Methods for constructing an in-vehicle sound environment to suppress abnormal noises in electric vehicles

Abstract

This invention provides a method for constructing an in-vehicle sound environment to suppress abnormal noises in electric vehicles. By matching the acoustic characteristics of in-vehicle abnormal noise signals with the correspondence between these characteristics and real-time road information and wheel speed, the method retrieves and plays associated ambient sound music from the in-vehicle sound environment storage unit to mask the abnormal noises. During the masking process, the controller re-analyzes the in-vehicle sound signal acquisition unit, which collects the abnormal noise signals in real time. The method evaluates the masking effect of the associated ambient sound music and optimizes it. Furthermore, it correlates changes in the comfort experience of passengers with the noise impact before and after optimization, aiming to ensure that passengers can genuinely perceive an improvement in the noise environment.

Description

Technical Field

[0001] This invention belongs to the field of electric vehicle noise treatment technology, specifically relating to a method for constructing an in-vehicle sound environment to suppress the impact of abnormal noises in electric vehicles. Background Technology

[0002] With the increasing popularity of EVs (pure electric vehicles), REEVs (range-extended electric vehicles), and PHEVs (plug-in hybrid electric vehicles) in China, more and more users are choosing pure electric travel. Electric vehicles (EVs), REEVs, and PHEVs, when driving in pure electric mode, do not produce engine vibration noise compared to traditional internal combustion engine vehicles (ICE). During driving, the background noise level inside the cabin is significantly reduced, approximately 10 dB(A) lower than that of traditional ICE vehicles, making it extremely quiet. Passengers are highly sensitive to abnormal noises caused by vibrations in the interior components, making such noises more noticeable. Furthermore, in JD Power's China Initial Quality Study (IQS), abnormal noises caused by vibrations in interior components have shown a year-on-year upward trend in automotive quality complaints. How to suppress abnormal noises caused by vibrations in interior components has become a major concern for OEMs. For example, the patent titled "A Method and System for Controlling In-Vehicle Noise and Vibration in New Energy Vehicles" (Patent No.: CN 114120955 A) discloses a method and system for controlling in-vehicle noise and vibration in new energy vehicles. The above solution analyzes the collected noise information and uses the vehicle audio system to output sound waves of corresponding frequency orders, aiming to cancel or reduce in-vehicle noise. Although it has a certain effect of eliminating or reducing noise, the actual effect of noise reduction is unknown, and whether the riding comfort of drivers and passengers is improved is also unknown. Summary of the Invention

[0003] This invention provides a method for constructing an in-vehicle sound environment to reduce the impact of abnormal noises in electric vehicles. design The method aims to ensure that drivers and passengers can truly feel the improvement in the noise environment.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] A method for constructing an in-vehicle sound environment to suppress abnormal noises in electric vehicles, characterized by comprising the following steps:

[0006] S1: The in-vehicle sound signal acquisition unit collects abnormal noise signals in the vehicle in real time;

[0007] S2: In-vehicle cameras record the status of drivers and passengers, while lidar and external cameras collect real-time road information, and wheel speed sensors monitor vehicle speed.

[0008] S3: The controller receives the information or signals collected in steps S1 and S2, and determines the acoustic characteristics of the abnormal noise signal inside the vehicle and the correspondence between the acoustic characteristics of the abnormal noise signal inside the vehicle and the real-time road information and wheel speed.

[0009] S4: The controller retrieves the associated ambient sound music stored in the in-vehicle sound environment storage unit and sends it to the playback unit for playback;

[0010] S5: The controller re-analyzes the abnormal noise signals in the vehicle that are collected in real time by the in-vehicle sound signal acquisition unit, evaluates the masking effect of the associated ambient sound music on the abnormal noise signals in the vehicle, and optimizes and plays the associated ambient sound music.

[0011] The above solution utilizes an in-vehicle sound signal acquisition unit to collect abnormal noise signals inside the vehicle in real time, and uses in-vehicle cameras to record the status of drivers and passengers, obtaining their physiological information. It also uses lidar and external cameras to collect real-time road information, and wheel speed sensors to monitor vehicle speed. The controller determines the acoustic characteristics of the abnormal noise signals inside the vehicle and their correspondence with real-time road information and wheel speed based on these signals. It then retrieves ambient sound music from the in-vehicle sound environment storage unit and plays it to the playback unit to mask the abnormal noises. During the masking process, the controller re-analyzes the in-vehicle sound signal acquisition unit, evaluates the masking effect of the associated ambient sound music, optimizes the associated ambient sound music, and correlates changes in driver and passenger comfort with the noise impact before and after environmental noise optimization. Attached Figure Description

[0012] Figure 1 This is a flowchart of the invention;

[0013] Figure 2 This is a flowchart of the tag creation process in this invention;

[0014] Figure 3 This is a flowchart of the matching process between driving scenario tags and abnormal noise condition tags in this invention;

[0015] Figure 4 This is a flowchart of the environmental sound and music optimization process in this invention. Detailed Implementation

[0016] like Figure 1 The method for constructing an in-vehicle sound environment to suppress abnormal noises in electric vehicles, as shown, is characterized by including the following steps:

[0017] S1: The in-vehicle sound signal acquisition unit collects abnormal noise signals in the vehicle in real time;

[0018] S2: In-vehicle cameras record the status of drivers and passengers, while lidar and external cameras collect real-time road information, and wheel speed sensors monitor vehicle speed.

[0019] S3: The controller receives the information or signals collected in steps S1 and S2, and determines the acoustic characteristics of the abnormal noise signal inside the vehicle and the correspondence between the acoustic characteristics of the abnormal noise signal inside the vehicle and the real-time road information and wheel speed.

[0020] S4: The controller retrieves the associated ambient sound music stored in the in-vehicle sound environment storage unit and sends it to the playback unit for playback;

[0021] S5: The controller re-analyzes the abnormal noise signals in the vehicle that are collected in real time by the in-vehicle sound signal acquisition unit, evaluates the masking effect of the associated ambient sound music on the abnormal noise signals in the vehicle, and optimizes and plays the associated ambient sound music.

[0022] The aforementioned technical solution utilizes an in-vehicle sound signal acquisition unit to collect real-time abnormal noise signals within the vehicle, and in-vehicle recording equipment to capture the state of the driver and passengers, obtaining their physiological information. Real-time road information and vehicle speed are collected through LiDAR, external recording equipment, and wheel speed sensors. The controller receives these signals and, based on these signals, determines the acoustic characteristics of the in-vehicle abnormal noise signals and the correspondence between these acoustic characteristics and real-time road information and wheel speed. It then retrieves associated ambient sound music from the in-vehicle sound environment storage unit and sends it to the playback unit to mask the abnormal noises. During the masking process, the controller re-analyzes the in-vehicle sound signal acquisition unit's real-time collection of abnormal noise signals, evaluating the masking effect of the associated ambient sound music. This includes assessing changes in the physiological characteristics of the driver and passengers, such as changes in facial expressions and changes before and after noise suppression. This allows for a direct and objective understanding of the actual noise reduction effect, enabling further optimization of the associated ambient sound music.

[0023] Furthermore, the in-vehicle sound signal acquisition unit in step S1 includes a microphone system installed on the vehicle roof and a built-in in-vehicle voice recognition system. The microphone system on the vehicle roof and the built-in in-vehicle voice recognition system capture in-vehicle sound signals in real time and send them to the controller.

[0024] In step S2, the in-vehicle camera captures and analyzes the driver's and passengers' facial expressions, eye movements, head postures, and other visual information in real time to obtain the driver's and passengers' physiological signals.

[0025] Specifically, the in-vehicle recording equipment includes a bioelectrical signal sensor that measures the skin resistance of drivers and passengers, reflects physiological indicators related to skin conductance and emotional stress, and an in-vehicle camera that captures and analyzes visual information such as facial expressions, eye movements, and head posture of drivers and passengers in real time to obtain their physiological signals.

[0026] In step S2, the lidar scans the road surface in real time to depict its undulations, obstacles, textures and other features. The wheel speed sensor continuously monitors the vehicle's speed. The controller receives relevant signals or information and establishes the correlation between road conditions, wheel speed and abnormal noise signals inside the vehicle.

[0027] The lidar and wheel speed sensor work together. The lidar is responsible for scanning the road surface in real time and accurately depicting its undulations, obstacles, textures and other features for road identification. The wheel speed sensor continuously monitors the vehicle's speed. The data from both are combined, and the controller receives relevant signals and establishes a correlation between road conditions, wheel speed and abnormal noise signals inside the vehicle.

[0028] like Figure 3 In step S3, the controller receives the information or signals collected in steps S1 and S2. It matches the corresponding tags based on the acoustic characteristics of the abnormal noise signals in the vehicle, which are called abnormal noise condition tags. It matches the corresponding tags based on the physiological signals of the driver and passengers and the current driving environment data of the vehicle, which are called driving scenario tags.

[0029] Based on the driving scenario tags and abnormal noise condition tags under the current situation, the controller retrieves the corresponding ambient sound music data of the driving scenario tags and abnormal noise condition tags from the associated ambient sound music library stored in the in-vehicle sound environment storage unit and sends it to the playback unit for playback.

[0030] The controller optimizes the associated ambient sound music by changing the intensity of different frequencies and the overall volume of the ambient sound music to continuously improve the masking effect of the associated ambient sound music.

[0031] like Figure 2 The in-vehicle sound signal acquisition unit in step S5 described above acquires the abnormal noise sound signal in the vehicle in real time and sends it to the controller. The controller analyzes the abnormal noise sound signal in the vehicle, evaluates the masking effect of the associated ambient sound on the abnormal noise sound signal in the vehicle, and optimizes the masking effect of the ambient sound accordingly.

[0032] like Figure 2 The steps for creating tags for associated ambient sound music stored in the in-vehicle sound environment storage unit, as shown, include:

[0033] The vehicle was driven on a surface with specific abnormal noise characteristics on the test track to collect abnormal noise sound signal data inside the vehicle;

[0034] Match music data from the ambient sound music library with in-vehicle noise signal data from roads with specific noise characteristics, compare the rhythmic structure of the ambient sound music, and evaluate the effect of reducing in-vehicle noise signals.

[0035] Based on the matching results above, assign corresponding abnormal noise condition tags to each ambient sound music piece;

[0036] Each ambient sound music track is assigned a driving scenario label based on its type.

[0037] Some specific abnormal noise conditions under classic operating conditions include, but are not limited to:

[0038] 1. On a cobblestone road surface with a driving speed of 0-40 km / h, the following abnormal noise risk points were identified: knocking and friction noise between interior / exterior trim parts; chassis shock absorber valve system; and loose steering system noise.

[0039] 2. On Brazilian cobblestone roads at driving speeds of 0–40 km / h, the following abnormal noise risk points were identified: knocking and friction noises from interior / exterior trim components (air ducts, air vents, instruments, guard panels, etc.) and abnormal noises from the damper valve system.

[0040] 3. On European brick roads with a driving speed of 0-40 km / h, the abnormal noise risk points found in the experiment are: abnormal noises caused by the knocking and friction between interior / exterior components (air ducts, air vents, instruments, guards, etc.).

[0041] 4. On a rough asphalt road at a driving speed of 60-80 km / h, the experimental findings revealed abnormal noise risk points: abnormal noise caused by loose interior parts.

[0042] 5. Smooth asphalt road at driving speeds of 60–80 km / h: The experimental findings indicate abnormal noise risk points: abnormal noise caused by severely loose interior trim parts.

[0043] 6. The risk points for abnormal noise were identified during experiments on damaged (patched) asphalt roads at speeds of 40–60 km / h: This confirmed the overall condition of abnormal noise from the vehicle on slightly undulating road surfaces. Driving speeds: 40 and 60 km / h.

[0044] 7. Grooved cement road at a driving speed of 60-80 km / h, the abnormal noise risk points found in the experiment: abnormal noise at the extreme positions of the chassis or body under large deceleration obstacles.

[0045] Specifically, vehicle driving scenarios include, but are not limited to, the following classic categories:

[0046] 1. Emotional regulation scenario: When driving alone, one needs to release stress, adjust emotions, and calm down to think.

[0047] Matching ambient sound music includes: mood-regulating music, such as sad or healing pop, folk, indie music, classical music, meditation music, New Age, and sad or uplifting electronic music.

[0048] Specifically, you can choose appropriate music based on your current emotional state to help soothe your emotions or boost your spirits.

[0049] 2. Long-distance driving scenarios: highway driving, long-distance travel, self-driving tours, etc.

[0050] Matching ambient music includes road trip-style rock, folk, country, world music, and upbeat pop songs. These ambient sounds help create a sense of openness and freedom of exploration, reducing driving fatigue and adding to the enjoyment of the journey.

[0051] 3. Urban commuting scenarios: daily commute, short trips, picking up and dropping off children, etc.

[0052] Matching ambient music includes: music suitable for work and study, such as classical music, movie scores, ambient music, electronic ambient music, or low-decibel indie pop and folk music. This type of ambient music helps maintain focus while driving, while providing a relatively quiet and soothing in-car atmosphere to relieve commuting stress.

[0053] 4. Romantic dating scenarios: going on a road trip with your partner, picking up your date, celebrating special moments in the car, etc.

[0054] Matching ambient music includes romantic date music such as romantic jazz, lyrical pop, R&B, soft classical music, romantic movie soundtracks, soul, soft rock, and classic love songs. These ambient sounds can create a warm and romantic atmosphere in the car, enhancing the date experience.

[0055] For the aforementioned classic driving scenarios and classic abnormal noise conditions, ambient sound music from the ambient sound music library will be used in conjunction with these scenarios and conditions.

[0056] For each ambient sound music track, the masking effect principle in acoustic theory is applied to accurately calculate the energy distribution of each music track in different frequency bands and the range of abnormal noise frequencies that can be effectively masked. The rhythmic structure of the music is carefully compared, especially its beat, tempo, and the frequency characteristics of abnormal noises under various operating conditions. This ensures that the selected music can suppress in-vehicle abnormal noises in a specific driving scenario or abnormal noise condition, thereby improving the comfort of the in-vehicle sound environment. Driving scenario tags and abnormal noise condition tags are created for each music track. Based on the driving scenario tags and abnormal noise condition tags under the current conditions, the controller retrieves ambient sound music data matching the tags from the associated ambient sound music library stored in the in-vehicle sound environment storage unit and sends it to the playback unit to reduce the impact of abnormal noises in electric vehicles. Specific Implementation Example 1

[0058] For example, during a driver's daily commute, the in-vehicle sound signal acquisition unit collects real-time abnormal noise signals from inside the vehicle, the in-vehicle camera records the status of the driver and passengers, the lidar and external camera collect real-time road information, and the wheel speed sensor monitors the vehicle's speed. The controller receives these signals and determines that the acoustic characteristics of the abnormal noise signals are caused by loose interior parts. It then determines that the driver is alone and fatigued during their daily commute, driving at 60-80 km / h on a rough asphalt road. The controller then uses the aforementioned abnormal noise condition tags, driving scenario tags, and data stored in the in-vehicle sound environment storage unit... The system matches relevant ambient sounds and music, retrieves the corresponding ambient sounds and music, and sends them to the playback unit for playback. While providing emotional value, it also masks abnormal noises inside the vehicle. During the masking process, the controller collects and re-analyzes the abnormal noise signals inside the vehicle in real time from the in-vehicle sound signal acquisition unit to evaluate the masking effect of the relevant ambient sounds and music on the abnormal noise signals inside the vehicle. This includes changes in the physiological characteristics of the driver and passengers, such as changes in their facial expressions and changes before and after noise suppression. This allows for a direct and objective understanding of the actual noise reduction effect, so as to whether further optimization of the relevant ambient sounds and music is necessary.

[0059] like Figure 4 As shown, the ambient sound and music signals are collected using the parameters mentioned above and input to the controller. The controller evaluates the masking effect of the associated ambient sound on the abnormal noise signals in the vehicle using four parameters: A-weighted sound pressure level, speech intelligibility (AI), sharpness, and jitter. Specifically, A-weighted sound pressure level reflects the overall noise level in the vehicle, speech intelligibility reflects the clarity of voice communication in the vehicle environment, sharpness reflects the harshness of the sound, and jitter reflects the amplitude and regularity of sound changes over time. The controller optimizes the ambient sound and music signals in real time based on the above four parameters to ensure the best masking effect.

Claims

1. A method for constructing an in-vehicle sound environment to suppress abnormal noises in electric vehicles, characterized in that, Includes the following steps: S1: The in-vehicle sound signal acquisition unit collects abnormal noise signals in the vehicle in real time; S2: The in-vehicle camera records the status of the driver and passengers, the lidar and the external camera collect real-time road information, and the wheel speed sensor monitors the vehicle speed; the lidar scans the road surface in real time to depict its undulations, obstacles and texture features, the wheel speed sensor continuously monitors the vehicle speed, and the controller receives relevant signals or information and establishes the correlation between road conditions, wheel speed and abnormal noise signals in the vehicle. S3: The controller receives the information or signals collected in steps S1 and S2, and determines the acoustic characteristics of the abnormal noise signal inside the vehicle and the correspondence between the acoustic characteristics of the abnormal noise signal inside the vehicle and the real-time road information and wheel speed. S4: The controller retrieves the associated ambient sound music stored in the in-vehicle sound environment storage unit and sends it to the playback unit for playback; S5: The controller re-analyzes the abnormal noise signals in the vehicle that are collected in real time by the in-vehicle sound signal acquisition unit, evaluates the masking effect of the associated ambient sound music on the abnormal noise signals in the vehicle, and optimizes and plays the associated ambient sound music.

2. The method according to claim 1, characterized in that: The in-vehicle sound signal acquisition unit in step S1 includes a microphone system installed on the vehicle roof and a built-in in-vehicle voice recognition system. The microphone system on the vehicle roof and the built-in in-vehicle voice recognition system capture in-vehicle sound signals in real time and send them to the controller.

3. The method according to claim 1, characterized in that: In step S2, the in-vehicle camera captures and analyzes the facial expressions, eye movements, and head posture of the driver and passengers in real time to obtain their physiological signals.

4. The method according to claim 1, 2, or 3, characterized in that: In step S3, the controller receives the information or signals collected in steps S1 and S2. It matches the corresponding tags based on the acoustic characteristics of the abnormal noise signals in the vehicle, which are called abnormal noise condition tags. It matches the corresponding tags based on the physiological signals of the driver and passengers and the current driving environment data of the vehicle, which are called driving scenario tags.

5. The method according to claim 4, characterized in that: Based on driving scenario tags and abnormal noise condition tags, the controller retrieves the corresponding ambient sound music data with driving scenario tags and abnormal noise condition tags from the associated ambient sound music library stored in the in-vehicle sound environment storage unit and sends it to the playback unit for playback.

6. The method according to claim 1, characterized in that: In step S5, the in-vehicle sound signal acquisition unit collects abnormal noise signals in the vehicle in real time and sends them to the controller. The controller analyzes the abnormal noise signals in the vehicle, evaluates the masking effect of associated ambient sounds on the abnormal noise signals in the vehicle, and optimizes the masking effect of ambient sounds accordingly.

7. The method according to claim 4, characterized in that: The steps for creating tags for associated ambient sound music stored in the in-vehicle sound environment storage unit include: The vehicle was driven on the test track's surface with abnormal noise characteristics to collect sound signal data of abnormal noises inside the vehicle; The music data in the ambient sound music library is matched with the in-vehicle noise signal data on the road surface with abnormal noise characteristics. The rhythm structure of the ambient sound music is compared to evaluate the effect of reducing the in-vehicle noise signal. Based on the matching results above, assign corresponding abnormal noise condition tags to each ambient sound music piece; Each ambient sound music track is assigned a driving scenario label based on its type.

8. The method according to claim 6, characterized in that: The controller optimizes the associated ambient sound music by changing the intensity of different frequencies and the overall volume of the ambient sound music to continuously improve the masking effect of the associated ambient sound music.

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