A vehicle-mounted active noise control system and a fusion method thereof

Abstract

The application discloses a kind of vehicle active noise control systems and fusion method thereof, system includes acceleration sensor, microphone, speaker and controller, acceleration sensor, microphone and controller access vehicle A2B bus, controller also accesses vehicle CAN bus, controller includes engine noise active controller and road noise active controller, the sound signal picked up by microphone is output as error signal to engine noise active controller and road noise active controller respectively;Road noise active controller and engine noise active controller generate first excitation signal and second excitation signal using signal respectively, and controller outputs two excitation signals to corresponding speaker after fusion and runs.The vehicle active noise control system and fusion method thereof provided by the application realize the fusion of car ENC algorithm and RNC algorithm, reduce the consumption of computing power, and reduce the number and cost of vehicle microphones by sharing the same set of microphones.

Description

Technical Field

[0001] This invention relates to the field of active noise reduction technology, and in particular to an on-board active noise control system and its fusion method. Background Technology

[0002] Traditional passive noise reduction solutions struggle to achieve significant noise reduction for the engine noise and tire noise generated by road surface excitation in gasoline-powered passenger vehicles during operation, and are also costly. Active noise control methods are generally employed. Engine Noise Active Control (ENC) uses the engine speed read from the vehicle's infotainment system as the reference signal for its algorithm, employing analog microphones to pick up error sound signals, and mostly uses time-domain algorithms for control. Road Noise Active Control (RNC) uses vibration signals collected by accelerometers deployed on the vehicle body as the reference signal for its algorithm, employing A2B microphones to pick up error sound signals; the accelerometers and microphones are connected on an A2B link. Both systems require microphones to pick up error sound signals for iterative algorithm calculations. However, due to differences in hardware and algorithm logic, the two systems currently operate independently, using two DSP controllers and two sets of microphones, increasing the cost of controllers and microphones, as well as the complexity of the in-vehicle audio wiring harness.

[0003] The above background information is provided only to assist in understanding the inventive concept and technical solution of this invention. It does not necessarily belong to the prior art of this patent application, nor does it necessarily provide technical teaching. In the absence of clear evidence that the above information was disclosed before the filing date of this patent application, the above background information should not be used to evaluate the novelty and inventiveness of this application. Summary of the Invention

[0004] To overcome the shortcomings of existing technologies, this invention provides an on-board active noise control system and its fusion method, the technical solution of which is as follows:

[0005] On one hand, the present invention provides an on-board active noise control system, including an acceleration sensor, a microphone, a speaker, and a controller. The acceleration sensor, microphone, and controller are connected to the vehicle's A2B bus, and the controller is also connected to the vehicle's CAN bus. The controller includes an active engine noise controller and an active road noise controller. The sound signal picked up by the microphone is used as an error signal and is output to the active engine noise controller and the active road noise controller respectively through the A2B bus.

[0006] The engine noise active controller connects to the vehicle's infotainment system via the CAN bus to obtain engine operating signals, and uses a time-domain point-by-point filtering algorithm to perform adaptive signal processing on the engine operating signals and error signals to obtain the first excitation signal.

[0007] The road noise active controller obtains the vibration signal collected by the acceleration sensor through the A2B bus, and outputs a second excitation signal through an adaptive filter. The adaptive filter is updated in the frequency domain by performing Fourier transform on the vibration signal and the error signal.

[0008] The controller merges the first excitation signal and the second excitation signal and outputs the result to the corresponding speaker for operation.

[0009] Furthermore, the signal processing of the active road noise controller includes the following steps:

[0010] Vibration signal x l (n) serves as the reference signal for the active road noise controller. It undergoes convolution processing via an adaptive filter to be output as a secondary sound source signal to the loudspeaker. The calculation formula for the first excitation signal of the j-th loudspeaker channel is as follows:

[0011]

[0012] Among them, w jl (n) is a time-reversed adaptive filter with order N. c l is the reference signal channel index value of the road noise active controller, L is the maximum value of the reference signal channel, j is the speaker position index value, n is the index value of the sampled signal, and x is the maximum value of the sampled signal. l (n) represents the vibration signal, derived from the currently acquired N. c It consists of 1 signal point.

[0013] Furthermore, the updating of the adaptive filter includes the following steps:

[0014] The vibration signal and error signal are subjected to windowing processing;

[0015] The windowed vibration signal and error signal are converted to frequency domain signals using Fourier transform;

[0016] By utilizing the secondary channel transfer function between the loudspeaker and the microphone, the frequency domain transformed signal of the vibration signal is filtered by the secondary channel, and combined with the frequency domain transformed signal of the error signal, the frequency domain gradient at the corresponding frequency point is obtained, thereby updating the adaptive filter, and the updated adaptive filter is transformed to the time domain for application.

[0017] Furthermore, the signal processing of the active engine noise controller includes the following steps:

[0018] The current engine noise frequency is obtained based on the speed and order information in the engine operating signal, and the calculation formula is as follows:

[0019]

[0020] Where Speed ​​is the engine speed, Order is the engine order, and k is the control frequency index value, which also corresponds to the order index value.

[0021] The engine noise frequency is input into a sine wave generator to produce two sinusoidal signals with a 90° phase difference, which serve as reference signals for the active engine noise controller, denoted as xs. k (n) and xc k (n), its calculation formula is as follows:

[0022] xs k (n)=Asin(2πf k t),

[0023] xc k (n)=Acos(2πf k t)

[0024] Where A is the reference signal gain, used to adjust the amplitude of the reference signal; f k Where is the engine noise frequency, and t is the vibration time;

[0025] The two sinusoidal signals are linearly filtered with their respective weighting coefficients to obtain the second excitation signal for the loudspeaker. The calculation formula is as follows:

[0026]

[0027] Where j is the speaker location index value, w qkj (n) represents the weighting coefficients, where q is the reference signal number at each control frequency, q=0 corresponds to sine, and q=1 corresponds to cosine.

[0028] Furthermore, the reference signal of the active engine noise controller is subjected to secondary channel filtering. The calculation formula for the filtered reference signal obtained from the secondary channel identification is as follows:

[0029]

[0030]

[0031] Where m is the index value of the secondary channel time-domain unit impulse response sequence, i is the microphone position index value, and s ij For transfer functions;

[0032] The weight coefficients in the active engine noise controller are updated using the reference signal filtered by the secondary channel, and the update formula is as follows:

[0033]

[0034]

[0035] Where μ′ is the step size factor, γ is the leakage coefficient, β is the anti-echo coefficient, p is the number of microphones used in the system, and e i (n) represents the error signal.

[0036] Furthermore, in the updating process of the adaptive filter, the vibration signal and error signal need to be passed through a bandpass filter in advance to filter out high-frequency signal information and undergo downsampling processing before use.

[0037] Furthermore, before the first excitation signal and the second excitation signal are fused, they need to be upsampled and high-frequency information is filtered out by a low-pass filter. The cutoff frequency of the low-pass filter is the same as the cutoff frequency of the band-pass filter.

[0038] On the other hand, the present invention provides a fusion method for an on-board active noise control system, comprising:

[0039] An active engine noise controller and an active road noise controller are integrated to form a system controller. The control algorithm of the system controller divides the in-vehicle noise reduction task into a time-domain task and a frequency-domain task. The time-domain task includes signal reception, secondary control sound generation and fusion, and acquisition of weight coefficients of the active engine noise controller. The frequency-domain task includes parameter updates of the adaptive filter in the active road noise controller. In the time-domain task, the active road noise controller and the active engine noise controller respectively generate a first excitation signal and a second excitation signal as secondary control sounds, and fuse them to output to the corresponding vehicle speakers for in-vehicle noise reduction.

[0040] Furthermore, in the time-domain task, the received signals include engine speed signals, vehicle body vibration signals, and error signals fed back from the in-vehicle microphones.

[0041] Furthermore, the road noise active controller obtains a first excitation signal using the vibration signal, and updates the road noise active controller in the frequency domain using the vibration signal and the error signal; the engine noise active controller obtains a second excitation signal using the speed signal, and updates the engine noise active controller in the time domain using the speed signal and the error signal.

[0042] The beneficial effects of the technical solution provided by this invention are as follows: by optimizing the algorithm to achieve real-time control of engine noise and tire road noise on a single DSP controller, the computing power consumption is reduced, and by sharing the same set of microphones, the number and cost of vehicle microphones are reduced, and the complexity of in-vehicle audio wiring harnesses is reduced. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a schematic diagram of the structural framework of the vehicle-mounted active noise control system provided in an embodiment of the present invention;

[0045] Figure 2 This is a schematic diagram of the hardware connection in the vehicle-mounted active noise control system provided in an embodiment of the present invention;

[0046] Figure 3 This is a schematic diagram of the algorithm fusion process in the fusion method of the vehicle active noise control system provided in the embodiment of the present invention;

[0047] The reference numerals in the attached figures are as follows: 100-accelerometer sensor, 101-A2B bus, 102-microphone, 103-speaker, 104-vehicle infotainment system, 105-controller. Detailed Implementation

[0048] To enable those skilled in the art to better understand the present invention and its objectives, technical solutions, and advantages, the technical solutions in the embodiments of the present invention are clearly and completely described below with reference to specific embodiments and accompanying drawings. It should be noted that implementations not illustrated or described in the accompanying drawings are forms known to those skilled in the art. Furthermore, while this document provides examples of parameters containing specific values, it should be understood that the parameters need not be exactly equal to the corresponding values, but can approximate the corresponding values ​​within acceptable error tolerances or design constraints. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort should fall within the scope of protection of the present invention. In addition, the terms "comprising" and "having," and any variations thereof, in the specification and claims of this invention are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices.

[0049] In one embodiment of the present invention, an on-board active noise control system is provided, which is a fusion system formed by integrating an engine noise active control system (ENC) and a road noise active control system (RNC). See [link to documentation]. Figure 1 It includes an acceleration sensor 100, a microphone 102, a speaker 103, and a controller 105. Multiple acceleration sensors are installed outside the vehicle body, and multiple microphones and speakers are installed inside the vehicle body. The acceleration sensors, microphones, and controller are connected to the vehicle's A2B bus 101. The controller is also connected to the vehicle's CAN bus. The controller includes an active engine noise controller and an active road noise controller. The sound signals picked up by the microphones are used as error signals and are output to the active engine noise controller and the active road noise controller respectively through the A2B bus.

[0050] The engine noise active controller connects to the vehicle's infotainment system 104 via a CAN bus to obtain engine operating signals, and uses a time-domain point-by-point filtering algorithm to adaptively process the engine operating signals and error signals to obtain a first excitation signal; the road noise active controller obtains the vibration signals collected by the acceleration sensor via an A2B bus, and outputs a second excitation signal through an adaptive filter, wherein the adaptive filter is updated in the frequency domain by performing Fourier transform on the vibration signals and error signals; the controller fuses the first excitation signal and the second excitation signal and outputs it to the corresponding speaker for operation.

[0051] Specifically, see Figure 1 and Figure 2 Four microphones are placed inside the vehicle as error microphones for the RNC and ENC fusion system, and four speakers in the doors are used as secondary sound sources for the fusion system. A set of microphones connected to the A2B bus picks up signals as error signal inputs for the RNC and ENC. The microphones collect sound signals in real time and transmit them to the RNC and ENC, thereby calculating and generating two secondary control sounds. These signals are then added together and fused into a single signal before being transmitted to the speakers, and then emitted through the speakers.

[0052] The vibration signal and error signal need to be passed through a bandpass filter to remove high-frequency signal information and downsampled before use. The first excitation signal and the second excitation signal need to be upsampled before merging and then filtered out high-frequency information by a low-pass filter. The cutoff frequency of the low-pass filter is the same as that of the bandpass filter.

[0053] The signal processing of the active road noise controller includes the following steps:

[0054] Vibration signal x l (n) serves as the reference signal for the active road noise controller. It undergoes convolution processing via an adaptive filter to be output as a secondary sound source signal to the loudspeaker. The calculation formula for the first excitation signal of the j-th loudspeaker channel is as follows:

[0055]

[0056] Among them, w jl (n) is a time-reversed adaptive filter with order N. c l is the reference signal channel index value of the road noise active controller, L is the maximum value of the reference signal channel, j is the speaker position index value, n is the index value of the sampled signal, and x is the maximum value of the sampled signal. l (n) represents the vibration signal, derived from the currently acquired N. c It consists of 1 signal point.

[0057] The updating of the adaptive filter includes the following steps:

[0058] The vibration signal and error signal are windowed; the windowed vibration signal and error signal are converted to frequency domain signals through Fourier transform; the secondary channel transfer function between the loudspeaker and the microphone is used to perform secondary channel filtering on the frequency domain transformed signal of the vibration signal, and combined with the frequency domain transformed signal of the error signal to obtain the frequency domain gradient at the corresponding frequency point, thereby realizing the update of the adaptive filter, and the updated adaptive filter is transformed to the time domain for application.

[0059] The signal processing of the active engine noise controller includes the following steps:

[0060] The current engine noise frequency is obtained based on the speed and order information in the engine operating signal, and the calculation formula is as follows:

[0061]

[0062] Where Speed ​​is the engine speed, Order is the engine order, and k is the control frequency index value, which also corresponds to the order index value.

[0063] The engine noise frequency is input into a sine wave generator to produce two sinusoidal signals with a 90° phase difference, which serve as reference signals for the active engine noise controller, denoted as xs. k (n) and xc k (n), its calculation formula is as follows:

[0064] xs k (n)=Asin(2πf k t),

[0065] xc k (n)=Acos(2πf k t)

[0066] Where A is the reference signal gain, used to adjust the amplitude of the reference signal; f k Where is the engine noise frequency, and t is the vibration time;

[0067] The two sinusoidal signals are linearly filtered with their respective weighting coefficients to obtain the second excitation signal for the loudspeaker. The calculation formula is as follows:

[0068]

[0069] Where j is the speaker location index value, w qkj (n) represents the weighting coefficients, where q is the reference signal number at each control frequency, q=0 corresponds to sine, and q=1 corresponds to cosine.

[0070] The parameter update of the active engine noise controller includes the following steps:

[0071] The reference signal of the active engine noise controller is filtered by a secondary channel. The calculation formula for the filtered reference signal obtained from the secondary channel identification is as follows:

[0072]

[0073]

[0074] Where m is the index value of the secondary channel time-domain unit impulse response sequence, i is the microphone position index value, and s ij For transfer functions;

[0075] The weight coefficients in the active engine noise controller are updated using the reference signal filtered by the secondary channel, and the update formula is as follows:

[0076]

[0077]

[0078] Where μ′ is the step size factor, γ is the leakage coefficient, β is the anti-echo coefficient, p is the number of microphones used in the system, and e i (n) represents the error signal.

[0079] In one embodiment of the present invention, a method for fusing an on-board active noise control system is provided, comprising: fusing an engine noise active controller and a road noise active controller to form a system controller, see [link to relevant documentation]. Figure 3 The control algorithm of the system controller divides the in-vehicle noise reduction task into a time-domain task and a frequency-domain task. The time-domain task includes signal reception, secondary control sound generation and fusion, and acquisition of weight coefficients of the active engine noise controller. The frequency-domain task includes parameter update of the adaptive filter in the active road noise controller. The active road noise controller and the active engine noise controller generate a first excitation signal and a second excitation signal respectively in the time-domain task as secondary control sounds, and fuse them to output to the corresponding vehicle speakers. The fused secondary control sounds reach the corresponding microphones through the secondary channel s(m) between the speakers and the microphones, canceling out the engine noise and road noise in the vehicle, thereby reducing the engine noise and road noise heard by people in the vehicle. The in-vehicle sound signal after active control is picked up by the microphone and used as an error signal e(n) as the input of the system at the next moment.

[0080] In the time-domain task, the received signals include engine speed signals, vehicle vibration signals, and error signals fed back from the in-vehicle microphones. The road noise active controller uses the vibration signals to obtain a first excitation signal, and the road noise active controller updates itself in the frequency domain task using the vibration signals and error signals; the engine noise active controller uses the speed signals to obtain a second excitation signal, and the engine noise active controller updates itself in the time-domain task using the speed signals and error signals.

[0081] Specifically, the fusion method includes the following steps:

[0082] Step 1: The vibration signal x collected by the accelerometer l(n) and the sound signal e collected by the microphone i (n) Perform preprocessing respectively, where l is the RNC reference signal channel index value and i is the microphone position index value.

[0083] Step 1.1 The vibration signal and error signal are passed through a bandpass filter designed to fit the RNC control frequency range to filter out high-frequency signal information and reduce the signal sampling rate to 2kHz for RNC algorithm calculation.

[0084] Step 1.2 The error signal before processing in Step 1.1 is passed through a bandpass filter designed to conform to the ENC control frequency range to filter out high-frequency signal information and reduce the sampling rate of the signal to 2kHz for calculation of the ENC algorithm.

[0085] The cutoff frequencies of the two bandpass filters mentioned above are not the same.

[0086] Step 2: Calculate the reference signal for ENC.

[0087] Step 2.1 Read the engine speed (Speed) from the CAN bus, and then adjust the speed and order accordingly. k Calculate the engine noise frequency f k

[0088]

[0089] Where k is the control frequency index value, and also the corresponding order index value.

[0090] Step 2.2 Based on the frequency f calculated in Step 2.1 k Two sinusoidal signals xs with a 90° phase difference are generated by a sine wave generator. k (n) and xc k (n)

[0091] xs k (n)=Asin(2πf k t), xc k (n)=Acos(2πf k t)

[0092] Where A is the reference signal gain, used to adjust the amplitude of the reference signal. These two signals are used as reference signals for the active engine noise control algorithm.

[0093] Step 3: The vibration signal x obtained in Step 1.1 l (n) serves as the reference signal for the RNC and the adaptive filter w jl (n) Perform a convolution operation to obtain points used to control road noise, which are then output as secondary sound sources to the loudspeakers, where the excitation signal y of the j-th loudspeaker channel is... j(n)

[0094]

[0095] Where w jl (n) is a time-reversed adaptive filter with order N. c l is the RNC reference signal channel index value, L is the maximum value of the reference signal channel, j is the speaker position index value, and x is the maximum value of the reference signal channel. l (n) is the time-series acceleration reference signal vector, derived from the most recently acquired N. c It consists of 1 signal point.

[0096] Step 4: Perform linear filtering on the two signals calculated in Step 2.2 with the weight coefficients to obtain the excitation signal u of the j-th speaker channel. j (n),

[0097]

[0098] Where w qkj (n) represents the weighting coefficients, where q is the reference signal index at each control frequency (q=0 corresponds to sine, q=1 corresponds to cosine).

[0099] The engine noise active controller will be updated using steps 5-7 below:

[0100] Step 5 performs secondary channel filtering on the reference signal of the engine active control algorithm, and then uses the secondary channel filtered reference signal obtained from the secondary channel identification.

[0101]

[0102]

[0103] Where m is the index value of the secondary channel time-domain unit impulse response sequence, i is the microphone position index value, and s ij It is a transfer function, and its value remains fixed after being calibrated.

[0104] Step 6: Weight coefficient update in the engine active control algorithm

[0105]

[0106]

[0107] Where μ′ is the step size factor, γ is the leakage coefficient, β is the anti-echo coefficient, and p is the number of microphones used in the system.

[0108] The road noise active controller will be updated in step 7 below:

[0109] Step 7: Update the adaptive filter in Step 3.

[0110] Step 7.1 Windowing process is applied to the signal before time-frequency transformation.

[0111] The selected window function is expressed as follows:

[0112] h(n)=(1-1.93cos(2πn / N f )+1.29cos(4πn / N f -0.388cos(6πn / N) f )+0.0322cos(8πn / N f )) / 4.634, 0≤n≤N f -1

[0113] Where h(n) represents the flat-top window function, N f The length of the window.

[0114] A windowing operation is performed on the reference signal and error signal obtained in step 1.1. The length N of the constructed time-domain transform vector is... f =2N c

[0115] x′ l (n)=x l (n)h(n)

[0116] e′ l (n)=e i (n)h(n)

[0117] Step 7.2 Convert the windowed reference signal and error signal from Step 7.1 to the frequency domain using Fourier transform.

[0118] Time-frequency transformation of the reference signal:

[0119] X l (n) = FFT[x′ l (n)]

[0120] Where FFT[·] denotes Fast Fourier Transform. X l (n) is the frequency domain reference signal vector obtained at the nth time point, and is of length N. f A complex vector.

[0121] Time-frequency transformation of the error signal:

[0122] E i (n)=FFT[e′ i (n)]

[0123] Among them, E i(n) is the frequency domain error signal vector obtained at the nth time point, with length N. f A complex vector.

[0124] Step 7.3 Secondary Channel Filtering

[0125] Using the secondary channel transfer function between the j-th loudspeaker and the i-th microphone to perform secondary channel filtering on the l-th signal can be expressed as:

[0126]

[0127] in, Let f be the transfer function of the secondary channel between the j-th loudspeaker and the i-th microphone, and f be the frequency ordinal number.

[0128] Step 7.4 Frequency Domain Gradient Acquisition

[0129] At the f-th frequency point, the frequency domain gradient is calculated as follows:

[0130]

[0131] Where, μ ijl(f) The step size correction factor at frequency point f can be expressed as:

[0132]

[0133]

[0134] Where δ E and δ P To ensure safety and prevent the denominator from being too small, λ1(f) is the spectral radius, and η is the power gain of the error signal.

[0135] Step 7.5 Update the adaptive filter based on the gradient calculated in Step 7.4.

[0136] W jl(f) (n+M)=[1-α (f) γ (f) W jl(f) (n)-α (f) dW jl(f) (n)

[0137] Among them W jl(f) (n+M) is the frequency domain representation of the adaptive filter, γ (f) To leak parameters, α (f) M represents the iteration step size. M indicates that the RNC algorithm is designed to perform a frequency domain calculation and update the adaptive filter every M points. Here, M... <N c The calculation and update time of each filter must be less than the time required for all M time-domain sampling points to be included in the algorithm.

[0138] Step 7.6 uses the inverse Fourier transform to transform the updated adaptive filter from step 7.5 to the time domain w. jl (n+M)=iFFT[W jl (n+M)]

[0139] Step 8 performs preprocessing on the excitation signals calculated in Steps 3 and 4 before fusion.

[0140] Step 8.1 Apply the excitation signal y calculated in Step 3. j (n) Perform upsampling and filter out high-frequency information through a low-pass filter. The cutoff frequency of the low-pass filter is the same as the high-end cutoff frequency of the band-pass filter at the corresponding input.

[0141] Step 8.2 Calculate the excitation signal u from step 4. j (n) Perform upsampling and filter out high-frequency information through a low-pass filter. The cutoff frequency of the low-pass filter is the same as the high-end cutoff frequency of the band-pass filter at the corresponding input.

[0142] Step 9 fuses the excitation signals processed in steps 8.1 and 8.2.

[0143] v j (n)=y j (n)+u j (n)

[0144] Step 10 outputs the fused signal from Step 9 through a speaker and then through the secondary channel s(m) to actively control engine noise and road noise inside the vehicle.

[0145] The vehicle-mounted active noise control system and its fusion method provided by this invention integrate the automotive ENC algorithm and RNC algorithm. The algorithm logic is rationally designed: the ENC employs a time-domain point-by-point filtering operation, while the RNC performs filter operations in the frequency domain and generates control signals in the time domain. The ENC task is cleverly integrated into the time-domain task of the RNC, while ensuring the timeliness of RNC filter parameter updates. The fused algorithm meets the computing power requirements of the controller. Experimental verification shows that a system based on a single microphone and speaker effectively achieves active control of engine noise and road noise inside the vehicle, with control performance no less than that of two systems operating independently.

[0146] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A vehicle mounted active noise control system, characterized by, It includes an acceleration sensor, a microphone, a speaker, and a controller. The acceleration sensor, microphone, and controller are connected to the vehicle's A2B bus. The controller is also connected to the vehicle's CAN bus. The controller includes an active engine noise controller and an active road noise controller. The sound signal picked up by the microphone is used as an error signal and is output to the active engine noise controller and the active road noise controller respectively through the A2B bus. The engine noise active controller connects to the vehicle's infotainment system via the CAN bus to obtain engine operating signals, and uses a time-domain point-by-point filtering algorithm to perform adaptive signal processing on the engine operating signals and error signals to obtain the first excitation signal. The active road noise controller obtains the vibration signal collected by the accelerometer via an A2B bus and outputs a second excitation signal through an adaptive filter. The adaptive filter is updated in the frequency domain by performing Fourier transform on the vibration signal and the error signal, including: windowing the vibration signal and the error signal; converting the windowed vibration signal and the error signal to a frequency domain signal using Fourier transform; using the secondary channel transfer function between the loudspeaker and the microphone to perform secondary channel filtering on the frequency domain transformed signal of the vibration signal, and combining it with the frequency domain transformed signal of the error signal to obtain the frequency domain gradient at the corresponding frequency point, thereby updating the adaptive filter; and then transforming the updated adaptive filter to the time domain for application. The controller merges the first excitation signal and the second excitation signal and outputs the result to the corresponding speaker for operation.

2. The vehicle-mounted active noise control system according to claim 1, characterized in that, The signal processing of the active road noise controller includes the following steps: Vibration signal The reference signal for the active road noise controller is processed by convolution through an adaptive filter to be output as a secondary sound source signal to the loudspeaker. The formula for calculating the first excitation signal of each speaker channel is as follows: ； in, For time-reversed adaptive filters, the order is... , Here, L is the reference signal channel index value for the active road noise controller, and L is the maximum value of the reference signal channel. This is the speaker location index value. This is the index value of the sampled signal. The vibration signal is generated from the currently acquired data. It consists of 1 signal point.

3. The vehicle-mounted active noise control system according to claim 1, characterized in that, The signal processing of the active engine noise controller includes the following steps: The current engine noise frequency is obtained based on the speed and order information in the engine operating signal, and the calculation formula is as follows: ； in, Engine speed, For engine order, To control the frequency index value, and at the same time the corresponding order index value; The engine noise frequency is input into a sine wave generator to produce two sinusoidal signals with a 90° phase difference, which serve as reference signals for the active engine noise controller. These are denoted as... and The calculation formula is as follows: ； ； Where A is the reference signal gain, used to adjust the amplitude of the reference signal; This refers to the engine noise frequency. The vibration time; The two sinusoidal signals are linearly filtered with their respective weighting coefficients to obtain the second excitation signal for the loudspeaker. The calculation formula is as follows: ； in, This is the speaker location index value. Here are the weighting coefficients, where Reference signal number for each control frequency Corresponding to sine, Corresponding cosine.

4. The vehicle-mounted active noise control system according to claim 3, characterized in that, The reference signal of the active engine noise controller is filtered by a secondary channel. The calculation formula for the filtered reference signal obtained from the secondary channel identification is as follows: ； ； in, This is the index value of the time-domain unit impulse response sequence of the secondary channel. This is the microphone position index value. For transfer functions; The weight coefficients in the active engine noise controller are updated using the reference signal filtered by the secondary channel, and the update formula is as follows: ； ； in Step size factor Leakage coefficient, To prevent echo coefficient, The number of microphones used in the system. This is the error signal.

5. The vehicle-mounted active noise control system according to claim 1, characterized in that, During the update process of the adaptive filter, the vibration signal and error signal need to be passed through a bandpass filter in advance to filter out high-frequency signal information and undergo downsampling processing before use.

6. The vehicle-mounted active noise control system according to claim 5, characterized in that, Before the first excitation signal and the second excitation signal are fused, they need to be upsampled and high-frequency information is filtered out by a low-pass filter. The cutoff frequency of the low-pass filter is the same as the cutoff frequency of the band-pass filter.

7. A fusion method for an on-board active noise control system, characterized in that, include: The engine noise active controller and the road noise active controller are integrated to form a system controller. The control algorithm of the system controller divides the in-vehicle noise reduction task into time domain task and frequency domain task. The time-domain task includes signal reception, secondary control sound generation and fusion, and acquisition of weight coefficients of the active engine noise controller; the frequency-domain task includes parameter update of the adaptive filter in the active road noise controller. The road noise active controller generates a first excitation signal in the time domain task, and the engine noise active controller generates a second excitation signal in the time domain task. The first excitation signal and the second excitation signal are used as secondary control sounds and are fused and output to the corresponding vehicle speakers for in-vehicle noise reduction.

8. The fusion method for vehicle-mounted active noise control systems according to claim 7, characterized in that, In the time-domain task, the received signals include engine speed signals, vehicle vibration signals, and error signals fed back from the in-vehicle microphones.

9. The fusion method for vehicle-mounted active noise control systems according to claim 8, characterized in that, The active road noise controller obtains a first excitation signal using vibration signals, and updates itself in the frequency domain using vibration signals and error signals; the active engine noise controller obtains a second excitation signal using speed signals, and updates itself in the time domain using speed signals and error signals.

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