Vehicle cabin space active noise reduction and music dynamic compensation system

Abstract

The invention relates to the technical field of vehicle-mounted data processing, in particular to a cabin space active noise reduction and music dynamic compensation system, which comprises a data acquisition module used for acquiring noise data, vehicle operation parameters and music playing signals in a cabin in real time; the dual-channel processing module is used for constructing a dual-channel processing model based on the collected noise data and the vehicle operation parameters, and performing parallel processing on the noise and music signals based on the dual-channel model to obtain final audio signals; the scene self-adaption module is used for acquiring external environment parameters and dynamically adjusting the dual-channel processing model according to the vehicle operation parameters and the external environment parameters; the output module is used for outputting the processed audio signal; and the acoustic feedback module is used for monitoring cabin acoustic feedback data in real time according to the processed audio output, and iteratively optimizing the processing model according to the cabin acoustic feedback data. According to the invention, the efficiency of vehicle-mounted audio noise reduction and tone quality compensation is effectively improved.

Description

Technical Field

[0001] This invention relates to the field of vehicle data processing technology, and in particular to an active noise reduction and dynamic music compensation system for vehicle cabin space. Background Technology

[0002] Current in-vehicle audio systems face severe challenges in complex driving environments. Low-frequency interference such as engine noise, wind noise, and tire noise generated during vehicle operation not only mask musical details but also force users to increase the volume, exacerbating auditory fatigue. Traditional passive noise cancellation methods (such as sound insulation cotton) are effective for mid-to-high frequencies but struggle to suppress low-frequency noise; while existing active noise cancellation technologies mostly focus on canceling single noises without fully considering the dynamic compensation of the music signal, easily leading to sound quality distortion or frequency band loss.

[0003] Furthermore, most systems lack real-time perception and adaptive capabilities to changes in the in-vehicle and external environments, employing fixed processing strategies that fail to accommodate varying road conditions, vehicle speeds, and user preferences. Especially on highways or bumpy roads, noise characteristics change rapidly, and traditional algorithms often lag behind, easily triggering high-frequency howling or compensation overshoot. Therefore, there is an urgent need for an in-vehicle audio processing system that can simultaneously achieve precise noise reduction and intelligent music restoration, while also possessing scene-adaptive and user-personalized capabilities. Summary of the Invention

[0004] The purpose of this invention is to provide an active noise reduction and dynamic music compensation system for vehicle cabin space, so as to solve the problems of severe sound quality damage, slow response speed and difficulty in eliminating high-frequency howling in the prior art.

[0005] This invention provides the following method:

[0006] An active noise cancellation and dynamic music compensation system for a vehicle cabin includes:

[0007] The dual-channel processing module is used to construct a dual-channel processing model based on the collected noise data and vehicle operating parameters, and to perform parallel processing of noise and music signals based on the dual-channel model to obtain the final audio signal;

[0008] The scene adaptation module is used to acquire external environmental parameters and dynamically adjust the dual-channel processing model based on vehicle operating parameters and external environmental parameters;

[0009] The output module is used to output the processed audio signal.

[0010] The acoustic feedback module is used to monitor the cabin acoustic feedback data in real time based on the processed audio output, and to iteratively optimize the processing model based on the cabin acoustic feedback data.

[0011] Furthermore, the dual-channel processing module includes a noise reduction processing unit, which generates a noise reverse sound wave signal based on noise data and vehicle operating parameters.

[0012] The phase reversal waveform of the noise signal within the sound wave generation period is calculated using an adaptive filtering algorithm, and the calculation result is used as the basic anti-sound waveform.

[0013] The result of adding the engine speed change rate within the previous sound wave generation cycle to the value 1 is taken as the sound wave variation index of the current sound wave generation cycle, and the sound wave variation index of the current sound wave generation cycle is denoted as Fz.

[0014] The product of the sound wave variation index and the sound pressure of the basic back acoustic waveform is used as the noise back acoustic wave signal.

[0015] Furthermore, the dual-channel processing module also includes a music compensation unit, which is used to identify attenuated frequency bands based on music playback signals and noise data, and generate repair waveforms for the attenuated frequency bands.

[0016] The music playback signal within the sound wave generation period is divided into frequency bands, and the frequency band attenuation index S(i) of each frequency band is calculated. S(i) is set as 1-[Pn(i) / Pm(i)], where Pn(i) is the noise power of the i-th frequency band, Pm(i) is the music power of the i-th frequency band, S(i) represents the attenuation index of the i-th frequency band, and i is the numerical number of the frequency band.

[0017] Set a frequency band attenuation constant, and compare the frequency band attenuation index of each frequency band with the frequency band attenuation constant. When S(i) is greater than the frequency band attenuation constant, the i-th frequency band is determined to be a weakened frequency band; otherwise, the i-th frequency band is determined to be a normal frequency band.

[0018] Furthermore, the music compensation unit calculates the restoration coefficient R(j) = 1 / (1-S(j)) of the weakened frequency band based on the attenuation index S(j) of the weakened frequency band, where R(j) represents the restoration gain of the j-th weakened frequency band and j is the numerical number of the weakened frequency band.

[0019] Based on the original waveform of the music playback signal, gain compensation is performed on the attenuated frequency band to generate a repair waveform: The calculation formula for the repair waveform is: Wr(j)=Wo(j)×R(j), where Wo(j) is the sound pressure of the j-th attenuated frequency band of the original music waveform, and Wr(j) is the sound pressure of the repair waveform of the j-th attenuated frequency band.

[0020] Furthermore, the scene adaptive module includes an audio mixing unit, which mixes the noise reverse acoustic wave signal with the repair waveform of the attenuated frequency band: when the noise reverse acoustic wave signal and the attenuated frequency band overlap, the final output waveform signal is determined by weighted mixing. The formula for determining the final output waveform signal is: Wfinal=α×Wnr(j)+(1-α)×Wr(j), where Wnr(j) is the sound pressure of the noise reverse acoustic wave signal corresponding to the j-th attenuated frequency band, α is the noise reduction weight coefficient, and the calculation formula is α=0.7+0.3×(1-S_avg), S_avg is the average attenuation index, and S_avg=ΣS(i) / N is set, where N is the number of frequency bands;

[0021] The final audio signal is output through the vehicle's speaker system at a specification of 16bit / 44.1kHz.

[0022] Furthermore, the scene adaptive module also includes an audio compensation unit, which is used to adjust the processing priority of the noise reduction and compensation channels based on external environmental parameters and vehicle operating parameters, and generate a compensation scheme.

[0023] Based on external environmental parameters and vehicle operating parameters, the environmental impact factor E is calculated and set as E=(0.4×Wf+0.6×Rf) / ZS×Nf, ​​where Wf is wind noise intensity, Rf is tire noise intensity, Nf is vehicle sealing coefficient, and ZS is preset external noise intensity.

[0024] Furthermore, a priority index is calculated based on the environmental impact factor E, and the processing priority of the noise reduction and compensation channels is adjusted according to the calculation results. The priority index calculation formula is: P=0.6×E+0.4×(1-S_avg);

[0025] When P>Y, no compensation is performed; when P≤Y, the noise reduction weight coefficient is compensated to α', and α'=α×(YP) / P is set; where Y is the preset priority compensation constant.

[0026] Furthermore, the user-defined music playback sound effects are obtained, and the corresponding sound effect frequency range is extracted.

[0027] Extract the characteristic frequency range corresponding to the music type identifier, and construct the user's preference weight β(k) for the current music playback signal based on historical user habit data. Set β(k) = n(k) × v(k) / ZN; where β(k) represents the user's preference weight for playing the current music playback signal with the k-th music playback effect, n(k) is the number of times the user plays the current music playback signal with the k-th music playback effect, v(k) is the completion rate of the user playing the current music playback signal with the k-th music playback effect, and ZN is the total number of times the user plays the current music playback signal.

[0028] The sound pressure is adjusted in the frequency range corresponding to the music playback sound effect by [β(k)+1], and the sound pressure is adjusted in the characteristic frequency range corresponding to the music type identifier by [2-β(k)].

[0029] Furthermore, the acoustic feedback module includes a feedback update unit, which is used to dynamically update the dual-channel processing model based on the acoustic feedback data.

[0030] The feedback update unit calculates the noise attenuation ratio sb and distortion rate sz based on the cabin acoustic feedback data, and sets the feedback index γ based on the calculation results. The formula is γ=a1×(sb-SB) / SB+a2×(sz-SZ) / SZ; where a1 and a2 are the noise weight and distortion weight, respectively, a1+a2=1, and SB and SZ are the noise attenuation threshold and distortion threshold, respectively.

[0031] Furthermore, the feedback update unit establishes a dynamic update process by setting a feedback constant: when γ is less than or equal to the feedback constant, no update is performed; when γ is greater than the feedback constant, if sb is less than SB and sz is greater than or equal to SZ, the acoustic wave variation index of the next acoustic wave generation cycle is updated to the product of the original acoustic wave variation index and [1+(sb-SB) / SB]; if sb is less than SB and sz is less than SZ, the noise reduction weight coefficient of the next acoustic wave generation cycle is updated to the product of the original noise reduction weight coefficient and [1+(sb-SB) / SB]; if sb is greater than or equal to SB and sz is greater than or equal to SZ, the noise reduction weight coefficient of the next acoustic wave generation cycle is updated to the product of the original noise reduction weight coefficient and [1-(sz-SZ) / SZ].

[0032] Compared with existing technologies, the advantages of this invention are as follows: By constructing a complete system architecture that integrates data acquisition, dual-channel parallel processing, scene adaptation, and acoustic feedback closed-loop optimization, this invention achieves a deep integration of active noise cancellation and dynamic music compensation within the vehicle cabin. This solution can not only cancel interference from engine, wind, and tire noise in real time, but also accurately identify and repair music frequency bands weakened by noise, effectively avoiding sound quality damage and high-frequency howling. Simultaneously, by dynamically adjusting processing strategies based on external environmental parameters and user preferences, it significantly improves audio clarity, immersion, and personalized experience, solving the core problems of existing technologies such as slow response, poor adaptability, and sound quality degradation. Attached Figure Description

[0033] Figure 1 This is a schematic diagram of the structure of an active noise reduction and dynamic music compensation system for a vehicle cabin space provided by one or more embodiments of the present invention.

[0034] Figure 2 This is a schematic diagram of the structure of the dual-channel processing module provided by the present invention.

[0035] Figure 3 This is a schematic diagram of the scene adaptive module provided by the present invention.

[0036] Figure 4 This is a schematic diagram of the acoustic feedback module provided by the present invention. Detailed Implementation

[0037] To more clearly illustrate the present invention, the following description, in conjunction with preferred embodiments and accompanying drawings, further explains the invention. Similar components in the drawings are indicated by the same reference numerals. Those skilled in the art should understand that the specific description below is illustrative rather than restrictive and should not be construed as limiting the scope of protection of the present invention.

[0038] It should be noted that although the terms first, second, third, etc., may be used in the embodiments of this application for description, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of this application, first can also be referred to as second, and similarly, second can also be referred to as first.

[0039] The acquisition, storage, use, and processing of data in the technical method of this application all comply with the relevant provisions of national laws and regulations.

[0040] Specifically, the active noise reduction and dynamic music compensation system for vehicle cabin space described in this application is applied to the reduction of external noise and the compensation of internal sound quality during in-vehicle music playback.

[0041] To apply the above-mentioned application scenarios, this application provides an active noise reduction and dynamic music compensation system for vehicle cabin space, the structural schematic diagram of which can be found in the attached diagram. Figure 1 As shown, it includes:

[0042] The data acquisition module is used to collect noise data, vehicle operating parameters, and music playback signals in the cabin in real time.

[0043] Specifically, the noise data is collected through a four-microphone array positioned within the vehicle cabin, with a sampling frequency of 16kHz to 20kHz, covering the range audible to the human ear; the vehicle operating parameters are directly read via the vehicle's CAN bus, including engine speed, motor operating frequency, and vehicle acceleration; the music playback signal comes from the in-vehicle entertainment system, including audio waveforms, frequency domain characteristics, and music genre identifiers. In this application, the music identifier refers to the music genre, such as rock, classical, or voice; in this application, the noise data, vehicle operating parameters, and music playback signal are synchronously collected at a fixed sampling rate, such as 44.1kHz; the microphone arrays are positioned in the front and rear rows and the roof of the vehicle cabin, spatially covering the entire cabin sound field; the CAN bus data reading cycle is 10 milliseconds.

[0044] Specifically, by synchronously collecting data from multiple sources, the system input is ensured to be comprehensive, providing real-time, multi-dimensional input for subsequent noise reduction and compensation. At the same time, the noise data and music playback signal described in this application are collected synchronously to avoid processing failure due to timing deviations.

[0045] For example, the noise data acquisition can be achieved through a digital microphone array; the vehicle operating parameters can be acquired directly through the OBD-II interface or the vehicle ECU; and the music playback signal can be acquired through an audio bus or a Bluetooth audio module.

[0046] Please continue reading. Figure 1 As shown, the system also includes:

[0047] The dual-channel processing module is used to construct a dual-channel processing model based on the collected noise data and vehicle operating parameters, and to process the noise and music signals in parallel based on the dual-channel model to obtain the final audio signal, which is then played through the vehicle speaker system. The dual channels are specifically a noise reduction channel and a music compensation channel. The dual-channel processing module is connected to the data acquisition module.

[0048] Please see Figure 2 The diagram shown is a structural schematic of the dual-channel processing module provided in this application, including:

[0049] The noise reduction processing unit is used to generate noise reverse sound wave signals based on noise data and vehicle operating parameters.

[0050] Specifically, the process of generating the noise reverse acoustic wave signal in the noise reduction processing unit is as follows:

[0051] The phase reversal waveform of the noise signal within the sound wave generation period is calculated using an adaptive filtering algorithm, and the calculation result is used as the basic anti-sound waveform.

[0052] The result of adding the engine speed change rate within the previous sound wave generation cycle to the value 1 is taken as the sound wave variation index of the current sound wave generation cycle, and the sound wave variation index of the current sound wave generation cycle is denoted as Fz.

[0053] The product of the sound wave variation index and the sound pressure of the basic back acoustic waveform is used as the noise back acoustic wave signal.

[0054] Specifically, the adaptive filtering algorithm used in this application is the FxLMS algorithm. This application does not impose specific limitations on the selection of the algorithm, and those skilled in the art can make their own selections. Meanwhile, the duration of the sound wave generation period in this application is 5ms.

[0055] Please continue reading. Figure 2 As shown, the dual-channel processing module further includes:

[0056] The music compensation unit is used to identify the attenuated frequency band based on the music playback signal and noise data, and generate a repair waveform for the attenuated frequency band. The music compensation unit is connected to the noise reduction processing unit.

[0057] Specifically, in the music compensation unit, the process of identifying the attenuated frequency band is as follows:

[0058] The music playback signal within the sound wave generation period is divided into frequency bands, and the frequency band attenuation index S(i) of each frequency band is calculated. S(i) is set as 1-[Pn(i) / Pm(i)], where Pn(i) is the noise power of the i-th frequency band, Pm(i) is the music power of the i-th frequency band, S(i) represents the attenuation index of the i-th frequency band, and i is the numerical number of the frequency band.

[0059] Set a frequency band attenuation constant, and compare the frequency band attenuation index of each frequency band with the frequency band attenuation constant. When S(i) is greater than the frequency band attenuation constant, the i-th frequency band is determined to be a weakened frequency band; otherwise, the i-th frequency band is determined to be a normal frequency band.

[0060] Specifically, the frequency band attenuation constant mentioned in this application is 0.3.

[0061] Specifically, in the music compensation unit, the process of generating the repair waveform for the attenuated frequency band is as follows:

[0062] The repair coefficient R(j) of the weakened frequency band is calculated based on the attenuation index S(j) of the weakened frequency band, which is 1 / (1-S(j)), where R(j) represents the repair gain of the j-th weakened frequency band and j is the numerical number of the weakened frequency band.

[0063] Based on the original waveform of the music playback signal, gain compensation is performed on the attenuated frequency band to generate a repair waveform: The calculation formula for the repair waveform is: Wr(j)=Wo(j)×R(j), where Wo(j) is the sound pressure of the j-th attenuated frequency band of the original music waveform, and Wr(j) is the sound pressure of the repair waveform of the j-th attenuated frequency band.

[0064] It is understood that the noise reduction processing unit and the music compensation unit in this application are processed synchronously; in this application, Wr(j) and Wo(j) are both sets of sound pressure data, and do not refer to a single value.

[0065] Please continue reading. Figure 2 As shown, the dual-channel processing module further includes:

[0066] An audio mixing unit is used to generate the final audio signal within the sound wave generation cycle by mixing the repair waveform of the attenuated frequency band with the noise reverse sound wave signal, and then playing it through the vehicle speaker system. The audio mixing unit is the same as the music compensation unit.

[0067] Specifically, the process by which the audio mixing unit generates the final audio signal is as follows:

[0068] The noise reverse acoustic wave signal is mixed with the repair waveform of the attenuated frequency band: When the noise reverse acoustic wave signal and the attenuated frequency band overlap, the final output waveform signal is determined by weighted mixing. The formula for determining the final output waveform signal is: Wfinal=α×Wnr(j)+(1-α)×Wr(j), where Wnr(j) is the sound pressure of the noise reverse acoustic wave signal corresponding to the j-th attenuated frequency band, α is the noise reduction weight coefficient, and the calculation formula is α=0.7+0.3×(1-S_avg), S_avg is the average attenuation index, and S_avg=ΣS(i) / N is set, where N is the number of frequency bands;

[0069] The final audio signal is output through the vehicle's speaker system at a specification of 16bit / 44.1kHz.

[0070] Specifically, the noise reduction weight coefficient in this application ranges from [0,1], and its specific value is set to 0.7.

[0071] Specifically, noise reduction and music compensation are separated into two parallel channels, enabling the system to simultaneously generate inverse noise waveforms and music restoration waveforms, avoiding the latency accumulation caused by traditional serial processing. This structure not only improves audio processing efficiency but also enhances the system's real-time performance and stability in complex acoustic environments, effectively mitigating high-frequency howling and sound quality degradation issues.

[0072] Please continue reading. Figure 1 As shown, the system also includes:

[0073] The scene adaptation module is used to acquire external environmental parameters and dynamically adjust the dual-channel processing model based on vehicle operating parameters and external environmental parameters. The scene adaptation module is connected to the dual-channel processing module.

[0074] Specifically, by combining external parameters such as wind noise, tire noise, and vehicle body sealing, the system dynamically calculates the environmental impact factor E and priority index P, and intelligently adjusts noise reduction and compensation strategies. This mechanism enables the system to automatically optimize the processing focus for different scenarios such as high-speed driving, urban congestion, or tunnel passage, significantly improving the system's robustness and adaptability in changing road environments.

[0075] Please see Figure 3 As shown, it is a structural diagram of the scene adaptation module provided in this application, including:

[0076] An environmental parameter acquisition unit is used to collect external environmental parameters in real time. The external environmental parameters include wind noise intensity, tire noise intensity, and vehicle sealing coefficient. The vehicle sealing coefficient is the ratio of the noise intensity inside the vehicle to the noise intensity outside the vehicle during the test.

[0077] Please continue reading. Figure 3 As shown, the scene adaptation module also includes:

[0078] The audio compensation unit is used to adjust the processing priority of the noise reduction and compensation channels based on external environmental parameters and vehicle operating parameters, and to generate a compensation scheme. The audio compensation unit is connected to the environmental parameter acquisition unit.

[0079] Specifically, in the audio compensation unit, the process of generating a compensation scheme is as follows:

[0080] Based on external environmental parameters and vehicle operating parameters, the environmental impact factor E is calculated and set as E=(0.4×Wf+0.6×Rf) / ZS×Nf, ​​where Wf is wind noise intensity, Rf is tire noise intensity, Nf is vehicle sealing coefficient, and ZS is preset external noise intensity.

[0081] The priority index is calculated based on the environmental impact factor E, and the processing priority of the noise reduction and compensation channels is adjusted according to the calculation results. The priority index calculation formula is: P=0.6×E+0.4×(1-S_avg);

[0082] When P>Y, no compensation is performed; when P≤Y, the noise reduction weight coefficient is compensated to α', and α'=α×(YP) / P is set; where Y is the preset priority compensation constant.

[0083] Specifically, the preset external noise intensity in this application is 60dB, and the preset priority compensation constant is 0.6.

[0084] Please continue reading. Figure 3 As shown, the scene adaptation module also includes:

[0085] A personalized adjustment unit is used to adjust the final audio signal based on music genre identifiers and user settings preferences. The personalized adjustment unit is connected to the audio compensation unit.

[0086] Specifically, in the personalized adjustment unit, the process of adjusting the final audio signal is as follows:

[0087] Get the music playback sound effects set by the user, and extract the frequency range of the sound effects corresponding to the music playback sound effects;

[0088] Extract the characteristic frequency range corresponding to the music type identifier, and construct the user's preference weight β(k) for the current music playback signal based on historical user habit data. Set β(k) = n(k) × v(k) / ZN; where β(k) represents the user's preference weight for playing the current music playback signal with the k-th music playback effect, n(k) is the number of times the user plays the current music playback signal with the k-th music playback effect, v(k) is the completion rate of the user playing the current music playback signal with the k-th music playback effect, and ZN is the total number of times the user plays the current music playback signal.

[0089] The sound pressure is adjusted in the frequency range corresponding to the music playback sound effect by [β(k)+1], and the sound pressure is adjusted in the characteristic frequency range corresponding to the music type identifier by [2-β(k)].

[0090] It is understood that the process of adjusting the sound pressure of the frequency range corresponding to the music playback sound effect in this application is to use the product of [β(k)+1] and the sound pressure of the frequency range corresponding to the music playback sound effect in the final audio signal as the adjusted final audio signal. The process of "adjusting the sound pressure of the characteristic frequency range corresponding to the music type identifier with [2-β(k)]" is the same. The user habit data includes the number of times the user plays the current music playback signal with the k-th music playback sound effect, the completion rate of the user playing the current music playback signal with the k-th music playback sound effect, and the total number of times the user plays the current music playback signal.

[0091] Please continue reading. Figure 1 As shown, the system also includes:

[0092] The output module is used to output the processed audio signal, and the output module is connected to the scene adaptive module.

[0093] Please continue reading. Figure 1 As shown, the system also includes:

[0094] An acoustic feedback module is used to monitor cabin acoustic feedback data in real time based on the processed audio output, and to iteratively optimize the processing model based on the cabin acoustic feedback data. The acoustic feedback module is connected to the output module.

[0095] Please see Figure 4 The diagram shown is a structural schematic of the acoustic feedback module provided in the application, including:

[0096] The data monitoring unit is used to monitor acoustic feedback data in real time through a microphone array; the acoustic feedback data includes the actual playback signal of the processed audio signal.

[0097] Please continue reading. Figure 4 As shown, the acoustic feedback module further includes:

[0098] The feedback update unit is used to dynamically update the dual-channel processing model based on acoustic feedback data, and the feedback update unit is connected to the data monitoring unit.

[0099] Specifically, in the feedback update unit, the process of updating the dual-channel processing model is as follows:

[0100] Based on the acoustic feedback data of the vehicle cabin, the noise attenuation ratio sb and the distortion rate sz are calculated, and the feedback index γ is set according to the calculation results. The formula is γ=a1×(sb-SB) / SB+a2×(sz-SZ) / SZ; where a1 and a2 are the noise weight and distortion weight, respectively, a1+a2=1, and SB and SZ are the noise attenuation threshold and distortion threshold, respectively.

[0101] A dynamic update process is established by setting a feedback constant: when γ is less than or equal to the feedback constant, no update is performed; when γ is greater than the feedback constant, if sb is less than SB and sz is greater than or equal to SZ, the acoustic variation index of the next acoustic wave generation cycle is updated to the product of the original acoustic variation index and [1+(sb-SB) / SB]; if sb is less than SB and sz is less than SZ, the noise reduction weight coefficient of the next acoustic wave generation cycle is updated to the product of the original noise reduction weight coefficient and [1+(sb-SB) / SB]; if sb is greater than or equal to SB and sz is greater than or equal to SZ, the noise reduction weight coefficient of the next acoustic wave generation cycle is updated to the product of the original noise reduction weight coefficient and [1-(sz-SZ) / SZ].

[0102] Specifically, the calculation process of the noise attenuation ratio and distortion rate described in this application is a technical means well known to those skilled in the art and has been fully disclosed in the prior art, so it will not be repeated in this application.

[0103] Specifically, by monitoring the actual playback effect in the cabin in real time, the noise attenuation ratio sb and distortion rate sz are calculated, and the sound wave variation index or noise reduction weight coefficient is dynamically updated accordingly. This closed-loop mechanism enables the system to have continuous learning and self-correction capabilities, and can cope with acoustic environmental disturbances such as changes in seat position, opening and closing of windows, or changes in the number of occupants, maintaining optimal performance over a long period of time.

[0104] The technical method of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical methods after such changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A vehicle cabin active noise reduction and dynamic music compensation system, characterized in that, include: The dual-channel processing module is used to construct a dual-channel processing model based on the collected noise data and vehicle operating parameters, and to perform parallel processing of noise and music signals based on the dual-channel model to obtain the final audio signal; The scene adaptation module is used to acquire external environmental parameters and dynamically adjust the dual-channel processing model based on vehicle operating parameters and external environmental parameters; The output module is used to output the processed audio signal. The acoustic feedback module is used to monitor the cabin acoustic feedback data in real time based on the processed audio output, and to iteratively optimize the processing model based on the cabin acoustic feedback data.

2. The protocol stack overload detection method according to claim 1, characterized in that, The dual-channel processing module includes a noise reduction processing unit, which generates a noise reverse sound wave signal based on noise data and vehicle operating parameters. The phase reversal waveform of the noise signal within the sound wave generation period is calculated using an adaptive filtering algorithm, and the calculation result is used as the basic anti-sound waveform. The result of adding the engine speed change rate within the previous sound wave generation cycle to the value 1 is taken as the sound wave variation index of the current sound wave generation cycle, and the sound wave variation index of the current sound wave generation cycle is denoted as Fz. The product of the sound wave variation index and the sound pressure of the basic back acoustic waveform is used as the noise back acoustic wave signal.

3. The protocol stack overload detection method according to claim 2, characterized in that, The dual-channel processing module also includes a music compensation unit, which is used to identify attenuated frequency bands based on music playback signals and noise data, and generate repair waveforms for the attenuated frequency bands. The music playback signal within the sound wave generation period is divided into frequency bands, and the frequency band attenuation index S(i) of each frequency band is calculated. S(i) is set as 1-[Pn(i) / Pm(i)], where Pn(i) is the noise power of the i-th frequency band, Pm(i) is the music power of the i-th frequency band, S(i) represents the attenuation index of the i-th frequency band, and i is the numerical number of the frequency band. Set a frequency band attenuation constant, and compare the frequency band attenuation index of each frequency band with the frequency band attenuation constant. When S(i) is greater than the frequency band attenuation constant, the i-th frequency band is determined to be a weakened frequency band; otherwise, the i-th frequency band is determined to be a normal frequency band.

4. The protocol stack overload detection method according to claim 3, characterized in that, The music compensation unit calculates the restoration coefficient R(j) = 1 / (1-S(j)) of the weakened frequency band based on the attenuation index S(j) of the weakened frequency band, where R(j) represents the restoration gain of the j-th weakened frequency band and j is the numerical number of the weakened frequency band. Based on the original waveform of the music playback signal, gain compensation is performed on the attenuated frequency band to generate a repair waveform: The calculation formula for the repair waveform is: Wr(j)=Wo(j)×R(j), where Wo(j) is the sound pressure of the j-th attenuated frequency band of the original music waveform, and Wr(j) is the sound pressure of the repair waveform of the j-th attenuated frequency band.

5. The protocol stack overload detection method according to claim 4, characterized in that, The scene adaptive module includes an audio mixing unit, which mixes the noise inverse acoustic wave signal with the repair waveform of the attenuated frequency band. When the noise inverse acoustic wave signal and the attenuated frequency band overlap, the final output waveform signal is determined by weighted mixing. The formula for determining the final output waveform signal is: Wfinal=α×Wnr(j)+(1-α)×Wr(j), where Wnr(j) is the sound pressure of the noise inverse acoustic wave signal corresponding to the j-th attenuated frequency band, α is the noise reduction weight coefficient, and the calculation formula is α=0.7+0.3×(1-S_avg), where S_avg is the average attenuation index, and S_avg=ΣS(i) / N is the number of frequency bands. The final audio signal is output through the vehicle's speaker system at a specification of 16bit / 44.1kHz.

6. The protocol stack overload detection method according to claim 5, characterized in that, The scene adaptive module also includes an audio compensation unit, which is used to adjust the processing priority of the noise reduction and compensation channels and generate a compensation scheme based on external environmental parameters and vehicle operating parameters. Based on external environmental parameters and vehicle operating parameters, the environmental impact factor E is calculated and set as E=(0.4×Wf+0.6×Rf) / ZS×Nf, ​​where Wf is wind noise intensity, Rf is tire noise intensity, Nf is vehicle sealing coefficient, and ZS is preset external noise intensity.

7. The protocol stack overload detection method according to claim 6, characterized in that, The priority index is calculated based on the environmental impact factor E, and the processing priority of the noise reduction and compensation channels is adjusted according to the calculation results. The priority index calculation formula is: P=0.6×E+0.4×(1-S_avg); When P>Y, no compensation is performed; when P≤Y, the noise reduction weight coefficient is compensated to α', and α'=α×(YP) / P is set; where Y is the preset priority compensation constant.

8. The protocol stack overload detection method according to claim 7, characterized in that, Get the music playback sound effects set by the user, and extract the frequency range of the sound effects corresponding to the music playback sound effects; Extract the characteristic frequency range corresponding to the music type identifier, and construct the user's preference weight β(k) for the current music playback signal based on historical user habit data. Set β(k) = n(k) × v(k) / ZN; where β(k) represents the user's preference weight for playing the current music playback signal with the k-th music playback effect, n(k) is the number of times the user plays the current music playback signal with the k-th music playback effect, v(k) is the completion rate of the user playing the current music playback signal with the k-th music playback effect, and ZN is the total number of times the user plays the current music playback signal. The sound pressure is adjusted in the frequency range corresponding to the music playback sound effect by [β(k)+1], and the sound pressure is adjusted in the characteristic frequency range corresponding to the music type identifier by [2-β(k)].

9. The protocol stack overload detection method according to claim 8, characterized in that, The acoustic feedback module includes a feedback update unit, which is used to dynamically update the dual-channel processing model based on the acoustic feedback data. The feedback update unit calculates the noise attenuation ratio sb and distortion rate sz based on the cabin acoustic feedback data, and sets the feedback index γ based on the calculation results. The formula is γ=a1×(sb-SB) / SB+a2×(sz-SZ) / SZ; where a1 and a2 are the noise weight and distortion weight, respectively, a1+a2=1, and SB and SZ are the noise attenuation threshold and distortion threshold, respectively.

10. The protocol stack overload detection method according to claim 9, characterized in that, The feedback update unit establishes a dynamic update process by setting a feedback constant: when γ is less than or equal to the feedback constant, no update is performed; when γ is greater than the feedback constant, if sb is less than SB and sz is greater than or equal to SZ, the acoustic wave variation index of the next acoustic wave generation cycle is updated to the product of the original acoustic wave variation index and [1+(sb-SB) / SB]; if sb is less than SB and sz is less than SZ, the noise reduction weight coefficient of the next acoustic wave generation cycle is updated to the product of the original noise reduction weight coefficient and [1+(sb-SB) / SB]. If sb is greater than or equal to SB and sz is greater than or equal to SZ, the noise reduction weight coefficient of the next sound wave generation cycle will be updated to the product of the original noise reduction weight coefficient and [1-(sz-SZ) / SZ].

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