Vehicle engine noise optimization method and device, equipment and storage medium

Abstract

The invention discloses a vehicle engine noise optimization method and device, equipment and a storage medium, and relates to the technical field of engine control, and the method comprises the steps: obtaining a current driving mode when a user drives a vehicle, and determining environment data and vehicle driving information during vehicle driving according to the current driving mode; a preset noise-electric quantity mapping table is inquired through the environment data and the vehicle driving information based on the current driving mode, the target engine rotating speed is obtained, a vehicle engine is controlled to operate at the target engine rotating speed, and perceptible engine noise is calculated based on the environment data and the vehicle driving data; a vehicle engine is controlled based on the perceptible engine noise to complete engine noise optimization. The engine noise is optimized by inquiring the proper engine rotating speed and taking the perceptible noise as the optimization target, and the uncomfortable experience of the engine noise under the working conditions of low speed red light and the like can be greatly reduced.

Description

Technical Field

[0001] The present application relates to the field of engine control technology, and in particular to a vehicle engine noise optimization method, device, equipment and storage medium. Background Art

[0002] Existing new energy hybrid electric vehicle (REV) / PHEV (Plug-in Hybrid Electric Vehicle) systems primarily control engine starts and stops, as well as operating points, based on rules or shallow optimization strategies within the traditional PDCM (Power Distribution Control and Management) / EMS (Energy Management System) framework. In urban traffic scenarios with frequent starts and stops, low-speed following, and high SOC (battery charge) demands, the following issues are prone to occur: frequent engine starts lead to noticeable increases in in-cabin noise, impacting the user's driving experience. Furthermore, the inability to plan engine operation in advance also impacts the user's driving experience. Summary of the Invention

[0003] The main purpose of this application is to provide a vehicle engine noise optimization method, device, equipment and storage medium, aiming to solve the technical problem that frequent engine starting causes obvious noise jumps in the car, affecting the user's driving experience.

[0004] To achieve the above objectives, the present application proposes a vehicle engine noise optimization method, which includes:

[0005] Acquiring a current driving mode of a user when driving a vehicle, and determining environmental data and vehicle driving information when the vehicle is driving according to the current driving mode;

[0006] Based on the current driving mode, a preset noise-to-electricity mapping table is searched using the environmental data and the vehicle driving information to obtain a target engine speed, wherein the preset noise-to-electricity mapping table stores a mapping relationship between vehicle speed, background noise, vehicle electric quantity, and engine speed;

[0007] controlling a vehicle engine to operate at the target engine speed and calculating perceptible engine noise based on the environmental data and the vehicle driving data;

[0008] The vehicle engine is controlled based on the perceived engine noise to achieve engine noise optimization.

[0009] In one embodiment, the step of querying a preset noise-to-electricity mapping table based on the current driving mode through the environmental data and the vehicle driving information to obtain the target engine speed includes:

[0010] When the current driving mode is a navigation mode not enabled by the user, obtaining background noise data and real-time engine speed according to the environmental data;

[0011] Performing fast Fourier transform processing on the engine speed to obtain main-order noise of the engine;

[0012] generating a main-order noise reduction strategy when a difference between a total value of the engine main-order noise and the background noise data is greater than a preset noise threshold;

[0013] A preset noise-electricity mapping table is queried according to the main-order noise reduction strategy and the real-time engine speed to obtain a target engine speed.

[0014] In one embodiment, the step of querying a preset noise-to-electricity mapping table based on the current driving mode through the environmental data and the vehicle driving information to obtain the target engine speed includes:

[0015] When the current driving mode is navigation mode turned on by the user, speed limit information, traffic light status information, traffic light duration information, and road congestion information in the navigation route are obtained based on the environmental data, and current vehicle power information and background noise data are obtained based on the vehicle driving information;

[0016] Predicting engine start / stop nodes and engine operation nodes during vehicle driving by an artificial intelligence model based on the speed limit information, the traffic light status information, the traffic light duration, the road congestion information, the vehicle current power information, and the background noise data;

[0017] Determine the slow-moving speed and the predicted battery power of the vehicle when the vehicle is in a slow-moving condition according to the engine start-stop node and the engine running node;

[0018] A preset noise-electricity mapping table is queried according to the slow vehicle speed and the predicted electric quantity to obtain a target engine speed.

[0019] In one embodiment, the step of controlling the vehicle engine to operate at the target engine speed and calculating the perceptible engine noise based on the environmental data and the vehicle driving data comprises:

[0020] Controlling the vehicle engine to operate at the target engine speed, and obtaining engine main-order noise, background noise data, and current vehicle speed based on the environmental data and the vehicle driving data;

[0021] determining a corresponding masking coefficient according to the current vehicle speed;

[0022] The perceptible engine noise is calculated according to the total value of the main order noise of the engine, the masking coefficient and the background noise data.

[0023] In one embodiment, the step of controlling the vehicle engine based on the perceptible engine noise to achieve engine noise optimization includes:

[0024] Determining the current environment of the vehicle based on the environmental data, and obtaining the current energy consumption of the vehicle based on the vehicle driving data;

[0025] When the vehicle is currently in a slow-moving operating environment, a first noise optimization weight is selected from a preset noise optimization weight range, and a first energy consumption optimization weight is selected from a preset energy consumption optimization weight range, wherein the first noise optimization weight is greater than the first energy consumption optimization weight;

[0026] Optimizing the target to be optimized by using the first noise optimization weight, the first energy consumption optimization weight, the perceptible engine noise, and the current energy consumption of the vehicle to obtain an optimized engine speed and a target engine torque;

[0027] The vehicle engine operation is controlled by the optimized engine speed and the target engine torque to achieve engine noise optimization.

[0028] In one embodiment, the step of controlling the vehicle engine based on the perceptible engine noise to achieve engine noise optimization includes:

[0029] Obtaining the current power level and energy consumption of the vehicle according to the vehicle driving data;

[0030] When the current battery level of the vehicle is less than a preset battery level threshold, selecting a second noise optimization weight from a preset noise optimization weight range, and selecting a second energy consumption optimization weight from a preset energy consumption optimization weight range, wherein the second noise optimization weight is less than the second energy consumption optimization weight;

[0031] Optimizing the target to be optimized by using the second noise optimization weight, the second energy consumption optimization weight, the perceptible engine noise, and the current energy consumption of the vehicle to obtain an optimized engine speed and a target engine torque;

[0032] The vehicle engine operation is controlled by the optimized engine speed and the target engine torque to achieve engine noise optimization.

[0033] In one embodiment, the step of obtaining a current driving mode of a user when driving a vehicle, and determining environmental data and vehicle driving information when the vehicle is driving according to the current driving mode includes:

[0034] Obtaining the current driving mode of the user when driving the vehicle. If the current driving mode is navigation mode, obtaining speed limit information, traffic light status information, traffic light duration, and road congestion information in the navigation route;

[0035] Obtain vehicle current battery information, background noise data, and driving speed;

[0036] The speed limit information, the traffic light status information, the traffic light duration, and the road congestion information are used as environmental data when the vehicle is traveling, and the vehicle current power information, the background noise data, and the driving speed are used as vehicle driving information;

[0037] When the current driving mode is a navigation mode not turned on by the user, background noise data and real-time engine speed are collected by an in-vehicle voice collection device;

[0038] Obtain map cruise information, driving speed, and road information identified by the on-board camera;

[0039] The map cruise information and the road information are used as environmental data when the vehicle is traveling, and the background noise data, the driving speed and the real-time engine speed are used as vehicle driving information.

[0040] In addition, to achieve the above-mentioned purpose, the present application also proposes a vehicle engine noise optimization device, which includes:

[0041] An acquisition module is used to acquire a current driving mode of a user when driving a vehicle, and determine environmental data and vehicle driving information when the vehicle is driving according to the current driving mode;

[0042] a query module, configured to query a preset noise-to-electricity mapping table based on the current driving mode using the environmental data and the vehicle driving information to obtain a target engine speed, wherein the preset noise-to-electricity mapping table stores a mapping relationship between vehicle speed, background noise, vehicle electric quantity, and engine speed;

[0043] a control module configured to control a vehicle engine to operate at the target engine speed and calculate perceptible engine noise based on the environmental data and the vehicle driving data;

[0044] The control module is further configured to control the vehicle engine based on the perceptible engine noise to achieve engine noise optimization.

[0045] In addition, to achieve the above-mentioned purpose, the present application also proposes a vehicle engine noise optimization device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the vehicle engine noise optimization method described above.

[0046] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium and stores a computer program. When the computer program is executed by a processor, the steps of the vehicle engine noise optimization method described above are implemented.

[0047] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps of the vehicle engine noise optimization method as described above are implemented.

[0048] One or more technical solutions proposed in this application obtain the current driving mode of a user and determine the vehicle's environmental data and driving information based on the current driving mode; based on the current driving mode, query a preset noise-to-power mapping table using the environmental data and vehicle driving information to obtain a target engine speed. The preset noise-to-power mapping table stores mappings between vehicle speed, background noise, vehicle power, and engine speed; control the vehicle engine to operate at the target engine speed and calculate the perceived engine noise based on the environmental data and vehicle driving data; and control the vehicle engine based on the perceived engine noise to achieve engine noise optimization. By querying the preset noise-to-power mapping table for an appropriate engine speed, the engine speed can be properly controlled while ensuring noise optimization, avoiding excessive power or fuel consumption and thereby improving the vehicle's energy efficiency. By controlling the perceived level of engine noise, the driver and passengers can be effectively reduced from noise disturbance, especially on low-speed or congested roads, reducing the discomfort caused by engine noise to passengers. The driver can enjoy a quieter and more comfortable driving environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0050] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0051] Figure 1 A schematic diagram of a flow chart provided for the first embodiment of the vehicle engine noise optimization method of the present application;

[0052] Figure 2 A flow chart illustrating a second embodiment of the vehicle engine noise optimization method of the present application;

[0053] Figure 3 A schematic diagram of a flow chart provided for the third embodiment of the vehicle engine noise optimization method of the present application;

[0054] Figure 4 A flow chart illustrating a fourth embodiment of the vehicle engine noise optimization method of the present application;

[0055] Figure 5 This is a schematic diagram of the module structure of the vehicle engine noise optimization device according to an embodiment of the present application;

[0056] Figure 6 Schematic diagram of the device structure of the hardware operating environment involved in the vehicle engine noise optimization method in the embodiment of the present application.

[0057] The purpose, features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0058] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the present application and are not intended to limit the present application.

[0059] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0060] The main solution of the embodiment of the present application is: obtaining the current driving mode of the user when driving the vehicle, and determining the environmental data and vehicle driving information of the vehicle when driving according to the current driving mode; based on the current driving mode, querying a preset noise-electricity mapping table through the environmental data and the vehicle driving information to obtain a target engine speed, and the preset noise-electricity mapping table stores a mapping relationship between vehicle speed, background noise, vehicle electric quantity and engine speed; controlling the vehicle engine to run at the target engine speed, and calculating the perceptible engine noise based on the environmental data and the vehicle driving data; and controlling the vehicle engine based on the perceptible engine noise to complete engine noise optimization.

[0061] The existing technology frequently starts the engine, causing a noticeable increase in in-vehicle noise, affecting the user's driving experience; energy control focuses on maintaining SOC and insufficiently considers NVH targets; it is unable to make advanced working point planning based on navigation and road prediction information, and the existing system does not introduce a dynamic ambient noise masking mechanism, resulting in NVH (noise, vibration and harshness) control without perceptual consistency.

[0062] This application provides a solution that uses AGI (Artificial General Intelligence) to predict paths, traffic and the environment, and plan the engine's low-noise operating conditions in advance; constructs a noise-power joint map to achieve the optimal operating point allocation of the engine's electric drive; introduces a dynamic background noise masking model to optimize the consistency of NVH control and human perception, and supports users in enabling intelligent mode switching in navigation scenarios.

[0063] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, mobile phone, etc., or an electronic device capable of performing the above functions, such as a vehicle engine noise optimization device. The following uses the vehicle engine noise optimization device as an example to illustrate this embodiment and the following embodiments.

[0064] Based on this, the embodiment of the present application provides a vehicle engine noise optimization method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the vehicle engine noise optimization method of the present application.

[0065] In this embodiment, the vehicle engine noise optimization method includes steps S10 to S40:

[0066] Step S10: Acquire the current driving mode of the user when driving the vehicle, and determine the environmental data and vehicle driving information when the vehicle is driving according to the current driving mode.

[0067] It should be noted that the user may turn on navigation or not when driving the vehicle. In this embodiment, the current driving mode includes the user turning on the navigation mode or the user not turning on the navigation mode. The user turning on the navigation mode is the strong prediction mode, and the subsequent engine control can be predicted based on the navigation data. The user not turning on the navigation mode is the perception response mode, and the engine can be controlled based on real-time perception data.

[0068] In specific implementations, different driving modes may result in different environmental data and vehicle information being acquired during driving. Environmental data during driving may include speed limit data, traffic light status data, traffic light duration data, road congestion information, map cruise information, road information identified by the vehicle's onboard camera, and other data, which are not limited in this embodiment. Vehicle driving information may include battery information, background noise data, engine speed data, engine torque data, driving speed data, and other data, which are not limited in this embodiment.

[0069] In a feasible implementation, step S10 may include steps A11 to A16:

[0070] Step A11: Obtaining the current driving mode of the user when driving the vehicle. When the current driving mode is the navigation mode turned on by the user, obtaining speed limit information, traffic light status information, traffic light duration, and road congestion information in the navigation route;

[0071] It should be noted that if the user turns on the navigation system, the current driving mode is to enter "navigation mode", and the vehicle will make relevant settings according to the navigation path.

[0072] Speed ​​limit information refers to the maximum speed set for the vehicle's route. It is usually determined by traffic signs, road conditions, and regulations. For example, on city roads, the speed limit may be 60km / h; on highways, the speed limit may be 120km / h. Traffic light status information refers to the current state of traffic lights, usually "red light", "green light", and "yellow light". Traffic light duration refers to the length of time the current traffic light state is maintained. The duration of the red and green lights predicted by the navigation software can be directly obtained. Road congestion information refers to the current traffic flow conditions on the road, including whether there are any vehicles stagnant or moving slowly. If the road where the vehicle is located is densely populated and the flow is slow, the system will display "severe congestion" or "minor congestion".

[0073] Specifically, in navigation mode, all information related to the current route can be obtained from the navigation system, such as speed limit, traffic light status, traffic light duration, and road congestion information. For example, the navigation route shows that the speed limit 5 kilometers ahead is 60 km / h, the red light duration is 45 seconds, and the road congestion level is medium.

[0074] Step A12: Obtain the vehicle's current battery information, background noise data, and driving speed;

[0075] The vehicle's current charge information can be directly detected by sensors, that is, the vehicle's current remaining energy. For example, if an electric vehicle shows that the remaining charge is 80%, the vehicle's current charge information SOC is 80%.

[0076] Background noise data refers to the noise generated by the environment inside and outside the vehicle, usually collected by sensors or microphones inside the vehicle. Driving speed refers to the current speed of the vehicle, which can be detected by the speed sensor.

[0077] Step A13: using the speed limit information, the traffic light status information, the traffic light duration, and the road congestion information as vehicle driving environment data, and using the vehicle current battery information, the background noise data, and the driving speed as vehicle driving information;

[0078] In specific implementation, when the navigation mode is turned on for the user in the current driving mode, the previously collected speed limit information, traffic light status, traffic light duration and road congestion conditions are regarded as "environmental data", while the battery information, background noise data and vehicle speed are regarded as "vehicle driving information".

[0079] Step A14: When the current driving mode is the navigation mode not enabled by the user, background noise data and real-time engine speed are collected by the in-vehicle voice collection device;

[0080] It should be noted that if the current driving mode is that the user has not turned on the navigation mode, the background noise data can be collected through the voice collection device in the car and the real-time engine speed can be obtained.

[0081] The in-car voice collection device can be a microphone installed in the car, or a noise sensor. The real-time engine speed can be detected by a speed sensor, for example, the real-time engine speed is 3000rpm.

[0082] Step A15: Obtaining map cruise information, vehicle speed, and road information recognized by the vehicle camera;

[0083] It should be noted that if the user does not enable navigation, the vehicle can cruise based on GPS or an onboard mapping system, thereby obtaining map cruise information. Map cruise information includes the driving route and related information obtained by GPS or an onboard mapping system, such as road type and section length. Onboard cameras can be installed around the vehicle and on the roof. The onboard cameras obtain relevant information about the current road by identifying road markings, traffic signs, obstacles, and other information.

[0084] Step A16: using the map cruise information and the road information as environmental data when the vehicle is traveling, and using the background noise data, the driving speed, and the real-time engine speed as vehicle driving information.

[0085] In a specific implementation, map cruise information and road information can be used as environmental data when the vehicle is traveling, and background noise data, driving speed and real-time engine speed can be used as vehicle driving information.

[0086] Step S20: Based on the current driving mode, a preset noise-electricity mapping table is queried through the environmental data and the vehicle driving information to obtain a target engine speed. The preset noise-electricity mapping table stores a mapping relationship between vehicle speed, background noise, vehicle electric quantity and engine speed.

[0087] It should be noted that the noise-to-battery mapping table stores the mapping relationships between vehicle speed, background noise, battery level, and engine speed in different environments. For example, when the vehicle speed is 60 km / h and the background noise is high, the recommended engine speed is 2000 rpm, while at lower speeds, the speed is set to 1500 rpm. Specifically, background noise at different vehicle speeds, engine speeds, and battery levels can be collected in advance to establish a mapping relationship between vehicle speed, engine speed, vehicle battery level, and background noise.

[0088] In a specific implementation, the current driving mode can be determined first. When the driving mode is different, the parameters of the preset noise-electricity mapping table are different. Therefore, the specific query parameters are determined from the environmental data and vehicle driving information according to the specific driving mode, and the corresponding engine speed is queried through the query parameters as the target engine speed.

[0089] The target engine speed is a speed with less noise in the current environment.

[0090] In a feasible implementation, step S20 may include steps A21 to A24:

[0091] Step A21: When the current driving mode is the navigation mode not enabled by the user, background noise data and real-time engine speed are obtained according to the environmental data;

[0092] It should be noted that if the current driving mode is that the user has not turned on the navigation mode, real-time collected data can be obtained, so background noise data and real-time engine speed data can be obtained through environmental data.

[0093] Step A22: performing fast Fourier transform processing on the engine speed to obtain the main order noise of the engine;

[0094] In a specific implementation, the engine speed can be processed by fast Fourier transform, the engine speed signal can be converted into a spectrum through FFT, and noise of different orders (such as 2nd order, 4th order, etc.) can be extracted to obtain the main order noise of the engine.

[0095] Step A23: When the difference between the total value of the main-order noise of the engine and the background noise data is greater than a preset noise threshold, generating a main-order noise reduction strategy;

[0096] In specific implementation, the main-order noises of the engine can be added together to obtain the total value of the main-order noise of the engine. The current total value of the main-order noise of the engine can be compared with the background noise level to determine whether it is "perceived abruptly". If the difference between the total value of the main-order noise of the engine and the background noise data is less than or equal to the preset noise threshold, the engine speed will not be adjusted, and the vehicle will continue to be controlled at the current engine speed.

[0097] The preset noise threshold can be set to 1 dBA, or other values, which are not limited in this embodiment. If the difference between the total value of the engine main-order noise and the background noise data is greater than the preset noise threshold, the AGI model needs to control the EMS to adjust the current operating conditions. Specifically, a strategy for reducing the main-order noise can be generated.

[0098] It should be noted that a delayed engine start-stop strategy can also be generated, for example, a delay time is set, such as 10 seconds, and the engine is controlled to start after 10 seconds.

[0099] Step A24: querying a preset noise-electricity mapping table according to the main-order noise reduction strategy and the real-time engine speed to obtain a target engine speed.

[0100] It should be noted that the preset noise-electricity mapping table can be queried by reducing the main-order noise strategy and the real-time engine speed, and the speed close to the real-time engine speed but less than the real-time engine speed can be queried as the target engine speed.

[0101] For example, if the real-time engine speed is 2000 rpm, the main-order noise reduction strategy is used to query the preset noise-power mapping table for engine speeds lower than 2000 rpm. For example, if the engine speed obtained by the query is 1500 rpm, the target engine speed is 1500 rpm.

[0102] It should be understood that if the current driving mode of the vehicle is a mode in which the user turns on navigation, prediction can be made using navigation data. Therefore, step S20 may further include steps A21' to A24':

[0103] Step A21': When the current driving mode is navigation mode enabled by the user, speed limit information, traffic light status information, traffic light duration information, and road congestion information in the navigation route are obtained based on the environmental data, and current vehicle battery information and background noise data are obtained based on the vehicle driving information;

[0104] It should be noted that if the current driving mode is navigation mode turned on by the user, the speed limit information, traffic light status information, traffic light duration and road congestion information in the navigation route can be obtained based on the environmental data, and the current battery information of the vehicle and background noise data can be obtained based on the vehicle driving information.

[0105] Step A22': predicting engine start / stop nodes and engine operation nodes during vehicle driving based on the speed limit information, the traffic light status information, the traffic light duration, the road congestion information, the vehicle current battery information, and the background noise data using an artificial intelligence model;

[0106] It is understandable that the AGI model can be used to predict the engine start and stop and operation nodes throughout the entire journey based on the above information.

[0107] Step A23': determining the slow-moving speed and the predicted battery power of the vehicle when the vehicle is in a slow-moving condition according to the engine start / stop node and the engine running node;

[0108] In specific implementations, it is possible to determine whether there is a slow-moving operating condition based on the specific engine start-stop nodes and engine operation nodes. Slow-moving operating conditions include waiting for red lights, driving in low-speed congestion, and following a vehicle (for example, the speed is less than 30km / h). To avoid sudden noise changes, AGI can avoid starting the engine during this period in advance. In actual driving, there may be unavoidable situations, so the corresponding operating conditions can be determined based on the specific engine start-stop nodes and operation nodes. When the vehicle is in the cache operating condition, the predicted slow-moving speed and predicted battery power of the vehicle in this condition can be obtained. The slow-moving speed can be predicted in the AGI model based on road congestion, and the predicted battery power can also be predicted by the AGI model based on the vehicle's real-time energy consumption and road information.

[0109] Step A24 ′: querying a preset noise-electricity mapping table according to the slow vehicle speed and the predicted electric quantity to obtain a target engine speed.

[0110] In a specific implementation, the appropriate engine speed can be queried in a preset noise-power mapping table according to the slow-moving speed of the vehicle and the predicted battery power, thereby controlling the engine operation.

[0111] Step S30: Controlling the vehicle engine to operate at the target engine speed, and calculating the perceptible engine noise based on the environmental data and the vehicle driving data.

[0112] In specific implementation, the vehicle can be controlled according to the target engine speed obtained by the query, and the vehicle engine can be controlled to run at the target engine speed, so as to make advanced working point planning based on navigation and road prediction information, formulate the optimal operating condition trajectory, plan the engine low-noise working point, and improve the user's driving experience.

[0113] It should be noted that after controlling the engine to run at the target engine speed, it can also be adjusted according to actual conditions. For example, when the speed is greater than a certain threshold (such as 60km / h), the background noise dominated by wind noise and tire noise often masks some engine order sounds, so the subjective perception may not be obvious. At this time, the optimization target can be adjusted according to the actual situation. Therefore, the perceptible engine noise can be calculated through environmental data and vehicle driving data.

[0114] Perceivable engine noise refers to the engine noise that a user can subjectively perceive in a vehicle. The perceivable engine noise varies depending on the user's environment.

[0115] Step S40: Controlling the vehicle engine based on the perceptible engine noise to achieve engine noise optimization.

[0116] It should be noted that after the perceptible engine noise is calculated, the vehicle's engine can be controlled again based on the perceptible engine noise, thereby adjusting the engine operation based on the user's perceptible engine noise to achieve engine noise optimization.

[0117] This embodiment provides a method for optimizing vehicle engine noise. The method obtains a user's current driving mode and determines environmental data and vehicle driving information based on the current driving mode. Based on the current driving mode, the method queries a preset noise-to-power mapping table using the environmental data and vehicle driving information to determine a target engine speed. The preset noise-to-power mapping table stores mappings between vehicle speed, background noise, vehicle power, and engine speed. The method controls the vehicle engine to operate at the target engine speed and calculates perceptible engine noise based on the environmental data and vehicle driving data. The method then controls the vehicle engine based on the perceptible engine noise to optimize engine noise. By querying the preset noise-to-power mapping table for an appropriate engine speed, the method allows for reasonable engine speed control while ensuring noise optimization, avoiding excessive power or fuel consumption and thereby improving vehicle energy efficiency. By controlling the perceived level of engine noise, the method effectively reduces noise disturbance to the driver and passengers, particularly on low-speed or congested roads, thereby reducing the discomfort caused by engine noise to passengers. This allows the driver to enjoy a quieter and more comfortable driving environment.

[0118] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above embodiment 1 can be referred to the above introduction and will not be described in detail later. Figure 2 , step S30 includes steps S301 to S303:

[0119] Step S301: Controlling the vehicle engine to run at the target engine speed, and obtaining the engine main-order noise, background noise data and current vehicle speed based on the environmental data and the vehicle driving data.

[0120] It should be noted that after obtaining the target engine speed, the vehicle engine can be controlled to operate at the target engine speed and environmental data and vehicle driving data at the target engine speed can be collected. Based on the environmental data and vehicle driving data, background noise data, engine speed data, and current vehicle speed can be obtained. The main order noise can be extracted by performing a fast Fourier transform on the engine speed data.

[0121] Step S302: determining a corresponding masking coefficient according to the current vehicle speed.

[0122] It is understandable that since the user's subjective perception of noise is not obvious when the speed is greater than a certain threshold, this embodiment introduces a dynamically corrected perception model for correction. Specifically, the speed-related masking coefficient can be set in advance. The masking coefficient can be subjectively calibrated for different vehicles and different speeds during the development stage, and the masking effect is stronger when driving at high speeds.

[0123] Step S303: Calculating the perceptible engine noise by using the total value of the main-order noise of the engine, the masking coefficient, and the background noise data.

[0124] In a specific implementation, the perceptible engine noise can be calculated by the total value of the main-order noise of the engine, the masking coefficient, and the background noise value, as follows:

[0125] N 感知 =N eng -α v ·N 背景

[0126] N 感知 That is, the engine noise can be felt inside the car, N eng That is the total value of the main order noise of the engine, α v is the masking coefficient corresponding to the current vehicle speed, N 背景 That is, the background noise related to vehicle speed (wind noise + road noise) can be obtained through pure electric driving.

[0127] This embodiment controls the vehicle engine to operate at the target engine speed and, based on environmental data and vehicle driving data, obtains engine main-order noise, background noise data, and the current vehicle speed. A corresponding masking coefficient is determined based on the current vehicle speed. The perceived engine noise is calculated using the total value of the main-order noise, the masking coefficient, and the background noise data. By dynamically incorporating masking effects such as wind and road noise to calculate the perceived noise, dynamic masking modeling ensures that NVH control closely matches the user's actual perception, enhancing user experience consistency.

[0128] Based on the first embodiment of the present application, in the third embodiment of the present application, the same or similar contents as those in the above embodiment 1 can be referred to the above introduction and will not be described in detail later. Figure 3 , step S40 includes steps S401 to S404:

[0129] Step S401: determining the current environment of the vehicle according to the environmental data, and obtaining the current energy consumption of the vehicle according to the vehicle driving data.

[0130] It should be noted that the vehicle's current environment can be determined based on environmental data. Perceivable noise varies depending on the vehicle's environment. For example, if the vehicle is stopped at a red light, the user may perceive a higher level of noise. However, if the vehicle is traveling at high speed, the user's perceived noise is reduced due to wind and road noise. Therefore, the vehicle's current environment can be determined based on environmental data, and the vehicle's current energy consumption (the vehicle's energy consumption over a period of time) can be derived based on the vehicle's current environment and current energy consumption. The optimization target can be determined based on the vehicle's current environment and energy consumption, and when multiple optimization targets exist, the priority of the optimization targets can be determined.

[0131] In a specific implementation, a weighted objective function of perceptible noise and unit energy consumption can be established, which is expressed as follows:

[0132]

[0133] In the above formula, n is the engine speed, T is the engine torque, v is the vehicle real-time speed, N 感知 is the perceptible engine noise level under the current working condition; E is the energy consumption of the vehicle under the current working condition, ω1 is the noise optimization weight, and ω2 is the energy consumption optimization weight. By solving the weighted objective function, multi-objective optimization can be achieved.

[0134] Step S402: When the vehicle is currently in a slow-moving operating environment, a first noise optimization weight is selected from a preset noise optimization weight range, and a first energy consumption optimization weight is selected from a preset energy consumption optimization weight range, wherein the first noise optimization weight is greater than the first energy consumption optimization weight.

[0135] It should be noted that if the vehicle is currently in a slow-moving environment, it means that the vehicle speed is low or it is in a city traffic light section. If the vehicle starts the engine at this time, there will be a lot of noise, so noise reduction needs to be prioritized. The preset noise optimization weight range and the preset energy consumption optimization weight range can be set in advance. For example, the preset noise optimization weight range is set to 0.3~0.8, and the preset energy consumption optimization weight range is set to 0.5~0.9. It can also be set to other ranges, and this embodiment does not limit this.

[0136] In a specific implementation, when priority noise reduction is required, the noise optimization weight is greater than the energy consumption optimization weight. Therefore, the first noise optimization weight is selected from the preset noise optimization weights, and the first energy consumption optimization weight is selected from the preset energy consumption optimization weight range. For example, the first noise optimization weight is 0.8, and the first energy consumption optimization weight is 0.5.

[0137] Step S403: Optimizing the target to be optimized by using the first noise optimization weight, the first energy consumption optimization weight, the perceptible engine noise, and the current energy consumption of the vehicle to obtain an optimized engine speed and a target engine torque.

[0138] It should be noted that the targets to be optimized include perceptible noise and vehicle energy consumption. Therefore, the targets to be optimized can be optimized using the first noise optimization weight, the first energy consumption optimization weight, the perceptible engine noise, and the current energy consumption of the vehicle, thereby obtaining the optimal engine speed and engine torque.

[0139] Step S404: Controlling the operation of the vehicle engine by using the optimized engine speed and the target engine torque to achieve engine noise optimization.

[0140] In specific implementation, the optimized engine speed can be used as the new target engine speed to control the engine operation, and the engine can be controlled by the target engine torque, so as to achieve "virtual quietness" of the engine under different states and complete the optimization of engine noise.

[0141] This embodiment determines the current environment of the vehicle based on the environmental data, and obtains the current energy consumption of the vehicle based on the vehicle driving data; when the current environment of the vehicle is a slow-moving condition, a first noise optimization weight is selected from a preset noise optimization weight range, and a first energy consumption optimization weight is selected from a preset energy consumption optimization weight range, wherein the first noise optimization weight is greater than the first energy consumption optimization weight; the optimization target is optimized by the first noise optimization weight, the first energy consumption optimization weight, the perceptible engine noise, and the current energy consumption of the vehicle to obtain an optimized engine speed and a target engine torque; the vehicle engine operation is controlled by the optimized engine speed and the target engine torque to complete engine noise optimization. By combining noise optimization with energy consumption optimization weights, the optimization parameters can be intelligently adjusted according to actual needs. Under slow-moving conditions, noise optimization takes precedence over energy consumption optimization, which meets the user's demand for a quiet driving environment and can be dynamically adjusted according to different driving conditions, driving habits, and environmental conditions to enhance the driving experience.

[0142] Based on the first embodiment of the present application, in the fourth embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction and will not be described in detail later. Figure 4 , step S40 includes steps S401' to S404':

[0143] Step S401 ′: obtaining the current battery level and energy consumption of the vehicle according to the vehicle driving data.

[0144] It should be noted that the vehicle's current battery level is the vehicle's current remaining SOC, which can be obtained directly based on the vehicle's driving data, or calculated based on the vehicle's current speed and congestion conditions. At the same time, the vehicle's current energy consumption can also be obtained based on the vehicle's driving data.

[0145] Step S402': When the current battery level of the vehicle is less than a preset battery level threshold, a second noise optimization weight is selected from a preset noise optimization weight range, and a second energy consumption optimization weight is selected from a preset energy consumption optimization weight range, wherein the second noise optimization weight is less than the second energy consumption optimization weight.

[0146] It can be understood that the preset power threshold is a critical value at which the vehicle may be unable to drive. If the current power of the vehicle is less than the preset power threshold, it means that the vehicle may be stuck. At this time, the control of the vehicle prioritizes power generation or energy efficiency. Therefore, when selecting weights, the value of the second energy consumption optimization weight is greater than the value of the second noise optimization weight. For example, the second energy consumption optimization weight is selected as 0.8, and the second noise optimization weight is selected as 0.5.

[0147] Step S403 ′: optimizing the target to be optimized by using the second noise optimization weight, the second energy consumption optimization weight, the perceptible engine noise, and the current energy consumption of the vehicle to obtain an optimized engine speed and a target engine torque.

[0148] In a specific implementation, the weighted objective function can be solved by selecting the optimization weights, the perceptible engine noise, and the current energy consumption of the vehicle to obtain the optimal engine speed and engine torque.

[0149] Step S404 ′: controlling the vehicle engine operation by using the optimized engine speed and the target engine torque to achieve engine noise optimization.

[0150] In specific implementation, the optimized engine speed can be used as the new target engine speed to control the engine operation, and the engine can be controlled by the target engine torque, so as to achieve "virtual quietness" of the engine under different states and complete the optimization of engine noise.

[0151] In another embodiment, the noise optimization weight and energy consumption optimization weight can be dynamically adjusted according to the vehicle driving mode and the user's driving style, so as to achieve engine noise control under different working conditions and reduce the user's uncomfortable experience of engine noise under slow driving conditions.

[0152] In specific implementation, the energy consumption and perceptible noise under different situations can also be counted in advance, and the weighted objective function can be solved to obtain the optimal engine speed and engine torque, thereby establishing a mapping relationship between energy consumption, perceptible noise, engine speed and engine torque. During actual driving, the corresponding optimal engine speed and engine torque can be queried based on the perceptible noise and vehicle energy consumption, so as to control vehicle driving through the optimal engine speed and optimal engine torque, balance noise and energy consumption, and improve control effect.

[0153] This embodiment obtains the vehicle's current battery level and energy consumption based on the vehicle driving data. When the vehicle's current battery level is less than a preset battery level threshold, a second noise optimization weight is selected from a preset noise optimization weight range, and a second energy consumption optimization weight is selected from a preset energy consumption optimization weight range, wherein the second noise optimization weight is less than the second energy consumption optimization weight. The optimization target is optimized using the second noise optimization weight, the second energy consumption optimization weight, the perceptible engine noise, and the vehicle's current energy consumption to obtain an optimized engine speed and a target engine torque. The vehicle's engine operation is controlled using the optimized engine speed and the target engine torque to achieve engine noise optimization. The optimization weights for noise and energy consumption are intelligently adjusted based on the vehicle's current battery level and energy consumption, so that when battery power is limited, the system automatically adjusts the weights, thereby more effectively balancing the vehicle's energy efficiency and noise control requirements. This enhances the vehicle's adaptability to different energy states and ensures that a high level of energy efficiency can be maintained even when battery power is limited.

[0154] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the vehicle engine noise optimization method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0155] This application also provides a vehicle engine noise optimization device, please refer to Figure 5 , the vehicle engine noise optimization device comprises:

[0156] The acquisition module 10 is used to acquire the current driving mode of the user when driving the vehicle, and determine the environmental data and vehicle driving information when the vehicle is driving according to the current driving mode.

[0157] The query module 20 is used to query a preset noise-electricity mapping table based on the current driving mode through the environmental data and the vehicle driving information to obtain a target engine speed. The preset noise-electricity mapping table stores a mapping relationship between vehicle speed, background noise, vehicle electric quantity and engine speed.

[0158] The control module 30 is configured to control the vehicle engine to operate at the target engine speed and calculate the perceptible engine noise based on the environmental data and the vehicle driving data.

[0159] The control module 30 is further configured to control the vehicle engine based on the perceptible engine noise to optimize the engine noise.

[0160] The vehicle engine noise optimization device provided in this application, utilizing the vehicle engine noise optimization method described in the aforementioned embodiments, can address the technical issue of frequent engine startups causing noticeable increases in in-vehicle noise, which impacts the user's driving experience. Compared to the prior art, the vehicle engine noise optimization device provided in this application offers the same beneficial effects as the vehicle engine noise optimization method described in the aforementioned embodiments. Other technical features of the vehicle engine noise optimization device are the same as those disclosed in the aforementioned embodiments and are not further elaborated here.

[0161] In one embodiment, the query module 20 is further configured to, when the current driving mode is navigation mode not enabled by the user, obtain background noise data and real-time engine speed based on the environmental data; perform fast Fourier transform processing on the engine speed to obtain main-order noise of the engine; generate a main-order noise reduction strategy when the difference between the total value of the main-order noise of the engine and the background noise data is greater than a preset noise threshold; and query a preset noise-to-electricity mapping table based on the main-order noise reduction strategy and the real-time engine speed to obtain a target engine speed.

[0162] In one embodiment, the query module 20 is also used to obtain speed limit information, traffic light status information, traffic light duration and road congestion information in the navigation path according to the environmental data when the current driving mode is the navigation mode turned on by the user, and obtain the vehicle's current power information and background noise data according to the vehicle driving information; predict the engine start and stop nodes and engine running nodes during the vehicle's driving process based on the speed limit information, the traffic light status information, the traffic light duration and the road congestion information, the vehicle's current power information and the background noise data through an artificial intelligence model; determine the slow-moving speed and predicted battery power when the vehicle is in a slow-moving condition according to the engine start and stop nodes and the engine running nodes; query a preset noise-power mapping table according to the slow-moving speed and the predicted power to obtain a target engine speed.

[0163] In one embodiment, the control module 30 is further used to control the vehicle engine to operate at the target engine speed, and obtain the engine main-order noise, background noise data and the current vehicle speed based on the environmental data and the vehicle driving data; determine the corresponding masking coefficient according to the current vehicle speed; and calculate the perceptible engine noise through the total value of the engine main-order noise, the masking coefficient and the background noise data.

[0164] In one embodiment, the control module 30 is further used to determine the current environment of the vehicle based on the environmental data, and obtain the current energy consumption of the vehicle based on the vehicle driving data; when the current environment of the vehicle is a slow-moving condition, select a first noise optimization weight from a preset noise optimization weight range, and select a first energy consumption optimization weight from a preset energy consumption optimization weight range, wherein the first noise optimization weight is greater than the first energy consumption optimization weight; optimize the target to be optimized by using the first noise optimization weight, the first energy consumption optimization weight, the perceptible engine noise and the current energy consumption of the vehicle to obtain an optimized engine speed and a target engine torque; control the operation of the vehicle engine by using the optimized engine speed and the target engine torque to complete engine noise optimization.

[0165] In one embodiment, the control module 30 is further used to obtain the current battery level of the vehicle and the current energy consumption of the vehicle based on the vehicle driving data; when the current battery level of the vehicle is less than a preset battery level threshold, select a second noise optimization weight from a preset noise optimization weight range, and select a second energy consumption optimization weight from a preset energy consumption optimization weight range, wherein the second noise optimization weight is less than the second energy consumption optimization weight; optimize the target to be optimized using the second noise optimization weight, the second energy consumption optimization weight, the perceptible engine noise, and the current energy consumption of the vehicle to obtain an optimized engine speed and a target engine torque; control the operation of the vehicle engine using the optimized engine speed and the target engine torque to complete engine noise optimization.

[0166] In one embodiment, the acquisition module 10 is further used to obtain the current driving mode of the user when driving the vehicle. When the current driving mode is the navigation mode turned on by the user, the speed limit information, traffic light status information, traffic light duration and road congestion information in the navigation route are obtained; the current battery information, background noise data and driving speed of the vehicle are obtained; the speed limit information, the traffic light status information, the traffic light duration and the road congestion information are used as environmental data when the vehicle is driving, and the current battery information, the background noise data and the driving speed of the vehicle are used as vehicle driving information; when the current driving mode is the navigation mode not turned on by the user, the background noise data and the real-time engine speed are collected through the in-vehicle voice collection device; map cruise information, driving speed and road information recognized by the vehicle-mounted camera are obtained; the map cruise information and the road information are used as environmental data when the vehicle is driving, and the background noise data, the driving speed and the real-time engine speed are used as vehicle driving information.

[0167] The present application provides a vehicle engine noise optimization device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the vehicle engine noise optimization method of the above-mentioned embodiment 1.

[0168] Reference below Figure 6 , which shows a schematic diagram of the structure of a vehicle engine noise optimization device suitable for implementing embodiments of the present application. The vehicle engine noise optimization device in embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 6 The vehicle engine noise optimization device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0169] like Figure 6As shown, the vehicle engine noise optimization device may include a processing device 1001 (e.g., a central processing unit, graphics processing unit, etc.), which can perform various appropriate actions and processes based on programs stored in ROM (Read Only Memory) 1002 or programs loaded from storage device 1003 into RAM (Random Access Memory) 1004. RAM 1004 also stores various programs and data required for the operation of the vehicle engine noise optimization device. Processing device 1001, ROM 1002, and RAM 1004 are interconnected via bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input device 1007, such as a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output device 1008, such as an LCD (Liquid Crystal Display), speaker, vibrator, etc.; storage device 1003, such as a magnetic tape, hard disk, etc.; and communication device 1009. Communication device 1009 can allow the vehicle engine noise optimization device to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a vehicle engine noise optimization device with various systems, it should be understood that it is not required to implement or have all of the systems shown. More or fewer systems may be implemented or have alternatively.

[0170] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0171] The vehicle engine noise optimization device provided in this application, utilizing the vehicle engine noise optimization method described in the aforementioned embodiment, can address the technical issue of frequent engine startups causing noticeable increases in in-vehicle noise, impacting the user's driving experience. Compared to the prior art, the beneficial effects of the vehicle engine noise optimization device provided in this application are the same as those of the vehicle engine noise optimization method described in the aforementioned embodiment. Other technical features of the vehicle engine noise optimization device are the same as those disclosed in the aforementioned embodiment and are not further elaborated here.

[0172] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0173] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0174] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, a computer program) stored thereon, wherein the computer-readable program instructions are used to execute the vehicle engine noise optimization method in the above-mentioned embodiment.

[0175] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable Read Only Memory or Flash memory), optical fiber, CD-ROM (CD-Read Only Memory, portable compact disk read-only memory), optical storage device, magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0176] The computer-readable storage medium may be included in the vehicle engine noise optimization device; or may exist independently without being assembled into the vehicle engine noise optimization device.

[0177] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the vehicle engine noise optimization device, the vehicle engine noise optimization device: obtains the current driving mode of the user when driving the vehicle, and determines the environmental data and vehicle driving information when the vehicle is driving according to the current driving mode; based on the current driving mode, queries a preset noise-electricity mapping table through the environmental data and the vehicle driving information to obtain a target engine speed, and the preset noise-electricity mapping table stores a mapping relationship between vehicle speed, background noise, vehicle electric quantity and engine speed; controls the vehicle engine to run at the target engine speed, and calculates the perceptible engine noise based on the environmental data and the vehicle driving data; controls the vehicle engine based on the perceptible engine noise to complete engine noise optimization.

[0178] The computer program code for performing the operations of the present application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate 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 can be connected to the user's computer through any type of network, including a LAN (Local Area Network) or a WAN (Wide Area Network), or can be connected to an external computer (e.g., using an Internet service provider to connect via the Internet).

[0179] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0180] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0181] The computer-readable storage medium provided in this application stores computer-readable program instructions (i.e., a computer program) for executing the aforementioned vehicle engine noise optimization method. This computer-readable storage medium can address the technical issue of frequent engine startups causing noticeable increases in in-vehicle noise, impacting the user's driving experience. Compared to the prior art, the beneficial effects of the computer-readable storage medium provided in this application are similar to those of the vehicle engine noise optimization method provided in the aforementioned embodiments, and are not further elaborated here.

[0182] The present application also provides a computer program product, comprising a computer program, which implements the steps of the vehicle engine noise optimization method as described above when the computer program is executed by a processor.

[0183] The computer program product provided in this application can address the technical issue of frequent engine startups causing noticeable increases in in-vehicle noise, impacting the user's driving experience. Compared to existing technologies, the beneficial effects of the computer program product provided in this application are similar to those of the vehicle engine noise optimization method provided in the aforementioned embodiments, and are not further elaborated here.

[0184] The above description is only part of the embodiments of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A vehicle engine noise optimization method, characterized in that: The vehicle engine noise optimization method comprises: Acquiring a current driving mode of a user when driving a vehicle, and determining environmental data and vehicle driving information when the vehicle is driving according to the current driving mode; Based on the current driving mode, a preset noise-to-electricity mapping table is searched using the environmental data and the vehicle driving information to obtain a target engine speed, wherein the preset noise-to-electricity mapping table stores a mapping relationship between vehicle speed, background noise, vehicle electric quantity, and engine speed; controlling a vehicle engine to operate at the target engine speed and calculating perceptible engine noise based on the environmental data and the vehicle driving data; The vehicle engine is controlled based on the perceived engine noise to achieve engine noise optimization.

2. The method according to claim 1, wherein The step of obtaining the target engine speed by querying a preset noise-electricity mapping table based on the current driving mode through the environmental data and the vehicle driving information includes: When the current driving mode is a navigation mode not enabled by the user, obtaining background noise data and real-time engine speed according to the environmental data; Performing fast Fourier transform processing on the engine speed to obtain main-order noise of the engine; generating a main-order noise reduction strategy when a difference between a total value of the engine main-order noise and the background noise data is greater than a preset noise threshold; A preset noise-electricity mapping table is queried according to the main-order noise reduction strategy and the real-time engine speed to obtain a target engine speed.

3. The method according to claim 1, wherein The step of obtaining the target engine speed by querying a preset noise-electricity mapping table based on the current driving mode through the environmental data and the vehicle driving information includes: When the current driving mode is navigation mode turned on by the user, speed limit information, traffic light status information, traffic light duration information, and road congestion information in the navigation route are obtained based on the environmental data, and current vehicle power information and background noise data are obtained based on the vehicle driving information; Predicting engine start / stop nodes and engine operation nodes during vehicle driving by an artificial intelligence model based on the speed limit information, the traffic light status information, the traffic light duration, the road congestion information, the vehicle current power information, and the background noise data; Determine the slow-moving speed and the predicted battery power of the vehicle when the vehicle is in a slow-moving condition according to the engine start-stop node and the engine running node; A preset noise-electricity mapping table is queried according to the slow vehicle speed and the predicted electric quantity to obtain a target engine speed.

4. The method according to claim 1, wherein The step of controlling the vehicle engine to operate at the target engine speed and calculating the perceptible engine noise based on the environmental data and the vehicle driving data includes: Controlling the vehicle engine to operate at the target engine speed, and obtaining engine main-order noise, background noise data, and current vehicle speed based on the environmental data and the vehicle driving data; Determining a corresponding masking coefficient according to the current vehicle speed; The perceptible engine noise is calculated according to the total value of the main order noise of the engine, the masking coefficient and the background noise data.

5. The method according to claim 1, wherein The step of controlling the vehicle engine based on the perceptible engine noise to optimize the engine noise includes: Determining the current environment of the vehicle based on the environmental data, and obtaining the current energy consumption of the vehicle based on the vehicle driving data; When the vehicle is currently in a slow-moving operating environment, a first noise optimization weight is selected from a preset noise optimization weight range, and a first energy consumption optimization weight is selected from a preset energy consumption optimization weight range, wherein the first noise optimization weight is greater than the first energy consumption optimization weight; Optimizing the target to be optimized by using the first noise optimization weight, the first energy consumption optimization weight, the perceptible engine noise, and the current energy consumption of the vehicle to obtain an optimized engine speed and a target engine torque; The vehicle engine operation is controlled by the optimized engine speed and the target engine torque to achieve engine noise optimization.

6. The method according to claim 1, wherein The step of controlling the vehicle engine based on the perceptible engine noise to optimize the engine noise includes: Obtaining the current power level and energy consumption of the vehicle according to the vehicle driving data; When the current battery level of the vehicle is less than a preset battery level threshold, selecting a second noise optimization weight from a preset noise optimization weight range, and selecting a second energy consumption optimization weight from a preset energy consumption optimization weight range, wherein the second noise optimization weight is less than the second energy consumption optimization weight; Optimizing the target to be optimized by using the second noise optimization weight, the second energy consumption optimization weight, the perceptible engine noise, and the current energy consumption of the vehicle to obtain an optimized engine speed and a target engine torque; The vehicle engine operation is controlled by the optimized engine speed and the target engine torque to achieve engine noise optimization.

7. The method according to any one of claims 1 to 6, characterized in that The step of obtaining the current driving mode of the user when driving the vehicle and determining the environmental data and vehicle driving information when the vehicle is driving according to the current driving mode includes: Obtaining the current driving mode of the user when driving the vehicle. If the current driving mode is navigation mode, obtaining speed limit information, traffic light status information, traffic light duration, and road congestion information in the navigation route; Obtain vehicle current battery information, background noise data, and driving speed; The speed limit information, the traffic light status information, the traffic light duration, and the road congestion information are used as environmental data when the vehicle is traveling, and the vehicle current power information, the background noise data, and the driving speed are used as vehicle driving information; When the current driving mode is a navigation mode not turned on by the user, background noise data and real-time engine speed are collected by an in-vehicle voice collection device; Obtain map cruise information, driving speed, and road information identified by the on-board camera; The map cruise information and the road information are used as environmental data when the vehicle is traveling, and the background noise data, the driving speed and the real-time engine speed are used as vehicle driving information.

8. A vehicle engine noise optimization device, characterized in that: The device comprises: An acquisition module is used to acquire a current driving mode of a user when driving a vehicle, and determine environmental data and vehicle driving information when the vehicle is driving according to the current driving mode; a query module, configured to query a preset noise-to-electricity mapping table based on the current driving mode using the environmental data and the vehicle driving information to obtain a target engine speed, wherein the preset noise-to-electricity mapping table stores a mapping relationship between vehicle speed, background noise, vehicle electric quantity, and engine speed; a control module configured to control a vehicle engine to operate at the target engine speed and calculate perceptible engine noise based on the environmental data and the vehicle driving data; The control module is further configured to control the vehicle engine based on the perceptible engine noise to achieve engine noise optimization.

9. A vehicle engine noise optimization device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the vehicle engine noise optimization method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the vehicle engine noise optimization method according to any one of claims 1 to 7 are implemented.

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