Vehicle noise reduction method and device and vehicle

Abstract

The invention relates to the technical field of vehicle noise reduction, and discloses a vehicle noise reduction method, which comprises the following steps: acquiring current external environment noise and in-vehicle noise of a vehicle; obtaining a first coherence value based on a driving parameter of a driving device of the vehicle and the in-vehicle noise, and obtaining a second coherence value based on the external environment noise and the in-vehicle noise; determining a main noise source of the vehicle from driving device noise and external environment noise according to the first coherence value and the second coherence value, wherein the driving device noise is generated when the driving device operates at the driving parameters; controlling the vehicle to output a secondary sound source according to the main noise source. According to the method, the correlation between the in-vehicle noise and the driving device noise and the correlation between the in-vehicle noise and the external environment noise are analyzed through the coherence algorithm, so that the current main noise source is determined, the secondary sound source is output in a targeted mode, and elimination of the in-vehicle noise is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle noise reduction, and in particular to a vehicle noise reduction method, device and vehicle. Background Art

[0002] With the rapid development of the automobile industry, in-vehicle noise control technology has gradually become an important research field to improve driving comfort and user experience. Active Noise Cancellation (ANC) is an important means of automobile noise reduction. Its core idea is to offset the in-vehicle noise by generating a secondary sound source signal with a phase opposite to the noise signal.

[0003] In the prior art, in-vehicle active noise reduction technology is mainly used to actively reduce engine noise and road noise, that is, the external environmental noise (such as wind noise, road noise and tire noise) during vehicle driving and the noise caused by the engine (such as vibration and sound waves generated by engine operation).

[0004] However, in certain scenarios, such as when parking or waiting at a red light, if there are other vehicles, especially large vehicles (such as light trucks, heavy trucks, etc.) nearby, their engine noise will be transmitted into the car through the air or structure, resulting in a significant increase in low-frequency noise inside the car, seriously affecting the comfort of the driver and passengers. Since the existing active noise reduction technology cannot distinguish the engine noise of the vehicle from the engine noise in the vehicle's external environment, this not only cannot eliminate the engine noise in the vehicle's external environment, but will also further affect the noise reduction effect of active noise reduction on the vehicle's noise.

[0005] Therefore, how to dynamically eliminate the noise inside the vehicle according to the ambient noise outside the vehicle has become a technical problem that needs to be solved urgently by those skilled in the art. Summary of the invention

[0006] In view of the above problems, on the one hand, the present disclosure provides a vehicle noise reduction method that overcomes the above problems or at least partially solves the above problems. The technical solution is as follows:

[0007] A vehicle noise reduction method, comprising:

[0008] Obtain the current external environmental noise and interior noise of the vehicle;

[0009] Obtaining a first coherence value based on a driving parameter of a driving device of the vehicle and the vehicle interior noise, and obtaining a second coherence value based on the external environmental noise and the vehicle interior noise;

[0010] Determine the main noise source of the vehicle from the drive device noise and the external environmental noise based on the first coherence value and the second coherence value, where the drive device noise is generated by the drive device when operating with the drive parameters;

[0011] Control the vehicle to output a secondary sound source according to the main noise source.

[0012] In order to effectively identify the noise source that contributes the most to the in-vehicle noise and provide a basis for generating a targeted secondary sound source subsequently. Preferably, determine the main noise source of the vehicle from the drive device noise and the external environmental noise based on the first coherence value and the second coherence value. Specifically:

[0013] If the first coherence value is greater than the second coherence value and greater than a preset threshold, use the drive device noise as the main noise source;

[0014] If the second coherence value is greater than the first coherence value and greater than the preset threshold, use the external environmental noise as the main noise source.

[0015] In order to accurately control the vehicle to output a targeted secondary sound source according to the determined main noise source to achieve effective noise cancellation. Preferably, control the vehicle to output a secondary sound source according to the main noise source. Specifically:

[0016] If the main noise source is the drive device noise, control the vehicle to output the secondary sound source according to the drive device noise;

[0017] If the main noise source is the external environmental noise, control the vehicle to output the secondary sound source according to the external environmental noise source.

[0018] In order to further refine the judgment logic of the main noise source according to the current state of the vehicle's drive device, so as to more accurately generate a secondary sound source to achieve effective noise reduction. Preferably, it further includes:

[0019] If the drive device in the current starting state includes an engine, the drive parameter is the engine noise frequency, and the engine noise frequency is generated according to the current engine speed;

[0020] If the drive device in the current starting state is only a motor, use the external environmental noise as the main noise source.

[0021] In order to intelligently generate and output targeted secondary sound sources according to the specific vehicle type and its noise environment, and significantly reduce the in-vehicle noise. Preferably, the in-vehicle noise is obtained by an error microphone provided inside the vehicle, and the external environmental noise is obtained by a collection microphone provided outside the vehicle. Controlling the vehicle to output a secondary sound source according to the main noise source specifically includes:

[0022] Set the sound parameters output by the speaker inside the vehicle according to the noise reduction standard corresponding to the main noise source and the type of the vehicle;

[0023] Control the speaker to output the secondary sound source according to the sound parameters.

[0024] In order to formulate and implement precise noise reduction strategies for different types of vehicles, and ensure that all vehicles can achieve the best noise control effect within their design ranges. Preferably, the noise reduction standard is specifically determined by the following method:

[0025] Determine the vehicle classification level of the vehicle, and each vehicle classification level corresponds to the in-vehicle noise limit of different levels of vehicles;

[0026] Determine the noise reduction standard of the vehicle according to the in-vehicle noise limit.

[0027] In order to improve the efficiency and pertinence of the noise reduction system, flexibly adapt to the situation where different seats are occupied, and ensure the best noise reduction effect for each passenger. Preferably, a plurality of error microphones are provided, and each error microphone corresponds to at least one seat. The method further includes:

[0028] Obtain the occupancy status of each seat and the in-vehicle area noise collected by each error microphone;

[0029] Adjust the correction weights of the error microphones according to the occupancy status;

[0030] Correct the secondary sound source based on the in-vehicle area noise signal of each error microphone and the correction weight of each error microphone.

[0031] In order to generate and adjust the secondary sound source according to the specific noise conditions in different regions, so as to achieve a more effective noise reduction effect. Preferably, a plurality of speakers are provided, and the method further includes:

[0032] If the main noise source is the external environmental noise, control each speaker to correct the secondary sound source according to the regional environmental noise collected by the collection microphone closest to each speaker.

[0033] In a second aspect, the present invention provides a vehicle noise reduction device, including:

[0034] A noise acquisition module for acquiring the current external environmental noise and in-vehicle noise of the vehicle;

[0035] A coherence value calculation module for obtaining a first coherence value based on the driving parameters of the driving device of the vehicle and the in-vehicle noise, and obtaining a second coherence value based on the external environmental noise and the in-vehicle noise;

[0036] A judgment module for determining the main noise source of the vehicle from the driving device noise and the external environmental noise according to the first coherence value and the second coherence value, where the driving device noise is generated by the driving device when operating at the driving parameters;

[0037] An execution module for controlling the vehicle to output a secondary sound source according to the main noise source.

[0038] In a third aspect, the present disclosure provides a vehicle, including:

[0039] A memory for storing executable program code;

[0040] A processor for calling and running the executable program code from the memory, so that the vehicle executes the method described in any one of the above.

[0041] The present application discloses a vehicle noise reduction method, device and vehicle. The method obtains the current external environmental noise and in-vehicle noise of the vehicle, and obtains a first coherence value based on the driving parameters of the driving device and the in-vehicle noise, and a second coherence value based on the external environmental noise and the in-vehicle noise, so as to accurately determine the main noise source of the vehicle from the driving device noise and the external environmental noise, solving the problem in the prior art that it is difficult to distinguish the engine noise of the vehicle from other noises in the external environment, and realizing the accurate identification of the main noise source; controlling the vehicle to output a secondary sound source according to the identified main noise source, and specifically eliminating or reducing the influence brought by the main noise source, thereby improving the efficiency and effect of noise reduction. Compared with the traditional active noise reduction method that only targets a single type of noise (such as engine noise or road noise), this solution is more flexible and effective, and can provide the best noise reduction experience in different scenarios; this method can respond in real time to changes in the vehicle's external environment, such as when parking and waiting for a red light and there is a large vehicle beside, dynamically adjusting the noise reduction strategy to adapt to the changing noise environment, ensuring that the passengers can enjoy a relatively quiet and comfortable in-vehicle environment in various situations, improving driving comfort and user experience, especially in a complex urban traffic environment. Description of the Drawings

[0042] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the following detailed description of the preferred embodiments. The drawings are only for the purpose of illustrating the preferred embodiments and are not considered to be a limitation of the present invention. Moreover, throughout the drawings, the same reference numerals are used to denote the same components. In the drawings:

[0043] Figure 1 It is a flowchart of a vehicle noise reduction method provided by an embodiment of the present invention;

[0044] Figure 2 It is a schematic structural diagram of a vehicle noise reduction device provided by an embodiment of the present invention;

[0045] Figure 3 It is a schematic structural diagram of a vehicle provided by an embodiment of the present invention. Detailed Embodiments

[0046] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be fully conveyed to those skilled in the art. It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other. Hereinafter, the present invention will be described in detail with reference to the drawings and in conjunction with the embodiments.

[0047] As Figure 1 shown, in some embodiments of the present application, this embodiment provides a vehicle noise reduction method. Specifically, the method includes the following steps:

[0048] Step S101, obtain the current external environmental noise and in-vehicle noise of the vehicle.

[0049] As described above, the current external environmental noise and in-vehicle noise of the vehicle are obtained through sensor technology. The external environmental noise refers to the noise generated by various sound sources outside the vehicle, such as wind noise, road noise, the noise generated by the friction between the tires and the ground, and the engine noise emitted by other nearby vehicles (such as large trucks or motorcycles). The in-vehicle noise refers to the noise actually present in the interior space of the vehicle, which comes from multiple aspects, including the propagation of external environmental noise, the vibration and sound waves generated when the vehicle drive device (such as an engine or a motor) operates, and the sounds generated when other mechanical components in the vehicle work.

[0050] To achieve this step, it is necessary to set up a collection microphone and an error microphone inside and outside the vehicle respectively. The external environmental noise is usually captured by the collection microphone installed outside the vehicle, while the interior noise is collected through error microphones arranged at different positions inside the vehicle. These microphones can sense the sound pressure level in real time and transmit the signals to the vehicle's control system for subsequent processing.

[0051] For example, assume a sedan is driving on an urban road and there is a heavy truck parked at a traffic light beside it. At this time, the external environmental noise mainly includes the low-frequency noise of the truck engine; the interior noise is composed of the truck engine noise transmitted into the vehicle through the air, the noise generated by the vehicle's own engine operation, and other background noises. Through the external collection microphone, the system can capture the truck engine noise and road noise; while through the error microphones inside the vehicle, the system can monitor the actual noise distribution inside the vehicle. These data provide basic information for subsequent analysis of the main noise sources. Assume the vehicle is driving on a highway, at this time the external environmental noise may mainly be wind noise and tire noise, and the interior noise includes the propagated parts of these noises and the vibration noise generated by the vehicle's drive device. Through the data collection in step S101, the system can distinguish these noise sources and provide a basis for further noise reduction operations.

[0052] It should be noted that in a specific implementation scenario, based on the above solution, a multi-point distributed collection scheme can also be adopted. That is, when collecting noise from the vehicle, in order to more comprehensively capture the noise distribution, multiple collection microphones and error microphones can be set outside and inside the vehicle. For example, collection microphones can be arranged at the front, rear, and both sides of the vehicle to cover the external environmental noise in different directions; error microphones can be arranged in key areas such as near the seats, on the roof, and on the floor inside the vehicle to accurately sense the spatial distribution characteristics of the interior noise. This multi-point distributed collection method can improve the accuracy and comprehensiveness of noise identification.

[0053] In a specific implementation scenario, based on the above solution, a dynamic sampling frequency adjustment scheme can also be adopted. That is, when collecting noise from the vehicle, according to the different driving states of the vehicle, the sampling frequency of the microphone is dynamically adjusted. For example, when driving at low speed or parking, focus on collecting low-frequency noise (such as engine noise); when driving at high speed, focus on high-frequency noise (such as wind noise and tire noise). This dynamic adjustment mechanism can optimize the data collection efficiency and reduce unnecessary consumption of computing resources.

[0054] In a specific implementation scenario, based on the above solution, an anti-interference design solution can also be adopted. That is, when collecting vehicle noise, in order to ensure that the collected noise data is not affected by strong external interferences (such as electromagnetic interference or other sudden noises), an anti-interference module can be added to the microphone hardware design, or a filtering algorithm can be used at the software level to remove outliers. This can ensure that the collected data is more real and reliable, thereby improving the stability of the entire noise reduction system.

[0055] Step S102: Obtain a first coherence value based on the driving parameters of the driving device of the vehicle and the in-vehicle noise, and obtain a second coherence value based on the external environmental noise and the in-vehicle noise.

[0056] As described above, two coherence values are calculated respectively through the coherence algorithm to quantify the correlation between the in-vehicle noise signal and the vehicle driving device (such as an engine or a motor) and the external environmental noise. The first coherence value is used to evaluate the degree of association between the in-vehicle noise signal frequency and the driving parameters of the vehicle driving device (such as engine speed, motor operating frequency, etc.). If the first coherence value is relatively high, it indicates that the in-vehicle noise mainly comes from the vehicle's own driving device. The second coherence value is used to evaluate the degree of association between the in-vehicle noise signal frequency and the out-of-vehicle environmental noise signal frequency. If the second coherence value is relatively high, it indicates that the in-vehicle noise mainly comes from the external environmental noise (such as the engine noise of other vehicles, wind noise, etc.). These two coherence values are the key basis for subsequent judgment of the main noise source, and their accuracy directly affects the noise reduction effect.

[0057] Specifically, the system uses the coherence algorithm to analyze the correlation between the in-vehicle noise signal and the reference signal. The coherence value reflects the matching degree of the two signals in terms of frequency and phase, and the numerical range is usually from 0 to 1. The larger the value, the stronger the correlation. The reference signal includes the driving parameters of the vehicle's driving device and the signal frequency of the external environmental noise. According to the coherence algorithm, the system calculates the following two coherence values respectively: the first coherence value is generated based on the in-vehicle noise signal frequency of the vehicle currently and the driving parameters of the vehicle's driving device; the second coherence value is generated based on the signal frequency of the external environmental noise of the vehicle currently and the in-vehicle noise signal frequency.

[0058] The specific coherence algorithm is as follows:

[0059]

[0060] Among them, S ij (k) is the average of the cross-power spectra, S ii (k) and S jj(k) is the average of the auto-power spectrum, and o represents different calculation and judgment regions inside the vehicle. Specifically, based on this coherence algorithm, first, the in-vehicle noise signal and the drive parameter signal of the vehicle's drive device are substituted into it to determine the first coherence value; then, the in-vehicle noise signal and the signal of the external environmental noise are substituted into it to determine the second coherence value.

[0061] For example, assume that a fuel vehicle is waiting for a red light while a large truck is idling beside it. At this time, the system will perform the following operations:

[0062] Collect the in-vehicle noise signal, that is, capture the current in-vehicle noise signal through the in-vehicle error microphone;

[0063] Obtain the drive device parameters, that is, read the engine speed information through the CAN bus, and calculate the main excitation frequency of the engine according to the formula

[0064]

[0065] Calculate the main excitation frequency of the engine;

[0066] Collect the external environmental noise, that is, capture the low-frequency noise signal of the truck engine through the out-of-vehicle microphone.

[0067] Calculate two coherence values respectively through the coherence algorithm: the first coherence value is calculated based on the correlation between the in-vehicle noise signal frequency and the engine excitation frequency; the second coherence value is calculated based on the correlation between the in-vehicle noise signal frequency and the frequency of the truck noise signal collected by the out-of-vehicle microphone. If the first coherence value is low while the second coherence value is high, it can be judged that the main source of the current in-vehicle noise is the engine noise of the external truck, rather than the engine of this vehicle.

[0068] Assume that a sedan is driving on the highway, and the in-vehicle noise is mainly composed of wind noise and tire noise, while the vehicle's engine is in a low-load state. At this time, the system will generate a reference signal according to the current engine speed (as a drive parameter) to characterize the possible noise characteristics generated by the engine. Then, perform a coherence analysis on the reference signal and the in-vehicle noise signal to obtain the first coherence value. At the same time, the system will also perform a coherence analysis on the external environmental noise (such as wind noise and tire noise) and the in-vehicle noise signal to obtain the second coherence value. If the first coherence value is low while the second coherence value is high, it can be judged that the main source of the current in-vehicle noise is the external environmental noise, rather than the engine noise of this vehicle, thus providing a basis for subsequent noise reduction operations.

[0069] It should be noted that in specific implementation scenarios, based on the above solutions, a multi-sensor data fusion solution can also be adopted. That is, when calculating the first coherence value, in addition to using the engine speed as an input, the data of vibration sensors (such as vibration signals at the firewall) can also be combined to more comprehensively reflect the impact of the vehicle drive device on the in-vehicle noise. When calculating the second coherence value, the signals of more external microphones (such as microphones at positions like the front bumper, rearview mirror, and roof rack) can be introduced, and the direction and intensity of the noise source can be located through beamforming technology.

[0070] In specific implementation scenarios, based on the above solutions, a dynamic time window optimization solution can also be adopted, that is, different time window lengths are set for different scenarios. For example, when driving at high speed, since the wind noise changes rapidly, a shorter time window (such as 50 ms) can be used; while in the parking condition, since the noise is relatively stable, a longer time window (such as 200 ms) can be used. For non-steady-state noise (such as sudden road impact sounds), these transient components can be removed through a filtering algorithm before calculating the coherence value to avoid interfering with the accuracy of the coherence value.

[0071] In specific implementation scenarios, based on the above solutions, a noise fingerprint library matching solution can also be adopted, that is, a noise fingerprint library is established to store the spectral characteristics of different types of noise (such as engine order noise, wind noise, tire noise, etc.). When calculating the coherence value, the in-vehicle noise signal is matched with the characteristics in the fingerprint library to improve the accuracy of noise recognition. For example, for electric vehicles, it can be quickly determined through the fingerprint library whether the external environmental noise is high-frequency motor whine, so as to generate anti-phase sound waves more accurately.

[0072] In specific implementation scenarios, based on the above solutions, a deep learning-assisted coherence value calculation solution can also be adopted, that is, a convolutional neural network (CNN) or a long short-term memory network (LSTM) is used to extract the time-frequency characteristics of the in-vehicle noise signal, and the vehicle state parameters (such as vehicle speed, window state, GPS positioning, etc.) are combined to predict the noise source. For example, before calculating the coherence value, the driving information and location information of the vehicle are obtained. When the system detects that the vehicle is in a tunnel, the impacts of wind noise and echo reverberation can be considered preferentially, and the calculation weight of the coherence value can be adjusted.

[0073] In a specific implementation scenario, based on the above solution, a zoned coherence value calculation scheme can also be adopted, that is, the vehicle interior space is divided into multiple zones (such as the driver's area, the rear passenger area), and the first coherence value and the second coherence value are calculated independently for each zone, so as to more accurately reflect the differences in noise sources in different zones. For example, in the driver's area, it may be mainly affected by engine noise, while in the rear area, it may be more affected by external wind noise or the noise of the vehicle behind. The above optional solutions all fall within the protection scope of this application.

[0074] Step S103: Determine the main noise source of the vehicle from the driving device noise and the external environmental noise according to the first coherence value and the second coherence value, where the driving device noise is generated by the driving device when operating with the driving parameters.

[0075] As described above, based on the comparison result of the first coherence value and the second coherence value, it is judged whether the main source of the current vehicle interior noise is the vehicle's own driving device (such as an engine or a motor) or external environmental noise. The first coherence value reflects the correlation between the vehicle interior noise signal and the parameters of the vehicle driving device, and is used to evaluate the contribution degree of the noise generated by the vehicle's own driving device (such as an engine or a motor) to the vehicle interior noise. If this value is high, it indicates that the vehicle interior noise is mainly caused by the vehicle's own driving device. The second coherence value reflects the correlation between the vehicle interior noise signal and the external environmental noise, and is used to evaluate the influence degree of the external environmental noise (such as wind noise, road noise, the noise of other vehicles, etc.) on the vehicle interior noise. If this value is high, it indicates that the vehicle interior noise is mainly caused by the external environmental noise. By comparing the magnitudes of these two coherence values and combining with a preset threshold for judgment, the type of the main noise source can be clarified. For example, if the first coherence value is significantly higher than the second coherence value, it means that the driving device noise is the main noise source; on the contrary, if the second coherence value is higher, it means that the external environmental noise is the main noise source. This mechanism can dynamically adapt to different driving scenarios and provide an accurate target for generating secondary sound sources subsequently.

[0076] For example, assume a sedan is driving on the highway at a speed of 120 kilometers per hour. At this time, the vehicle interior noise mainly includes the following two parts: driving device noise, that is, the engine is in a high-speed rotation state and generates a certain amount of low-frequency vibration noise; external environmental noise, including the high-frequency noise generated by the friction between the tires and the ground and wind noise. The system obtains based on the coherence algorithm: the first coherence value is 0.3, indicating a low correlation between the vehicle interior noise and the engine noise; the second coherence value is 0.8, indicating a high correlation between the vehicle interior noise and the external environmental noise (especially wind noise and tire noise). According to the determination logic of step S103, the system will identify the external environmental noise as the main noise source and take corresponding noise reduction measures for this part of the noise (such as generating a secondary sound source to cancel the wind noise).

[0077] Suppose the vehicle is stopped at a traffic light on an urban road and a heavy truck starts beside it. At this time, the in-vehicle noise may include the low-frequency noise of the truck engine. Based on the coherence algorithm, the system obtains: the first coherence value is 0.1 because the vehicle's engine is not running and the drive device noise is almost non-existent; the second coherence value is 0.9 because the in-vehicle noise is highly correlated with the external environmental noise (the truck engine noise). Therefore, the system will determine that the external environmental noise is the main noise source and output a secondary sound source accordingly to reduce the low-frequency noise transmitted into the vehicle from the truck.

[0078] It should be noted that in a specific implementation scenario, on the basis of the above scheme, a fuzzy logic control optimization judgment rule scheme can also be adopted, that is, when comparing the coherence values, a fuzzy logic controller is introduced to comprehensively consider the first coherence value, the second coherence value and their differences, and dynamically allocate the weights of internal and external noises. For example, when the first coherence value is close to the second coherence value (such as both are about 0.7), the system can make a weighted decision according to other auxiliary information (such as vehicle speed, window state) to avoid the limitations of single-threshold judgment.

[0079] In a specific implementation scenario, on the basis of the above scheme, a multi-dimensional noise feature fusion scheme can also be adopted, that is, when judging the main noise source, in addition to relying on the coherence value, the energy distribution, spectral characteristics and time-domain characteristics of the noise can also be combined. For example: if the external noise energy suddenly increases and the spectrum is concentrated in the high-frequency band, it is more likely to be wind noise; if the noise energy changes slowly and the spectrum is concentrated in the low-frequency band, it is more likely to be engine noise.

[0080] In a specific implementation scenario, on the basis of the above scheme, a scenario adaptation mechanism scheme can also be adopted, that is, when comparing the coherence values, different judgment strategies are set for different driving scenarios. For example: in the parking condition scenario, give priority to paying attention to the external environmental noise, especially the low-frequency noise (such as the engine sound of the large vehicle beside); in the high-speed cruise scenario, give priority to paying attention to wind noise and tire noise because these noises usually increase significantly with the increase of vehicle speed. At the same time, the scenario mode can be automatically switched through GPS positioning or in-vehicle sensor data (such as vehicle speed, window state).

[0081] In a specific implementation scenario, on the basis of the above scheme, a spatial positioning scheme of the noise source can also be adopted, that is, after determining the main noise source according to the coherence value, the microphone array technology can be further combined to perform spatial positioning on the noise source. For example, by analyzing the data of the acquisition microphones and error microphones at different positions, the specific direction and propagation path of the noise source are determined. This spatial positioning ability helps to optimize the generation strategy of the secondary sound source and make it more accurate to cancel the target noise.

[0082] In a specific implementation scenario, based on the above solution, a user personalized configuration solution can also be adopted, that is, a user interface is provided to allow the driver to adjust the judgment rules of the main noise source according to personal needs. For example: in the "sport mode", even if the first coherence value is high, its weight can be artificially reduced to retain part of the engine sound wave; in the "comfort mode", priority is given to completely eliminating all noises. The above optional solutions all fall within the protection scope of this application.

[0083] Step S104, control the vehicle to output a secondary sound source according to the main noise source.

[0084] As described above, according to the determined main noise source (i.e., vehicle drive device noise or external environmental noise), the vehicle is controlled to output a secondary sound source to cancel or reduce the in-vehicle noise. The secondary sound source is a sound wave signal with a phase opposite to that of the target noise signal and a similar amplitude, and effectively suppresses the in-vehicle noise through active noise cancellation technology (ANC).

[0085] If the main noise source is drive device noise (such as noise generated by an engine or a motor), the system will generate a secondary sound source signal matching the characteristics of the noise and output it through the speakers in the vehicle to cancel the influence of the drive device noise; if the main noise source is external environmental noise (such as wind noise, road noise or other vehicle noises), the system will generate a corresponding secondary sound source signal based on the characteristics of the external environmental noise and output it through the speakers to reduce the interference of these noises on the in-vehicle environment.

[0086] In this process, the system ensures that the parameters (such as frequency, amplitude and phase) of the secondary sound source can accurately match the target noise by comprehensively considering factors such as the spectral characteristics, intensity distribution and propagation path of the noise, so as to achieve the best noise reduction effect.

[0087] For example, assume a sedan is driving on a highway and the system determines that the main noise source is external environmental noise (mainly wind noise and tire noise). At this time: The system will analyze the spectral characteristics of the wind noise and tire noise and find that they are mainly concentrated in the high-frequency band; according to the analysis results, a set of secondary sound source signals with opposite phases and matching amplitudes to the high-frequency band noise will be generated; after the in-vehicle speakers receive these secondary sound source signals, they will play them out, which are superimposed and cancelled with the actual wind noise and tire noise, thus significantly reducing the in-vehicle noise level and improving the comfort of the driver and passengers. Assume that when the vehicle is stopped at a traffic light on an urban road and a heavy truck starts beside it, the system determines that the main noise source is external environmental noise (the low-frequency noise of the truck engine). At this time: The system will analyze the characteristics of the low-frequency noise and generate a set of secondary sound source signals in the low-frequency band; after the speakers play these signals, they interact with the truck engine noise, effectively reducing the impact of the in-vehicle low-frequency noise and preventing the driver and passengers from feeling discomfort due to the low-frequency noise.

[0088] It should be noted that in a specific implementation scenario, based on the above solutions, a multi-region independent control solution can also be adopted, that is, when outputting secondary sound sources, the in-vehicle space is divided into multiple independent regions (such as the driver's area and the rear passenger area), and the sound parameters of the secondary sound sources are adjusted separately for each region. For example, in the driver's area, some ambient sounds may need to be retained so that the driver can perceive the surrounding situation, while in the rear passenger area, stronger noise reduction processing can be implemented to provide a quieter resting environment.

[0089] In a specific implementation scenario, based on the above solutions, a human ear sensitive frequency band priority processing solution can also be adopted, that is, when outputting secondary sound sources, more noise reduction resources are preferentially allocated to the high-frequency band (such as 2 kHz to 4 kHz) that is sensitive to the human ear. For example, when the battery power is low, the system can selectively only perform noise reduction on these sensitive frequency bands to save energy consumption.

[0090] In a specific implementation scenario, based on the above solutions, a noise reduction solution optimized by combining the seat occupancy status can also be adopted, that is, when outputting secondary sound sources, the system can, according to the occupancy status of the seats in the vehicle (such as whether there is a passenger sitting on a certain seat), preferentially strengthen the noise reduction processing for the areas with passengers. For example, if there is no one sitting in the rear seats, the output of the secondary sound sources of the rear speakers can be reduced, and the resources can be concentrated to optimize the noise reduction effect in the front area. The above optional solutions all fall within the protection scope of this application.

[0091] In some embodiments of the present application, in order to effectively identify the noise source that contributes the most to the in-vehicle noise, provide a basis for generating targeted secondary sound sources subsequently, and thus improve the noise reduction effect and ride comfort. The main noise source of the vehicle is determined from the driving device noise and the external environmental noise according to the first coherence value and the second coherence value. Specifically:

[0092] If the first coherence value is greater than the second coherence value and greater than a preset threshold, the driving device noise is taken as the main noise source;

[0093] If the second coherence value is greater than the first coherence value and greater than the preset threshold, the external environmental noise is taken as the main noise source.

[0094] As described above, the first coherence value reflects the correlation degree between the in-vehicle noise and the driving device noise; the second coherence value reflects the correlation degree between the in-vehicle noise and the external environmental noise. The preset threshold is a standard for judging whether the coherence value is significant. Only when the coherence value exceeds this threshold is it considered that the corresponding noise source has a significant impact on the in-vehicle noise. The preset threshold can be determined according to experimental data, empirical values, or the noise characteristics of a specific vehicle model. In this embodiment, the preset threshold is set to 0.8.

[0095] If the first coherence value is greater than the second coherence value and greater than the preset threshold, it means that the correlation between the driving device noise and the in-vehicle noise is stronger, and this correlation exceeds the preset standard. Therefore, the driving device noise can be determined as the main noise source. For example, when the vehicle is accelerating or climbing a slope, the engine speed increases, resulting in an increase in engine noise, and at this time, the first coherence value may be relatively high.

[0096] If the second coherence value is greater than the first coherence value and greater than the preset threshold, it indicates that the correlation between the external environmental noise (such as wind noise, road noise, or other vehicle noises) and the in-vehicle noise is higher, and this correlation also exceeds the preset standard. Therefore, the external environmental noise is identified as the main noise source. For example, when driving at high speed, wind noise and tire noise may be the main sources of in-vehicle noise.

[0097] If neither of the two coherence values exceeds the preset threshold, it indicates that there is no significant single source for the current in-vehicle noise, and it may be caused by the combined action of multiple noises. In this case, the system can adopt a default strategy or further analyze other factors (such as passenger conversations, audio playback, etc.) to decide how to perform noise reduction operations. If the first coherence value and the second coherence value are very close but both exceed the preset threshold, the system can select the main noise source according to the specific situation or consider the influence of both at the same time, and adjust the generation strategy of the secondary sound source to cover a wider noise frequency band.

[0098] Through the above steps, the system can accurately identify the main noise sources of the vehicle based on the real-time collected data and the pre-set rules, thereby providing a clear target for subsequent active noise reduction measures. This process not only improves the flexibility and adaptability of the noise reduction system but also ensures the best noise reduction effect under various driving conditions.

[0099] In some embodiments of the present application, in order to accurately control the vehicle to output targeted secondary sound sources according to the determined main noise sources (driving device noise or external environmental noise) to achieve effective noise cancellation. Controlling the vehicle to output secondary sound sources according to the main noise sources specifically includes:

[0100] If the main noise source is the driving device noise, controlling the vehicle to output the secondary sound source according to the driving device noise;

[0101] If the main noise source is the external environmental noise, controlling the vehicle to output the secondary sound source according to the external environmental noise source.

[0102] As described above, if it is determined that the main noise source is the driving device noise (such as the noise generated by the engine or motor), then enter the secondary sound source generation process for the driving device noise; if the main noise source is the external environmental noise (such as wind noise, road noise or other vehicle noises), then enter the secondary sound source generation process for the external environmental noise.

[0103] Generating a secondary sound source for the driving device noise includes: The system analyzes the specific spectral characteristics, intensity and variation law of the driving device noise. Specifically, the main excitation of the driving device is determined by the engine speed; based on the above results, a secondary sound source signal with a phase opposite to that of the driving device noise and a comparable amplitude is generated; the generated secondary sound source signal is sent to the speakers in the vehicle, and these signals are played through the speakers, thereby forming a sound waveform opposite to the driving device noise in the vehicle to achieve the noise reduction effect.

[0104] Generating a secondary sound source for the external environmental noise includes: The system conducts a detailed spectral analysis of the external environmental noise to determine its frequency distribution, intensity and variation over time; according to the characteristics of the external environmental noise, a corresponding secondary sound source signal is generated; the secondary sound source signal is transmitted to the speakers in the vehicle, and by adjusting the output parameters of the speakers (such as volume, frequency, etc.), it is ensured that the secondary sound source can produce the best noise reduction effect in the vehicle.

[0105] Meanwhile, the system has the ability to monitor the noise change in real time and dynamically adjust the parameters of the secondary sound source according to the actual situation. For example, when the vehicle speed increases and the wind noise intensifies, the system should promptly adjust the frequency and intensity of the secondary sound source to maintain a good noise reduction effect. To more precisely cover the noise in various areas inside the vehicle, the system can output the secondary sound source for the noise characteristics at different positions by means of multiple speakers working together, which can not only improve the noise reduction efficiency but also avoid the problem of uneven local noise reduction that may be caused by a single speaker.

[0106] In some embodiments of the present application, in order to further refine the judgment logic of the main noise source according to the state of the current driving device of the vehicle (whether it includes an engine or only uses a motor), so as to more accurately generate the secondary sound source to achieve effective noise reduction. It also includes:

[0107] If the driving device in the current starting state includes an engine, the driving parameter is the engine noise frequency, and the engine noise frequency is generated according to the current engine speed;

[0108] If the driving device in the current starting state is only a motor, the external environmental noise is taken as the main noise source.

[0109] As described above, when the driving device of the vehicle includes an engine, the system needs to calculate the engine noise frequency according to the current engine speed of the engine. Specifically, the engine speed information is read through the CAN bus, and according to the formula

[0110]

[0111] the engine noise frequency is calculated.

[0112] Based on the calculated engine noise frequency, the system can more accurately analyze the correlation between the noise inside the vehicle and the engine noise, and then determine the first coherence value. Once it is confirmed that the engine noise is the main noise source, the system will generate the corresponding secondary sound source signal according to the specific characteristics of the engine noise and play these signals through the speakers to offset the impact of the engine noise on the interior environment of the vehicle.

[0113] When the driving device of the vehicle is only a motor, in the normal operating state, the noise generated by the motor is usually low and will not have a significant impact on the noise inside the vehicle. Therefore, by default, the external environmental noise (such as wind noise, road noise, etc.) is regarded as the main noise source. When it is determined that the external environmental noise is the main noise source, the system can directly enter the secondary sound source generation process for the external environmental noise, including performing spectral analysis on the external environmental noise, generating a secondary sound source signal with the opposite phase, and playing these signals through the speakers inside the vehicle to achieve the effect of reducing the noise inside the vehicle.

[0114] Through this embodiment, the noise reduction system can adapt to different types of vehicles and their driving modes. Whether it is a traditional fuel vehicle or an electric vehicle, the system can adjust its working mode according to the actual situation to ensure that the best noise reduction effect can always be provided. For example, in a hybrid vehicle, when the vehicle switches driving modes, the system can also correspondingly adjust its noise recognition and noise reduction strategies.

[0115] In some embodiments of the present application, in order to intelligently generate and output targeted secondary sound sources according to the specific vehicle type and the noise environment it is in, significantly reduce the in-vehicle noise, and improve the comfort of the passengers and drivers. The in-vehicle noise is obtained by error microphones arranged inside the vehicle, and the external environmental noise is obtained by acquisition microphones arranged outside the vehicle. Controlling the vehicle to output a secondary sound source according to the main noise source specifically includes:

[0116] Set the sound parameters output by the speakers inside the vehicle according to the noise reduction standard corresponding to the type of the main noise source and the vehicle;

[0117] Control the speakers to output the secondary sound source according to the sound parameters.

[0118] As described above, the in-vehicle noise is collected by error microphones installed inside the vehicle. These error microphones are distributed at different positions inside the vehicle to monitor the actual noise levels in various areas inside the vehicle; the external environmental noise is captured by acquisition microphones installed outside the vehicle. These acquisition microphones are responsible for monitoring various noise sources from outside the vehicle, such as wind noise, road noise, and the noise of other vehicles, etc.

[0119] Different types of vehicles (such as sedans, SUVs, trucks, etc.) have different in-vehicle space structures and usage scenarios, so their noise reduction requirements are also different. The system will set the sound parameters output by the speakers according to the specific type of the vehicle, referring to the corresponding noise reduction standards. For example, for luxury sedans, higher noise reduction standards may be required to provide an extremely quiet experience; while for commercial vehicles, more attention may be paid to practicality and economy, and the cost is balanced on the premise of meeting the basic noise reduction requirements.

[0120] According to the characteristics of the main noise source (such as frequency range, intensity, etc.) and the noise reduction standard corresponding to the vehicle type, the system will calculate the most suitable sound parameters for the secondary sound source. These parameters include but are not limited to the frequency, amplitude, and phase of the secondary sound source, with the aim of enabling the secondary sound source to most effectively cancel out the target noise. For example, if the main noise source is low-frequency engine noise, the system may generate a secondary sound source signal with a corresponding low-frequency band and opposite phase; if it is high-frequency wind noise or tire noise, a high-frequency band secondary sound source signal will be generated.

[0121] The system sends the calculated sound parameters to the speakers in the vehicle, instructing them to play the secondary sound source signal according to the specified parameters. After receiving the instruction, the speakers start to play the secondary sound source signal that matches the main noise source. Since the secondary sound source signal has the same frequency as the target noise but the opposite phase, when the two meet in the vehicle, an interference effect will occur, effectively reducing the noise level in the vehicle. At the same time, the system has the ability of real-time monitoring and dynamic adjustment, and updates the sound parameters of the secondary sound source in a timely manner according to the changes in the vehicle noise, ensuring continuous provision of the optimal noise reduction effect.

[0122] In some embodiments of the present application, in order to formulate and implement precise noise reduction strategies for different types of vehicles and ensure that all vehicles can achieve the best noise control effect within their design ranges. The noise reduction standard is specifically determined in the following manner:

[0123] Determine the vehicle classification level of the vehicle, and each vehicle classification level corresponds to the in-vehicle noise limit values of different levels of vehicles;

[0124] Determine the noise reduction standard of the vehicle according to the in-vehicle noise limit value.

[0125] As described above, the vehicle classification levels are divided based on multiple factors, such as vehicle use (household, commercial, etc.), size, weight, and market positioning, etc. Different classification levels correspond to different performance requirements and user experience standards. For example, vehicles can be divided into different categories such as general vehicles, mid-level vehicles, and high-level vehicles, and each category has its specific design goals and user expectations.

[0126] Each vehicle classification level corresponds to a specific in-vehicle noise limit value (i.e., the maximum noise level, usually in decibels dB), and these limit values reflect the specific requirements of different types of vehicles in terms of noise control. For general vehicles, the in-vehicle noise limit value is usually set to ≤78 dB. Such vehicles are mainly for daily use scenarios and have certain requirements for cost control, so the requirements for noise control are relatively loose; for mid-level vehicles, the in-vehicle noise limit value is set to ≤76 dB. Such vehicles not only provide a good driving experience but also pay attention to cost performance, so the noise limit is more stringent than that of general vehicles; for high-level vehicles, the in-vehicle noise limit value is set to ≤75 dB. Such vehicles pursue extreme comfort and quietness, so they have the highest requirements for in-vehicle noise control.

[0127] The noise reduction standard is determined according to the in-vehicle noise limit values of vehicles at each classification level. That is, the system will adjust the parameters (frequency, amplitude, etc.) of the secondary sound source based on the current main noise sources of the vehicle (such as drive device noise or external environmental noise) in combination with the set maximum allowable in-vehicle noise limit value to ensure that the in-vehicle noise does not exceed the specified limit. For example, if the maximum allowable in-vehicle noise level of a certain high-class vehicle is 75 dB and the currently detected in-vehicle noise reaches 77 dB, the system will calculate the specific decibel value that needs to be reduced and generate an appropriate secondary sound source signal accordingly to make the final in-vehicle noise drop below 75 dB.

[0128] In some embodiments of the present application, in order to improve the efficiency and pertinence of the noise reduction system, flexibly adapt to the situation where different seats are occupied, and ensure the best noise reduction effect for each passenger. A plurality of error microphones are provided, and each of the error microphones corresponds to at least one seat. The method further includes:

[0129] Obtaining the occupancy status of each seat and the in-vehicle area noise collected by each error microphone;

[0130] Adjusting the correction weight of each error microphone according to the occupancy status;

[0131] Correcting the secondary sound source based on the in-vehicle area noise signal of each error microphone and the correction weight of each error microphone.

[0132] As described above, a plurality of error microphones are arranged at different positions inside the vehicle, and each microphone corresponds to at least one seat. For example, error microphones are respectively installed at the positions of the front-row driver and co-driver seats, rear-row seats, etc. These error microphones are used to collect the noise signals in their respective responsible areas (i.e., near the corresponding seats) in real time, helping the system to more accurately understand the spatial distribution of the in-vehicle noise.

[0133] The system first determines whether each seat is occupied through seat sensors or other detection means. At the same time, the system will obtain the current noise data in the area responsible for each error microphone, and these data reflect the actual noise level in a specific area. According to the occupancy status of the seat, the system will assign different correction weights to each error microphone. For example, if a certain seat is not occupied, the correction weight of the error microphone corresponding to that seat may be reduced; on the contrary, if the seat is occupied, the corresponding correction weight will be increased. The adjustment of the correction weight is to ensure that when generating the secondary sound source, the areas with passengers are given priority, so that the noise reduction effect is more concentrated on improving the comfort of passengers.

[0134] The system combines the in-vehicle area noise signals collected by each error microphone with their respective correction weights, and comprehensively calculates the optimal secondary sound source parameters for the entire in-vehicle space. Specifically, the system weights the noise signals provided by each error microphone, and then uses these weighted noise signals to adjust the sound parameters (such as frequency, amplitude, and phase) of the secondary sound source to achieve a better noise reduction effect. This method based on the error microphone signals and correction weights enables the secondary sound source to more accurately cancel the noise in the target area, especially for areas with passengers, further enhancing the pertinence and effectiveness of noise reduction.

[0135] In some embodiments of the present application, in order to generate and adjust the secondary sound source according to the specific noise conditions in different regions in the case of uneven noise distribution inside and outside the vehicle, so as to achieve a more effective noise reduction effect. A plurality of speakers are provided, and the method further includes:

[0136] If the main noise source is the external environmental noise, control each of the speakers to correct the secondary sound source according to the area environmental noise collected by the acquisition microphone closest to each of the speakers.

[0137] As described above, a plurality of speakers are installed at different positions in the vehicle. These speakers are used to play the secondary sound source to cancel the noise in the vehicle. Each speaker is responsible for covering a specific in-vehicle area to ensure that the entire in-vehicle space can be effectively noise-reduced.

[0138] After the system confirms that the main noise source is the external environmental noise, for each speaker, the system will find one or more external acquisition microphones closest to its physical position. These external acquisition microphones are responsible for monitoring the noise level and characteristics (such as frequency and intensity) in the corresponding area outside the vehicle. The system uses the external environmental noise data captured by the acquisition microphone closest to each speaker to adjust the secondary sound source output by the corresponding speaker. For example, if a strong high-frequency wind noise is detected by the external acquisition microphone near a certain speaker, then this speaker will generate a secondary sound source signal with a matching frequency and opposite phase according to this information to specifically cancel this part of the noise. The adjustment process includes but is not limited to modifying the frequency, amplitude, and phase of the secondary sound source so that it can more effectively cancel the target noise.

[0139] By means of this personalized adjustment method for the noise characteristics of each speaker and its nearby area, the noise reduction effect in the local area can be significantly improved. For example, there may be more wind noise near the driver's seat, while the rear seats may be more affected by tire noise. The system can provide the most suitable secondary sound sources for each area according to these differences, so as to achieve the best overall noise reduction experience. And as the driving conditions of the vehicle change (such as the increase in speed leading to enhanced wind noise), the system can update the secondary sound source parameters of each speaker in real time to ensure continuous provision of the optimal noise reduction effect. This dynamic adaptation ability enables the vehicle interior environment to remain quiet and comfortable whether driving on urban roads or highways.

[0140] In some embodiments of the present application, in order to effectively filter out the transient interference factors in the noise signal and ensure that the data used to calculate the first coherence value and the second coherence value is more stable and reliable. Before respectively obtaining the first coherence value and the second coherence value, it further includes:

[0141] Filtering out the non-steady components from the external environmental noise, or collecting the external environmental noise that does not contain the non-steady components;

[0142] And / or, collecting when there is no non-linear fluctuation of the driving parameters within a specified time window.

[0143] As described above, the transient or non-steady components are filtered out from the external environmental noise collected by the external microphone. These non-steady components may include sudden road impact sounds, the honking sounds of other vehicles, or other irregular noises. For example, a low-pass filter is used to remove high-frequency transient noise, or an adaptive filtering technique is applied to identify and filter out sudden noise events. This preprocessing step can ensure that the external environmental noise used to calculate the second coherence value is stable and avoid misjudgment caused by transient noise.

[0144] The system can select to collect the external environmental noise within a specific time period, during which the influence of non-steady noise should be avoided as much as possible. For example, collect when the vehicle is driving on a relatively smooth section or when the surrounding environment is relatively quiet in the parked state. The system can monitor the vehicle state through sensors (such as accelerometers, vehicle speed sensors, etc.) and select an appropriate time to collect the noise to ensure the stability of the data.

[0145] Before calculating the first coherent value, the system needs to ensure that the drive parameters (such as engine speed or motor frequency) do not show significant nonlinear fluctuations within a specified time window. For example, if the engine speed changes dramatically in a short period of time (such as rapid acceleration or deceleration), the data collected at this time may contain more nonlinear components and is not suitable for calculating coherent values. The system can determine whether it is in a stable state by monitoring the rate of change of the engine speed in real time. If the speed change rate is lower than the set threshold within a certain time window (such as 50ms or 100ms), it is considered that the drive parameters are in a stable state and suitable for data collection.

[0146] In practical applications, the above two methods can be used in combination to further improve the reliability and accuracy of the data. For example, the system can select a relatively quiet period of time to collect external environmental noise while detecting that the engine speed is stable, ensuring that both data are free of transient interference as much as possible.

[0147] The system can also dynamically adjust the collection strategy based on the results of real-time monitoring. For example, when a sudden increase in external environmental noise or a fluctuation in engine speed is detected, the system can temporarily stop data collection and wait for conditions to stabilize before continuing. According to different driving scenarios and noise characteristics, the system can flexibly adjust the length of the time window for data collection. For example, when driving at high speed, due to the rapid change of external noise, a shorter time window (such as 50ms) can be used; in parking conditions, the noise is relatively stable, and a longer time window (such as 200ms) can be used.

[0148] Compared with the prior art, the embodiment of the present application discloses a vehicle noise reduction method, which obtains the current external environmental noise and interior noise of the vehicle, obtains a first coherence value based on the driving parameters of the driving device and the interior noise of the vehicle, and obtains a second coherence value based on the external environmental noise and the interior noise, so that the main noise source of the vehicle can be accurately determined from the driving device noise and the external environmental noise, thereby solving the problem in the prior art that it is difficult to distinguish the engine noise of the vehicle from other noises in the external environment, and realizing accurate identification of the main noise source; according to the identified main noise source, the vehicle output secondary sound source is controlled to eliminate or reduce the influence of the main noise source in a targeted manner, thereby improving the efficiency and effect of noise reduction. Compared with the traditional active noise reduction method that only targets a single type of noise (such as engine noise or road noise), this solution is more flexible and effective, and can provide the best noise reduction experience in different scenarios; this method can respond to changes in the external environment of the vehicle in real time, such as when there is a large vehicle next to the vehicle when parking at a red light, and dynamically adjust the noise reduction strategy to adapt to the changing noise environment, ensuring that the driver and passengers can enjoy a relatively quiet and comfortable interior environment in various situations, improving driving comfort and user experience, especially in a complex urban traffic environment.

[0149] To more clearly illustrate the technical solutions provided in the embodiments of the present application, the following will further describe Figure 2 a vehicle noise reduction method provided by the present application.

[0150] In addition, as Figure 2 shown, Figure 2 is a schematic structural diagram of a vehicle noise reduction device provided by an embodiment of the present application. The device includes:

[0151] a noise acquisition module, configured to acquire the current external environmental noise and in-vehicle noise of the vehicle;

[0152] a coherence value calculation module, configured to obtain a first coherence value based on the driving parameters of the driving device of the vehicle and the in-vehicle noise, and obtain a second coherence value based on the external environmental noise and the in-vehicle noise;

[0153] a judgment module, configured to determine the main noise source of the vehicle from the driving device noise and the external environmental noise according to the first coherence value and the second coherence value, where the driving device noise is generated by the driving device when operating at the driving parameters;

[0154] an execution module, configured to control the vehicle to output a secondary sound source according to the main noise source.

[0155] Figure 3 is a schematic structural diagram of a vehicle provided by an embodiment of the present application.

[0156] Exemplarily, as Figure 3 shown, the vehicle includes: a memory and a processor, where the memory stores executable program code, and the processor is configured to call and execute the executable program code to execute the above-mentioned vehicle noise reduction method.

[0157] In this embodiment, the vehicle can be divided into functional modules according to the above method examples. For example, each functional module can be corresponding, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware. It should be noted that the division of modules in this embodiment is illustrative, only a logical function division, and there may be other division methods in actual implementation.

[0158] In the case of dividing each functional module according to each function, the vehicle may include: an analysis module, a judgment module, and an execution module. It should be noted that all relevant contents of each step involved in the above method embodiment can be cited in the function description of the corresponding functional module, and will not be repeated here.

[0159] The vehicle provided in this embodiment is used to execute the above vehicle noise reduction method, so the same effect as the above implementation method can be achieved.

[0160] In the case of adopting an integrated unit, the vehicle may include a processing module and a storage module. Among them, the processing module can be used to control and manage the actions of the vehicle. The storage module can be used to support the vehicle to execute mutual program codes, data, etc.

[0161] Among them, the processing module can be a processor or a controller, which can implement or execute various exemplary logic blocks, modules and circuits shown in combination with the disclosure content of this application. The processor can also be a combination that realizes computing functions, such as including a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc. The storage module can be a memory.

[0162] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0163] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the processes and / or blocks in the flowchart and / or block diagram can also be implemented. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate for implementing in the process Figure 1 one process or multiple processes and / or blocks Figure 1 a device for the functions specified in one block or multiple blocks.

[0164] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing devices to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured product including an instruction device, and the instruction device implements in the process Figure 1 one process or multiple processes and / or blocks Figure 1 a device for the functions specified in one block or multiple blocks.

[0165] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions for implementing the steps of the process Figure 1 one process or a plurality of processes and / or blocks Figure 1 steps for the functions specified in one block or a plurality of blocks.

[0166] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications or equivalent replacements can still be made to the specific embodiments of the present invention. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. A vehicle noise reduction method, characterized in that: include: Obtain the current external environmental noise and interior noise of the vehicle; Obtaining a first coherence value based on a driving parameter of a driving device of the vehicle and the vehicle interior noise, and obtaining a second coherence value based on the external environmental noise and the vehicle interior noise; determining a main noise source of the vehicle from a drive device noise and the external environment noise according to the first coherence value and the second coherence value, wherein the drive device noise is generated when the drive device is running with the drive parameters; The vehicle is controlled to output a secondary sound source based on the primary noise source.

2. The method according to claim 1, characterized in that Determining the main noise source of the vehicle from the driving device noise and the external environment noise according to the first coherence value and the second coherence value is specifically: If the first coherence value is greater than the second coherence value and greater than a preset threshold, the driving device noise is regarded as the main noise source; If the second coherence value is greater than the first coherence value and greater than the preset threshold, the external environmental noise is regarded as the main noise source.

3. The method according to claim 2, characterized in that Controlling the vehicle to output a secondary sound source according to the primary noise source, specifically: If the primary noise source is the driving device noise, controlling the vehicle to output the secondary sound source according to the driving device noise; If the primary noise source is the external environmental noise, the vehicle is controlled to output the secondary sound source according to the external environmental noise source.

4. The method according to claim 3, characterized in that Also includes: If the driving device currently in the startup state includes an engine, the driving parameter is an engine noise frequency, and the engine noise frequency is generated according to a current rotation speed of the engine; If the driving device currently in the startup state is only the motor, the external environmental noise is used as the main noise source.

5. The method according to claim 2, characterized in that The in-vehicle noise is obtained by an error microphone disposed inside the vehicle, and the external environmental noise is obtained by a collection microphone disposed outside the vehicle. The vehicle is controlled to output a secondary sound source according to the main noise source, specifically: Setting sound parameters output by a speaker inside the vehicle according to a noise reduction standard corresponding to the main noise source and the type of the vehicle; The speaker is controlled to output the secondary sound source according to the sound parameter.

6. The method according to claim 5, characterized in that The noise reduction standard is specifically determined by the following method: Determining a vehicle classification level of the vehicle, each of the vehicle classification levels corresponds to a vehicle interior noise limit value of a different grade of vehicle; The noise reduction standard of the vehicle is determined according to the in-vehicle noise limit value.

7. The method according to claim 5, characterized in that There are a plurality of error microphones, and each of the error microphones corresponds to at least one seat. The method further includes: Obtaining the occupancy status of each seat and the in-vehicle regional noise collected by each error microphone; adjusting a correction weight of each of the error microphones according to the occupancy state; The secondary sound source is corrected based on the vehicle interior area noise signal of each error microphone and the correction weight of each error microphone.

8. The method according to claim 5, characterized in that The speaker is provided with a plurality of speakers, and the method further comprises: If the main noise source is the external environmental noise, each of the speakers is controlled to correct the secondary sound source according to the regional environmental noise collected by the collection microphone closest to each of the speakers.

9. A vehicle noise reduction device, characterized in that: The device comprises: The noise collection module is used to obtain the current external environmental noise and the noise inside the vehicle; A coherence value calculation module, configured to obtain a first coherence value based on a driving parameter of a driving device of the vehicle and the vehicle interior noise, and to obtain a second coherence value based on the external environment noise and the vehicle interior noise; a judgment module, configured to determine a main noise source of the vehicle from a driving device noise and the external environment noise according to the first coherence value and the second coherence value, wherein the driving device noise is generated when the driving device operates with the driving parameters; An execution module is used to control the vehicle to output a secondary sound source according to the main noise source.

10. A vehicle, characterized in that: The vehicle comprises: A memory for storing executable program codes; A processor, configured to call and run the executable program code from the memory so that the vehicle executes the method according to any one of claims 1 to 8.

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