In-vehicle sound wave generation method, controller, system, vehicle, and medium

Abstract

The application discloses an in-vehicle sound wave generation method, a controller, a system, a vehicle and a medium, and relates to the technical field of vehicles. The in-vehicle sound wave generation method is applied to a new energy vehicle and comprises the following steps: obtaining a target sound wave type, vehicle working condition information and first target vehicle parameter information; and generating a target sound wave signal of the target sound wave type according to the target sound wave type, the vehicle working condition information and the first target vehicle parameter information. The in-vehicle sound wave generation method provided by the application can be applied to a new energy vehicle and can solve the problem of high limitation of a traditional sound wave synthesis mode of a new energy vehicle.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and more specifically, to a method for generating in-vehicle sound, a vehicle controller, an in-vehicle sound playback system, a vehicle, and a computer-readable storage medium. Background Technology

[0002] With the development of science and technology and the economy, new energy vehicles, such as electric vehicles, are being used more and more widely.

[0003] However, the working principle of the power system of new energy vehicles differs from that of traditional gasoline vehicles. This results in new energy vehicles producing relatively less engine noise during operation. This quiet driving environment means that new energy vehicles lack the dynamic feel provided by the engine noise of traditional gasoline vehicles, thus reducing the driver's experience. Therefore, to improve the driver's experience, some new energy vehicles currently possess the ability to synthesize the engine noise of traditional gasoline vehicles, mimicking the sound of those vehicles. However, this means that the engine noise synthesis method for new energy vehicles cannot be separated from that of traditional gasoline vehicles, indicating a high degree of limitation in the engine noise synthesis method for new energy vehicles. Summary of the Invention

[0004] One objective of this application is to provide a new technical solution for synthesizing sound waves in electric vehicles.

[0005] According to a first aspect of this application, a method for synthesizing in-vehicle sound is provided, applicable to new energy vehicles, including:

[0006] Acquire the target sound type, vehicle operating condition information, and parameter information of the first target vehicle;

[0007] Based on the target sound wave type, vehicle operating condition information, and first target vehicle parameter information, a target sound wave signal of the target sound wave type is generated;

[0008] The target sound wave signal is processed for in-vehicle playback.

[0009] Optionally, the target sound type includes the desired listening experience type and / or the desired number of engine cylinders, and the first target vehicle parameter information includes at least common parameter information, which is parameter information shared by the new energy vehicle and the non-new energy vehicle.

[0010] Optionally, generating a target sound wave signal of the target sound wave type based on the target sound wave type, vehicle operating condition information, and first target vehicle parameter information includes:

[0011] Based on the target sound wave type, a target mapping relationship is determined from multiple candidate mapping relationships. Each candidate mapping relationship corresponds to a candidate sound wave type, and the candidate mapping relationship reflects the correspondence between the vehicle operating condition information of the new energy vehicle, the first target vehicle parameter information, and the sound wave signal of the corresponding candidate sound wave type.

[0012] Based on the vehicle operating condition information, the first target vehicle parameter information, and the target mapping relationship, a target sound wave signal of the target sound wave type is generated.

[0013] Optionally, the method further includes:

[0014] The steps to obtain the candidate mapping relationships;

[0015] The process of obtaining candidate mapping relationships includes:

[0016] Obtain a training sample set, which includes multiple sets of training samples. Each set of training samples includes sample non-new energy vehicle parameter information, sample non-new energy vehicle operating condition information, and sample non-new energy vehicle sound signals of the candidate sound wave type corresponding to the candidate mapping relationship.

[0017] The candidate mapping relationship is obtained based on the training sample set.

[0018] Optionally, obtaining the training sample set includes:

[0019] Acquire actual sound signals from multiple non-new energy vehicles;

[0020] For any of the actual sound wave signals, determine the sound wave type and evaluation result of the actual sound wave signal based on the actual sound wave signal;

[0021] Among the actual sound wave signals belonging to the same sound wave type, the actual sound wave signals that output excellent evaluation results correspond to non-new energy vehicles and are used as sample non-new energy vehicles of the corresponding sound wave type.

[0022] For any type of sound wave, non-new energy vehicles are sampled, and training samples are collected based on the non-new energy vehicles.

[0023] Optionally, the first target vehicle parameter information includes shared parameter information and virtual parameter information. The shared parameter information is the parameter information that is shared by the new energy vehicle and the non-new energy vehicle, and the virtual parameter information is the parameter information that the new energy vehicle lacks compared to the non-new energy vehicle.

[0024] The method further includes:

[0025] For any candidate mapping relationship, obtain sample new energy vehicle parameter information and sample new energy vehicle operating condition information. The sample new energy vehicle parameter information includes common sample parameter information and virtual sample parameter information.

[0026] Based on the candidate mapping relationship, determine the test sound signals corresponding to the sample new energy vehicle parameter information and sample new energy vehicle operating condition information;

[0027] If the test sound wave signal does not conform to the candidate sound wave type corresponding to the candidate mapping relationship, adjust the parameter value corresponding to the sample virtual parameter information to obtain updated virtual sample parameter information;

[0028] The updated virtual sample parameter information and the common sample parameter information are used as the sample new energy vehicle parameter information. The process of determining the test sound wave signal corresponding to the sample new energy vehicle parameter information and the sample new energy vehicle operating condition information according to the candidate mapping relationship is repeated until the test sound wave signal matches the candidate sound wave type corresponding to the candidate mapping relationship.

[0029] The virtual sample parameter information of the test sound wave signal that conforms to the selected sound wave type corresponding to the selected mapping relationship is used as the optimal virtual parameter information corresponding to the selected mapping relationship.

[0030] Optionally, after determining the target mapping relationship from a plurality of candidate mapping relationships based on the target sound wave type, the method further includes:

[0031] The optimal virtual parameter information corresponding to the target mapping relationship and the common parameter information are used as the first target vehicle parameter information.

[0032] Optionally, the method further includes:

[0033] A first display interface is provided, which displays the optimal virtual parameter information corresponding to the target mapping relationship;

[0034] In response to the adjustment input of the optimal virtual parameter information corresponding to the target mapping relationship, the adjusted virtual parameter information is obtained;

[0035] The step of generating a target sound wave signal of the target sound wave type based on the vehicle operating condition information, the first target vehicle parameter information, and the target mapping relationship includes:

[0036] Based on the vehicle operating condition information, the second target vehicle parameter information, and the target mapping relationship, a target sound wave signal of the target sound wave type is generated. The second target vehicle parameter information includes the adjusted virtual parameter information and the common parameter information in the first target vehicle parameter information.

[0037] Optionally, the method further includes:

[0038] Provide input interface;

[0039] In response to input operations on the input interface, obtain information on setting virtual parameters;

[0040] The step of generating a target sound wave signal of the target sound wave type based on the vehicle operating condition information, the first target vehicle parameter information, and the target mapping relationship includes:

[0041] Based on the vehicle operating condition information, the third target vehicle parameter information, and the target mapping relationship, a target sound wave signal of the target sound wave type is generated. The third target vehicle parameter information includes: setting virtual parameter information and common parameter information in the first target vehicle parameter information.

[0042] Optionally, the shared parameter information includes in-vehicle sound field characteristics, and the virtual parameter information includes: engine parameters, acoustic characteristics of the intake and exhaust system, location of the sound wave transmission device, and any combination of the acoustic characteristics of the sound wave transmission device.

[0043] Optionally, the vehicle operating condition information includes any combination of motor speed, vehicle speed, accelerator pedal opening, and brake pedal opening.

[0044] Optionally, acquiring the target sound wave type, vehicle operating condition information, and first target vehicle parameter information includes:

[0045] Inspect the vehicle's powertrain type;

[0046] When the vehicle power type is a new energy type, the target sound type, vehicle operating condition information, and first target vehicle parameter information are obtained.

[0047] Optionally, obtaining the target sound wave type includes:

[0048] A second display interface is provided, which displays different selectable sound wave types;

[0049] In response to the selection input for the candidate sound wave type, the target sound wave type is determined based on the selection input.

[0050] According to a second aspect of this application, a vehicle controller is provided, the vehicle controller including a memory and a processor, the memory for storing computer instructions, and the processor for recalling the computer instructions from the memory to perform the method as described in any one of the first aspects.

[0051] According to a third aspect of this application, a vehicle is provided, including a vehicle controller as described in the second aspect.

[0052] According to a fourth aspect of this application, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method described in any one of the first aspects.

[0053] This application provides a method for generating in-vehicle sound waves, applicable to new energy vehicles. The method includes: acquiring a target sound wave type, vehicle operating condition information, and first target vehicle parameter information; generating a target sound wave signal of the target sound wave type based on the target sound wave type, vehicle operating condition information, and first target vehicle parameter information; and performing in-vehicle playback processing on the target sound wave signal. The in-vehicle sound wave generation method for new energy vehicles provided by this application can be separated from traditional fuel vehicles, solving the problem of high limitations in traditional sound wave synthesis methods for new energy vehicles.

[0054] Other features and advantages of this application will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0055] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments of the present application and, together with their description, serve to explain the principles of the present application.

[0056] Figure 1 This is a flowchart illustrating a method for generating in-vehicle sound waves provided in this application;

[0057] Figure 2 This is a schematic diagram of the structure of a vehicle controller provided in this application. Detailed Implementation

[0058] Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present application.

[0059] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the scope of this application and its application or use.

[0060] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0061] In all the examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0062] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0063] This application provides a method for generating in-vehicle sound, which can be applied to new energy vehicles, such as... Figure 1 As shown, the method includes the following steps S110 to S130.

[0064] Step S110: Obtain the target sound type, vehicle condition information, and parameter information of the first target vehicle.

[0065] In this embodiment, the new energy vehicle can be an electric vehicle, a hybrid electric vehicle, or a gas-electric hybrid vehicle. The non-new energy vehicle refers to any vehicle other than a new energy vehicle, such as a traditional gasoline-powered vehicle.

[0066] In one embodiment of this application, the target sound type includes a desired auditory experience type and / or a desired number of engine cylinders. The first target vehicle parameter information includes at least common parameter information, which is parameter information shared by both new energy vehicles and non-new energy vehicles.

[0067] The target sound type is the sound type desired by users of new energy vehicles. Examples of desired sound quality include: sporty, quiet, technological, and comfortable. Examples of desired engine cylinder count include: 2-cylinder, 4-cylinder, and 6-cylinder.

[0068] In one embodiment of this application, the target sound wave type can be specified by the user. Based on this, the method for obtaining the target sound wave type in step S110 above can be implemented according to the following steps S111 and S112.

[0069] Step S111: Provide a second display interface, which displays different selectable sound wave types.

[0070] Step S112: In response to the selection input for the candidate sound wave type, determine the target sound wave type based on the selection input.

[0071] In this embodiment, the candidate sound wave types can be displayed on the second display interface. The user can select the sound wave type that meets their needs from the candidate sound wave types displayed on the second display interface by making a selection input. The candidate sound wave type selected by the user is recorded as the target sound wave type.

[0072] In this embodiment, the shared parameter information refers to parameters common to both new energy vehicles and non-new energy vehicles. In one embodiment, the shared parameter information includes in-vehicle sound field characteristics. In one example, the in-vehicle sound field characteristics may specifically be the vehicle body sound vibration transfer function and / or the in-vehicle noise transfer function.

[0073] In one embodiment of this application, the first target vehicle parameter information may specifically include only common parameter information. Of course, it may also include other information in addition to common parameter information. For example, the first target vehicle parameter information may specifically include common parameter information and virtual parameter information. The virtual parameter information is parameter information that new energy vehicles lack compared to non-new energy vehicles, and the virtual parameter information may specifically be parameter information with a set of default parameter values. This application does not limit this.

[0074] In one embodiment of this application, the shared parameter information includes in-vehicle sound field characteristics, and the virtual parameter information includes: engine parameters, acoustic characteristics of the intake and exhaust system, location of the sound wave conduction device, and any combination of the acoustic characteristics of the sound wave conduction device.

[0075] In one embodiment of this application, the virtual parameter information can be set by the user. Based on this, the in-vehicle sound generation method provided in this application further includes the following steps S140 and S150.

[0076] Step S140: Provide an input interface.

[0077] The input interface is used for users to input virtual parameter information. Users can set different virtual parameter information according to their individual needs.

[0078] Step S150: In response to an input operation on the input interface, obtain virtual parameter setting information.

[0079] In this embodiment, the information input by the user at the input interface is regarded as virtual parameter information and is recorded as setting virtual parameter information.

[0080] Based on the steps S140 and S150 above, the specific implementation of step S120 is as follows: according to the vehicle operating condition information, the third target vehicle parameter information and the target mapping relationship, a target sound wave signal of the target sound wave type is generated. The third target vehicle parameter information includes: setting virtual parameter information and common parameter information in the first target vehicle parameter information.

[0081] In this embodiment, the shared parameter information and the set virtual parameter information from the first target vehicle parameter information are used as the third target vehicle parameter information. Based on this, according to the vehicle operating condition information, the third target vehicle parameter information, and the target mapping relationship, a target sound wave signal of the target sound wave type that meets the user's personalized needs can be generated. Furthermore, it can enhance the user's sense of participation.

[0082] In another embodiment, the vehicle operating condition information includes any combination of motor speed, vehicle speed, accelerator pedal opening, and brake pedal opening.

[0083] Step S120: Generate a target sound wave signal of the target sound wave type based on the target sound wave type, vehicle operating condition information, and first target vehicle parameter information.

[0084] In one embodiment, step S120 can be implemented specifically through steps S121 and S122.

[0085] Step S121: Determine the target mapping relationship from multiple candidate mapping relationships based on the target sound wave type.

[0086] Among them, one candidate mapping relationship corresponds to one candidate sound wave type, and the candidate mapping relationship reflects the correspondence between the vehicle operating condition information, the first target vehicle parameter information and the sound wave signal of the corresponding candidate sound wave type for new energy vehicles.

[0087] In this embodiment, multiple candidate mapping relationships are provided. Each candidate mapping relationship can output a sound wave signal of one sound wave type. The sound wave type corresponding to the sound wave signal output by a candidate mapping relationship is denoted as the candidate sound wave type corresponding to that candidate mapping relationship.

[0088] Based on the above, from multiple candidate mapping relationships, the candidate mapping relationship corresponding to the candidate sound wave type that can output the same type as the target sound wave can be determined. In this embodiment, the aforementioned candidate mapping relationship is denoted as the target mapping relationship.

[0089] It should be noted that the aforementioned candidate mapping relationships can be obtained through various fitting methods. For example, any multiple linear regression model can be used to obtain the candidate mapping relationships, and this application does not impose any limitations on this. It should also be noted that the aforementioned multiple linear regression model can be a simple polynomial function reflecting the candidate mapping relationship, where the coefficients of each order of the polynomial function are initially set to default values. By inputting training samples into the polynomial function, the specific values ​​of the coefficients of each order of the polynomial function are determined, thereby obtaining the candidate mapping relationship. Of course, the multiple linear regression model can also be a neural network model. The training samples can be set based on experience, and this application does not impose any limitations on this.

[0090] Step S122: Generate a target sound wave signal of the target sound wave type based on the vehicle operating condition information, the first target vehicle parameter information, and the target mapping relationship.

[0091] In this embodiment, vehicle operating condition information and first target vehicle parameter information are input into the target mapping relationship, and the target mapping relationship outputs the target sound wave signal of the target sound wave type.

[0092] Step S130: Perform in-vehicle playback processing on the target sound wave signal.

[0093] In this implementation, after obtaining the target sound signal, the vehicle's speakers, such as the in-vehicle audio system, are controlled to play the target sound signal. This allows the vehicle's occupants to hear a sound signal of the target sound type.

[0094] Combining steps S110 to S130 above, any new energy vehicle can generate a target sound wave signal of the target sound wave type based on the target sound wave type, vehicle operating condition information, and first target vehicle parameter information. This process does not require benchmarking against the sound wave of a traditional fuel vehicle. In other words, the in-vehicle sound wave generation method for new energy vehicles provided in this application can be separated from traditional fuel vehicles, solving the problem of high limitations in traditional sound wave synthesis methods for new energy vehicles.

[0095] This application provides a method for generating in-vehicle sound waves, applicable to new energy vehicles. The method includes: acquiring a target sound wave type, vehicle operating condition information, and first target vehicle parameter information; generating a target sound wave signal of the target sound wave type based on the target sound wave type, vehicle operating condition information, and first target vehicle parameter information; and performing in-vehicle playback processing on the target sound wave signal. The in-vehicle sound wave generation method for new energy vehicles provided by this application can be separated from traditional fuel vehicles, solving the problem of high limitations in traditional sound wave synthesis methods for new energy vehicles.

[0096] In one embodiment of this application, based on the embodiments shown in steps S121 and S122 above, the in-vehicle sound generation method provided by this application further includes the following step S123.

[0097] Step S123: Obtain the candidate mapping relationship. This step is specifically implemented through the following steps S1231 and S1232.

[0098] Step S1231: Obtain the training sample set.

[0099] The training sample set includes multiple sets of training samples. Each set of training samples includes parameter information of sample non-new energy vehicles, operating condition information of sample non-new energy vehicles, and sound wave signals of sample non-new energy vehicles corresponding to the candidate sound wave type of the candidate mapping relationship.

[0100] In one embodiment, taking non-new energy vehicles as fuel vehicles, and the candidate sound types including auditory types, taking the auditory type as sporty as an example, the specific implementation of the above steps S1231 can be as follows: Select fuel vehicles with a sporty sound type from the fuel vehicles; record the selected fuel vehicles as sample non-new energy vehicles; for any sample non-new energy vehicle, control the sample non-new energy vehicle to work under different vehicle operating conditions, and record the sound signals and vehicle parameter information under different operating conditions (the vehicle parameter information refers to the parameter information possessed by the fuel vehicle); for a sample non-new energy vehicle, record its vehicle operating condition information, vehicle parameter information under the vehicle operating condition information, and sound signal under the vehicle operating condition information as a set of training samples, wherein the vehicle parameter information of the sample non-new energy vehicle is recorded as sample non-new energy vehicle parameter information, the operating condition information of the sample non-new energy vehicle is recorded as sample non-new energy vehicle operating condition information, and the sound signal output by the sample non-new energy vehicle is recorded as sample non-new energy vehicle sound signal. Understandably, if the candidate sound type includes the desired number of engine cylinders, non-new energy vehicles can first be classified according to the number of engine cylinders, and then the above steps can be performed on non-new energy vehicles with a certain number of engine cylinders.

[0101] In another embodiment, step S1231 can be specifically implemented by steps S1231-1 to S1231-4.

[0102] Step S1231-1: Obtain the actual sound signals of multiple non-new energy vehicles.

[0103] In this embodiment, actual sound signals from multiple non-new energy vehicles are collected to achieve the above steps S1231-1.

[0104] In one embodiment, the aforementioned non-new energy vehicles may specifically be non-new energy vehicles whose engine sound is highly popular in the market.

[0105] In one embodiment, the aforementioned non-new energy vehicle may specifically be a non-electric vehicle that does not possess a sound simulation or sound enhancement system. Based on this, the training sample set obtained through the following steps is more accurate.

[0106] Step S1231-2: For any actual sound wave signal, determine the sound wave type and evaluation result of the actual sound wave signal based on the actual sound wave signal.

[0107] In one embodiment, the actual sound wave signal can be subjectively evaluated, classified, and scored based on existing sound quality evaluation models or platforms, such as multiple linear regression models or, more specifically, regression models based on convolutional neural networks. Furthermore, the sound wave type of the actual sound wave signal is determined based on the subjective evaluation classification, and the evaluation result of the actual sound wave signal is determined based on the subjective evaluation score.

[0108] Step S1231-3: Among the sound wave signals belonging to the same sound wave type, the non-new energy vehicles corresponding to the sound wave signals that output excellent evaluation results are used as sample non-new energy vehicles of the corresponding sound wave type.

[0109] In one embodiment of this application, the evaluation results can be sorted from high to low, and the top preset number of evaluation results are recorded as excellent evaluation results. Furthermore, the sound signal corresponding to the output of excellent evaluation results is used as a sample non-new energy vehicle for the corresponding sound type. It is understood that the sound signal corresponding to the excellent evaluation results represents a pleasant listening experience for users.

[0110] Step S1231-4: For any wave type of sample non-new energy vehicle, collect training samples based on the non-new energy vehicle data.

[0111] In this embodiment, for any sample non-new energy vehicle with a certain sound wave type, the sample non-new energy vehicle is controlled to operate under different vehicle operating conditions, and the sound wave signal and vehicle parameter information under different operating conditions are recorded simultaneously. For a sample non-new energy vehicle, its vehicle operating condition information, vehicle parameter information under the vehicle operating condition information, and sound wave signal under the vehicle operating condition information are recorded as a set of training samples. Among them, the vehicle parameter information of the sample non-new energy vehicle is recorded as sample non-new energy vehicle parameter information, the operating condition information of the sample non-new energy vehicle is recorded as sample non-new energy vehicle operating condition information, and the sound wave signal output by the sample non-new energy vehicle is recorded as sample non-new energy vehicle sound wave signal.

[0112] Based on steps S1231-1 to S1231-4 above, for any candidate sound wave type, sample non-new energy vehicles that output sound wave signals representing excellent evaluation results can be selected. This allows the candidate mapping relationship trained based on training samples collected from sample non-new energy vehicles to output sound wave signals representing excellent evaluation results based on input vehicle parameter information and vehicle operating condition information. That is, steps S1231-1 to S1231-4 above provide the basis for outputting the target sound wave signal representing excellent evaluation results in step S120 above.

[0113] Step S1232: Obtain candidate mapping relationships based on the training sample set.

[0114] In this embodiment, candidate mapping relationship data are obtained based on the training sample set using various fitting methods. The fitting method can be exemplified as machine learning.

[0115] Steps S1231 and S1232 above provide a way to obtain candidate mapping relationships.

[0116] It should be noted that although non-new energy vehicles are involved in the specific implementation of step S123 above, step S123 is only a process of obtaining a candidate mapping relationship. When used on the client vehicle, new energy vehicles can use it directly. That is, when new energy vehicles use the in-vehicle sound generation method provided in this application, they can be separated from non-new energy vehicles, such as traditional fuel vehicles.

[0117] In one embodiment of this application, the first target vehicle parameter information includes shared parameter information and virtual parameter information, where shared parameter information is included. The shared parameter information is the parameter information common to both new energy vehicles and non-new energy vehicles, while the virtual parameter information is the parameter information that new energy vehicles lack compared to non-new energy vehicles.

[0118] In one embodiment, the virtual parameter information includes: engine parameters, acoustic characteristics of the intake and exhaust systems, location of the sound wave conduction device, and any combination of the acoustic characteristics of the sound wave conduction device. In one example, the engine parameters include any combination of engine temperature, engine location, and engine fuel type; the acoustic characteristics of the intake and exhaust systems can specifically be the acoustic impedance of the intake and exhaust systems; and the acoustic characteristics of the sound wave conduction device can specifically be the sound transfer function of the sound wave conduction device.

[0119] In addition to steps S1231 and S1232, the in-vehicle sound generation method provided in this application further includes the following steps S1233 to S1237.

[0120] Step S1233: For any candidate mapping relationship, obtain the parameter information and operating condition information of the sample new energy vehicle.

[0121] The parameter information of the sample new energy vehicles includes shared sample parameter information and virtual sample parameter information.

[0122] It is understandable that the virtual sample parameter information represents the parameters that the sample new energy vehicles lack compared to non-new energy vehicles. The shared sample parameter information represents the parameters that the sample new energy vehicles possess.

[0123] In one embodiment, the specific implementation of step S1233 above can be as follows: for a new energy vehicle, the new energy vehicle is designated as a sample new energy vehicle, and the operation of the sample new energy vehicle is controlled; virtual parameter information with default parameter values ​​is set for the sample new energy vehicle as virtual sample parameter information; during the operation of the sample new energy vehicle, the operating condition information of the sample new energy vehicle is collected and designated as sample new energy vehicle operating condition information; and the common sample parameter information of the sample new energy vehicle is recorded and designated as common sample parameter information.

[0124] Step S1234: Based on the candidate mapping relationship, determine the test sound signals corresponding to the parameter information and operating condition information of the sample new energy vehicles.

[0125] Based on the above steps S1233, the sample new energy vehicle parameter information and sample new energy vehicle operating condition information, which consist of common sample parameter information and virtual sample parameter information, are input into the candidate mapping relationship, and the candidate mapping relationship outputs the corresponding test sound wave signal.

[0126] Step S1235: If the test sound wave signal does not match the selected sound wave type corresponding to the selected mapping relationship, adjust the corresponding parameter value of the virtual sample parameter information to obtain the updated virtual sample parameter information.

[0127] Step S1236: Update the virtual sample parameter information and the common sample parameter information as the sample new energy vehicle parameter information. Repeatedly determine the test sound signal corresponding to the sample new energy vehicle parameter information and the sample new energy vehicle operating condition information according to the candidate mapping relationship until the new energy vehicle sound signal matches the candidate sound type corresponding to the candidate mapping relationship.

[0128] Step S1237: The virtual sample parameter information of the test sound wave signal that meets the requirements of the candidate sound wave type corresponding to the candidate mapping relationship is used as the optimal virtual parameter information corresponding to the candidate mapping relationship.

[0129] In this embodiment, if the sound signal of the new energy vehicle does not match the selected sound type corresponding to the selected mapping relationship, it indicates that the parameter values ​​of the virtual sample parameter information in the sample new energy vehicle parameter information are not set appropriately. At this time, the parameter values ​​of the virtual sample parameter information in the sample new energy vehicle parameter information are adjusted, and steps S1234 are repeated until the sound signal of the new energy vehicle matches the selected sound type corresponding to the selected mapping relationship. Based on this, the virtual sample parameter information where the test sound signal matches the selected sound type corresponding to the selected mapping relationship is taken as the optimal virtual parameter information corresponding to the selected mapping relationship. That is, the latest adjusted virtual sample parameter information is taken as the optimal virtual parameter information corresponding to the selected mapping relationship.

[0130] It should be noted that the same candidate sound type can correspond to different design concepts, appearance styles, and brand characteristics. Based on this, for a certain model of new energy vehicle, the parameter values ​​of the virtual sample parameter information in the sample new energy vehicle parameter information can be adjusted, and the above steps S1234 can be repeated until the sound signal of the new energy vehicle matches the candidate sound type corresponding to the candidate mapping relationship, and the candidate sound type matches the design concept, appearance style, and brand characteristics of the aforementioned new energy vehicle model.

[0131] Based on the above steps S1233 to S1237, the in-vehicle sound generation method provided in this application further includes the following step S124 after the above step S121.

[0132] Step S124: The optimal virtual parameter information corresponding to the target mapping relationship and the common parameter information are used as the first target vehicle parameter information.

[0133] In this embodiment, each candidate mapping relationship corresponds to a set of optimal virtual parameter information. Based on this, and having determined the target mapping relationship, the optimal virtual parameter information corresponding to the target mapping relationship can also be determined. Furthermore, the optimal virtual parameter information corresponding to the target mapping relationship and the shared parameter information corresponding to the new energy vehicle are used as the first target vehicle parameter information.

[0134] Based on step S124 above, the first target vehicle parameter information obtained in step S110 and the target mapping relationship can be aligned in the dimension of the vehicle parameter information in the training samples used during training. This results in a more accurate and higher-quality target sound signal obtained in subsequent steps.

[0135] In one embodiment of this application, in conjunction with the embodiments shown in steps S1233 to S1237 above, the in-vehicle sound generation method provided by this application further includes the following steps S160 and S170.

[0136] Step S160: Provide the first display interface.

[0137] The first display interface displays the optimal virtual parameter information corresponding to the target mapping relationship.

[0138] Step S170: In response to the adjustment input for the optimal virtual parameter information corresponding to the target mapping relationship, the adjusted virtual parameter information is obtained.

[0139] In this embodiment, after determining the target mapping relationship, such as after determining the target sound wave type based on the above steps S111 and S112, the optimal virtual parameter information of the target mapping relationship can be displayed on the first display interface. The user can adjust this optimal virtual parameter information, for example, by increasing or decreasing it. This allows the user to input virtual parameter information according to their personalized needs. In this embodiment, the optimal virtual parameter information adjusted by the user is recorded as the adjusted virtual parameter information.

[0140] Based on the above steps S160 and S170, the specific implementation of step S120 is as follows: according to the vehicle operating condition information, the second target vehicle parameter information and the target mapping relationship, a target sound wave signal of the target sound wave type is generated, wherein the second target vehicle parameter information includes: the adjusted virtual parameter information and the common parameter information in the first target vehicle parameter information.

[0141] In this embodiment, the optimal virtual parameter information in the first target vehicle parameter information is replaced with the optimal virtual parameter information adjusted by the user; that is, the optimal virtual parameter information in the first target vehicle parameter information is replaced with adjusted virtual parameter information to form the second target vehicle parameter information. Based on this, according to the vehicle operating condition information, the second target vehicle parameter information, and the target mapping relationship, a target sound wave signal of the target sound wave type that meets the user's personalized needs can be generated. Furthermore, it can enhance the user's sense of participation.

[0142] Based on any of the above embodiments, step S110 can be specifically implemented through the following steps S113 and S114.

[0143] Step S113: Detect the vehicle's power type.

[0144] Step S114: If the vehicle power type is new energy type, obtain the target sound type, vehicle operating condition information and first target vehicle parameter information.

[0145] In this embodiment, the vehicle power type is first detected. If the vehicle power type is determined to be a new energy vehicle, then the target sound type, vehicle operating condition information, and first target vehicle parameter information are acquired. This avoids interference from noise generated by power sources other than electric power sources when using the in-vehicle sound generation method provided in this application with the target sound signal generated by this application, even in non-new energy vehicles, thus preventing poor audibility of the target sound signal synthesized by the in-vehicle sound generation method provided in this application.

[0146] Corresponding to step S114 above, if the vehicle power type is not a new energy type, then the target sound type, vehicle operating condition information and first target vehicle parameter information are not acquired.

[0147] This application also provides a vehicle controller 200, such as Figure 2 As shown, the vehicle controller includes a memory 210 and a processor 220. The memory 210 is used to store computer instructions, and the processor 220 is used to retrieve the computer instructions from the memory 210 to execute any of the in-vehicle sound synthesis methods provided in the above method embodiments.

[0148] This application also provides a vehicle that includes the vehicle controller 200 as described in the above embodiments.

[0149] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the in-vehicle sound generation methods provided in the above-described method embodiments.

[0150] This application may be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this application.

[0151] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination thereof. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0152] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0153] The computer program instructions used to perform the operations of this application may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuits, such as programmable logic circuits, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), are personalized by utilizing state information from the computer-readable program instructions. These electronic circuits can execute the computer-readable program instructions to implement various aspects of this application.

[0154] Various aspects of this application are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0155] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0156] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0157] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions. It will be well known to those skilled in the art that implementation in hardware, implementation in software, and implementation using a combination of software and hardware are equivalent.

[0158] The various embodiments of this application have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical applications, or technical improvements to the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein. The scope of this application is defined by the appended claims.

Claims

1. A method for generating in-vehicle sound, characterized in that, Applied to new energy vehicles, including: Acquire the target sound type, vehicle operating condition information, and parameter information of the first target vehicle; Based on the target sound wave type, a target mapping relationship is determined from multiple candidate mapping relationships. Each candidate mapping relationship corresponds to a candidate sound wave type, and the candidate mapping relationship reflects the correspondence between the vehicle operating condition information of the new energy vehicle, the first target vehicle parameter information, and the sound wave signal of the corresponding candidate sound wave type. Based on the vehicle operating condition information, the first target vehicle parameter information, and the target mapping relationship, a target sound wave signal of the target sound wave type is generated; The step of generating a target sound wave signal of the target sound wave type based on the vehicle operating condition information, the first target vehicle parameter information, and the target mapping relationship includes: The second target vehicle parameter information is determined based on the adjusted virtual parameter information and the shared parameter information in the first target vehicle parameter information; Based on the vehicle operating condition information, the second target vehicle parameter information, and the target mapping relationship, a target sound wave signal of the target sound wave type is generated; The virtual parameter information is obtained by adjusting the optimal virtual parameter information corresponding to the target mapping relationship displayed on the first display interface. The optimal virtual parameter information corresponding to the target mapping relationship is the parameter information that the new energy vehicle lacks compared to the non-new energy vehicle, and makes the output of the target mapping relationship conform to the sound type corresponding to the target mapping relationship. The shared parameter information is the parameter information shared by the new energy vehicle and the non-new energy vehicle.

2. The method according to claim 1, characterized in that, The target sound type includes at least the desired auditory experience type and / or the desired number of engine cylinders, and the first target vehicle parameter information includes at least common parameter information.

3. The method according to claim 1, characterized in that, Before determining the target mapping relationship from multiple candidate mapping relationships based on the target sound wave type, the method further includes: The steps to obtain multiple candidate mapping relationships include: Obtain a training sample set, which includes multiple sets of training samples. Each set of training samples includes sample non-new energy vehicle parameter information, sample non-new energy vehicle operating condition information, and sample non-new energy vehicle sound signals of the candidate sound wave type corresponding to the candidate mapping relationship. Multiple candidate mapping relationships are obtained based on the training sample set.

4. The method according to claim 3, characterized in that, The acquisition of the training sample set includes: Acquire actual sound signals from multiple non-new energy vehicles; For any of the actual sound wave signals, determine the sound wave type and evaluation result of the actual sound wave signal based on the actual sound wave signal; Among the actual sound wave signals belonging to the same sound wave type, the actual sound wave signals that output excellent evaluation results correspond to non-new energy vehicles and are used as sample non-new energy vehicles of the corresponding sound wave type. For any type of sound wave, non-new energy vehicles are sampled, and training samples are collected based on the non-new energy vehicles.

5. The method according to claim 3, characterized in that, The first target vehicle parameter information includes shared parameter information and optimal virtual parameter information corresponding to the target sound wave type; Before acquiring the target sound type, vehicle operating condition information, and first target vehicle parameter information, the method further includes: For any candidate mapping relationship, obtain the sample new energy vehicle parameter information and sample new energy vehicle operating condition information. The sample new energy vehicle parameter information includes common sample parameter information and virtual sample parameter information. The virtual sample parameter information is the parameter information that the sample new energy vehicle lacks compared to non-new energy vehicles. Based on the candidate mapping relationship, determine the test sound signals corresponding to the sample new energy vehicle parameter information and sample new energy vehicle operating condition information; If the test sound wave signal does not conform to the candidate sound wave type corresponding to the candidate mapping relationship, adjust the parameter value corresponding to the virtual sample parameter information to obtain updated virtual sample parameter information; The updated virtual sample parameter information and the common sample parameter information are used as the sample new energy vehicle parameter information. The process of determining the test sound wave signal corresponding to the sample new energy vehicle parameter information and the sample new energy vehicle operating condition information according to the candidate mapping relationship is repeated until the test sound wave signal matches the candidate sound wave type corresponding to the candidate mapping relationship. The virtual sample parameter information of the test sound wave signal that conforms to the selected sound wave type corresponding to the selected mapping relationship is used as the optimal virtual parameter information corresponding to the selected mapping relationship.

6. The method according to claim 1, characterized in that, Before generating the target sound wave signal of the target sound wave type based on the vehicle operating condition information, the first target vehicle parameter information, and the target mapping relationship, the method further includes: Based on the target mapping relationship, determine the optimal virtual parameter information corresponding to the target mapping relationship; Based on the optimal virtual parameter information and common parameter information corresponding to the target mapping relationship, the parameter information of the first target vehicle is determined.

7. The method according to claim 1, characterized in that, The step of generating a target sound wave signal of the target sound wave type based on the vehicle operating condition information, the first target vehicle parameter information, and the target mapping relationship includes: The third target vehicle parameter information is determined based on the set virtual parameter information and the common parameter information in the first target vehicle parameter information; Based on the vehicle operating condition information, the third target vehicle parameter information, and the target mapping relationship, a target sound wave signal of the target sound wave type is generated; The virtual parameter information is obtained based on the parameter information that the new energy vehicle lacks compared to the non-new energy vehicle, which is input through the input interface displayed on the second display interface.

8. The method according to claim 1, characterized in that, The shared parameter information includes the in-vehicle sound field characteristics. The parameter information that the new energy vehicle lacks compared to the non-new energy vehicle includes: engine parameters, acoustic characteristics of the intake and exhaust system, location of the sound wave transmission device, and any combination of the acoustic characteristics of the sound wave transmission device.

9. The method according to claim 1, characterized in that, The vehicle operating information includes any combination of motor speed, vehicle speed, accelerator pedal opening, and brake pedal opening.

10. The method according to claim 1, characterized in that, The acquisition of the target sound wave type, vehicle operating condition information, and first target vehicle parameter information includes: Inspect the vehicle's powertrain type; When the vehicle power type is a new energy type, the target sound type, vehicle operating condition information, and first target vehicle parameter information are obtained.

11. The method according to claim 1, characterized in that, The target sound wave type is obtained by selecting different candidate sound wave types displayed on the third display interface.

12. A vehicle controller, characterized in that, The vehicle controller includes a memory and a processor, the memory for storing computer instructions, and the processor for retrieving the computer instructions from the memory to perform the method as described in any one of claims 1-11.

13. An in-vehicle sound playback system, characterized in that, Includes the vehicle controller as described in claim 12 and the speaker, wherein: The speaker is connected to the processor in the vehicle controller and is used to play the target sound wave signal.

14. A vehicle, characterized in that, Including the in-vehicle sound playback system as described in claim 13.

15. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the method according to any one of claims 1-11.

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