Vehicle noise reduction method, device and storage medium for broadband noise

Abstract

The present invention discloses a vehicle noise reduction method and device, and a storage medium for broadband noise. The vehicle road noise control method: collects a reference signal of vehicle road noise at each sampling moment, collects a residual noise signal at each sampling moment of the area to be noise-reduced and records it as an error signal, and if the data of the reference signal and the error signal are accumulated to N respectively, then executes a frequency domain calculation step, and updates the filter parameters obtained in the frequency domain to the time domain; wherein the coupling effect between channels is taken into account, and for each frequency point, the filter reference signal is constructed as the following two-dimensional matrix U(k), and a gradient vector in the frequency domain is generated; according to the gradient vector Ψ in the frequency domain j，l Generate the gradient vector in the time domain and update the filter control parameter W in the frequency domain j，l，new The present invention can actively reduce road noise caused by the friction between vehicle tires and the road surface, has a faster convergence speed, requires fewer computing resources, is more accurate in calculation, and has a better noise reduction effect.

Description

Technical Field

[0001] The present invention belongs to the field of vehicle noise control, and relates to the field of vehicle active noise reduction, and specifically provides a vehicle noise reduction method and device, and a storage medium for broadband noise. Background Art

[0002] With the development of modern industry, noise pollution has attracted more and more attention, and high-intensity noise signals have also affected the comfort of listeners. Due to the effect of sound masking, the volume needs to be increased to obtain a higher signal-to-noise ratio and a clear listening effect. The long-term high sound pressure caused by this will cause irreversible damage to hearing. With the improvement of vehicle intelligence, drivers and passengers have increasingly stringent requirements for the acoustic environment in the car. The noise in the car will reduce the comfort of the driver and passengers, causing irritability and fatigue of the passengers in the car; it will also affect the clarity of communication calls, and even affect the driver's perception of the signal sound outside the car, increasing traffic hazards. Automobile NVH (Noise, Vibration, Harshness) is an important issue that car manufacturers are concerned about. Reducing noise by modifying the structural design, adding damping materials or using devices such as shock-absorbing springs is collectively referred to as passive noise control; this method has a better noise reduction effect on mid- and high-frequency noise. However, this method has a poor effect on low frequencies, especially road noise caused by the collision and friction between the road surface and tires, which is often concentrated in low frequencies. In addition, passive noise control requires a long time to adjust and it is difficult to control costs. The active noise reduction solution uses the vehicle's audio system to create a counter-signal to the noise signal, forming a secondary sound wave to offset the noise in the target area, reduce noise pollution, and improve subjective listening comfort. However, it adds almost no extra weight to the vehicle, helps reduce exhaust emissions, and is a green, energy-saving solution.

[0003] The FxLMS (Filtered-x Least Mean Square) algorithm is a commonly used algorithm in active noise control. It is widely used because of its low consumption of computing resources and good algorithm robustness. However, the FxLMS algorithm has the problem of slow convergence. A normalized factor can be introduced, also called the NFxLMS (Normalized Filtered-x Least Mean Square) algorithm or FxNLMS. Although there are patents (such as US10789932B2) that mention the normalized FxLMS algorithm, the normalized calculation of the algorithm at that time only estimated the energy of each reference signal itself, without considering the influence of the secondary channel transfer function. In addition, the NFxLMS algorithm is often a single-channel (SISO, Single Input Single Output) algorithm. Controlling road noise requires a multi-channel algorithm (MIMO, Multiple Inputs Multiple Outputs). However, the multi-channel NFxLMS algorithms introduced in articles such as "A Diffusion Strategy for the Multichannel Active Noise Control System in Distributed Network", Ju-man Song, 2016 and "Multichannel Feedforward Active Noise Control System with Optimal Reference Microphone Selector Based on Time Difference of Arrival", Kenta Iwai, 2018 are all performed in the time domain, especially in the case of multiple channels, which requires relatively large computing resources. Summary of the invention

[0004] The purpose of the present invention is to provide a vehicle road noise control method and device based on time-frequency domain, which can actively reduce the road noise caused by the friction between the vehicle tires and the road surface, reduce the noise pollution inside the vehicle and have a faster convergence speed, while requiring less computing resources and more accurate calculations.

[0005] The present invention also provides a computer-readable storage medium storing a program capable of implementing the above-mentioned vehicle road noise control method.

[0006] According to a first aspect of the present invention, a vehicle noise reduction method for broadband noise comprises the following steps:

[0007] The J channel reference signal of vehicle road noise is collected at each sampling moment, denoted as x j (n), j = 1, 2, ..., J, J is the number of channels of the reference signal, and n represents the sampling time;

[0008] Generate a control signal according to the filter control coefficient at the current moment and the multi-channel reference signal, and feed the control signal to the sound playback device of the vehicle corresponding to the area where noise reduction is required;

[0009] Collect the residual noise signal at each sampling moment in the area where noise reduction is required, and record it as the error signal e m (n), m = 1, 2, ..., M;

[0010] The vehicle road noise control method further comprises: if the accumulated data of the reference signal and the error signal reach N respectively, a frequency domain calculation step is performed, and the frequency domain calculation step comprises:

[0011] S101, generate a reference signal X in the frequency domain j , where X j =[X j (0), X j (1), …X j (2N-1)] T , X j (0), X j (1) X j (2N-1) represents the characteristics of the corresponding reference signals at the 1st, 2nd, and 2Nth analysis frequencies, respectively;

[0012] S102, generate an error signal E in the frequency domain m , where E m =[E m (0), E m (1), …E m (2N-1)] T , E m (0), E m (1) E m (2N-1) represents the characteristics of the corresponding error signals at the 1st, 2nd, and 2Nth analysis frequencies respectively;

[0013] S103: Generate a reference signal after frequency domain filtering It is expressed as follows

[0014]

[0015] Among them, S l，m =[s l，，m (0), S l，m (1), …S l，m (2N-1)]T , l=1,2,…,L; m=1,2,…,M,S l，m represents the transfer function between the lth loudspeaker and the mth residual noise signal collecting device, where M is the number of residual noise signal collecting devices;

[0016] S104, transform the reference signal after frequency domain filtering into the time domain, and intercept the first N points, recorded as

[0017] in, Respectively represent the filtered reference signals at the 1st, 2nd, and Nth sampling time points;

[0018] S105, re-transform to obtain the filtered reference signal in the frequency domain

[0019] S106. For each frequency point, construct the filtered reference signal into the following two-dimensional matrix U(k):

[0020]

[0021] in, Represents the frequency domain value of the jth reference signal after the transfer function filtering from the lth speaker to the mth microphone, ∈R J·L×M represents a matrix with JL rows and M columns;

[0022] S107, for each frequency point, generate a gradient vector in the frequency domain, as shown in the following formula:

[0023] Φ(k)=μ·conj(U(k))[U T (k)U(k)+δI] -1 •Err(k)∈R J·L×1 k = 0, 1, ..., 2N-1;

[0024] Among them, Err(k)=[E1(k), E2(k), …E M (k)] T :conj(•) means taking its conjugate; μ is the convergence factor; δ is the regularization factor; I is the identity matrix;

[0025] The element composition of Φ(k) is defined as Φ(k)=[Ψ 1，1 (k),Ψ 1，2 (k), …Ψ J，L (k)] T ; The gradient increment from each channel is expressed as Ψ j，l =[Ψ j，l (0),Ψ j，l (1), …Ψ j，l(k)…Ψ j，l (2N-1)] T ;

[0026] S108, according to the gradient vector Ψ in the frequency domain j，l Generate the gradient vector in the time domain, transform the frequency domain value to the time domain, and intercept the first N points, which is

[0027] S109, according to Regenerate the gradient vector Ψ in the frequency domain j，l ;

[0028] S110, update the filter control parameter W in the frequency domain according to the following formula: j，l，new ,

[0029] W j，l，new =W j，l，old +Ψ j，l

[0030] Among them, W j，l，old , W j，l，new are the filter control parameters in the frequency domain before and after updating respectively;

[0031] S111, according to the filter control parameter W in the frequency domain j，l，new Transform to obtain the filter control coefficient w in the time domain j，l .

[0032] In a preferred embodiment, in step S101, a reference signal in the frequency domain is generated by the following formula:

[0033]

[0034] Where FFT stands for Fourier transform, x j (n) = [x j (n-N+1),…,x j (n-1), x j (n)] T , x j (n+N) represents the value of the reference signal at sampling time n+N and N time sampling times before that.

[0035] In a preferred embodiment, in step S102, a frequency error signal is generated by the following formula:

[0036]

[0037] Among them, e m (n) = [e m (n-N+1),…,e m (n-1), e m (n)]T .

[0038] In a preferred embodiment, in step S104, the reference signal after frequency filtering is transformed into the time domain by the following formula:

[0039]

[0040] l=1,2,…,L; m=1,2,…,M.

[0041] In a preferred embodiment, in step S105, the frequency filtering reference signal is re-transformed according to the following formula: It is expressed as follows

[0042]

[0043] in, Represents the vector of the filtered reference signal transformed into time domain sampling points, whose length is N and the initial sampling time is n.

[0044] In a preferred embodiment, in step S108, a gradient vector in the time domain is generated according to the following formula:

[0045]

[0046] In step S109, the gradient vector in the frequency domain is regenerated according to the following formula:

[0047]

[0048] In a preferred embodiment, in step S110, the filter control parameter w in the time domain is obtained according to the following formula: j，l ,

[0049] w j，l =G·IFFT[W j，l，new ]j=1,2,…,J; l=1,2,…,L;

[0050] Among them, w j，l =[w j，l (1), w j，l (2), …w j，l (N)] T .

[0051] In a preferred embodiment, the control signal y fed to the sound reproduction unit is generated according to the following formula: l (n),

[0052]

[0053] Among them, w j，l(i) indicates that the input is the jth reference signal and the output corresponds to the control coefficient of the filter of the lth sound reproduction device at the current moment.

[0054] In a preferred embodiment, the frequency domain calculation step is performed within a time period of N sampling time points. If the data of the reference signal and the error signal reaches N, the counter is reset, and the filter parameters obtained in the frequency domain through the frequency domain calculation step are updated to the time domain, and a new round of frequency domain calculation is started; if not, the vehicle road noise and error signal continue to be collected, and the counter continues to accumulate.

[0055] In a preferred embodiment, a vibration signal generated by the friction between the wheel and the road surface is collected by a vibration sensor as the reference signal.

[0056] More preferably, the vibration sensor is arranged on a floor of the vehicle.

[0057] In a preferred embodiment, a noise signal generated by the friction between the wheel and the road surface is collected by a first microphone as the reference signal.

[0058] More preferably, the first microphone is disposed at a location of the vehicle adjacent to a wheel.

[0059] In a preferred embodiment, the sound reproduction device includes a vehicle-mounted speaker arranged in the vehicle compartment. The vehicle-mounted speaker is arranged in the vehicle compartment or at least radiates sound to the vehicle compartment, including but not limited to: a headrest speaker, a ceiling speaker, a door panel speaker, etc.

[0060] In a preferred embodiment, the error signal acquisition device includes a plurality of second microphones, and the acoustic signals in the vehicle compartment are collected by the plurality of second microphones, and the plurality of second microphones are arranged at a plurality of sampling positions in the vehicle compartment.

[0061] According to a second aspect of the present invention, a vehicle road noise control device based on active noise reduction includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the vehicle road noise control method as described above when executing the program; the vehicle road noise control device also includes a road noise collection device for collecting noise or vibration signals caused by friction between wheels and road surfaces, a sound playback device for forming secondary sound waves for canceling noise in a vehicle compartment according to a control signal sent by the control device, and an error signal collection device for collecting participating noise signals at multiple positions in the vehicle compartment.

[0062] In a preferred embodiment, the road noise collecting device includes a vibration sensor disposed on a floor of the vehicle or a first microphone disposed at a location adjacent to a wheel of the vehicle.

[0063] In a preferred embodiment, the sound reproduction device includes a vehicle-mounted speaker. The vehicle-mounted speaker is placed in the vehicle compartment or at least radiates sound to the vehicle compartment, including but not limited to: a headrest speaker, a ceiling speaker, a door panel speaker, etc.

[0064] According to a third aspect of the present invention, a computer-readable storage medium stores a computer program, which, when executed by a processor, implements the vehicle road noise control method as described above.

[0065] The present invention adopts the above solution, which has the following advantages compared with the prior art:

[0066] The vehicle noise reduction method and device of the present invention adopt an improved time-frequency domain multi-channel FxNLMS (Time Frequency Domain Multiple InputsMultiple Outputs Filtered-x Normalized Least Mean Square) algorithm to target broadband noise such as road noise caused by friction between tires and the road surface. The filter parameters obtained in the frequency domain are calculated every N sampling time points and updated in the time domain. Compared with the time domain multi-channel NFxLMS algorithm, it requires less computing resources and converges faster than the traditional time-frequency domain FxLMS algorithm. It takes into account the coupling effect between channels, has more accurate calculations, and obtains better noise reduction performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the technical solution of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0068] Figure 1 4 is a flow chart of the time domain part of the multi-channel FxNLMS algorithm in the time and frequency domain according to an embodiment of the present invention.

[0069] Figure 2 4 is a flow chart of the frequency domain part of the multi-channel FxNLMS algorithm in the time-frequency domain according to an embodiment of the present invention.

[0070] Figure 3 4 is a block diagram of a multi-channel FxNLMS algorithm in the time-frequency domain according to an embodiment of the present invention.

[0071] Figure 4 3 is a comparison chart of the noise reduction performance at position 1 between the traditional multi-channel FxLMS algorithm and the multi-channel FxNLMS algorithm implemented in this paper.

[0072] Figure 5This is a comparison chart of the noise reduction performance at position 5 between the traditional multi-channel FxLMS algorithm and the multi-channel FxNLMS algorithm implemented in this paper. DETAILED DESCRIPTION

[0073] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings so that the advantages and features of the present invention can be more easily understood by those skilled in the art. It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention.

[0074] This embodiment provides a vehicle noise reduction method based on active noise reduction, which uses a time-frequency domain multi-channel FxNLMS algorithm (denoted as TFD MIMO NFxLMS, ​​Time Frequency Domain Multiple Inputs Multiple Outputs Filtered-x Normalized Least Mean Square) to target road noise caused by friction between vehicle tires and road surfaces. The algorithm consists of two parts, one is time domain calculation and the other is frequency domain calculation. Figures 1 to 3 The method is described in detail as follows.

[0075] Figure 1 It is the time domain calculation step of the algorithm. The calculation is performed at each sampling time point.

[0076] S201, reference signal acquisition: At each sampling time n, a reference signal is collected from a sensor, such as a vibration signal of the car floor from a vibration sensor, or a sound signal is collected through a microphone set near the wheel, etc. The vibration signal or the sound signal is used as a reference signal for the noise reduction object (noise caused by friction between the tire and the road surface). There are J channel reference signals, denoted as x j (n), j=1, 2,…, J.

[0077] S202, error signal acquisition: At each sampling time n, the residual noise signal of the target area (for example, the interior of the vehicle) is collected from the microphones arranged in the vehicle. There are M microphone signals in total, denoted as e m (n), m=1, 2,…,M.

[0078] S203, control signal generation: according to the filter control coefficient w at the current moment j，l (n) and the reference signal obtained in the previous step to generate the control signal y l (n), fed to the car speakers and other sound reproduction units in the car,

[0079]

[0080] The number of speaker channels is L, and the order of the adaptive filter is N. j，l (i) indicates that the input is the jth reference signal, and the output is the control coefficient of the filter corresponding to the lth control sound source (car speaker) at the current moment.

[0081] It is determined whether the reference signal and the error signal data are accumulated to N. If yes, the counter is cleared, the filter coefficients obtained in the frequency domain are updated to the time domain, and a new round of frequency domain calculation is started; if no, the counter continues to accumulate, and the above steps S201 to S203 are continued.

[0082] Figure 2 It is the frequency domain calculation step of the algorithm. The calculation is performed within a time period of N sampling time points.

[0083] S101, generate a reference signal in the frequency domain. According to the overlap-save method, perform FFT operation on 2N data of the reference signal of each channel, which is specifically expressed as

[0084]

[0085] Among them, x j (n) = [x j (n-N+1),…,x j (n-1), x j (n)] T ;X j =[X j (0), X j (1), …X j (2N-1)] T .

[0086] S102, generating an error signal in the frequency domain. According to the overlap-save method, the error signal of each channel is padded with zeros and then FFT calculation is performed, which is specifically expressed as:

[0087]

[0088] Among them, e m (n) = [e m (n-N+1),…,e m (n-1), e m (n)] T ; E m =[E m (0), E m (1), …E m (2N-1)] T .

[0089] S103, generate a filtered reference signal. An important step in the FxNLMS algorithm is to filter the reference signal. It is generally believed that the transfer function of the secondary channel includes the transfer path of the digital control signal y(n) through the DAC module, analog filter, power amplifier module, vehicle speaker, spatial propagation of sound waves, microphone, analog filter, and ADC module. The transfer function S of the secondary channel is obtained through online and offline system identification methods. It is a digital filter with a length of N. Here we consider its frequency domain form as S l，m =[S l，m (0), S l，m (1), …S l，m (2N-1)] T , l = 1, 2, ..., L; m = 1, 2, ..., M, represents the transfer function between the lth speaker and the mth microphone. M is the number of microphones. The reference signal after filtering is calculated as

[0090]

[0091] k=0, 1,…,2N-1; j=1, 2,…,J;

[0092] l=1,2,…,L; m=1,2,…,M.

[0093] Among them, k represents the kth frequency point. Since the length of FFT is 2N, there are 2N frequency points.

[0094] S104, transform the reference signal after frequency domain filtering into time domain, and intercept the first N points

[0095]

[0096] k=0, 1,…,2N-1; j=1, 2,…,J;

[0097] l=1,2,…,L; m=1,2,…,M

[0098] in

[0099] S105, re-transform to obtain the filtered reference signal in the frequency domain

[0100]

[0101] j=1,2,…,J; l=1,2,…,L; m=1,2,…,M.

[0102] S106: For each frequency point, the filtered reference signal is constructed into a two-dimensional matrix

[0103]

[0104] Among them, ∈R J·L×M represents a matrix with JL rows and M columns;

[0105] S107, for each frequency point, generate a gradient vector in the frequency domain,

[0106] Φ(k)=μ·conj(U(k))[U T (k)U(k)+δI] -1 Err(k)∈R J·L×1

[0107] k = 0, 1, ..., 2N-1;

[0108] Among them, Err(k)=[E1(k), E2(k), …E M (k)] T ; conj(·) means taking its conjugate; μ is the convergence factor, which is a constant, and its value is usually between 0 and 2; δ is the regularization factor, which is a decimal close to 0; I is the identity matrix. This expression normalizes the expression of the LMS algorithm, but it is extended to multiple channels and takes into account the coupling effect between channels. Note that the element composition of Φ(k) is defined as Φ(k)=[Ψ 1，1 (k),Ψ 1，2 (k), …Ψ J，L (k)] T ; At the same time, the gradient increment from each channel is expressed as Ψ j，l =[Ψ j，l (0),Ψ j，l (1), …Ψ j，l (k)…Ψ j，l (2N-1)] T ; The elements are reorganized from the perspective of frequency domain and from the perspective of channel number.

[0109] S108, generate a gradient vector in the time domain, transform the value in the frequency domain to the time domain, and then intercept the first N points.

[0110]

[0111] in,

[0112] S109, regenerate the gradient vector in the frequency domain

[0113]

[0114] S110, updating filter control parameters in frequency domain

[0115] W j，l，new =Wj，l，old +Ψ j，l j=1,2,…,J; l=1,2,…,L;

[0116] Among them, W j，l =[W j，l (0), W j，l (1), …W j，l (2N-1)] T .

[0117] S111, transform to obtain the filter control parameters in the time domain, and intercept the first N points

[0118] w j，l =G·IFFT[W j，l，new ]j=1,2,…,J; l=1,2,…,L;

[0119] Among them, w j，l =[w j，l (1), w j，l (2), …w j，l (N)] T .

[0120] Simulation Example

[0121] The convergence performance of the algorithm was simulated. In the simulation experiment, the target noise is a broadband signal with a frequency band covering 80Hz-320Hz, which is a typical frequency band distribution of road noise. The noise signal is a white noise signal generated by passing through a bandpass filter. The number of reference signal channels K=2, the number of vehicle-mounted speakers L=5, and the number of error signal acquisition microphones in the car M=5. The transfer function between the speaker and the microphone, which is also the transfer function of the secondary channel mentioned above, is collected in the actual vehicle. In the simulation experiment, the relationship between the change of noise energy before and after active noise control with the number of iterations (also corresponding to time) is compared. More importantly, the traditional multi-channel FxLMS algorithm and the multi-channel time-frequency domain FxNLMS algorithm proposed in this embodiment are compared. Figure 4 The relationship between the amplitude of the residual noise signal at the first position and the iteration is given. It can be seen from the figure that the traditional FxLMS algorithm has a certain noise reduction effect; using the FxNLMS algorithm of this embodiment, the algorithm converges faster and the final noise reduction amount is similar. Figure 5 The relationship between the residual noise signal amplitude at the fifth position and the iteration change is given. It can be seen from the figure that the traditional FxLMS algorithm has almost no noise reduction effect; the FxNLMS algorithm of this embodiment has a significant noise reduction effect, fast convergence speed, and large noise reduction amount.

[0122] Those skilled in the art will appreciate that, unless otherwise stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present application refers to the presence of features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0123] The above embodiment is only for illustrating the technical concept and features of the present invention, and is a preferred embodiment. Its purpose is to enable people familiar with the technology to understand the content of the present invention and implement it accordingly, and it cannot be used to limit the protection scope of the present invention. Any equivalent transformation or modification made according to the spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. A vehicle noise reduction method for broadband noise, comprising the following steps: The J channel reference signal of vehicle road noise is collected at each sampling moment, denoted as x j (n), j = 1, 2, ..., J, J is the number of channels of the reference signal, and n represents the sampling time; Generate a control signal according to the filter control coefficient at the current moment and the reference signal, and feed the control signal to the sound playback device of the vehicle corresponding to the area where noise reduction is required; Collect the residual noise signal at each sampling moment in the area where noise reduction is required, and record it as the error signal e m (n), m = 1, 2, ..., M; It is characterized in that The vehicle road noise control method further includes: if the accumulated data of the reference signal and the error signal reach N respectively, executing a frequency domain calculation step, the frequency domain calculation step including: S101, generate a reference signal X in the frequency domain j , where X j =[X j (0),X j (1),…X j (2N-1)] T , X j (0), X j (1) X j (2N-1) represents the characteristics of the corresponding reference signals at the 1st, 2nd, and 2Nth analysis frequencies, respectively; S102, generate an error signal E in the frequency domain m , where E m =[E m (0),E m (1),…E m (2N-1)] T , E m (0), E m (1) E m (2N-1) represents the characteristics of the corresponding error signals at the 1st, 2nd, and 2Nth analysis frequencies respectively; S103: Generate a reference signal after frequency domain filtering It is expressed as follows Among them, S l,m =[S l,m (0),S l,m (1),…S l,m (2N-1)] T ,l=1,2,…,L; m=1,2,…,M,s l,m represents the transfer function between the lth loudspeaker and the mth residual noise signal collecting device, where M is the number of residual noise signal collecting devices; S104, transform the reference signal after frequency domain filtering into the time domain, and intercept the first N points, recorded as in, Respectively represent the filtered reference signals at the 1st, 2nd, and Nth sampling time points; S105, re-transform to obtain the filtered reference signal in the frequency domain S106. For each frequency point, construct the filtered reference signal into the following two-dimensional matrix U(k): in, Represents the frequency domain value of the jth reference signal after the transfer function filtering from the lth speaker to the mth microphone, ∈R J·L×M represents a matrix with JL rows and M columns; S107, for each frequency point, generate a gradient vector in the frequency domain, as shown in the following formula: Φ(k)=μ·conj(U(k))[UT(k)U(k)+δI| -1 ·Err(k)∈R J·L×1 k=0,1,…,2N-1; Where Err(k)=[E1(k),E2(k),…E M (k)] T ; conj(·) means taking its conjugate; μ is the convergence factor; δ is the regularization factor; I is the unit matrix; The element composition of Φ(k) is defined as Φ(k)=[Ψ 1,1 (k),Ψ 1,2 (k),…Ψ J,L (k)] T ; The gradient increment from each channel is expressed as Ψ j,l =[Ψ j,l (0),Ψ j,l (1),…Ψ j,l (k)…Ψ j,l (2N-1)] T ; S108, according to the gradient vector Ψ in the frequency domain j,l Generate the gradient vector in the time domain, transform the frequency domain value to the time domain, and intercept the first N points, which is S109, according to Regenerate the gradient vector ψ in the frequency domain j,l ; S110, update the filter control parameter W in the frequency domain according to the following formula: j,l,new , W j,l,new =W j,l,old +Ψ j,l Among them, W j,l,old , W j,l,new are the filter control parameters in the frequency domain before and after updating respectively; S111, according to the filter control parameter W in the frequency domain j,l,new Transform to obtain the filter control coefficient w in the time domain j,l .

2. The vehicle noise reduction method according to claim 1, characterized in that: In step S101, a reference signal in the frequency domain is generated by the following formula: Where FFT stands for Fourier transform, x j (n) = [x j (n-N+1),…,x j (n-1),x j (n)] T , x j (n+N) represents the value of the reference signal at sampling time n+N and N time sampling times before that; and / or, In step S102, the error signal in the frequency domain is generated by the following formula: Among them, e m (n) = [e m (n-N+1),…,e m (n-1), e m (n)] T .

3. The vehicle noise reduction method according to claim 1, characterized in that: In step S104, the reference signal after frequency filtering is transformed into the time domain by the following formula: And / or, in step S105, the frequency filtering reference signal is re-transformed according to the following formula: It is expressed as follows in, Represents the vector of the filtered reference signal transformed into time domain sampling points, whose length is N and the initial sampling time is n.

4. The vehicle noise reduction method according to claim 1, characterized in that: In step S108, the gradient vector in the time domain is generated according to the following formula: And / or, in step S109, the gradient vector in the frequency domain is regenerated according to the following formula: And / or, in step S110, the filter control coefficient w in the time domain is obtained according to the following formula: j,l , w j,l =G·IFFT[W j,l,new ] j=1,2,…,J;l=1,2,…,L; where, w j,l = [w j,l (1), w j,l (2), … w j,l (N)] T .

5. The vehicle noise reduction method according to claim 1 or 4, characterized in that: The control signal y fed to the sound reproduction unit is generated according to the following formula l (n), Among them, w j,l (i) indicates that the input is the jth reference signal and the output corresponds to the control coefficient of the filter of the lth sound reproduction device at the current moment.

6. The vehicle noise reduction method according to claim 1, characterized in that: The frequency domain calculation step is performed within a time period of N sampling time points. If the data of the reference signal and the error signal reaches N, the counter is reset, and the filter parameters obtained in the frequency domain through the frequency domain calculation step are updated to the time domain, and a new round of frequency domain calculation is started; if not, the vehicle road noise and error signal continue to be collected, and the counter continues to accumulate.

7. The vehicle noise reduction method according to claim 1, characterized in that: The vibration signal generated by the friction between the wheel and the road surface is collected by a vibration sensor as the reference signal; and / or, the noise signal generated by the friction between the wheel and the road surface is collected by a first microphone as the reference signal, and the first microphone is arranged at a position adjacent to the wheel of the vehicle.

8. The vehicle noise reduction method according to claim 1, characterized in that: The sound reproduction device includes a vehicle-mounted speaker arranged in the vehicle compartment; and / or, the residual noise signal in the vehicle compartment is collected by multiple second microphones, and the multiple second microphones are arranged at multiple sampling positions in the vehicle compartment.

9. A vehicle road noise control device based on active noise reduction, 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 program, the vehicle noise reduction method according to any one of claims 1 to 8 is implemented; the vehicle road noise control device also includes a road noise collection device for collecting noise or vibration signals caused by friction between the wheels and the road surface, a sound playback device for forming a secondary sound wave in the car to offset the noise according to the control signal sent by the control device, and an error signal collection device for collecting participating noise signals at multiple positions in the car.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the vehicle noise reduction method according to any one of claims 1 to 8.

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