Passenger car abnormal sound inspection method based on DMU and computer equipment
Through the DMU-based passenger car abnormal noise inspection method, historical data is obtained, a DMU model is built, and structural data is evaluated. The difficult problems of preventing and solving abnormal noise problems in passenger cars are solved, a mode shift from passive to active is achieved, and ride comfort and vehicle quality are improved.
Patent Information
- Application Number
- CN202510706342.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-29
- Publication Date
- 2025-09-19
AI Technical Summary
Existing technologies are difficult to effectively prevent and solve the problem of abnormal noise generated by passenger cars during driving, which affects user riding comfort and vehicle safety.
A noise inspection method based on a digital vehicle model (DMU) is used to obtain historical noise data, build a DMU model for the target vehicle model, determine the integrity and accuracy of vehicle data, evaluate structural data, and discover and resolve potential noise problems.
It has achieved a shift from the passive "test-and-rectify" mode to the active "prediction-and-prevention" mode, improving the efficiency of predicting and resolving abnormal noise problems, reducing design-related abnormal noise problems, and improving user riding comfort and vehicle quality.
Smart Images
Figure CN120668252A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of vehicle abnormal noise prevention methods, and in particular to a DMU-based passenger vehicle abnormal noise inspection method and computer equipment. Background Art
[0002] Currently, abnormal noise and squeaks account for approximately 30%-50% of passenger car noise complaints, with the specific proportion varying by vehicle model and technology type. Traditional mechanical components (steering, transmission) account for a higher proportion, while new energy vehicle noise and squeaks are more often related to electronic devices or new structural designs. Automakers need to optimize design and testing processes for different technology paths to minimize the impact of these noise and squeaks on passenger comfort. The "2024 Passenger Car Initial Quality Report" lists interior noise and squeaks (such as those in the center console) as a major complaint point. Furthermore, cracked dashboards and body noise and squeaks frequently appear on the complaint list for Japanese vehicles such as Toyota and Honda. Vehicle noise and squeaks are abnormal noises produced during normal driving or operation. They are typically caused by loose components or improper design, resulting in changes in relative displacement between parts. These noises are often irregular and unpleasant, resulting from friction, impact, or resonance. Squeaks and squeaks are a type of noise that directly impacts the level of noise within the noise, harshness, or humming (NVH) framework, a key metric used to assess vehicle comfort and quietness. Abnormal noises will reduce the user's riding comfort experience. Continuous abnormal noises will make users feel that there are problems with the vehicle's quality. Some abnormal noises may also be early warning signals of potential faults, affecting the vehicle's normal driving safety. Summary of the Invention
[0003] To address at least one aspect of the above-mentioned problems, the present invention provides a DMU-based passenger car abnormal noise inspection method, comprising: acquiring abnormal noise historical data, determining abnormal noise inspection item information based on the abnormal noise historical data, wherein the abnormal noise inspection item information includes an inspection target and structural parameters corresponding to the inspection target; constructing a DMU model of a target vehicle model, judging the integrity of the whole vehicle data of the DMU model in response to a received inspection instruction, judging the accuracy of the whole vehicle data when the whole vehicle data is complete, judging whether the whole vehicle coordinates of the DMU model are qualified when the whole vehicle data accuracy is qualified, determining the structural data of the inspection target based on the abnormal noise inspection items and the whole vehicle data when the whole vehicle coordinates are qualified, and evaluating the structural data based on the structural parameters of the inspection target; returning unqualified inspection target information when the structural data of the inspection target is unqualified, and updating the DMU model based on the unqualified inspection target when the structural data of the inspection target is qualified; and performing actual vehicle inspection on the target vehicle model when the structural data of the inspection target is qualified.
[0004] Preferably, the actual vehicle detection result is obtained, and when the actual vehicle detection result includes abnormal noise, the abnormal noise inspection item is updated according to the abnormal noise.
[0005] Preferably, the structural parameters include interference parameters, contact parameters and distance parameters.
[0006] Preferably, the abnormal noise inspection item information also includes the inspection area, inspection subsystem, and inspection subassembly corresponding to the inspection target.
[0007] Preferably, the inspection area includes a cabin area and a floor area.
[0008] Preferably, the inspection subsystem of the cockpit area includes the air conditioner, the instrument area, the seat, the A, B, C, and C pillars, the door area and the luggage compartment, and the inspection subsystem of the floor area includes the fuel system module.
[0009] Preferably, the inspection targets of the cockpit area include the left foot air duct opening, the left foot air outlet duct and the surrounding cover and anti-collision bar, the right foot air duct opening, the right air duct opening fixing method and the bottom cover and surrounding parts, the side cover fixing buckle, the glove box buffer device, the instrument panel display support buckle, the instrument panel display fixing structure and the instrument cover, the storage box buffer device, the seat belt latch of the foot side cover, the middle armrest buffer device, the switch button, the seat belt retractor and the sheet metal, the seat belt Lock tongue and guard plate, A-pillar guard plate and instrument panel, C-pillar guard plate and glass, trim and ambient light frame, inner opening handle, inner opening handle buffer device, door guard plate frame and door sheet metal, left front door glass and door sheet metal, left front door glass and limiter, left rear door glass and door sheet metal, left rear door glass and limiter, inner molding, left front door lock bracket and glass and outer handle, side guard plate, rear cover guard plate pipeline and wiring harness, trunk lock, trunk lock and lock hook, spare tire tool and tire, fuel pipe, fuel pipe and peripheral parts.
[0010] On the other hand, a computer device is provided, comprising a memory and a processor, wherein the memory comprises a computer program, and when the computer program is executed by the processor, the method for detecting abnormal noise of a passenger car based on a DMU as claimed in any one of claims 1 to 7 is implemented.
[0011] The DMU-based passenger car abnormal noise inspection method according to the embodiment of the present invention has the following beneficial effects: Traditionally, abnormal noise problems of the entire vehicle are discovered through testing, focusing on a test-and-rectification system analysis of abnormal noise problems within the entire vehicle. The core value of the passenger car abnormal noise inspection method according to the embodiment of the present invention, which is based on the DMU model, lies in transforming the traditional "test-and-rectify" passive mode into an "prediction-and-prevention" active mode, and summarizing multiple abnormal noise inspection items as inspection standard items, thereby realizing a "prediction-and-prevention" abnormal noise solution for the entire vehicle. BRIEF DESCRIPTION OF THE DRAWINGS
[0012] To better understand the above and other objects, features, advantages, and functions of the present invention, reference may be made to the embodiments shown in the accompanying drawings. Like reference numerals in the accompanying drawings refer to like components. Those skilled in the art should understand that the accompanying drawings are intended to schematically illustrate preferred embodiments of the present invention and have no limiting effect on the scope of the present invention. The components in the drawings are not drawn to scale.
[0013] Figure 1 A flow chart of a method for detecting abnormal noise in a passenger car based on a DMU according to an embodiment of the present invention is shown;
[0014] Figure 2 A schematic diagram of an application scenario based on a DMU according to an embodiment of the present invention is shown. DETAILED DESCRIPTION
[0015] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.
[0016] As used herein, the term "including" and its variations represent open inclusion, i.e., "including but not limited to." Unless otherwise stated, the term "or" means "and / or." The term "based on" means "based at least in part on." The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment." The term "another embodiment" means "at least one additional embodiment." The terms "first," "second," etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.
[0017] In order to at least partially solve one or more of the above problems and other potential problems, the embodiments of the present disclosure provide a method for detecting abnormal noise in passenger vehicles based on a DMU, such as Figure 1 As shown, it includes: step S1, obtaining abnormal sound history data, and determining abnormal sound inspection item information according to the abnormal sound history data, where the abnormal sound inspection item information includes an inspection target and a structural parameter corresponding to the inspection target.
[0018] Specifically, the abnormal noise history data includes abnormal noise data for multiple vehicle models. The abnormal noise data includes the abnormal noise area, abnormal road conditions, and abnormal noise audio. The abnormal noise inspection item information is determined based on the abnormal noise data. The inspection target is determined based on the abnormal noise area and abnormal noise audio. The design parameters of the inspection target are determined based on the inspection target. The structural parameters corresponding to the inspection target are determined based on the inspection target's design parameters, abnormal noise audio, and abnormal road conditions. For example, the cause of the abnormal noise is determined based on the inspection target's design parameters, abnormal noise audio, and abnormal road conditions, and the structural parameters of the inspection target are determined based on the cause of the abnormal noise.
[0019] In some embodiments, the structural parameters include interference parameters, contact parameters, and distance parameters.
[0020] Specifically, the interference parameters are used to determine the minimum preset gap between inspection targets with an interference relationship, the contact parameters are used to determine the thresholds of contact stiffness, friction coefficient, contact area, and penetration depth between inspection targets with a contact relationship, and the distance parameters are used to determine the distance threshold between adjacent inspection targets.
[0021] Step S2: Build a DMU model of the target vehicle model. In response to the received inspection instruction, determine the integrity of the vehicle data of the DMU model. When the vehicle data is complete, determine the accuracy of the vehicle data. When the accuracy of the vehicle data is qualified, determine whether the vehicle coordinates of the DMU model are qualified. When the vehicle coordinates are qualified, determine the structural data of the inspection target based on the abnormal sound inspection items and the vehicle data. Evaluate the structural data based on the structural parameters of the inspection target.
[0022] Specifically, the DMU model includes the entire vehicle data, including the structural data, electrical data, and motion data of the target vehicle model. The DMU model is constructed as the object of abnormal noise inspection.
[0023] The authenticity of the DMU model is ensured by verifying the integrity of the entire vehicle data. In some embodiments, the DMU model's entire vehicle data is individually checked using the complete data sheet of the target vehicle model. For example, the dashboard area is a parts assembly, containing many body parts, electronic components, and wiring harnesses. Therefore, the DMU model's entire vehicle data must be checked to ensure that the digital prototype accurately reflects the physical prototype. Incomplete inspection data can affect the DMU inspection results. For example, if the air conditioning assembly data lacks data on the connection with the left footwell air duct, the DMU inspection cannot be performed. The accuracy of the structural parameters of the inspection target is ensured by verifying the accuracy of the entire vehicle data. The coordinate system of the associated inspection target's structural data is ensured by verifying the entire vehicle coordinates, ensuring the stability of the inspection results.
[0024] In some embodiments, a detection module for realizing abnormal noise detection includes a complete data checking unit, a whole vehicle data accuracy checking unit, a whole vehicle coordinate checking unit and an inspection target structure data evaluation unit. The complete data checking unit is used to check the whole vehicle data of the DMU model one by one according to the complete data table of the preset target vehicle model, and output a whole vehicle data complete signal when the whole vehicle data is complete. The whole vehicle data accuracy checking unit detects the whole vehicle data accuracy according to the preset whole vehicle data accuracy table in response to the whole vehicle data complete signal output by the complete data checking unit, and outputs a whole vehicle data accuracy qualified signal when the whole vehicle data accuracy is qualified. The whole vehicle coordinate checking unit judges the whole vehicle coordinates in response to the received whole vehicle data accuracy qualified signal, and outputs whole vehicle coordinate qualified information when the coordinate system of the whole vehicle coordinates is consistent with the coordinate system corresponding to the whole vehicle data. The inspection target structure data evaluation unit evaluates the inspection target according to the preset inspection target structure parameters in response to the received whole vehicle coordinate qualified information.
[0025] According to the data involved in each inspection standard, if the data source is newly developed, it needs to be provided by the designer. If the data is borrowed from other models, it can be found in the existing database.
[0026] Step S3: When the structural data of the inspection target is unqualified, the unqualified inspection target information is returned, and the DMU model is updated according to the unqualified inspection target. When the structural data of the inspection target is qualified, the target vehicle model is subjected to actual vehicle inspection.
[0027] Specifically, when the structural data of the inspection target fails, the designer is prompted to modify the structural data of the inspection target by returning the failed inspection target. When all inspection targets pass, actual vehicle inspection is performed, such as verification through experiments.
[0028] like Figure 2For example, the DMU inspection and analysis of the noise between the left foot duct and the air conditioner first determines the inspection data scope, including the instrument panel and the auxiliary instrument panel. The integrity of the body and electrical data must be verified, ensuring no missing data. The data quality is then verified to ensure it meets the required accuracy and precision requirements, and the vehicle coordinates are correct. Finally, an analysis is performed to ensure that no kinematic relationships exist between the data. Inspections are then conducted according to the inspection standards. The first inspection revealed a 0.2mm clearance between the duct and the air conditioner, contrary to the standard requirement of 0mm. A 0.2mm clearance can lead to loose assembly between the duct and the air conditioner during normal driving, resulting in flexible coupling and periodic collision or friction, which can cause noise. After consultation with the duct designer, they agreed to modify the design to meet the inspection standard of a 0mm clearance between the duct and the air conditioner. Furthermore, the second phase of the vehicle noise DMU inspection confirmed that the vehicle noise and noise issue met the inspection standard. Subsequent subjective evaluations of the road test also confirmed no noise issues in this area.
[0029] Before the advent of the DMU inspection standard for abnormal noise, subjective and objective evaluation tests were typically conducted simultaneously. The frequent occurrence of design-related abnormal noise issues often necessitated multiple rounds of testing to identify and resolve them, which was time-consuming, labor-intensive, and costly. Vehicle projects that meet the DMU inspection standard for abnormal noise significantly reduce the number of design-related abnormal noise issues identified through subjective evaluation, often even eliminating them altogether for some models. Focusing on design solutions that do not meet the DMU inspection standard for abnormal noise also improves testing efficiency. Generally, abnormal noise issues are present during road tests that do not meet the DMU inspection standard. Road tests that meet the DMU inspection standard do not exhibit any abnormal noise issues. Newly identified abnormal noise issues not covered by the 34 abnormal noise inspection standards are classified as accumulated abnormal noise issues for statistical analysis. When a DMU inspection standard for the accumulated issue can be derived using the vehicle-wide abnormal noise analysis method based on DMU technology, this accumulated issue is transformed into a new abnormal noise inspection standard, added to the existing abnormal noise inspection standard library, and provided to designers as a new design standard.
[0030] In some embodiments, actual vehicle inspection results are obtained, and when the actual vehicle inspection results include abnormal noise, the abnormal noise inspection item is updated according to the abnormal noise.
[0031] Specifically, actual vehicle testing is performed on target vehicle models that have passed the DMU model abnormal noise detection, and the test results are recorded. For example, actual vehicle testing is performed using general passenger car abnormal noise evaluation road standards and load spectrum collection specifications.
[0032] In some embodiments, the abnormal noise inspection item information also includes the inspection area, inspection subsystem, and inspection subassembly corresponding to the inspection target.
[0033] Specifically, accurate positioning of the inspection target can be achieved through information on the inspection area, inspection subsystem and inspection subassembly corresponding to the inspection target. For example, when an abnormal noise occurs, it is usually the result of the interaction between multiple parts. Therefore, accurate positioning of the inspection target can be achieved through information such as the inspection area to which each inspection target belongs.
[0034] In some embodiments, the inspection area includes a cabin area and a floor area. In some embodiments, the inspection subsystem of the cabin area includes air conditioning, an instrument area, seats, ABC columns, a door area, and a trunk, and the inspection subsystem of the floor area includes a fuel system module.
[0035] In some embodiments, the inspection targets of the cockpit area include the left foot air duct, the left foot air outlet duct and the surrounding cover and anti-collision bar, the right foot air duct, the right air duct fixing method and the bottom cover and surrounding parts, the side cover fixing buckle, the glove box buffer device, the instrument panel display support buckle, the instrument panel display fixing structure and the instrument cover, the storage box buffer device, the seat belt latch of the foot side cover, the middle armrest buffer device, the switch button, the seat belt retractor and the sheet metal, the safety With lock tongue and guard plate, A-pillar guard plate and instrument panel, C-pillar guard plate and glass, trim and ambient light frame, inner opening handle, inner opening handle buffer device, door guard plate frame and door sheet metal, left front door glass and door sheet metal, left front door glass and limiter, left rear door glass and door sheet metal, left rear door glass and limiter, inner molding, left front door lock bracket and glass and outer handle, side guard plate, rear cover guard plate pipeline and wiring harness, trunk lock, trunk lock and lock hook, spare tire tool and tire, fuel pipe, fuel pipe and peripheral parts.
[0036] On the other hand, a computer device is provided, including a memory and a processor, wherein the memory includes a computer program, and when the computer program is executed by the processor, the computer program implements any of the above-mentioned methods for detecting abnormal noises in passenger cars based on a DMU.
[0037] Specifically, the computer devices in the embodiments of the present application may include but are not limited to mobile terminals such as laptop computers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), etc., and fixed terminals such as digital TVs, desktop computers, etc.
[0038] A computer device may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) that can perform various appropriate actions and processes according to a program stored in a read-only memory or a program loaded from a memory into a random access memory. The processing device, the read-only memory, and the random access memory are connected to each other via a bus.
[0039] While various embodiments of the present disclosure have been described above, the foregoing description is intended to be illustrative, non-exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is selected to best explain the principles of the embodiments, their practical applications, or technological improvements in the marketplace, or to enable others skilled in the art to understand this document.
Claims
1. A passenger car abnormal noise inspection method based on DMU, characterized in that: include: Acquiring abnormal noise historical data, and determining abnormal noise inspection item information based on the abnormal noise historical data, wherein the abnormal noise inspection item information includes an inspection target and a structural parameter corresponding to the inspection target; Construct a DMU model of the target vehicle model, determine the integrity of the vehicle data of the DMU model in response to the received inspection instruction, determine the accuracy of the vehicle data if the vehicle data is complete, determine whether the vehicle coordinates of the DMU model are qualified if the vehicle data accuracy is qualified, determine the structural data of the inspection target based on the abnormal noise inspection items and the vehicle data if the vehicle coordinates are qualified, and evaluate the structural data based on the structural parameters of the inspection target; When the structural data of the inspection target fails to meet the requirements, the unqualified inspection target information is returned, and the DMU model is updated according to the unqualified inspection target. When the structural data of the inspection target meets the requirements, the target vehicle model is subjected to actual vehicle inspection.
2. The method according to claim 1, characterized in that Obtain the actual vehicle inspection results. When the actual vehicle inspection results include abnormal noise, update the abnormal noise inspection items based on the abnormal noise.
3. The method according to claim 2, characterized in that Structural parameters include interference parameters, contact parameters and distance parameters.
4. The method according to claim 3, characterized in that The abnormal noise inspection item information also includes the inspection area, inspection subsystem, and inspection subassembly corresponding to the inspection target.
5. The method according to claim 3, characterized in that The inspection area includes the cockpit area and the floor area.
6. The method according to claim 3, characterized in that The inspection subsystem of the cockpit area includes air conditioning, instrument area, seats, ABC columns, door area and luggage compartment, and the inspection subsystem of the floor area includes the fuel system module.
7. The method according to claim 3, characterized in that The inspection targets of the cockpit area include the left foot air duct, the left foot air outlet duct and the surrounding cover and anti-collision bar, the right foot air duct, the right air duct fixing method and the bottom cover and surrounding parts, the side cover fixing buckle, the glove box buffer device, the instrument panel display support buckle, the instrument panel display fixing structure and the instrument cover, the storage box buffer device, the seat belt latch of the foot side cover, the middle armrest buffer device, the switch button, the seat belt retractor and sheet metal, and the seat belt lock tongue And guard plate, A-pillar guard plate and instrument panel, C-pillar guard plate and glass, trim and ambient light frame, inner opening handle, inner opening handle buffer device, door guard plate frame and door sheet metal, left front door glass and door sheet metal, left front door glass and limiter, left rear door glass and door sheet metal, left rear door glass and limiter, inner molding, left front door lock bracket and glass and outer handle, side guard plate, rear cover guard plate pipeline and wiring harness, trunk lock, trunk lock and lock hook, spare tire tool and tire, fuel pipe, fuel pipe and peripheral parts.
8. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory comprises a computer program, and when the computer program is executed by the processor, the method for detecting abnormal noise of a passenger car based on a DMU as claimed in any one of claims 1 to 7 is implemented.