A method and system for active noise reduction in automobiles under acceleration conditions

Abstract

This invention provides a method and system for active noise reduction in automobiles under acceleration conditions. The method includes analyzing noise data and designing a muffler to obtain an air intake muffler for initial noise reduction; decomposing the vehicle noise to obtain main noise data and single-frequency noise data; updating the weights of a first initial filter based on the main noise data, and performing noise reduction filtering on the main noise data based on the first updated filter; updating the weights of a second initial filter based on the single-frequency noise data to obtain a second updated filter, and performing noise reduction filtering on the single-frequency noise data based on the second updated filter to complete active noise reduction in automobiles under acceleration conditions. This invention can reduce different types of noise, thereby improving driving comfort.

Description

Technical Field

[0001] This invention belongs to the technical field of automotive noise reduction, specifically relating to an active noise reduction method and system for automobiles under acceleration conditions. Background Technology

[0002] During the driving process, the vehicle's parts, the road surface, the vehicle speed, and other external factors can cause the driver to experience significant noise, especially during acceleration. This noise can create a booming sensation inside the vehicle, thus affecting the driver's driving experience and comfort. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention provides a method and system for active noise reduction in automobiles under acceleration conditions, which solves the technical problems in the prior art.

[0004] On the one hand, the present invention provides the following technical solution: a method for active noise reduction in automobiles under acceleration conditions, comprising:

[0005] Noise data of the air intake and the interior of the vehicle under acceleration conditions are obtained, and the noise data is analyzed and a muffler is designed to obtain an air intake muffler. The vehicle is then subjected to the first noise reduction based on the air intake muffler.

[0006] The vehicle noise after the first noise reduction is collected, and the vehicle noise is decomposed to obtain the main noise data and single-frequency noise data;

[0007] A first initial filter is constructed, and the weights of the first initial filter are updated based on the main noise data to obtain a first updated filter. The main noise data is then subjected to noise reduction filtering based on the first updated filter.

[0008] A second initial filter is constructed, and the weights of the second initial filter are updated based on the single-frequency noise data to obtain a second updated filter. The single-frequency noise data is then subjected to noise reduction filtering based on the second updated filter to complete the active noise reduction of the vehicle under acceleration conditions.

[0009] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention first acquires noise data of the air intake and interior of the vehicle under acceleration conditions, analyzes the noise data and designs a muffler to obtain an air intake muffler, and performs the first noise reduction on the vehicle based on the air intake muffler; then, it collects the vehicle noise after the first noise reduction, decomposes the vehicle noise to obtain main noise data and single-frequency noise data; then, it constructs a first initial filter, updates the weights of the first initial filter based on the main noise data to obtain a first updated filter, and performs noise reduction filtering on the main noise data based on the first updated filter; finally, it constructs a second initial filter, updates the weights of the second initial filter based on the single-frequency noise data to obtain a second updated filter, and performs noise reduction filtering on the single-frequency noise data based on the second updated filter, thereby completing the active noise reduction of the vehicle under acceleration conditions. This invention uses noise data of the vehicle under acceleration conditions and a muffler to perform the first noise reduction, then classifies the noise and uses ANC active noise cancellation technology to reduce different types of noise, thereby improving driving comfort.

[0010] Preferably, the step of analyzing the noise data and designing the muffler to obtain the air intake muffler includes:

[0011] Perform spectral analysis on the noise data to obtain the main frequency bands corresponding to the noise data;

[0012] The initial silencer for the corresponding frequency band is determined based on the main frequency band;

[0013] Calculate the sound transmission loss of the initial muffler. :

[0014] ;

[0015] In the formula, This represents the initial inlet area of ​​the muffler. This represents the initial outlet area of ​​the muffler. For the output sound pressure, The entrance sound pressure level, For the speed of sound, The velocity of the particle vibration;

[0016] Determine the sound transmission loss of the initial muffler Does it meet the preset range? If the initial sound transmission loss of the muffler... If the parameters do not meet the preset range, the parameters of the initial muffler are adjusted, and the loss calculation and parameter adjustment are performed cyclically to output the air inlet muffler.

[0017] Preferably, the step of constructing a first initial filter and updating the weights of the first initial filter based on the main noise data to obtain a first updated filter includes:

[0018] Construct a first initial filter, and calculate the secondary signal of the first initial filter based on the first initial filter and the main noise data. :

[0019] ;

[0020] In the formula, This represents the initial weight vector of the first initial filter. A vector representing the main noise data;

[0021] Calculate the Gaussian white noise signal based on the main noise data. :

[0022] ;

[0023] In the formula, This represents the impulse response of the first initial filter;

[0024] Calculate the update factor :

[0025] ;

[0026] In the formula, Indicates the initial update factor. Indicates parameter adjustment;

[0027] Based on the secondary signal The Gaussian white noise signal Calculate the error signal of the first initial filter :

[0028] ;

[0029] In the formula, , These represent the channel parameters of the primary and secondary channels of the first initial filter, respectively. express The signal output after filtering by the first initial filter;

[0030] Based on update factor With error signal Determine the first iteration formula and the second iteration formula, and determine the first update filter based on the first iteration formula and the second iteration formula.

[0031] Preferably, the update factor-based With error signal The steps for determining the first iteration formula and the second iteration formula, and then determining the first update filter based on the first iteration formula and the second iteration formula, include:

[0032] Based on the update factor With error signal Determine the formula for the first iteration:

[0033] ;

[0034] In the formula, Indicates the first The weight vector of the first initial filter after the next iteration;

[0035] Based on the update factor With error signal Determine the formula for the second iteration:

[0036] ;

[0037] In the formula, Indicates the first The impulse response of the first initial filter after the next iteration;

[0038] The weights of the first initial filter are updated based on the first iteration formula and the second iteration formula until the first iteration termination condition is met, so as to obtain the first updated filter.

[0039] Preferably, the step of updating the weights of the second initial filter based on the single-frequency noise data to obtain the second updated filter includes:

[0040] Calculate the output signal of the second initial filter. :

[0041] ;

[0042] In the formula, This represents the weights of the second initial filter. This represents single-frequency noise data. This represents the channel parameters of the secondary channel of the second initial filter. Indicates the iteration step size;

[0043] Calculate the total error between the first updated filter and the second initial filter. :

[0044] ;

[0045] In the formula, This represents the interference signal corresponding to the main noise data. Indicates the first The interference signal corresponding to the single-frequency noise data, Indicates the type of single-frequency noise data. This represents the output signal of the first update filter. Indicates the first The output signal after inputting single-frequency noise data into the second initial filter;

[0046] Based on the total error Determine the formula for the third iteration;

[0047] The additional filter is determined based on the third iteration formula, and the second update filter is determined based on the additional filter.

[0048] Preferably, the statement based on the total error The steps to determine the third iteration formula include:

[0049] Calculate the first iteration factor With the second iteration factor :

[0050] ; ;

[0051] In the formula, , , These are the first, second, and third adjustable parameters, respectively. Indicates the first The total error after the nth iteration;

[0052] Based on the first iteration factor With the second iteration factor Calculate iteration coefficients :

[0053] ;

[0054] In the formula, This is the fourth adjustable parameter;

[0055] Based on iteration coefficients Determine the formula for the third iteration:

[0056] ;

[0057] In the formula, , They represent the first , The weights of the second initial filter after the next iteration. Indicates the first The reference signal corresponding to the single-frequency noise data after the next iteration.

[0058] Preferably, the step of determining the additional filter based on the third iterative formula and determining the second updated filter based on the additional filter includes:

[0059] The weights of the second initial filter are updated based on the third iterative formula until the second iteration termination condition is met, so as to obtain the second undetermined update filter.

[0060] Determine additional filters based on the second undetermined update filter. :

[0061] ;

[0062] In the formula, , These represent the virtual secondary channel and virtual primary channel of the second undetermined update filter, respectively. , These represent the physical secondary channel and physical primary channel of the second undetermined update filter, respectively.

[0063] Based on additional filters Determine the second update filter with the second pending update filter. :

[0064] .

[0065] Secondly, the present invention provides the following technical solution: an active noise reduction system for automobiles under acceleration conditions, the system comprising:

[0066] The first noise reduction module is used to acquire noise data of the car's air intake and interior, analyze the noise data and design a muffler to obtain an air intake muffler, and perform the first noise reduction on the car based on the air intake muffler.

[0067] The decomposition module is used to collect the car noise after the first noise reduction, and decompose the car noise to obtain the main noise data and single-frequency noise data.

[0068] The second noise reduction module is used to construct a first initial filter, update the weights of the first initial filter based on the main noise data to obtain a first updated filter, and perform noise reduction filtering on the main noise data based on the first updated filter.

[0069] The third noise reduction module is used to construct a second initial filter, update the weights of the second initial filter based on the single-frequency noise data to obtain a second updated filter, and perform noise reduction filtering on the single-frequency noise data based on the second updated filter to complete the active noise reduction of the vehicle under acceleration conditions.

[0070] Thirdly, the present invention provides the following technical solution: a computer, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described active noise reduction method for automobiles under acceleration conditions.

[0071] Fourthly, the present invention provides the following technical solution: a storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the above-described active noise reduction method for automobiles under acceleration conditions. Attached Figure Description

[0072] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0073] Figure 1 This is a flowchart of the active noise reduction method for automobiles under acceleration conditions provided in Embodiment 1 of the present invention;

[0074] Figure 2 This is a structural block diagram of the active noise reduction system for automobiles under acceleration conditions provided in Embodiment 2 of the present invention;

[0075] Figure 3 This is a schematic diagram of the hardware structure of a computer provided for another embodiment of the present invention.

[0076] The embodiments of the present invention will be further described below with reference to the accompanying drawings. Detailed Implementation

[0077] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain embodiments of the present invention, and should not be construed as limiting the present invention.

[0078] In the description of the embodiments of the present invention, it should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the embodiments of the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the present invention.

[0079] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of embodiments of the present invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0080] In the embodiments of the present invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of the present invention according to the specific circumstances.

[0081] Example 1

[0082] In Embodiment 1 of the present invention, as Figure 1 As shown, an active noise reduction method for automobiles under acceleration conditions includes:

[0083] S1. Obtain noise data of the air intake and the interior of the vehicle under acceleration conditions, analyze the noise data and design a muffler to obtain an air intake muffler, and perform the first noise reduction on the vehicle based on the air intake muffler.

[0084] Specifically, when a car is accelerating, the radiated noise from its intake system is generally quite high. Therefore, installing a muffler at the car's intake system can reduce the radiated noise.

[0085] Step S1 includes:

[0086] S11. Perform spectral analysis on the noise data to obtain the main frequency bands corresponding to the noise data;

[0087] Specifically, noise data can be collected by installing sound pressure sensors at the vehicle's air intake, various parts of the vehicle body, and near the driver's ears.

[0088] S12. Determine the initial silencer for the corresponding frequency band based on the main frequency band;

[0089] Specifically, the initial muffler can be a resistive muffler, an impedance composite muffler, a reactive muffler, etc., and this type of muffler is commonly used in the field of automotive noise reduction, so it will not be elaborated on again.

[0090] S13. Calculate the sound transmission loss of the initial silencer. :

[0091] ;

[0092] In the formula, This represents the initial inlet area of ​​the muffler. This represents the initial outlet area of ​​the muffler. For the output sound pressure, The entrance sound pressure level, For the speed of sound, The velocity of the particle is denoted as .

[0093] S14. Determine the sound transmission loss of the initial muffler. Does it meet the preset range? If the initial sound transmission loss of the muffler... If the parameters of the initial muffler are not within the preset range, the loss calculation and parameter adjustment are performed repeatedly, and the air inlet muffler is output.

[0094] Specifically, when the initial muffler's sound transmission loss When the sound transmission loss of the initial muffler meets the preset range, the initial muffler can achieve the sound reduction requirement. If the parameters do not meet the preset range, the initial silencer parameters need to be adjusted, such as the area of ​​the inlet and outlet, the size of the cavity, the silencer material, etc.

[0095] S2. Collect the car noise after the first noise reduction, and decompose the car noise to obtain the main noise data and single-frequency noise data.

[0096] Specifically, after collecting vehicle noise data, since the types of noise are different, they can include wind noise, tire noise, engine noise, vibration noise of vehicle parts, interior noise, etc. The noise can be decomposed according to the acoustic characteristics of different noises to obtain main noise data and single-frequency noise data. The main noise data mainly refers to the main noise components such as engine noise and wind noise, while the single-frequency noise data includes secondary noise components such as vibration noise of vehicle parts and interior noise.

[0097] S3. Construct a first initial filter, update the weights of the first initial filter based on the main noise data to obtain a first updated filter, and perform noise reduction filtering on the main noise data based on the first updated filter.

[0098] Step S3 includes:

[0099] S31. Construct a first initial filter, and calculate the secondary signal of the first initial filter based on the first initial filter and the main noise data. :

[0100] ;

[0101] In the formula, This represents the initial weight vector of the first initial filter. This represents a vector composed of the main noise data.

[0102] S32. Calculate the Gaussian white noise signal based on the main noise data. :

[0103] ;

[0104] In the formula, This represents the impulse response of the first initial filter.

[0105] S33, Calculate the update factor :

[0106] ;

[0107] In the formula, Indicates the initial update factor. This indicates that the parameters are being adjusted.

[0108] S34, Based on the secondary signal The Gaussian white noise signal Calculate the error signal of the first initial filter :

[0109] ;

[0110] In the formula, , These represent the channel parameters of the primary and secondary channels of the first initial filter, respectively. express The signal output after being filtered by the first initial filter.

[0111] S35, Based on Update Factor With error signal Determine the first iteration formula and the second iteration formula, and determine the first update filter based on the first iteration formula and the second iteration formula;

[0112] Step S35 includes:

[0113] S351, Based on the update factor With error signal Determine the formula for the first iteration:

[0114] ;

[0115] In the formula, Indicates the first The weight vector of the first initial filter after the next iteration.

[0116] S352, Based on the update factor With error signal Determine the formula for the second iteration:

[0117] ;

[0118] In the formula, Indicates the first The impulse response of the first initial filter after the next iteration.

[0119] S353. The weights of the first initial filter are updated based on the first iteration formula and the second iteration formula until the first iteration termination condition is met, so as to obtain the first updated filter.

[0120] Specifically, the first noise reduction process is completed through the ANC active noise cancellation system, in which... Specifically, it refers to the number of iterations, and the termination condition for the first iteration is the error signal. Once the minimum value is reached or the iteration reaches a certain point, it stops changing.

[0121] S4. Construct a second initial filter, update the weights of the second initial filter based on the single-frequency noise data to obtain a second updated filter, and perform noise reduction filtering on the single-frequency noise data based on the second updated filter to complete the active noise reduction of the vehicle under acceleration conditions.

[0122] Step S4 includes:

[0123] S41. Calculate the output signal of the second initial filter. :

[0124] ;

[0125] In the formula, This represents the weights of the second initial filter. This represents single-frequency noise data. This represents the channel parameters of the secondary channel of the second initial filter. This indicates the iteration step size.

[0126] S42. Calculate the total error between the first updated filter and the second initial filter. :

[0127] ;

[0128] In the formula, This represents the interference signal corresponding to the main noise data. Indicates the first The interference signal corresponding to the single-frequency noise data, Indicates the type of single-frequency noise data. This represents the output signal of the first update filter. Indicates the first The output signal after inputting single-frequency noise data into the second initial filter.

[0129] S43, Based on the total error Determine the formula for the third iteration;

[0130] Step S43 includes:

[0131] S431. Calculate the first iteration factor. With the second iteration factor :

[0132] ; ;

[0133] In the formula, , , These are the first, second, and third adjustable parameters, respectively. Indicates the first The total error after the nth iteration;

[0134] S432, Based on the first iteration factor With the second iteration factor Calculate iteration coefficients :

[0135] ;

[0136] In the formula, This is the fourth adjustable parameter;

[0137] Specifically, in this embodiment, the first, second, third, and fourth adjustable parameters are 1, 0.5, 0.1, and 0.1, respectively.

[0138] S433, Based on Iteration Coefficients Determine the formula for the third iteration:

[0139] ;

[0140] In the formula, , They represent the first , The weights of the second initial filter after the next iteration. Indicates the first The reference signal corresponding to the single-frequency noise data after the next iteration.

[0141] S44. Determine the additional filter based on the third iteration formula, and determine the second update filter based on the additional filter;

[0142] Step S44 includes:

[0143] S441. The weights of the second initial filter are updated based on the third iterative formula until the second iteration termination condition is met, so as to obtain the second undetermined update filter.

[0144] Specifically, the termination condition for the second iteration is that the total error is minimized or the total error no longer changes after a certain number of iterations.

[0145] S442. Determine additional filters based on the second pending update filter. :

[0146] ;

[0147] In the formula, , These represent the virtual secondary channel and virtual primary channel of the second undetermined update filter, respectively. , These represent the physical secondary channel and physical primary channel of the second undetermined update filter, respectively.

[0148] Specifically, the second initial filter needs to go through a training and actual noise reduction process. During the training process, it is regarded as using a virtual sensor to collect single-frequency noise data. Therefore, when determining the final second update filter, it is necessary to determine an additional filter and convert it into data collected by the physical sensor through the additional filter, so as to obtain the corresponding physical second update filter.

[0149] S443, based on additional filters Determine the second update filter with the second pending update filter. :

[0150] .

[0151] The active noise reduction method for automobiles under acceleration conditions provided in Embodiment 1 of this invention first acquires noise data from the air intake and interior of the vehicle under acceleration conditions. The noise data is analyzed and a muffler is designed to obtain an air intake muffler. The vehicle undergoes its first noise reduction based on the air intake muffler. Then, the vehicle noise after the first noise reduction is collected and decomposed to obtain main noise data and single-frequency noise data. Next, a first initial filter is constructed, and its weights are updated based on the main noise data to obtain a first updated filter. The main noise data is then subjected to noise reduction filtering based on the first updated filter. Finally, a second initial filter is constructed, and its weights are updated based on the single-frequency noise data to obtain a second updated filter. The single-frequency noise data is then subjected to noise reduction filtering based on the second updated filter to complete the active noise reduction for automobiles under acceleration conditions. This invention uses noise data from automobiles under acceleration conditions and employs a muffler for the first noise reduction, then classifies the noise and uses Active Noise Cancellation (ANC) technology to reduce different types of noise, thereby improving driving comfort.

[0152] Example 2

[0153] like Figure 2 As shown, in Embodiment 2 of the present invention, an active noise reduction system for automobiles under acceleration conditions is provided. The system includes:

[0154] The first noise reduction module 1 is used to acquire noise data of the car's air intake and the interior of the car, analyze the noise data and design a muffler to obtain an air intake muffler, and perform the first noise reduction on the car based on the air intake muffler.

[0155] Decomposition module 2 is used to collect the car noise after the first noise reduction, and decompose the car noise to obtain the main noise data and single-frequency noise data.

[0156] The second noise reduction module 3 is used to construct a first initial filter, update the weights of the first initial filter based on the main noise data to obtain a first updated filter, and perform noise reduction filtering on the main noise data based on the first updated filter.

[0157] The third noise reduction module 4 is used to construct a second initial filter, update the weights of the second initial filter based on the single-frequency noise data to obtain a second updated filter, and perform noise reduction filtering on the single-frequency noise data based on the second updated filter to complete the active noise reduction of the vehicle under acceleration conditions.

[0158] The first noise reduction module 1 includes:

[0159] The analysis submodule is used to perform spectral analysis on the noise data to obtain the main frequency bands corresponding to the noise data;

[0160] A muffler determination submodule is used to determine the initial muffler for the corresponding frequency band based on the main frequency band.

[0161] The loss submodule is used to calculate the sound transmission loss of the initial muffler. :

[0162] ;

[0163] In the formula, This represents the initial inlet area of ​​the muffler. This represents the initial outlet area of ​​the muffler. For the output sound pressure, The entrance sound pressure level, For the speed of sound, The velocity of the particle vibration;

[0164] The adjustment submodule is used to determine the initial sound transmission loss of the muffler. Does it meet the preset range? If the initial sound transmission loss of the muffler... If the parameters do not meet the preset range, the parameters of the initial muffler are adjusted, and the loss calculation and parameter adjustment are performed cyclically to output the air inlet muffler.

[0165] The second noise reduction module 3 includes:

[0166] The first construction submodule is used to construct a first initial filter and calculate the secondary signal of the first initial filter based on the first initial filter and the main noise data. :

[0167] ;

[0168] In the formula, This represents the initial weight vector of the first initial filter. A vector representing the main noise data;

[0169] The first calculation submodule is used to calculate the Gaussian white noise signal based on the main noise data. :

[0170] ;

[0171] In the formula, This represents the impulse response of the first initial filter;

[0172] The second calculation submodule is used to calculate the update factor. :

[0173] ;

[0174] In the formula, Indicates the initial update factor. Indicates parameter adjustment;

[0175] The third calculation submodule is used to calculate based on the secondary signal. The Gaussian white noise signal Calculate the error signal of the first initial filter :

[0176] ;

[0177] In the formula, , These represent the channel parameters of the primary and secondary channels of the first initial filter, respectively. express The signal output after filtering by the first initial filter;

[0178] The first iteration submodule is used to update the factor. With error signal Determine the first iteration formula and the second iteration formula, and determine the first update filter based on the first iteration formula and the second iteration formula.

[0179] The first iterative submodule includes:

[0180] The first calculation unit is used to calculate based on the update factor. With error signal Determine the formula for the first iteration:

[0181] ;

[0182] In the formula, Indicates the first The weight vector of the first initial filter after the next iteration;

[0183] The second calculation unit is used to calculate based on the update factor. With error signal Determine the formula for the second iteration:

[0184] ;

[0185] In the formula, Indicates the first The impulse response of the first initial filter after the next iteration;

[0186] The first iteration unit is used to update the weights of the first initial filter based on the first iteration formula and the second iteration formula until the first iteration termination condition is met, so as to obtain the first updated filter.

[0187] The third noise reduction module 4 includes:

[0188] The fourth calculation submodule is used to calculate the output signal of the second initial filter. :

[0189] ;

[0190] In the formula, This represents the weights of the second initial filter. This represents single-frequency noise data. This represents the channel parameters of the secondary channel of the second initial filter. Indicates the iteration step size;

[0191] The fifth calculation submodule is used to calculate the total error between the first updated filter and the second initial filter. :

[0192] ;

[0193] In the formula, This represents the interference signal corresponding to the main noise data. Indicates the first The interference signal corresponding to the single-frequency noise data, Indicates the type of single-frequency noise data. This represents the output signal of the first update filter. Indicates the first The output signal after inputting single-frequency noise data into the second initial filter;

[0194] The sixth calculation submodule is used to calculate based on the total error. Determine the formula for the third iteration;

[0195] The second iteration submodule is used to determine the additional filter based on the third iteration formula, and to determine the second update filter based on the additional filter.

[0196] The sixth calculation submodule includes:

[0197] The third calculation unit is used to calculate the first iteration factor. With the second iteration factor :

[0198] ; ;

[0199] In the formula, , , These are the first, second, and third adjustable parameters, respectively. Indicates the first The total error after the nth iteration;

[0200] The fourth calculation unit is used to calculate based on the first iteration factor. With the second iteration factor Calculate iteration coefficients :

[0201] ;

[0202] In the formula, This is the fourth adjustable parameter;

[0203] The fifth calculation unit is used for calculations based on iteration coefficients. Determine the formula for the third iteration:

[0204] ;

[0205] In the formula, , They represent the first , The weights of the second initial filter after the next iteration. Indicates the first The reference signal corresponding to the single-frequency noise data after the next iteration.

[0206] The second iteration submodule includes:

[0207] The second iteration unit is used to update the weights of the second initial filter based on the third iteration formula until the second iteration termination condition is met, so as to obtain the second undetermined update filter.

[0208] Additional filter unit, used to determine additional filters based on the second undetermined update filter. :

[0209] ;

[0210] In the formula, , These represent the virtual secondary channel and virtual primary channel of the second undetermined update filter, respectively. , These represent the physical secondary channel and physical primary channel of the second undetermined update filter, respectively.

[0211] Filter output unit, used for filtering based on additional filters Determine the second update filter with the second pending update filter. :

[0212] .

[0213] In other embodiments of the present invention, the present invention provides the following technical solution: a computer, including a memory 102, a processor 101, and a computer program stored in the memory 102 and executable on the processor 101, wherein the processor 101 executes the computer program to implement the active noise reduction method for automobiles under acceleration conditions as described above.

[0214] Specifically, the processor 101 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of the present invention.

[0215] The memory 102 may include a large-capacity memory for data or instructions. For example, and not limitingly, the memory 102 may include a hard disk drive (HDD), a floppy disk drive, a solid-state drive (SSD), flash memory, an optical disk drive, a magneto-optical disk drive, magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 102 may include removable or non-removable (or fixed) media. Where appropriate, the memory 102 may be internal or external to a data processing device. In a particular embodiment, the memory 102 is non-volatile memory. In a particular embodiment, the memory 102 includes read-only memory (ROM) and random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable read-only memory (PROM), an erasable read-only memory (EPROM), an electrically erasable read-only memory (EEPROM), an electrically alterable read-only memory (EAROM), or flash memory, or a combination of two or more of these. Where appropriate, the RAM can be Static Random-Access Memory (SRAM) or Dynamic Random-Access Memory (DRAM). DRAM can be Fast Page Mode Dynamic Random Access Memory (FPMDRAM), Extended Data Out Dynamic Random Access Memory (EDODRAM), Synchronous Dynamic Random-Access Memory (SDRAM), etc.

[0216] The memory 102 can be used to store or cache various data files that need to be processed and / or used for communication, as well as possible computer program instructions executed by the processor 101.

[0217] The processor 101 reads and executes the computer program instructions stored in the memory 102 to implement the above-mentioned active noise reduction method for automobiles under acceleration conditions.

[0218] In some embodiments, the computer may further include a communication interface 103 and a bus 100. For example, Figure 3 As shown, the processor 101, memory 102, and communication interface 103 are connected through bus 100 and complete communication with each other.

[0219] The communication interface 103 is used to enable communication between the various modules, devices, units, and / or equipment in the embodiments of the present invention. The communication interface 103 can also enable data communication with other components such as external devices, image / data acquisition devices, databases, external storage, and image / data processing workstations.

[0220] Bus 100 includes hardware, software, or both, that couples components of a computer device together. Bus 100 includes, but is not limited to, at least one of the following: data bus, address bus, control bus, expansion bus, and local bus. For example, and not as a limitation, bus 100 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 100 may include one or more buses. Although specific buses are described and illustrated in the embodiments of the present invention, the present invention is contemplated by any suitable bus or interconnect.

[0221] The computer can execute the active noise reduction method for vehicles under acceleration conditions according to the present invention based on the information obtained about the active noise reduction system for vehicles under acceleration conditions, thereby realizing active noise reduction for vehicles under acceleration conditions.

[0222] In some further embodiments of the present invention, in conjunction with the above-described active noise reduction method for automobiles under acceleration conditions, the present invention provides the following technical solution: a storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the above-described active noise reduction method for automobiles under acceleration conditions.

[0223] Those skilled in the art will understand that the logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can mean any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0224] More specific examples of readable media (a non-exhaustive list) include: electrical connections (electronic devices) with one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0225] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0226] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0227] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A method for active noise reduction in automobiles under acceleration conditions, characterized in that, include: Noise data of the air intake and the interior of the vehicle under acceleration conditions are obtained, and the noise data is analyzed and a muffler is designed to obtain an air intake muffler. The vehicle is then subjected to the first noise reduction based on the air intake muffler. The vehicle noise after the first noise reduction is collected, and the vehicle noise is decomposed to obtain the main noise data and single-frequency noise data; A first initial filter is constructed, and the weights of the first initial filter are updated based on the main noise data to obtain a first updated filter. The main noise data is then subjected to noise reduction filtering based on the first updated filter. A second initial filter is constructed, and the weights of the second initial filter are updated based on the single-frequency noise data to obtain a second updated filter. The single-frequency noise data is then subjected to noise reduction filtering based on the second updated filter to complete the active noise reduction of the vehicle under acceleration conditions.

2. The active noise reduction method for automobiles under acceleration conditions according to claim 1, characterized in that, The steps of analyzing the noise data and designing the muffler to obtain the air intake muffler include: Perform spectral analysis on the noise data to obtain the main frequency bands corresponding to the noise data; The initial silencer for the corresponding frequency band is determined based on the main frequency band; Calculate the sound transmission loss of the initial muffler. : ； In the formula, Let be the initial inlet area of ​​the muffler. This represents the initial outlet area of ​​the muffler. For the output sound pressure, The entrance sound pressure level, For the speed of sound, The velocity of the particle vibration; Determine the sound transmission loss of the initial muffler Does it meet the preset range? If the initial sound transmission loss of the muffler... If the parameters do not meet the preset range, the parameters of the initial muffler are adjusted, and the loss calculation and parameter adjustment are performed cyclically to output the air inlet muffler.

3. The active noise reduction method for automobiles under acceleration conditions according to claim 1, characterized in that, The step of constructing a first initial filter and updating the weights of the first initial filter based on the main noise data to obtain a first updated filter includes: Construct a first initial filter, and calculate the secondary signal of the first initial filter based on the first initial filter and the main noise data. : ； In the formula, This represents the initial weight vector of the first initial filter. A vector representing the main noise data; Calculate the Gaussian white noise signal based on the main noise data. : ； In the formula, This represents the impulse response of the first initial filter; Calculate the update factor : ； In the formula, Indicates the initial update factor. Indicates parameter adjustment; Based on the secondary signal The Gaussian white noise signal Calculate the error signal of the first initial filter : ； In the formula, , These represent the channel parameters of the primary and secondary channels of the first initial filter, respectively. express The signal output after filtering by the first initial filter; Based on update factor With error signal Determine the first iteration formula and the second iteration formula, and determine the first update filter based on the first iteration formula and the second iteration formula.

4. The active noise reduction method for automobiles under acceleration conditions according to claim 3, characterized in that, Based on update factor With error signal The steps for determining the first iteration formula and the second iteration formula, and then determining the first update filter based on the first iteration formula and the second iteration formula, include: Based on the update factor With error signal Determine the formula for the first iteration: ； In the formula, Indicates the first The weight vector of the first initial filter after the next iteration; Based on the update factor With error signal Determine the formula for the second iteration: ； In the formula, Indicates the first The impulse response of the first initial filter after the next iteration; The weights of the first initial filter are updated based on the first iteration formula and the second iteration formula until the first iteration termination condition is met, so as to obtain the first updated filter.

5. The active noise reduction method for automobiles under acceleration conditions according to claim 1, characterized in that, The step of updating the weights of the second initial filter based on the single-frequency noise data to obtain the second updated filter includes: Calculate the output signal of the second initial filter. : ； In the formula, This represents the weights of the second initial filter. This represents single-frequency noise data. This represents the channel parameters of the secondary channel of the second initial filter. Indicates the iteration step size; Calculate the total error between the first updated filter and the second initial filter. : ； In the formula, This represents the interference signal corresponding to the main noise data. Indicates the first The interference signal corresponding to the single-frequency noise data, Indicates the type of single-frequency noise data. This represents the output signal of the first update filter. Indicates the first The output signal after inputting single-frequency noise data into the second initial filter; Based on the total error Determine the formula for the third iteration; The additional filter is determined based on the third iteration formula, and the second update filter is determined based on the additional filter.

6. The active noise reduction method for automobiles under acceleration conditions according to claim 5, characterized in that, Based on the total error The steps to determine the third iteration formula include: Calculate the first iteration factor With the second iteration factor : ； ； In the formula, , , These are the first, second, and third adjustable parameters, respectively. Indicates the first The total error after the nth iteration; Based on the first iteration factor With the second iteration factor Calculate iteration coefficients : ； In the formula, This is the fourth adjustable parameter; Based on iteration coefficients Determine the formula for the third iteration: ； In the formula, , They represent the first , The weights of the second initial filter after the next iteration. Indicates the first The reference signal corresponding to the single-frequency noise data after the next iteration.

7. The active noise reduction method for automobiles under acceleration conditions according to claim 5, characterized in that, The steps of determining the additional filter based on the third iterative formula and determining the second updated filter based on the additional filter include: The weights of the second initial filter are updated based on the third iterative formula until the second iteration termination condition is met, so as to obtain the second undetermined update filter. Determine additional filters based on the second undetermined update filter. : ； In the formula, , These represent the virtual secondary channel and virtual primary channel of the second undetermined update filter, respectively. , These represent the physical secondary channel and physical primary channel of the second undetermined update filter, respectively. Based on additional filters Determine the second update filter with the second pending update filter. : 。 8. An active noise reduction system for automobiles under acceleration conditions, characterized in that, The system includes: The first noise reduction module is used to acquire noise data of the car's air intake and interior, analyze the noise data and design a muffler to obtain an air intake muffler, and perform the first noise reduction on the car based on the air intake muffler. The decomposition module is used to collect the car noise after the first noise reduction, and decompose the car noise to obtain the main noise data and single-frequency noise data. The second noise reduction module is used to construct a first initial filter, update the weights of the first initial filter based on the main noise data to obtain a first updated filter, and perform noise reduction filtering on the main noise data based on the first updated filter. The third noise reduction module is used to construct a second initial filter, update the weights of the second initial filter based on the single-frequency noise data to obtain a second updated filter, and perform noise reduction filtering on the single-frequency noise data based on the second updated filter to complete the active noise reduction of the vehicle under acceleration conditions.

9. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the active noise reduction method for automobiles under acceleration conditions as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the active noise reduction method for automobiles under acceleration conditions as described in any one of claims 1 to 7.

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