Vehicle NVH performance evaluation method and device, electronic equipment and storage medium

Abstract

The invention relates to a vehicle NVH performance evaluation method and device, electronic equipment and a storage medium, and the method comprises the steps: calculating a professional average score of each evaluation subitem based on the score of each first user for each evaluation subitem in NVH evaluation items of a current vehicle, based on the positive evaluation number and the negative evaluation number of each evaluation subitem by each second user, obtaining a market original score of each evaluation subitem and performing normalization processing to obtain a market word-of-mouth score of each evaluation subitem; and obtaining an NVH score of the current vehicle according to the professional average score of each evaluation subitem and the market word-of-mouth score of each evaluation subitem. Therefore, the problems that the evaluation method in the related technology does not fully consider the demand of the market user and the evaluation result is not accurate enough are solved, the NVH subjective score of the vehicle is obtained by increasing the feedback of the market user and the weight factor of the evaluation subitem, and thus the NVH competitiveness of the vehicle is increased.

Description

Technical Field

[0001] This application relates to the technical field of vehicle NVH performance development, and particularly to a method, device, electronic device, and storage medium for evaluating vehicle NVH (Noise, Vibration, Harshness) performance. Background Art

[0002] With the transformation of the automotive industry towards new energy and intelligence, NVH performance has become one of the important indicators for measuring vehicle quality. The setting of NVH subjective target values is extremely important for automotive R & D. It determines the technical solutions, costs, weights, performances, and market competitiveness of products, thus directly affecting driving comfort and user experience. Therefore, accurately setting and optimizing NVH target values is crucial for enhancing the overall competitiveness of vehicles.

[0003] In related technologies, existing NVH performance evaluation methods usually rely on the subjective evaluation of professionals and laboratory test data. For example, the patent "CN116933499A" proposes a method for evaluating the health index of vehicle NVH performance. By collecting vehicle-level NVH development target information and verification results at the current node, the health index is calculated, aiming to monitor the health status process of NVH performance throughout the development cycle and provide a management tool for the forward development of NVH performance.

[0004] However, the evaluation methods of related technologies focus on professional evaluations. The sample size of professional evaluations is small, and the real feelings of end-users and market demands are ignored, resulting in the disconnection between the set NVH targets and the actual user experience. In addition, existing methods often regard all evaluation sub-items as equally important and do not consider the different degrees of influence of different sub-items on user perception, which may lead to incomplete and inaccurate evaluation results and urgently need to be solved. Summary of the Invention

[0005] This application provides a method, device, electronic device, and storage medium for evaluating vehicle NVH performance to solve the problems that the evaluation methods of related technologies do not fully consider the needs of market users and the evaluation results are not accurate enough. By increasing the feedback of market users and the weight factors of evaluation sub-items, the NVH subjective score of the vehicle is obtained, thereby increasing the NVH competitiveness of the vehicle.

[0006] The first aspect embodiment of this application provides a method for evaluating vehicle NVH performance, including the following steps:

[0007] Obtain the NVH evaluation items of the current vehicle, the scores of each evaluation sub-item of the NVH evaluation items by multiple first users, the number of positive evaluations and the number of negative evaluations of each evaluation sub-item by multiple second users;

[0008] Based on the scores given by each first user to each evaluation sub-item, calculate the professional average score of each evaluation sub-item, and based on the number of positive evaluations and negative evaluations of each evaluation sub-item given by each second user, obtain the market raw score of each evaluation sub-item, and perform normalization processing on the market raw score to obtain the market word-of-mouth score of each evaluation sub-item;

[0009] According to the professional average score of each evaluation sub-item and the market word-of-mouth score of each evaluation sub-item, obtain the NVH score of the current vehicle.

[0010] According to an embodiment of the present application, the obtaining the NVH score of the current vehicle according to the professional average score of each evaluation sub-item and the market word-of-mouth score of each evaluation sub-item includes:

[0011] According to the professional average score of each evaluation sub-item and the first preset weight of each evaluation sub-item, obtain the professional score of each evaluation sub-item, and according to the market word-of-mouth score of each evaluation sub-item and the second preset weight of each evaluation sub-item, obtain the market score of each evaluation sub-item;

[0012] According to the professional score of each evaluation sub-item, the market score of each evaluation sub-item and the third preset weight of each evaluation sub-item, obtain the total score of each evaluation sub-item, and sum according to the total score of each evaluation sub-item to obtain the NVH score of the current vehicle.

[0013] According to an embodiment of the present application, the obtaining the market raw score of each evaluation sub-item based on the number of positive evaluations and negative evaluations of each evaluation sub-item given by each second user, and performing normalization processing on the market raw score to obtain the market word-of-mouth score of each evaluation sub-item includes:

[0014] Calculate the difference between the number of positive evaluations and the number of negative evaluations of each evaluation sub-item, and calculate the ratio of the difference to the total number of evaluations of each evaluation sub-item to obtain the market raw score of each evaluation sub-item;

[0015] Calculate the product of the market raw score of each evaluation sub-item and the first preset threshold of each evaluation sub-item, and calculate the sum of the product and the second preset threshold of each evaluation sub-item to obtain the market word-of-mouth score of each evaluation sub-item.

[0016] According to an embodiment of the present application, the first preset weight, the second preset weight and the third preset weight are determined by the importance degree among the evaluation sub-items of the NVH evaluation item.

[0017] According to an embodiment of the present application, the NVH evaluation items of the current vehicle include at least one of a road noise evaluation sub-item, a wind noise evaluation sub-item, an acceleration and deceleration evaluation sub-item, a rattling noise evaluation sub-item, and a sound quality evaluation sub-item.

[0018] For the vehicle NVH performance evaluation method according to an embodiment of the present application, based on the scores given by a first user to each evaluation sub-item in the NVH evaluation items of the current vehicle, the professional average score of each evaluation sub-item is calculated, and based on the number of positive evaluations and negative evaluations of each evaluation sub-item given by a second user, the market raw score of each evaluation sub-item is obtained and normalized to obtain the market word-of-mouth score of each evaluation sub-item; according to the professional average score of each evaluation sub-item and the market word-of-mouth score of each evaluation sub-item, the NVH score of the current vehicle is obtained. Thus, the problems that the evaluation method in the related art does not fully consider the needs of market users and the evaluation result is not accurate enough are solved. By adding the feedback of market users and the weight factor of the evaluation sub-item, the subjective NVH score of the vehicle is obtained, thereby increasing the NVH competitiveness of the vehicle.

[0019] An embodiment of the second aspect of the present application provides a vehicle NVH performance evaluation device, including:

[0020] An acquisition module, configured to acquire the NVH evaluation items of the current vehicle, the scores given by a plurality of first users to each evaluation sub-item of the NVH evaluation items, and the number of positive evaluations and negative evaluations of each evaluation sub-item given by a plurality of second users;

[0021] A processing module, configured to calculate the professional average score of each evaluation sub-item based on the scores given by each first user to each evaluation sub-item, and obtain the market raw score of each evaluation sub-item based on the number of positive evaluations and negative evaluations of each evaluation sub-item given by each second user, and normalize the market raw score to obtain the market word-of-mouth score of each evaluation sub-item;

[0022] A calculation module, configured to obtain the NVH score of the current vehicle according to the professional average score of each evaluation sub-item and the market word-of-mouth score of each evaluation sub-item.

[0023] According to an embodiment of the present application, the processing module is configured to:

[0024] Obtain the professional score of each evaluation sub-item according to the professional average score of each evaluation sub-item and the first preset weight of each evaluation sub-item, and obtain the market score of each evaluation sub-item according to the market word-of-mouth score of each evaluation sub-item and the second preset weight of each evaluation sub-item;

[0025] Based on the professional score of each evaluation sub-item, the market score of each evaluation sub-item, and the third preset weight of each evaluation sub-item, obtain the total score of each evaluation sub-item, and sum up the total scores of each evaluation sub-item to obtain the NVH score of the current vehicle.

[0026] According to an embodiment of the present application, the processing module is configured to:

[0027] Calculate the difference between the number of positive evaluations and the number of negative evaluations of each evaluation sub-item, and calculate the ratio of the difference to the total number of evaluations of each evaluation sub-item to obtain the market raw score of each evaluation sub-item;

[0028] Calculate the product of the market raw score of each evaluation sub-item and the first preset threshold of each evaluation sub-item, and calculate the sum of the product and the second preset threshold of each evaluation sub-item to obtain the market word-of-mouth score of each evaluation sub-item.

[0029] According to an embodiment of the present application, the first preset weight, the second preset weight, and the third preset weight are determined by the importance degree among the evaluation sub-items of the NVH evaluation item.

[0030] According to an embodiment of the present application, the NVH evaluation item of the current vehicle includes at least one of a road noise evaluation sub-item, a wind noise evaluation sub-item, an acceleration / deceleration evaluation sub-item, a rattling noise evaluation sub-item, and a sound quality evaluation sub-item.

[0031] The vehicle NVH performance evaluation device according to the embodiment of the present application calculates the professional average score of each evaluation sub-item based on the score of each evaluation sub-item in the NVH evaluation item of the current vehicle by the first user, and obtains the market raw score of each evaluation sub-item based on the number of positive evaluations and negative evaluations of each evaluation sub-item by the second user and performs normalization processing to obtain the market word-of-mouth score of each evaluation sub-item; according to the professional average score of each evaluation sub-item and the market word-of-mouth score of each evaluation sub-item, obtain the NVH score of the current vehicle. Thereby, the problems that the evaluation method in the related technology does not fully consider the needs of market users and the evaluation result is not accurate enough are solved. By adding the feedback of market users and the weight factor of the evaluation sub-item, the subjective NVH score of the vehicle is obtained, thereby increasing the NVH competitiveness of the vehicle.

[0032] An embodiment of the third aspect of the present application provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor executes the program to implement the vehicle NVH performance evaluation method as described in the above embodiment.

[0033] The fourth aspect of the present application provides a computer-readable storage medium, on which a computer program is stored, and the program is executed by a processor to implement the vehicle NVH performance evaluation method as described in the above embodiments.

[0034] Additional aspects and advantages of the present application will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0036] Figure 1 is a flowchart of a vehicle NVH performance evaluation method according to an embodiment of the present application;

[0037] Figure 2 is a block diagram of a vehicle NVH performance evaluation device according to an embodiment of the present application;

[0038] Figure 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0039] Embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present application, and should not be construed as limiting the present application.

[0040] A vehicle NVH performance evaluation method, device, electronic device, and storage medium according to an embodiment of the present application will be described below with reference to the accompanying drawings.

[0041] Before introducing the vehicle NVH performance evaluation method of the embodiments of the present application, a brief introduction to the NVH performance evaluation method of the related art will be given.

[0042] In the related art, the current mainstream NVH performance evaluation method in the industry is based on benchmark evaluation, generally relying on the subjective scoring of developers. Although it can effectively avoid serious NVH problems, there are deficiencies, such as the evaluation indicators may not match the user's concerns, the evaluation weight distribution is uneven, and the sample size may be small. In addition, the existing methods do not fully consider the market user feedback, nor do they rank the importance of the evaluation sub-items or calculate the comprehensive score.

[0043] Therefore, based on the above situation, the present application proposes a method for evaluating the NVH performance of vehicles that combines professional personnel and market users. By integrating the feedback from professional personnel and market users, introducing the weight factors of evaluation sub-items, and calculating the comprehensive NVH score of the vehicle, it provides a new idea for the evaluation of vehicle NVH performance. This method can more accurately evaluate the NVH performance of vehicles and enhance the NVH competitiveness of vehicles.

[0044] The following introduces the method for evaluating the NVH performance of vehicles proposed in the present application.

[0045] Specifically, Figure 1 FIG. is a schematic flow chart of a method for evaluating the NVH performance of a vehicle provided in an embodiment of the present application.

[0046] As Figure 1 shown, the method for evaluating the NVH performance of the vehicle includes the following steps:

[0047] In step S101, obtain the NVH evaluation items of the current vehicle, the scores of each evaluation sub-item of the NVH evaluation items by multiple first users, the number of positive evaluations and the number of negative evaluations of each evaluation sub-item by multiple second users.

[0048] Among them, in some embodiments, the NVH evaluation items of the current vehicle include at least one of a road noise evaluation sub-item, a wind noise evaluation sub-item, an acceleration / deceleration evaluation sub-item, a rattling noise evaluation sub-item, and a sound quality evaluation sub-item. The first users refer to professional technical personnel, and the second users refer to market customers.

[0049] Specifically, in the embodiment of the present application, a series of NVH evaluation items can be formulated by professional NVH engineers according to the characteristics of the vehicle and industry standards. It is also possible to refer to the NVH evaluation items of the same-level or same-type vehicles, collect them as references, and then adjust them in combination with the characteristics of the current vehicle.

[0050] Furthermore, in the embodiment of the present application, a professional NVH test team can be organized to let professional technical personnel drive the vehicle and score each evaluation sub-item. It is also possible to use professional NVH test equipment to collect data under different driving conditions, and then let professional technical personnel give scores based on these data. It is also possible to set up an online platform to invite experts or other professional technical personnel in the industry to remotely participate in the evaluation and submit their scores. There is no specific limitation here.

[0051] Among them, the scores of each evaluation sub-item of the NVH evaluation items by the first users can be based on a preset standard. For example, as shown in Table 1, a ten-point system is used to score the evaluation sub-items.

[0052] Table 1

[0053]

[0054]

[0055] Table 1 provides a subjective evaluation standard for NVH professionals. This standard divides the evaluation into different levels, from "doesn't work at all" to "imperceptible to professionals", with each level corresponding to a score from 1 to 10. The functional levels include "terrible", "bad", "very poor", "poor", "conditionally acceptable", "pass", "good", "fine", "excellent", and "superb", providing a quantitative framework for professionals so that they can evaluate various aspects of NVH performance based on functionality and perception, thereby determining whether the vehicle can be delivered to customers.

[0056] Furthermore, the embodiments of the present application can collect evaluation feedback information of market customers through social media, automotive forums, or official APPs, and conduct semantic analysis according to the classification of evaluation sub-items, and count the number of positive evaluations and negative evaluations for each evaluation sub-item. In addition, during the vehicle sales or after-sales service process, feedback information of market customers can be collected through questionnaires. The questionnaires can include specific questions for each evaluation sub-item, and according to the questionnaire results of market customers collected, the number of positive evaluations and negative evaluations for each evaluation sub-item can be counted.

[0057] It should be noted that the above methods for obtaining the NVH evaluation items of the current vehicle, the scores of each evaluation sub-item of the NVH evaluation items by multiple first users, and the number of positive evaluations and negative evaluations of each evaluation sub-item by multiple second users are only exemplary and do not limit the present application. Those skilled in the art can use other methods in the prior art to obtain the NVH evaluation items of the current vehicle, the scores of each evaluation sub-item of the NVH evaluation items by multiple first users, and the number of positive evaluations and negative evaluations of each evaluation sub-item by multiple second users, which are not specifically limited herein.

[0058] In step S102, based on the scores of each evaluation sub-item by each first user, calculate the professional average score of each evaluation sub-item, and based on the number of positive evaluations and negative evaluations of each evaluation sub-item by each second user, obtain the market raw score of each evaluation sub-item, and perform normalization processing on the market raw score to obtain the market word-of-mouth score of each evaluation sub-item.

[0059] Specifically, as shown in Table 2, taking a pure electric project as an example, first, subjective evaluation scores are given by professional technicians (first users). Based on the scores of each evaluation sub-item by each first user, calculate the professional average score of each evaluation sub-item.

[0060] Table 2

[0061]

[0062]

[0063] As shown in Table 2, Table 2 shows an exemplary process of calculating the professional average score of each evaluation sub-item based on the scores given by each first user to each evaluation sub-item. It includes multiple evaluation sub-items, such as road noise evaluation sub-item, wind noise evaluation sub-item, acceleration and deceleration evaluation sub-item, abnormal noise evaluation sub-item, and sound quality evaluation sub-item, as well as the scores given by multiple professional technicians such as Expert A, Expert B, Expert C... Expert N to each evaluation sub-item and the professional average score of each evaluation sub-item. This table reflects the subjective evaluation of each evaluation sub-item by collecting the scores of different experts, and obtains the professional comprehensive score of each evaluation sub-item by calculating the average score, which helps to more comprehensively evaluate the NVH performance of the vehicle.

[0064] Furthermore, in some embodiments, based on the number of positive evaluations and negative evaluations of each evaluation sub-item given by each second user, the market raw score of each evaluation sub-item is obtained, and the market raw score is normalized to obtain the market word-of-mouth score of each evaluation sub-item, including: calculating the difference between the number of positive evaluations and the number of negative evaluations of each evaluation sub-item, and calculating the ratio of the difference to the total number of evaluations of each evaluation sub-item to obtain the market raw score of each evaluation sub-item; calculating the product of the market raw score of each evaluation sub-item and the first preset threshold of each evaluation sub-item, and calculating the sum of the product and the second preset threshold of each evaluation sub-item to obtain the market word-of-mouth score of each evaluation sub-item.

[0065] Optionally, the first preset threshold can be 5, and the second preset threshold can be 5, which is not specifically limited herein.

[0066] Specifically, first, calculate the difference between the number of positive evaluations and the number of negative evaluations of each obtained evaluation sub-item, and calculate the ratio of the difference to the total number of evaluations of each evaluation sub-item to obtain the market raw score of each evaluation sub-item. Secondly, perform normalization processing, calculate the product of the market raw score of each evaluation sub-item and the first preset threshold of each evaluation sub-item, and calculate the sum of the product and the second preset threshold of each evaluation sub-item to obtain the market word-of-mouth score of each evaluation sub-item.

[0067] For example, if an evaluation sub-item has 10 positive evaluations and 6 negative evaluations, then the total number of evaluations is the sum of 10 positive evaluations and 6 negative evaluations, that is, 16. The raw score is (10 - 6) / 16 = 0.25. In order to be combined with the professional score, the raw score can be normalized, that is, the raw score of 0.25 is adjusted according to the ten-point system, and 0.25 * 5 + 5 is calculated to obtain the market word-of-mouth score of this evaluation sub-item as 6.25.

[0068] In addition, the embodiments of the present application can also implement a point system for the positive and negative evaluations of each evaluation sub-item. For example, a positive evaluation is given +1 point, and a negative evaluation is given -1 point. Then, calculate the first product between the number of positive evaluations of each evaluation sub-item and its corresponding positive evaluation score, obtain the positive evaluation score of each evaluation sub-item, and calculate the second product between the number of negative evaluations of each evaluation sub-item and its corresponding negative evaluation score, obtain the negative evaluation score of each evaluation sub-item. Furthermore, calculate the sum of the positive evaluation score and the negative evaluation score of each evaluation sub-item, calculate the ratio of the sum value to the total number of evaluations of each evaluation sub-item, obtain the original market score of each evaluation sub-item. Secondly, perform normalization processing, calculate the product between the original market score of each evaluation sub-item and the first preset threshold of each evaluation sub-item, and calculate the sum of the product and the second preset threshold of each evaluation sub-item, obtain the market word-of-mouth score of each evaluation sub-item.

[0069] To facilitate the understanding of the process of calculating the market word-of-mouth score of each evaluation sub-item by those skilled in the art, the following will be described in detail with reference to Table 3.

[0070] Specifically, as shown in Table 3, M in Table 3 i is the total number of comments on evaluation sub-item i, and I i is the number of positive evaluations of evaluation sub-item i, and J i is the number of negative evaluations of evaluation sub-item i. In order to comprehensively combine the market score and the professional score, the original score can be adjusted according to the ten-point system, and the original score is converted into the range of 0 to 10 for subsequent comprehensive scoring.

[0071] Table 3

[0072]

[0073] In step S103, according to the professional average score of each evaluation sub-item and the market word-of-mouth score of each evaluation sub-item, obtain the NVH score of the current vehicle.

[0074] Furthermore, in some embodiments, obtaining the NVH score of the current vehicle according to the professional average score of each evaluation sub-item and the market word-of-mouth score of each evaluation sub-item includes: obtaining the professional score of each evaluation sub-item according to the professional average score of each evaluation sub-item and the first preset weight of each evaluation sub-item, and obtaining the market score of each evaluation sub-item according to the market word-of-mouth score of each evaluation sub-item and the second preset weight of each evaluation sub-item; obtaining the total score of each evaluation sub-item according to the professional score of each evaluation sub-item, the market score of each evaluation sub-item and the third preset weight of each evaluation sub-item, and summing up according to the total score of each evaluation sub-item to obtain the NVH score of the current vehicle.

[0075] Among them, in some embodiments, the first preset weight, the second preset weight, and the third preset weight are determined by the importance degree among the evaluation sub-items of the NVH evaluation item. Those skilled in the art of the present application can set the first preset weight, the second preset weight, and the third preset weight respectively according to the actual situation, and no specific limitation is made herein.

[0076] Specifically, as shown in Table 4, calculate the product of the professional average score of each evaluation sub-item and the first preset weight of each evaluation sub-item to obtain the professional score of each evaluation sub-item. Calculate the product of the market reputation score of each evaluation sub-item and the second preset weight of each evaluation sub-item to obtain the market score of each evaluation sub-item. After obtaining the professional score and the market score of each evaluation sub-item, sum and synthesize the two to obtain the comprehensive score of each evaluation sub-item:

[0077] Q i =(x i *p i +y i *(1 - p i ))

[0078] Among them, Q i is the comprehensive score of evaluation sub-item i, x i is the professional average score of evaluation sub-item i, p i is the first preset weight of evaluation sub-item i, y i is the market reputation score of evaluation sub-item i, and 1 - p i is the second preset weight of evaluation sub-item i.

[0079] Table 4

[0080]

[0081] Furthermore, as shown in Table 5, the evaluation items include road noise evaluation sub-item, wind noise evaluation sub-item, acceleration and deceleration evaluation sub-item, abnormal noise evaluation sub-item, sound quality evaluation sub-item, etc. The evaluation dimensions include professional score and market score. The weight (i.e., the third preset weight) of each evaluation sub-item can be set according to the power type, and weighted calculation is performed, that is, calculate the product of the comprehensive score of each evaluation sub-item and its corresponding third preset weight to obtain the total score of each evaluation sub-item.

[0082] Table 5

[0083]

[0084] Thus, by summing up the total scores of different evaluation sub-items, the NVH score Q of the vehicle can be obtained.

[0085]

[0086] Among them, Q is the NVH score of the vehicle, and Q i is the comprehensive score of each evaluation sub-item i, and q i is the third preset weight of the evaluation sub-item i, and x i is the professional average score of the evaluation sub-item i, and p i is the first preset weight of the evaluation sub-item i, and y i is the market word-of-mouth score of the evaluation sub-item i, and 1 - p i is the second preset weight of the evaluation sub-item i.

[0087] According to the vehicle NVH performance evaluation method of the embodiments of the present application, based on the scores of each evaluation sub-item in the NVH evaluation items of the current vehicle by the first user, the professional average score of each evaluation sub-item is calculated, and based on the number of positive evaluations and negative evaluations of each evaluation sub-item by the second user, the market raw score of each evaluation sub-item is obtained and normalized to obtain the market word-of-mouth score of each evaluation sub-item; according to the professional average score of each evaluation sub-item and the market word-of-mouth score of each evaluation sub-item, the NVH score of the current vehicle is obtained. Thus, the problems that the evaluation method in the related technology does not fully consider the needs of market users and the evaluation results are not comprehensive and accurate enough are solved. By adding the feedback of market users and the weight factors of the evaluation sub-items, the subjective NVH score of the vehicle is obtained, thereby increasing the NVH competitiveness of the vehicle.

[0088] Next, a vehicle NVH performance evaluation device according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0089] Figure 2 is a block diagram of a vehicle NVH performance evaluation device according to an embodiment of the present application.

[0090] As Figure 2 shown, the vehicle NVH performance evaluation device 10 includes: an acquisition module 100, a processing module 200, and a calculation module 300.

[0091] Among them, the acquisition module 100 is used to acquire the NVH evaluation items of the current vehicle, the scores of each evaluation sub-item in the NVH evaluation items by multiple first users, and the number of positive evaluations and negative evaluations of each evaluation sub-item by multiple second users; the processing module 200 is used to calculate the professional average score of each evaluation sub-item based on the scores of each evaluation sub-item by each first user, and obtain the market raw score of each evaluation sub-item based on the number of positive evaluations and negative evaluations of each evaluation sub-item by each second user, and normalize the market raw score to obtain the market word-of-mouth score of each evaluation sub-item; the calculation module 300 is used to obtain the NVH score of the current vehicle according to the professional average score of each evaluation sub-item and the market word-of-mouth score of each evaluation sub-item.

[0092] Further, in some embodiments, the processing module 200 is configured to: obtain the professional score of each evaluation sub-item according to the professional average score of each evaluation sub-item and the first preset weight of each evaluation sub-item, and obtain the market score of each evaluation sub-item according to the market word-of-mouth score of each evaluation sub-item and the second preset weight of each evaluation sub-item; obtain the total score of each evaluation sub-item according to the professional score of each evaluation sub-item, the market score of each evaluation sub-item and the third preset weight of each evaluation sub-item, and sum up the total scores of each evaluation sub-item to obtain the NVH score of the current vehicle.

[0093] Further, in some embodiments, the processing module 200 is configured to: calculate the difference between the number of positive evaluations and the number of negative evaluations of each evaluation sub-item, and calculate the ratio of the difference to the total number of evaluations of each evaluation sub-item to obtain the market raw score of each evaluation sub-item; calculate the product of the market raw score of each evaluation sub-item and the first preset threshold, and calculate the sum of the product and the second preset threshold of each evaluation sub-item to obtain the market word-of-mouth score of each evaluation sub-item.

[0094] Further, in some embodiments, the first preset weight, the second preset weight and the third preset weight are determined by the importance degree among the evaluation sub-items of the NVH evaluation item.

[0095] Further, in some embodiments, the NVH evaluation item of the current vehicle includes at least one of a road noise evaluation sub-item, a wind noise evaluation sub-item, an acceleration / deceleration evaluation sub-item, a rattling noise evaluation sub-item and a sound quality evaluation sub-item.

[0096] It should be noted that the foregoing explanation of the embodiments of the vehicle NVH performance evaluation method also applies to the vehicle NVH performance evaluation device of this embodiment, and will not be elaborated here.

[0097] According to the vehicle NVH performance evaluation device of the embodiments of the present application, based on the scores of each evaluation sub-item in the NVH evaluation item of the current vehicle given by the first user, the professional average score of each evaluation sub-item is calculated, and based on the number of positive evaluations and negative evaluations of each evaluation sub-item given by the second user, the market raw score of each evaluation sub-item is obtained and normalized to obtain the market word-of-mouth score of each evaluation sub-item; according to the professional average score of each evaluation sub-item and the market word-of-mouth score of each evaluation sub-item, the NVH score of the current vehicle is obtained. Thereby, the problems that the evaluation method in the related technology does not fully consider the needs of market users and the evaluation result is not accurate enough are solved. By adding the feedback of market users and the weight factors of the evaluation sub-items, the subjective NVH score of the vehicle is obtained, thereby increasing the NVH competitiveness of the vehicle.

[0098] Figure 3Schematic diagram of the structure of the electronic device provided by the embodiment of the present application. The electronic device may include:

[0099] A memory 301, a processor 302, and a computer program stored on the memory 301 and executable on the processor 302.

[0100] When the processor 302 executes the program, it implements the vehicle NVH performance evaluation method provided in the above embodiment.

[0101] Furthermore, the electronic device further includes:

[0102] A communication interface 303 for communication between the memory 301 and the processor 302.

[0103] The memory 301 is used to store a computer program executable on the processor 302.

[0104] The memory 301 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory.

[0105] If the memory 301, the processor 302, and the communication interface 303 are implemented independently, the communication interface 303, the memory 301, and the processor 302 may be interconnected through a bus and communicate with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For the sake of simplicity of representation, Figure 3 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0106] Optionally, in a specific implementation, if the memory 301, the processor 302, and the communication interface 303 are integrated on a chip, the memory 301, the processor 302, and the communication interface 303 may communicate with each other through an internal interface.

[0107] The processor 302 may be a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0108] Embodiments of the present application also provide a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the vehicle NVH performance evaluation method as described above is implemented.

[0109] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, without conflict, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples.

[0110] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality" is at least two, such as two, three, etc., unless otherwise specifically and clearly defined.

[0111] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A vehicle NVH performance evaluation method, characterized in that: The following steps are involved: Obtaining the NVH evaluation item of the current vehicle, the scores of multiple first users on each evaluation sub-item of the NVH evaluation item, and the number of positive and negative reviews of multiple second users on each evaluation sub-item; Based on the score of each first user on each evaluation sub-item, the professional average score of each evaluation sub-item is calculated, and based on the number of positive reviews and the number of negative reviews of each second user on each evaluation sub-item, the market raw score of each evaluation sub-item is obtained, and the market raw score is normalized to obtain the market reputation score of each evaluation sub-item; The NVH score of the current vehicle is obtained according to the professional average score of each evaluation sub-item and the market reputation score of each evaluation sub-item.

2. The method according to claim 1, characterized in that The NVH score of the current vehicle is obtained according to the professional average score of each evaluation sub-item and the market reputation score of each evaluation sub-item, including: Obtaining a professional score for each evaluation sub-item according to the professional average score of each evaluation sub-item and the first preset weight of each evaluation sub-item, and obtaining a market score for each evaluation sub-item according to the market reputation score of each evaluation sub-item and the second preset weight of each evaluation sub-item; According to the professional score of each evaluation sub-item, the market score of each evaluation sub-item and the third preset weight of each evaluation sub-item, the total score of each evaluation sub-item is obtained, and the NVH score of the current vehicle is obtained by summing the total scores of each evaluation sub-item.

3. The method according to claim 1, characterized in that The obtaining of the market original score of each evaluation sub-item based on the number of positive comments and the number of negative comments by each second user on each evaluation sub-item, and normalizing the market original score to obtain the market reputation score of each evaluation sub-item includes: Calculate the difference between the number of positive reviews of each evaluation sub-item and the number of negative reviews of each evaluation sub-item, and calculate the ratio of the difference to the total number of reviews of each evaluation sub-item to obtain the original market score of each evaluation sub-item; The product of the original market score of each evaluation sub-item and the first preset threshold of each evaluation sub-item is calculated, and the sum of the product and the second preset threshold of each evaluation sub-item is calculated to obtain the market reputation score of each evaluation sub-item.

4. The method according to claim 2, characterized in that: The first preset weight, the second preset weight and the third preset weight are determined by the importance between the evaluation sub-items of the NVH evaluation item.

5. The method according to any one of claims 1 to 4, characterized in that The NVH evaluation item of the current vehicle includes at least one of a road noise evaluation sub-item, a wind noise evaluation sub-item, an acceleration / deceleration evaluation sub-item, an abnormal noise evaluation sub-item and a sound quality evaluation sub-item.

6. A vehicle NVH performance evaluation device, characterized in that: include: An acquisition module, used to acquire the NVH evaluation item of the current vehicle, the scores of multiple first users on each evaluation sub-item of the NVH evaluation item, and the number of positive and negative reviews of multiple second users on each evaluation sub-item; A processing module, configured to calculate the professional average score of each evaluation sub-item based on the score of each first user on each evaluation sub-item, and obtain the market raw score of each evaluation sub-item based on the number of positive reviews and the number of negative reviews of each second user on each evaluation sub-item, and perform normalization processing on the market raw score to obtain the market reputation score of each evaluation sub-item; The calculation module is used to obtain the NVH score of the current vehicle according to the professional average score of each evaluation sub-item and the market reputation score of each evaluation sub-item.

7. The device according to claim 6, characterized in that The processing module is used for: Obtaining a professional score for each evaluation sub-item according to the professional average score of each evaluation sub-item and the first preset weight of each evaluation sub-item, and obtaining a market score for each evaluation sub-item according to the market reputation score of each evaluation sub-item and the second preset weight of each evaluation sub-item; According to the professional score of each evaluation sub-item, the market score of each evaluation sub-item and the third preset weight of each evaluation sub-item, the total score of each evaluation sub-item is obtained, and the NVH score of the current vehicle is obtained by summing the total scores of each evaluation sub-item.

8. The device according to claim 6, characterized in that The processing module is used for: Calculate the difference between the number of positive reviews of each evaluation sub-item and the number of negative reviews of each evaluation sub-item, and calculate the ratio of the difference to the total number of reviews of each evaluation sub-item to obtain the original market score of each evaluation sub-item; The product of the original market score of each evaluation sub-item and the first preset threshold of each evaluation sub-item is calculated, and the sum of the product and the second preset threshold of each evaluation sub-item is calculated to obtain the market reputation score of each evaluation sub-item.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the vehicle NVH performance evaluation method as described in any one of claims 1 to 5.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the vehicle NVH performance evaluation method as described in any one of claims 1 to 5.

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