Active noise reduction method for vehicle

Abstract

The embodiment of the invention provides an active noise reduction method for a vehicle, and the method comprises the steps: recognizing the current driving state of the vehicle, and detecting the internal noise generated by the vehicle in the current driving state; and determining an initial noise reduction parameter corresponding to the current driving state, obtaining noise information in the initial noise reduction parameter, adjusting the noise information to obtain a target noise reduction parameter, and performing active noise reduction on the internal noise by using the target noise reduction parameter. According to the embodiment of the invention, by adopting the initial noise reduction parameter for the current driving state of the vehicle, differential noise reduction parameters are adopted for different working conditions, the initial noise reduction parameter is further adjusted according to the actual noise reduction characteristic of the initial noise reduction parameter, the more accurate target noise reduction parameter is obtained and used for active noise reduction, and the noise reduction efficiency is improved. Therefore, the noise reduction effect is improved and the stability of the control system is ensured.

Description

Technical Field

[0001] The present application relates to the automotive field, and in particular to an active noise reduction method for a vehicle. Background Art

[0002] In the automotive industry, active noise cancellation (ANC) is often used to reduce in-cabin noise and improve driving comfort when vehicle driving conditions (such as speed, engine speed, and road conditions) change. ANC cancels or attenuates noise by generating sound waves with a phase opposite to the original noise. The system uses a microphone to capture in-cabin noise signals. A controller then generates an anti-phase sound wave, which is played back through the speakers to cancel out the original noise.

[0003] However, as a vehicle's driving conditions constantly change, the vehicle's noise reduction system may not be able to immediately adapt to the new noise characteristics, resulting in a deterioration in noise reduction effectiveness at the moment of change. For example, when a vehicle's driving conditions change frequently and rapidly (such as frequent acceleration, deceleration, and lane changes on urban roads), the system may be unable to keep up with these rapid changes, resulting in unstable noise reduction and further deteriorating the stability of the active noise reduction system.

[0004] When performing active noise reduction, different noise reduction parameters are usually set to cope with the noise characteristics under different driving conditions. These noise reduction parameters may include gain, delay, etc. to optimize the noise reduction effect. However, when the driving state changes, the noise reduction parameters will suddenly change. This phenomenon affects the functionality and stability of the noise reduction algorithm. Summary of the Invention

[0005] The embodiment of the present application provides an active noise reduction method for a vehicle to solve the problem that when the driving state changes, the noise reduction parameters may suddenly change, resulting in unstable noise reduction effect.

[0006] The present application discloses an active noise reduction method for a vehicle, the method comprising:

[0007] identifying a current driving state of a vehicle and detecting interior noise generated by the vehicle in the current driving state;

[0008] determining initial noise reduction parameters corresponding to the current driving state, and obtaining noise information from the initial noise reduction parameters, wherein the initial noise reduction parameters are used to represent characteristic parameters of active noise reduction operation, and the noise information is used to represent characteristic parameter values of the initial noise reduction parameters under the current driving state;

[0009] The noise information is adjusted to obtain a target noise reduction parameter, and the target noise reduction parameter is used to actively reduce the internal noise.

[0010] Optionally, before identifying the current driving state of the vehicle, the method includes:

[0011] Classify the driving status of the vehicle;

[0012] collecting a noise signal of the vehicle in each of the driving states, and obtaining a first noise reduction parameter corresponding to the noise signal;

[0013] Running a preset calibration algorithm to perform convergence calculation on the first noise reduction parameter to obtain a second noise reduction parameter corresponding to the driving state;

[0014] The second noise reduction parameters corresponding to each type of the driving state are aggregated to generate a noise reduction parameter set.

[0015] Optionally, the running of a preset calibration algorithm to perform convergence calculation on the first noise reduction parameter to obtain a second noise reduction parameter corresponding to the driving state includes:

[0016] Performing spectrum analysis on the noise signal to obtain the amplitude, phase and frequency of the noise signal;

[0017] generating a target signal according to the amplitude, phase and frequency of the noise signal, wherein the target signal is a signal having a phase opposite to that of the noise signal and the same amplitude and frequency as that of the noise signal;

[0018] Actively reduce noise on the noise signal according to the first noise reduction parameter, and generate a control signal for the noise signal;

[0019] An error between the control signal and the target signal is calculated, and the first noise reduction parameter is inversely updated using the error to obtain the second noise reduction parameter.

[0020] Optionally, determining the initial noise reduction parameters corresponding to the current driving state includes:

[0021] The initial noise reduction parameter corresponding to the current driving state is matched from the noise reduction parameter set.

[0022] Optionally, adjusting the noise information to obtain a target noise reduction parameter includes:

[0023] generating a noise reduction parameter curve corresponding to the initial noise reduction parameter, and determining a mutation point corresponding to the noise information on the noise reduction parameter curve;

[0024] The noise information is adjusted until the mutation point is converted into a smooth point, and the target noise reduction parameter corresponding to the smooth point is obtained.

[0025] Optionally, adjusting the noise information until the mutation point is converted into a smooth point includes:

[0026] Setting a starting control point and an ending control point before and after the mutation point, and determining the coverage range of the starting control point and the ending control point as the interpolation interval;

[0027] Obtaining a first vector of the starting control point and a second vector of the ending control point;

[0028] Calculating using the first vector and the second vector to obtain a first tangent vector corresponding to the starting control point and a second tangent vector corresponding to the ending control point;

[0029] Calculating using the starting control point and the ending control point to obtain a virtual control point;

[0030] Obtaining curvature control parameters for the first tangent vector and the second tangent vector;

[0031] Adjusting the first tangent vector and the second tangent vector using the curvature control parameter and the virtual control point to obtain a first target tangent vector of the starting control point and a second target tangent vector of the ending control point;

[0032] Acquire basis functions for the interpolation interval, where the basis functions include position basis functions and geometric adjustment basis functions;

[0033] Substituting the first vector and the second vector into the position basis function, and substituting the first target tangent vector and the second target tangent vector into the geometric adjustment basis function, to obtain the coordinates of the interpolation point corresponding to the interpolation interval;

[0034] The coordinates of the interpolation points are used to convert the mutation points into the smooth points.

[0035] Optionally, the actively reducing the internal noise by using the target noise reduction parameter comprises:

[0036] Converting the internal noise into a first noise signal, and acquiring the phase, frequency, and amplitude of the first noise signal;

[0037] generating an anti-phase noise signal according to the target noise reduction parameter, wherein the anti-phase noise signal is a signal having an opposite phase, equal frequency, and equal amplitude to the first noise signal;

[0038] The first noise signal and the anti-phase noise signal are superimposed to cancel the internal noise.

[0039] The present application also discloses an active noise reduction device for a vehicle, the device comprising:

[0040] a noise detection module, configured to identify a current driving state of a vehicle and detect interior noise generated by the vehicle in the current driving state;

[0041] a parameter determination module, configured to determine initial noise reduction parameters corresponding to the current driving state, and obtain noise information from the initial noise reduction parameters, wherein the initial noise reduction parameters are used to represent characteristic parameters of active noise reduction operation, and the noise information is used to represent characteristic parameter values of the initial noise reduction parameters under the current driving state;

[0042] The active noise reduction module is configured to adjust the noise information to obtain target noise reduction parameters, and to perform active noise reduction on the internal noise using the target noise reduction parameters.

[0043] Optionally, the device further comprises:

[0044] A classification module, used to classify the driving status of the vehicle;

[0045] an acquisition module, configured to acquire a noise signal of the vehicle in each of the driving states, and obtain a first noise reduction parameter corresponding to the noise signal;

[0046] a calculation module, configured to execute a preset calibration algorithm to perform convergence calculation on the first noise reduction parameter to obtain a second noise reduction parameter corresponding to the driving state;

[0047] The set generating module is configured to aggregate the second noise reduction parameters corresponding to each type of the driving state to generate a noise reduction parameter set.

[0048] Optionally, the calculation module further includes:

[0049] A spectrum analysis module, configured to perform spectrum analysis on the noise signal to obtain the amplitude, phase, and frequency of the noise signal;

[0050] a target signal generating module, configured to generate a target signal according to the amplitude, phase and frequency of the noise signal, wherein the target signal is a signal having a phase opposite to that of the noise signal and the same amplitude and frequency;

[0051] a control signal generating module, configured to perform active noise reduction on the noise signal according to the first noise reduction parameter, and generate a control signal for the noise signal;

[0052] A reverse updating module is used to calculate the error between the control signal and the target signal, and use the error to reversely update the first noise reduction parameter to obtain the second noise reduction parameter.

[0053] Optionally, the parameter determination module is specifically configured to match initial noise reduction parameters corresponding to the current driving state from the noise reduction parameter set.

[0054] Optionally, the active noise reduction module includes:

[0055] a curve generating module, configured to generate the noise reduction parameter curve corresponding to the initial noise reduction parameter, and determine a mutation point corresponding to the noise information on the noise reduction parameter curve;

[0056] The target noise reduction parameter acquisition module is used to adjust the noise information until the mutation point is converted into a smooth point, and obtain the target noise reduction parameter corresponding to the smooth point.

[0057] Optionally, the target noise reduction parameter acquisition module includes:

[0058] A control point setting module, configured to set a starting control point and an ending control point before and after the mutation point, and determine the coverage of the starting control point and the ending control point as an interpolation interval;

[0059] a vector calculation module, configured to obtain a first vector of the starting control point and a second vector of the ending control point; and to perform calculations using the first vector and the second vector to obtain a first tangent vector corresponding to the starting control point and a second tangent vector corresponding to the ending control point;

[0060] A virtual control point setting module, configured to calculate using the starting control point and the ending control point to obtain a virtual control point;

[0061] a curvature control parameter acquisition module, configured to acquire curvature control parameters for the first tangent vector and the second tangent vector;

[0062] a vector adjustment module, configured to adjust the first tangent vector and the second tangent vector using the curvature control parameter and the virtual control point to obtain a first target tangent vector of the starting control point and a second target tangent vector of the ending control point;

[0063] A basis function acquisition module, configured to acquire basis functions for the interpolation interval, wherein the basis functions include position basis functions and geometric adjustment basis functions;

[0064] a coordinate value acquisition module, configured to substitute the first vector and the second vector into the position basis function, and substitute the first target tangent vector and the second target tangent vector into the geometric adjustment basis function, to obtain the coordinates of the interpolation point corresponding to the interpolation interval;

[0065] The mutation point conversion module is used to convert the mutation point into the smooth point by using the coordinates of the interpolation point.

[0066] Optionally, the active noise reduction module further includes:

[0067] a noise conversion module, configured to convert the internal noise into a first noise signal and obtain the phase, frequency, and amplitude of the first noise signal;

[0068] an anti-phase noise signal generating module, configured to generate an anti-phase noise signal according to the target noise reduction parameter, wherein the anti-phase noise signal is a signal having an opposite phase, equal frequency, and equal amplitude to the first noise signal;

[0069] A signal superposition module is used to superimpose the first noise signal and the anti-phase noise signal to offset the internal noise.

[0070] The embodiment of the present application further discloses an electronic device, comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0071] The memory is used to store computer programs;

[0072] The processor is used to implement the method described in the embodiment of the present application when executing the program stored in the memory.

[0073] The embodiment of the present application further discloses a computer-readable storage medium having instructions stored thereon, which, when executed by one or more processors, causes the processors to execute the method described in the embodiment of the present application.

[0074] The embodiments of the present application include the following advantages:

[0075] The embodiments of the present application identify the current driving state of the vehicle and detect the internal noise generated by the vehicle in the current driving state; determine the initial noise reduction parameters corresponding to the current driving state, obtain noise information from the initial noise reduction parameters, adjust the noise information to obtain target noise reduction parameters, and use the target noise reduction parameters to actively reduce the internal noise. By using the initial noise reduction parameters based on the current driving state of the vehicle, the embodiments of the present application achieve differentiated noise reduction parameters for different operating conditions. The initial noise reduction parameters will be further adjusted based on the actual noise reduction characteristics of the initial noise reduction parameters to obtain more accurate target noise reduction parameters for active noise reduction, thereby improving the noise reduction effect and ensuring the stability of the control system. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 This is a flowchart of the steps of an active noise reduction method for a vehicle provided in an embodiment of the present application;

[0077] Figure 2 is a schematic diagram of the Hermite spline curve provided in the embodiments of the present application;

[0078] Figure 3Schematic diagram of optimizing a noise reduction parameter curve based on a Hermite spline curve provided in an embodiment of the present application;

[0079] Figure 4 This is a structural block diagram of an active noise reduction device for a vehicle provided in an embodiment of the present application;

[0080] Figure 5 This is a block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0081] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0082] When a vehicle changes its driving state, such as accelerating, decelerating, or turning, noise is generated inside the vehicle due to changes in engine speed, transmission shifting, tire-road friction, and wind noise. On the one hand, noise can affect passenger comfort, especially during long drives or at high speeds, where it can exacerbate fatigue. Long-term exposure to high-noise environments can damage hearing and even affect passengers' mental health. On the other hand, noise can distract the driver, especially in complex road conditions. Reducing noise can help improve driving safety. Therefore, in such situations, active noise reduction is necessary.

[0083] Active Noise Control (ANC) is a technology that actively cancels out in-car noise while the vehicle is in motion. ANC uses microphones inside the vehicle to capture noise signals generated by the engine, tires, wind, and other sources. It then analyzes and processes these signals, generating an anti-phase sound wave based on the processed signal to cancel out the original noise signal.

[0084] In practice, active noise reduction technology requires real-time adjustment of noise reduction parameters to adapt to the changing noise environment under different driving conditions. However, the transitions between driving conditions (such as acceleration, deceleration, gear shifting, and cornering) are often accompanied by sudden changes in noise characteristics, resulting in discontinuities or sudden changes in noise reduction parameters at the moment of transition. This sudden change not only affects the smooth transition of the noise reduction effect but may also generate new noise, thereby reducing the overall noise reduction performance.

[0085] Reference Figure 1 , shows a flowchart of a method for active noise reduction of a vehicle provided in an embodiment of the present application, which may specifically include the following steps:

[0086] Step 101 : Identify the current driving state of the vehicle and detect the interior noise generated by the vehicle in the current driving state.

[0087] In an embodiment of the present application, before actively reducing noise on a vehicle, it is necessary to first identify the current driving state of the vehicle so that active noise reduction can be performed more accurately according to the current driving state. Specifically, identification can be performed through sensors. For example, the speed of the vehicle can be measured by a vehicle speed sensor to determine whether the vehicle is stationary, traveling at a low speed, or traveling at a high speed; the acceleration of the vehicle can be measured by an acceleration sensor to determine whether the vehicle is accelerating, decelerating, or traveling at a constant speed; the steering angle of the steering wheel can be measured by a steering angle sensor to determine whether the vehicle is turning; the engine speed can be measured by an engine speed sensor to determine the working state of the engine (such as idling, accelerating, decelerating, etc.); the gear position and shifting state of the gearbox can be measured by a transmission sensor to determine the power output state of the vehicle; and the pressure of the brake pedal or the pressure of the brake system can be measured by a brake sensor to determine whether the vehicle is braking.

[0088] The current driving state of the vehicle is then comprehensively judged through the data measured by the sensor. For example, when the vehicle speed is zero and the engine is idling, the vehicle is at a standstill; when the vehicle speed is stable and the engine speed is stable, the vehicle is at a constant speed; when the vehicle speed increases and the engine speed increases, the vehicle is in an accelerating state; when the vehicle speed decreases, the engine speed decreases or enters a braking state, the vehicle is in a decelerating state; when the steering angle changes, the vehicle speed and acceleration may change, the vehicle is in a turning state. This application does not specifically limit the determination of the vehicle's driving state.

[0089] In one embodiment of the present application, multiple microphones may be installed in the vehicle to capture noise signals from different directions and positions.

[0090] Step 102: Determine initial noise reduction parameters corresponding to the current driving state and obtain noise information in the initial noise reduction parameters. The initial noise reduction parameters are used to represent characteristic parameters of active noise reduction operation, and the noise information is used to represent characteristic parameter values of the initial noise reduction parameters in the current driving state.

[0091] In an embodiment of the present application, before identifying the current driving state of the vehicle, it is necessary to generate a noise reduction parameter set. The noise reduction parameter set includes noise reduction parameters corresponding to several vehicle driving states, and is used to match the corresponding noise reduction parameters according to the vehicle driving state. The specific steps for generating the noise reduction parameter set are as follows:

[0092] Classify the vehicle's driving state. In one feasible embodiment, various parameter value ranges corresponding to a vehicle's driving state, such as speed, acceleration, transmission gear, steering angle, etc., can be pre-set. Then, when the vehicle's parameter value at that moment falls within a pre-set parameter value range, the vehicle is determined to be in the driving state corresponding to that parameter range, thereby achieving driving state classification.

[0093] The vehicle's noise signal is collected and a first noise reduction parameter corresponding to the noise signal is obtained. The noise signal is collected for each driving state of the vehicle in advance, and the first noise reduction parameter for active noise reduction under normal circumstances is obtained. The first noise reduction parameter can also be understood as the initial value of the noise reduction parameter under various vehicle operating conditions (i.e., different driving states).

[0094] Under each type of driving state, the preset calibration algorithm is run to perform convergence calculation on the first noise reduction parameter to obtain the second noise reduction parameter. The second noise reduction parameter can be understood as the noise reduction parameter calibration value of the vehicle under various working conditions. The specific noise reduction parameter calibration value can be obtained by manual calibration or according to the calibration algorithm. This application does not impose any specific restrictions on this. In one embodiment, the noise reduction parameters under various driving conditions can be set by the calibration algorithm, so that the active noise reduction under various driving conditions has excellent effects. The noise reduction parameters include but are not limited to the iteration step size, the variable step size influencing factor, the leakage factor, etc. These noise reduction parameters show a trend of step-by-step change. Common calibration algorithms include the minimum mean square error algorithm, the recursive least squares algorithm, the Kalman filter algorithm, the genetic algorithm and the particle swarm optimization algorithm. This application does not impose any restrictions on the specific algorithm selection.

[0095] When performing convergence calculations, it is necessary to perform spectral analysis on the noise signal to obtain the amplitude, phase, and frequency of the noise signal, and generate a target signal based on the amplitude, phase, and frequency of the noise signal. The target signal is a signal with the opposite phase to the noise signal and the same amplitude and frequency.

[0096] The target signal is the ideal signal generated when active noise reduction is performed. It is the inverted signal of the noise signal. When the target signal is superimposed on the noise signal, it can completely cancel out the internal noise. The control signal is the signal actually generated by processing and analyzing the noise signal. When active noise reduction is actually performed, it is difficult to generate the target signal due to various error reasons. Therefore, it is necessary to perform multiple iterative optimizations on the actually generated control signal until the error between the control signal and the target signal is within the preset convergence range, that is, the control signal is infinitely close to the target signal. Specifically, the following steps are included:

[0097] Actively reduce noise on the noise signal according to the first noise reduction parameter to generate a control signal for the noise signal;

[0098] The error between the control signal and the target signal is calculated, and the error is used to reversely update the first noise reduction parameter to obtain the second noise reduction parameter.

[0099] After generating the second noise reduction parameters, the second noise reduction parameters are aggregated to generate a noise reduction parameter set.

[0100] After generating the noise reduction parameter set, the embodiment of the present application can match the initial noise reduction parameters corresponding to the current driving state from the noise reduction parameter set based on the current driving state of the vehicle. In the noise reduction parameter set, each type of driving state has a corresponding noise reduction parameter.

[0101] For the initial noise reduction parameters corresponding to the vehicle's current driving state, a noise reduction parameter curve corresponding to the initial noise reduction parameters can be generated. The noise reduction parameter curve represents the variation of the noise reduction parameters under different driving states. The characteristic parameter values corresponding to these corresponding variation values are used as noise information for active noise reduction.

[0102] Step 103: Adjust the noise information to obtain target noise reduction parameters, and use the target noise reduction parameters to actively reduce the internal noise.

[0103] In the embodiment of the present application, adjusting the noise information to obtain the target noise reduction parameter is essentially performed by adjusting the noise reduction parameter curve. When the vehicle suddenly changes its driving state during driving, the noise reduction parameter curve is specifically manifested as a step mutation point. The step mutation point will affect the active noise reduction control effect and the stability of the control system. Therefore, it is necessary to optimize and adjust the step mutation point to a smooth point, which specifically includes the following steps:

[0104] Generate a noise reduction parameter curve corresponding to the initial noise reduction parameters, and determine the mutation point corresponding to the noise information on the noise reduction parameter curve;

[0105] The noise information is adjusted until the mutation point is converted into a smooth point, and the target noise reduction parameter corresponding to the smooth point is obtained.

[0106] Specifically, when adjusting the mutation point to a smooth point, each step mutation point can be smoothed by using a Hermite spline curve. The Hermite spline curve is generally defined as formula (1):

[0107]

[0108] Where s represents the normalized arc length, satisfying 0≤s≤1; is the vector pointing to the starting point of the noise reduction parameter curve, at this time s=0; is the vector pointing to the end point of the noise reduction parameter curve, and s = 1; and are the tangent vectors of the starting and ending points of the noise reduction parameter curve, which are used to control the direction and shape of the curve. Figure 2 shown.

[0109] Considering that the active noise reduction control parameter curve is a rectangular coordinate system, formula (1) can be simplified as follows:

[0110]

[0111] According to the step-wise shape of the control parameters, in order to facilitate subsequent calculations, the tangent vector can be used as the vertex value and Perform a replacement operation, the replacement form is:

[0112]

[0113] Where α and β are curvature control parameters. Different curve curvature controls can be achieved by controlling the values of α and β. Substituting formulas (3) and (4) into formula (2), we get:

[0114]

[0115]

[0116] The design of the Hermite spline curve can be completed by calculating formula (5).

[0117] In one embodiment, adjusting the noise information until the mutation point is converted into a smooth point specifically includes the following steps:

[0118] Set the starting control point and the ending control point before and after the mutation point, and determine the coverage of the starting control point and the ending control point as the interpolation interval;

[0119] Get the first vector of the starting control point and the second vector of the ending control point;

[0120] Calculate the first tangent vector of the starting control point and the second tangent vector of the ending control point using the first vector of the starting control point and the second vector of the ending control point;

[0121] The starting control point and the ending control point are used for calculation to obtain the virtual control point;

[0122] Obtaining curvature control parameters for the first tangent vector and the second tangent vector;

[0123] The first tangent vector of the starting control point and the second tangent vector of the ending control point are adjusted using the curvature control parameter and the virtual control point to obtain a first target tangent vector of the starting control point and a second target tangent vector of the ending control point;

[0124] Obtaining basis functions for the interpolation interval, the basis functions including position basis functions and geometric adjustment basis functions;

[0125] Substitute the first vector of the starting control point and the second vector of the ending control point into the position basis function, and substitute the first target tangent vector of the starting control point and the second target tangent vector of the ending control point into the geometric adjustment basis function to obtain the coordinates of the interpolation point corresponding to the interpolation interval;

[0126] The coordinates of the interpolation points are used to convert the sudden points into smooth points.

[0127] In the embodiment of the present application, a starting control point H(0) and an ending control point H(1) are set before and after the mutation point, and their coverage range is defined as the interpolation interval 0≤s≤1; the position vector of the starting control point is obtained. and tangent vector and the position vector of the terminal control point and tangent vector Introduction

[0128] The initial step mutation curve is converted into a curve with a smooth transition. In the embodiment of the present application, the virtual control point is used to determine the bending direction of the noise reduction parameter curve (i.e., the Hermite spline curve) (such as whether the curve is convex or concave), and the curvature control parameter adjusts the direction and length of the tangent vector of the starting control point and the ending control point to control the curvature of the curve, and then combines the curvature control parameter and the virtual control point to adjust the bending degree and direction of the noise reduction parameter curve at the starting control point and the ending control point. Finally, a plurality of interpolation points are generated in the interpolation interval by the Hermite basis function, and a smooth noise reduction parameter curve is formed by connecting the plurality of interpolation points to achieve fine control of the smooth transition of the curve, thereby achieving a smooth transition of the noise reduction parameter curve.

[0129] Reference Figure 3 ,After the mutation point is adjusted to a smooth point, the noise reduction ,parameter curve is also adjusted from a step mutation curve to a ,smoothly connected curve, where rpm is the engine speed.

[0130] In step 103, when actively reducing internal noise using the target noise reduction parameters, the captured internal noise needs to be preprocessed, including filtering, noise reduction, and amplification, to improve signal quality. An anti-phase noise signal for active noise reduction is generated based on the target noise reduction parameters. Specifically, the following steps are included:

[0131] Converting the internal noise into a first noise signal, and obtaining the phase, frequency, and amplitude of the first noise signal;

[0132] generating an anti-phase noise signal according to the target noise reduction parameter, wherein the anti-phase noise signal is a signal having an opposite phase, equal frequency, and equal amplitude to the first noise signal;

[0133] The first noise signal and the inverted noise signal are superimposed to cancel the internal noise.

[0134] The embodiments of the present application identify the current driving state of the vehicle and detect the internal noise generated by the vehicle in the current driving state; determine the initial noise reduction parameters corresponding to the current driving state, obtain noise information from the initial noise reduction parameters, adjust the noise information to obtain target noise reduction parameters, and use the target noise reduction parameters to actively reduce the internal noise. By using the initial noise reduction parameters specific to the current driving state of the vehicle, the embodiments of the present application achieve differentiated noise reduction parameters for different operating conditions. The initial noise reduction parameters will be further adjusted based on the actual noise reduction characteristics of the initial noise reduction parameters to obtain more accurate target noise reduction parameters for active noise reduction, thereby improving the noise reduction effect and ensuring the stability of the control system.

[0135] It should be noted that for the method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present application are not limited by the order of the actions described, because according to the embodiments of the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present application.

[0136] Reference Figure 4 , shows a structural block diagram of an active noise reduction device for a vehicle provided in an embodiment of the present application, which may specifically include the following modules:

[0137] Noise detection module 401, used to identify the current driving state of the vehicle and detect the internal noise generated by the vehicle in the current driving state;

[0138] Parameter determination module 402, configured to determine initial noise reduction parameters corresponding to the current driving state and obtain noise information from the initial noise reduction parameters, wherein the initial noise reduction parameters are used to represent characteristic parameters of active noise reduction operation, and the noise information is used to represent characteristic parameter values of the initial noise reduction parameters under the current driving state;

[0139] The active noise reduction module 403 is configured to adjust the noise information to obtain target noise reduction parameters, and perform active noise reduction on the internal noise using the target noise reduction parameters.

[0140] Optionally, the device further comprises:

[0141] A classification module, used to classify the driving status of the vehicle;

[0142] An acquisition module, configured to acquire a noise signal of the vehicle in each type of driving state and obtain a first noise reduction parameter corresponding to the noise signal;

[0143] a calculation module, configured to run a preset calibration algorithm to perform convergence calculation on the first noise reduction parameter under each type of driving state, and obtain a second noise reduction parameter corresponding to the driving state;

[0144] The set generation module is used to summarize the second noise reduction parameters corresponding to each type of driving state to generate a noise reduction parameter set.

[0145] Optionally, the computing module further includes:

[0146] The spectrum analysis module is used to perform spectrum analysis on the noise signal to obtain the amplitude, phase and frequency of the noise signal;

[0147] A target signal generation module is used to generate a target signal based on the amplitude, phase and frequency of the noise signal. The target signal is a signal with a phase opposite to that of the noise signal and the same amplitude and frequency;

[0148] a control signal generating module, configured to perform active noise reduction on the noise signal according to the first noise reduction parameter and generate a control signal for the noise signal;

[0149] The reverse updating module is used to calculate the error between the control signal and the target signal, and use the error to reversely update the first noise reduction parameter to obtain the second noise reduction parameter.

[0150] Optionally, the parameter determination module 402 is specifically configured to match initial noise reduction parameters corresponding to the current driving state from the noise reduction parameter set.

[0151] Optionally, the active noise reduction module 403 includes:

[0152] A curve generation module is used to generate a noise reduction parameter curve corresponding to the initial noise reduction parameters and determine the mutation point corresponding to the noise information on the noise reduction parameter curve;

[0153] The target noise reduction parameter acquisition module is used to adjust the noise information until the mutation point is converted into a smooth point, and obtain the target noise reduction parameter corresponding to the smooth point.

[0154] Optionally, the target noise reduction parameter acquisition module includes:

[0155] A control point setting module is used to set a starting control point and an ending control point before and after the mutation point, and determine the coverage range of the starting control point and the ending control point as the interpolation interval;

[0156] A vector calculation module is used to obtain a first vector of a starting control point and a second vector of an ending control point; and to calculate using the first vector and the second vector to obtain a first tangent vector of the starting control point and a second tangent vector of the ending control point;

[0157] A virtual control point setting module is used to calculate using the starting control point and the ending control point to obtain a virtual control point;

[0158] a curvature control parameter acquisition module, configured to acquire curvature control parameters for the first tangent vector and the second tangent vector;

[0159] a vector adjustment module, configured to adjust the first tangent vector and the second tangent vector using the curvature control parameter and the virtual control point to obtain a first target tangent vector of the starting control point and a second target tangent vector of the ending control point;

[0160] A basis function acquisition module is used to obtain basis functions for the interpolation interval, where the basis functions include position basis functions and geometric adjustment basis functions;

[0161] A coordinate value acquisition module is used to substitute the first vector and the second vector into the position basis function, and substitute the first target tangent vector and the second target tangent vector into the geometric adjustment basis function to obtain the coordinates of the interpolation point corresponding to the interpolation interval;

[0162] The mutation point conversion module is used to convert the mutation point into a smooth point according to the coordinates of the interpolation point.

[0163] Optionally, the active noise reduction module 403 further includes:

[0164] a noise conversion module, configured to convert the internal noise into a first noise signal and obtain the phase, frequency, and amplitude of the first noise signal;

[0165] an anti-phase noise signal generating module, configured to generate an anti-phase noise signal according to a target noise reduction parameter, wherein the anti-phase noise signal is a signal having an opposite phase, equal frequency, and equal amplitude to the first noise signal;

[0166] The signal superposition module is used to superimpose the first noise signal and the anti-phase noise signal to offset the internal noise.

[0167] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0168] The embodiments of the present application identify the current driving state of the vehicle and detect the internal noise generated by the vehicle in the current driving state; determine the initial noise reduction parameters corresponding to the current driving state, obtain noise information from the initial noise reduction parameters, adjust the noise information to obtain target noise reduction parameters, and use the target noise reduction parameters to actively reduce the internal noise. By using the initial noise reduction parameters based on the current driving state of the vehicle, the embodiments of the present application achieve differentiated noise reduction parameters for different operating conditions. The initial noise reduction parameters will be further adjusted based on the actual noise reduction characteristics of the initial noise reduction parameters to obtain more accurate target noise reduction parameters for active noise reduction, thereby improving the noise reduction effect and ensuring the stability of the control system.

[0169] Figure 5 A block diagram of an electronic device for implementing various embodiments of the present application.

[0170] The electronic device includes but is not limited to: a processor 501, a communication interface 502, a memory 503 and a communication bus 504, wherein the processor 501, the communication interface 502, and the memory 503 communicate with each other via the communication bus 504;

[0171] Memory 503, used for storing computer programs;

[0172] The processor 501 is configured to execute the program stored in the memory 503 by performing the following steps:

[0173] Identify the current driving state of the vehicle and detect the interior noise generated by the vehicle in the current driving state;

[0174] Determining initial noise reduction parameters corresponding to the current driving state and obtaining noise information from the initial noise reduction parameters, wherein the initial noise reduction parameters are used to represent characteristic parameters of active noise reduction operation, and the noise information is used to represent characteristic parameter values of the initial noise reduction parameters under the current driving state;

[0175] The noise information is adjusted to obtain target noise reduction parameters, and the target noise reduction parameters are used to actively reduce the internal noise.

[0176] The bus mentioned in the terminal can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. This bus can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is used in the figure, but this does not mean that there is only one bus or only one type of bus.

[0177] The memory may include random access memory (RAM) or non-volatile memory, such as at least one disk storage. Alternatively, the memory may be at least one storage device located away from the processor.

[0178] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, and discrete hardware components.

[0179] The present application also provides a computer-readable storage medium having instructions stored thereon. When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the active noise reduction method for a vehicle in the aforementioned embodiment.

[0180] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0181] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0182] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

[0183] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the embodiments of this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0184] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0185] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0186] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0187] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0188] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

[0189] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for active noise reduction of a vehicle, characterized in that: The method comprises: identifying a current driving state of a vehicle and detecting interior noise generated by the vehicle in the current driving state; determining initial noise reduction parameters corresponding to the current driving state, and obtaining noise information from the initial noise reduction parameters, wherein the initial noise reduction parameters are used to represent characteristic parameters of active noise reduction operation, and the noise information is used to represent characteristic parameter values of the initial noise reduction parameters under the current driving state; The noise information is adjusted to obtain a target noise reduction parameter, and the target noise reduction parameter is used to actively reduce the internal noise.

2. The method according to claim 1, characterized in that Before identifying the current driving state of the vehicle, the method further includes: classifying the driving state of the vehicle; collecting a noise signal of the vehicle in each of the driving states, and obtaining a first noise reduction parameter corresponding to the noise signal; Running a preset calibration algorithm to perform convergence calculation on the first noise reduction parameter to obtain a second noise reduction parameter corresponding to the driving state; The second noise reduction parameters corresponding to each type of the driving state are aggregated to generate a noise reduction parameter set.

3. The method according to claim 2, characterized in that The running of a preset calibration algorithm to perform convergence calculation on the first noise reduction parameter to obtain a second noise reduction parameter corresponding to the driving state includes: Performing spectrum analysis on the noise signal to obtain the amplitude, phase and frequency of the noise signal; generating a target signal according to the amplitude, phase and frequency of the noise signal, wherein the target signal is a signal having a phase opposite to that of the noise signal and the same amplitude and frequency as that of the noise signal; Actively reduce noise on the noise signal according to the first noise reduction parameter, and generate a control signal for the noise signal; An error between the control signal and the target signal is calculated, and the first noise reduction parameter is inversely updated using the error to obtain the second noise reduction parameter.

4. The method according to claim 2, characterized in that The determining of the initial noise reduction parameters corresponding to the current driving state includes: The initial noise reduction parameter corresponding to the current driving state is matched from the noise reduction parameter set.

5. The method according to claim 1, wherein The adjusting the noise information to obtain a target noise reduction parameter includes: generating a noise reduction parameter curve corresponding to the initial noise reduction parameter, and determining a mutation point corresponding to the noise information on the noise reduction parameter curve; The noise information is adjusted until the mutation point is converted into a smooth point, and the target noise reduction parameter corresponding to the smooth point is obtained.

6. The method according to claim 5, characterized in that The adjusting the noise information until the mutation point is converted into a smooth point includes: Setting a starting control point and an ending control point before and after the mutation point, and determining the coverage range of the starting control point and the ending control point as the interpolation interval; Obtaining a first vector of the starting control point and a second vector of the ending control point; Calculating using the first vector and the second vector to obtain a first tangent vector corresponding to the starting control point and a second tangent vector corresponding to the ending control point; Calculating using the starting control point and the ending control point to obtain a virtual control point; Obtaining curvature control parameters for the first tangent vector and the second tangent vector; Adjusting the first tangent vector and the second tangent vector using the curvature control parameter and the virtual control point to obtain a first target tangent vector of the starting control point and a second target tangent vector of the ending control point; Acquire basis functions for the interpolation interval, where the basis functions include position basis functions and geometric adjustment basis functions; Substituting the first vector and the second vector into the position basis function, and substituting the first target tangent vector and the second target tangent vector into the geometric adjustment basis function, to obtain the coordinates of the interpolation point corresponding to the interpolation interval; The coordinates of the interpolation points are used to convert the mutation points into the smooth points.

7. The method according to claim 1, characterized in that The actively reducing the internal noise by using the target noise reduction parameter includes: Converting the internal noise into a first noise signal, and acquiring the phase, frequency, and amplitude of the first noise signal; generating an anti-phase noise signal according to the target noise reduction parameter, wherein the anti-phase noise signal is a signal having an opposite phase, equal frequency, and equal amplitude to the first noise signal; The first noise signal and the anti-phase noise signal are superimposed to cancel the internal noise.

8. An active noise reduction device for a vehicle, characterized in that: The device comprises: a noise detection module, configured to identify a current driving state of a vehicle and detect interior noise generated by the vehicle in the current driving state; a parameter determination module, configured to determine initial noise reduction parameters corresponding to the current driving state, and obtain noise information from the initial noise reduction parameters, wherein the initial noise reduction parameters are used to represent characteristic parameters of active noise reduction operation, and the noise information is used to represent characteristic parameter values of the initial noise reduction parameters under the current driving state; The active noise reduction module is configured to adjust the noise information to obtain target noise reduction parameters, and to perform active noise reduction on the internal noise using the target noise reduction parameters.

9. An electronic device, characterized in that: comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; The memory is used to store computer programs; The processor is configured to implement the method according to any one of claims 1 to 7 when executing a program stored in the memory.

10. A computer-readable storage medium having instructions stored thereon, which, when executed by one or more processors, cause the processors to perform the method according to any one of claims 1 to 7.

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