Control method and device, vehicle and machine readable storage medium

Abstract

The embodiment of the invention discloses a control method and device, a vehicle and a machine readable storage medium, and belongs to the technical field of noise reduction. The control method is applied to the vehicle with an engine noise elimination system and comprises the steps that at least one noise signal collected by a microphone is obtained; determining a filter coefficient of each filter according to the current rotating speed of the engine and a preset user attention order; filtering the noise signal according to the filter coefficient of each filter to obtain an engine noise component; determining engine noise energy according to the engine noise components; adjusting a leakage factor according to the engine noise energy; and starting and stopping of the engine noise elimination system are controlled according to the adjusted leakage factor. When the system is in an abnormal state, the noise reduction performance is sacrificed and the stability of the system is kept; and when the system is recovered to a normal state, the noise reduction performance is recovered, and stability control in the engine noise elimination system is realized.

Description

Technical Field

[0001] This application relates to the field of noise reduction technology, and more specifically to a control method, apparatus, vehicle, and machine-readable storage medium. Background Technology

[0002] Engine noise cancellation systems are specific active noise reduction systems implemented in vehicles to minimize engine noise inside the passenger compartment. Stability control technology aims to ensure that the engine noise cancellation system remains stable under all conditions and does not generate increased noise.

[0003] Currently, the two commonly used stability control technologies are: stability control based on the vehicle's CAN (Controller Area Network) bus and stability control based on microphone input and speaker output energy. The former can cause instability in the engine noise cancellation system when no CAN message is provided, while the latter is prone to misjudgment. Both of these existing technologies directly shut down the engine noise cancellation system when dealing with instability, failing to maintain a certain level of engine noise reduction while ensuring the continuous stability of the engine noise cancellation system. Summary of the Invention

[0004] The purpose of this application is to provide a control method, device, vehicle, and machine-readable storage medium to solve the technical problem in the prior art that it is impossible to both retain a certain engine noise reduction effect and ensure the continuous stability of the engine noise elimination system.

[0005] To achieve the above objectives, the first aspect of this application provides a control method, comprising:

[0006] Acquire at least one noise signal captured by the microphone;

[0007] The filter coefficients for each filter are determined based on the engine's current RPM and the preset user focus order.

[0008] Based on the filter coefficients of each filter, the noise signal is filtered to obtain the engine noise components;

[0009] Determine engine noise energy based on engine noise components;

[0010] Adjust the leakage factor based on engine noise energy;

[0011] The engine noise cancellation system is started and stopped based on the adjusted leakage factor.

[0012] According to a specific embodiment disclosed in this application, the filter coefficients of each filter are determined based on the current engine speed and the preset user attention order, including:

[0013] The center frequency of the filter is calculated based on the current engine speed and the preset user focus order.

[0014] The center frequency radians of the filter are calculated based on the center frequency of the filter.

[0015] The alpha coefficient of the filter is calculated based on the center frequency radian of the filter and the user-preset quality factor.

[0016] The filter coefficients for each filter are calculated based on the center frequency radians and the alpha coefficient.

[0017] According to a specific embodiment disclosed in this application, the filter coefficients of the filter include: a first filter coefficient, a second filter coefficient, a third filter coefficient, a fourth filter coefficient, a fifth filter coefficient, and a sixth filter coefficient;

[0018] The first filter coefficient is the alpha coefficient;

[0019] The coefficients of the second filter are zero;

[0020] The coefficients of the third filter are the negatives of the alpha coefficients;

[0021] The fourth filter coefficient is one plus the aforementioned alpha coefficient;

[0022] The coefficients of the fifth filter are negative two times the cosine of the center frequency radians of the filter described above;

[0023] The coefficient of the sixth filter is one minus the alpha coefficient.

[0024] According to a specific embodiment disclosed in this application, the step of filtering the noise signal based on the filter coefficients of each filter to obtain the engine noise components includes:

[0025] Each noise signal is input to each filter, and the noise signal is filtered based on the filter coefficients of each filter to obtain multiple engine noise components;

[0026] Based on the filter coefficients and the noise signal collected by the microphone, the filter retains only the signal components within the passband.

[0027] The filter coefficients are updated in real time based on the current engine speed inside the vehicle and the preset user focus order.

[0028] According to a specific embodiment disclosed in this application, determining the engine noise energy based on engine noise components includes:

[0029] Based on the engine noise components, the root mean square value of the engine noise components is calculated using the time-domain energy calculation method.

[0030] The engine noise energy is obtained by performing a logarithmic transformation based on the root mean square value of the engine noise components.

[0031] According to a specific embodiment disclosed in this application, the leakage factor is adjusted based on engine noise energy, as follows:

[0032] Reduce the leakage factor when any engine noise energy is greater than or equal to the corresponding preset maximum energy threshold.

[0033] When all engine noise energy is less than the user-preset maximum energy threshold, the leakage factor is increased.

[0034] According to a specific embodiment disclosed in this application, controlling the start-up and shutdown of the engine noise cancellation system based on an adjusted leakage factor includes:

[0035] When the adjusted leakage factor continues to decrease and falls below the user-preset threshold, the engine noise cancellation system will be turned off.

[0036] Secondly, embodiments of this application provide a control device applied to a vehicle having an engine noise cancellation system, comprising:

[0037] The memory is configured to store instructions;

[0038] The processor is configured to retrieve instructions from memory and, when executing instructions, to implement control methods as described in the first aspect.

[0039] Thirdly, embodiments of this application provide a vehicle, including:

[0040] Engine noise cancellation system;

[0041] According to the control device of the second aspect.

[0042] Fourthly, embodiments of this application provide a machine-readable storage medium storing a program or instructions that, when executed by a processor, implement the steps of the method as described in the first aspect.

[0043] Through the above technical solution, this application can maintain the stability of the system by sacrificing noise reduction performance when the system is in an abnormal state; and restore the noise reduction performance when the system returns to a normal state, so as to more accurately complete the stability control of the engine noise elimination system under unstable conditions.

[0044] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0045] The accompanying drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the following detailed description to explain the embodiments of this application, but do not constitute a limitation on the embodiments of this application. In the drawings:

[0046] Figure 1 The schematic diagram illustrates a flow chart of a control method according to an embodiment of this application;

[0047] Figure 2 This schematically illustrates an example block diagram of an LMS active noise reduction algorithm according to an embodiment of this application;

[0048] Figure 3 The diagram illustrates a stability control block diagram for a multi-microphone, multi-noise reduction system according to an embodiment of this application. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0050] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0051] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0052] To better illustrate the control method provided in the embodiments of the present invention, a brief description of the engine noise cancellation system in the prior art is provided below:

[0053] Engine noise cancellation systems are specific active noise reduction systems implemented in vehicles to minimize unwanted engine noise inside the passenger compartment. Active noise reduction systems use the principle of anti-phase noise to cancel out noise.

[0054] Active noise cancellation systems generate anti-phase sound waves. These anti-phase sound waves have the same frequency and amplitude as the original noise sound waves, but are opposite in phase. When the anti-phase sound waves meet the original noise, they cancel each other out. In engine noise cancellation systems, the unwanted engine noise is the original noise sound wave. The sound generated by the subwoofer of the in-car audio system, controlled by the engine noise system, is an anti-phase sound wave. When the two meet, they cancel each other out, thus reducing the level of engine noise inside the vehicle.

[0055] The processor receives a reference signal of engine noise and a microphone signal that monitors the noise level in real time, and calculates the anti-phase sound through an active noise reduction algorithm.

[0056] A typical implementation of active noise reduction algorithms is the LMS (Least Mean Square) algorithm. Please refer to [link / reference]. Figure 1 , Figure 1 A schematic diagram of an LMS algorithm according to an embodiment of this application is shown. Figure 1 As shown, x(n) is the engine noise signal, which is transmitted through a single path P(z) to obtain the engine noise signal d(n) at the noise-canceling microphone. Here, P(z) represents the transmission path from the point where the engine generates the original noise to the noise-canceling microphone.

[0057] The engine noise signal x(n) is filtered by filter W(z) to obtain the speaker output signal y(n). The speaker output signal y(n) then passes through a secondary transmission path S(z) to obtain the anti-phase sound y′(n) at the noise-canceling microphone. Here, S(z) represents the transmission path from the point where the anti-phase sound is generated by the speaker to the noise-canceling microphone.

[0058] The engine noise signal x(n) is also transmitted through the estimated quadratic path. The filtered reference signal x′(n) for the LMS module is obtained. The error signal of the LMS module is the sum of the engine noise signal d(n) at the noise-canceling microphone and the anti-phase noise y′(n). The LMS module is used to update the coefficients of the W filter W(z) in real time, and its update formula is:

[0059]

[0060] In the formula, w(n) represents the coefficients of the W-filter W(z), and step represents the update step size of the coefficients of the W-filter W(z). Let represent the estimated secondary propagation path, e(n) represent the error signal, and γ be the leakage factor for updating the coefficients of the W filter W(z). The default value for the leakage factor is 1.0, meaning it has no effect. When the leakage factor is less than 1.0, it takes effect, ensuring greater system stability at the expense of some noise reduction performance. The smaller the leakage factor, the greater the sacrifice in noise reduction performance, but the better the system stability.

[0061] Engine noise cancellation systems need to reduce engine noise levels inside the vehicle while ensuring system stability. In certain special scenarios, the actual secondary transmission path S(z) changes, such as when a window is opened, which affects the estimated secondary transmission path. The deviation from the actual secondary transmission path S(z) is significant. In this case, the LMS algorithm will diverge, causing the engine noise cancellation system to become unstable inside the vehicle and produce severe noise increase. Stability control technology aims to ensure that the engine noise cancellation system remains stable under all conditions and does not produce noise increase. Currently, two commonly used stability control technologies are: stability control technology based on vehicle CAN bus control and stability control technology based on microphone input and speaker output energy.

[0062] Most vehicles support CAN bus control, sending this information to the control logic unit of the engine noise cancellation system via the vehicle's infotainment system. The control logic unit determines whether to activate the engine noise cancellation system only when all conditions are closed, such as doors, windows, trunk, and sunroof being closed; otherwise, it deactivates the engine noise cancellation system.

[0063] Stability control technology based on microphone input and speaker output energy requires calculating the energy of the microphone input and the energy of the out-of-sound output. This data is then compared to corresponding thresholds to determine if instability has occurred. If any signal energy, such as the microphone input energy, exceeds a preset threshold, instability is considered to have occurred. In this case, the control logic unit will disable the engine noise cancellation system; otherwise, it will enable the system.

[0064] Both of these existing technologies directly shut down the engine noise reduction system when dealing with unstable situations, failing to both retain a certain level of engine noise reduction and ensure continuous system stability.

[0065] Based on this situation, this invention proposes a control method to more accurately achieve stability control of the engine noise cancellation system under unstable conditions. For details, please refer to... Figure 2 , Figure 2 The schematic diagram illustrates a flow chart of a control method according to an embodiment of this application. The method may include the following steps:

[0066] S110. Acquire at least one noise signal collected by the microphone.

[0067] The microphone is usually placed close to the passenger's ear to collect noise signals inside the vehicle in real time. This means that the noise is the result of the superposition of engine noise and the anti-phase sound emitted by the speakers at the microphone.

[0068] S120. Determine the filter coefficients for each filter based on the current engine speed and the preset user focus order.

[0069] In this embodiment, the filter coefficients are dynamically adjusted based on the engine's current RPM and a preset user focus order, thereby improving the filtering effect. Indicatively, the filter can be a bandpass filter.

[0070] In one optional implementation, step 120 includes:

[0071] S121. Calculate the center frequency of the filter based on the current engine speed and the preset user attention order.

[0072] Indicatively, in this embodiment of the application, the center frequency of the filter can be determined according to the following formula (1):

[0073]

[0074] In the formula, freq represents the center frequency of the filter, ord represents the preset user-focused order, and rpm represents the engine speed.

[0075] That is, the center frequency of the filter is the product of the current engine speed and the preset user-focused order, divided by sixty.

[0076] S122. Calculate the center frequency radians of the filter based on its center frequency.

[0077] Indicatively, in this embodiment of the application, the center frequency of the filter can be determined according to the following formula (2):

[0078]

[0079] In the formula, ω0 represents the center frequency of the filter in radians, freq represents the center frequency of the filter, and fs represents the sampling frequency of the filter, typically 48kHz.

[0080] That is, the center frequency radians of the filter is the product of pi and the center frequency of the filter, multiplied by two and divided by the sampling frequency of the filter.

[0081] S123. Calculate the alpha coefficient of the filter based on the center frequency radian of the filter and the user-preset quality factor.

[0082] Indicatively, in this embodiment of the application, the center frequency of the filter can be determined according to the following formula (3):

[0083]

[0084] In the formula, α represents the alpha coefficient of the filter, Q represents the user-preset quality factor, which is a dimensionless parameter in physics and engineering used to describe the damping properties and resonance characteristics of an oscillator, and ω0 represents the center frequency radians of the filter.

[0085] That is, the alpha coefficient of the filter is the sine of the center frequency radians of the filter divided by twice the quality factor.

[0086] S124. Calculate the filter coefficients for each filter based on the center frequency radian and the alpha coefficient.

[0087] Indicatively, in this embodiment, the filter coefficients of the filter include: a first filter coefficient, a second filter coefficient, a third filter coefficient, a fourth filter coefficient, a fifth filter coefficient, and a sixth filter coefficient, which are determined by the following formulas (4)-(9):

[0088] b0=α (4)

[0089] b1 = 0 (5)

[0090] b2=-α (6)

[0091] a0 = 1 + α (7)

[0092] a1=-2·cos(ω0) (8)

[0093] a2=1-α (9)

[0094] In the formula, α represents the alpha coefficient of the filter, and b0, b1, b2, a0, a1, and a2 represent the first filter coefficient, the second filter coefficient, the third filter coefficient, the fourth filter coefficient, the fifth filter coefficient, and the sixth filter coefficient, respectively.

[0095] That is, the first filter coefficient is the alpha coefficient;

[0096] The coefficients of the second filter are zero;

[0097] The coefficients of the third filter are the negatives of the alpha coefficients;

[0098] The fourth filter coefficient is one plus the alpha coefficient;

[0099] The coefficients of the fifth filter are negative two times the cosine of the center frequency radians of the filter.

[0100] The coefficient of the sixth filter is one minus the alpha coefficient.

[0101] S130. Filter the noise signal according to the filter coefficients of each filter to obtain the engine noise components.

[0102] In the embodiments of this application, the filter coefficients of the filter can be updated in real time. Therefore, when using the filter to filter the noise signal, a noise component that better meets the requirements can be obtained.

[0103] In one optional implementation, S130 includes:

[0104] S131. Input each noise signal into each filter, and filter the noise signal based on the filter coefficients of each filter to obtain multiple engine noise components.

[0105] Please refer to the following for details. Figure 3 , Figure 3 The diagram illustrates a stability control block diagram for multiple microphones and multiple noise reduction orders according to an embodiment of this application.

[0106] For example, the input N noise-canceling microphone signals are passed through M filters to obtain the engine noise components at the current engine speed and the preset user attention order, for a total of M*N. It is understood that the preset user attention order for each filter can be set independently, and the specific values ​​of the preset user attention order for each filter can be the same or different.

[0107] Indicatively, in this embodiment of the application, the engine noise components can be determined according to the following formula (10):

[0108] a0·y(n)=b2·x(n-2)+b1·x(n-1)+b0·x(n)+a2·y(n-2)+a1·y(n-1) (10)

[0109] In the formula, n represents time, x(n) represents noise signal, y(n) represents engine noise component, and [b2, b1, b0, a2, a1, a0] represents filter coefficients.

[0110] The filter coefficients are updated in real time based on the engine's current RPM and the preset user-focused order.

[0111] S140. Determine the engine noise energy based on the engine noise components.

[0112] Engine noise energy refers to the energy carried by the sound produced by the engine during its propagation. Calculating noise energy typically involves factors such as sound intensity and frequency, and requires analysis of the engine noise components.

[0113] In one optional implementation, S140 includes:

[0114] S141. Based on the engine noise components, calculate the root mean square value of the engine noise components using the time-domain energy calculation method.

[0115] Indicatively, in this embodiment of the application, the root mean square value of the engine noise component can be determined according to the following formula (11):

[0116] rms(n) = |y(n)|·rms b0 +rms(n-1)·rms a1 +rms(n-2)·rms a2 (11)

[0117] In the formula, y(n) represents the engine noise component, rms(n) is the root mean square value of the engine noise component, [rms b0 rms a1 rms a2 [These are the coefficients of a second-order low-pass filter used to calculate signal energy in the time domain; typical values ​​are...]

[0118] [2.7272457662617143 -5 , 1.9895553922691913, -9.8958266472685397 -1 ].

[0119] S142. Based on the root mean square value of the engine noise components, perform a logarithmic transformation to obtain the engine noise energy.

[0120] Indicatively, in this embodiment of the application, the engine noise energy can be determined according to the following formula (12):

[0121] P(n)=20×lg(rms(n)) (12)

[0122] In the formula, P(n) represents the engine noise energy, and rms(n) is the root mean square value of the engine noise component.

[0123] That is, the engine noise energy is the root mean square value of the engine noise components multiplied by twenty.

[0124] S150, adjusts the leakage factor according to engine noise energy.

[0125] In this embodiment, the leakage factor is dynamically adjusted based on engine noise energy. When the engine noise energy is greater than a threshold, the system is determined to be in an abnormal state, the leakage factor is attenuated, and noise reduction performance is sacrificed to maintain system stability. When the engine noise energy is detected to be less than the threshold, the system is determined to have returned to a normal state, and the leakage factor is restored, thereby restoring the noise reduction performance.

[0126] In one optional implementation, step S150 includes:

[0127] S151. When the noise energy of any engine is greater than or equal to the corresponding preset maximum energy threshold, reduce the leakage factor.

[0128] Indicatively, in this embodiment of the application, the leakage factor can be determined according to the following formula (13):

[0129] γ(n)=γ(n-1)×att (13)

[0130] In the formula, att is the leakage factor decay coefficient, which reflects the rate at which the leakage factor decays, with a typical value of 0.999.

[0131] That is, the leakage factor at the next moment is the leakage factor at the previous moment multiplied by the attenuation coefficient.

[0132] S152. When all engine noise energy is less than the user-preset maximum energy threshold, increase the leakage factor.

[0133] Indicatively, in this embodiment of the application, the leakage factor can be determined according to the following formula (14):

[0134]

[0135] In the formula, rel is the leakage factor recovery coefficient, which reflects the speed of leakage factor recovery, with a typical value of 0.999.

[0136] That is, the leakage factor at the next moment is the leakage factor at the previous moment divided by the attenuation coefficient.

[0137] S160. Control the start and stop of the engine noise cancellation system according to the adjusted leakage factor.

[0138] In this embodiment, the control logic module controls the opening or closing of the engine noise cancellation system based on the real-time adjusted leakage factor value. When it is determined that the noise reduction system is in an abnormal state and cannot be restored, the engine noise cancellation system is turned off.

[0139] In one optional implementation, step S160 includes:

[0140] When the adjusted leakage factor continues to decrease and falls below the preset leakage factor threshold, the engine noise cancellation system will be turned off.

[0141] Understandably, if the leakage factor continues to decrease, it means that the engine noise energy is always greater than the threshold, the system is in an abnormal state and cannot be restored by reducing the leakage factor. Therefore, the engine noise cancellation system can be turned off directly.

[0142] In the embodiments of this application, the smaller the leakage factor, the greater the sacrifice in noise reduction performance, but the better the system stability. This invention utilizes this principle to adjust the leakage factor in real time based on the engine noise energy, enabling the system to maintain stability by sacrificing noise reduction performance when in an abnormal state; and to restore noise reduction performance when the system returns to a normal state, thus more accurately achieving stability control of the engine noise elimination system under unstable conditions.

[0143] This application embodiment also provides a control device, which may include:

[0144] The memory is configured to store instructions; and

[0145] The processor is configured to retrieve instructions from memory and to implement the aforementioned control methods when executing instructions.

[0146] Optionally, embodiments of this application also provide a vehicle, including an engine noise cancellation system, a processor, and a memory, wherein the memory stores a program or instructions, and the program or instructions are executed by the processor to implement the control method described above.

[0147] This application also provides a machine-readable storage medium storing instructions that cause a machine to perform the control method described above.

[0148] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0149] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0150] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0151] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0152] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0153] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, like read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0154] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0155] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0156] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A control method characterized by, The control method is applied to a vehicle with an engine noise cancellation system, and the control method comprises: acquiring at least one noise signal collected by a microphone; determining filter coefficients of each filter according to a current engine speed and a preset user concerned order; filtering the noise signal according to the filter coefficients of each filter to obtain an engine noise component; determining engine noise energy according to the engine noise component; adjusting a leakage factor according to the engine noise energy; controlling start and stop of the engine noise cancellation system according to the adjusted leakage factor.

2. The control method according to claim 1, characterized by, The determination of the filter coefficients of each filter according to the current engine speed and the preset user concerned order comprises: calculating a center frequency of the filter according to the current engine speed and the preset user concerned order; calculating a center frequency radian of the filter according to the center frequency of the filter; calculating an alpha coefficient of the filter according to the center frequency radian of the filter and a preset quality factor; calculating the filter coefficients of each filter according to the center frequency radian of the filter and the alpha coefficient.

3. The control method according to claim 2, characterized by, The filter coefficients of the filter include a first filter coefficient, a second filter coefficient, a third filter coefficient, a fourth filter coefficient, a fifth filter coefficient and a sixth filter coefficient. The first filter coefficient is the alpha coefficient. The second filter coefficient is zero. The third filter coefficient is the alpha coefficient taken as negative. The fourth filter coefficient is one plus the alpha coefficient. The fifth filter coefficient is negative two times a cosine value of the center frequency radian of the filter. The sixth filter coefficient is one minus the alpha coefficient.

4. The control method according to claim 1, characterized by, The filtering of the noise signal according to the filter coefficients of each filter to obtain the engine noise component comprises: inputting each noise signal into each filter respectively, and filtering the noise signal based on the filter coefficients of each filter to obtain multiple engine noise components. According to the filter coefficients of the filter and the noise signal collected by the microphone, only the signal component in the passband range is retained through the filter. The filter coefficients of the filter are updated in real time according to the current engine speed in the vehicle and the preset user concerned order.

5. The control method according to claim 1, characterized by, The determination of the engine noise energy according to the engine noise component comprises: calculating a root mean square value of the engine noise component by using a time domain energy calculation method according to the engine noise component; performing logarithmic conversion on the root mean square value of the engine noise component to obtain the engine noise energy.

6. The control method according to claim 1, characterized by, The adjustment of the leakage factor according to the engine noise energy is specifically as follows: in a case where any one of the engine noise energies is greater than or equal to a corresponding preset maximum energy threshold, the leakage factor is reduced; in a case where all the engine noise energies are less than a maximum energy threshold preset by a user, the leakage factor is increased.

7. The control method according to claim 1, characterized by, The control of the start and stop of the engine noise cancellation system according to the adjusted leakage factor comprises: when the adjusted leakage factor continues to decrease and is less than a user preset threshold, turning off the engine noise cancellation system.

8. A control device characterized by comprising: The control device is applied to a vehicle with an engine noise cancellation system, and the control device comprises: a memory configured to store instructions; a processor configured to call the instructions from the memory and implement the control method according to any one of claims 1 to 7 when the instructions are executed.

9. A vehicle characterized by comprising: comprising: an engine noise cancellation system; the control device according to claim 8.

10. A machine-readable storage medium, characterized in that, The machine readable storage medium has a computer program stored thereon, and the computer program is executed by the processor to implement the control method according to any one of claims 1 to 7.

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