Spraying control method of windscreen wiper system and vehicle

Abstract

The invention relates to a spraying control method of a windscreen wiper system and a vehicle, and aims to obtain water drop contact angle information and water film form information of a cleaning area of the windscreen wiper system through image recognition, so that objective and quantitative perception of the hydrophobic state of the surface of the windscreen is realized; the problem of low cleaning efficiency or waste of cleaning fluid caused by fixed spraying due to lack of objective and quantitative perception is solved. Secondly, the water drop contact angle information and the water film form information are fused to obtain a comprehensive hydrophobicity index, and the accuracy and robustness of evaluation under different environment working conditions are improved. And finally, spraying is dynamically controlled based on the hydrophobicity index, accurate on-demand control is achieved, and therefore the contradiction between low cleaning efficiency and waste of the cleaning liquid is fundamentally and synchronously solved, and unification of improving the cleaning efficiency and avoiding resource waste is achieved.

Description

Technical Field

[0001] This disclosure relates to the field of windshield wiper systems, and more particularly to a spray control method for a windshield wiper system and a vehicle. Background Technology

[0002] This section is intended to provide background or context for the embodiments of this disclosure as set forth in the claims. The description herein is not intended to be a prior art simply because it is included in this section.

[0003] The wiper system integrates a spray device for spraying glass washer fluid (commonly known as windshield washer fluid). In conjunction with the wiping action of the wipers, the spray device sprays the glass washer fluid to clean the windshield.

[0004] In related technologies, the spray control of windshield wiper systems usually adopts a fixed mode scheme, that is, the spray volume and spray time are usually fixed.

[0005] However, since the spray volume and spray time are fixed, there is a problem of low cleaning efficiency when the windshield is not clean enough, and a problem of wasting glass cleaning fluid when the windshield is clean enough. Summary of the Invention

[0006] To overcome or at least partially solve the above problems, this disclosure provides a spray control method for a windshield wiper system and a vehicle.

[0007] A first aspect of this disclosure provides a spray control method for a windshield wiper system, comprising: The image of the wiper system cleaning area of ​​the windshield is identified to obtain the contact state information between the liquid in the wiper system cleaning area and the windshield; Based on the contact state information, the hydrophobicity index of the cleaning area of ​​the wiper system is determined; The spray action of the wiper system is controlled based on the hydrophobicity index.

[0008] Based on the same inventive concept, a second aspect of the present disclosure provides a vehicle including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method as described in the first aspect.

[0009] The technical solution provided in this disclosure has the following advantages: By acquiring water droplet contact angle and water film morphology information of the wiper system's cleaning area on the windshield through image recognition, an objective and quantitative perception of the windshield's hydrophobic state is achieved. This solves the problem of low cleaning efficiency or wasted cleaning fluid caused by fixed spraying due to a lack of objective and quantitative perception. Secondly, by fusing the water droplet contact angle and water film morphology information, a comprehensive hydrophobicity index is obtained, improving the accuracy and robustness of assessments under different environmental conditions. Finally, dynamic spraying control based on the hydrophobicity index achieves precise, on-demand control, fundamentally resolving the contradiction between low cleaning efficiency and wasted cleaning fluid, and achieving a balance between improving cleaning efficiency and avoiding resource waste. Attached Figure Description

[0010] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0011] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram of an application scenario of the spray control method for a wiper system provided in an exemplary embodiment of this disclosure; Figure 2 This is a schematic flowchart of a spray control method for a wiper system provided in an exemplary embodiment of the present disclosure; Figure 3 This is a schematic diagram of a spray control device for a wiper system provided in an exemplary embodiment of the present disclosure; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an exemplary embodiment of this disclosure; Figure 5 This is a schematic diagram of the structure of a vehicle provided in an exemplary embodiment of this disclosure. Detailed Implementation

[0013] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the type, scope of use, and usage scenarios of the image information of the wiper system cleaning area of ​​the windshield involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0014] As an example, before implementing the technical solution, a prompt message is sent to the user to explicitly inform them that this technical solution requires acquiring and using image information of the wiper system's cleaned area on the windshield. This allows the user to autonomously choose, based on the prompt message, whether to provide the wiper system's cleaned area image information to the software or hardware such as electronic devices, applications, servers, or storage media performing the operation of this disclosed technical solution.

[0015] As an optional but non-limiting implementation, the prompt message can be sent to the user in the form of a pop-up window, which can display the prompt message in text format. In addition, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide the electronic device with an image of the windshield wiper system's cleaning area.

[0016] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this disclosure.

[0017] It is understood that the image data of the windshield wiper system cleaning area involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and related provisions.

[0018] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0019] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0020] To address the issues of low cleaning efficiency or wasted windshield washer fluid due to fixed spray volume and spray time, several spray control schemes for wiper systems exist in related technologies: In a spray control scheme for a wiper system provided by related technologies, the location and type of foreign objects on the windshield are obtained through image recognition. The adjustable-angle sprayer is controlled to spray cleaning fluid only onto the target area, and then the wiper removes the foreign objects. This achieves on-demand spraying, improves cleaning efficiency, and reduces resource consumption.

[0021] However, the inventors of this disclosure have discovered the following problems: When the hydrophobic coating (such as a fluorinated coating) on ​​the windshield surface is worn or even fails, the wear and failure of the hydrophobic coating significantly reduces the windshield's hydrophobicity, making it difficult for water droplets to form beads. After the wipers wipe, a thin layer of water, i.e., a water film residue, remains on the glass and is not completely removed, which can affect the driver's vision. Therefore, it is necessary to increase the spray volume and / or spraying time to ensure cleaning effectiveness. However, the above solution can only identify foreign objects on the windshield and cannot effectively identify wear and failure of the hydrophobic coating. Therefore, it cannot achieve on-demand spraying for cases of hydrophobic coating wear and failure, resulting in poor cleaning effect.

[0022] When an oil film forms on the windshield surface (where an oil film refers to an organic film formed by pollutants such as vehicle exhaust, asphalt volatiles, and insect carcasses on the windshield surface), the oil film significantly reduces the windshield's hydrophobicity, making it difficult for water droplets to form beads. After the wipers wipe, a thin layer of water residue remains on the glass, which cannot be completely removed and affects the driver's vision. Therefore, it is necessary to increase the spray volume and / or spraying time to ensure cleaning effectiveness. The oil film is usually thin, nearly transparent, and uniformly adhered to the windshield surface. The above methods are difficult to effectively identify the oil film. Therefore, for situations where an oil film forms on the windshield surface, on-demand spraying cannot be achieved, resulting in poor cleaning performance.

[0023] The above solution relies on adjustable-angle water sprayers, which requires additional equipment on the vehicle, increasing costs and raising the implementation threshold. Furthermore, adjustable-angle water sprayers are relatively sophisticated machines with a high failure rate and poor stability.

[0024] In another spray control scheme for a wiper system provided by related technologies, a time threshold is set to determine whether the interval between two starts exceeds the threshold. If the threshold is exceeded, the water spray device is controlled to spray water before the wiper arm is driven, so as to reduce the frequency of ineffective water spraying and improve resource utilization.

[0025] However, the inventors of this disclosure have discovered the following problems: This solution is out of touch with the actual cleaning needs of the windshield. The necessity of spraying depends on the real-time dirt level and condition of the windshield. This solution is too one-sided to decide whether to clean based solely on the length of the interval between two activations.

[0026] For example, in some scenarios, vehicles may pass through dirty road sections in a short period of time (such as passing through multiple mud-splattered areas in succession), at which point the glass gets dirty quickly, and this solution will delay cleaning, seriously impairing driving safety.

[0027] For example, in other scenarios, vehicles may continuously drive through relatively clean road sections for an extended period of time, during which the glass becomes dirty slowly. This solution would over-clean, resulting in a waste of resources. At the same time, at high speeds, excessive cleaning fluid may be blown into the side windows by airflow, creating secondary safety hazards.

[0028] To overcome the above problems, this disclosure provides a spray control method for a windshield wiper system, and various non-limiting embodiments of this disclosure are described in detail below.

[0029] See Figure 1 This is a schematic diagram of an application scenario of the spray control method for a wiper system provided in an exemplary embodiment of this disclosure.

[0030] This application scenario includes a camera device 110, an in-vehicle terminal 120, a server 130, and a windshield wiper system 140.

[0031] The camera device 110, vehicle terminal 120, server 130 and wiper system 140 can be connected via wired or wireless communication networks to achieve data interaction.

[0032] The camera device 110 includes any camera capable of capturing images of the area cleaned by the windshield wiper system, such as a dashcam camera or a driver assistance system camera.

[0033] The vehicle-mounted terminal 120 is a terminal installed on the vehicle, possessing data acquisition and processing capabilities. It can be a vehicle controller or a central processing unit in an autonomous driving system. The vehicle-mounted terminal 110 is capable of acquiring and processing relevant information. In this embodiment, the vehicle-mounted terminal 110 is the electronic device that ultimately controls the vehicle.

[0034] Server 130 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0035] The wiper system 140 includes a spray device 142, which is used to spray windshield washer fluid (commonly known as glass cleaner).

[0036] In some exemplary embodiments, the vehicle terminal 120 receives an image of the wiper system cleaning area of ​​the windshield sent by the camera device 110, the image being captured by the camera device 110. The vehicle terminal 120 identifies the image of the wiper system cleaning area of ​​the windshield to obtain contact state information between the liquid in the wiper system cleaning area and the windshield. The vehicle terminal 120 fuses the contact state information between the liquid and the windshield to obtain a hydrophobicity index of the wiper system cleaning area. Based on the hydrophobicity index, the vehicle terminal 120 controls the spraying action of the spray device 142 in the wiper system 140.

[0037] In some exemplary embodiments, the vehicle terminal 120 receives an image of the wiper system cleaning area of ​​the windshield sent by the camera device 110, the image being captured by the camera device 110. The vehicle terminal 120 sends the image of the wiper system cleaning area of ​​the windshield to the server 130 and receives a hydrophobicity index sent by the server 130. This hydrophobicity index is obtained as follows: the server 130 identifies the image of the wiper system cleaning area of ​​the windshield to obtain contact state information between the liquid in the wiper system cleaning area and the windshield. The server 130 fuses the contact state information between the liquid and the windshield to obtain the hydrophobicity index of the wiper system cleaning area. Based on the hydrophobicity index, the vehicle terminal 120 controls the spraying action of the spray device 142 in the wiper system 140.

[0038] The following is combined with Figure 1 The above application scenarios are used to describe the spray control scheme of the wiper system according to exemplary embodiments of this disclosure. It should be noted that the above application scenarios are shown only to facilitate understanding of the spirit and principles of this disclosure, and the embodiments of this disclosure are not limited in any way. Rather, the embodiments of this disclosure can be applied to any applicable scenario.

[0039] refer to Figure 2 This is a schematic flowchart of a first method for spray control of a wiper system provided in an exemplary embodiment of the present disclosure.

[0040] The spray control method for a windshield wiper system includes the following steps: Step S210: Recognize the image of the wiper system cleaning area of ​​the windshield to obtain the contact state information between the liquid in the wiper system cleaning area and the windshield.

[0041] The following section will describe how to acquire images of the wiper system's cleaned area on the windshield.

[0042] In this disclosure, the term "windshield" refers to a transparent protective device installed on a vehicle, which typically includes a front windshield (commonly known as a front window), a rear windshield (commonly known as a rear window), and side windshields (commonly known as side windows).

[0043] The wiper system as described in this disclosure includes a drive motor, wiper blades, and a spray device for spraying windshield washer fluid (commonly known as windshield washer fluid).

[0044] A wiper system is usually installed on the front windshield, and wiper systems can also be installed on the rear windshield and side windshields.

[0045] The wiper system cleaning area of ​​the windshield refers to the continuous area swept by the wiper blades of the wiper system during their working stroke on the outer surface of the windshield. This area is the target area for evaluating the hydrophobicity of the windshield surface and performing spray cleaning in subsequent steps of this disclosure.

[0046] The following section describes the hardware for acquiring images of the wiper system-cleaned areas of the windshield: In some exemplary embodiments, an existing camera in the vehicle that can capture images of the area cleaned by the windshield wiper system can be reused.

[0047] As an example, images of the wiper system cleaning area of ​​the windshield are captured using at least one of the following cameras: Cameras in dashcams and driver assistance systems.

[0048] A dashcam is a device that records images and sounds during a vehicle's journey. After installation, a dashcam can record video and audio of the entire driving process.

[0049] Driver assistance systems are active safety technologies that use onboard sensors such as millimeter-wave radar, cameras, and lidar, combined with navigation data, to achieve environmental perception.

[0050] In the above exemplary embodiments, the existing camera in the vehicle is reused to capture the area cleaned by the windshield wiper system, eliminating the need to install additional camera equipment, reducing costs, lowering the hardware requirements for implementing this disclosure, and improving the adaptability of this disclosure.

[0051] In some exemplary embodiments, a camera may be added inside the vehicle specifically for capturing images of the area cleaned by the windshield wipers.

[0052] As an example, an additional camera specifically designed to capture the wiper system cleaning area of ​​the windshield can be installed near the rearview mirror inside the vehicle, facing the wiper system cleaning area on the outer surface of the windshield.

[0053] In the above exemplary embodiment, a dedicated camera is added to photograph the wiper system cleaning area of ​​the windshield. On the one hand, this avoids affecting the function of the existing cameras in the vehicle. On the other hand, the parameters of the dedicated camera can be configured according to the needs of photographing the wiper system cleaning area of ​​the windshield, thereby improving the recognition accuracy in subsequent steps.

[0054] The camera's parameters will be introduced below: In some exemplary embodiments, considering the captured image of the wiper system cleaning area of ​​the windshield, information on the contact state between the liquid in the wiper system cleaning area and the windshield is obtained. Therefore, there are certain requirements for the resolution and frame rate of the camera that captures the image of the wiper system cleaning area of ​​the windshield.

[0055] As an example, the camera capturing images of the wiper system cleaning area of ​​the windshield has a resolution greater than a pixel threshold; the camera capturing images of the wiper system cleaning area of ​​the windshield has a frame rate greater than a frame rate threshold.

[0056] The pixel threshold can be configured based on the average distance between the camera and the windshield wiper system's cleaning area; the frame rate threshold can be configured based on the wiper blade's wiping speed.

[0057] In the above exemplary embodiments, the hardware for acquiring images of the wiper system clean area of ​​the windshield was described. The triggering conditions for acquiring images of the wiper system clean area of ​​the windshield will be described below: In some exemplary embodiments, before identifying the image of the wiper system cleaning area of ​​the windshield to obtain contact state information between the liquid in the wiper system cleaning area and the windshield, the method further includes: In response to a wiper system trigger signal, an image of the wiper system-cleaned area is acquired.

[0058] As an example, when the driver operates the wiper stalk, a wiper system trigger signal is generated.

[0059] The windshield wiper stalk is usually located on the right side of the steering wheel. It is the physical operating component that controls the vehicle's windshield wipers, and its main functions include operating the wipers and cleaning the windshield.

[0060] As an example, when the driver activates the windshield wiper system via the central control screen, a windshield wiper system trigger signal is generated.

[0061] Among them, you can click the virtual icon representing the wiper system on the central control screen.

[0062] As an example, when the vehicle starts, a signal is generated to trigger the windshield wiper system.

[0063] Specifically, when the vehicle is started (e.g., when the vehicle is powered on or the engine is started), a wiper system trigger signal is automatically generated to activate the wiper system, check whether the wiper system is functioning properly, and clean the windshield.

[0064] As an example, a wiper system trigger signal is generated based on a preset cycle.

[0065] During vehicle operation, a wiper system trigger signal is automatically generated at a low frequency (e.g., every 30 minutes) to activate the wiper system and clean the windshield.

[0066] The preset period value can be set according to the specific application scenario. The smaller the preset period value, the higher the efficiency; the larger the preset period value, the lower the cost. Therefore, if there is a higher demand for improving efficiency, a smaller preset period value can be configured; if there is a higher demand for reducing costs, a larger preset period value can be configured.

[0067] In the above exemplary embodiments, a method for acquiring images of the wiper system cleaning area of ​​the windshield was described. Below, a method for identifying images of the wiper system cleaning area of ​​the windshield to obtain contact state information between the liquid in the wiper system cleaning area and the windshield will be described: In some exemplary embodiments, the step of recognizing an image of the wiper system cleaning area of ​​the windshield to obtain contact state information between the liquid in the wiper system cleaning area and the windshield includes: A first image of the area cleaned by the wiper system between spraying and wiping operations; The first image is identified to obtain the water droplet contact angle information; A second image of the area cleaned by the wiper system after the wiper system has sprayed and wiped; The second image is identified to obtain water film morphology information; The contact state information includes the water droplet contact angle information and the water film morphology information.

[0068] Among them, during the process of the wiper system spraying and wiping, two key time periods are selected: the first time period from the end of spraying to the beginning of wiping, and the second time period from the end of wiping to the beginning of the next spraying.

[0069] In the first time period (i.e., after spraying and before wiping), the liquid on the windshield (sprayed glass cleaner, commonly known as glass water) appears as water droplets. Therefore, the first image of the first time period is selected from the previously collected images to identify the water droplet contact angle information.

[0070] In the second time period (i.e., from the end of the wiping process to the next spray), the liquid on the windshield (sprayed glass cleaner, commonly known as windshield washer fluid) appears as a water film. Therefore, the second image from the second time period is selected from the previously collected images to identify the water film morphology information.

[0071] The images collected are image sequences (e.g., videos or a set of image frames arranged in chronological order). The first image can be a set of image frames or a single image frame, and the second image is a set of image frames arranged in chronological order.

[0072] In the above exemplary embodiments, the timing of image acquisition is clearly defined. Acquiring the first image between spraying and scraping ensures that the analyzed water droplets are in an initial stable state before being cleaned, avoiding scraping interference and allowing the contact angle measurement results to directly reflect the original impact of the contaminants. Acquiring the second image after spraying and scraping accurately captures the morphology of the residual water film after cleaning, thereby directly assessing the actual cleaning effect. The acquisition of these two types of information provides a reliable data foundation for subsequent accurate evaluation.

[0073] In the above exemplary embodiments, an image for identifying the contact state information between the liquid and the windshield was described. The method for identifying the contact state information between the liquid and the windshield will be described below: Contact status information includes water droplet contact angle information and water film morphology information.

[0074] First, we will introduce the method for identifying the water droplet contact angle information: The water droplet contact angle is a physical quantity that measures the degree to which a water droplet wets the windshield surface; specifically, it refers to the angle between the solid (windshield) and liquid (water droplet) interfaces at the point of contact. A larger water droplet contact angle indicates stronger hydrophobicity of the windshield surface. This disclosure uses image analysis technology to calculate the contact angle of water droplets on the windshield in real time, serving as a key indicator for hydrophobicity assessment.

[0075] In some exemplary embodiments, the step of identifying the first image to obtain water droplet contact angle information includes: Identify the water droplets in the first image and obtain the outline of the water droplets; The water droplet's outline is fitted to a preset curve to obtain the water droplet's contact angle information.

[0076] In some exemplary embodiments, before identifying water droplets in the first image and obtaining the outline of the water droplets, the method further includes: The first image is preprocessed.

[0077] As an example, preprocessing includes noise reduction.

[0078] Among these methods, Gaussian filtering or median filtering algorithms can be used to eliminate noise in the image.

[0079] As an example, preprocessing includes contrast enhancement.

[0080] Among them, histogram equalization or adaptive contrast limiting algorithms are used to enhance the contrast between the water droplet edge and the windshield background.

[0081] As an example, preprocessing includes delineating the region of interest.

[0082] The processing scope is focused on the stable analysis sub-region within the wiper system's cleaning area, excluding interfering areas such as wiper blades.

[0083] In some exemplary embodiments, identifying water droplets in the first image and obtaining the outline of the water droplets includes: Convert the first image into a binary image; Connectivity analysis is performed on the binary image to obtain the contour lines of the connected regions, which are used as the contour lines of the water droplets.

[0084] As an example, the first image is converted into a black-and-white binary image based on adaptive thresholding methods (such as Otsu's method, Otsu's method) or edge detection methods (such as the Canny operator), where the white parts represent water droplet regions.

[0085] As an example, the connected component analysis algorithm identifies all the individual white region outlines, with each outline corresponding to a water droplet.

[0086] As an example, after identifying the outline of the water droplets, based on preset area thresholds and roundness, excessively small outlines (which may be water mist, noise points, or non-droplet contaminants) are filtered out, retaining valid water droplets for contact angle calculation, thus improving the accuracy of water droplet contact angle information.

[0087] In some exemplary embodiments, fitting the outline of the water droplet to a preset curve to obtain the water droplet contact angle information includes: The water droplet's outline is fitted with the preset curve using nonlinear least squares fitting to obtain the water droplet's contact angle information.

[0088] In this process, the extracted contour of the actual water droplet is fitted with a set of pre-set theoretical curves using nonlinear least squares fitting. The contact angle corresponding to the theoretical curve with the highest goodness of fit is determined as the contact angle of the water droplet.

[0089] As an example, the preset curve is a model curve based on the Young-Laplace equation.

[0090] The Young-Laplace model curves are not measured directly from a single image, but rather are a series of theoretical droplet profiles pre-calculated based on physical laws. This serves as a benchmark or template library for matching and comparison. The Young-Laplace equations describe the balance between the internal pressure difference (caused by surface tension) and the interface curvature of a stationary droplet (such as a water droplet) on a solid surface. The core parameters of the equations are the surface tension coefficient and the contact angle. A corresponding theoretical profile curve is generated for each contact angle value and stored.

[0091] In the above exemplary embodiments, robust extraction of the water droplet profile is achieved through binarization and connected component analysis, effectively separating the windshield background from the water droplet target. Nonlinear least squares fitting ensures the accuracy and stability of the process from profile to contact angle.

[0092] In extreme cases, as long as there is a single water droplet on the wiper system's cleaning area of ​​the windshield, the water droplet's contact angle information can be obtained, thus providing an extremely high tolerance for error.

[0093] To further improve the accuracy of water droplet contact angle information, this disclosure identifies water droplet contact angle information of multiple water droplets, performs statistical processing on the water droplet contact angle information of multiple water droplets, and obtains average contact angle information and contact angle distribution uniformity information (e.g., standard deviation).

[0094] As an example, for all the selected valid water droplets in the first image (e.g., the number is between 5 and 20), calculate the contact angle of each water droplet, and calculate the mean and standard deviation of the contact angles of multiple water droplets.

[0095] In the above exemplary embodiments, a fitting algorithm based on a physical model of water droplet shape (such as the Young-Laplace equation) is introduced, which can more accurately handle asymmetrical or deformed water droplets caused by gravity and glass tilt in reality, thereby obtaining a higher precision contact angle value.

[0096] The following will introduce the methods for identifying water film morphology information: Among them, water film morphology refers to the shape of the water film formed on the windshield surface after the wiper blade completes one wiping action.

[0097] In some exemplary embodiments, the step of recognizing the second image to obtain water film morphology information includes: Identify the water film area in the second image, and obtain the water film coverage rate based on the area of ​​the water film area and the area of ​​the wiper system cleaning area; Based on the multiple water film coverage rates corresponding to multiple image frames arranged in chronological order in the second image, the average rate of decrease of the multiple water film coverage rates over time is determined as the water film rupture rate. The water film morphology information includes the water film coverage and the water film rupture rate.

[0098] Identifying the water film morphology is a crucial step in assessing the hydrophobicity of windshield surfaces, particularly in detecting oil film contamination and hydrophobic coating failure. Unlike static analysis of water droplet contact angle, water film morphology analysis focuses more on the residual behavior of water after dynamic wiping.

[0099] As an example, after the wiper blades complete a single wiping motion, a very short delay (e.g., 100 to 300 milliseconds) is made to allow the water film flow to initially stabilize before image acquisition is triggered. To analyze the dynamic evolution of the water film, a short sequence of images (e.g., three frames taken at 0.3 seconds, 1.0 seconds, and 2.0 seconds after the wiping is completed) is acquired, rather than a single image.

[0100] In some exemplary embodiments, before identifying the second image to obtain water film morphology information, the method further includes: The second image is preprocessed.

[0101] As an example, preprocessing includes noise reduction.

[0102] Among these methods, Gaussian filtering or median filtering algorithms can be used to eliminate noise in the image.

[0103] As an example, preprocessing includes contrast enhancement.

[0104] Among them, histogram equalization or adaptive contrast limiting algorithms are used to enhance the contrast between the water film edge and the dry area of ​​the windshield.

[0105] As an example, preprocessing includes delineating the region of interest.

[0106] The processing scope is focused on the stable analysis sub-region within the wiper system's cleaning area, excluding interfering areas such as wiper blades.

[0107] In some exemplary embodiments, identifying the water film region in the second image and obtaining the water film coverage rate based on the area of ​​the water film region and the area of ​​the wiper system cleaning area includes: The second image is compared with a preset dry windshield image to obtain a difference image; Convert the difference image into a binary image; The binary image is subjected to noise removal, and adjacent regions of the noise-removed binary image are connected to obtain the water film region. The water film coverage rate is obtained by calculating the ratio between the area of ​​the water film region and the area of ​​the wiper system cleaning region.

[0108] As an example, a difference image can be converted into a black-and-white binary image based on adaptive thresholding methods (such as Otsu's method, Otsu's method) or edge detection methods (such as the Canny operator), where the white portion represents the water film region.

[0109] As an example, morphological opening and closing operations are used to eliminate noise points and connect adjacent regions to obtain an accurate water film region.

[0110] As an example, the formula for calculating water film coverage is as follows: Water film coverage = (Area of ​​water film area / Area of ​​wiper system cleaning area) × 100%.

[0111] The higher the water film coverage, the worse the hydrophobicity of the glass.

[0112] In the exemplary embodiments described above, by comparing the current image with a reference image in a clean and dry state, minute changes in reflectivity or texture caused by the presence of a water film can be detected with high sensitivity, effectively overcoming interference from complex backgrounds and changes in illumination. Combined with subsequent noise reduction and region connection processing, continuous and complete water film regions can be accurately segmented, thereby providing accurate pixel-level baseline data for calculating water film coverage and rupture velocity. This provides strong robustness, ensuring high-precision water film morphology analysis.

[0113] In some exemplary embodiments, determining the water film rupture rate over time based on multiple water film coverage rates corresponding to multiple image frames arranged in chronological order in the second image includes: Calculate the water film coverage of each frame in the multiple image frames arranged in chronological order in the second image; The average rate of decrease in the coverage of the multiple water films over time is calculated as the water film rupture rate.

[0114] Among them, a faster water film rupture rate, that is, the water film breaks down quickly and shrinks into discrete small water droplets, indicates strong hydrophobicity; a slower water film rupture rate, that is, the water film spreads evenly and dissipates slowly, indicates weak hydrophobicity and the possible presence of an oil film.

[0115] In the exemplary embodiments described above, the water film morphology information is precisely defined and quantified. Specifically, by introducing the dynamic parameter of water film rupture rate, the speed of water film contraction and rupture can be quantified to characterize the hydrophobicity of the windshield surface. Combining static coverage with dynamic rupture rate enhances the evaluation dimensions of water film morphology. This improves the detection and differentiation capabilities for subtle changes in the glass surface condition (especially the effectiveness of the hydrophobic coating and minor oil films).

[0116] Step S220: Based on the contact state information, determine the hydrophobicity index of the cleaning area of ​​the wiper system.

[0117] The hydrophobicity index is used to characterize the ability of a windshield surface to resist liquid wetting. For windshields, high hydrophobicity means that water droplets form a large contact angle (usually greater than 90 degrees) with the glass surface, and the water droplets are spherical and easily roll off; low hydrophobicity means that the contact angle is smaller, and the water droplets easily spread into a film.

[0118] The hydrophobicity index is used to quantify the real-time hydrophobicity of windshield surfaces.

[0119] In some exemplary embodiments, determining the hydrophobicity index of the wiper system cleaning area based on the contact state information includes: The water droplet contact angle information is mapped to a first standardized score, and the water film morphology information is mapped to a second standardized score; A first confidence level is determined for the water droplet contact angle information, and a first weight is determined for the first standardized score based on the first confidence level. A second confidence level is determined for the water film morphology information, and a second weight is determined for the second standardized score based on the second confidence level. The hydrophobicity index is obtained by weighting the first standardized score, the first weight, the second standardized score, and the second weight.

[0120] As an example, mapping the water droplet contact angle information to a first standardized score includes: Based on historical and / or experimental data, a mapping is established between water droplet contact angle information and the first standardized score.

[0121] As an example, mapping the water film morphology information to a second standardized score includes: Based on historical and / or experimental data, a mapping is established between water film morphology information and a second standardized score.

[0122] As an example, determining the first confidence level of the water droplet contact angle information includes: A first confidence level is determined based on the number and clarity of the water droplets to determine the water droplet contact angle information.

[0123] The greater the quantity and the higher the clarity, the higher the first confidence level.

[0124] As an example, determining the second confidence level of the water film morphology information includes: A second confidence level for the water film morphology information is determined based on the clarity of the water film.

[0125] The higher the resolution, the higher the second confidence level.

[0126] As an example, the hydrophobicity index is a normalized value between 0 and 100%.

[0127] In the above exemplary embodiments, the hydrophobicity index of the wiper system cleaning area is obtained through logical judgment rules. However, this disclosure is not limited to this. In some exemplary embodiments, the hydrophobicity index of the wiper system cleaning area can be obtained through a regression model. In some exemplary embodiments, determining the hydrophobicity index of the wiper system cleaning area based on the contact state information includes: The water droplet contact angle information and the water film morphology information are input into a preset hydrophobicity index model to obtain the hydrophobicity index output by the hydrophobicity index model. The hydrophobicity index model is constructed and trained based on a regression model framework.

[0128] The hydrophobicity index model in this disclosure will be introduced below: As an example, the hydrophobicity index model employs a fully connected feedforward neural network, also known as a multilayer perceptron.

[0129] The hydrophobicity index model includes an input layer module, a hidden layer module, and an output layer module.

[0130] The input layer module contains a number of neurons equal to the number of input features.

[0131] The input data includes water droplet contact angle information (including average contact angle information and contact angle distribution uniformity information) and water film morphology information (including water film coverage and water film rupture velocity).

[0132] The hidden layer module contains one or more hidden layers, such as 1 to 2 layers. Each layer contains a number of neurons (e.g., 8 or 16), the number of which is determined through hyperparameter tuning.

[0133] Each hidden layer neuron is followed by a non-linear activation function, such as the ReLU function, to introduce non-linear transformation capabilities, enabling the model to learn complex feature relationships.

[0134] The hidden layer neurons are fully connected. That is, every neuron in the previous layer is connected to every neuron in the next layer. Each connection has a weight to be trained, and each neuron also has a bias to be trained.

[0135] The output layer module contains only one neuron, which outputs the final hydrophobicity exponent. The activation function uses the sigmoid function, compressing the neuron's output to the (0, 1) interval, which is naturally mapped to the exponent range of 0 to 100% by multiplying by 100. The output layer module is fully connected to the last hidden layer.

[0136] As an example, the construction of training data: Data collection: Various real-world scenarios were simulated on a large number of experimental vehicles (such as new glass, glass coated with hydrophobic coatings of different states, and glass covered with oil film / stains of different degrees), and under different environments (sunny days, rainy days, and nighttime).

[0137] Feature extraction: Input data is collected and calculated synchronously in each scenario.

[0138] True value annotation: A standard true value for the hydrophobicity index is manually determined for each scenario by professional technicians or by using high-precision instruments (such as laboratory contact angle measuring instruments combined with cleanliness assessment).

[0139] Dataset partitioning: Randomly divide all collected data pairs into training set (e.g., 70%, for model learning), validation set (e.g., 15%, for parameter tuning and preventing overfitting), and test set (e.g., 15%, for final model performance evaluation).

[0140] As an example, training a hydrophobicity index model: Initialization: Randomly initialize all weights and biases of the hydrophobicity index model.

[0141] Forward propagation: Take a batch of data from the training set, input it into the network, and pass it through the input layer, hidden layer (with weighted summation and ReLU activation), and output layer (with weighted summation and Sigmoid activation) to obtain the predicted output (predicted value) of the hydrophobicity index model.

[0142] Loss calculation: Calculate the difference between the predicted value and the true value, i.e., the loss.

[0143] Backpropagation: Using automatic differentiation, starting from the output layer, the gradient of the loss function with respect to each weight and bias parameter is calculated in reverse.

[0144] Parameter update: All parameters are updated based on the gradient using an optimization algorithm. For example, the Adam optimizer can be used, which combines momentum and an adaptive learning rate.

[0145] Iterative loop: Repeat the steps from forward propagation to parameter update described above until all training data has been traversed; this is called one training cycle. The hydrophobicity index model requires multiple training cycles until the loss function value no longer decreases significantly on the validation set.

[0146] Final evaluation: The performance of the trained hydrophobicity index model is evaluated using a test set that has never been used for training (e.g., calculating the correlation coefficient between predicted and true values, and the mean absolute error) to confirm the generalization ability of the hydrophobicity index model.

[0147] In the exemplary embodiments described above, adaptive weighted fusion is performed based on confidence levels, taking into account the varying reliability of different information sources under different operating conditions (e.g., low contact angle confidence in heavy rain, while image quality affects water film confidence in low light). By dynamically adjusting the weights, more reliable data sources can be automatically trusted in different scenarios, resulting in a more robust and accurate comprehensive hydrophobicity index. This effectively solves the problem of misjudgment caused by the failure of a single information source or noise interference, significantly improving applicability and reliability in complex real-world environments.

[0148] Step S230: Based on the hydrophobicity index, control the spray action of the wiper system.

[0149] The spray parameters of the wiper system include spray volume and / or spray time.

[0150] In some exemplary embodiments, controlling the spray action of the wiper system based on the hydrophobicity index includes: Based on the mapping relationship between the hydrophobicity index and multiple preset spray control levels, the target spray parameters are determined. A spray control signal is generated based on the target spray parameters, and the spray volume and / or spray time of the wiper system are controlled based on the spray control signal.

[0151] The mapping relationship is configured such that: the higher the hydrophobicity index, the lower the corresponding spray volume and / or the shorter the spray time; the lower the hydrophobicity index, the higher the corresponding spray volume and / or the longer the spray time.

[0152] As an example, a "hydrophobicity index - spray parameters" lookup table is pre-stored in the vehicle control unit. This table is based on a large amount of bench and real vehicle test data to ensure good cleaning results under every working condition.

[0153] As an example, the hydrophobicity index is a normalized value between 0 and 100%.

[0154] As an example, if the hydrophobicity index is greater than or equal to 70%, the spray volume coefficient is 0.3 to 0.6, and the spray time is 0.3s, then the spray is minimized and only a lubricating film is formed. If the hydrophobicity index is greater than or equal to 10% and less than 70%, the spray volume coefficient is 0.7 to 1 (standard spray volume), and the spray time is 0.6 seconds. In this case, standard spraying and routine cleaning are performed. If the hydrophobicity index is greater than or equal to 20% and less than 40%, the spray volume coefficient is 1.2 to 1.5 and the spraying time is 0.9s. In this case, the spraying should be intensified to deal with mild pollution. If the hydrophobicity index is less than 20%, the spray volume coefficient is 1.8 to 2.5, and the spraying time is 1.2s. At this time, the maximum spraying is performed to powerfully remove the oil film.

[0155] Wherein, spray volume = standard spray volume × spray volume coefficient.

[0156] As an example, the amount of glass cleaning fluid sprayed per unit time can be controlled by adjusting the operating voltage of the washing pump, the PWM duty cycle, or the valve opening.

[0157] As an example, the spraying time can be controlled by controlling the energization duration of the washing pump or solenoid valve.

[0158] In the exemplary embodiments described above, a clear and structured mapping is established between the hydrophobicity index and control actions. Continuous index values ​​are transformed into specific target spray parameters through table lookups or mapping relationships, enabling precise execution of intelligent decisions. Clearly controlling the spray volume and / or spray time, encompassing the two core control dimensions of flow rate and duration, provides a direct means to achieve fine-grained control ranging from enhanced scouring to micro-lubrication.

[0159] In some exemplary embodiments, after determining the hydrophobicity index of the wiper system cleaning area based on the contact state information, the method further includes: Add the hydrophobicity index to the hydrophobicity index sequence; A trend analysis is performed on the hydrophobicity index sequence, and in response to the determination that the hydrophobicity index in the hydrophobicity index sequence shows a continuous downward trend, a maintenance prompt message is generated.

[0160] As an example, the hydrophobicity index sequence obtained over multiple consecutive historical working cycles is determined, the long-term trend of the hydrophobicity index sequence is analyzed, and when the long-term trend is determined to be a continuous decline, a maintenance prompt message is generated and sent to the vehicle terminal user interface.

[0161] As an example, the hydrophobicity index sequence obtained over multiple consecutive historical working cycles is determined, the numerical level of the hydrophobicity index sequence is analyzed, and when it is determined that the numerical level is continuously below a preset threshold, a maintenance prompt message is generated and sent to the vehicle terminal user interface.

[0162] As an example, maintenance prompts are used to alert users to problems such as severe wear of the hydrophobic coating and / or severe oil film buildup, in order to encourage user intervention and avoid safety hazards caused by poor visibility, thus upgrading maintenance from "passive response" to "proactive early warning".

[0163] In the exemplary embodiments described above, predictive maintenance capabilities are added, achieving an advancement from real-time control to long-term health management. By continuously recording and analyzing historical trends in the hydrophobicity index, performance degradation caused by uniform coating wear or slow oil film accumulation can be identified early, and warnings can be issued to the user before complete failure. This improves the convenience and safety of vehicle use, and also helps users plan maintenance scientifically, extending component lifespan.

[0164] It should be noted that the method of this disclosure embodiment can be executed by a single device, such as a computer or server. The method of this embodiment can also be applied to a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method of this disclosure embodiment, and the multiple devices will interact with each other to complete the method described.

[0165] It should be noted that the above description describes some embodiments of this disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0166] Based on the same inventive concept, corresponding to any of the above embodiments, this disclosure also provides a spray control device for a windshield wiper system.

[0167] refer to Figure 3 This is a schematic diagram of a spray control device for a wiper system provided in an exemplary embodiment of the present disclosure.

[0168] The wiper system spray control device 300 includes the following modules: The contact state information determination module 310 is configured to identify an image of the wiper system cleaning area of ​​the windshield to obtain contact state information between the liquid in the wiper system cleaning area and the windshield. The hydrophobicity index determination module 320 is configured to determine the hydrophobicity index of the wiper system cleaning area based on the contact state information. The spray control module 330 is configured to control the spray action of the wiper system based on the hydrophobicity index.

[0169] In some exemplary embodiments, the contact state information determination module 310 is configured to: A first image of the area cleaned by the wiper system between spraying and wiping operations; The first image is identified to obtain the water droplet contact angle information; A second image of the area cleaned by the wiper system after the wiper system has sprayed and wiped; The second image is identified to obtain water film morphology information; The contact state information includes the water droplet contact angle information and the water film morphology information.

[0170] In some exemplary embodiments, the contact state information determination module 310 is configured to: Identify the water droplets in the first image and obtain the outline of the water droplets; The water droplet's outline is fitted to a preset curve to obtain the water droplet's contact angle information.

[0171] In some exemplary embodiments, the contact state information determination module 310 is configured to: Convert the first image into a binary image; Connectivity analysis is performed on the binary image to obtain the contour lines of the connected regions, which are used as the contour lines of the water droplets. The step of fitting the outline of the water droplet to a preset curve to obtain the water droplet contact angle information includes: The water droplet's outline is fitted with the preset curve using nonlinear least squares fitting to obtain the water droplet's contact angle information.

[0172] In some exemplary embodiments, the contact state information determination module 310 is configured to: Identify the water film area in the second image, and obtain the water film coverage rate based on the area of ​​the water film area and the area of ​​the wiper system cleaning area; Based on the multiple water film coverage rates corresponding to multiple image frames arranged in chronological order in the second image, the average rate of decrease of the multiple water film coverage rates over time is determined as the water film rupture rate. The water film morphology information includes the water film coverage and the water film rupture rate.

[0173] In some exemplary embodiments, the contact state information determination module 310 is configured to: The second image is compared with a preset dry windshield image to obtain a difference image; Convert the difference image into a binary image; The binary image is subjected to noise removal, and adjacent regions of the noise-removed binary image are connected to obtain the water film region. The water film coverage rate is obtained by calculating the ratio between the area of ​​the water film region and the area of ​​the wiper system cleaning region.

[0174] In some exemplary embodiments, the hydrophobicity index determination module 320 is configured to: The water droplet contact angle information is mapped to a first standardized score, and the water film morphology information is mapped to a second standardized score; A first confidence level is determined for the water droplet contact angle information, and a first weight is determined for the first standardized score based on the first confidence level. A second confidence level is determined for the water film morphology information, and a second weight is determined for the second standardized score based on the second confidence level. The hydrophobicity index is obtained by weighting the first standardized score, the first weight, the second standardized score, and the second weight.

[0175] In some exemplary embodiments, the sprinkler control module 330 is configured to: Based on the mapping relationship between the hydrophobicity index and multiple preset spray control levels, the target spray parameters are determined. A spray control signal is generated based on the target spray parameters, and the spray volume and / or spray time of the wiper system are controlled based on the spray control signal.

[0176] In some exemplary embodiments, the spray control device 300 of the wiper system further includes a maintenance reminder module (not shown in the figure), configured to: Add the hydrophobicity index to the hydrophobicity index sequence; A trend analysis is performed on the hydrophobicity index sequence, and in response to the determination that the hydrophobicity index in the hydrophobicity index sequence shows a continuous downward trend, a maintenance prompt message is generated.

[0177] For ease of description, the above apparatus is described in terms of its functions, divided into various modules. Of course, in implementing this disclosure, the functions of each module can be implemented in one or more software and / or hardware.

[0178] It should be noted that, Figure 3 The spray control device 300 of the wiper system shown can execute the various steps in the above method embodiments and achieve the various processes and effects in the above method embodiments, which will not be elaborated here.

[0179] Based on the same inventive concept, corresponding to any of the above-described embodiments, this disclosure also provides an electronic device.

[0180] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure.

[0181] In this embodiment of the disclosure, Figure 4 The electronic device shown can be a server or a terminal, wherein the terminal specifically includes vehicle-mounted terminals, etc., which are not limited here.

[0182] like Figure 4 As shown, the electronic device may include a processor 410 and a memory 420 storing computer program instructions.

[0183] Specifically, the processor 410 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this disclosure.

[0184] Memory 420 may include a large-capacity storage device for information or instructions. For example, and not limitingly, memory 420 may include a hard disk drive (HDD), a floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 420 may include removable or non-removable (or fixed) media. Where appropriate, memory 420 may be internal or external to the integrated gateway device. In a particular embodiment, memory 420 is a non-volatile solid-state memory. In a particular embodiment, memory 420 includes read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (Electrically Programmable ROM, EPROM), an electrically erasable programmable PROM (EEPROM), an electrically alterable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0185] The processor 410 reads and executes computer program instructions stored in the memory 420 to perform the steps of the spray control method for the wiper system provided in the embodiments of this disclosure.

[0186] In one example, the electronic device may also include a transceiver 430 and a bus 440. Wherein, as... Figure 4 As shown, the processor 410, memory 420 and transceiver 430 are connected via bus 440 and communicate with each other.

[0187] Bus 440 may include hardware, software, or both. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industrial Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 440 may include one or more buses.

[0188] This disclosure also provides a computer-readable storage medium that can store a computer program. When the computer program is executed by a processor, the processor enables the processor to implement the spray control method for the wiper system provided in this disclosure.

[0189] The aforementioned storage medium may, for example, include a memory 420 containing computer program instructions, which can be executed by a processor 410 to complete the spray control method of the wiper system provided in this embodiment. Optionally, the storage medium may be a non-transitory computer-readable storage medium, such as a read-only memory (ROM), random access memory (RAM), external cache memory, compact disc ROM (CD-ROM), magnetic tape, floppy disk, flash memory, and optical data storage device. By way of illustration and not limitation, RAM is available in various forms, such as static random access memory (SRAM) and dynamic random access memory (DRAM).

[0190] refer to Figure 5 This disclosure also provides a vehicle 500, which includes one or more processors 510 and one or more memories 520.

[0191] Processor 510 may include one or more processing cores, such as a quad-core processor, a deca-core processor, etc. Processor 510 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Processor 510 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 510 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, processor 510 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0192] The memory 520 may include one or more computer-readable storage media, which may be non-transitory. The memory 520 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 520 are used to store at least one computer program, which is executed by the processor 510 to implement the driveable lane identification method provided in the method embodiments of this disclosure.

[0193] Those skilled in the art will understand that Figure 5 The structure shown does not constitute a limitation on vehicle 500 and may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0194] Based on the same inventive concept, corresponding to the spray control method of the wiper system described in any of the above embodiments, this disclosure also provides a computer program product, which includes computer program instructions. In some embodiments, the computer program instructions can be executed by one or more processors of a computer to cause the computer and / or the processor to perform the spray control method of the wiper system. Corresponding to the execution entity for each step in each embodiment of the spray control method of the wiper system, the processor executing the corresponding step can belong to the corresponding execution entity.

[0195] The computer program product of the above embodiments is used to cause the computer and / or the processor to execute the spray control method of the wiper system as described in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0196] Those skilled in the art will recognize that embodiments of this disclosure can be implemented as a system, method, or computer program product. Therefore, this disclosure can be implemented as entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, this disclosure can also be implemented as a computer program product contained in one or more computer-readable media, which includes computer-readable program code.

[0197] Any combination of one or more computer-readable media may be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example,, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (not exhaustive) of a computer-readable storage medium may include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0198] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0199] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0200] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0201] It should be understood that each block of a flowchart and / or block diagram, as well as combinations of blocks in a flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine that, when executed by a computer or other programmable data processing device, creates means for implementing the functions / operations specified in the blocks of the flowchart and / or block diagram.

[0202] These computer program instructions may also be stored in a computer-readable medium that enables a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable medium produce a product comprising an instruction apparatus that implements the functions / operations specified in the boxes of a flowchart and / or block diagram.

[0203] Computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, such that the instructions that execute on the computer or other programmable apparatus can provide a process for implementing the functions / operations specified in the boxes of a flowchart and / or block diagram.

[0204] Furthermore, although the operations of the methods of this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all of the operations shown must be performed to achieve the desired result. Rather, the steps depicted in the flowcharts may be executed in a different order. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0205] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. Each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0206] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0207] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this disclosure (including the claims) is limited to these examples; within the framework of this disclosure, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this disclosure as described above, which are not provided in detail for the sake of brevity.

[0208] Additionally, to simplify the description and discussion, and to avoid obscuring the embodiments of this disclosure, the provided drawings may or may not show well-known power / ground connections to integrated circuit (IC) chips and other components. Furthermore, the apparatus may be shown in block diagram form to avoid obscuring the embodiments of this disclosure, and this also takes into account the fact that the details of implementation of these block diagram apparatuses are highly dependent on the platform on which the embodiments of this disclosure will be implemented (i.e., these details should be fully understood by those skilled in the art). While specific details (e.g., circuits) have been set forth to describe exemplary embodiments of this disclosure, it will be apparent to those skilled in the art that the embodiments of this disclosure can be implemented without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0209] Although this disclosure has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0210] This disclosure is intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

[0211] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus 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 apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0212] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0213] While the spirit and principles of this disclosure have been described with reference to several specific embodiments, it should be understood that this disclosure is not limited to the disclosed specific embodiments, and the division of aspects does not imply that features in these aspects cannot be combined for benefit; such division is merely for convenience of expression. This disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims. The scope of the appended claims is to be interpreted in the broadest sense, thereby encompassing all such modifications and equivalent structures and functions.

Claims

1. A spray control method for a windshield wiper system, characterized in that, include: The image of the wiper system cleaning area of ​​the windshield is identified to obtain the contact state information between the liquid in the wiper system cleaning area and the windshield; Based on the contact state information, the hydrophobicity index of the cleaning area of ​​the wiper system is determined; The spray action of the wiper system is controlled based on the hydrophobicity index.

2. The method according to claim 1, characterized in that, The process of identifying the image of the wiper system cleaning area of ​​the windshield to obtain contact state information between the liquid in the wiper system cleaning area and the windshield includes: A first image of the area cleaned by the wiper system between spraying and wiping operations; The first image is identified to obtain the water droplet contact angle information; A second image of the area cleaned by the wiper system after the wiper system has sprayed and wiped; The second image is identified to obtain water film morphology information; The contact state information includes the water droplet contact angle information and the water film morphology information.

3. The method according to claim 2, characterized in that, The step of identifying the first image to obtain the water droplet contact angle information includes: Identify the water droplets in the first image and obtain the outline of the water droplets; The water droplet's outline is fitted to a preset curve to obtain the water droplet's contact angle information.

4. The method according to claim 3, characterized in that, The step of identifying water droplets in the first image and obtaining the outline of the water droplets includes: Convert the first image into a binary image; Connectivity analysis is performed on the binary image to obtain the contour lines of the connected regions, which are used as the contour lines of the water droplets. The step of fitting the outline of the water droplet to a preset curve to obtain the water droplet contact angle information includes: The water droplet's outline is fitted with the preset curve using nonlinear least squares fitting to obtain the water droplet's contact angle information.

5. The method according to claim 2, characterized in that, The step of recognizing the second image to obtain water film morphology information includes: Identify the water film area in the second image, and obtain the water film coverage rate based on the area of ​​the water film area and the area of ​​the wiper system cleaning area; Based on the multiple water film coverage rates corresponding to multiple image frames arranged in chronological order in the second image, the average rate of decrease of the multiple water film coverage rates over time is determined as the water film rupture rate. The water film morphology information includes the water film coverage and the water film rupture rate.

6. The method according to claim 5, characterized in that, The step of identifying the water film region in the second image and obtaining the water film coverage rate based on the area of ​​the water film region and the area of ​​the wiper system cleaning area includes: The second image is compared with a preset dry windshield image to obtain a difference image; Convert the difference image into a binary image; The binary image is subjected to noise removal, and adjacent regions of the noise-removed binary image are connected to obtain the water film region. The water film coverage rate is obtained by calculating the ratio between the area of ​​the water film region and the area of ​​the wiper system cleaning region.

7. The method according to claim 2, characterized in that, The step of determining the hydrophobicity index of the wiper system's cleaning area based on the contact state information includes: The water droplet contact angle information is mapped to a first standardized score, and the water film morphology information is mapped to a second standardized score; A first confidence level is determined for the water droplet contact angle information, and a first weight is determined for the first standardized score based on the first confidence level. A second confidence level is determined for the water film morphology information, and a second weight is determined for the second standardized score based on the second confidence level. The hydrophobicity index is obtained by weighting the first standardized score, the first weight, the second standardized score, and the second weight.

8. The method according to claim 1, characterized in that, The step of controlling the spray action of the wiper system based on the hydrophobicity index includes: Based on the mapping relationship between the hydrophobicity index and multiple preset spray control levels, the target spray parameters are determined. A spray control signal is generated based on the target spray parameters, and the spray volume and / or spray time of the wiper system are controlled based on the spray control signal.

9. The method according to claim 1, characterized in that, After determining the hydrophobicity index of the wiper system's cleaning area based on the contact state information, the method further includes: Add the hydrophobicity index to the hydrophobicity index sequence; A trend analysis is performed on the hydrophobicity index sequence, and in response to the determination that the hydrophobicity index in the hydrophobicity index sequence shows a continuous downward trend, a maintenance prompt message is generated.

10. A vehicle, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method according to any one of claims 1 to 9.

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