An assignment module, configured to assign values to the noise evaluation index data based on the preset standard evaluation data to obtain the target subjective evaluation value of the in-vehicle noise data; A determination module, configured to determine the noise performance of the vehicle according to the target subjective evaluation value; The in-vehicle noise data includes multiple groups of in-vehicle noise acquisition data, and the step of extracting index data from the in-vehicle noise data of the vehicle based on the noise evaluation indexes to obtain noise evaluation index data includes: Performing frequency domain calculation on each group of the in-vehicle noise acquisition data to obtain the self-power spectrum corresponding to each group of the in-vehicle noise acquisition data; Performing energy averaging on the self-power spectra corresponding to multiple groups of the in-vehicle noise acquisition data to obtain an averaged target self-power spectrum; Extracting index data from the target self-power spectrum based on the noise evaluation indexes to obtain the noise evaluation index data.

8. A vehicle noise performance determination device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, the steps of the vehicle noise performance determination method according to any one of claims 1 to 6 are implemented.

9. A readable storage medium storing a computer program, characterized in that, when the computer program is executed by a processor, the steps of the vehicle noise performance determination method according to any one of claims 1 to 6 are implemented.

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