Vehicle defogger adjustment methods, devices, equipment and storage media
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- DONGFENG LIUZHOU MOTOR
- Filing Date
- 2023-05-23
- Publication Date
- 2026-06-30
Smart Images
Figure CN116985748B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of data processing technology, and in particular to a method, apparatus, device, and storage medium for adjusting vehicle defogging. Background Technology
[0002] During vehicle operation, the windows are prone to fogging due to environmental factors, obstructing the view of the driver and other passengers, potentially leading to accidents. Currently, vehicle defogging processes lack adjustable defogging modes and cannot adaptively adjust power consumption and modes based on the current scenario. This results in significant energy loss or poor defogging performance, impacting the driver's driving experience and leading to a subpar user experience.
[0003] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention
[0004] The main objective of this invention is to provide a vehicle defogging adjustment method, apparatus, device, and storage medium, aiming to solve the technical problem that the existing technology cannot adaptively adjust the power consumption and mode of defogging based on the current scenario, resulting in poor vehicle defogging effect and energy waste.
[0005] To achieve the above objectives, the present invention provides a vehicle defogging adjustment method, the method comprising the following steps:
[0006] Based on the region information of the vehicle's current location, obtain candidate fog data corresponding to the region;
[0007] Environmental information is collected about the environment in which the vehicle is located to obtain current environmental information;
[0008] The candidate fog data is corrected based on the current environmental information to obtain the target fog data;
[0009] The target fog data is input into a pre-built defogging analysis model for defogging analysis, and the defogging mode of the vehicle is adjusted based on the defogging analysis results.
[0010] Optionally, obtaining candidate fog data corresponding to the region based on the region information of the vehicle's current location includes:
[0011] The vehicle is located based on its current location information to determine its current location.
[0012] Obtain the climate mapping table corresponding to the region based on the region information;
[0013] Based on the current time, the climate mapping table is consulted to determine the current climate characteristics of the region.
[0014] Candidate fog data for the region are obtained based on the aforementioned climate characteristics.
[0015] Optionally, obtaining candidate fog data corresponding to the region based on the climate characteristics includes:
[0016] Based on the climate characteristics, a preset feature mapping table is searched to determine the fog characteristics corresponding to the climate characteristics;
[0017] Obtain the initial fog data corresponding to the fog features;
[0018] Determine the current day / night information based on the current time;
[0019] Based on the climate characteristics and the current day-night information, the initial fog data is cleaned to obtain candidate fog data corresponding to the region.
[0020] Optionally, the current environmental information includes light intensity and ambient temperature and humidity information; the step of correcting the candidate fog data based on the current environmental information to obtain the target fog data includes:
[0021] Environmental information is collected from the vehicle's cabin to obtain cabin temperature and humidity information.
[0022] The cabin temperature and humidity information is compared with the ambient temperature and humidity information to obtain temperature and humidity difference information;
[0023] The candidate fog data is corrected based on the light intensity and the temperature and humidity difference information to obtain the target fog data.
[0024] Optionally, the step of correcting the candidate fog data based on the light intensity and the temperature and humidity difference information to obtain the target fog data includes:
[0025] Obtain the current environmental wind information of the region, and the current driving status of the vehicle;
[0026] The airflow field information of the vehicle's onboard glass wall is determined based on the current ambient wind information and the current driving status.
[0027] A fog classification strategy is formulated based on the airflow field information, the light intensity, and the temperature and humidity difference information.
[0028] The candidate fog data is corrected based on the fog classification strategy to obtain the target fog data.
[0029] Optionally, the step of correcting the candidate fog data based on the current environmental information to obtain the target fog data includes:
[0030] Obtain the destination information and waypoint information of the vehicle;
[0031] The destination information and the waypoint information are input into a pre-built driving route prediction model to obtain the predicted route of the vehicle.
[0032] The areas the vehicle will pass through are determined based on the predicted route and the area where the vehicle is currently located.
[0033] The candidate fog data is corrected based on the regional information and weather information of the route area to obtain the target fog data.
[0034] Optionally, before inputting the target fog data into a pre-built defogging analysis model for defogging analysis, and adjusting the vehicle's defogging mode based on the defogging analysis results, the method further includes:
[0035] Obtain multiple sets of fog data from a preset fog database, as well as the corresponding impact data of the fog data, wherein the impact data is the data on the impact of fog on the vehicle glass;
[0036] Determine the data weights corresponding to multiple sets of fog data based on the impact data;
[0037] Based on the data weights, obtain the defogging modes corresponding to multiple sets of fog data;
[0038] A defogging analysis model is constructed based on multiple sets of fog data and the corresponding defogging modes.
[0039] Furthermore, to achieve the above objectives, the present invention also proposes a vehicle defogging adjustment device, the vehicle defogging adjustment device comprising:
[0040] The region data acquisition module is used to acquire candidate fog data corresponding to the region based on the region information of the current location of the vehicle;
[0041] The environmental information acquisition module is used to collect environmental information about the environment in which the vehicle is located and obtain the current environmental information.
[0042] A fog data correction module is used to correct the candidate fog data based on the current environmental information to obtain the target fog data;
[0043] The defogging analysis module is used to input the target fog data into a pre-built defogging analysis model for defogging analysis, and adjust the vehicle's defogging mode based on the defogging analysis results.
[0044] Furthermore, to achieve the above objectives, the present invention also proposes a vehicle defogging adjustment device, which includes: a memory, a processor, and a vehicle defogging adjustment program stored in the memory and executable on the processor, wherein the vehicle defogging adjustment program is configured to implement the steps of the vehicle defogging adjustment method described above.
[0045] In addition, to achieve the above objectives, the present invention also proposes a storage medium storing a vehicle defogging adjustment program, wherein when the vehicle defogging adjustment program is executed by a processor, the steps of the vehicle defogging adjustment method described above are implemented.
[0046] This invention obtains candidate fog data corresponding to the vehicle's current location based on the vehicle's regional information, collects environmental information about the vehicle's environment to obtain current environmental information, corrects the candidate fog data based on the current environmental information to obtain target fog data, inputs the target fog data into a pre-built defogging analysis model for defogging analysis, and adjusts the vehicle's defogging mode based on the defogging analysis results. Because this invention corrects the candidate fog data corresponding to the vehicle's location based on the collected current environmental information, and inputs the corrected target fog data into the defogging analysis model for defogging analysis, it obtains a defogging mode suitable for the vehicle's current driving scenario, providing the vehicle with a suitable defogging strategy. This ensures defogging effectiveness in heavily foggy environments, improves vehicle defogging efficiency, and avoids energy waste during the defogging process in lightly foggy environments. Attached Figure Description
[0047] Figure 1 This is a schematic diagram of the structure of a vehicle defogging adjustment device in the hardware operating environment involved in the embodiments of the present invention;
[0048] Figure 2 This is a flowchart illustrating the first embodiment of the vehicle defogging adjustment method of the present invention;
[0049] Figure 3 This is a schematic diagram of the defogging analysis model of the first embodiment of the vehicle defogging adjustment method of the present invention;
[0050] Figure 4 This is a flowchart illustrating the second embodiment of the vehicle defogging adjustment method of the present invention;
[0051] Figure 5 This is a flowchart illustrating the third embodiment of the vehicle defogging adjustment method of the present invention;
[0052] Figure 6 This is a structural block diagram of the first embodiment of the vehicle defogging adjustment device of the present invention.
[0053] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation
[0054] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.
[0055] Reference Figure 1 , Figure 1 This is a schematic diagram of the vehicle defogging adjustment device structure in the hardware operating environment involved in the embodiments of the present invention.
[0056] like Figure 1 As shown, the vehicle defogging adjustment device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen or an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wireless-Fidelity (Wi-Fi) interface). The memory 1005 may be high-speed random access memory (RAM) or stable non-volatile memory (NVM), such as a disk storage device. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.
[0057] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on vehicle defogging adjustment equipment and may include more or fewer components than shown, or combine certain components, or have different component arrangements.
[0058] like Figure 1 As shown, the memory 1005, which serves as a storage medium, may include an operating system, a network communication module, a user interface module, and a vehicle defogging adjustment program.
[0059] exist Figure 1In the vehicle defogging adjustment device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the vehicle defogging adjustment device of the present invention can be set in the vehicle defogging adjustment device, and the vehicle defogging adjustment device calls the vehicle defogging adjustment program stored in the memory 1005 through the processor 1001 and executes the vehicle defogging adjustment method provided in the embodiment of the present invention.
[0060] This invention provides a method for adjusting vehicle defogging, referring to... Figure 2 , Figure 2 This is a flowchart illustrating the first embodiment of a vehicle defogging adjustment method according to the present invention.
[0061] In this embodiment, the vehicle defogging adjustment method includes the following steps:
[0062] Step S10: Obtain candidate fog data corresponding to the region based on the region information of the current location of the vehicle.
[0063] It should be understood that the execution subject of the method in this embodiment may be a vehicle defogging adjustment device with data processing, network communication and program operation functions, such as an on-board controller, or other devices or equipment that can achieve the same or similar functions. Here, the above-mentioned vehicle defogging adjustment device (hereinafter referred to as defogging adjustment device) is used as an example for explanation.
[0064] It should be noted that the region can be the area or city where the vehicle is currently located. The aforementioned region information may include local climate type (e.g., tropical monsoon climate, temperate maritime climate, plateau climate, coastal climate, etc.), seasonal characteristics, temperature and humidity characteristics, etc. The aforementioned candidate fog data can be fog impact data that causes fogging of vehicle windows. For example, if the climate of the area where the vehicle is located is a coastal climate, the humidity in coastal areas is high, so the vehicle windows are prone to fogging when driving in that area.
[0065] It should be understood that the defogging adjustment device in this embodiment obtains the regional climate characteristics corresponding to the current location of the vehicle, obtains the corresponding candidate fog data based on the regional climate characteristics, determines the fogging characteristics of the vehicle glass when the vehicle is driving in the current region based on the candidate fog data, and adjusts the vehicle's defogging strategy based on the fogging characteristics, thereby achieving adaptive adjustment of the vehicle's defogging mode, thus realizing personalized defogging adjustment, effectively improving defogging efficiency and reducing defogging energy consumption.
[0066] For example, the defogging adjustment equipment determines the current location of the vehicle, obtains the regional information of the region, determines that the region has a coastal climate, and determines that the region is a coastal city. Since the regional humidity of coastal cities is relatively high, the vehicle's defogging strategy is adjusted to a high-power defogging mode, thereby improving the vehicle's defogging efficiency.
[0067] Step S20: Collect environmental information about the environment in which the vehicle is located to obtain current environmental information.
[0068] It should be noted that the environment in which the vehicle is located can refer to the environment in which the vehicle is currently driving. The aforementioned current environmental information can be relevant parameter information of the external environment in which the vehicle is currently driving, such as the current ambient temperature, current ambient humidity, current sunlight intensity, current wind speed, etc.
[0069] It should be understood that since vehicle window fogging is affected by the environment, the candidate fog data obtained above is only the theoretical fogging characteristics of the area where the vehicle is located. Therefore, in order to accurately understand the local fogging characteristics, this embodiment collects environmental information about the environment in which the vehicle is located, and obtains environmental information such as temperature, humidity, sunlight intensity, wind speed, and wind direction in the current driving environment, thereby determining the factors affecting window fogging in the current driving environment.
[0070] Step S30: Correct the candidate fog data according to the current environmental information to obtain the target fog data.
[0071] It should be noted that the target fog data can be the fog impact data that causes fogging of vehicle windows after correcting the candidate fog data based on the current environmental information.
[0072] It should be understood that because environmental information varies in different regions under different seasons, times, and day and night conditions, candidate fog data determined solely based on regional information has low accuracy. Therefore, in order to accurately understand the environmental characteristics of the current vehicle environment, the candidate fog data is corrected to obtain target fog data, thereby determining the fog characteristics that cause the glass to fog up in the environment where the vehicle is driving.
[0073] For example, the defogging adjustment device determines that the vehicle is currently driving in region A. Based on the regional information of region A, it determines that the candidate fog data in region A has a large temperature difference and high humidity. By collecting environmental information about the current driving environment of the vehicle, it determines that the current humidity is moderate and the temperature difference is small. The candidate fog data is corrected to the target fog data with moderate humidity and small temperature difference. Based on the target fog data, the defogging mode is adjusted to a medium power consumption defogging mode.
[0074] Furthermore, in order to prevent fogging at different points along the route during vehicle operation, step S30 may include:
[0075] Obtain the destination information and waypoint information of the vehicle;
[0076] The destination information and the waypoint information are input into a pre-built driving route prediction model to obtain the predicted route of the vehicle.
[0077] The areas the vehicle will pass through are determined based on the predicted route and the area where the vehicle is currently located.
[0078] The candidate fog data is corrected based on the regional information and weather information of the route area to obtain the target fog data.
[0079] It should be noted that the destination information can be the destination of the vehicle's current route, along with its location and weather information. The waypoint information can be the locations the vehicle will pass through on its journey to the destination, along with their location and weather information. The route prediction model can be a neural network model pre-built by the defogging adjustment equipment to predict the vehicle's route. This model can predict the vehicle's route to the destination and through each waypoint based on the input destination and waypoints. The transit areas can be the regions / cities the vehicle will pass through during its journey.
[0080] It should be understood that this embodiment corrects fog data based on the vehicle's predicted driving route and weather changes during the driving process, and then adjusts the defogging mode based on the corrected fog data to prevent fogging. For example, if the vehicle travels from city A to city B, the defogging mode is adjusted accordingly; if the weather changes from sunny to rainy during the vehicle's journey, the defogging mode is adjusted in advance based on weather forecasts. This embodiment adjusts the defogging mode based on the vehicle's predicted driving route and weather changes during the driving process, which can improve the defogging effect and reduce energy consumption, thereby achieving a more intelligent and efficient defogging system.
[0081] Understandably, defogging adjustment equipment can determine the areas a vehicle will pass through on its predicted route. Depending on the weather characteristics of different cities or regions, the defogging mode can be pre-adjusted to adapt to the weather conditions of the destination city or region. For example, if a vehicle is about to travel to a northern city, the defogging mode can be pre-adjusted to a high-power heating mode adapted to cold climates to cope with possible low temperatures and high humidity.
[0082] It should be understood that defoggers can adjust based on weather changes during driving: weather forecasts or other meteorological information sources can be used to obtain real-time weather information during vehicle operation. Based on this real-time weather information, the defogger mode can be dynamically adjusted to adapt to the changing weather. For example, if the weather changes from sunny to rainy during driving, the defogger mode can be promptly adjusted to a medium-power heating mode suitable for rainy conditions to address potential fog formation.
[0083] Step S40: Input the target fog data into the pre-built defogging analysis model for defogging analysis, and adjust the defogging mode of the vehicle based on the defogging analysis results.
[0084] It should be noted that the fog analysis model can be a pre-built neural network model. The fog adjustment equipment builds training and testing sets based on weather data, fog impact data, and fog removal effect data, and then trains the model based on the training and testing sets to build the fog analysis model.
[0085] It should be understood that the aforementioned weather data may include fog data under different seasons and weather conditions, such as fog concentration, humidity, and temperature data under different cities, times, and weather conditions. Weather data can be obtained from sources such as meteorological observation stations, meteorological forecast data, and historical meteorological data. The aforementioned fog impact data may include data on the impact of fog on images or videos caused by different weather or environments, such as image or video data under foggy conditions, including image or video data under different fog concentrations and visibility. The aforementioned defogging effect data may include image or video data processed by different defogging algorithms or methods, such as foggy image or video data processed using different defogging algorithms or methods, including the processing effects under different parameter settings.
[0086] Furthermore, in order to accurately analyze the fog data, the following may be included before step S40:
[0087] Obtain multiple sets of fog data from a preset fog database, as well as the corresponding impact data of the fog data, wherein the impact data is the data on the impact of fog on the vehicle glass;
[0088] Determine the data weights corresponding to multiple sets of fog data based on the impact data;
[0089] Based on the data weights, obtain the defogging modes corresponding to multiple sets of fog data;
[0090] A defogging analysis model is constructed based on multiple sets of fog data and the corresponding defogging modes.
[0091] It should be noted that data weights can be the degree of importance of each data point in the fog data. For example, temperature and humidity have a greater impact on fogging, so the weights of temperature and humidity data are set higher; other data with lower importance or less impact on fogging effect are set with lower weights.
[0092] It should be understood that the defogging strip device in this embodiment constructs a training set and a test set based on multiple sets of fog data from a preset fog database. The fog data may include weather data, fog impact data, and defogging effect data. A defogging analysis model is constructed based on the training set and the test set, referring to… Figure 3 , Figure 3 This is a schematic diagram of a defogging analysis model, where X1 and X2 are fog data, C1, C2 and C3 are different radial basis functions, W1 and W2 represent different weight parameters, which are used in the neural network model to adjust the model's learning and prediction, and Y is the output defogging mode.
[0093] This embodiment obtains candidate fog data corresponding to the region where the vehicle is currently located based on the regional information of the region. It then collects environmental information about the vehicle's environment to obtain current environmental information. Based on this current environmental information, it corrects the candidate fog data to obtain target fog data. The target fog data is then input into a pre-built defogging analysis model for defogging analysis, and the vehicle's defogging mode is adjusted based on the defogging analysis results. Because this embodiment corrects the candidate fog data corresponding to the vehicle's region based on the collected current environmental information, and inputs the corrected target fog data into the defogging analysis model for defogging analysis, it obtains a defogging mode that matches the vehicle's current driving scenario. This provides the vehicle with a suitable defogging strategy, ensuring defogging effectiveness in foggy conditions and improving vehicle defogging efficiency, while avoiding energy waste during the defogging process in sparsely foggy conditions.
[0094] refer to Figure 4 , Figure 4 This is a flowchart illustrating a second embodiment of a vehicle defogging adjustment method according to the present invention.
[0095] Based on the first embodiment described above, in this embodiment, step S10 may include:
[0096] Step S11: Locate the vehicle based on its current location information to determine the current location of the vehicle.
[0097] It should be noted that location information can be the vehicle's current geographical location information. Based on the location information, the region / city where the vehicle is currently located can be determined, thereby obtaining the climate or environmental characteristics of the region / city where the vehicle is located.
[0098] Step S12: Obtain the climate mapping table corresponding to the region based on the region information.
[0099] It should be noted that the climate mapping table can be a data table containing the mapping relationship between climate characteristics and time. The defogging adjustment equipment has pre-constructed corresponding mapping relationship tables based on different regions and the climate characteristics of the regions at different time points. For example, based on the climate mapping table of region A, it is determined that the climate characteristics of region A in summer are humid and have a large temperature difference, while the climate characteristics in winter are dry and have a small temperature difference.
[0100] In practical implementation, the defogging adjustment device obtains regional information corresponding to multiple regions, determines the regional climate corresponding to multiple regions based on the regional information, and determines the climate characteristics of each region at different times and seasons based on the regional climate. For example, region Y is a subtropical monsoon climate, with hot summers and mild winters, distinct seasons, simultaneous rain and heat, and a well-developed monsoon. Based on the climate characteristics of region Y in different seasons, a climate mapping table corresponding to region Y is constructed.
[0101] Step S13: Based on the current time, look up the climate mapping table to determine the current climate characteristics of the region.
[0102] It should be noted that the current time can be the time point when the vehicle is currently traveling. The current time can include the current day / night time and the current season. The climate characteristics of a region vary depending on the season and the time of day / night. The aforementioned climate characteristics can be the climate characteristics of the region where the vehicle is currently located at the current season and the current time of day / night.
[0103] For example, the defogging adjustment equipment determines that the current season is spring and the current day / night is night. Based on the current situation, it looks up the corresponding climate mapping table for the current region to determine the current climate characteristics of the region, which are rainy and have large temperature differences between day and night in spring.
[0104] Step S14: Obtain candidate fog data corresponding to the region based on the climate characteristics.
[0105] It should be understood that the defogging adjustment equipment determines the current climatic and environmental factors causing fogging in a region based on climatic characteristics, thereby determining candidate fog data. For example, the defogging adjustment equipment determines that the current climatic characteristics of region A are small diurnal temperature range and relatively dry climate. Therefore, it determines the candidate fog data for this region as low humidity, small temperature range, and less prone to fogging.
[0106] Furthermore, in order to accurately obtain candidate fog data corresponding to a region, step S14 above may include:
[0107] Step S141: Based on the climate characteristics, search a preset feature mapping table to determine the fog characteristics corresponding to the climate characteristics;
[0108] Step S142: Obtain the initial fog data corresponding to the fog features;
[0109] Step S143: Determine the current day / night information based on the current time;
[0110] Step S144: Based on the climate characteristics and the current day and night information, perform data cleaning on the initial fog data to obtain candidate fog data corresponding to the region.
[0111] It should be noted that the preset feature mapping table can be a pre-constructed data table containing multiple sets of mapping relationships between climate features and fog features. The aforementioned fog features can be the fog characteristics of the local climate in different seasons. The initial fog data package contains daytime and nighttime fog features for the current season. The aforementioned data cleaning can remove invalid fog data from the initial fog data. For example, if the vehicle is currently driving during the day, then the nighttime fog data in the initial fog data will be removed, retaining only the daytime fog data. Then, defogging adjustments will be performed based on the candidate fog data obtained after cleaning.
[0112] It should be understood that fog data varies under different day and night conditions. When the temperature difference is large during the day, the defogging adjustment equipment adopts a medium-power heating mode to moderately heat the glass surface and remove fog; when the temperature difference is small at night, a low-power heating mode is adopted to reduce energy consumption and improve energy conversion efficiency.
[0113] This embodiment locates the vehicle based on its current location information, determines the region where the vehicle is currently located, obtains a climate mapping table corresponding to the region based on the region information, searches the climate mapping table based on the current time, determines the climate characteristics corresponding to the region, and obtains candidate fog data corresponding to the region based on the climate characteristics. Because this embodiment determines the fog data during the vehicle's current driving process by locating the vehicle and then determining the climate characteristics corresponding to the vehicle's current location based on the current time, it achieves pre-collection of fog data, improving the efficiency of subsequently selecting an appropriate defogging mode for reasonable defogging.
[0114] refer to Figure 5 , Figure 5 This is a flowchart illustrating a third embodiment of a vehicle defogging adjustment method according to the present invention.
[0115] Based on the first embodiment described above, in this embodiment, step S30 includes:
[0116] Step S31: Collect environmental information from the vehicle's cabin to obtain cabin temperature and humidity information.
[0117] It should be noted that the current environmental information includes light intensity and ambient temperature and humidity information. The aforementioned cabin temperature and humidity information can be the temperature and humidity information inside the vehicle cabin. Since the temperature and humidity on both the inside and outside of the vehicle's glass walls affect the fogging effect, this embodiment collects environmental information from the vehicle cabin to obtain the temperature and humidity inside the cabin, thereby determining the temperature and humidity on the inside of the vehicle's glass.
[0118] Step S32: Compare the cabin temperature and humidity information with the ambient temperature and humidity information to obtain temperature and humidity difference information.
[0119] It should be noted that the temperature and humidity difference information can be the difference between the temperature and humidity inside the vehicle cabin and the temperature and humidity outside the vehicle environment. In other words, the temperature and humidity difference information can be the temperature difference and humidity difference between the inside and outside of the vehicle glass.
[0120] It should be understood that since the temperature difference and humidity difference on both sides of the glass will affect the fogging effect of the glass, this embodiment determines the temperature difference between the inside and outside of the vehicle glass by comparing the temperature inside the cabin with the temperature of the vehicle driving environment, and determines the humidity difference between the inside and outside of the vehicle glass by comparing the humidity inside the cabin with the humidity of the vehicle driving environment.
[0121] Step S33: Correct the candidate fog data based on the light intensity and the temperature and humidity difference information to obtain the target fog data.
[0122] It should be noted that the light intensity refers to the intensity of sunlight shining on the vehicle's windows while the vehicle is in motion.
[0123] It should be understood that this embodiment can employ different heating powers and heating times for defogging depending on the intensity of sunlight. For example, in strong sunlight, a high-power heating mode can be used to accelerate the heating of the glass surface, thereby removing fog more quickly. In weak sunlight, a low-power heating mode can be used to avoid energy waste and overheating of the glass.
[0124] It should be noted that the temperature difference refers to the difference between the interior and exterior temperatures of the vehicle. This embodiment adjusts the heating power and heating time based on the magnitude of the temperature difference to achieve the best defogging effect. For example, when the temperature difference is large, a higher power heating mode can be used to quickly remove fog from the window surface. Conversely, when the temperature difference is small, a lower power heating mode can be used to avoid overheating and energy waste.
[0125] It should be understood that humidity is a significant factor in fog formation. This embodiment allows for adjustment of heating power and heating time based on varying humidity levels to meet defogging needs under different humidity conditions. For example, in high humidity conditions, a higher power heating mode can be used to remove fog from the glass surface more quickly. Conversely, in low humidity conditions, a lower power heating mode can be used to avoid overheating and energy waste.
[0126] Furthermore, to improve the accuracy of the correction, step S33 above may include:
[0127] Step S331: Obtain the current environmental wind information of the region and the current driving status of the vehicle;
[0128] Step S332: Determine the airflow field information of the vehicle's onboard glass wall based on the current ambient wind information and the current driving state;
[0129] Step S333: Formulate a fog classification strategy based on the airflow field information, the light intensity, and the temperature and humidity difference information;
[0130] Step S334: Correct the candidate fog data based on the fog classification strategy to obtain the target fog data.
[0131] It should be noted that the current ambient wind information can include wind direction, wind speed, and wind intensity in the area where the vehicle is located. The current driving status can refer to the vehicle's current driving conditions, such as high-speed driving, slow driving, continuous driving, and intermittent driving. The aforementioned airflow field information can be related to the airflow field affecting each surface area of the target vehicle's glass, such as airflow rate, airflow direction, and airflow density.
[0132] It should be understood that the airflow field generated on the vehicle's glass surface also affects the formation and dissipation of fog on the windows. This embodiment adjusts the glass defogging power and time based on information such as airflow rate, airflow direction, and airflow density to achieve the best defogging effect. For example, when the airflow rate is low, a lower-power defogging mode can be used because the airflow rate slows down fog formation on the windows. Conversely, when the airflow rate is high, a higher-power defogging mode can be used to quickly remove fog from the window surface and prevent fog from reforming.
[0133] This embodiment collects environmental information from the vehicle's cabin to obtain cabin temperature and humidity information. This cabin temperature and humidity information is then compared with the ambient temperature and humidity information to obtain temperature and humidity difference information. Based on the light intensity and the temperature and humidity difference information, the candidate fog data is corrected to obtain target fog data. Because this embodiment determines the temperature and humidity difference between the vehicle's interior and exterior by comparing the cabin temperature and humidity information with the ambient temperature information, and accurately corrects the candidate fog data based on the light intensity and temperature and humidity difference information, the accuracy of data correction is improved, resulting in more precise target fog data.
[0134] Furthermore, this embodiment of the invention also proposes a storage medium storing a vehicle defogging adjustment program, which, when executed by a processor, implements the steps of the vehicle defogging adjustment method described above.
[0135] Since this storage medium adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought about by the technical solutions of the above embodiments, which will not be repeated here.
[0136] Reference Figure 6 , Figure 6 This is a structural block diagram of the first embodiment of the vehicle defogging adjustment device of the present invention.
[0137] like Figure 6 As shown, the vehicle defogging adjustment device proposed in this embodiment of the invention includes:
[0138] The region data acquisition module 10 is used to acquire candidate fog data corresponding to the region based on the region information of the current location of the vehicle;
[0139] The environmental information acquisition module 20 is used to collect environmental information about the environment in which the vehicle is located and obtain current environmental information.
[0140] Fog data correction module 30 is used to correct the candidate fog data according to the current environmental information to obtain target fog data;
[0141] The defogging analysis module 40 is used to input the target fog data into a pre-built defogging analysis model for defogging analysis, and adjust the defogging mode of the vehicle based on the defogging analysis results.
[0142] Furthermore, the region data acquisition module 10 is also used to locate the vehicle based on the vehicle's current location information and determine the region where the vehicle is currently located; to obtain the climate mapping table corresponding to the region based on the region's region information; to search the climate mapping table based on the current time and determine the climate characteristics corresponding to the region; and to obtain candidate fog data corresponding to the region based on the climate characteristics.
[0143] Furthermore, the regional data acquisition module 10 is also used to search a preset feature mapping table based on the climate features to determine the fog features corresponding to the climate features; acquire the initial fog data corresponding to the fog features; determine the current day and night information based on the current time; and perform data cleaning on the initial fog data based on the climate features and the current day and night information to obtain candidate fog data corresponding to the region.
[0144] Furthermore, the fog data correction module 30 is also used to collect environmental information of the vehicle's cabin to obtain cabin temperature and humidity information; compare the cabin temperature and humidity information with the ambient temperature and humidity information to obtain temperature and humidity difference information; and correct the candidate fog data based on the light intensity and the temperature and humidity difference information to obtain target fog data.
[0145] Furthermore, the fog data correction module 30 is also used to acquire the current environmental wind information of the region and the current driving status of the vehicle; determine the airflow field information of the vehicle's on-board glass wall based on the current environmental wind information and the current driving status; formulate a fog classification strategy based on the airflow field information, the light intensity and the temperature and humidity difference information; and correct the candidate fog data based on the fog classification strategy to obtain the target fog data.
[0146] Furthermore, the fog data correction module 30 is also used to acquire the vehicle's destination information and waypoint information; input the destination information and waypoint information into a pre-built driving route prediction model to obtain the vehicle's predicted route; determine the vehicle's transit areas based on the predicted route and the vehicle's current location; and correct the candidate fog data according to the region information and weather information of the transit areas to obtain the target fog data.
[0147] Furthermore, the vehicle defogger adjustment device also includes:
[0148] The model building module 50 is used to acquire multiple sets of fog data from a preset fog database, as well as the impact data corresponding to the fog data, wherein the impact data is the data on the impact of fog on the vehicle glass; determine the data weights corresponding to the multiple sets of fog data based on the impact data; acquire the defogging modes corresponding to the multiple sets of fog data based on the data weights; and construct a defogging analysis model based on the multiple sets of fog data and the defogging modes corresponding to the multiple sets of fog data.
[0149] This embodiment obtains candidate fog data corresponding to the region where the vehicle is currently located based on the regional information of the region. It then collects environmental information about the vehicle's environment to obtain current environmental information. Based on this current environmental information, it corrects the candidate fog data to obtain target fog data. The target fog data is then input into a pre-built defogging analysis model for defogging analysis, and the vehicle's defogging mode is adjusted based on the defogging analysis results. Because this embodiment corrects the candidate fog data corresponding to the vehicle's region based on the collected current environmental information, and inputs the corrected target fog data into the defogging analysis model for defogging analysis, it obtains a defogging mode that matches the vehicle's current driving scenario. This provides the vehicle with a suitable defogging strategy, ensuring defogging effectiveness in foggy conditions and improving vehicle defogging efficiency, while avoiding energy waste during the defogging process in sparsely foggy conditions.
[0150] It should be understood that the above are merely illustrative examples and do not constitute any limitation on the technical solutions of the present invention. In specific applications, those skilled in the art can make settings as needed, and the present invention does not impose any restrictions on this.
[0151] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of this invention. In practical applications, those skilled in the art can select some or all of the workflow to achieve the purpose of this embodiment according to actual needs, and no restrictions are imposed here.
[0152] In addition, for technical details not described in detail in this embodiment, please refer to the vehicle defogging adjustment method provided in any embodiment of the present invention, which will not be repeated here.
[0153] Furthermore, it should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.
[0154] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.
[0155] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory (ROM) / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.
[0156] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.
Claims
1. A method for adjusting vehicle defogging, characterized in that, The vehicle defogging adjustment method includes: The vehicle is located based on its current location information to determine its current location. Obtain the climate mapping table corresponding to the region based on the region information; Based on the current time, the climate mapping table is consulted to determine the current climate characteristics of the region. Based on the aforementioned climate characteristics, candidate fog data corresponding to the region are obtained; Environmental information is collected about the environment in which the vehicle is located to obtain current environmental information; The candidate fog data is corrected based on the current environmental information to obtain the target fog data; The target fog data is input into a pre-built defogging analysis model for defogging analysis, and the defogging mode of the vehicle is adjusted based on the defogging analysis results.
2. The vehicle defogging adjustment method as described in claim 1, characterized in that, The step of obtaining candidate fog data corresponding to the region based on the climate characteristics includes: Based on the climate characteristics, a preset feature mapping table is searched to determine the fog characteristics corresponding to the climate characteristics; Obtain the initial fog data corresponding to the fog features; Determine the current day / night information based on the current time; Based on the climate characteristics and the current day-night information, the initial fog data is cleaned to obtain candidate fog data corresponding to the region.
3. The vehicle defogging adjustment method as described in any one of claims 1 to 2, characterized in that, The current environmental information includes light intensity and ambient temperature and humidity information; the step of correcting the candidate fog data based on the current environmental information to obtain target fog data includes: Environmental information is collected from the vehicle's cabin to obtain cabin temperature and humidity information. The cabin temperature and humidity information is compared with the ambient temperature and humidity information to obtain temperature and humidity difference information; The candidate fog data is corrected based on the light intensity and the temperature and humidity difference information to obtain the target fog data.
4. The vehicle defogging adjustment method as described in claim 3, characterized in that, The step of correcting the candidate fog data based on the light intensity and the temperature and humidity difference information to obtain the target fog data includes: Obtain the current environmental wind information of the region, and the current driving status of the vehicle; The airflow field information of the vehicle's onboard glass wall is determined based on the current ambient wind information and the current driving status. A fog classification strategy is formulated based on the airflow field information, the light intensity, and the temperature and humidity difference information. The candidate fog data is corrected based on the fog classification strategy to obtain the target fog data.
5. The vehicle defogging adjustment method as described in any one of claims 1 to 2, characterized in that, The step of correcting the candidate fog data based on the current environmental information to obtain the target fog data includes: Obtain the destination information and waypoint information of the vehicle; The destination information and the waypoint information are input into a pre-built driving route prediction model to obtain the predicted route of the vehicle. The areas the vehicle will pass through are determined based on the predicted route and the area where the vehicle is currently located. The candidate fog data is corrected based on the regional information and weather information of the route area to obtain the target fog data.
6. The vehicle defogging adjustment method as described in any one of claims 1 to 2, characterized in that, Before inputting the target fog data into a pre-built defogging analysis model for defogging analysis, and adjusting the vehicle's defogging mode based on the defogging analysis results, the method further includes: Obtain multiple sets of fog data from a preset fog database, as well as the corresponding impact data of the fog data, wherein the impact data is the data on the impact of fog on the vehicle glass; Determine the data weights corresponding to multiple sets of fog data based on the impact data; Based on the data weights, obtain the defogging modes corresponding to multiple sets of fog data; A defogging analysis model is constructed based on multiple sets of fog data and the corresponding defogging modes.
7. A vehicle defogger adjustment device, characterized in that, The vehicle defogging adjustment device includes: The regional data acquisition module is used to locate the vehicle based on its current location information and determine the region where the vehicle is currently located; obtain a climate mapping table corresponding to the region based on the regional information; search the climate mapping table based on the current time to determine the climate characteristics corresponding to the region; and obtain candidate fog data corresponding to the region based on the climate characteristics. The environmental information acquisition module is used to collect environmental information about the environment in which the vehicle is located and obtain the current environmental information. A fog data correction module is used to correct the candidate fog data based on the current environmental information to obtain the target fog data; The defogging analysis module is used to input the target fog data into a pre-built defogging analysis model for defogging analysis, and adjust the vehicle's defogging mode based on the defogging analysis results.
8. A vehicle defogging adjustment device, characterized in that, The vehicle defogging adjustment device includes: a memory, a processor, and a vehicle defogging adjustment program stored in the memory and executable on the processor, the vehicle defogging adjustment program being configured to implement the vehicle defogging adjustment method as described in any one of claims 1 to 6.
9. A storage medium, characterized in that, The storage medium stores a vehicle defogging adjustment program, which, when executed by a processor, implements the vehicle defogging adjustment method as described in any one of claims 1 to 6.