Range-extended automobile noise processing system and processing method

Abstract

The invention discloses a range-extended automobile noise processing system and method, and relates to the technical field of automobiles, the range-extended automobile noise processing system comprises a noise detection module, a signal processing module, a noise suppression module, a system control module and a visualization module, the noise suppression module comprises a noise threshold adjustment unit, a noise reduction weight unit and a noise processing unit, the noise threshold adjustment unit is used for evaluating noise data, the noise reduction weight unit is used for evaluating the priority of noise reduction processing, and the noise processing unit is used for adjusting the gain and phase of noise to achieve the noise reduction effect. The noise processing system can adapt to the complexity and dynamic variability of a noise environment, the noise reduction weight unit evaluates the priority of noise reduction processing by combining a noise threshold value, finally, the noise processing unit accurately adjusts the gain and phase of noise to realize noise reduction, and the noise processing accuracy and processing efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of automobiles, and in particular to a noise processing system and a noise processing method for an extended-range automobile. Background Art

[0002] With the rapid development of the automobile industry, the number of cars in my country has increased year by year. Among them, the extended-range vehicle is an electric vehicle that adds an internal combustion engine to the pure electric vehicle to charge the power battery or directly drive the motor to increase the range. When the battery power is sufficient, the vehicle runs in pure electric mode; when the battery power is insufficient to support the current driving needs, the internal combustion engine starts to either charge the battery or directly drive the motor to increase the range. People have higher and higher requirements for the "safety, comfort, and environmental protection" of cars. Among them, noise greatly affects the subjective feeling of comfort of passengers, and has potential chronic harm to human health, and even causes safety hazards during driving.

[0003] In the existing extended-range vehicle noise processing process, the types and intensities of noise generated by extended-range vehicles under different road conditions are different, and the noise sources may come from multiple directions and locations. The existing system cannot adapt to the changes in noise sources in real time. When dealing with multiple noise sources, the traditional method is not flexible in resource allocation and cannot give priority to the noise sources with the greatest impact, which reduces the processing efficiency of the noise processing system. Summary of the invention

[0004] The purpose of the present invention is to provide a noise processing system and method for an extended-range vehicle, which solves the problems raised in the above-mentioned background technology.

[0005] To achieve the above-mentioned object, the present invention provides the following technical solutions: a noise processing system for an extended-range vehicle, comprising a noise detection module, a noise suppression module, a system control module, and a visualization module;

[0006] The noise detection module includes a sensor unit and a data collection unit, which are used to collect noise data during the operation of the vehicle;

[0007] The noise suppression module includes a noise threshold adjustment unit, a noise reduction weight unit and a noise processing unit;

[0008] The noise threshold adjustment unit obtains the noise threshold Tn at the current moment n according to the historical average noise intensity; the noise reduction weight unit determines the noise reduction weight Wi of the i-th noise according to the noise threshold Tn; the noise processing unit obtains the control parameter adjustment amount Pn+1 at the next moment according to the noise reduction weight Wi, which is used to adjust the gain and phase of the noise to achieve the noise reduction effect;

[0009] The visualization module includes a graphical user interface and a data chart, which is used to display the noise processing results.

[0010] Optionally, the evaluation formula of the noise threshold adjustment unit is as follows:

[0011]

[0012] Where T n is the noise threshold at the current time n;

[0013] S n is the noise intensity at the current time n;

[0014] is the historical average noise intensity;

[0015] α is the noise intensity influence coefficient.

[0016] Optionally, the noise weight processing formula of the noise reduction weight unit is as follows:

[0017]

[0018] Where W i is the denoising weight of the i-th noise;

[0019] D i is the intensity of the i-th noise;

[0020] T n is the noise threshold at the current moment n;

[0021] β is the noise intensity difference influence coefficient, and the initial value of β is 0.9;

[0022] σ i is the standard deviation of the i-th noise, indicating the noise fluctuation amplitude;

[0023] γ is σ i Influence coefficient;

[0024] W i The higher the value, the more serious the noise impact. The noise reduction weight unit dynamically adjusts the noise reduction weight of each noise according to the intensity of the noise source and the noise fluctuation amplitude, giving priority to the noise with serious impact.

[0025] Optionally, the processing formula of the noise processing unit is as follows:

[0026]

[0027] Where P n is the control parameter adjustment amount at the current moment n, which is the system preset;

[0028] P n+1 is the control parameter adjustment amount for the next moment n+1;

[0029] is the weighted effect bias;

[0030] Z is the weighted effect deviation influence coefficient;

[0031] W i is the denoising weight of the i-th noise

[0032] E i is the reduction amount of the i-th noise intensity;

[0033] J i is the intensity reduction of the i-th noise target;

[0034] m is the total number of noises;

[0035] Set the noise processing unit to adjust the current control parameter P n and the next moment control parameter adjustment amount P n+1 Stop when the change is less than 0.1, that is, |P n+1 -P n | Stop updating when < 0.1;

[0036] Setting weighted effect bias The threshold value is Y, when When it is greater than Y, it means that the noise variation is too large. At this time, the β value in the noise reduction weight unit is reduced to increase W i , the specific reduction is 0.2, and the change stops when the β value decreases to less than 0.3;

[0037] By setting the threshold Y of the weighted effect deviation and dynamically adjusting β, the system can adjust the β value in time when the noise changes too much.

[0038] Optionally, the sensor unit includes a microphone and an analog converter, the microphone is responsible for receiving sound wave signals in the environment and converting them into electrical signals, and converting the electrical signals output by the microphone into digital signals. The data collection unit includes a data collector, a wireless communication module and a storage device.

[0039] Optionally, a signal processing module is also included, and the signal processing module includes filtering, spectrum analysis, noise source location and feature extraction.

[0040] Optionally, the graphical user interface is a touch screen, and the data charts include line charts, bar charts and pie charts.

[0041] The present application provides a method for processing noise of an extended-range vehicle, comprising the following steps:

[0042] The noise data during the operation of the vehicle is collected by the sensor unit in the noise detection module, and the collected noise data is stored by the data collection unit;

[0043] The collected noise data is processed through the signal processing module to improve the quality of the noise data;

[0044] Obtain the noise threshold Tn at the current time n according to the historical average noise intensity;

[0045] Determine the noise reduction weight Wi of the i-th noise according to the noise threshold Tn;

[0046] The noise processing unit obtains the next moment control parameter adjustment amount Pn+1 according to the noise reduction weight Wi, which is used to adjust the gain and phase of the noise to achieve the noise reduction effect.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] 1. The present invention uses historical data and real-time monitoring to continuously update the threshold through the noise threshold adjustment unit, ensuring that the system can still maintain good responsiveness when the noise changes, and dynamically adjust the noise threshold, so that the noise processing system can adapt to the complexity and dynamic variability of the noise environment, and improve the adaptability of the noise processing system. Then, the noise reduction weight unit evaluates the priority of noise reduction processing by combining the noise threshold, determines the processing order according to the noise priority, and dynamically adjusts the noise reduction weight according to the intensity and characteristics of each noise source, so that resource allocation is more flexible and the noise source with the greatest impact is processed first. Finally, the noise processing unit accurately adjusts the gain and phase of the noise to achieve the noise reduction effect. The above algorithm units influence and communicate with each other, and jointly improve the accuracy and processing efficiency of noise processing.

[0049] 2. The present invention sets a threshold value Y of the weighted effect deviation and dynamically adjusts β. When the noise changes too much, the system can adjust the β value in time to enhance the response capability to noise changes. By setting the threshold value Y to decide whether to adjust the β value, excessive adjustment caused by small noise changes is effectively avoided, thereby improving the stability of the noise processing system and reducing control oscillation. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is a system block diagram of the present invention;

[0051] Figure 2 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] For example, see Figure 1 to Figure 2 ,This embodiment provides a noise processing system for an extended-range vehicle, including a noise detection module, a signal processing module, a noise suppression module, a system control module, and a visualization module. The system control module includes a central processing unit, and the system control module is used to control the operation of other modules;

[0054] The noise detection module includes a sensor unit and a data collection unit, which are used to collect noise data during the operation of the vehicle;

[0055] The sensor unit includes a microphone and an analog converter. The microphone is responsible for receiving sound wave signals in the environment and converting them into electrical signals. The electrical signals output by the microphone are converted into digital signals for subsequent digital processing and analysis by a computer. The data collection unit includes a data collector, a wireless communication module and a storage device.

[0056] The signal processing module is used to process the collected noise data to improve the data quality;

[0057] The noise suppression module includes a noise threshold adjustment unit, a noise reduction weight unit and a noise processing unit;

[0058] The noise threshold adjustment unit is used to evaluate the noise data and obtain the noise threshold T at the current time n. n , the denoising weight unit is used to evaluate the priority of noise denoising processing and obtain the denoising weight W of the i-th noise i The processing order is determined according to the noise weight. The noise processing unit combines W i Get the next moment control parameter adjustment amount P n+1 , used to adjust the gain and phase of the noise to achieve noise reduction effect;

[0059] The visualization module includes a graphical user interface and data charts to display the noise processing results.

[0060] More specifically, in this embodiment: the noise data during the operation of the vehicle is collected by the noise detection module, and after the quality of the collected noise data is improved by the signal processing module, the noise threshold adjustment unit uses historical data and real-time monitoring to continuously update the threshold, ensuring that the system can still maintain good responsiveness when the noise changes, and dynamically adjust the noise threshold, so that the noise processing system can adapt to the complexity and dynamic variability of the noise environment, and improve the adaptability of the noise processing system. After that, the noise reduction weight unit evaluates the priority of the noise reduction processing by combining the noise threshold, and determines the processing order according to the noise priority. For noise sources from different directions and positions, and according to the intensity and characteristics of each noise source, the noise reduction weight is dynamically adjusted to make resource allocation more flexible, and give priority to the noise source with the greatest impact. Finally, the noise processing unit accurately adjusts the gain and phase of the noise to achieve the noise reduction effect, and improves the accuracy and processing efficiency of the noise processing.

[0061] Furthermore, the noise threshold adjustment unit evaluation process is as follows:

[0062]

[0063] Where T n is the noise threshold at the current time n;

[0064] S n is the noise intensity at the current time n;

[0065] is the historical average noise intensity;

[0066] α is the noise intensity influence coefficient;

[0067] Specifically, the closer the noise intensity is to T n , indicating that the greater the noise impact at this time, the noise threshold adjustment unit can dynamically adjust the noise threshold according to the real-time changes of the system environment, that is, the historical noise data, so that the extended-range vehicle can cope with the complex and changeable noise environment during driving. Whether it is instantaneous noise fluctuations or long-term noise changes, the threshold can be effectively adjusted to improve the robustness and stability of the system.

[0068] Furthermore, the noise weight processing process of the denoising weight unit is as follows:

[0069]

[0070] Where W i is the denoising weight of the i-th noise;

[0071] D i is the intensity of the i-th noise;

[0072] T nis the noise threshold at the current time n;

[0073] β is the noise intensity difference influence coefficient, and the initial value of β is 0.9;

[0074] σ i is the standard deviation of the i-th noise, indicating the amplitude of noise fluctuation;

[0075] γ is σ i Influence coefficient;

[0076] Specifically, D i With T n The smaller the gap between them, the more serious the noise impact is, which will make W i The higher the value, the more accurate the noise reduction will be. The noise reduction weight unit can dynamically adjust the noise reduction weight of each noise according to the intensity of the noise source and the noise fluctuation amplitude, give priority to the noise with serious impact, ensure that the key noise problems are solved first, and dynamically adjust the weight of each noise according to its real-time impact, ensuring that the system can handle key noise more accurately, improve the overall noise reduction accuracy of the noise processing system, optimize resource allocation, and thus improve the accuracy and efficiency of noise reduction.

[0077] Furthermore, the noise processing unit processes as follows:

[0078]

[0079] Where P n is the adjustment amount of the control parameter n at the current moment, which is preset by the system;

[0080] P n+1 is the adjustment amount of the n+1 control parameter at the next moment;

[0081] is the weighted effect bias;

[0082] Z is the weighted effect deviation influence coefficient;

[0083] W i is the denoising weight of the i-th noise

[0084] E i is the i-th noise intensity reduction;

[0085] J i is the intensity reduction of the i-th noise target;

[0086] m is the total number of noises;

[0087] Set the noise processing unit to adjust the current control parameter P n and the next moment control parameter adjustment amount P n+1 Stop when the change is less than 0.1, that is, |P n+1 -Pn | Stop updating when < 0.1;

[0088] Specifically, the weighted effect deviation combines the influence of all noises and takes into account the weight of each noise. It can accurately reflect the current noise processing effect of the system, making the system's response to important noise more accurate. The weighted effect deviation, as feedback information, can reflect the current system's processing effect on noise. Finally, the current control parameter adjustment amount P is obtained. n Accurately adjust the gain and phase of the noise to achieve the noise reduction effect, and through continuous iteration, the feedback optimization control algorithm can gradually improve the performance of the noise reduction system and improve the accuracy and efficiency of noise processing;

[0089] Furthermore, we set the weighted effect bias The threshold value is Y, when When it is greater than Y, it means that the noise variation is too large. At this time, the β value in the noise reduction weight unit is reduced to increase W i The specific reduction is 0.2, and the change stops when the β value decreases to less than 0.3.

[0090] Specifically, by setting the threshold Y of the weighted effect deviation and the dynamic adjustment of β, when the noise changes too much, the system can adjust the β value in time to enhance the response to noise changes. By setting the threshold Y to decide whether to adjust the β value, it effectively avoids excessive adjustment caused by small noise changes, improves the stability of the noise processing system, and reduces control oscillation.

[0091] Furthermore, the graphical user interface is a touch screen, and the data charts include line charts, bar charts and pie charts.

[0092] Specifically, the user can operate the graphic objects on the touch screen according to the external input device or by touching it with his hands to achieve interaction with the computer, and by displaying the noise data in charts, the user can understand the noise data information more intuitively.

[0093] Furthermore, the signal processing module includes filtering, spectrum analysis, noise source location and feature extraction.

[0094] Specifically, filtering can remove high-frequency noise and interference components in noise data and retain useful information related to the noise source. Spectral analysis can calculate the power spectral density of the noise signal to understand the energy distribution of each frequency component, provide a basis for the identification and control of the noise source, and convert the time domain signal into a frequency domain signal to analyze the frequency distribution characteristics of the noise data. The noise source is located by analyzing the correlation between the noise data received by different sensors and comparing the time delay and phase difference of the noise data to determine the location of the noise source. Feature extraction can extract the time domain statistical characteristics of the signal, including mean, variance, kurtosis and skewness, etc., which can reflect the temporal variation characteristics of the noise signal. By processing the collected noise data, the data quality can be effectively improved to ensure the accuracy of subsequent noise processing.

[0095] See also Figure 2 , the system provides a processing method for the noise processing system of the extended range vehicle, comprising the following steps:

[0096] Step S1: collecting and storing noise data during vehicle operation through the sensor unit and the data collection unit in the noise detection module;

[0097] Step S2: Processing the collected noise data through a signal processing module to improve the quality of the noise data;

[0098] Step S3: The noise threshold adjustment unit uses historical data and real-time monitoring to continuously update the threshold, and dynamically adjusts the noise threshold so that the noise processing system can adapt to changes in the noise environment;

[0099] Step S4: The noise reduction weight unit evaluates the priority of noise reduction processing by combining the noise threshold, and dynamically adjusts the noise reduction weight according to the strength of each noise source, and determines the processing order according to the noise weight, so that resource allocation is more flexible and the noise with the largest weight is processed first;

[0100] Step S5: After determining the noise processing order, the noise gain and phase are precisely adjusted by the noise processing unit to achieve the noise reduction effect.

[0101] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A noise processing system for an extended-range vehicle, characterized in that: It includes noise detection module, noise suppression module, system control module and visualization module; The noise detection module includes a sensor unit and a data collection unit, which are used to collect noise data during the operation of the vehicle; The noise suppression module includes a noise threshold adjustment unit, a noise reduction weight unit and a noise processing unit; The noise threshold adjustment unit obtains the noise threshold T at the current time n according to the historical average noise intensity. n The noise reduction weight unit is based on the noise threshold T n Determine the denoising weight W of the i-th noise i The noise processing unit is based on the noise reduction weight W i Get the next moment control parameter adjustment amount P n+1 , used to adjust the gain and phase of the noise to achieve noise reduction effect; The visualization module includes a graphical user interface and a data chart, which is used to display the noise processing results.

2. The noise processing system for an extended-range vehicle according to claim 1, characterized in that: The evaluation formula of the noise threshold adjustment unit is as follows: Where T n is the noise threshold at the current time n; S n is the noise intensity at the current time n; is the historical average noise intensity; α is the noise intensity influence coefficient.

3. The noise processing system for extended-range vehicles according to claim 2, characterized in that: The processing formula of the noise weight of the noise reduction weight unit is as follows: Where W i is the denoising weight of the i-th noise; D i is the intensity of the i-th noise; T n is the noise threshold at the current moment n; β is the noise intensity difference influence coefficient, and the initial value of β is 0.9; σ i is the standard deviation of the i-th noise, indicating the noise fluctuation amplitude; γ is σ i Influence coefficient; W i The higher the value, the more serious the noise impact. The noise reduction weight of each noise is dynamically adjusted according to the intensity of the noise source and the noise fluctuation amplitude through the noise reduction weight unit, giving priority to the noise with serious impact.

4. The noise processing system for an extended-range vehicle according to claim 3, characterized in that: The processing formula of the noise processing unit is as follows: Where P n is the control parameter adjustment amount at the current moment n, which is the system preset; P n+1 is the control parameter adjustment amount for the next moment n+1; is the weighted effect bias; Z is the weighted effect deviation influence coefficient; W i is the denoising weight of the i-th noise E i is the reduction amount of the i-th noise intensity; J i is the intensity reduction of the i-th noise target; m is the total number of noises; Set the noise processing unit to adjust the current control parameter P n and the next moment control parameter adjustment amount P n+1 Stop when the change is less than 0.1, that is, |P n+1 -P n | Stop updating when < 0.1; Setting weighted effect bias The threshold value is Y, when When it is greater than Y, it means that the noise variation is too large. At this time, the β value in the noise reduction weight unit is reduced to increase W i , the specific reduction is 0.2, and the change stops when the β value decreases to less than 0.3; By setting the threshold Y of the weighted effect deviation and dynamically adjusting β, the system can adjust the β value in time when the noise changes too much.

5. The noise processing system for extended-range vehicles according to claim 4, characterized in that: The sensor unit includes a microphone and an analog converter. The microphone is responsible for receiving sound wave signals in the environment and converting them into electrical signals, and converting the electrical signals output by the microphone into digital signals. The data collection unit includes a data collector, a wireless communication module and a storage device.

6. The noise processing system for extended-range vehicles according to claim 5, characterized in that: The extended-range vehicle noise processing system also includes a signal processing module; The signal processing module includes filtering, spectrum analysis, noise source location and feature extraction.

7. The extended-range vehicle noise processing system according to claim 1, characterized in that: The graphical user interface is a touch screen, and the data charts include line charts, bar charts and pie charts.

8. A method for processing noise of an extended-range vehicle, characterized in that: The following steps are involved: Step S1: collecting noise data during vehicle operation through a sensor unit in a noise detection module, and storing the collected noise data using a data collection unit; Step S2: Processing the collected noise data to improve the quality of the noise data; Step S3: Obtain the noise threshold T at the current time n based on the historical average noise intensity n ; Step S4: According to the noise threshold T n Determine the denoising weight W of the i-th noise i ; Step S5: The noise processing unit processes the noise according to the noise reduction weight W. i Get the next moment control parameter adjustment amount P n+1 , which is used to adjust the gain and phase of the noise to achieve noise reduction effect.

Images