Automobile window opening noise reduction control method and system based on working condition self-adaption and application

Abstract

The invention belongs to the technical field of automobile noise control, and provides an automobile windowing noise reduction control method and system based on working condition self-adaption and application, and the method comprises the steps that when it is detected that an automobile meets active noise reduction conditions, multi-dimensional working condition data are synchronously collected; based on the multi-dimensional working condition data, the current driving working condition is determined through a wind noise-working condition prediction model, and airflow control parameters and acoustic control parameters are obtained through calculation; according to the airflow control parameters, an intelligent flow deflector array arranged on the upper edge of the vehicle window is driven to act to the target angle; meanwhile, according to the acoustic control parameters, sound signals inside and outside the vehicle are collected, and corresponding offset sound waves and optimized sound signals are output after acoustic processing; and when it is detected that the vehicle meets the maintenance condition, the intelligent flow deflector array is controlled to reset, and self-cleaning operation is executed on the intelligent flow deflector array. According to the invention, a dual noise reduction mechanism of active diversion and acoustic offset is adopted, the noise reduction effect is greatly improved, selective sound scene management can be realized, and the driving and riding comfort is improved.

Description

Technical Field

[0001] This application relates to the field of automotive noise control technology, and in particular to a method, system and application of automotive window opening noise reduction control based on operating condition adaptation. Background Technology

[0002] When a traditional car is traveling at high speed with the windows open, large-scale turbulent vortices are generated at the edge of the window opening due to the shearing effect of the high-speed airflow. These vortices periodically impact the rear edge of the window, exciting Helmholtz resonance in the air cavity inside the car, and thus generating strong wind noise with frequencies concentrated in the 100-500Hz range. This noise has a high sound pressure level and strong penetrating power, easily causing physiological discomfort such as tinnitus and dizziness for passengers. It also causes frequent fluctuations in air pressure inside the car, seriously affecting driving comfort and speech clarity.

[0003] To address this issue, the industry currently employs two main technological approaches, but both have significant shortcomings:

[0004] I. Physical Isolation Technology: This method passively intervenes in airflow using static structures. It mechanically blocks or guides the airflow into the vehicle by adding fixed deflectors, windscreens, or sealing strips at the window openings. Its noise reduction principle lies in disrupting the conditions for turbulent vortex formation or altering the airflow path. Real-world testing shows that optimized physical isolation can reduce wind noise by up to 10-15 dB. However, this rigid isolation method completely blocks direct air exchange between the vehicle interior and the external environment, preventing users from experiencing the natural airflow and the sense of openness and interaction with the outside world. This not only defeats the core purpose of window ventilation but also renders the fixed structure unsuitable for varying driving conditions, appearing simplistic and passive.

[0005] II. Electronic Noise Cancellation Technology: Traditional in-vehicle active noise cancellation (ANC) systems primarily target steady-state low-frequency noise such as engine noise. Their working principle involves collecting noise signals through microphones, generating inverse sound waves through a processor, and playing them through speakers to achieve acoustic cancellation. However, when applied to scenarios with windows open, their inherent limitations become apparent: the system struggles to effectively distinguish between "harmful wind noise" that needs to be suppressed and "beneficial environmental sounds" (such as birdsong, distant traffic audibles, and nearby human voices) that should be preserved. While the generated broadband inverse sound waves cancel out wind noise, they indiscriminately suppress most external sounds, resulting in a muffled auditory experience with open windows and a lack of spatial depth. More importantly, ANC technology only operates at the acoustic level and is completely ineffective against the physical impact of airflow turbulence and air pressure fluctuations.

[0006] Furthermore, with the development of automotive noise control technology, more advanced noise optimization methods have emerged in the market. For example, patent application CN119940209A discloses a method, device, equipment, and storage medium for optimizing automotive wind vibration noise, relating to the field of automotive noise control technology. The disclosed method for optimizing automotive wind vibration noise includes: responding to a current window opening command and acquiring the current vehicle speed, current window opening state, and a window opening control parameter table; determining an initial window opening combination based on the current window opening command and the current window opening state; determining a target window opening command based on the current vehicle speed, the initial window opening combination, the window opening control parameter table, and the current window opening command; and responding to the target window opening command and controlling the target window to the target window opening degree to complete the automotive wind vibration noise optimization. This solution can optimize automotive wind vibration noise during driving with the windows open at low cost by adjusting the current window opening command. Furthermore, based on parameters such as vehicle speed and window opening degree, this solution automatically selects the optimal window opening combination through a predefined window opening control parameter table, thereby disrupting the resonance conditions of wind vibration noise. However, this method is based on a predefined window opening control parameter table and cannot adapt to dynamic driving conditions such as crosswinds and tunnels in real time. Summary of the Invention

[0007] In view of the shortcomings of the prior art, the present invention provides a method, system and application for vehicle window opening noise reduction control based on working condition adaptation. It adopts a dual noise reduction mechanism of active airflow guidance and acoustic cancellation, which greatly improves the noise reduction effect and can realize selective sound scene management to improve driving comfort.

[0008] To achieve the above and related objectives, the present invention adopts the following technical solution:

[0009] The first aspect of this invention provides a vehicle window noise reduction control method based on operating condition adaptation, comprising the following steps:

[0010] Step S100: When the vehicle is detected to meet the active noise reduction conditions, multi-dimensional operating condition data is collected simultaneously.

[0011] Step S200: Based on multi-dimensional operating condition data, determine the current driving condition through the wind noise-operating condition prediction model, and calculate the airflow control parameters and acoustic control parameters.

[0012] In step S300, according to the airflow control parameters, the intelligent air guide array set on the upper edge of the window is driven to move to the target angle to shape the airflow flowing into the vehicle; at the same time, according to the acoustic control parameters, the sound signals inside and outside the vehicle are collected, and after acoustic processing, the corresponding canceling sound waves and optimized sound signals are output.

[0013] In step S400, when the vehicle is detected to meet the maintenance conditions, the intelligent guide vane array is reset and a self-cleaning operation is performed on the intelligent guide vane array.

[0014] Furthermore, in step S100, the active noise reduction conditions include the window opening reaching a first preset threshold, or the vehicle being predicted to enter a preset special road section based on navigation information. The special road section includes tunnels, crosswind zones of viaducts, and highways.

[0015] Furthermore, in step S300, driving the intelligent air deflector array positioned along the upper edge of the window to the target angle includes:

[0016] When the current driving condition is the first type of condition, the thermal deformation characteristics of the shape memory alloy component are used to drive the intelligent guide vane array to perform basic angle adjustment.

[0017] When the current driving condition is the second type of condition, the micro stepper motor is started to finely adjust the angle of the intelligent guide vane array;

[0018] The complexity of the second type of working condition is higher than that of the first type of working condition.

[0019] Further, in step S300, the acoustic processing includes:

[0020] The system performs spectral decoupling on the sound signals inside and outside the vehicle to separate wind noise, ambient sound, and in-vehicle sound signals. Based on the wind noise, it generates corresponding canceling sound waves. After amplifying the ambient sound signal, it outputs an optimized sound signal.

[0021] Furthermore, step S300 also includes:

[0022] Real-time monitoring of whether multi-dimensional operating condition data changes;

[0023] If changes occur, steps S200 and S300 will be re-executed within a preset delay time to update the control parameters and execute actions.

[0024] Furthermore, in step S400, performing a self-cleaning operation on the intelligent flow guide array includes:

[0025] After the intelligent guide vane array is reset, a miniature high-pressure air pump is started, and a high-speed airflow is sprayed onto the surface of the intelligent guide vane array through the built-in air channel opened at the root of the intelligent guide vane array.

[0026] Furthermore, after step S300, the method further includes:

[0027] In response to user input adjustment commands, the system prioritizes adjusting airflow control parameters and / or acoustic control parameters according to the adjustment commands, and stores the parameter preferences corresponding to the adjustment commands in the user's associated file.

[0028] A second aspect of the present invention provides a vehicle window noise reduction control system based on operating condition adaptation, comprising:

[0029] The data acquisition module is used to simultaneously acquire multi-dimensional operating condition data when the vehicle is detected to meet the active noise reduction conditions;

[0030] The calculation module is used to determine the current driving conditions based on multi-dimensional operating condition data through a wind noise-operating condition prediction model, and to calculate airflow control parameters and acoustic control parameters.

[0031] The execution module is used to drive the intelligent air guide array set on the upper edge of the window to move to the target angle according to the airflow control parameters in order to shape the airflow flowing into the vehicle; at the same time, according to the acoustic control parameters, it collects the sound signals inside and outside the vehicle, and outputs corresponding canceling sound waves and optimized sound signals after acoustic processing.

[0032] The maintenance module is used to control the intelligent deflector array to reset and perform a self-cleaning operation on the intelligent deflector array when the vehicle is detected to meet the maintenance conditions.

[0033] A third aspect of the present invention provides a computer-readable storage medium storing computer-readable instructions thereon, which, when executed by a computer's processor, cause the computer to execute the aforementioned vehicle window opening noise reduction control method based on operating condition adaptation.

[0034] A fourth aspect of the present invention provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described adaptive vehicle window noise reduction control method.

[0035] The beneficial technical effects of this invention are as follows:

[0036] This invention uses an intelligent airflow guide array to shape the turbulent flow entering the vehicle into laminar flow, reducing wind noise at its source; and generates anti-phase canceling sound waves through acoustic processing to accurately cancel residual wind noise, further reducing noise. Thus, it achieves a dual noise reduction mechanism of active airflow guidance and acoustic cancellation, significantly improving the noise reduction effect.

[0037] This invention allows passengers to enjoy natural breezes while effectively suppressing external noise when the car windows are open. It breaks the traditional contradiction of "open windows are noisy and comfort requires closed windows" and creates a third option of "gentle airflow, low noise, and clear ambient sound," greatly enhancing the driving and riding experience.

[0038] This invention can predict and extract operating conditions, realize multi-dimensional operating condition perception, and has good intelligent adaptive capabilities, enabling it to adapt to changing driving conditions.

[0039] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0040] The accompanying drawings, incorporated in and forming part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without inventive effort. In the drawings:

[0041] Figure 1 This is a flowchart of the vehicle window opening noise reduction control method based on working condition adaptation in this application;

[0042] Figure 2 This is a schematic diagram of the intelligent laminar flow generation module and the window structure of this application;

[0043] Figure 3 This is a schematic diagram showing the connections between the modules in this application;

[0044] Figure 4 This is a framework diagram of the automotive window opening noise reduction control system based on working condition adaptation in this application;

[0045] Figure 5 A schematic diagram of the structure of a computer system suitable for an embodiment of this application is shown. Detailed Implementation

[0046] Unless otherwise defined, all technical and / or scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should be understood that certain features of the invention (described in the context of separate embodiments for clarity) may also be provided in a single embodiment. Conversely, multiple features of the invention (described in the context of a single embodiment for brevity) may also be provided separately or in any suitable combination or, where appropriate, in any other described embodiment of the invention. Certain features described in the context of various embodiments will not be considered essential features of those embodiments unless the embodiment is inoperable without those elements. The invention is further illustrated below by specific examples; however, it should be noted that the specific process conditions and results described in the embodiments of the invention are merely illustrative and should not be construed as limiting the scope of protection of the invention. All equivalent changes or modifications made in accordance with the spirit and essence of the invention should be covered within the scope of protection of the invention.

[0047] Please refer to Figure 1, which is a flowchart of the vehicle window opening noise reduction control method based on working condition adaptation in this application, detailed below:

[0048] Step S100: When the vehicle is detected to meet the active noise reduction conditions, multi-dimensional operating condition data are collected simultaneously.

[0049] Specifically, the active noise reduction conditions of this application include the window opening reaching a first preset threshold, or the vehicle being predicted to enter a preset special road section based on navigation information. Special road sections include tunnels, crosswind zones of elevated bridges, and highways. The first preset threshold is set according to actual needs, such as 5cm. The "imminent" threshold referred to in this application can be the prediction that the vehicle will enter the special road section 1 to 3 seconds beforehand.

[0050] Specifically, in combination Figure 3 This application can synchronously collect multi-dimensional operating condition data through the dimensional operating condition perception module of the vehicle system, including:

[0051] 1) The basic operating condition data obtained by the basic operating condition sensor is reused by the original vehicle speed sensor and the window opening sensor installed on the window guide rail to obtain the vehicle driving status and window opening degree in real time.

[0052] 2) Environmental condition data acquired by environmental perception sensors, including a miniature weather station integrated on the roof of the vehicle, which contains a wind speed sensor, a wind direction sensor and a temperature sensor, used to acquire the airflow environment outside the vehicle in real time.

[0053] 3) Passenger condition data acquired by passenger perception sensors are used to identify passenger sitting posture and head position by installing infrared array sensors inside the vehicle, which provides a targeted basis for adjusting the angle of the intelligent air guide array.

[0054] 4) The prediction module obtains future road condition data and connects it to the vehicle navigation system. When it detects that it is about to enter a tunnel, crosswind area under an overpass, or highway section, it starts the system pre-adjustment 1 to 3 seconds in advance to avoid fluctuations in experience caused by sudden changes in operating conditions.

[0055] Step S200: Based on multi-dimensional operating condition data, the current driving condition is determined by the wind noise-operating condition prediction model, and the airflow control parameters and acoustic control parameters are calculated.

[0056] Specifically, the vehicle-mounted central control unit of this application receives and integrates the aforementioned multi-dimensional operating condition data. It compares the current multi-dimensional operating condition data with preset operating conditions using a wind noise-operating condition prediction model to determine the current driving condition of the vehicle. This includes low-speed cruising, primarily referring to urban road driving at lower speeds, such as below 60 km / h; high-speed driving, primarily referring to highway driving at higher speeds, such as above 80 km / h; crosswind conditions, primarily triggered when a significant crosswind is detected by a micro-weather station; and tunnel conditions, triggered by navigation system prediction or sudden airflow changes upon entering a tunnel. The wind noise-operating condition prediction model of this application is a model with machine learning and advanced logic, trained through extensive wind tunnel testing and real-vehicle data.

[0057] Specifically, after determining the current driving conditions, this application calculates airflow control parameters, specifically the target angle of the intelligent air deflector array, based on passenger position information. This application also fine-tunes the angle of the intelligent air deflector array based on passenger head position to ensure that the shaped laminar flow accurately bypasses the passenger's head area, maximizing comfort and avoiding direct airflow. Furthermore, based on the predicted wind noise characteristic frequency and intensity under the current conditions, the model calculates the amplitude and phase of the anti-phase sound wave to be generated, i.e., the cancellation intensity. The model also intelligently determines which external sounds, such as birdsong, ocean waves, and important traffic announcements, are beneficial environmental sounds by combining vehicle speed, window opening, and external sensor data, and calculates an optimal gain value to preserve or even moderately enhance them, ultimately obtaining the acoustic control parameters.

[0058] In step S300, according to the airflow control parameters, the intelligent air guide array set on the upper edge of the window is driven to move to the target angle to shape the airflow flowing into the vehicle; at the same time, according to the acoustic control parameters, the sound signals inside and outside the vehicle are collected, and after acoustic processing, the corresponding canceling sound waves and optimized sound signals are output.

[0059] Specifically, the method by which this application drives the intelligent air deflector array located on the upper edge of the vehicle window to move to the target angle includes:

[0060] When the current driving condition is the first type of condition, the thermal deformation characteristics of the shape memory alloy components are used to drive the intelligent guide vane array to perform basic angle adjustment;

[0061] When the current driving condition is the second type, the micro stepper motor is activated to fine-tune the angle of the intelligent guide vane array; the complexity of the second type is higher than that of the first type.

[0062] Specifically, in combination Figure 2 and Figure 3This application features an intelligent airflow deflector array installed along the upper edge of each side window. Specifically, each side window is equipped with 8-12 ultra-thin airflow deflectors, which are integrally molded from composite materials and possess variable curvature characteristics to adapt to the optimal aerodynamic shape at different angles. Furthermore, the airflow deflectors are concealed within the sheet metal recesses along the upper edge of the window, retracting flush with the vehicle body without affecting appearance or wind resistance. When extended, they form an adjustable angle with the window glass, actively intervening in airflow. More specifically, this application also includes an intelligent laminar flow generation module, including a hybrid drive unit comprising a shape memory alloy component. This component undergoes a phase change at a specific temperature, resulting in deformation, which is linked to the external airflow temperature to achieve thermal deformation drive, enabling large-stroke, low-power basic angle adjustment. It also includes a micro stepper motor, which acts as a high-precision actuator, activating when needed to perform small-range, high-precision fine-tuning of the airflow deflector angle.

[0063] Specifically, the first type of operating condition in this application is low-speed or conventional operating conditions, such as low-speed cruising or medium-speed driving in mild weather. At this time, the airflow is relatively stable, and the requirements for the precision and response speed of the guide vane adjustment are not high. It is driven by the shape memory alloy component. More specifically, according to the target angle, a small control current is applied to the shape memory alloy component to raise its temperature, or in combination with the external temperature of the vehicle, the alloy deforms, causing the guide vane to unfold to the basic angle.

[0064] Specifically, the second type of working condition in this application is high-speed or complex working conditions, such as high-speed driving, entering a tunnel, strong crosswinds, etc. At this time, the airflow is turbulent and the impact force is large, which requires high precision in the angle adjustment of the guide vane, rigidity and dynamic response speed. After the shape memory alloy component completes the basic positioning, the micro stepper motor is started for precise fine adjustment.

[0065] Specifically, the acoustic processing in this application includes: decoupling the spectral density of the sound signals inside and outside the vehicle to separate the wind noise signal, the ambient sound signal and the in-vehicle sound signal, and generating a corresponding canceling sound wave based on the wind noise; and outputting an optimized sound signal after amplifying the ambient sound signal.

[0066] More specifically, in combination Figure 3 This application also includes a selective soundscape management module, comprising an acoustic sensing array including three external microphones respectively installed below the left and right rearview mirrors and in the center of the roof. The left and right microphones can form a beamforming array for spatially locating wind noise sources; the roof microphone is used to collect unobstructed overall ambient sound samples. It also includes an internal microphone installed inside the A-pillar for collecting the final sound mixture transmitted into the vehicle after preliminary physical noise reduction (i.e., active noise reduction by the air deflector), as well as internal human voices and music. This application can simultaneously collect external wind noise, ambient sound, internal residual wind noise, and human voices through the acoustic sensing array.

[0067] Specifically, the selective soundscape management module of this application also includes an AI acoustic processor, which incorporates a lightweight CNN neural network model. It uses beamforming technology to locate wind noise sources and then employs a spectrum decoupling algorithm to separate three main signals: wind noise (primarily low to mid-frequency, 100-500Hz), ambient sound (high-frequency or irregular frequency band, 500-5000Hz), and in-vehicle sound. The AI ​​acoustic processor generates inverse-phase sound waves only for the wind noise characteristic spectrum, performs lossless amplification of the ambient sound signal, and optimizes noise reduction for the in-vehicle sound signal, thus suppressing wind noise interference.

[0068] Specifically, the selective soundscape management module of this application also includes an acoustic output unit, which reuses the in-vehicle door speakers and roof surround speakers. The anti-phase sound waves (i.e., canceled sound waves) and the optimized sound signals are output synchronously after phase calibration to ensure a balance between wind noise cancellation effect and the naturalness of ambient sound.

[0069] Specifically, this application uses acoustic processing to accurately distinguish and process wind noise and ambient noise, achieving noise reduction without compromising the scenery.

[0070] Specifically, step S300 of this application further includes: real-time monitoring of whether multi-dimensional operating condition data has changed; if it has changed, steps S200 and S300 are re-executed within a preset delay time to update control parameters and execution actions. More specifically, this application monitors whether multi-dimensional operating condition data has changed in real time, especially vehicle speed, ambient wind speed and direction, window opening, and navigation information; if a change exceeding a preset threshold occurs, such as the vehicle speed increasing from 60km / h to 100km / h, it indicates that the current control parameters are no longer optimal and need to be updated. The central control unit of this application incorporates an adaptive PID + fuzzy control algorithm. Adaptive PID control can quickly calculate the correction amount based on the deviation between the target value and the current value, while fuzzy control can handle uncertainties and empirical problems and make intelligent decisions based on expert rules. When a change in operating conditions is confirmed, the central control unit immediately re-invokes the wind noise-operating condition prediction model, using the new multi-dimensional operating condition data as input. Within 0.3 seconds, it re-identifies the current driving condition, recalculates the optimal airflow control parameters and acoustic control parameters based on the new conditions, and sends instructions to other modules to ensure seamless coordination between airflow adjustment and acoustic control. This application achieves a control delay of ≤0.3 seconds, ensuring a continuous user experience.

[0071] Specifically, after step S300, the method of this application further includes: responding to the adjustment command input by the user, preferentially adjusting the airflow control parameters and / or acoustic control parameters according to the adjustment command, and storing the parameter preference corresponding to the adjustment command in the file associated with the user.

[0072] Specifically, this application also includes a personalized interaction module, comprising a central control screen for providing a visual operating interface, calibrating three preset modes, such as "Fresh Breeze Mode" (prioritizing noise reduction and gentle airflow), "Balanced Mode" (balancing wind feel and noise reduction), and "Strong Wind Mode" (increasing airflow intensity while retaining some natural wind dynamics), which users can switch with a single click according to their current preferences; it also supports voice control, recognizing natural language commands such as "reduce wind noise," "increase wind feel," and "turn off ambient sound"; and it can be linked to the seat memory function to automatically store the preference parameters of different users. When users manually adjust parameters via the central control screen or voice commands, the system prioritizes personalized settings and updates them to the user's preference profile.

[0073] In step S400, when the vehicle is detected to meet the maintenance conditions, the intelligent guide vane array is reset and a self-cleaning operation is performed on the intelligent guide vane array.

[0074] Specifically, the self-cleaning operation of the intelligent guide vane array in this application includes: after the intelligent guide vane array is reset, a micro high-pressure air pump is started, and a high-speed airflow is sprayed onto the surface of the intelligent guide vane array through the built-in air channel opened at the root of the intelligent guide vane array.

[0075] Specifically, the maintenance conditions for this application are when the window opening is less than 5cm, or when the user manually closes the system. This application also includes a self-cleaning unit, integrating a miniature high-pressure air pump and a built-in air duct, with the surface of the deflector plate covered with a superhydrophobic nano-coating. When the window is closed and the deflector plate retracts, the miniature high-pressure air pump automatically starts, spraying high-pressure airflow through the air duct to remove dust and rainwater residue from the surface and crevices of the deflector plate, achieving a cleaning efficiency of ≥95% and ensuring smooth, long-term use.

[0076] Specifically, after the intelligent air guide array is reset, all related electronic modules such as the central control unit, selective sound scene management module, and sensors are switched to a low-power sleep mode, retaining only the monitoring of wake-up conditions such as window opening.

[0077] Please see Figure 4 This is a framework diagram of the automotive window opening noise reduction control system 400 based on working condition adaptive design, as described in this application, including:

[0078] The acquisition module 410 is used to simultaneously acquire multi-dimensional operating condition data when the vehicle is detected to meet the active noise reduction conditions;

[0079] The calculation module 420 is used to determine the current driving conditions based on multi-dimensional operating condition data through a wind noise-operating condition prediction model, and to calculate airflow control parameters and acoustic control parameters.

[0080] The execution module 430 is used to drive the intelligent air guide array set on the upper edge of the window to move to the target angle according to the airflow control parameters in order to shape the airflow flowing into the vehicle; at the same time, according to the acoustic control parameters, it collects the sound signals inside and outside the vehicle, and outputs corresponding canceling sound waves and optimized sound signals after acoustic processing.

[0081] The maintenance module 440 is used to control the intelligent deflector array to reset and perform a self-cleaning operation on the intelligent deflector array when the vehicle is detected to meet the maintenance conditions.

[0082] It should be noted that the vehicle window noise reduction control system based on adaptive operating conditions provided in the above embodiments and the vehicle window noise reduction control method based on adaptive operating conditions provided in the above embodiments belong to the same concept. The specific operation methods of each module and unit have been described in detail in the method embodiments and will not be repeated here. In practical applications, the vehicle window noise reduction control system based on adaptive operating conditions provided in the above embodiments can be assigned to different functional modules as needed, that is, the internal structure of the system can be divided into different functional modules to complete all or part of the functions described above. This is not a limitation here.

[0083] Embodiments of this application also provide a computer device, including: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the computer device to implement the vehicle window opening noise reduction control method based on working condition adaptation provided in the above embodiments.

[0084] Figure 5 A schematic diagram of the structure of a computer system suitable for an embodiment of this application is shown. It should be noted that... Figure 5 The computer system 500 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0085] like Figure 5As shown, the computer system 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage section 508 into a random access memory (RAM) 503, such as performing the methods described in the above embodiments. Various programs and data required for system operation are also stored in the RAM 503. The CPU 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504. The following components are connected to the I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN (local area network) card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A driver 510 is also connected to the I / O interface 505 as needed. Removable media 511, such as disks, optical discs, magneto-optical discs, semiconductor memories, etc., are installed on drive 510 as needed so that computer programs read from them can be installed into storage section 508 as needed.

[0086] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer tool programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by central processing unit (CPU) 501, it performs various functions defined in the system of this application.

[0087] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, flash memory, an optical fiber, a portable compact disk read-only memory, an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. Computer programs contained on computer-readable media can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0088] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0089] The units described in the embodiments of this application can be implemented by tools or by hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the unit itself.

[0090] Another aspect of this application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a computer's processor, causes the computer to perform the aforementioned vehicle window opening noise reduction control method based on adaptive operating conditions. This computer-readable storage medium may be included in the computer device described in the above embodiments, or it may exist independently and not assembled into the computer device.

[0091] Another aspect of this application provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the vehicle window noise reduction control method based on operating condition adaptation provided in the various embodiments above.

[0092] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A vehicle window opening noise reduction control method based on adaptive operating conditions, characterized in that, Includes the following steps: Step S100: When the vehicle is detected to meet the active noise reduction conditions, multi-dimensional operating condition data is collected simultaneously. Step S200: Based on the multi-dimensional operating condition data, determine the current driving condition through the wind noise-operating condition prediction model, and calculate the airflow control parameters and acoustic control parameters. Step S300: According to the airflow control parameters, drive the intelligent air guide array set on the upper edge of the window to move to the target angle to shape the airflow flowing into the vehicle; at the same time, according to the acoustic control parameters, collect the sound signals inside and outside the vehicle, and output the corresponding canceling sound waves and optimized sound signals after acoustic processing. Step S400: When the vehicle is detected to meet the maintenance conditions, control the intelligent guide vane array to reset and perform a self-cleaning operation on the intelligent guide vane array.

2. The method according to claim 1, characterized in that, In step S100, the active noise reduction conditions include the window opening reaching a first preset threshold, or the vehicle being predicted to enter a preset special road section based on navigation information. The special road section includes tunnels, crosswind zones of elevated bridges, and highways.

3. The method according to claim 1, characterized in that, In step S300, driving the intelligent air deflector array located on the upper edge of the window to move to the target angle includes: When the current driving condition is the first type of condition, the intelligent guide vane array is driven to perform basic angle adjustment by utilizing the thermal deformation characteristics of the shape memory alloy component. When the current driving condition is the second type of condition, the micro stepper motor is started to finely adjust the angle of the intelligent guide vane array; The complexity of the second type of working condition is higher than that of the first type of working condition.

4. The method according to claim 3, characterized in that, In step S300, the acoustic processing includes: The sound signals inside and outside the vehicle are decoupled spectrally to separate wind noise, ambient sound, and in-vehicle sound. The corresponding canceling sound wave is generated based on the wind noise. The optimized sound signal is output after amplification of the ambient sound signal.

5. The method according to claim 1, characterized in that, Step S300 further includes: Real-time monitoring to check for changes in the multi-dimensional operating condition data; If changes occur, steps S200 and S300 will be re-executed within a preset delay time to update the control parameters and execute actions.

6. The method according to claim 1, characterized in that, In step S400, performing a self-cleaning operation on the intelligent flow guide array includes: After the intelligent guide vane array is reset, a miniature high-pressure air pump is started, and a high-speed airflow is injected onto the surface of the intelligent guide vane array through the built-in air channel opened at the root of the intelligent guide vane array.

7. The method according to claim 1, characterized in that, After step S300, the method further includes: In response to a user-inputted adjustment command, the airflow control parameters and / or the acoustic control parameters are adjusted according to the adjustment command, and the parameter preference corresponding to the adjustment command is stored in the user's associated file.

8. A vehicle window noise reduction control system based on adaptive operating conditions, characterized in that, include: The data acquisition module is used to simultaneously acquire multi-dimensional operating condition data when the vehicle is detected to meet the active noise reduction conditions; The calculation module is used to determine the current driving conditions based on the multi-dimensional operating condition data through the wind noise-operating condition prediction model, and to calculate the airflow control parameters and acoustic control parameters. The execution module is used to drive the intelligent air guide array set on the upper edge of the window to move to the target angle according to the airflow control parameters, so as to shape the airflow flowing into the vehicle; at the same time, according to the acoustic control parameters, it collects the sound signals inside and outside the vehicle, and outputs corresponding canceling sound waves and optimized sound signals after acoustic processing. The maintenance module is used to control the intelligent deflector array to reset and perform a self-cleaning operation on the intelligent deflector array when the vehicle is detected to meet the maintenance conditions.

9. A computer-readable storage medium, characterized in that, It stores computer-readable instructions, which, when executed by the computer's processor, cause the computer to perform the vehicle window opening noise reduction control method based on working condition adaptation as described in any one of claims 1 to 7.

10. A computer device, comprising: 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, it implements the steps of the vehicle window opening noise reduction control method based on working condition adaptation as described in any one of claims 1 to 7.

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