Vehicle noise reduction method, system and device and storage medium

Abstract

The invention discloses a vehicle noise reduction method, system and device and a storage medium, and relates to the technical field of noise reduction. The vehicle noise reduction method comprises the steps that under the condition that a current warning sound signal for pedestrians outside a vehicle is output through a first loudspeaker, a reference signal is determined according to the current warning sound signal for the pedestrians outside the vehicle and a preset filtering algorithm; extracting a corresponding error signal through each microphone; determining an offset signal of each second loudspeaker according to the reference signal, each error signal and a preset narrowband adaptive filter algorithm; wherein the offset signal is used for carrying out noise reduction on the corresponding target area. According to the vehicle noise reduction method provided by the invention, the plurality of loudspeakers and microphones are arranged in the target areas needing noise reduction in the vehicle, and the offset signals of the target areas are accurately output by using the multi-channel narrow-band adaptive filter algorithm; therefore, accurate noise reduction of each target area in the vehicle is realized when the vehicle gives out the warning sound for pedestrians outside the vehicle.

Description

Technical Field

[0001] The present application relates to the field of noise reduction technology, and in particular to a vehicle noise reduction method, system, device and storage medium. Background Art

[0002] Electric and hybrid vehicles are typically quiet at low speeds, relying on an acoustic vehicle alerting system (AVAS) to alert pedestrians. However, the warning sounds transmitted into the cabin can be distracting to the driver. Therefore, noise reduction measures are necessary to mitigate these in-cabin noises. Summary of the Invention

[0003] Purpose of the invention: The embodiments of the present application provide a vehicle noise reduction method, system, device and storage medium to achieve noise reduction inside the vehicle for pedestrian warning sounds outside the vehicle.

[0004] Technical Solution: A vehicle noise reduction method according to an embodiment of the present application is used to achieve in-vehicle noise reduction based on a pedestrian warning sound outside the vehicle. The vehicle is provided with a first speaker outside the vehicle; the vehicle interior includes multiple target areas; at least two microphones and a second speaker are provided around each target area; the method comprises:

[0005] When a current pedestrian warning sound signal is output through the first speaker, determining a reference signal according to the current pedestrian warning sound signal and a preset filtering algorithm;

[0006] extracting corresponding error signals through each of the microphones;

[0007] A cancellation signal of each second loudspeaker is determined according to the reference signal, each error signal, and a preset multi-channel narrowband adaptive filter algorithm; wherein the cancellation signal is used to reduce noise in the corresponding target area.

[0008] In some embodiments, each second speaker corresponds to a first filter; the first filter is a narrowband adaptive filter; and determining the cancellation signal of each second speaker based on the reference signal, each error signal, and a preset multi-channel narrowband adaptive filter algorithm includes:

[0009] determining a secondary estimated path from each of the microphones to the second loudspeaker in the target area;

[0010] determining a currently updated filter coefficient of the first filter according to each of the secondary estimation paths, the reference signal, the error signal, and a filter coefficient of the first filter corresponding to the second speaker at a previous moment;

[0011] A cancellation signal of the second speaker corresponding to the first filter is determined according to the currently updated filter coefficient corresponding to the first filter and the reference signal.

[0012] In some embodiments, determining the current updated filter coefficient of the first filter based on each of the secondary estimation paths, the reference signal, the error signal, and the filter coefficient of the first filter corresponding to the second speaker at a previous moment includes:

[0013] determining a first convolution result of each of the secondary estimation paths and the reference signal;

[0014] determining a second convolution result of each first convolution result and the error signal corresponding to the microphone;

[0015] The currently updated filter coefficient of the first filter is determined according to the sum of the filter coefficient of the first filter at the previous moment and each of the second convolution results.

[0016] In some embodiments, determining a secondary estimated path from each of the microphones to the second speaker in the target area comprises:

[0017] outputting a linear frequency modulation signal through the second speaker in the target area;

[0018] Each of the secondary estimation paths is determined according to the linear frequency modulation signal, a signal received by each of the microphones based on the linear frequency modulation signal, and a preset least mean square filtering algorithm.

[0019] In some embodiments, determining the cancellation signal of the second speaker corresponding to the first filter according to the currently updated filter coefficient corresponding to the first filter and the reference signal includes:

[0020] A cancellation signal of the second speaker corresponding to the first filter is determined according to a third convolution of the current updated filter coefficient corresponding to the first filter and the reference signal.

[0021] In some embodiments, determining a reference signal based on the current external pedestrian warning sound signal and a preset filtering algorithm includes:

[0022] Filtering the current pedestrian warning sound signal outside the vehicle through a second filter in descending order of energy to remove a preset number of narrowband signals; wherein the second filter is a bandpass filter;

[0023] The preset number of narrowband signals are combined into the reference signal.

[0024] In some embodiments, the method for determining the current external pedestrian warning sound signal includes:

[0025] Get the current vehicle speed;

[0026] The current external pedestrian warning sound signal is determined according to the current vehicle speed and a preset warning sound original sound source.

[0027] Accordingly, an embodiment of the present application further provides a vehicle noise reduction system for achieving noise reduction inside a vehicle based on a pedestrian warning sound outside the vehicle, wherein a first speaker is provided outside the vehicle; the vehicle interior includes multiple target areas; at least two microphones and a second speaker are provided around each of the target areas; the system comprises:

[0028] a first determining module, configured to determine a reference signal according to the current external pedestrian warning sound signal and a preset filtering algorithm when the current external pedestrian warning sound signal is outputted through the first speaker;

[0029] an extraction module, configured to extract corresponding error signals through each of the microphones;

[0030] The second determination module is configured to determine a cancellation signal for each of the second speakers based on the reference signal, each of the error signals, and a preset narrowband adaptive filter algorithm; wherein the cancellation signal is used to perform noise reduction on the corresponding target area.

[0031] Correspondingly, an embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the vehicle noise reduction method as described above when executing the computer program.

[0032] Accordingly, an embodiment of the present application further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the vehicle noise reduction method as described above is implemented.

[0033] Beneficial effects: Compared with the prior art, the vehicle noise reduction method, system, device and storage medium of the embodiments of the present application include: when the current pedestrian warning sound signal outside the vehicle is output through the first speaker, determining a reference signal based on the current pedestrian warning sound signal outside the vehicle and a preset filtering algorithm; extracting corresponding error signals through each microphone; determining the cancellation signal of each second speaker based on the reference signal, each error signal and a preset narrowband adaptive filter algorithm; wherein the cancellation signal is used to reduce noise in the corresponding target area. The vehicle noise reduction method provided by the present application achieves precise noise reduction in each target area inside the vehicle when the vehicle emits a pedestrian warning sound outside the vehicle by setting multiple speakers and microphones in the target area where noise reduction is required inside the vehicle, and using a multi-channel narrowband adaptive filter algorithm to accurately output the cancellation signal of each target area. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0035] Figure 1 is a flow chart of a vehicle noise reduction method provided in an embodiment of the present application;

[0036] Figure 2 This is a schematic diagram of the overall framework of active noise reduction for an external pedestrian warning sound inside a vehicle based on a multi-channel narrowband adaptive filtering algorithm provided in an embodiment of the present application;

[0037] Figure 3 This is a schematic diagram of signal transmission in a vehicle cabin provided in an embodiment of the present application;

[0038] Figure 4 1 is a schematic diagram of an AVAS noise active control algorithm framework based on multi-channel FXLMS provided in an embodiment of the present application;

[0039] Figure 5 This is a principle structural block diagram of a vehicle noise reduction system provided in an embodiment of the present application;

[0040] Figure 6 It is a structural diagram of an electronic device adopted in an embodiment of the present application.

[0041] Reference numerals:

[0042] 101 - first determination module; 102 - extraction module; 103 - second determination module; 100 - vehicle noise reduction system. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0044] It should be understood that although the terms first, second, etc. may be used herein to describe various components, these components should not be limited by these terms. These terms are used to distinguish one component from another. Thus, the first component discussed below could be referred to as the second component without departing from the teachings of the present invention. As used herein, the term "and / or" includes any one and all combinations of one or more of the associated listed items.

[0045] Those skilled in the art will appreciate that the drawings are merely schematic diagrams of exemplary embodiments and may not be to scale. The modules or processes in the drawings are not necessarily required to implement the present application and therefore cannot be used to limit the scope of protection of the present application.

[0046] The applicant's research has found that the power system of electric vehicles produces almost no mechanical noise like traditional internal combustion engines during operation, resulting in a quiet appearance at low speeds. This makes it difficult for pedestrians to judge the vehicle's approach by hearing. AVAS alerts pedestrians by emitting a warning sound at a certain sound pressure level when driving and reversing, thereby alleviating pedestrian safety risks. However, in reality, there is a contradiction between in-car acoustic comfort and external safety warnings. During low-speed driving, the warning sound can be transmitted into the car, causing distress to the driver or passengers, such as distracting the driver's attention and affecting navigation clarity.

[0047] Narrowband Active Noise Control (NANC) is a technology that actively controls noise at specific frequencies. It generates a counter-noise wave with equal amplitude and opposite phase to the target noise, creating destructive interference with the original noise and canceling out the acoustic energy. However, current applications of NANC technology are primarily focused on controlling motor and engine noise, neglecting the potential disruption to the driver caused by pedestrian warning sounds intruding into the vehicle.

[0048] In view of this, the embodiments of the present application provide a vehicle noise reduction method, system, device and storage medium. The present application sets multiple speakers and microphones in the target areas in the vehicle where noise reduction is required, and uses a multi-channel narrowband adaptive filter algorithm to accurately output the cancellation signals of each target area, thereby achieving precise noise reduction in each target area in the vehicle when the vehicle emits a pedestrian warning sound outside the vehicle.

[0049] It should be noted that the vehicles in the embodiments of the present application include electric vehicles, hybrid vehicles, etc., which can be specifically configured according to actual conditions and are not specifically limited here.

[0050] Figure 1 This is a flow chart of a vehicle noise reduction method provided in an embodiment of the present application. This method can be applied to a vehicle control system to implement a process of reducing vehicle interior noise based on pedestrian warning sounds in low-speed driving scenarios. This method can be executed by a vehicle noise reduction system, which can be implemented in software and / or hardware and can be configured in a processor or controller of a vehicle control system. Figure 1 , the method comprises the following steps:

[0051] Step 110 : When the first speaker outputs a current external pedestrian warning sound signal, determine a reference signal according to the current external pedestrian warning sound signal and a preset filtering algorithm.

[0052] Specifically, a current external pedestrian warning sound signal is determined, and the current external pedestrian warning sound signal is output through the first speaker.

[0053] Among them, the external pedestrian warning sound (hereinafter referred to as AVAS signal X) is a warning sound emitted by an external horn (or external speaker) when the vehicle is traveling at a low speed to remind pedestrians that a vehicle is approaching.

[0054] Among them, the first speaker is set outside the car and is used to emit a pedestrian warning sound signal outside the car to remind pedestrians.

[0055] In some embodiments, the method for determining a current external pedestrian warning sound signal includes: obtaining a current vehicle speed; and determining the current external pedestrian warning sound signal according to the current vehicle speed and a preset warning sound original sound source.

[0056] The preset original sound source of the warning sound is the original sound source of the AVAS signal.

[0057] There is a linear relationship between the current vehicle speed and the original sound source of the AVAS signal. Based on the known current vehicle speed and the original sound source of the AVAS signal, the current AVAS signal X can be obtained. For example, assuming the current vehicle speed is a, and the original sound source of the AVAS signal contains frequencies f1, f2, f3, and f4, the frequency components of the current AVAS signal X obtained at the current vehicle speed are (a×k×f1, a×k×f2, a×k×f3, a×k×f4), where k is a fixed parameter. The specific value can be set according to actual conditions and is not specifically limited here.

[0058] The current AVAS signal X is composed of multiple narrowband signals. Specifically, a preset filtering algorithm is used to filter the current AVAS signal X to filter several narrowband signals with larger energy to form the reference signal x.

[0059] In some embodiments, determining a reference signal based on a current external pedestrian warning sound signal and a preset filtering algorithm includes filtering the current external pedestrian warning sound signal through a second filter in descending order of energy to remove a predetermined number of narrowband signals. The second filter is a bandpass filter. Combining the predetermined number of narrowband signals into the reference signal.

[0060] The preset number may be 3, 4, 5, etc., and may be set according to actual conditions, and no specific limitation is given here.

[0061] Among them, the original sound source of the AVAS signal is preset, so the frequency bands with larger energy are obtained. For example, the frequency bands with the largest energy are 110Hz, 230Hz, and 350Hz. Specifically, the specific implementation process of filtering out the preset number of narrowband signals of the current pedestrian warning sound signal outside the vehicle through the second filter in the order of energy from large to small is as follows: the original sound source of the AVAS signal will be frequency modulated according to the current vehicle speed. Assuming that the signals of the above three frequency bands are modulated to 130Hz, 250Hz, and 370Hz, then use three bandpass filters (with center frequencies of 130Hz, 250Hz, and 370Hz respectively) to filter the modulated signals respectively, and the three narrowband signals can be obtained.

[0062] Step 120: extract corresponding error signals through each microphone.

[0063] The vehicle interior (the cabin) is also equipped with multiple secondary speakers, multiple microphones, and multiple target areas. The target areas include the driver's seat and passenger seats, among others. Each target area is surrounded by at least two microphones and at least two secondary speakers. For example, if the target area is the driver's seat, a microphone and a secondary speaker are placed on the left and right sides of the driver's headrest (near the driver's ears).

[0064] Assume that there are n microphones in the car, and each microphone in the car is used to extract the multi-channel noise signal or error signal (including the warning sound outside the car, wind noise, etc.) of the corresponding area. d includes [d1…d n ]. Wherein, n is a positive integer.

[0065] Step 130 : Determine the cancellation signal of each second loudspeaker according to the reference signal, each error signal, and a preset multi-channel narrowband adaptive filter algorithm.

[0066] The cancellation signal is used to reduce noise in the corresponding target area. The second speaker is a cancellation speaker.

[0067] Figure 2 This is a schematic diagram of the overall framework of an active noise reduction system for pedestrian warning sounds outside the vehicle based on a multi-channel narrowband adaptive filtering algorithm provided in an embodiment of the present application. Figure 2 First, the current AVAS signal X at the current vehicle speed is obtained based on the known current vehicle speed information and the original sound source of the AVAS signal. Among them, the current AVAS signal X is played by the first speaker, propagated through the air and picked up by the microphone inside the car. Then, since the current AVAS signal X is composed of multiple narrowband signals, a bandpass filter is used to obtain several narrowband signals with larger energy and combine them into a new reference signal x. Finally, the obtained reference signal x and the multi-channel noise signal d collected by the microphone inside the car at this time, including the warning sound outside the car, wind noise, etc., are input into the multi-channel narrowband adaptive filter algorithm. Assume that there are n microphones, and the multi-channel signal d is [d1…d n The cancellation signal y obtained by the multi-channel narrowband adaptive filter algorithm is emitted by multiple second speakers in the car. Assume that there are m cancellation speakers. The cancellation signal y is [y1…y m ]. This allows for multi-channel active noise reduction of pedestrian warning sounds in various target areas of the vehicle in low-speed driving scenarios by using multiple microphones, multiple speakers, and a multi-channel narrowband adaptive filtering algorithm. This achieves quietness in specific areas and improves in-vehicle acoustic comfort while ensuring that pedestrian warning sounds comply with regulations.

[0068] Figure 3 This is a schematic diagram of signal transmission in a vehicle cabin provided in an embodiment of the present application. Figure 3 , multiple microphones and multiple second speakers are set in the vehicle cabin. The current AVAS signal X is played by the first speaker, propagated through the air and picked up by multiple microphones in the vehicle to generate a multi-channel signal d = [d1…d n Then, the current AVAS signal X is composed of multiple narrowband signals. The bandpass filter is used to obtain several narrowband signals with larger energy and combine them into a reference signal x. The reference signal x and the multi-channel signal d = [d1…d n ] obtain multiple cancellation signals y=[y1…y m]. Thus, at least two microphones and at least two second speakers are arranged around the target area. For example, a microphone and a second speaker are respectively arranged on the left and right sides of the headrest of the driver's seat (close to the driver's ears), and the noise signal in the cabin is collected synchronously through two channels, so as to more accurately simulate the noise characteristics of the target area (for example, the noise characteristics at the driver's or passenger's ears). At the same time, using two or more speakers to transmit the cancellation signal can ensure that both ears can obtain a balanced noise reduction effect.

[0069] It should be noted that the embodiments of the present application can also achieve single-channel active noise reduction, for example, only one microphone and one second speaker are configured in the target area. However, a single microphone can only collect noise signals at a certain point in space. When the noise levels on both sides of the head are inconsistent, the collection results cannot accurately reflect the noise distribution actually perceived by the human ear. In addition, sound waves will attenuate during propagation, resulting in a limited effective range of active noise reduction. If both ears are not in the optimal noise reduction range at the same time, the noise reduction intensity on both sides will also be inconsistent, and it may be possible that one side will reduce the noise while the other side will be enhanced. Therefore, the above-mentioned multi-channel active noise reduction method provided in the embodiments of the present application can more accurately simulate the noise characteristics at the driver's or passenger's ears, and achieve active and precise noise reduction of pedestrian warning sounds in the cabin through a multi-channel narrowband adaptive filtering algorithm and in-car speakers, thereby improving in-car acoustic comfort and driver attention without affecting the in-car warning function.

[0070] In some embodiments, each second speaker corresponds to a first filter; the first filter is a narrowband adaptive filter; and determining the cancellation signal of each second speaker based on the reference signal, each error signal, and a preset multi-channel narrowband adaptive filter algorithm specifically includes the following steps:

[0071] Step 1: Determine a secondary estimated path from each microphone to the second loudspeaker in the target area.

[0072] Active Noise Control (ANC) is a technology that cancels out noise by generating sound waves with opposite phases to the original noise. When two sound waves with the same frequency and amplitude but opposite phases are superimposed, they cancel each other out, reducing noise energy in a specific area. Currently, it's widely used in the automotive field to address engine noise, tire noise, and wind noise, improving cabin quietness.

[0073] Narrowband adaptive filter is an adaptive filtering system designed specifically for narrowband signals. It can effectively extract or suppress signal components within a specific frequency range by dynamically adjusting filter parameters.

[0074] The AVAS signal modifies the original audio at different vehicle speeds, with the pitch increasing with increasing speed. The original audio consists of multiple narrowband components, so a narrowband adaptive filter can be used to achieve active noise control for the AVAS signal.

[0075] For example, in the technical solution of the embodiment of the present application, the core algorithm of the narrowband adaptive filter selects the Filtered-X Least Mean Square (FXLMS) algorithm, which is an extended version of the Least Mean Square (LMS) algorithm and is widely used in noise control, signal enhancement and other fields.

[0076] Figure 4 This is a schematic diagram of the framework of an AVAS noise active control algorithm based on multi-channel FXLMS provided in the embodiment of this application. For example, please refer to Figure 4 The AVAS noise active control algorithm of the multi-channel FXLMS includes the primary path P, the secondary path S and the secondary estimation path In the multi-channel FXLMS algorithm, the secondary path S is a core concept. It represents the transmission path from the secondary sound source (for example, the speaker in the car that sends the algorithm output signal, that is, the second speaker) to the microphone in the car. It reflects the overall transmission process of the reverse sound wave after propagation through the air and attenuation and then being detected by the microphone in the car. In order to compensate for the influence of the secondary path, the FXLMS algorithm proposes to use the secondary estimated path The reference signal is filtered and then combined with the error signal d picked up by the error microphone to update the filter coefficient w of the adaptive filter.

[0077] In some embodiments, determining a secondary estimated path from each microphone to a second speaker in a target area includes: outputting a linear frequency modulation signal through the second speaker in the target area; and determining each secondary estimated path based on the linear frequency modulation signal, a signal received by each microphone based on the linear frequency modulation signal, and a preset minimum mean square filtering algorithm.

[0078] Assume that there are m cancellation speakers (i.e., second speakers) and n microphones in the current system. There are m×n secondary paths from the m cancellation speakers to the n microphones. The matrix S of the secondary paths is:

[0079]

[0080] Among them, the matrix of the secondary estimation path for:

[0081]

[0082] Among them, s nmrepresents the secondary path from the nth microphone to the mth second loudspeaker; represents the secondary estimated path from the nth microphone to the mth second loudspeaker.

[0083] Exemplarily, the secondary path of the embodiment of the present application adopts offline modeling to reduce the computing power of multi-channel active noise reduction, thereby improving the speed, accuracy and reliability of multi-channel active noise reduction. Specifically, the secondary path from each microphone to each second speaker in the vehicle cabin is measured. Assume that the second speaker in the vehicle cabin sends a specific signal (such as a linear frequency modulation signal) p, and the nth microphone receives the signal q. The secondary estimated path is obtained using the least mean square filtering algorithm. in,

[0084] Step 2: Determine the current updated filter coefficient of the first filter according to each secondary estimation path, the reference signal, the error signal, and the filter coefficient of the first filter corresponding to the second speaker at the previous moment.

[0085] The first filter is a narrowband adaptive filter.

[0086] The cancellation signal of each second loudspeaker is generated by a narrowband adaptive filter algorithm, and the number of the second loudspeakers is the same as the number of the first filters.

[0087] In some embodiments, the currently updated filter coefficient of the first filter is determined based on each secondary estimation path, the reference signal, the error signal, and the filter coefficient of the first filter corresponding to the second speaker at the previous moment, including: determining the first convolution result of each secondary estimation path and the reference signal; determining the second convolution result of each first convolution result and the error signal of the corresponding microphone; and determining the currently updated filter coefficient of the first filter based on the filter coefficient of the first filter at the previous moment and the sum of each second convolution result.

[0088] Among them, the narrowband adaptive filter simultaneously reduces the noise of multiple narrowband components in the microphone's error signal (wherein each narrowband component has its own narrowband adaptive filter, which can be used to achieve simultaneous noise reduction of multiple narrowband components, improving the noise reduction effect and reliability), which can effectively control the AVAS noise in the car. Since the noise reduction area is limited, the closer the microphone is to the target area (for example, the closer to the ears of the main driver's seat), the better the noise reduction effect. The AVAS signal frequency is relatively high (usually in the 200Hz-500Hz frequency band), so the microphone can be preferentially placed on the headrest of the seat in the target area. If the microphone is far away from the human ear, the noise reduction effect may drop sharply.

[0089] The original audio of the AVAS signal is composed of t narrowband signals. Different vehicle speeds will generate different AVAS signals X. The corresponding t frequency magnitudes after pitch shifting can be obtained based on the algorithm that generates the AVAS signal. The k largest frequency components are selected based on their energy magnitude and these k components are filtered out using a bandpass filter as the reference signal x = [x1, x2…x k ]. Among them, x k represents the reference signal corresponding to the kth frequency component, where k is less than or equal to t.

[0090] Among them, the specific implementation process of the t frequencies corresponding to the modulation can be obtained according to the algorithm for generating the AVAS signal: for example, assuming that the original sound source signal of the pedestrian warning sound outside the vehicle is x0, the AVAS signal under different vehicle speeds v is X=f(v, x0). Different vehicle speeds will modulate the frequency of x0. Exemplarily, the frequency modulation algorithm is linear frequency modulation. The process of linear frequency modulation of x0 at different vehicle speeds is: the coefficient k0*vehicle speed v*each frequency component of the sound source signal x0 is equal to the frequency after frequency modulation. For example, assuming that the strongest energy in the original signal is f1, f2, f3, the frequency after frequency modulation is k0*v*f1, k0*v*f2, k0*v*f3. Among them, the specific value of the coefficient k0 can be set according to the actual situation, and no specific limitation is made here.

[0091] Since the current environment is a vehicle cabin, in order to use a smaller calculation example to ensure real-time performance, the error signals obtained by different microphones are jointly processed to update the same adaptive filter. The update formula for the filter coefficient corresponding to the mth adaptive filter is:

[0092]

[0093] Among them, w m w′ represents the filter coefficient of the first filter corresponding to the second loudspeaker in the target area at the previous moment; m represents the current updated filter coefficient of the first filter corresponding to the second loudspeaker in the target area at the current moment; μ represents the step size, which is used to control the convergence speed of the FXLMS algorithm; x′ im represents the first convolution of the secondary estimation path from the i-th microphone to the m-th second filter with the reference signal; d i represents the error signal of the i-th microphone input.

[0094] Step three: determining a cancellation signal of the second speaker corresponding to the first filter according to the currently updated filter coefficient corresponding to the first filter and the reference signal.

[0095] In some embodiments, determining the cancellation signal of the second speaker corresponding to the first filter based on the currently updated filter coefficient corresponding to the first filter and the reference signal includes: determining the cancellation signal of the second speaker corresponding to the first filter based on the third convolution of the currently updated filter coefficient corresponding to the first filter and the reference signal.

[0096] Among them, the reference signal can be used to obtain the cancellation signal after passing through the adaptive filter. The specific calculation formula is as follows:

[0097] y m =x*w′ m ;

[0098] Among them, y m represents the cancellation signal of the mth second loudspeaker.

[0099] It can be understood that the vehicle noise reduction method provided by the present application sets multiple speakers and microphones in the target areas in the vehicle where noise reduction is required, and uses a multi-channel narrowband adaptive filter algorithm to accurately output the cancellation signals of each target area, thereby achieving precise noise reduction in each target area in the vehicle when the vehicle emits a pedestrian warning sound outside the vehicle.

[0100] As a specific implementation method, based on the above multi-channel narrowband adaptive filter algorithm, the specific process of active noise reduction inside the vehicle for the external pedestrian warning sound is as follows:

[0101] First, the secondary path from the canceling speaker (i.e., the second speaker) to the microphone in the vehicle cabin is measured. The second speaker in the cabin sends a specific signal (such as a linear frequency modulation signal) p, and the nth microphone receives the signal q. The secondary estimated path is obtained by using the least mean square filter.

[0102] Then, an AVAS signal X is obtained based on the vehicle speed information and simultaneously transmitted to an external speaker (i.e., the first speaker) and a bandpass filter. The bandpass filter filters out k narrowband signals with larger energy and combines them into a reference signal x for subsequent narrowband noise reduction.

[0103] Secondly, the reference signal x and the error signal d extracted by the microphone are input into a multi-channel narrowband adaptive filter to obtain the filtering result, i.e., the cancellation signal y, and update the filter coefficient w of the filter.

[0104] Finally, the resulting cancellation signal y is output to the second speaker in the car for playback. Repeating the above steps can achieve active noise reduction of the AVAS signal in a specific target area.

[0105] In summary, the vehicle noise reduction method provided by the embodiment of the present application can achieve the following: in the low-speed driving scenario of electric vehicles and hybrid electric vehicles, for the noise of pedestrian warning sounds outside the vehicle transmitted into the cabin during the low-speed driving of electric vehicles and hybrid electric vehicles, the noise energy of the target area position is actively controlled through a multi-channel narrowband adaptive filtering algorithm, so as to achieve active noise reduction of pedestrian warning sounds in the corresponding target area. During the low-speed driving of the vehicle, the noise signal (i.e., error signal) of the current target area is monitored and obtained in real time in combination with the microphone in the vehicle cabin, the reverse signal (i.e., cancellation signal) of the noise in the target area is generated in combination with the AVAS reference signal and the multi-channel narrowband adaptive filtering algorithm, and the cancellation signal is played by the in-vehicle speaker to achieve active noise reduction in the target area. The present application can improve the quietness and comfort inside the vehicle without affecting the warning function outside the vehicle and ensuring that the sound pressure level outside the vehicle meets the regulations.

[0106] Figure 5 This is a principle structure diagram of a vehicle noise reduction system provided in the embodiment of the present application. Correspondingly, the embodiment of the present application also provides a vehicle noise reduction system, please refer to Figure 5 The vehicle noise reduction system 100 includes: a first determination module 101, configured to determine a reference signal based on the current pedestrian warning sound signal and a preset filtering algorithm when the current pedestrian warning sound signal is output through the first speaker; an extraction module 102, configured to extract corresponding error signals through each microphone; and a second determination module 103, configured to determine a cancellation signal for each second speaker based on the reference signal, each error signal, and a preset narrowband adaptive filter algorithm; wherein the cancellation signal is used to reduce noise in the corresponding target area.

[0107] The technical solution of the embodiment of the present application provides a vehicle noise reduction system, which achieves precise noise reduction in each target area inside the vehicle by setting multiple speakers and microphones in the target areas where noise reduction is required in the vehicle, and using a multi-channel narrowband adaptive filter algorithm to accurately output the cancellation signal of each target area, thereby achieving precise noise reduction in each target area inside the vehicle when the vehicle emits a pedestrian warning sound outside the vehicle.

[0108] In some embodiments, each second speaker corresponds to a first filter; the first filter is a narrowband adaptive filter; the second determination module 103 is also used to: determine the secondary estimation path from each microphone to the second speaker in the target area; determine the current updated filter coefficient of the first filter based on each secondary estimation path, the reference signal, the error signal, and the filter coefficient of the first filter corresponding to the second speaker at the previous moment; determine the cancellation signal of the second speaker corresponding to the first filter based on the current updated filter coefficient corresponding to the first filter and the reference signal.

[0109] In some embodiments, the second determination module 103 is also used to: determine the first convolution result of each secondary estimation path and the reference signal; determine the second convolution result of each first convolution result and the error signal of the corresponding microphone; determine the current updated filter coefficient of the first filter based on the filter coefficient of the first filter at the previous moment and the sum of each second convolution result.

[0110] In some embodiments, the second determination module 103 is further used to: output a linear frequency modulation signal through a second speaker in the target area; and determine each secondary estimation path according to the linear frequency modulation signal, the signal received by each microphone based on the linear frequency modulation signal, and a preset minimum mean square filtering algorithm.

[0111] In some embodiments, the second determination module 103 is further configured to determine a cancellation signal of the second speaker corresponding to the first filter according to a third convolution of a current updated filter coefficient corresponding to the first filter and the reference signal.

[0112] In some embodiments, the first determination module 101 is further used to: filter out a preset number of narrowband signals from the current external pedestrian warning sound signal through a second filter in descending order of energy; wherein the second filter is a bandpass filter; and combine the preset number of narrowband signals into a reference signal.

[0113] In some embodiments, the first determining module 101 is further configured to: obtain a current vehicle speed; and determine a current external pedestrian warning sound signal according to the current vehicle speed and a preset original sound source of the warning sound.

[0114] Figure 6 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. Figure 6 The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the vehicle noise reduction method described above are implemented. Since the vehicle noise reduction method has been described in detail above, it will not be repeated here.

[0115] Accordingly, an embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-mentioned vehicle noise reduction method. Since the vehicle noise reduction method has been described in detail above, it will not be repeated here.

[0116] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0117] The above is a detailed introduction to the vehicle noise reduction method, system, device and storage medium provided in the embodiments of the present application, and specific examples are used to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the technical solutions and core ideas of the present application; ordinary technicians in this field should understand that they can still modify the technical solutions recorded in the aforementioned embodiments, or replace some of the technical features therein with equivalents; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A vehicle noise reduction method, characterized in that: Used to achieve noise reduction in the vehicle based on the pedestrian warning sound outside the vehicle, the first speaker is provided outside the vehicle; The vehicle includes multiple target areas; At least two microphones and a second speaker are arranged around each target area; the method comprises: When a current pedestrian warning sound signal is output through the first speaker, determining a reference signal according to the current pedestrian warning sound signal and a preset filtering algorithm; extracting corresponding error signals through each of the microphones; A cancellation signal of each second loudspeaker is determined according to the reference signal, each error signal, and a preset multi-channel narrowband adaptive filter algorithm; wherein the cancellation signal is used to reduce noise in the corresponding target area.

2. The vehicle noise reduction method according to claim 1, characterized in that: Each of the second speakers corresponds to a first filter; the first filter is a narrowband adaptive filter; The determining of the cancellation signal of each second loudspeaker according to the reference signal, each error signal, and a preset multi-channel narrowband adaptive filter algorithm includes: determining a secondary estimated path from each of the microphones to the second loudspeaker in the target area; determining a currently updated filter coefficient of the first filter according to each of the secondary estimation paths, the reference signal, the error signal, and a filter coefficient of the first filter corresponding to the second speaker at a previous moment; A cancellation signal of the second speaker corresponding to the first filter is determined according to the currently updated filter coefficient corresponding to the first filter and the reference signal.

3. The vehicle noise reduction method according to claim 2, characterized in that: The determining, based on each of the secondary estimation paths, the reference signal, the error signal, and the filter coefficient of the first filter corresponding to the second speaker at a previous moment, a current updated filter coefficient of the first filter includes: determining a first convolution result of each of the secondary estimation paths and the reference signal; determining a second convolution result of each first convolution result and the error signal corresponding to the microphone; The currently updated filter coefficient of the first filter is determined according to the sum of the filter coefficient of the first filter at the previous moment and each of the second convolution results.

4. The vehicle noise reduction method according to claim 2, characterized in that: The determining a secondary estimated path from each of the microphones to the second loudspeaker in the target area comprises: outputting a linear frequency modulation signal through the second speaker in the target area; Each of the secondary estimation paths is determined according to the linear frequency modulation signal, a signal received by each of the microphones based on the linear frequency modulation signal, and a preset least mean square filtering algorithm.

5. The vehicle noise reduction method according to claim 2, characterized in that: The determining, according to the currently updated filter coefficient corresponding to the first filter and the reference signal, a cancellation signal of the second speaker corresponding to the first filter includes: A cancellation signal of the second speaker corresponding to the first filter is determined according to a third convolution of the current updated filter coefficient corresponding to the first filter and the reference signal.

6. The vehicle noise reduction method according to claim 1, characterized in that: The determining of the reference signal according to the current external pedestrian warning sound signal and a preset filtering algorithm includes: Filtering the current pedestrian warning sound signal outside the vehicle through a second filter in descending order of energy to remove a preset number of narrowband signals; wherein the second filter is a bandpass filter; The preset number of narrowband signals are combined into the reference signal.

7. The vehicle noise reduction method according to claim 1, characterized in that: The method for determining the current external pedestrian warning sound signal includes: Get the current vehicle speed; The current external pedestrian warning sound signal is determined according to the current vehicle speed and a preset warning sound original sound source.

8. A vehicle noise reduction system, characterized in that: Used to achieve noise reduction in a vehicle based on a pedestrian warning sound outside the vehicle, the vehicle is provided with a first speaker outside the vehicle; the vehicle interior includes multiple target areas; At least two microphones and a second speaker are arranged around each target area; the system comprises: a first determining module, configured to determine a reference signal according to the current external pedestrian warning sound signal and a preset filtering algorithm when the current external pedestrian warning sound signal is outputted through the first speaker; an extraction module, configured to extract corresponding error signals through each of the microphones; The second determination module is configured to determine a cancellation signal for each of the second speakers based on the reference signal, each of the error signals, and a preset narrowband adaptive filter algorithm; wherein the cancellation signal is used to perform noise reduction on the corresponding target area.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the vehicle noise reduction method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the vehicle noise reduction method according to any one of claims 1 to 7 is implemented.

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