CN116913241A

CN116913241A - Active noise reduction method, device and system for vehicle and storage medium

Info

Publication number: CN116913241A
Application number: CN202310970663.5A
Authority: CN
Inventors: 张洁; 柳燕飞; 李龙晨; 许震洪; 支洪平; 雷琴辉; 刘俊峰
Original assignee: iFlytek Co Ltd
Current assignee: iFlytek Co Ltd
Priority date: 2023-08-01
Filing date: 2023-08-01
Publication date: 2023-10-20

Abstract

The application discloses a method, a device, a system and a storage medium for actively reducing noise of a vehicle, which are used for acquiring state information in the running process of the vehicle and an image of a target road surface to be driven in the advancing direction of the vehicle, and analyzing the image to acquire the state information of the target road surface; based on a pre-configured vehicle noise database, inquiring target road noise data corresponding to the combination of the state information of the vehicle and the target road surface state information, determining the amplitude of an active noise reduction signal based on the target road noise data, setting the phase of the active noise reduction signal to be opposite to the phase of the target road noise data, and playing the active noise reduction signal through a loudspeaker in the vehicle after the vehicle enters the target road surface. The method can realize the estimation of the road noise in the vehicle when the vehicle passes through the front road surface based on the constructed vehicle noise database, and further can improve the noise reduction effect through active noise reduction.

Description

Active noise reduction method, device and system for vehicle and storage medium

Technical Field

The application relates to the technical field of vehicle noise reduction, in particular to a vehicle active noise reduction method, device and system and a storage medium.

Background

With the continuous development of the automobile industry, users are particularly dislike road noise in the automobile in the driving process, and the control of the road noise by the whole automobile is particularly complex at present due to different noise level differences in the automobile when the automobile runs on different roads.

In-car road noise frequency bands are usually concentrated in low frequency bands (below 500 Hz), and low frequency band noise is mainly transmitted through a whole car structural member. The traditional passive noise reduction scheme is to analyze the transmission path in the early development process of the whole vehicle, so as to optimize the structure and realize sound insulation and vibration prevention. However, the noise performance after integration cannot be accurately predicted during front-stage development and structure optimization of the whole vehicle, so that the noise optimization from the transmission path is relatively passive. Meanwhile, the trend of light weight also makes the traditional sound insulation and vibration prevention technology limited, and the traditional passive noise reduction means has little effect.

Disclosure of Invention

In view of the above problems, the present application is provided to provide a method, apparatus, system and storage medium for actively reducing noise of a vehicle, so as to reduce road noise in the vehicle in an active noise reduction manner and improve noise reduction effect. The specific scheme is as follows:

in a first aspect, a method for actively reducing noise in a vehicle is provided, including:

Acquiring state information in the running process of a vehicle;

acquiring an image of a target road surface to be driven in the vehicle advancing direction, and analyzing the image to obtain target road surface state information, wherein the target road surface state information comprises various types of parameters affecting road noise in a vehicle;

inquiring target road noise data corresponding to the combination of the state information of the vehicle and the target road surface state information based on a pre-configured vehicle noise database, wherein the vehicle noise database stores a mapping relation among the vehicle state information, the road surface state information and the road noise data in the vehicle, which are built based on the data collected by historic;

and determining the amplitude of an active noise reduction signal based on the target road noise data, setting the phase of the active noise reduction signal to be opposite to the phase of the target road noise data, and playing the active noise reduction signal through a loudspeaker in the vehicle after the vehicle is driven into the target road surface.

Preferably, the method further comprises:

and in the running process of the vehicle, acquiring a vibration signal of a vehicle suspension control system, and carrying out initial phase alignment on the active noise reduction signal based on the vibration signal.

Preferably, determining the amplitude of the active noise reduction signal based on the target road noise data comprises:

Determining the amplitude of the target road noise data as the amplitude of the active noise reduction signal;

or alternatively, the first and second heat exchangers may be,

and adding the amplitude of the target road noise data with a gain, wherein the gain is determined based on a feedback adjustment algorithm as the amplitude of the active noise reduction signal.

Preferably, the method further comprises:

acquiring in-vehicle noise data acquired by an in-vehicle microphone assembly after the vehicle is driven into the target road surface;

and calculating the amplitude difference between the noise data in the vehicle and the noise data of the target road, taking the amplitude difference as an error feedback signal, and determining the gain size based on the error feedback signal so as to calculate the amplitude of the active noise reduction signal at the next moment.

Preferably, the state information includes a vehicle attribute parameter and a running parameter related to a running state of the vehicle; the vehicle attribute parameters include: a first parameter indicative of a vehicle life condition, a second parameter related to a vehicle structure;

the first parameter includes a total driving range;

the second parameter includes any one or more of the following: tire model, vehicle suspension type, vehicle weight, vehicle model;

the driving parameters include any one or more of the following: vehicle speed, gear, travel direction angle, steering wheel angle, and vehicle acceleration and deceleration.

Preferably, the target road surface state information includes any one or more parameters of a road surface type, a road surface roughness, a road surface unevenness, and a road surface construction depth.

Preferably, the process for establishing the vehicle noise database includes:

acquiring state information in the running process of a vehicle;

acquiring an image of a road surface through which a vehicle runs in the running process, and analyzing the image to obtain road surface state information, wherein the road surface state information comprises various types of parameters affecting road noise in the vehicle;

acquiring road noise data in a vehicle in the running process of the vehicle;

and aligning the state information of the vehicle, the road surface state information and the road noise data in the vehicle in time and establishing a time sequence mapping relation to form a vehicle noise database.

Preferably, the acquiring the state information during the running of the vehicle includes:

acquiring real-time vehicle state information in the running process of the vehicle;

the obtaining an image of a road surface through which the vehicle travels in the driving process includes:

acquiring a vision module arranged outside the vehicle, and shooting an image of a road surface in the advancing direction in the running process of the vehicle;

the obtaining road noise data in a vehicle during the running process of the vehicle comprises the following steps:

And acquiring a microphone assembly arranged in the vehicle, and acquiring road noise data in the vehicle in real time in the running process of the vehicle.

Preferably, the aligning the state information of the vehicle, the road surface state information and the road noise data in the vehicle in time and establishing a time sequence mapping relation includes:

aligning the state information of the vehicles collected at the same moment and road noise data in the vehicles;

aiming at a target image shot by the vision module at the ith moment, calculating the duration delta t of the vehicle reaching a pavement area corresponding to the target image based on real-time state information of the vehicle;

and aligning the road surface state information obtained by analyzing the target image shot at the ith moment with the state information of the vehicle and the road noise data in the vehicle acquired at the (i+delta) th moment, and establishing a mapping relation of the state information of the vehicle, the road surface state and the road noise data in the vehicle on time sequence.

Preferably, for the target image shot by the vision module at the ith moment, calculating the duration Δt of the vehicle reaching the road surface corresponding to the target image based on the real-time state information of the vehicle, including:

If the vehicle is in a straight running state at the ith moment based on the state information of the vehicle, calculating the duration delta t of the vehicle reaching a pavement area corresponding to a target image shot by the vision module at the ith moment based on the setting position of the vision module, the shooting visual angle and the real-time speed of the vehicle;

if the vehicle is in a steering state at the ith moment based on the state information of the vehicle, calculating the position of the vehicle at the ith moment based on a constructed vehicle steering model, and calculating the length of a route between road areas corresponding to the target image shot by the vision module at the ith moment;

and calculating the duration delta t of the vehicle reaching the road surface area corresponding to the target image shot by the vision module at the ith moment based on the route length and the real-time speed of the vehicle.

Preferably, the process of analyzing the image to obtain the target road surface state information includes:

and extracting a target area image passed by the tire of the vehicle from the image, and analyzing the target area image to obtain target pavement state information.

In a second aspect, there is provided a vehicle active noise reduction device comprising:

a vehicle state information acquisition unit for acquiring state information during running of the vehicle;

A target road surface state information acquisition unit for acquiring an image of a target road surface to be driven in a vehicle advancing direction and analyzing the image to obtain target road surface state information including various types of parameters affecting road noise in a vehicle;

the road noise estimating unit is used for inquiring target road noise data corresponding to the combination of the target state information of the vehicle and the target road surface state information based on a pre-configured vehicle noise database, wherein the target state information is the state information of the vehicle before entering the target road surface, and the vehicle noise database stores the mapping relation among the vehicle state information, the road surface state information and the road noise data in the vehicle, which are built based on the data collected by history;

the active noise reduction unit is used for determining the amplitude of an active noise reduction signal based on the target road noise data, setting the phase of the active noise reduction signal to be opposite to the phase of the target road noise data, and playing the active noise reduction signal through a loudspeaker in the vehicle after the vehicle is driven into the target road surface.

In a third aspect, a vehicle active noise reduction system is provided, comprising: the system comprises a vision module arranged outside a vehicle, a loudspeaker arranged inside the vehicle, a vehicle state acquisition module and a central processing module;

The vehicle state acquisition module is used for acquiring state information in the running process of the vehicle and sending the state information to the central processing module;

the vision module is used for acquiring an image of a target road surface to be driven in the vehicle advancing direction and sending the image to the central processing module;

the central processing module is used for analyzing the image to obtain target road surface state information, the target road surface state information comprises various parameters affecting road noise in a vehicle, the target road noise data corresponding to the combination of the state information of the vehicle and the target road surface state information is inquired based on a pre-configured vehicle noise database, and the mapping relation among the vehicle state information, the road surface state information and the road noise data in the vehicle, which are established based on the data collected by historic, is stored in the vehicle noise database; and determining the amplitude of an active noise reduction signal based on the target road noise data, setting the phase of the active noise reduction signal to be opposite to the phase of the target road noise data, and controlling the loudspeaker to play the active noise reduction signal after the vehicle is driven into the target road.

Preferably, the method further comprises: the microphone assembly is arranged in the vehicle and is used for collecting noise data in the vehicle after the vehicle is driven into the target road surface and sending the noise data to the central processing module;

The central processing module is further configured to calculate an amplitude difference between the noise data in the vehicle and the noise data of the target road, take the amplitude difference as an error feedback signal, and determine a gain based on the error feedback signal, so as to calculate an amplitude of the active noise reduction signal at a next time.

In a third aspect, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of a vehicle active noise reduction method as described above.

By means of the technical scheme, various factors influencing vehicle road noise data, such as vehicle states, road states on which the vehicle runs and the like, are fully considered, and the vehicle noise database is configured and used for storing the mapping relation among the vehicle state information, the road state information and the road noise data in the vehicle, which are established based on the historical acquisition data. On the basis, the state information in the running process of the vehicle and the image of the target road surface to be driven in the running direction of the vehicle can be acquired, the image is analyzed to obtain the target road surface state information, then the target road noise data corresponding to the combination of the state information of the vehicle and the target road surface state information can be queried based on the vehicle noise database, namely, the target road noise data after the vehicle is driven in the target road surface can be predicted, the amplitude of the active noise reduction signal can be determined based on the target road noise data in an active noise reduction mode, the phase of the active noise reduction signal is set to be opposite to the phase of the target road noise data, and the active noise reduction signal is played through a loudspeaker in the vehicle after the vehicle is driven in the target road surface, so that the active noise reduction is realized. Obviously, the scheme of the application can realize the estimation of the road noise in the vehicle when the vehicle passes through the front road surface based on the constructed vehicle noise database, and the vehicle noise database is established based on the historical acquisition data, and the stored mapping relationship is closer to the real condition, namely more accurate, so that the accuracy of the estimated road noise data in the vehicle can be improved, and the noise reduction effect can be improved by active noise reduction on the basis.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the application. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:

fig. 1 is a schematic structural diagram of an active noise reduction system for a vehicle according to an embodiment of the present application;

FIG. 2 is a schematic diagram of another active noise reduction system for a vehicle according to an embodiment of the present application;

FIG. 3 is a schematic flow chart of a method for actively reducing noise in a vehicle according to an embodiment of the present application;

FIG. 4 illustrates a schematic view of a multi-type pavement;

FIG. 5 illustrates a schematic view of road surface roughness from road surface image analysis;

FIG. 6 illustrates a front view of a straight-line driving model of a vehicle;

FIG. 7 illustrates a top view of a straight-line driving model of a vehicle;

FIG. 8 illustrates a schematic view of a vehicle steering model;

FIG. 9 is an enlarged schematic view of FIG. 8;

fig. 10 is a schematic structural diagram of an active noise reduction device for a vehicle according to an embodiment of the present application;

fig. 11 is a schematic structural diagram of a data processing device according to an embodiment of the present application.

Detailed Description

The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

The application provides a vehicle active noise reduction scheme, which can estimate in-vehicle road noise data when a vehicle passes a road surface at the next moment based on a pre-configured vehicle noise database, and can reduce the in-vehicle road noise level when the vehicle passes the road surface at the next moment in an active noise reduction mode based on the estimated in-vehicle road noise data.

The scheme of the application can be implemented based on vehicle-mounted end equipment (such as a vehicle-mounted vision module, a loudspeaker, various types of sensors, a processor and the like) or service end equipment, or the vehicle-mounted end equipment and the service end equipment cooperatively implement the vehicle active noise reduction scheme of the application.

The vehicle active noise reduction scheme of the present application can be applied to the system shown in fig. 1, including a vision module 10 disposed outside the vehicle, a speaker 11 disposed inside the vehicle, a vehicle state acquisition module 12, and a central processing unit 13. Wherein:

The vehicle state acquisition module 12 is configured to acquire state information during a running process of a vehicle, and send the state information to the central processing module 13.

The vehicle state information may include various types, and in an alternative classification, the vehicle state information may include a vehicle attribute parameter and a driving parameter related to a driving state of the vehicle.

The vehicle attribute parameters may in turn further include a first parameter indicative of a vehicle life condition and a second parameter related to the vehicle structure. The first parameter may include, for example, a total driving range of the vehicle, or a service life of the vehicle. The second parameter examples may include, for example, tire model, vehicle suspension type, vehicle weight, vehicle model, etc.

The driving parameters of the vehicle may include vehicle speed, gear, driving direction angle, steering wheel angle, vehicle acceleration and deceleration, vehicle left turn, vehicle right turn, parking idle, etc.

The vision module 10 is configured to acquire an image of a target road surface to be driven in a vehicle forward direction, and transmit the image to the central processing module 13.

The vision module 10 may employ a vision sensor such as a camera. The number of vision modules 10 may be one or more, and the location may be a roof, front, rear, etc. of the vehicle exterior. Referring to fig. 6 to 7, which illustrate a case where two vision modules 10 are provided on a vehicle, the two vision modules 10 are respectively provided at the front and rear positions of the roof of the vehicle, and the view angle of the front vision module 10 is directed forward for photographing road surface images in front of the vehicle when the vehicle moves forward. The rear vision module 10 is rearward in view and is used to capture a road surface image of the rear of the vehicle as it moves rearward. By disposing the vision module 10 on the roof of the automobile, the viewing angle of the vision module can be increased, and a larger area of road surface can be photographed.

Of course, in some scenarios, the vision module 10 disposed at the rear may be omitted if the road noise in the vehicle is negligible when considering that the speed of the vehicle is not high during reverse.

It should be noted that fig. 6-7 illustrate only one alternative arrangement of the vision module 10, and that the vision module 10 may be located at other external locations on the vehicle, such as at the front of the vehicle, etc.

The central processing module 13 is configured to analyze the image sent by the vision module 10 to obtain target road surface state information, where the target road surface state information includes various types of parameters affecting road noise in a vehicle, and query, based on a pre-configured vehicle noise database, target road noise data corresponding to a combination of the vehicle state information and the target road surface state information, where a mapping relationship between the vehicle state information, the road surface state information, and the road noise data established based on the data collected in history is stored in the vehicle noise database; and determining the amplitude of the active noise reduction signal based on the target road noise data, setting the phase of the active noise reduction signal to be opposite to the phase of the target road noise data, and controlling the loudspeaker 11 to play the active noise reduction signal after the vehicle is driven into the target road.

The above-mentioned central processing module 13 analyzes the image to obtain target road surface state information, wherein the target road surface state information may include various types of parameters affecting road noise in the vehicle, for example, the target road surface state information may include parameters such as road surface type, road surface roughness, road surface unevenness, road surface construction depth, and the like. The road surface roughness refers to the capability of the edges and corners of the road surface aggregate to prevent the tire from sliding, and can be expressed by the road surface friction coefficient. The road surface unevenness refers to a deviation value of the amount of unevenness in the longitudinal direction of the road surface. The road surface structure depth refers to the average depth of open pores with a certain area of road surface irregularities.

The vehicle noise database may be constructed based on data collected from history, and stored in a local database or server of the vehicle, and the construction process of the vehicle noise database will be described in detail in the following embodiments.

In this embodiment, the central processing module 13 may be disposed at the vehicle end, for example, a central control processor of the vehicle may be used as the central processing module 13 of this embodiment, or a central processing module 13 may be additionally disposed on the vehicle. In addition, the central processing module 13 may be disposed at a remote server, and the central processing module 13 may establish a communication connection with the vehicle through the communication module.

According to the scheme, factors affecting the road noise data of the vehicle, such as the vehicle state, the road surface state on which the vehicle runs and the like, are fully considered, and the vehicle noise database is configured and used for storing the mapping relation among the vehicle state information, the road surface state information and the road noise data in the vehicle, which are established based on the historical acquisition data. On the basis, the state information in the running process of the vehicle can be acquired through the vehicle state acquisition module, the image of the target road surface to be driven in the running direction of the vehicle is acquired through the vision module, the image is analyzed through the central processing module to obtain the target road surface state information, further, the target road noise data corresponding to the combination of the state information of the vehicle and the target road surface state information can be queried based on the vehicle noise database, namely, the target road noise data after the vehicle is driven in the target road surface can be predicted, the active noise reduction mode can be adopted, the amplitude of the active noise reduction signal is determined based on the target road noise data, the phase of the active noise reduction signal is set to be opposite to the phase of the target road noise data, and the active noise reduction signal is played through a loudspeaker in the vehicle after the vehicle is driven in the target road surface, so that the active noise reduction is realized. Obviously, the scheme of the application can realize the estimation of the road noise in the vehicle when the vehicle passes through the front road surface based on the constructed vehicle noise database, and the vehicle noise database is established based on the historical acquisition data, and the stored mapping relationship is closer to the real condition, namely more accurate, so that the accuracy of the estimated road noise data in the vehicle can be improved, and the noise reduction effect can be improved by active noise reduction on the basis.

Further, in order to improve the effect of active noise reduction, when calculating the amplitude of the active noise reduction signal, the gain determined by the feedback adjustment algorithm can be introduced in addition to the target road noise data obtained by reference query, that is, the amplitude of the target road noise data can be added with the gain to be used as the amplitude of the active noise reduction signal. To introduce a feedback adjustment algorithm, which requires the acquisition of actual noise data within the vehicle, the vehicle active noise reduction system may further include a microphone assembly 14 disposed within the vehicle as shown in connection with FIG. 2.

The microphone assembly 14 is used for collecting noise data in the vehicle after the vehicle is driven into the target road surface and sending the noise data to the central processing module 13.

The central processing module 13 is further configured to calculate an amplitude difference between the noise data in the vehicle and the noise data of the target road, take the amplitude difference as an error feedback signal, and determine a gain based on the error feedback signal, so as to calculate an amplitude of the active noise reduction signal at a next time.

The microphone assembly is introduced to measure the actual noise level in the vehicle, and then the gain can be calculated through the feedback adjustment algorithm and used for calculating the amplitude of the active noise reduction signal at the next moment, so that the noise reduction effect is improved.

In some embodiments of the present application, the vehicle active noise reduction method of the present application is described in conjunction with FIG. 3. The method is applied to a data processing device, which may be a central processing module shown in fig. 1, for example, and the vehicle active noise reduction method may specifically include the following steps:

step S100, acquiring state information in the running process of the vehicle.

Specifically, the data processing device may directly collect state information during the running process of the vehicle, or may receive state information during the running process of the vehicle uploaded by other modules (such as various types of sensors). The state information of the vehicle may be specifically described with reference to the foregoing embodiments.

Step S110, an image of a target road surface to be driven in the vehicle advancing direction is acquired, and the image is analyzed to obtain target road surface state information.

In this embodiment, the data processing device may receive an image of a target road surface to be driven in a vehicle driving direction uploaded by another module, for example, may receive an image of a target road surface at a set distance in front of a vehicle captured by a vision module disposed outside the vehicle, or may acquire an image of a target road surface to be driven in a vehicle driving direction captured by an aerial photographing device, or may acquire a remote sensing image of a satellite, where the remote sensing image includes an image of a target road surface to be driven in a vehicle driving direction captured by the vehicle driving process.

In this embodiment, the acquired image may be directly analyzed, and the road surface state information may be obtained through recognition. Furthermore, consider a motor vehicleOnly the tire part is contacted with the road surface when passing the road surface so as to generate road noise, therefore, in the embodiment, the image of the target area through which the tire of the vehicle passes can be extracted from the image, and then the image of the target area is analyzed to obtain the road surface state information. As shown in fig. 7, where W is the tire width, the road surface through which the left and right tires pass is the detection road surface L, respectively (four vertexes of the corresponding rectangular area may be denoted as a _R 、A' _R 、B _R 、B' _R ) And detecting the road surface R (four vertexes of the corresponding rectangular region may be denoted as a _L 、A′ _L 、B _L 、B′ _L )。

The road surface state information includes various types of parameters affecting road noise in the vehicle, and may include parameters such as road surface type, road surface roughness, road surface unevenness, road surface construction depth, and the like. Among the road surface types include, but are not limited to: cement road surfaces, asphalt road surfaces, brick road surfaces, gravel road surfaces, other special construction road surfaces, and the like.

As in fig. 4, which illustrates examples of several road surface types, in order from top to bottom: asphalt pavement, cement pavement, hexagonal stone pavement, irregular round pavement and star stone pavement.

In this step, the target road surface state information can be obtained by analyzing the image. As shown in fig. 5, an example of this is analysis of an image to obtain n sets of road surface roughness curves, where each set of road surface roughness curves represents the roughness value of the road surface at each location point along the length of the road surface. Dividing the images along the width direction at set intervals to obtain n groups of sub-images, and sequentially corresponding to n groups of road surface roughness curves.

And in the process of analyzing the image to obtain the target pavement state information, an image analysis algorithm or an image analysis model can be adopted. For example, image samples of various types of pavement may be collected, pavement state information of the image samples may be manually or otherwise marked, and then the image analysis model may be trained using the image samples. After the training of the model is completed, the image analysis model can be utilized to analyze the acquired image of the target road surface, so as to obtain the state information of the target road surface.

Step S120, based on a pre-configured vehicle noise database, inquiring target road noise data corresponding to a combination of the state information of the vehicle and the target road surface state information.

The vehicle noise database stores the mapping relation among vehicle state information, road surface state information and road noise data in the vehicle, which are established based on the data collected by history.

The state information of the vehicle may include state information of each time, and in this step, one target vehicle state information may be determined based on state information of each time between the current time of the vehicle and the time immediately before the vehicle enters the target road surface, for example, the state information of the current time of the vehicle or the time immediately before the vehicle enters the target road surface is directly taken as the target vehicle state information, the target vehicle state information and the target road surface state are combined, and the target road noise data corresponding to the combination is queried based on the vehicle noise database.

Step S130, determining the amplitude of an active noise reduction signal based on the target road noise data, setting the phase of the active noise reduction signal to be opposite to the phase of the target road noise data, and playing the active noise reduction signal through a loudspeaker in the vehicle after the vehicle is driven into the target road surface.

After the target road noise data when the vehicle passes through the target road surface is predicted in the foregoing steps, active noise reduction can be performed by adopting an active noise reduction mode. The magnitude of the active noise reduction signal may be determined based on the magnitude of the target road noise data, such as by determining the magnitude of the target road noise data as the magnitude of the active noise reduction signal, or by adding the magnitude of the target road noise data to a gain in consideration of an error, the result being the magnitude of the active noise reduction signal, wherein the magnitude of the gain may be determined based on a feedback adjustment algorithm.

The phase of the active noise reduction signal is opposite to the phase of the target road noise data. After the vehicle is driven into the target road surface, the active noise reduction signal can be played through the loudspeaker, so that the active noise reduction signal and the generated road noise data are mutually offset, and the purpose of active noise reduction is achieved.

Optionally, the target road noise data may include road noise data at different seats in the vehicle, and after the active noise reduction signal generated in the step is played through a speaker, the amplitude of the sound signal transmitted to each different seat is the same as the amplitude of the road noise data at the corresponding position, and the phases are opposite, so that the noise reduction effect at different seats in the vehicle is ensured.

According to the scheme, factors affecting the road noise data of the vehicle, such as the vehicle state, the road surface state on which the vehicle runs and the like, are fully considered, and the vehicle noise database is configured and used for storing the mapping relation among the vehicle state information, the road surface state information and the road noise data in the vehicle, which are established based on the historical acquisition data. On the basis, the state information in the running process of the vehicle and the image of the target road surface to be driven in the running direction of the vehicle can be acquired, the image is analyzed to obtain the target road surface state information, then the target road noise data corresponding to the combination of the state information of the vehicle and the target road surface state information can be queried based on the vehicle noise database, namely, the target road noise data after the vehicle is driven in the target road surface can be predicted, the amplitude of the active noise reduction signal can be determined based on the target road noise data in an active noise reduction mode, the phase of the active noise reduction signal is set to be opposite to the phase of the target road noise data, and the active noise reduction signal is played through a loudspeaker in the vehicle after the vehicle is driven in the target road surface, so that the active noise reduction is realized. Obviously, the scheme of the application can realize the estimation of the road noise in the vehicle when the vehicle passes through the front road surface based on the constructed vehicle noise database, and the vehicle noise database is established based on the historical acquisition data, and the stored mapping relationship is closer to the real condition, namely more accurate, so that the accuracy of the estimated road noise data in the vehicle can be improved, and the noise reduction effect can be improved by active noise reduction on the basis.

In some embodiments of the present application, a scheme for initial phase alignment of an active noise reduction signal is provided.

Specifically, during vehicle travel, a vibration signal of a vehicle suspension control system may be acquired, and an initial phase alignment may be performed on the active noise reduction signal based on the vibration signal.

The above-mentioned process of performing initial phase alignment on the active noise reduction signal may be performed once after the vehicle is started, or may be performed once again every fixed period in the following vehicle driving process, and the specific policy may be set according to the user selection.

In some embodiments of the present application, a feedback adjustment algorithm is further provided during the active noise reduction process described above. Specifically:

and after the vehicle is driven into the target road surface, acquiring the noise data in the vehicle, which are acquired by the microphone component in the vehicle. Whether the noise data in the vehicle accords with the expected noise level can be judged, for example, whether the noise size in the vehicle is lower than a set threshold value is judged, if yes, the noise reduction effect is good, otherwise, the noise reduction effect needs to be optimized, the amplitude difference between the noise data in the vehicle and the noise data of the target road can be further calculated, the amplitude difference is used as an error feedback signal, the gain size is determined based on the error feedback signal, and the amplitude of the active noise reduction signal is calculated at the next moment, so that the noise reduction effect is continuously corrected through feedback adjustment.

In some embodiments of the present application, the process of creating the vehicle noise database used in the foregoing embodiments is further described.

The process of establishing the vehicle noise database needs to be based on data collected by historic data, the historic data can be collected by a plurality of different vehicles in the actual running process, and the vehicle for collecting the historic data can be different from or comprises the vehicle for actively reducing noise. Since the history data needs to contain road noise data in the vehicle, the vehicle interior needs to be provided with a microphone assembly. The execution body for constructing the vehicle noise database may be the same as or different from the aforementioned body for executing active noise reduction of the vehicle, and in this embodiment, taking the same execution body as an example, the process for establishing the vehicle noise database is introduced, and the method may include the following steps:

s1, acquiring state information in the running process of the vehicle.

Specifically, the state information of the vehicle may be specifically referred to the description of the foregoing embodiment.

S2, obtaining an image of a road surface through which the vehicle runs in the running process, and analyzing the image to obtain road surface state information.

Specifically, an image of a road surface through which the vehicle travels may be acquired through various approaches, for example, an image of a road surface captured by a vision module disposed outside the vehicle may be acquired, or an image of a road surface captured by an aerial photographing device for the vehicle traveling may be acquired, or a remote sensing image of a satellite may be acquired, where the remote sensing image includes an image captured for the vehicle traveling.

In this embodiment, the acquired image may be directly analyzed, and the road surface state information may be obtained through recognition. In addition, considering that road noise is generated due to contact between the tire part and the road surface when the automobile passes through the road surface, the image of the target area through which the tire of the automobile passes can be extracted from the image, and then the image of the target area is analyzed to obtain the road surface state information.

The road surface state information may include various types of parameters affecting road noise in the vehicle, and may include, for example, parameters of road surface type, road surface roughness, road surface unevenness, road surface construction depth, and the like.

The process of analyzing the image to obtain the road surface state information can adopt an image analysis algorithm or an image analysis model. For example, image samples of various types of pavement may be collected, pavement state information of the image samples may be manually or otherwise marked, and then the image analysis model may be trained using the image samples. After training of the model is completed, the acquired road surface image can be analyzed by using the image analysis model, so that road surface state information is obtained.

S3, acquiring road noise data in the vehicle in the running process of the vehicle.

In particular, road noise data in the vehicle during the driving of the vehicle may be collected by a microphone assembly in the vehicle.

In consideration of the possible difference in the magnitudes of road noise at different seats in the vehicle interior space, the road noise data at different seats in the vehicle during the running of the vehicle can be acquired in the present embodiment. For example, microphone assemblies may be provided in the vicinity of different seats in the vehicle, respectively, for collecting road noise data at the corresponding seats and uploading to the data processing device.

And S4, aligning the state information of the vehicle, the road surface state information and the road noise data in the vehicle in time and establishing a time sequence mapping relation to form a vehicle noise database.

Specifically, the vehicle state information, the road surface state information, and the in-vehicle road noise data acquired in the above steps are all time-dependent data. In this step, three kinds of data can be aligned in time, and a mapping relation in time sequence is established, that is, road noise data in a vehicle at each moment, corresponding state information of the vehicle at the moment and road surface state information passed by the vehicle are determined, and the obtained mapping relation is combined into a vehicle noise database.

According to the vehicle noise database construction method provided by the embodiment of the application, factors affecting vehicle road noise data, such as vehicle states, road states on which the vehicle runs and the like, are fully considered, on the basis, state information in the running process of the vehicle and road images passed by the running process of the vehicle are acquired, the images are analyzed to obtain the road state information, and the road noise data in the vehicle in the running process of the vehicle is acquired. The obtained various types of data are all related to time, so that the obtained state information of the vehicle, the road surface state and the road noise data in the vehicle can be aligned in time and a time sequence mapping relation is established, namely, the road noise data in the vehicle at each moment, the corresponding state information of the vehicle at the moment and the road surface state information passed by the vehicle are determined, the obtained mapping relation is combined into a vehicle noise database, and the acquisition process of the vehicle road noise data is completed. Obviously, the method can determine the corresponding vehicle state information and the road surface state information of the vehicle according to the vehicle interior road noise data at different moments in the vehicle driving process, namely the vehicle interior road noise data in various scenes is covered, and support is provided for the follow-up implementation of the vehicle active noise reduction method.

Further optionally, after the vehicle noise database is obtained, the vehicle noise database may be further processed, for example, road noise data in the vehicle may be analyzed according to different dimensions, such as analyzing vehicle noise data in different life stages, different vehicle speeds, and different road states of the vehicle. The data tracking and analysis of the whole life cycle of the vehicle can be realized.

In addition, on the basis of the vehicle noise database, interpolation or fitting can be performed on the data, the vehicle noise data is represented as z, the vehicle state information is represented as x, and the road surface state information is represented as y, so that z=f (x, y) can be obtained through fitting, wherein f represents a function after fitting.

By the data processing, a mapping function between the vehicle noise data and the vehicle state information and road surface state information can be obtained. When the active noise reduction is carried out based on the vehicle noise database in the follow-up, the vehicle noise data can be estimated based on the mapping function, and then the active noise reduction processing can be realized.

In some embodiments of the present application, the above step S4 is a process of aligning the state information of the vehicle, the road surface state information, and the road noise data in the vehicle in time and establishing a time-series mapping relationship.

It should be noted that, the state information of the vehicle is obtained in real time during the running process of the vehicle, that is, corresponding vehicle state information exists at different moments. The road noise data in the vehicle can be the microphone assembly, and the road noise data in the vehicle is collected in real time in the running process of the vehicle. Therefore, the state information of the vehicle and the road noise data in the vehicle are directly aligned in time, namely the state information of the vehicle and the road noise data in the vehicle, which are collected at the same time, can be directly aligned, and a mapping relation between the state information and the road noise data in the vehicle is established.

The image of the road surface through which the vehicle runs in the running process can be the image which is shot by the vision module on the road surface in the advancing direction of the vehicle and is also real-time, but because the road surface image shot by the vision module is positioned in front of the vehicle and is not the road surface position where the vehicle is positioned at the current moment, the time length which is needed for the vehicle to take from the current position to reach the road surface area corresponding to the image shot at the current moment needs to be further calculated.

Specifically, for a target image shot by the ith moment vision module, calculating the duration delta t of the vehicle reaching the road surface corresponding to the target image based on the real-time state information of the vehicle.

On the basis, the road surface state information obtained by analyzing the target image shot at the ith moment is aligned with the state information of the vehicle and the road noise data in the vehicle acquired at the (i+delta t) moment, and a mapping relation of the state information of the vehicle, the road surface state and the road noise data in the vehicle on time sequence is established.

In some embodiments of the present application, the above-described calculation process of the time period Δt is explained.

In this embodiment, the calculation process of the duration Δt in the two states may be introduced separately according to whether the vehicle is in the straight-line running state or the steering state at the i-th time.

Wherein it can be determined whether the vehicle is in a straight running state or a steering state at the i-th time based on the state information of the vehicle. The state information of the vehicle may include parameters such as a speed and a steering angle of the vehicle at each time, and it may be determined whether the vehicle is in a straight running state or a steering state at the i-th time based on the steering angle of the vehicle.

1. If the vehicle is in the straight running state at the ith moment based on the state information of the vehicle:

the duration Δt of the vehicle reaching the road surface area corresponding to the target image photographed by the vision module at the i-th moment can be calculated based on the setting position of the vision module, the photographing view angle, and the real-time speed of the vehicle.

As shown in connection with fig. 6:

assuming that the height of the vision module from the ground is H, the distance between the vision module and the projection point D, C of the tire center on the ground is P, the furthest point which can be identified by the shooting view angle of the vision module is A, the closest point which can be identified is B, and the included angles between the upper edge and the lower edge of the shooting view angle of the vision module and the ground are alpha and beta respectively.

Selecting a point on the AB road as a mark point of the AB road area, for example, setting the midpoint A of the AB road _C As a marker point of the AB road section area, a distance from the vehicle to the road surface area corresponding to the target image photographed by the vision module at the i-th time may be represented as S.

The vehicle speed is denoted as V, and V, H, P, α, β are all known parameters, which can be calculated as:

the duration delta t of the road surface area corresponding to the target image shot by the vision module at the ith moment when the vehicle reaches the position at the current moment is as follows:

Δt＝S/V

2. if the vehicle is determined to be in a steering state at the ith moment based on the state information of the vehicle:

as shown in fig. 8 and 9 in combination, a vehicle steering model (fig. 8 and 9 are only exemplarily illustrated with a model when the vehicle is steered right) may be constructed. Based on the constructed vehicle steering model, calculating the position of the vehicle at the ith moment, and the length of the route between road surface areas corresponding to the target image shot by the vision module at the ith moment, namely the arc length A' _C C。

Specifically:

in FIG. 8, the projected point of the tire on the ground is C, and the vertical line is drawn at the C point along the direction perpendicular to the advancing direction of the tire, passing throughAnd (3) crossing the circle center O, and making a circle by taking OC as a radius. And taking the center point of the wheelbase of the vehicle, and making a vertical line along the direction vertical to the wheelbase, wherein the vertical line passes through the circle center O and intersects with the edge of the circle at the point E. The vision module detects forward along a straight line, the detected area is shown as the vehicle tire runs forward along the edge curve of the circle, and when the vehicle tire runs near the straight line detection area, the projection point of the tire on the ground is shown as A' _C . Line segment OA' _C Intersection of the extension line of line CC 'with the extension line of line CC' at point A _C 。

When the vehicle turns, knowing that the steering angle of the steering wheel of the vehicle is a', and the wheelbase of the vehicle is L:

β′＝k*a′

k is a coefficient of steering angle of the automobile along with steering of the steering wheel, and is a constant.

The calculation formula of the steering radius of the automobile can be known:

it follows from the trigonometric function relation that:

arc length A' _C C＝OC*γ′

Namely:

The following describes the vehicle active noise reduction device provided by the embodiment of the present application, and the vehicle active noise reduction device described below and the vehicle active noise reduction method described above may be referred to correspondingly.

Referring to fig. 10, fig. 10 is a schematic structural diagram of an active noise reduction device for a vehicle according to an embodiment of the present application.

As shown in fig. 10, the apparatus may include:

a vehicle state information acquisition unit 100 for acquiring state information during running of the vehicle;

a target road surface state information acquisition unit 110 for acquiring an image of a target road surface to be driven in a vehicle advancing direction, and analyzing the image to obtain target road surface state information including various types of parameters affecting road noise in a vehicle;

the road noise estimating unit 120 is configured to query, based on a preconfigured vehicle noise database, target road noise data corresponding to a combination of target state information of a vehicle and the target road surface state information, where the target state information is state information of the vehicle before entering the target road surface, and a mapping relationship between the vehicle state information, the road surface state information and the road noise data in the vehicle, which is established based on data collected by history, is stored in the vehicle noise database;

The active noise reduction unit 130 is configured to determine an amplitude of an active noise reduction signal based on the target road noise data, set a phase of the active noise reduction signal opposite to a phase of the target road noise data, and play the active noise reduction signal through a speaker in the vehicle after the vehicle is driven into the target road surface.

Optionally, the apparatus of the present application may further include:

and the initial phase alignment unit is used for acquiring a vibration signal of a vehicle suspension control system in the running process of the vehicle and carrying out initial phase alignment on the active noise reduction signal based on the vibration signal.

Optionally, the process of determining the amplitude of the active noise reduction signal by the active noise reduction unit based on the target road noise data includes:

or alternatively, the first and second heat exchangers may be,

Optionally, the apparatus of the present application may further include:

the in-vehicle noise data acquisition unit is used for acquiring in-vehicle noise data acquired by the in-vehicle microphone assembly after the vehicle is driven into the target road surface;

And the feedback adjusting unit is used for calculating the amplitude difference between the noise data in the vehicle and the noise data of the target road, taking the amplitude difference as an error feedback signal, and determining the gain size based on the error feedback signal so as to calculate the amplitude of the active noise reduction signal at the next moment.

Optionally, the apparatus of the present application may further include: a vehicle noise database creation unit for creating a vehicle noise database, the process comprising:

acquiring state information in the running process of a vehicle;

acquiring road noise data in a vehicle in the running process of the vehicle;

Optionally, the process of acquiring the state information in the running process of the vehicle by the vehicle noise database building unit includes:

A process of acquiring an image of a road surface through which a vehicle travels by a vehicle noise database creation unit, comprising:

the process of acquiring road noise data in a vehicle during the running of the vehicle by the vehicle noise database building unit comprises the following steps:

Further, the process of aligning the state information of the vehicle, the road surface state information, and the road noise data in the vehicle in time and establishing a mapping relationship in time sequence by the vehicle noise database establishing unit includes:

Optionally, the process of calculating, by the vehicle noise database building unit, for the target image captured by the vision module at the ith moment and based on the real-time state information of the vehicle, a duration Δt of the vehicle reaching a road surface corresponding to the target image includes:

Optionally, the process of analyzing the image by the vehicle noise database building unit to obtain the road surface state information includes:

And extracting a target area image through which the tire of the vehicle passes from the image, and analyzing the target area image to obtain pavement state information.

The vehicle active noise reduction device provided by the embodiment of the application can be applied to data processing equipment, such as a vehicle-mounted terminal, a server and the like. Alternatively, fig. 11 shows a block diagram of a hardware structure of a data processing apparatus, and referring to fig. 11, the hardware structure of the apparatus may include: at least one processor 1, at least one communication interface 2, at least one memory 3 and at least one communication bus 4;

in the embodiment of the application, the number of the processor 1, the communication interface 2, the memory 3 and the communication bus 4 is at least one, and the processor 1, the communication interface 2 and the memory 3 complete the communication with each other through the communication bus 4;

processor 1 may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement embodiments of the present application, etc.;

the memory 3 may comprise a high-speed RAM memory, and may further comprise a non-volatile memory (non-volatile memory) or the like, such as at least one magnetic disk memory;

Wherein the memory stores a program, the processor is operable to invoke the program stored in the memory, the program operable to:

acquiring state information in the running process of a vehicle;

Alternatively, the refinement function and the extension function of the program may be described with reference to the above.

The embodiment of the present application also provides a storage medium storing a program adapted to be executed by a processor, the program being configured to:

Acquiring state information in the running process of a vehicle;

Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

In the present specification, each embodiment is described in a progressive manner, and each embodiment focuses on the difference from other embodiments, and may be combined according to needs, and the same similar parts may be referred to each other.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method of actively reducing noise in a vehicle, comprising:

acquiring state information in the running process of a vehicle;

2. The method as recited in claim 1, further comprising:

3. The method of claim 1, wherein determining the magnitude of the active noise reduction signal based on the target road noise data comprises:

or alternatively, the first and second heat exchangers may be,

4. A method according to claim 3, further comprising:

5. The method of claim 1, wherein the status information includes vehicle attribute parameters and travel parameters related to a vehicle travel status; the vehicle attribute parameters include: a first parameter indicative of a vehicle life condition, a second parameter related to a vehicle structure;

the first parameter includes a total driving range;

6. The method of claim 1, wherein the target road surface state information comprises any one or more of a road surface type, a road surface roughness, a road surface unevenness, a road surface construction depth.

7. The method according to any one of claims 1-6, wherein the establishing of the vehicle noise database comprises:

Acquiring state information in the running process of a vehicle;

acquiring road noise data in a vehicle in the running process of the vehicle;

8. The method of claim 7, wherein the obtaining status information during travel of the vehicle comprises:

9. The method of claim 8, wherein temporally aligning the state information of the vehicle, the road surface state information, and the road noise data in the vehicle and establishing a time-series mapping relationship comprises:

10. The method according to claim 9, wherein for the target image captured by the vision module at the i-th time, calculating a time period Δt for the vehicle to reach a road surface corresponding to the target image based on real-time state information of the vehicle, includes:

11. An active noise reduction device for a vehicle, comprising:

12. An active noise reduction system for a vehicle, comprising: the system comprises a vision module arranged outside a vehicle, a loudspeaker arranged inside the vehicle, a vehicle state acquisition module and a central processing module;

13. The system of claim 12, further comprising: the microphone assembly is arranged in the vehicle and is used for collecting noise data in the vehicle after the vehicle is driven into the target road surface and sending the noise data to the central processing module;

14. A storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the vehicle active noise reduction method according to any one of claims 1 to 10.