A vehicle road noise control method, system and storage medium based on active noise reduction

Abstract

The present invention discloses a vehicle road noise control method, system, and storage medium based on active noise cancellation. The vehicle road noise control method includes: collecting multi-channel reference signals of vehicle road noise; generating a control signal according to the filter coefficients at the current moment and the multi-channel reference signals, and feeding it to the sound reproduction device of the vehicle; collecting sound signals at multiple sampling positions inside the vehicle compartment to obtain a vector of error signals; filtering the reference signals to obtain filtered reference signals; writing the filtered reference signals in matrix form; and updating the filter coefficients according to the matrix form of the filtered reference signals and the vector of error signals. The present invention can perform active noise cancellation on the road noise caused by the friction between vehicle tires and the road surface, reduce the in-vehicle noise pollution, and has a relatively fast convergence speed and relatively high accuracy.

Description

Technical Field

[0001] The present invention belongs to the field of vehicle noise control, and relates to a vehicle road noise control method and system based on active noise reduction, and a storage medium. 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 and is often a single-channel (SISO, Single Input Single Output) algorithm. The control of road noise requires a multi-channel algorithm (MIMO, Multiple Inputs Multiple Outputs). However, the multi-channel NFxLMS algorithm 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, all consider the channels to be orthogonal, ignoring the influence of the coupling term, so there is a certain error. Summary of the invention

[0004] The purpose of the present invention is to provide a vehicle road noise control method and system based on active noise reduction, 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 and better accuracy.

[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 road noise control method based on active noise reduction comprises the following steps:

[0007] A. Collect the multi-channel reference signal of vehicle road noise, denoted as x k (n), k = 1, 2, ..., K, K is the number of channels of the reference signal, and n represents the sampling time;

[0008] B. generating a control signal according to the filter coefficient at the current moment and the multi-channel reference signal, and feeding the control signal to a sound playback device of the vehicle;

[0009] C. Collecting acoustic signals at multiple sampling positions in the vehicle compartment to obtain a vector e(n) of an error signal;

[0010] D. Filtering the reference signal to obtain a filtered reference signal As shown in the following formula,

[0011]

[0012] Where N is the filter length, L is the number of channels of the sound reproduction unit, M is the number of sampling positions, and s l，m represents the transfer function between the lth speaker and the mth sampling position, which is a finite length filter of order N. l，m (i) is the i-th coefficient of the filter; x k (ni) represents the k-th reference signal at the previous i sampling moments;

[0013] E. Write the filtered reference signal in matrix form as shown below:

[0014]

[0015]

[0016] in, represents a matrix of size K·L rows and M columns, the elements of which are the filtered reference signal at the current sampling time. constitute; represents a matrix of size K·L·N rows and M columns, the elements of which are composed of the filtered reference signals at the current sampling time and the historical sampling time. represents a matrix of size K·L rows and M columns, the elements of which are the filtered reference signal at the previous N-1th moment Composition, ∈R K·L×M Indicates that this is a matrix with K·L rows and M columns, ∈R K·LN×M It means that this is a matrix with K·L·N rows and M columns;

[0017] F. Update the filter coefficients in step B according to the following formula:

[0018]

[0019] Among them, w(n+1) represents the updated filter coefficient, w(n) represents the filter coefficient at the current moment, μ is the convergence factor, δ is the regularization factor, and I is the unit matrix.

[0020] In a preferred embodiment, the matrix form of the filter coefficients w(n) is:

[0021] w(n)=[[w 1，1 (0),…,w J，K (0)]…[w 1，1 (N-1),…,w J，K (N-1)]] T ∈R K·L·N×1

[0022] Among them, ∈R K·L·N×1 Indicates that this is a matrix with K·L·N rows and 1 column;

[0023] In step B, the control signal is as follows:

[0024]

[0025] Among them, w k，l (i) is an element in the w(n) matrix, specifically representing the i-th order coefficient of the filter whose input is the k-th reference signal and whose output is the l-th sound reproduction device. There are K·L such filters in total, with an order of N. Each order i of the K·L filters is combined into an array [w 1，1 (i), …, w J，K (i)]; and all order coefficients together constitute w(n).

[0026] In a preferred embodiment, in step A, a vibration signal generated by the friction between the wheel and the road surface is collected by a vibration sensor as the reference signal.

[0027] More preferably, the vibration sensor is arranged on a floor of the vehicle.

[0028] In a preferred embodiment, in step A, a noise signal generated by the friction between the wheel and the road surface is collected by a first microphone as the reference signal.

[0029] More preferably, the first microphone is disposed at a location of the vehicle adjacent to a wheel.

[0030] In a preferred embodiment, in step B, the sound reproduction device includes a vehicle-mounted speaker disposed in the vehicle compartment. The vehicle-mounted speaker is disposed 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.

[0031] In a preferred embodiment, in step C, acoustic signals in the vehicle compartment are collected by a plurality of second microphones, and the plurality of second microphones are arranged at a plurality of sampling positions in the vehicle compartment.

[0032] According to a second aspect of the present invention, a vehicle road noise control system based on active noise reduction comprises:

[0033] A road noise collection device, which is used to collect noise or vibration signals caused by the friction between the wheels and the road surface;

[0034] A control device, which is used to generate a multi-channel reference signal according to the noise or vibration signal collected by the road noise collection device; and is also used to generate a control signal according to the filter coefficient at the current moment and the multi-channel reference signal;

[0035] a sound reproducing device for generating a secondary sound wave for canceling noise in the vehicle compartment according to a control signal sent by the control device; and

[0036] An error signal acquisition device, which is used to collect acoustic signals at multiple positions in the carriage to obtain a vector e(n) of the error signal;

[0037] The control device is further used to filter the reference signal and write it into a matrix form, and update the filter coefficient according to the matrix form of the filtered reference signal and the vector of the error signal according to the following formula:

[0038]

[0039] Among them, w(n+1) represents the updated filter coefficient, w(n) represents the filter coefficient at the current moment, μ is the convergence factor, is the matrix form of the filtered reference signal, δ is the regularization factor, and I is the identity matrix.

[0040] In a preferred embodiment, the reference signal is filtered to obtain a filtered reference signal As shown in the following formula,

[0041]

[0042] Where N is the filter length, L is the number of channels of the sound reproduction unit, M is the number of sampling positions, and s l，m represents the transfer function between the lth speaker and the mth sampling position, which is a finite length filter of order N. l，m (i) is the i-th coefficient of the filter; x k (ni) represents the k-th reference signal at the previous i sampling moments;

[0043] E. Write the filtered reference signal in matrix form as shown below:

[0044]

[0045]

[0046] in, represents a matrix of size K·L rows and M columns, the elements of which are the filtered reference signal at the current sampling time. constitute; represents a matrix of size K·L·N rows and M columns, the elements of which are composed of the filtered reference signals at the current sampling time and the historical sampling time. represents a matrix of size K·L rows and M columns, the elements of which are the filtered reference signal at the previous N-1th moment Composition, ∈R K·L×M Indicates that this is a matrix with K·L rows and M columns, ∈R K·L·N×M This means that this is a matrix with K·L·N rows and M columns.

[0047] In a preferred embodiment, the matrix form of the filter coefficients w(n) is:

[0048] w(n)=[[w 1，1 (0),…,w J，K (0)]…[w 1，1 (N-1),…,w J，K (N-1)]] T ∈R K·L·N×1

[0049] Among them, ∈R K·L·N×1 Indicates that this is a matrix with K·L·N rows and 1 column;

[0050] In step B, the control signal is as follows:

[0051]

[0052] Among them, w k，l (i) is an element in the w(n) matrix, specifically representing the i-th order coefficient of the filter whose input is the k-th reference signal and whose output is the l-th sound reproduction device. There are K·L such filters in total, with an order of N. Each order i of the K·L filters is combined into an array [w 1，1 (i), …, w J，K (i)]; and all order coefficients together constitute w(n).

[0053] 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.

[0054] 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.

[0055] 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.

[0056] The present invention adopts the above solution, which has the following advantages compared with the prior art:

[0057] The vehicle road noise control method and system of the present invention adopt an improved multi-channel normalized FxLMS algorithm to normalize the convergence factor for the road noise caused by the friction between the tire and the road surface, which converges faster than the traditional FxLMS algorithm; the normalized calculation takes into account the coupling between channels, and is more accurate and converges faster than the existing multi-channel NFxLMS algorithm. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] 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.

[0059] Figure 1 4 is a flowchart of a MIMO MNFxLMS algorithm according to an embodiment of the present invention.

[0060] Figure 2 is a block diagram of a MIMO MNFxLMS algorithm according to an embodiment of the present invention.

[0061] Figure 3 The figure is a comparison chart of the convergence performance of the three algorithms, MIMO FxLMS, ​​MIMO NFxLMS and MIMO MNFxLMS, ​​at position 1.

[0062] Figure 4 The figure is a comparison of the convergence performance of the three algorithms, MIMO FxLMS, ​​MIMO NFxLMS and MIMO MNFxLMS, ​​at position 2. DETAILED DESCRIPTION

[0063] 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.

[0064] This embodiment provides a vehicle road noise control method based on active noise reduction, which uses an improved multi-channel normalized FxLMS (denoted as MIMOMNFxLMS, ​​Multiple InputsMultiple Outputs Modified Normalized Filtered-x Least Mean Square) algorithm to perform active noise reduction on the road noise caused by the friction between the vehicle tires and the road surface. Figure 1 and Figure 2 The method is described in detail as follows.

[0065] (1) Reference signal acquisition

[0066] At each sampling time n, a reference signal is collected from a sensor, such as a vibration signal from a vibration sensor (typically located on the bottom plate of the vehicle) or an acoustic signal from a microphone (typically located on a portion of the vehicle adjacent to the wheel). There are a total of K channel reference signals, denoted by x k (n), k=1, 2,…,K.

[0067] (2) Control signal generation

[0068] According to the current parameter w k，l (n) and the reference signal obtained in the previous step to generate the control signal y l (n) feeding a sound reproduction device. Specifically in this embodiment, the sound reproduction device includes a vehicle-mounted speaker.

[0069]

[0070] Among them, the number of speaker channels is L, and the order of the adaptive filter is N. k，l (i) indicates that the input of the filter is the kth reference signal and the output is the lth controlled sound source, which is the speaker here.

[0071] (3) Generate a filtered reference signal

[0072] An important step in the FxLMS 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, 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 and is expressed as S'. It is a digital filter with a length of N, expressed as s l，m, 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

[0073]

[0074] (4) Write the filtered reference signal in the form of a matrix

[0075]

[0076]

[0077] Among them, ∈R K·L×M Indicates that this is a matrix with K·L rows and M columns, ∈R K·L·N×M Indicates that this is a matrix with K·L·N rows and M columns.

[0078] (5) According to the error signal e collected by each microphone m (n)

[0079] There are M microphone signals in total, and the vector of error signals is obtained, which is expressed as

[0080] e(n)=[e 1 (n),…,e M (n)] T ∈R M×1

[0081] (6) Update the control filter parameter w(n), expressed as

[0082]

[0083] Where δ is the regularization factor, which is usually a small number based on experience. I is the unit matrix. μ is the convergence factor, which is usually a number selected based on experience, and its value range is usually between 0 and 2. The matrix form of w(n) is

[0084] w(n)=[[w 1，1 (0),…,w J，K (0)]…[w 1，1 (N-1),…,w J，K (N-1)]] T ∈R K·L·N×1

[0085] Among them, w k，l The definition of (i) is given in step (2).

[0086] Simulation Example

[0087] 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 a bandpass filter. The number of channels of the reference signal is set to K=2, the number of speakers is set to L=5, and the number of microphones for collecting error signals is set to 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 respectively. More importantly, the traditional multi-channel FxLMS algorithm (MIMO FxLMS), the existing multi-channel normalized FxlMS algorithm (MIMO NFxLMS) and the improved normalized FxLMS algorithm (MIMO MNFxLMS) proposed in the present invention are compared. Figure 3 The relationship between the residual noise signal amplitude at the first position and the iteration is given, from Figure 3 It can be seen that the traditional FxLMS algorithm has a certain noise reduction effect; after normalization, the algorithm converges faster; and the improved normalization algorithm of the present invention can achieve a faster convergence effect. Figure 4 The relationship between the residual noise signal amplitude at the fifth position and the iteration is given. Figure 4 It can be seen that the traditional FxLMS algorithm has almost no noise reduction effect; after normalization processing, there is an obvious noise reduction effect. If the improved normalization algorithm of the present invention is adopted, considering the coupling effect between channels, a faster convergence speed and a larger noise reduction amount can be achieved.

[0088] 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.

[0089] It is further understood that in the present disclosure, "plurality" refers to two or more than two, and other quantifiers are similar. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship. The singular forms "a", "the" and "the" are also intended to include the plural forms, unless the context clearly indicates other meanings.

[0090] It is further understood that the terms "first", "second", etc. are used to describe various information, but such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other, and do not indicate a specific order or degree of importance. In fact, the expressions "first", "second", etc. can be used interchangeably. For example, without departing from the scope of the present disclosure, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as the first information.

[0091] 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 road noise control method based on active noise cancellation, comprising the following steps: A. Collect multi-channel reference signals of vehicle road noise, denoted as x k (n), k = 1, 2, …, K, where K is the number of channels of the reference signal, and n represents the sampling time; B. Generate a control signal according to the filter coefficients at the current moment and the multi-channel reference signal, and feed it to the sound reproduction device of the vehicle; Characterized in that, The vehicle road noise control method further comprises the following steps: C. Collect the sound signals at multiple sampling positions inside the vehicle compartment to obtain the vector e(n) of the error signal; D. Filter the reference signal to obtain a filtered reference signal As shown in the following formula where N is the filter length, L is the number of channels of the sound reproduction unit, M is the number of sampling positions, and s l,m represents the transfer function between the l-th loudspeaker and the m-th sampling position, and s l,m (i) is the i-th coefficient of the filter; x k (n - i) represents the k-th reference signal at the previous i sampling instants; E. Write the filtered reference signal in the matrix form shown in the following formula, Among them, represents a matrix with K·L rows and M columns, and the elements of the matrix are composed of the filtered reference signal at the current sampling moment constitute; represents a matrix with K·L·N rows and M columns, and the elements of the matrix are composed of the filtered reference signals at the current sampling moment and historical sampling moments, represents a matrix with K·L rows and M columns, and the elements of the matrix are composed of the filtered reference signal at the previous (N - 1)-th moment constitute, ∈R K·L×M indicates that this is a matrix with K·L rows and M columns, ∈R K·L·N×M indicates that this is a matrix with K·L·N rows and M columns; F. Update the filter coefficients in step B according to the following formula, where w(n + 1) represents the updated filter coefficients, which are used to filter and generate the output control signal at the next sampling moment n + 1; w(n) represents the filter coefficients at the current moment, μ is the convergence factor, δ is the regularization factor, and I is the identity matrix.

2. The vehicle road noise control method according to claim 1, Characterized in that, The matrix form of the filter coefficients w(n) is: w(n) = [[w 1,1 (0), …, w J,K (0)] … [w 1,1 (N - 1), …, w J,K (N - 1)]] T ∈R K·L·N×1 where ∈ R K·L·N×1 represents a matrix with K·L·N rows and 1 column; In step B, the control signal is as shown in the following formula: where, w k,l (i) is an element in the w(n) matrix, specifically representing the i-th order coefficient of the filter whose input is the k-th reference signal and output is the l-th sound reproduction device. There are a total of K·L such filters, and the order is N; for each order i of the K·L filters, they are combined into an array form [w 1,1 (i), …, w J,K (i)]; and all order coefficients together constitute w(n).

3. The vehicle road noise control method according to claim 1, Characterized in that, In step A, a vibration signal generated by the friction between the wheel and the road surface is collected by a vibration sensor as the reference signal.

4. The vehicle road noise control method according to claim 3, Characterized in that, The vibration sensor is arranged on the vehicle floor.

5. The vehicle road noise control method according to claim 1, Characterized in that, In step A, a noise signal generated by the friction between the wheel and the road surface is collected by a first microphone as the reference signal.

6. The vehicle road noise control method according to claim 5, Characterized in that, The first microphone is arranged at a position of the vehicle adjacent to the wheel.

7. The vehicle road noise control method according to claim 1, Characterized in that, In step B, the sound reproduction device includes an in-vehicle speaker arranged inside the vehicle compartment; and / or, in step C, the sound signals inside the vehicle compartment are collected by a plurality of second microphones, and the plurality of second microphones are arranged at multiple sampling positions inside the vehicle compartment.

8. A vehicle road noise control system based on active noise cancellation, Characterized in that, For implementing the vehicle road noise control method as claimed in claim 1, the vehicle road noise control system includes: A road noise collection device for collecting noise or vibration signals caused by the friction between the wheel and the road surface; A control device for generating a multi-channel reference signal according to the noise or vibration signals collected by the road noise collection device; and also for generating a control signal according to the filter coefficients at the current moment and the multi-channel reference signal; A sound reproduction device for forming a secondary sound wave for canceling noise inside the compartment according to the control signal sent by the control device; and An error signal collection device for collecting the sound signals at multiple positions inside the compartment to obtain the vector e(n) of the error signal; The control device is further configured to filter the reference signal and write it in matrix form, and update the filter coefficients according to the matrix form of the filtered reference signal and the vector of the error signal according to the following formula, Among them, \(w(n + 1)\) represents the updated filter coefficients, \(w(n)\) represents the filter coefficients at the current moment, and \(\mu\) is the convergence factor. is the matrix form of the filtered reference signal, \(\delta\) is the regularization factor, and \(I\) is the identity matrix.

9. The vehicle road noise control system according to claim 8, Characterized in that, The road noise acquisition device includes a vibration sensor disposed on the vehicle floor or a first microphone disposed at a position adjacent to the vehicle wheel; and / or, the sound reproduction device includes an in-vehicle speaker.

10. A computer-readable storage medium, characterized in that, a computer program is stored on the computer-readable storage medium, and when the program is executed by a processor, it implements the vehicle road noise control method according to any one of claims 1 to 7.

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