Low-speed prompt tone generation method and device for electric vehicle, vehicle and storage medium

Abstract

The invention relates to a low-speed warning tone generation method and device of an electric vehicle, the vehicle and a storage medium, and the method comprises the steps that the sound style of the low-speed warning tone of the electric vehicle is determined; the whole vehicle frequency response of the electric vehicle and the pedestrian warning indicator frequency response are tested and analyzed, and the main frequency band of the low-speed warning tone is determined; on the basis of the main frequency band, respectively recording in-vehicle noise of the electric vehicle in a low-speed pedestrian warning tone road test and a low-speed pedestrian warning tone-free road test under the condition that the electric vehicle runs at a preset low speed to obtain a frequency range and noise masking data of the in-vehicle road noise, and outputting the in-vehicle road noise after the frequency range and the noise masking data meet preset conditions. And generating a low-speed prompt tone. Therefore, the problems that in the related technology, warning tone generated by an external loudspeaker is transmitted into a cabin through structural sound transmission and air sound transmission ways, so that the sound quality in a vehicle is poor, and the sound pressure level in the vehicle is increased once a self-adaptive control system is used for improving the warning loudness to compensate the external environment noise, and the sound quality is poor are solved. The driving comfort is influenced, and the like.

Description

Technical Field

[0001] This application relates to the field of active sound technology for electric vehicles, and in particular to a method, device, vehicle, and storage medium for generating low-speed warning sounds for electric vehicles. Background Technology

[0002] With global resource scarcity, the development of new energy vehicles has been rapid. Compared to gasoline vehicles, they are quieter to drive, leading to the enactment of relevant regulations by various countries. To ensure pedestrian safety, new energy vehicles should emit a low-speed warning sound with sufficient sound pressure to alert pedestrians at speeds between 0-30 km / h. The sound frequency shifts with speed, reaching its maximum sound pressure level at 20 km / h. Automakers calibrate the low-speed warning sound in semi-anechoic chambers that meet design standards, adjusting the sound pressure level at external measuring points to meet the national standard GB / T 37153-2018 "Low-Speed ​​Warning Sound for Electric Vehicles". However, since sound cannot be completely isolated by the vehicle's acoustic enclosure, a relatively high sound pressure level inside the vehicle for the low-speed warning sound is a common problem for new energy vehicles.

[0003] In related technologies, external speaker systems, harmonic injection technology based on drive motors, and adaptive control systems are used. External speaker systems are usually installed in the front compartment or bottom of the vehicle and use specific frequency warning sounds to alert pedestrians. For example, a shell cavity internal and external pressure balance design and a small and lightweight internal magnetic speaker are used to solve the problem of internal and external pressure balance of the sound cavity caused by full sealing and waterproofing.

[0004] However, in related technologies, low-frequency sound waves from external speakers can easily penetrate the vehicle's acoustic package and enter the cabin through structural vibrations, resulting in poor sound quality inside the vehicle. In order to compensate for external environmental noise, the adaptive control system increases the intensity of warning sounds, which leads to an increase in the sound pressure level inside the vehicle and affects driving comfort, and urgently needs to be improved. Summary of the Invention

[0005] This application provides a method, device, vehicle, and storage medium for generating low-speed warning sounds for electric vehicles, in order to solve the problems in related technologies, where warning sounds generated by external speakers are transmitted into the cabin through structural and airborne sound transmission paths, resulting in poor sound quality inside the vehicle. Furthermore, if an adaptive control system increases the intensity of the warning sound to compensate for external environmental noise, it will lead to an increase in the sound pressure level inside the vehicle, affecting driving comfort.

[0006] The first aspect of this application provides a method for generating a low-speed warning sound for an electric vehicle, comprising the following steps: determining the sound style of the low-speed warning sound of the electric vehicle; testing and analyzing the overall frequency response of the electric vehicle and the frequency response of the pedestrian warning device to determine the main frequency band of the low-speed warning sound; and based on the main frequency band, respectively recording the in-vehicle noise of the electric vehicle under road test conditions with and without low-speed pedestrian warning sound at a preset low speed, to obtain the frequency range and noise masking data of the in-vehicle road noise, until the frequency range and noise masking data meet preset conditions, and generating the low-speed warning sound.

[0007] Through the above-mentioned technical means, the embodiments of this application can clearly define the sound style of the vehicle characteristics, accurately identify the main frequency band of the prompt tone, and obtain the noise masking characteristics by combining real vehicle road tests, thereby generating a low-speed prompt tone that is coordinated with the noise of the in-vehicle environment. In this way, while meeting the regulations outside the vehicle, the sound pressure level inside the vehicle is reduced, the driving experience of the driver inside the vehicle is improved, the sound quality inside the vehicle is improved, the vehicle development cycle is reduced, and efficiency is improved.

[0008] Optionally, in one embodiment of this application, the step of testing and analyzing the overall frequency response of the electric vehicle and the frequency response of the pedestrian warning device to determine the main frequency band of the low-speed warning sound includes: acquiring the frequency response of the pedestrian warning device, the external measuring point and the internal measuring point; and determining the main frequency band based on the frequency response.

[0009] Through the above-mentioned technical means, the embodiments of this application can collect frequency response data from multiple locations and perform comprehensive analysis to determine the main frequency band of the low-speed warning sound. This allows the main frequency band to not only match the sound output capability of the pedestrian warning device but also balance the external warning effect with the internal acoustic environment, laying the foundation for improving the sound quality inside the vehicle.

[0010] Optionally, in one embodiment of this application, determining the sound style of the low-speed warning sound of the electric vehicle includes: acquiring at least one of the electric vehicle's model information, market positioning information, styling information, and interior information; and matching the sound style of the low-speed warning sound according to at least one of the electric vehicle's model information, market positioning information, styling information, and interior information.

[0011] Through the above-mentioned technical means, the embodiments of this application can obtain information on the electric vehicle's model, market positioning, styling, and interior to match the corresponding low-speed warning sound style, match the low-speed warning sound style with the vehicle's overall design concept and brand tone, enhance brand recognition and user experience consistency, integrate the warning sound with the overall characteristics of the vehicle, and improve user satisfaction.

[0012] Optionally, in one embodiment of this application, before generating the low-speed prompt tone, the method further includes: obtaining the identity identifier of the target user; obtaining the user's preference information based on the identity identifier; and adjusting the low-speed prompt tone according to the preference information.

[0013] Through the above-mentioned technical means, the embodiments of this application can obtain the user's preference information through the target user's identity identifier, and adjust the prompt sound according to the preference information. The prompt sound is customized for different users' preferences, making the prompt sound more in line with the user's personal needs and improving the user's acceptance of the prompt sound and user experience.

[0014] Optionally, in one embodiment of this application, generating the low-speed warning sound further includes: determining the target population for the electric vehicle; and adjusting the low-speed warning sound according to the target population.

[0015] Through the above-mentioned technical means, the embodiments of this application adjust the low-speed warning sound based on the target group of electric vehicles, optimize the warning sound design based on the common preferences of the group, so that the warning sound is more in line with the expectations of most target users. While maintaining a personalized experience, it ensures that the warning sound design meets the economic and feasibility requirements of mass production, and achieves an effective balance between user experience and engineering practice.

[0016] A second aspect of this application provides a low-speed warning sound generation device for an electric vehicle, comprising: a determining module for determining the sound style of the low-speed warning sound of the electric vehicle; an analysis module for testing and analyzing the overall frequency response of the electric vehicle and the frequency response of the pedestrian warning device to determine the main frequency band of the low-speed warning sound; and a generation module for, based on the main frequency band, recording the in-vehicle noise of the electric vehicle under road tests with and without low-speed pedestrian warning sounds at a preset low speed, to obtain the frequency range and noise masking data of the in-vehicle road noise, until the frequency range and noise masking data meet preset conditions, and then generating the low-speed warning sound.

[0017] Through the above-mentioned technical means, the embodiments of this application can clearly define the sound style of the vehicle characteristics, accurately identify the main frequency band of the prompt tone, and obtain the noise masking characteristics by combining real vehicle road tests, thereby generating a low-speed prompt tone that is coordinated with the noise of the in-vehicle environment. In this way, while meeting the regulations outside the vehicle, the sound pressure level inside the vehicle is reduced, the driving experience of the driver inside the vehicle is improved, the sound quality inside the vehicle is improved, the vehicle development cycle is reduced, and efficiency is improved.

[0018] Optionally, in one embodiment of this application, the analysis module includes: a frequency response acquisition unit, used to acquire the frequency response of the pedestrian warning device, the external measuring point and the internal measuring point; and a frequency determination unit, used to determine the main frequency band based on the frequency response.

[0019] Through the above-mentioned technical means, the embodiments of this application can collect frequency response data from multiple locations and perform comprehensive analysis to determine the main frequency band of the low-speed warning sound. This allows the main frequency band to not only match the sound output capability of the pedestrian warning device but also balance the external warning effect with the internal acoustic environment, laying the foundation for improving the sound quality inside the vehicle.

[0020] Optionally, in one embodiment of this application, the determining module includes: an information acquisition unit, configured to acquire at least one of the electric vehicle's model information, market positioning information, styling information, and interior information; and a matching unit, configured to match the sound style of the low-speed warning sound according to at least one of the electric vehicle's model information, market positioning information, styling information, and interior information.

[0021] Through the above-mentioned technical means, the embodiments of this application can obtain information on the electric vehicle's model, market positioning, styling, and interior to match the corresponding low-speed warning sound style, match the low-speed warning sound style with the vehicle's overall design concept and brand tone, enhance brand recognition and user experience consistency, integrate the warning sound with the overall characteristics of the vehicle, and improve user satisfaction.

[0022] Optionally, in one embodiment of this application, it further includes: an identity acquisition module, configured to acquire the identity identifier of the target user before generating the low-speed prompt tone; a preference acquisition module, configured to acquire the user's preference information based on the identity identifier before generating the low-speed prompt tone; and a first adjustment module, configured to adjust the low-speed prompt tone according to the preference information before generating the low-speed prompt tone.

[0023] Through the above-mentioned technical means, the embodiments of this application can obtain the user's preference information through the target user's identity identifier, and adjust the prompt sound according to the preference information. The prompt sound is customized for different users' preferences, making the prompt sound more in line with the user's personal needs and improving the user's acceptance of the prompt sound and user experience.

[0024] Optionally, in one embodiment of this application, it further includes: a suitable user group determination module, used to determine the suitable user group of the electric vehicle before generating the low-speed warning sound; and a second adjustment module, used to adjust the low-speed warning sound according to the suitable user group before generating the low-speed warning sound.

[0025] Through the above-mentioned technical means, the embodiments of this application adjust the low-speed warning sound based on the target group of electric vehicles, optimize the warning sound design based on the common preferences of the group, so that the warning sound is more in line with the expectations of most target users. While maintaining a personalized experience, it ensures that the warning sound design meets the economic and feasibility requirements of mass production, and achieves an effective balance between user experience and engineering practice.

[0026] A third aspect of this application provides a vehicle, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the low-speed warning sound generation method for an electric vehicle as described in the above embodiments.

[0027] A fourth aspect of this application provides a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for generating a low-speed warning sound for an electric vehicle.

[0028] A fifth aspect of this application provides a computer program product that stores a computer program that, when executed by a processor, implements the above-described method for generating a low-speed warning sound for an electric vehicle.

[0029] This application's embodiments can clearly define the sound style of a vehicle's characteristics, accurately identify the main frequency band of the warning tone, and combine this with noise masking characteristics obtained from real-vehicle road tests. This generates a low-speed warning tone that harmonizes with the ambient noise inside the vehicle, thereby reducing the sound pressure level inside the vehicle while meeting regulations outside the vehicle. This improves the driving experience for the driver, enhances in-vehicle sound quality, reduces the vehicle's development cycle, and increases efficiency. Therefore, it solves the problems in related technologies where warning tones generated by external speakers enter the cabin through structural and airborne sound transmission, resulting in poor in-vehicle sound quality; and where adaptive control systems increase the intensity of warning tones to compensate for external ambient noise, leading to increased in-vehicle sound pressure levels and affecting driving comfort.

[0030] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0031] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of a method for generating a low-speed warning sound for an electric vehicle according to an embodiment of this application; Figure 2 This is a schematic diagram of the location of the external microphone measuring point according to an embodiment of this application; Figure 3 This is a schematic diagram of the position of the in-vehicle microphone measuring point according to an embodiment of this application; Figure 4 This is a schematic diagram of the frequency response curve of a pedestrian warning device according to an embodiment of this application; Figure 5 This is a schematic diagram of the frequency response curve of a vehicle according to an embodiment of this application; Figure 6 This is a flowchart of a method for generating a low-speed warning sound for an electric vehicle according to an embodiment of this application; Figure 7 This is a schematic diagram of a low-speed warning sound generation device for an electric vehicle according to an embodiment of this application; Figure 8 This is a structural schematic diagram of a vehicle provided according to an embodiment of this application.

[0032] Figure label: 10-Low speed warning sound generation device for electric vehicles; 100-Determination module, 200-Analysis module, 300-Generation module; 801-Memory, 802-Processor, 803-Communication interface. Detailed Implementation

[0033] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0034] The following description, with reference to the accompanying drawings, outlines a method, apparatus, vehicle, and storage medium for generating low-speed warning sounds for electric vehicles according to embodiments of this application. Addressing the issues raised in the background art, warning sounds generated by external speakers are transmitted into the cabin via structural and airborne sound transmission, resulting in poor in-vehicle sound quality. Furthermore, if an adaptive control system increases the intensity of the warning sound to compensate for external environmental noise, it leads to increased in-vehicle sound pressure levels, affecting driving comfort. This application provides a method for generating low-speed warning sounds for electric vehicles. This method clearly defines the sound style characteristic of the vehicle, accurately identifies the main frequency band of the warning sound, and combines this with noise masking characteristics obtained from real-vehicle road tests. This generates low-speed warning sounds that are coordinated with the in-vehicle environmental noise, thereby reducing the in-vehicle sound pressure level while meeting external regulations, improving the driving experience for the driver, enhancing in-vehicle sound quality, reducing vehicle development cycles, and increasing efficiency. This solves the problem in related technologies where the alert sounds generated by external speakers are transmitted into the cabin through structural and airborne sound transmission, resulting in poor in-vehicle sound quality. Furthermore, if the adaptive control system increases the intensity of the alert sounds to compensate for external environmental noise, it will lead to an increase in the in-vehicle sound pressure level, affecting driving comfort.

[0035] Specifically, Figure 1 This is a flowchart illustrating a method for generating a low-speed warning sound for an electric vehicle, as provided in an embodiment of this application.

[0036] like Figure 1As shown, the method for generating a low-speed warning sound for this electric vehicle includes the following steps: In step S101, the sound style of the low-speed warning sound of the electric vehicle is determined.

[0037] It is understood that the sound style in the embodiments of this application can be a set of acoustic features presented by the low-speed prompt tone, including but not limited to timbre, rhythm, and dynamic changes, providing a basic direction for the specific generation of subsequent prompt tones.

[0038] In practical implementation, this application embodiment can access a vehicle database to read information such as the vehicle's model, market positioning (e.g., luxury, sport, family), and exterior styling language. Based on this information, a style matching the vehicle's prompts can be selected or synthesized using style matching rules or machine learning models, such as cluster analysis, to map vehicle attributes to an acoustic feature library. For example, a sporty SUV can be matched with a more dynamic, higher-frequency sound style, while a luxury sedan can be matched with a more stable, mellow sound style.

[0039] The embodiments of this application can determine the sound style of the low-speed warning sound of electric vehicles according to vehicle model, market positioning, etc., and transform the low-speed warning sound into an acoustic symbol that matches the characteristics of the vehicle. This satisfies the basic warning function, conveys the design concept of the vehicle, and enhances the user's overall perception of the vehicle.

[0040] Optionally, in one embodiment of this application, determining the sound style of the low-speed warning sound of an electric vehicle includes: obtaining at least one of the electric vehicle's model information, market positioning information, styling information, and interior information; and matching the sound style of the low-speed warning sound based on at least one of the electric vehicle's model information, market positioning information, styling information, and interior information.

[0041] It is understood that in the embodiments of this application, the vehicle model information of the electric vehicle can be a sedan, SUV, sports car, etc.; the market positioning information can be luxury, economy, sporty; the styling information can be a streamlined body and tough lines; the interior information can be a high-tech panel and retro materials. The embodiments of this application can determine the sound style through multi-dimensional vehicle attributes.

[0042] For example, in this embodiment of the application, information such as the vehicle model, market positioning, styling, and interior of the electric vehicle can be obtained through the vehicle's CAN (Controller Area Network bus), a pre-built vehicle configuration database, or by inputting the VIN (Vehicle Identification Number). Based on this information, a sound style for the low-speed warning tone can be matched. For instance, for a vehicle whose model information is a sports car, market positioning is for young performance users, and styling information is a fastback design, the model can match a sound style with a high proportion of high-frequency components and dramatic changes in sound pressure level. For a vehicle whose model information is a family MPV (Multi-Purpose Vehicle), market positioning is for family users, and interior information is primarily made of soft materials, a sound style with smooth low frequencies and small sound pressure level fluctuations can be matched.

[0043] This application embodiment can obtain information about the electric vehicle's model, market positioning, styling, and interior to match the corresponding low-speed warning sound style. By matching the low-speed warning sound style with the vehicle's overall design concept and brand tone, it enhances brand recognition and user experience consistency, integrates the warning sound with the overall characteristics of the vehicle, and improves user satisfaction.

[0044] In step S102, the overall frequency response of the electric vehicle and the frequency response of the pedestrian warning device are tested and analyzed to determine the main frequency band of the low-speed warning sound.

[0045] It is understood that the vehicle frequency response and pedestrian warning device frequency response in the embodiments of this application can be understood as the frequency response characteristics of the sound after it is emitted from the warning device and propagates to the driver's ears outside the vehicle and inside the vehicle.

[0046] The sound pressure level inside new energy vehicles is relatively high, mainly affected by factors such as the installation location of pedestrian warning devices, the frequency composition of the low-speed warning sound itself, the vehicle's sound insulation performance, and the position of the seats. The first three are the primary influencing factors. Pedestrian warning devices are generally fixed to the front bumper crossbeam, with the sound-emitting surface facing downwards. When the pedestrian warning device location is determined at the initial stage of the project, the sound pressure level of the warning sound inside the vehicle is determined by the frequency composition of the low-speed warning sound itself and the acoustic package. Since the vehicle's acoustic package is a solution developed at the initial stage of the project based on market positioning and cost, later modifications are time-consuming, labor-intensive, and costly. Therefore, the main approach to reducing the sound pressure level inside the vehicle is to modify the sound frequency composition.

[0047] In actual implementation, after determining the sound style based on vehicle model, market positioning, etc., the embodiments of this application can test and analyze the frequency response of the whole vehicle and the frequency response of the pedestrian warning device to determine the main frequency band of the sound. The main frequency band needs to be in the area where the frequency response of the pedestrian warning device is good, the frequency response of the external measuring point is good, and the frequency response of the internal measuring point is poor. In this way, the effectiveness of external warning and the acoustic comfort inside the vehicle are taken into account in the sound source frequency planning stage.

[0048] The embodiments of this application can determine the main frequency band by testing and analyzing the frequency response of the whole vehicle and the frequency response of the pedestrian warning device.

[0049] Optionally, in one embodiment of this application, the frequency response of the electric vehicle and the frequency response of the pedestrian warning device are tested and analyzed to determine the main frequency band of the low-speed warning sound, including: acquiring the frequency response of the pedestrian warning device, the external measuring point and the internal measuring point; and determining the main frequency band based on the frequency response.

[0050] It is understood that, in the embodiments of this application, the frequency response of the external measuring point can be the frequency attenuation and gain characteristics of the sound as it propagates from the warning device to the external measuring point as specified by regulations; while the frequency response of the internal measuring point refers to the frequency response characteristics of the sound as it is transmitted to the internal measuring point through the vehicle body structure, air, and other paths.

[0051] like Figure 2 and Figure 3 As shown, the low-speed warning audio has three measurement points: one microphone on each of the left and right sides outside the vehicle, and one microphone in the driver's inner ear inside the vehicle. The height of the microphone inside the vehicle from the seat can be 0.7 ± 0.05 meters.

[0052] For example, embodiments of this application can acquire the frequency response of pedestrian warning devices, external measuring points, and internal measuring points; determine the main frequency band and the frequency response of the pedestrian warning device based on the frequency response. Figure 4 As shown, the frequency response is good between 200-400Hz and near 2000Hz, and this frequency band is more likely to meet national standards. The overall vehicle frequency response is as follows... Figure 5 As shown, the left and right are two measuring points outside the vehicle. Between 250-350Hz and 950-1150Hz, the frequency response difference between inside and outside the vehicle is significant. The difference is even greater in the 950-1150Hz band, meaning the sound pressure level is higher outside and lower inside. According to... Figure 4 Although the frequency response of pedestrian warning devices in the 950-1150Hz band is slightly inferior to that in the 250-350Hz band, considering that they can generate a greater sound pressure difference between the inside and outside of the vehicle, both of these bands can be identified as candidate ranges for the main frequency bands and become the main frequency bands for sound source design.

[0053] This application embodiment can collect frequency response data from multiple locations and perform comprehensive analysis to determine the main frequency band of the low-speed warning sound. This allows the main frequency band to be adapted to the sound output capability of the pedestrian warning device and to balance the external warning effect with the internal acoustic environment, laying the foundation for improving the sound quality inside the vehicle.

[0054] In step S103, based on the main frequency band, the in-vehicle noise of the electric vehicle is recorded in road tests with and without low-speed pedestrian warning sounds when driving at a preset low speed, so as to obtain the frequency range and noise masking data of the in-vehicle road noise. A low-speed warning sound is generated after the frequency range and noise masking data meet the preset conditions.

[0055] It is understood that the noise masking data in the embodiments of this application may include the sound pressure level distribution of masking noise (i.e., in-vehicle road noise) in each frequency band, the signal-to-mask ratio of the prompt tone and noise in different critical frequency bands, and the masking threshold spectrum based on the psychoacoustic model; the preset condition may be that the sound pressure level of the prompt tone in the target frequency band is lower than the masking threshold of the masking noise in that frequency band. The preset condition may be set by those skilled in the art according to the actual situation, and no specific limitation is made here.

[0056] In practical implementation, this application embodiment can conduct real-vehicle road tests based on the main frequency band, controlling the vehicle to travel within a low-speed range of 0-30 km / h. The in-vehicle noise is recorded for both road tests with and without low-speed pedestrian warning sounds at preset low speeds, to obtain the frequency range and noise masking data of the in-vehicle road noise. Based on the collected noise data, the main frequency range of in-vehicle road noise (such as inherent noise generated by tire rolling and airflow disturbance) is further analyzed, and the masking effect of road noise on the low-speed warning sound is evaluated. Based on the noise masking effect, the spectral structure, sound pressure level, and other parameters of the low-speed warning sound are repeatedly calibrated and optimized until both external regulatory requirements and the in-vehicle noise masking threshold target are met within the frequency range, thus completing the generation of the low-speed warning sound.

[0057] The embodiments of this application can be precisely optimized based on the main frequency band, combined with real vehicle road noise data and auditory masking effect. During the sound source frequency design stage, the effectiveness of low-speed warning sounds in alerting pedestrians outside the vehicle can be ensured. Furthermore, by leveraging frequency response characteristics and noise masking rules, the sound pressure level inside the vehicle can be significantly reduced, the sound quality inside the vehicle can be improved, and the high cost and long cycle problems caused by modifying the acoustic package can be avoided, thus achieving a balance between technical performance and cost control.

[0058] Optionally, in one embodiment of this application, before generating the low-speed prompt tone, the method further includes: obtaining the identity identifier of the target user; obtaining the user's preference information based on the identity identifier; and adjusting the low-speed prompt tone according to the preference information.

[0059] It is understood that the identity identifier in this application embodiment can be understood as a credential used to uniquely identify the user, and its form may include, but is not limited to, vehicle account system login ID, smart key code or mobile device Bluetooth address; preference information may refer to the parameterized selection of the auditory characteristics of the prompt tone that the user has preset or that the system has extracted by learning historical operations, such as preferred timbre, fundamental frequency, rhythm or overall loudness level.

[0060] For example, in this embodiment of the application, the user's identity can be identified through a vehicle account system, key, or mobile phone Bluetooth identifier, and the acoustic preference settings bound to that identity can be retrieved from local storage or a cloud server accordingly, such as "preferring a soft tone" or "desiring a lower pitch for the prompts". Subsequently, based on these preference parameters, the system performs personalized rendering within its adjustable range on the basis of the generated prompts that comply with external vehicle regulations and in-vehicle masking requirements, such as fine-tuning the proportion of harmonic components in the spectrum to change the timbre, or making limited overall gain adjustments.

[0061] This application embodiment can obtain the user's preference information through the target user's identity identifier, and adjust the prompt sound according to the preference information. The prompt sound is customized for different users' preferences, making the prompt sound more in line with the user's personal needs and improving the user's acceptance of the prompt sound and the user experience.

[0062] Optionally, in one embodiment of this application, after generating the low-speed warning sound, the method further includes: determining the target audience for the electric vehicle; and adjusting the low-speed warning sound according to the target audience.

[0063] It is understood that the target audience in this application embodiment can be the target user group of the vehicle determined based on market research, vehicle positioning, and pre-sale data.

[0064] For example, in the early stages of vehicle development, user profiling and competitor analysis, or user pre-order analysis, can be used to identify the target demographic for a particular vehicle model. The system pre-stores several acoustic configuration files optimized for different demographics, such as futuristic electronic sound effects for "young tech enthusiasts" and gentler sounds for "family users." For models where the target demographic is already determined before sales, this method is even more targeted. The system can directly select or synthesize the prompt sound style most likely to match the preferences of the majority of members of that demographic based on pre-sale demographic data, and use this as the default or recommended setting for the pre-sale batch of vehicles.

[0065] This application's embodiments adjust the low-speed warning tone based on the target user group of electric vehicles, and optimize the warning tone design based on the common preferences of the group, so that the warning tone is more in line with the expectations of most target users. While maintaining a personalized experience, it ensures that the warning tone design meets the economic and feasibility requirements of mass production, and achieves an effective balance between user experience and engineering practice.

[0066] Specifically, it can be combined with Figure 6 As shown, the working principle of the low-speed warning sound generation method for electric vehicles in this application is explained in detail with a specific embodiment.

[0067] like Figure 6 As shown, embodiments of this application may include the following steps: Step S601: Car model, market positioning, styling, interior, etc.

[0068] In this embodiment of the application, information such as vehicle model, market positioning, styling, and interior can be obtained by accessing a vehicle pre-configured database or configuration parameter file.

[0069] Step S602: Determine the low-speed prompt tone style.

[0070] In this embodiment of the application, the sound style of the low-speed warning sound can be matched according to at least one of the electric vehicle's model information, market positioning information, styling information, and interior information.

[0071] Step S603: Test the frequency response of the entire vehicle.

[0072] In this embodiment of the application, the frequency response characteristics of sound propagating outside the vehicle after being emitted from the alarm can be tested.

[0073] Step S604: Test the speaker frequency response.

[0074] In this embodiment of the application, the frequency response characteristics of the sound transmitted from the alarm to the driver's ear inside the vehicle can be tested, and the loudspeaker is the pedestrian alarm.

[0075] Step S605: Analyze the main frequency band of the low-speed prompt tone.

[0076] In this application embodiment, the frequency response of the entire electric vehicle and the frequency response of the pedestrian warning device can be tested and analyzed to determine the main frequency band of the low-speed warning sound.

[0077] Step S606: Test on roads with and without AVAS (Audible Vehicle Alerting System) at speeds of 0-30 km / h.

[0078] In this embodiment, real vehicle road tests can be conducted based on the main frequency band, controlling the vehicle to drive in the low speed range of 0-30km / h, and respectively recording the in-vehicle noise of the electric vehicle under the condition of driving at a preset low speed with low-speed pedestrian warning sound road test and without low-speed pedestrian warning sound road test.

[0079] Step S607: Analyze the frequency range of in-vehicle noise and the masking effect.

[0080] In this application embodiment, based on in-vehicle noise, the main frequency range of in-vehicle road noise can be further analyzed, and the masking effect of road noise on low-speed warning sounds can be evaluated.

[0081] Step S608: Determine whether the target value has been reached. If yes, end the process; otherwise, proceed to step S606.

[0082] In this embodiment, the spectral structure, sound pressure level and other parameters of the low-speed warning sound can be repeatedly calibrated and optimized based on the noise masking effect until the low-speed warning sound is generated while simultaneously meeting the external regulatory requirements and the internal noise masking target value within the frequency range.

[0083] The low-speed warning sound generation method for electric vehicles proposed in this application can clearly define the sound style of the vehicle, accurately identify the main frequency band of the warning sound, and combine it with noise masking characteristics obtained from real-vehicle road tests to generate a low-speed warning sound that is coordinated with the ambient noise inside the vehicle. This reduces the sound pressure level inside the vehicle while meeting regulations outside the vehicle, improving the driving experience for the driver, enhancing in-vehicle sound quality, reducing the vehicle development cycle, and increasing efficiency. This solves the problem in related technologies where warning sounds generated by external speakers are transmitted into the cabin through structural and airborne sound transmission, resulting in poor in-vehicle sound quality. Furthermore, if an adaptive control system increases the loudness of the warning sound to compensate for external ambient noise, it will lead to an increase in the in-vehicle sound pressure level, affecting driving comfort.

[0084] Next, referring to the accompanying drawings, a low-speed warning sound generation device for electric vehicles according to an embodiment of this application is described.

[0085] Figure 7 This is a schematic diagram of the structure of the low-speed warning sound generation device for electric vehicles according to an embodiment of this application.

[0086] like Figure 7 As shown, the low-speed warning sound generation device 10 for the electric vehicle includes: a determination module 100, an analysis module 200, and a generation module 300.

[0087] The determining module 100 is used to determine the sound style of the low-speed warning sound of the electric vehicle.

[0088] Analysis module 200 is used to test and analyze the overall frequency response of electric vehicles and the frequency response of pedestrian warning devices in order to determine the main frequency band of the low-speed warning sound.

[0089] The generation module 300 is used to record the in-vehicle noise of electric vehicles under the condition of driving at a preset low speed with and without low-speed pedestrian warning sound, based on the main frequency band, so as to obtain the frequency range and noise masking data of the in-vehicle road noise, until the frequency range and noise masking data meet the preset conditions, and then generate a low-speed warning sound.

[0090] Optionally, in one embodiment of this application, the analysis module 300 includes: a frequency response acquisition unit and a frequency determination unit.

[0091] The frequency response acquisition unit is used to acquire the frequency response of the pedestrian warning device, the external measuring point and the internal measuring point.

[0092] The frequency determination unit is used to determine the main frequency band based on the frequency response.

[0093] Optionally, in one embodiment of this application, the determining module 100 includes an information acquisition unit and a matching unit.

[0094] The information acquisition unit is used to acquire at least one of the following: electric vehicle model information, market positioning information, styling information, and interior information.

[0095] The matching unit is used to match the sound style of the low-speed warning sound based on at least one of the electric vehicle's model information, market positioning information, styling information, and interior information.

[0096] Optionally, in one embodiment of this application, the low-speed warning sound generation device 10 for electric vehicles further includes: an identity acquisition module, a preference acquisition module, and a first adjustment module.

[0097] The identity acquisition module is used to acquire the target user's identity identifier before generating a low-speed prompt tone.

[0098] The preference acquisition module is used to obtain the user's preference information based on their identity before generating a low-speed prompt tone.

[0099] The first adjustment module is used to adjust the low-speed alert tone according to preference information before generating the low-speed alert tone.

[0100] Optionally, in one embodiment of this application, the low-speed warning sound generation device 10 for electric vehicles further includes: a target audience determination module and a second adjustment module.

[0101] The target audience determination module is used to determine the target audience for electric vehicles before generating the low-speed warning sound.

[0102] The second adjustment module is used to adjust the low-speed prompt tone according to the target audience before generating the low-speed prompt tone.

[0103] It should be noted that the explanation of the above-described embodiment of the method for generating low-speed warning sounds for electric vehicles also applies to the low-speed warning sound generation device for electric vehicles in this embodiment, and will not be repeated here.

[0104] The low-speed warning sound generation device for electric vehicles proposed in this application can clearly define the sound style of the vehicle, accurately identify the main frequency band of the warning sound, and combine it with noise masking characteristics obtained from real vehicle road tests to generate a low-speed warning sound that is coordinated with the ambient noise inside the vehicle. This reduces the sound pressure level inside the vehicle while meeting regulations outside the vehicle, improving the driving experience for the driver, enhancing in-vehicle sound quality, reducing the vehicle development cycle, and increasing efficiency. This solves the problem in related technologies where warning sounds generated by external speakers are transmitted into the cabin through structural and airborne sound transmission, resulting in poor in-vehicle sound quality. Furthermore, if an adaptive control system increases the loudness of the warning sound to compensate for external ambient noise, it will lead to an increase in the in-vehicle sound pressure level, affecting driving comfort.

[0105] Figure 8 A schematic diagram of the structure of a vehicle provided in an embodiment of this application. The vehicle may include: The memory 801, the processor 802, and the computer program stored on the memory 801 and capable of running on the processor 802.

[0106] When the processor 802 executes the program, it implements the method for generating low-speed warning sounds for electric vehicles provided in the above embodiments.

[0107] Furthermore, the vehicle also includes: Communication interface 803 is used for communication between memory 801 and processor 802.

[0108] The memory 801 is used to store computer programs that can run on the processor 802.

[0109] The memory 801 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0110] If the memory 801, processor 802, and communication interface 803 are implemented independently, then the communication interface 803, memory 801, and processor 802 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized into address buses, data buses, control buses, etc. For ease of representation, Figure 8 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0111] Optionally, in a specific implementation, if the memory 801, processor 802, and communication interface 803 are integrated on a single chip, then the memory 801, processor 802, and communication interface 803 can communicate with each other through an internal interface.

[0112] The processor 802 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0113] This application also provides a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for generating a low-speed warning sound for an electric vehicle.

[0114] This application also provides a computer program product storing a computer program that, when executed by a processor, implements the above-described method for generating a low-speed warning sound for an electric vehicle.

[0115] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0116] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0117] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0118] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0119] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or more of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0120] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0121] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0122] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for generating a low-speed warning sound for an electric vehicle, characterized in that, Includes the following steps: Determine the sound style of the low-speed warning tone for electric vehicles; The overall frequency response of the electric vehicle and the frequency response of the pedestrian warning device were tested and analyzed to determine the main frequency band of the low-speed warning sound. as well as Based on the main frequency band, the in-vehicle noise of the electric vehicle is recorded in road tests with and without low-speed pedestrian warning sounds when driving at a preset low speed, so as to obtain the frequency range and noise masking data of the in-vehicle road noise. The low-speed warning sound is generated after the frequency range and noise masking data meet the preset conditions.

2. The method according to claim 1, characterized in that, The testing and analysis of the overall vehicle frequency response and pedestrian warning device frequency response of the electric vehicle to determine the main frequency band of the low-speed warning sound includes: Acquire the frequency response of pedestrian warning devices, external vehicle measuring points, and internal vehicle measuring points; The main frequency band is determined based on the frequency response.

3. The method according to claim 1, characterized in that, The determination of the sound style of the low-speed warning sound for electric vehicles includes: Obtain at least one of the following: vehicle model information, market positioning information, styling information, and interior information of the electric vehicle; The sound style of the low-speed warning sound is matched based on at least one of the electric vehicle's model information, market positioning information, styling information, and interior information.

4. The method according to claim 1, characterized in that, Before generating the low-speed alert tone, the following is also included: Obtain the target user's identity identifier; The user's preference information is obtained based on the identity identifier; The low-speed alert tone is adjusted based on the preference information.

5. The method according to claim 1, characterized in that, After generating the low-speed alert tone, the process also includes: Determine the target population for the electric vehicle; The low-speed prompt tone is adjusted according to the target audience.

6. A low-speed warning sound generation device for an electric vehicle, characterized in that, include: The determination module is used to determine the sound style of the low-speed warning sound for electric vehicles; The analysis module is used to test and analyze the overall frequency response of the electric vehicle and the frequency response of the pedestrian warning device to determine the main frequency band of the low-speed warning sound. as well as The generation module is used to record the in-vehicle noise of the electric vehicle under the condition of driving at a preset low speed with and without a low-speed pedestrian warning sound, based on the main frequency band, so as to obtain the frequency range and noise masking data of the in-vehicle road noise, until the frequency range and noise masking data meet the preset conditions, and then generate the low-speed warning sound.

7. The apparatus according to claim 6, characterized in that, The analysis module includes: The frequency response acquisition unit is used to acquire the frequency response of the pedestrian warning device, the external measuring point and the internal measuring point of the vehicle; A frequency determination unit is used to determine the main frequency band based on the frequency response.

8. A vehicle, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the method for generating a low-speed warning sound for an electric vehicle as described in any one of claims 1-5.

9. A non-volatile computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by a processor to implement the method for generating a low-speed warning sound for an electric vehicle as described in any one of claims 1-5.

10. A computer program product, comprising a computer program, characterized in that, The computer program is executed to implement the method for generating a low-speed warning sound for an electric vehicle as described in any one of claims 1-5.

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