Noise reduction method and device of engine, vehicle and storage medium

Abstract

The invention relates to a noise reduction method and device of an engine, a vehicle and a storage medium, and relates to the technical field of vehicles. The technical problem that the driving experience of a user is affected due to high vehicle noise in related technologies is solved at least. The method comprises the following steps: acquiring a target noise reference signal of target order noise of an engine; and FxRLS filtering processing is conducted on the target noise reference signal based on a preset filtering weight coefficient, a first anti-noise signal is obtained, and the first anti-noise signal is used for counteracting noise generated when the engine rotates. And sending a first anti-noise signal.

Description

Technical Field

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

[0002] In recent years, with the development of the automobile industry and the improvement of people's living standards, users pay more and more attention to the driving experience of vehicles, and excessive noise of vehicles will affect the user's driving experience. At present, some algorithms can reduce the noise of vehicles to meet user needs. However, these algorithms still have a lot of room for improvement in transient characteristics, convergence speed, and steady-state error.

[0003] Therefore, a new noise reduction algorithm is needed to reduce the noise of the vehicle. Summary of the invention

[0004] According to the first aspect provided by the present application, the present application provides an engine noise reduction method, device, vehicle and storage medium to at least solve the technical problem in the related art that high vehicle noise affects the user's driving experience.

[0005] The method includes: obtaining a target noise reference signal of a target order noise of an engine, performing FxRLS filtering on the target noise reference signal based on a preset filtering weight coefficient, obtaining a first anti-noise signal, the first anti-noise signal being used to offset the noise generated when the engine rotates, and issuing the first anti-noise signal.

[0006] In a possible implementation, noise reference signals of multiple order noises of the engine are obtained. Based on the noise reference signals of the multiple order noises, a rotational speed frequency corresponding to the noise reference signal of each order noise is determined to determine multiple rotational speed frequencies. A target frequency less than a preset frequency threshold is determined from the multiple rotational speed frequencies. A target noise reference signal corresponding to the target frequency is determined from the noise reference signals of the multiple order noises.

[0007] In a possible implementation, the second anti-noise signal and the noise signal of the engine are collected by a microphone, an error signal is generated based on the second anti-noise signal and the noise signal of the engine, and a preset filter weight coefficient is updated based on the error signal to obtain an updated preset filter weight coefficient.

[0008] In a possible implementation, a transfer function corresponding to a secondary channel is obtained, where the secondary channel is a channel between a loudspeaker and a microphone, and a second anti-noise signal is obtained based on the transfer function and the first anti-noise signal.

[0009] In a possible implementation, a historical error signal is obtained, and one historical error signal corresponds to one historical preset filter weight coefficient. Based on the historical error signal, the error signal, the weight coefficient of the historical error signal, and the weight coefficient of the error signal, an objective function is generated, and the weight coefficient is positively correlated with the number of times the preset filter weight coefficient is updated. The objective function is processed to obtain an objective function gradient, and the objective function gradient is used to indicate the partial derivative of the objective function with respect to the preset filter weight coefficient. Based on the objective function gradient, the weight coefficient is updated.

[0010] In a possible implementation manner, the target noise reference signal includes at least one of the following: a second-order noise reference signal and a fourth-order noise reference signal.

[0011] According to a second aspect provided by the present application, a noise reduction device for an engine is provided, the device comprising an acquisition module and a processing module. The acquisition module is used to acquire a target noise reference signal of a target order noise of the engine. The processing module is used to perform FxRLS filtering on the target noise reference signal based on a preset filtering weight coefficient to obtain a first anti-noise signal, the first anti-noise signal being used to offset the noise generated when the engine rotates. The processing module is also used to send the first anti-noise signal.

[0012] In a possible implementation, the acquisition module is further used to acquire noise reference signals of multiple order noises of the engine. The processing module is further used to determine the rotational speed frequency corresponding to the noise reference signal of each order noise based on the noise reference signals of the multiple order noises, so as to determine multiple rotational speed frequencies. The processing module is further used to determine a target frequency less than a preset frequency threshold from the multiple rotational speed frequencies. The processing module is further used to determine a target noise reference signal corresponding to the target frequency from the noise reference signals of the multiple order noises.

[0013] In a possible implementation, the processing module is further used to collect the second anti-noise signal and the noise signal of the engine through a microphone. The processing module is further used to generate an error signal based on the second anti-noise signal and the noise signal of the engine. The processing module is further used to update the preset filter weight coefficient based on the error signal to obtain an updated preset filter weight coefficient.

[0014] In a possible implementation, the acquisition module is further configured to acquire a transfer function corresponding to a secondary channel, where the secondary channel is a channel between a speaker and a microphone. The processing module is further configured to obtain a second anti-noise signal based on the transfer function and the first anti-noise signal.

[0015] In a possible implementation, the acquisition module is also used to acquire a historical error signal, and one historical error signal corresponds to a historical preset filter weight coefficient. The processing module is also used to generate an objective function based on the historical error signal, the error signal, the weight coefficient of the historical error signal, and the weight coefficient of the error signal, and the weight coefficient is positively correlated with the number of times the preset filter weight coefficient is updated. The processing module is also used to process the objective function to obtain the objective function gradient, and the objective function gradient is used to indicate the partial derivative of the objective function with respect to the preset filter weight coefficient. The processing module is also used to update the weight coefficient based on the objective function gradient.

[0016] In a possible implementation manner, the target noise reference signal includes at least one of the following: a second-order noise reference signal and a fourth-order noise reference signal.

[0017] According to the third aspect provided by the present application, a vehicle is provided, comprising: a processor; a memory for storing processor executable instructions; wherein the processor is configured to execute instructions to implement the method of the above-mentioned first aspect and any possible implementation manner thereof.

[0018] According to the fourth aspect provided by the present application, a computer-readable storage medium is provided. When the instructions in the computer-readable storage medium are executed by the processor of the vehicle, the vehicle is enabled to execute the method in the above-mentioned first aspect and any possible implementation method thereof.

[0019] According to the fifth aspect provided by the present application, a computer program product is provided, the computer program product comprising computer instructions, and when the computer instructions are executed on a vehicle, the vehicle executes the method in the above-mentioned first aspect and any possible implementation manner thereof.

[0020] Therefore, the above technical features of the present application have the following beneficial effects:

[0021] (1) Obtaining a target noise reference signal of the target order noise of the engine. By obtaining the target noise reference signal of the target order, the frequency of the corresponding noise signal can be obtained. Since there are noise reference signals of multiple order noises, obtaining the target noise reference signal of the target order noise from multiple order noises can reduce the amount of calculation and improve the noise reduction effect. Afterwards, the target noise reference signal is subjected to FxRLS filtering based on a preset filtering weight coefficient to obtain a first anti-noise signal. Compared with other adaptive filtering algorithms, the FxRLS algorithm has a faster convergence speed and can effectively monitor the changes in the statistical characteristics of the target noise reference signal to ensure the stability and accuracy of the filtering effect. In this way, the first anti-noise signal obtained by the FxRLS algorithm can suppress noise more accurately and effectively. Then, the first anti-noise signal is issued. Since the first anti-noise and the noise signal have the same frequency and amplitude, but opposite phase, by issuing the first anti-noise signal, the noise generated when the engine is running can be offset and the noise of the vehicle can be reduced.

[0022] (2) By collecting the second anti-noise signal and the engine noise signal through the microphone, more accurate data can be obtained. Afterwards, an error signal is generated based on the second anti-noise signal and the engine noise signal. The error signal can reflect the degree of deviation between the actual noise reduction effect and the ideal noise reduction effect. The preset filter weight coefficient is updated based on the error signal to obtain an updated preset filter weight coefficient. By adjusting the preset filter weight coefficient, fine control of the filtering effect can be achieved. The anti-noise is calculated through the updated preset filter weight coefficient, which can achieve more accurate noise reduction. In this way, by monitoring the changes in the error signal in real time and automatically adjusting the noise reduction strategy and parameters, it is possible to more flexibly cope with various complex scenarios and noise environments to improve the noise reduction effect and user experience.

[0023] It should be noted that the technical effects brought about by any implementation method in the second to fifth aspects can refer to the technical effects brought about by the corresponding implementation method in the first aspect, and will not be repeated here.

[0024] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application, and do not constitute an improper limitation on the present application.

[0026] Figure 1 is a system architecture diagram of a noise reduction system for an engine according to an exemplary embodiment;

[0027] Figure 2 is a flow chart of a noise reduction method for an engine according to an exemplary embodiment;

[0028] Figure 3 is a flow chart of another engine noise reduction method according to an exemplary embodiment;

[0029] Figure 4 is a schematic structural diagram of a noise reduction device for an engine according to an exemplary embodiment;

[0030] Figure 5 It is a schematic structural diagram of another engine noise reduction device according to an exemplary embodiment. DETAILED DESCRIPTION

[0031] In order to enable ordinary persons in the art to better understand the technical solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0032] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims.

[0033] At present, new energy vehicles such as plug-in hybrid electric vehicles (PHEV), range extend electric vehicles (REEV), and hybrid electric vehicles (HEV) are increasing in the market, and the problem of high engine noise in new energy vehicles has also begun to emerge. The engine active noise cancellation (ANC) function, as a noise solution with digital and intelligent characteristics, has gradually become a standard technology for new energy vehicles.

[0034] Compared with traditional noise reduction technology, active noise reduction technology has a more obvious improvement on mid- and low-frequency noise. The principle of active noise reduction technology is to collect reference signals related to in-vehicle noise and engine speed through an electroacoustic system. After being processed by the noise reduction module, the speaker generates anti-noise with the same frequency and opposite phase as the noise, and the two cancel each other out to achieve a noise reduction effect.

[0035] At present, the filter-x least mean square (FxLMS) adaptive filtering algorithm has become the most commonly used algorithm in engine active noise reduction algorithms due to its simple implementation and small amount of calculation.

[0036] In some embodiments, the speed reference signal is normalized based on the FxLMS algorithm, which can effectively reduce the influence of reference signal fluctuations and the amount of processor calculation, and improve the convergence speed and stability of the active noise reduction method.

[0037] In some embodiments, the engine speed signal is smoothed to construct a more stable internal reference signal, which significantly improves the convergence performance and noise reduction performance of the FxLMS algorithm in the presence of engine speed fluctuations.

[0038] In some embodiments, the error noise signal at the actual installation position of the error microphone and the virtual microphone algorithm are used to fit the error noise signal near the ear of the occupant based on the FxLMS algorithm, thereby improving the ANC noise reduction effect and occupant comfort.

[0039] However, the FxLMS algorithm requires an adaptive operation process, so there is still much room for improvement in terms of transient characteristics, convergence speed, and steady-state error. Compared with the FxLMS algorithm, the filtered-x recursive least squares (FxRLS) algorithm has a faster convergence speed, is insensitive to the dispersion of the characteristic roots of the autocorrelation matrix of the reference signal, and has a small steady-state error. However, the FxRLS algorithm has a large amount of calculation. Therefore, it has high technical difficulty and hardware cost to implement it in engineering.

[0040] In order to solve the above problems, the present application provides a noise reduction method for an engine, the method comprising: obtaining a target noise reference signal of a target order noise of the engine. By obtaining the target noise reference signal of the target order, a frequency of a corresponding noise signal can be obtained. Since there are noise reference signals of multiple order noises, obtaining the target noise reference signal of the target order noise from multiple order noises can reduce the amount of calculation and improve the noise reduction effect. Afterwards, the target noise reference signal is subjected to FxRLS filtering based on a preset filtering weight coefficient to obtain a first anti-noise signal. Compared with other adaptive filtering algorithms, the FxRLS algorithm has a faster convergence speed and can effectively monitor the changes in the statistical characteristics of the target noise reference signal to ensure the stability and accuracy of the filtering effect. In this way, the first anti-noise signal obtained by the FxRLS algorithm can suppress noise more accurately and effectively. Then, the first anti-noise signal is issued. Since the first anti-noise has the same frequency and amplitude as the noise signal, but the phase is opposite, by issuing the first anti-noise signal, the noise generated when the engine rotates can be offset and the vehicle can be noise-reduced.

[0041] The embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0042] like Figure 1 , which is a system architecture diagram of an engine noise reduction system provided in an embodiment of the present application, the system includes: an input device, a control device and an output device.

[0043] The input device is used to obtain the engine speed signal and the engine noise signal, and send the first reference signal and the noise signal to the control device.

[0044] In one possible design, the input device includes a reference signal sensor, a controller area network (CAN) bus, and an error microphone. The reference signal sensor is used to measure the engine speed, convert the speed into a speed signal, and send the speed signal to the control device through the CAN bus. The error microphone is used to collect noise signals and anti-noise signals emitted by the system, and send the noise signals and anti-noise signals to the control device through the CAN bus. The CAN bus is used to obtain vehicle operation data and send the vehicle operation data to the control device. The vehicle operation data includes engine speed, vehicle speed, accelerator pedal position, gear position, window lifting status, and door switch status. The window lifting status is used to indicate that the vehicle window is in an up state or a down state, and the door switch status is used to indicate that the door is in an open state or a closed state.

[0045] In a possible design, the error microphone includes at least one. When the noise reduction system of the engine is not working, the error microphone is used to collect the noise signal of the engine; when the noise reduction system of the engine starts working, the error microphone is used to collect the error signal after the noise signal of the engine and the anti-noise signal emitted by the system are superimposed.

[0046] Exemplarily, there are four error microphones, which are respectively arranged at unobstructed locations near the handles on both sides of the front and rear roof of the vehicle.

[0047] The control device is used to receive the speed signal and the error signal sent by the input device, and calculate the preset filter weight coefficient and the speed signal to obtain the anti-noise signal. In addition, the control device is also used to update the preset filter weight coefficient through the speed signal and the error signal.

[0048] In one possible design, the control device includes a control algorithm, a microcontroller unit (MCU), a digital signal processor (DSP) chip, and a digital-to-analog converter. The MCU is used to receive the speed signal sent by the CAN bus, process the engine speed signal, and send it to the DSP chip. The DSP chip is used to calculate the processed speed signal and the preset filter weight coefficient through the control algorithm to obtain an anti-noise signal, and send it to the digital-to-analog converter. The DSP chip is also used to calculate the speed signal and the error signal through the control algorithm to update the preset filter weight coefficient. The digital-to-analog converter is used to process the anti-noise signal and send it to the output device.

[0049] In one possible design, the control algorithm includes an FxRLS algorithm.

[0050] The output device is used to receive the anti-noise signal sent by the control device and send out anti-noise to offset the noise inside the vehicle.

[0051] In one possible design, the output device includes a power amplifier and at least one speaker, the power amplifier is connected to the speaker. The power amplifier is used to amplify the power of the anti-noise signal processed by the digital-to-analog converter and output it through the speaker. The speaker is used to emit the anti-noise.

[0052] Exemplarily, there are four door speakers and one subwoofer. The four door speakers are respectively arranged on the inner sides of four vehicle doors, and the subwoofer is arranged in the trunk of the vehicle.

[0053] In some embodiments, the input device collects the noise signal (i.e., d(n)) in real time. The noise reduction system of the engine starts to work and performs the first noise reduction. The input device sends the speed signal (i.e., rpm(n)) to the control device. The control device generates the second-order and fourth-order sine and cosine reference signals (i.e., x) based on the speed signal. 11 (n), x 12 (n), x 21 (n), x 22 (n)). The control device controls the sine and cosine reference signals and the preset filter weight coefficients (i.e., w 11 (n), w 12 (n), w 21 (n), w 22 (n)) is calculated to obtain the initial first anti-noise signal (i.e., y1(n), y2(n)). The initial first anti-noise signal is accumulated to obtain the first anti-noise signal (i.e., y(n)), and sent to the output device. After that, the output device sends the first anti-noise signal. After the first anti-noise signal passes through the secondary channel (i.e., s(n)), the second anti-noise signal (i.e., y s (n)). The second anti-noise signal is superimposed on the noise signal to obtain an error signal (i.e., e(n)). The input device collects the error signal and sends it to the control device. Then, the noise reduction system of the engine performs a second noise reduction, and the input device sends the updated speed signal to the control device, which generates updated second-order and fourth-order sine and cosine reference signals. The control device calculates and updates the preset filter weight coefficient based on the FxRLS algorithm (i.e., F-xRLS in the figure), the error signal, and the updated sine and cosine reference signal to obtain an updated preset filter weight coefficient. In the calculation process, in order to simplify the formula, the filter reference signal is defined as X rf (n), ^

[0054] (i.e., the updated sine and cosine reference signals pass through H(z) and enter the F-xRLS algorithm). Afterwards, the control device calculates the updated sine and cosine reference signals and the updated preset filter weight coefficients to obtain an updated first anti-noise signal. After the updated first anti-noise signal passes through the secondary channel (i.e., s(n)), an updated second anti-noise signal (i.e., y s (n)). The updated second anti-noise signal is superimposed on the current noise signal to obtain an updated error signal. The input device collects the updated error signal and sends it to the control device. This cycle is repeated until the noise reduction system of the engine stops working and the noise reduction is completed.

[0055] For ease of understanding, the engine noise reduction method provided by the present application is specifically introduced below with reference to the accompanying drawings.

[0056] Figure 2 is a flow chart of a noise reduction method for an engine according to an exemplary embodiment. Figure 2 As shown, the noise reduction method of the engine includes:

[0057] S201 : Acquire a target noise reference signal of a target order noise of an engine.

[0058] In a possible implementation, the type, working mode and ignition strategy of the engine are obtained, and the ignition strategy of the engine is used to indicate the number of ignitions of the engine in one crankshaft rotation cycle (i.e., 360 degrees or one circle). The target order noise is obtained by order analysis. Order analysis is used to indicate the proportional relationship between the main frequency components of the engine vibration or noise and the speed by analyzing the type, working mode and ignition strategy of the engine.

[0059] It should be noted that in rotating machinery, the order refers to the proportional relationship between the frequency of vibration or noise and the rotation speed. For an engine, the proportional relationship between the main frequency components of the engine vibration or noise and the rotation speed can be obtained through the number of ignition times of the engine cylinders and the number of rotations of the crankshaft.

[0060] In some embodiments, the target noise reference signal includes at least one of the following: a second-order noise reference signal and a fourth-order noise reference signal.

[0061] In the embodiment of the present application, for a four-cylinder four-stroke engine, ignition is performed twice in one revolution, and a proportional relationship of 2:1 can be obtained between the main frequency component of vibration or noise and the rotation speed, so the target order is the second order.

[0062] It should be noted that in addition to the main second-order vibration, due to the combined effect of multiple factors such as imbalance between cylinders, dynamic effects of crankshafts and connecting rods, pulsation of intake and exhaust systems, and the response of engine mounting and supporting structures, significant fourth-order vibrations can also be generated. Although these fourth-order vibrations are not dominant vibrations, they may have a significant impact on the overall vibration and noise level of the engine in the event of a component failure in the engine. Therefore, the fourth order is also the target order.

[0063] In a possible implementation, the engine speed signal and the engine noise are obtained. The noise is subjected to spectrum analysis to obtain the sound pressure levels of multiple order noises. The sound pressure levels of multiple order noises are compared, and the order noise that meets the preset conditions is determined as the target order noise. Afterwards, the corresponding sine speed signal or cosine speed signal is generated as the target noise reference signal through the speed signal corresponding to the target order noise.

[0064] In a possible design, the preset condition may be that the sound pressure level of the noise of multiple orders is the largest, or the preset condition is that the sound pressure level of the order noise is greater than a preset sound pressure value.

[0065] It should be noted that the present application does not limit the preset sound pressure value. For example, the preset sound pressure value may be 80, 85, 90, 95, or 100.

[0066] In another possible implementation, noise reference signals of multiple order noises of the engine are obtained. Based on the noise reference signals of the multiple order noises, a rotational speed frequency corresponding to the noise reference signal of each order noise is determined to determine multiple rotational speed frequencies. A target frequency less than a preset frequency threshold is determined from the multiple rotational speed frequencies. A target noise reference signal corresponding to the target frequency is determined from the noise reference signals of the multiple order noises.

[0067] In a possible design, the noise signal is preprocessed so that the noise signal and the rotation speed signal are synchronized in time. After that, the preprocessed noise information is subjected to spectrum analysis to obtain the rotation speed frequency related to the rotation speed signal.

[0068] It should be noted that the present application does not limit the preset frequency threshold. For example, the preset frequency threshold may be 80, 100, 150, 250, or 500.

[0069] In another possible implementation, the speed signal is filtered and the noise spectrum is obtained by Fourier transform. Then, the energy spectrum of different frequency components is calculated to determine the frequency with the largest energy in the speed signal, and the significant peak in the energy spectrum is obtained by the peak detection algorithm to obtain the frequency of the target order noise. Based on the frequency of the target order noise, the target noise reference signal is obtained.

[0070] Exemplarily, the target noise reference signal X(n)=[x 2sin (n),x 2cos (n),x 4sin (x),x 4cos (n)] where x 2sin (n) = sin[2*x(n) / 60] is the second-order noise sinusoidal reference signal, x 2cos (n) = cos[2*x(n) / 60] is the second-order noise cosine reference signal, x 4sin (n) = sin[4*x(n) / 60] is the fourth-order noise sinusoidal reference signal, x 4cos (n)=cos[4*x(n) / 60] is the fourth-order noise cosine reference signal.

[0071] S202 . Perform FxRLS filtering on the target noise reference signal based on a preset filtering weight coefficient to obtain a first anti-noise signal.

[0072] The preset filtering weight coefficient is used to adjust the first anti-noise signal, and the first anti-noise signal is used to offset the noise generated when the engine rotates.

[0073] In a possible implementation manner, the target noise reference signal is convolved with a preset filtering weight coefficient to obtain a first anti-noise signal.

[0074] In some embodiments, the preset filtering weight coefficient of the target noise reference signal to the speaker is initially zero, and then the preset filtering weight coefficient is updated by the FxRLS algorithm to obtain an updated preset filtering weight coefficient, and the target noise reference signal is convolved with the preset filtering weight coefficient to obtain an updated first anti-noise signal.

[0075] Exemplarily, the first anti-noise signal may satisfy Formula 1.

[0076] y(n)=X(n)*W(n) Formula 1.

[0077] Wherein, y(n) is used to represent the first anti-noise signal, X(n) is used to represent the target noise reference signal, and W(n) is used to represent the preset filter weight coefficient.

[0078] S203: Send a first anti-noise signal.

[0079] In a possible implementation, after the first anti-noise signal is obtained, the first anti-noise signal is sent to a speaker to drive the speaker to emit the first anti-noise signal.

[0080] Based on the above technical solution, a target noise reference signal of the target order noise of the engine is obtained. By obtaining the target noise reference signal of the target order, the frequency of the corresponding noise signal can be obtained. Since there are noise reference signals of multiple order noises, obtaining the target noise reference signal of the target order noise from multiple order noises can reduce the amount of calculation and improve the noise reduction effect. Afterwards, the target noise reference signal is subjected to FxRLS filtering based on a preset filtering weight coefficient to obtain a first anti-noise signal. Compared with other adaptive filtering algorithms, the FxRLS algorithm has a faster convergence speed and can effectively monitor the changes in the statistical characteristics of the target noise reference signal to ensure the stability and accuracy of the filtering effect. In this way, the first anti-noise signal obtained by the FxRLS algorithm can suppress noise more accurately and effectively. Then, the first anti-noise signal is issued. Since the first anti-noise has the same frequency and amplitude as the noise signal, but the phase is opposite, by issuing the first anti-noise signal, the noise generated when the engine rotates can be offset and the vehicle can be noise-reduced.

[0081] Figure 3 is a flow chart of a noise reduction method for an engine according to an exemplary embodiment. Figure 3 As shown, in the noise reduction method of the engine, in S202, the target noise reference signal is subjected to FxRLS filtering based on a preset filtering weight coefficient, and further includes:

[0082] S301 . Collect a second anti-noise signal and an engine noise signal through a microphone.

[0083] In a possible implementation, a transfer function corresponding to a secondary channel is obtained, where the secondary channel is a channel between a loudspeaker and a microphone. Then, a second anti-noise signal is obtained based on the transfer function and the first anti-noise signal.

[0084] It should be noted that after the first anti-noise signal is processed by the circuit, the digital-to-analog conversion, the sound power amplifier, the speaker, and the sound field space will change, and the transfer function is used to describe the change of the first anti-noise in the sound field space.

[0085] Exemplarily, the second anti-noise signal may satisfy Formula 2.

[0086]

[0087] Among them, y s (n) is the second anti-noise signal, Y(n) is the set of all first anti-noise vectors from the previous M times to the current time, S is the transfer function, which is a set of M transfer coefficients, S = [s0, s1, ..., s M-1 ]. M is the filter order of the secondary channel transfer function.

[0088] S302: Generate an error signal based on the second anti-noise signal and the noise signal of the engine.

[0089] In a possible implementation, the second anti-noise signal is compared and superimposed with the noise signal of the engine to generate an error signal.

[0090] It can be understood that the error signal is the actual sound generated in the vehicle after the second anti-noise signal and the engine noise signal are compared and superimposed. The smaller the error noise, the better the noise reduction effect.

[0091] Exemplarily, the error signal may satisfy Formula 3.

[0092] e(n)=d(n)-y s (n) Formula 3.

[0093] Among them, e(n) is the error signal and d(n) is the noise signal of the engine.

[0094] S303 . Update the preset filtering weight coefficient based on the error signal to obtain an updated preset filtering weight coefficient.

[0095] In a possible implementation, a historical error signal is obtained, and one historical error signal corresponds to a historical preset filter weight coefficient. Based on the historical error signal, the error signal, the weight coefficient of the historical error signal, and the weight coefficient of the error signal, an objective function is generated, and the weight coefficient is positively correlated with the number of times the preset filter weight coefficient is updated. The objective function is processed to obtain an objective function gradient, and the objective function gradient is used to indicate the partial derivative of the objective function with respect to the preset filter weight coefficient. Based on the objective function gradient, the weight coefficient is updated.

[0096] Exemplarily, the objective function may satisfy Formula 4.

[0097]

[0098] Where J(n) is the objective function, λ is the weight coefficient of the historical error signal, and e(i) is the error signal of the i-th time.

[0099] Exemplarily, the objective function gradient may satisfy Formula 5.

[0100]

[0101] in, is the objective function gradient, d(i) is the noise signal of the ith time, X(n-m+1) is the target noise reference signal of the n-m+1th time, and W(n-m+1) is the preset filter weight coefficient of the n-m+1th time.

[0102] Define the filtering reference signal as

[0103] X rf (i) Substitute into formula 5 to obtain

[0104] in, For X rf The transposed matrix of (i).

[0105] Let formula 6 be equal to zero, then So we can get

[0106] make According to the matrix inversion lemma, we can get formula 9.

[0107]

[0108] Among them, R -1 (n) is the inverse matrix of R(n).

[0109] Expand Formula 9 to obtain Formula 10.

[0110]

[0111] Substituting formula 7, formula 8, and formula 9 into formula 10, the iterative formula of the preset filter weight coefficient W(n) can be obtained: W(n) = W(n-1) + e(n-1) * R -1 (n)*X rf (n) Formula XI.

[0112] Among them, W(n) represents the updated weight coefficient, and W(n-1) represents the weight coefficient of the previous iteration.

[0113] Based on the above technical solution, more accurate data can be obtained by collecting the second anti-noise signal and the noise signal of the engine through a microphone. Afterwards, an error signal is generated based on the second anti-noise signal and the noise signal of the engine. The error signal can reflect the degree of deviation between the actual noise reduction effect and the ideal noise reduction effect. The preset filter weight coefficient is updated based on the error signal to obtain an updated preset filter weight coefficient. By adjusting the preset filter weight coefficient, fine control of the filtering effect can be achieved. The anti-noise is calculated through the updated preset filter weight coefficient, which can achieve more accurate noise reduction. In this way, by monitoring the changes in the error signal in real time and automatically adjusting the noise reduction strategy and parameters, it is possible to more flexibly cope with various complex scenarios and noise environments to improve the noise reduction effect and user experience.

[0114] The above mainly introduces the solution provided by the embodiment of the present application from the perspective of the method. In order to achieve the above functions, the noise reduction device of the engine includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0115] The embodiment of the present application can divide the noise reduction device of the engine into functional modules according to the above method. For example, the noise reduction device of the engine can include various functional modules corresponding to the various functional divisions, or two or more functions can be integrated into one processing module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiment of the present application is schematic and is only a logical functional division. There may be other division methods in actual implementation.

[0116] Figure 4 is a schematic diagram of the structure of a noise reduction device for an engine according to an exemplary embodiment. Figure 4 The engine noise reduction device includes an acquisition module 401 and a processing module 402.

[0117] The acquisition module 401 is used to acquire a target noise reference signal of a target order noise of the engine.

[0118] The processing module 402 is used to perform FxRLS filtering on the target noise reference signal based on a preset filtering weight coefficient to obtain a first anti-noise signal, which is used to offset the noise generated when the engine rotates. It is also used to send the first anti-noise signal.

[0119] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0120] Figure 5 FIG. 1 is a schematic diagram of a vehicle structure according to an exemplary embodiment. Figure 5 As shown, the vehicle includes, but is not limited to: a processor 501 and a memory 502 .

[0121] The memory 502 is used to store executable instructions of the processor 501. It can be understood that the processor 501 is configured to execute instructions to implement the engine noise reduction method in the above embodiment.

[0122] It should be noted that those skilled in the art can understand that Figure 5 The vehicle structure shown in the figure does not constitute a limitation on the vehicle, and the vehicle may include Figure 5 More or fewer components may be shown, or certain components may be combined, or the components may be arranged differently.

[0123] The processor 501 is the control center of the vehicle, which uses various interfaces and lines to connect various parts of the entire vehicle, and executes various functions of the vehicle and processes data by running or executing software programs and / or modules stored in the memory 502, and calling data stored in the memory 502, so as to monitor the vehicle as a whole. The processor 501 may include one or more processing units. Optionally, the processor 501 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 501.

[0124] The memory 502 can be used to store software programs and various data. The memory 502 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application program required by at least one functional module (such as a determination unit, a processing unit, etc.), etc. In addition, the memory 502 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0125] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory 502 including instructions, and the above instructions can be executed by a processor 501 of a vehicle to implement the method in the above embodiment.

[0126] In actual implementation, Figure 4 The functions of the acquisition module 401 and the processing module 402 in Figure 5 The processor 501 in the embodiment calls the computer program stored in the memory 502. The specific execution process can refer to the description of the method part in the above embodiment, which will not be repeated here.

[0127] Optionally, the computer-readable storage medium may be a non-temporary computer-readable storage medium, for example, the non-temporary computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0128] In an exemplary embodiment, the present application also provides a computer program product including one or more instructions, which can be executed by the processor 501 of the vehicle to complete the method in the above embodiment.

[0129] It should be noted that when the instructions in the above-mentioned computer-readable storage medium or one or more instructions in the computer program product are executed by the vehicle's processor, the various processes of the above-mentioned method embodiment are implemented, and the same technical effect as the above-mentioned method can be achieved. To avoid repetition, they will not be repeated here.

[0130] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0131] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0132] The units described as separate components may or may not be physically separated, and the components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0133] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0134] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or the full classification part or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium, including a number of instructions to enable a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to execute the full classification part or part of the steps of each embodiment method of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, ROM, RAM, disk or CD and other media that can store program code.

[0135] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto, and any changes or substitutions within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for reducing noise of an engine, characterized in that: The method comprises: Acquire a target noise reference signal of a target order noise of the engine; Performing FxRLS filtering on the target noise reference signal based on a preset filtering weight coefficient to obtain a first anti-noise signal, wherein the first anti-noise signal is used to offset the noise generated when the engine rotates; The first anti-noise signal is issued.

2. The method according to claim 1, characterized in that Obtaining a target noise reference signal of a target order noise of the engine, including: Acquire noise reference signals of multiple orders of noise of the engine; Based on the noise reference signals of the multiple order noises, determining the rotational speed frequency corresponding to the noise reference signal of each order noise to determine multiple rotational speed frequencies; Determining a target frequency that is less than a preset frequency threshold from the plurality of rotational speed frequencies; The target noise reference signal corresponding to the target frequency is determined from the noise reference signals of the multiple noise orders.

3. The method according to claim 1, characterized in that Applied to a vehicle, the vehicle includes a microphone and a speaker, the speaker is used to send the first anti-noise signal; the method also includes: collecting a second anti-noise signal and a noise signal of the engine through the microphone; generating an error signal based on the second anti-noise signal and a noise signal of the engine; The preset filtering weight coefficient is updated based on the error signal to obtain an updated preset filtering weight coefficient.

4. The method according to claim 3, characterized in that Collecting a second anti-noise signal through the microphone includes: Obtaining a transfer function corresponding to a secondary channel, where the secondary channel is a channel between the speaker and the microphone; The second anti-noise signal is obtained based on the transfer function and the first anti-noise signal.

5. The method according to claim 3, characterized in that: The updating of the preset filtering weight coefficient based on the error signal to obtain the updated preset filtering weight coefficient includes: Obtaining a historical error signal, where one historical error signal corresponds to a historical preset filtering weight coefficient; generating an objective function based on the historical error signal, the error signal, a weight coefficient of the historical error signal, and a weight coefficient of the error signal, wherein the weight coefficient is positively correlated with the number of times the preset filter weight coefficient is updated; Taking partial derivative of the objective function with respect to the preset filter weight coefficient, to obtain the objective function gradient; Based on the objective function gradient, the weight coefficient is updated.

6. The method according to any one of claims 1 to 5, characterized in that The target noise reference signal includes at least one of the following: a second-order noise reference signal and a fourth-order noise reference signal.

7. A noise reduction device for an engine, characterized in that: The device comprises an acquisition module and a processing module; The acquisition module is used to acquire a target noise reference signal of a target order noise of the engine; The processing module is used to perform FxRLS filtering on the target noise reference signal based on a preset filtering weight coefficient to obtain a first anti-noise signal, wherein the first anti-noise signal is used to offset the noise generated when the engine rotates; The processing module is further configured to send the first anti-noise signal.

8. A vehicle, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: When the computer-executable instructions stored in the computer-readable storage medium are executed by a processor of a vehicle, the vehicle is capable of performing the method of any one of claims 1 to 6.

10. A computer program product, characterized in that The computer program product comprises computer instructions which, when executed on a vehicle, enable the vehicle to perform the method according to any one of claims 1 to 6.

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