A method and system for preventing and removing ice and frost from a vehicle window

Abstract

This invention discloses a method and system for preventing and removing frost from vehicle windows, relating to the field of automotive electronics and body control technology, and addressing the problem of inaccurate prediction of vehicle icing risk in existing technologies. The method includes: acquiring real-time environmental information of the vehicle; calculating and determining the real-time risk of vehicle icing based on the real-time environmental information; using the current real-time risk as the current risk of vehicle icing, and the real-time risks corresponding to previous times as the historical risks of vehicle icing; weighted and fusing the current risk and the historical risks of vehicle icing to obtain the final vehicle icing risk; and determining vehicle frost prevention and removal strategies based on the vehicle icing risk. This achieves accurate prediction of vehicle icing risk.

Description

Technical Field

[0001] This invention relates to the field of automotive electronics and body control technology, and in particular to a method and system for preventing and removing frost from vehicle windows. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] In cold and damp winter conditions, after vehicles have been parked for extended periods, ice or frost can easily form on the surface of the windows due to the low temperature and condensation of moisture in the air. The presence of frost severely impairs the driver's visibility and poses a significant safety hazard during winter driving. Therefore, effectively preventing and removing frost from car windows is a common need in automotive use.

[0004] In related technologies, the risk of vehicle icing is determined based on the current environmental information of the vehicle. When the risk of icing is high, timely frost prevention and control measures are taken for the vehicle. However, since vehicle fogging and icing gradually form according to environmental changes, determining the icing risk based solely on the current environmental information cannot reflect the gradual process of fogging and icing, resulting in inaccurate determination of the icing risk and failure to effectively prevent and remove vehicle frost. Summary of the Invention

[0005] To address the aforementioned problems, this invention proposes a method and system for preventing and removing vehicle window frost. When determining the risk of vehicle icing, this method considers not only the current risk of icing but also the historical risk, enabling the final determined vehicle icing risk to more accurately characterize the vehicle's icing state. This improves the accuracy of determining vehicle frost prevention and removal strategies, achieving effective prevention and removal of vehicle frost.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: Firstly, a method for preventing and removing frost from car windows is proposed, including: Obtain real-time environmental information of the vehicle; Based on the real-time environmental information of the vehicle, the real-time risk of vehicle icing is calculated and determined; The current real-time risk is taken as the current risk of vehicle icing, and the real-time risks corresponding to previous times are taken as the historical risks of vehicle icing. The current risk of vehicle icing and the historical risk of vehicle icing are weighted and merged to obtain the final risk of vehicle icing. Determine vehicle icing prevention and removal strategies based on the risk of vehicle icing.

[0007] Preferably, the real-time environmental information includes ambient dew point temperature, glass surface temperature, and ambient humidity; Calculate the difference between the glass surface temperature and the ambient dew point temperature as the temperature difference at the set time. The humidity weighting factor is calculated and determined based on the ambient humidity. The temperature difference is taken as a negative number and multiplied by the humidity weighting factor to calculate and determine the real-time risk of vehicle icing.

[0008] Preferably, the ambient dew point temperature is calculated and determined based on the ambient temperature and ambient humidity.

[0009] Preferably, the real-time risks corresponding to multiple previous times are obtained, and the real-time risks corresponding to previously set times are used as historical time risks; The impact weight of the historical risk is calculated and determined based on the time difference between the corresponding time of the historical risk and the current time. The historical risk of vehicle icing is obtained by multiplying the risk of each historical moment of vehicle icing by its corresponding impact weight and then summing the results.

[0010] Preferably, based on the risk of vehicle icing, a vehicle icing prevention and removal strategy is determined, including: Determine the vehicle icing risk level based on the vehicle's icing risk. When the vehicle icing risk level is medium, inhibit the further formation of vehicle frost; When the vehicle icing risk level is high, determine whether the user is about to use the vehicle; When it is determined that the user is about to use the vehicle, the system will control the vehicle to defrost the windows.

[0011] Preferably, when the risk of vehicle icing is less than or equal to a set first risk threshold, the risk level of vehicle icing is determined to be low. When the risk of vehicle icing is less than or equal to the set second risk threshold, but greater than the set first risk threshold, the vehicle icing risk level is determined to be medium risk. When the risk of vehicle icing exceeds the set second risk threshold, the vehicle icing risk level is determined to be high risk.

[0012] Secondly, a system for preventing and removing frost from car windows is proposed, including: The information acquisition unit is used to acquire real-time environmental information about the vehicle's location. The real-time risk calculation unit is used to calculate and determine the real-time risk of vehicle icing based on the real-time environmental information of the vehicle. The icing risk calculation unit is used to take the real-time risk corresponding to the current moment as the current risk of vehicle icing, take the real-time risk corresponding to the previous moment as the historical risk of vehicle icing, and perform weighted fusion of the current risk of vehicle icing and the historical risk of vehicle icing to obtain the final vehicle icing risk. The strategy determination unit is used to determine vehicle icing prevention and removal strategies based on the risk of vehicle icing.

[0013] Thirdly, a computer device is proposed, the device comprising: A processor, adapted to execute computer programs; A computer-readable storage medium storing a computer program, which, when executed by the processor, implements the method for preventing and removing frost from car windows as proposed in the first aspect.

[0014] Fourthly, a computer-readable storage medium is proposed, wherein the computer-readable storage medium stores a computer program adapted to be loaded by a processor and executed by a processor to provide a method for preventing and removing frost from car windows as proposed in the first aspect.

[0015] Fifthly, a computer program product is proposed, which includes a computer program that, when executed by a processor, implements a method for preventing and removing frost from car windows as proposed in the first aspect.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention proposes a method and system for preventing and removing frost from vehicle windows. The method acquires real-time environmental information about the vehicle's location, calculates and determines the real-time risk of vehicle icing based on this information, uses the current real-time risk as the current risk of icing, and uses the real-time risks from previous times as historical risks of icing. The current and historical risks of icing are then weighted and fused to obtain the final vehicle icing risk. This achieves accurate prediction of window icing risk, thereby improving the accuracy of determining vehicle frost prevention and removal strategies and enabling effective prevention and removal of vehicle frost. It also solves the technical problem that current vehicle icing risk prediction only considers the current environmental information and does not take into account the impact of historical environmental information on vehicle icing, leading to inaccurate predictions.

[0017] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0018] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments of this application and their descriptions are used to explain this application and do not constitute an undue limitation of this application.

[0019] Figure 1 This is a flowchart illustrating a method for preventing and removing frost from car windows, as proposed in an embodiment of the present invention. Detailed Implementation

[0020] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0021] It should be noted that the following detailed descriptions are illustrative and intended to provide a preferred description of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0022] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0023] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0024] It should be noted that all data acquisition is conducted in accordance with laws and regulations and with user consent, and the data is used legally.

[0025] In cold and damp winter conditions, after vehicles have been parked for extended periods, ice or frost can easily form on the surface of the windows due to the low temperature and condensation of moisture in the air. The presence of frost severely impairs the driver's visibility and poses a significant safety hazard during winter driving. Therefore, effectively preventing and removing frost from car windows is a common need in automotive use.

[0026] Currently, common methods drivers use to deal with icy or frosty car windows include: mechanically scraping the window surface with tools such as ice scrapers; pouring hot water on the windows to melt the frost; and starting the vehicle and turning on the air conditioning heating system, letting it idle and waiting for the warm air to melt the frost. Mechanical scraping is time-consuming and laborious, and carries the risk of scratching the glass surface and wiper blades; pouring hot water may cause cracks in the glass due to the sudden temperature difference between the inside and outside; and idling the vehicle with the heating system requires a long waiting time, which increases energy consumption and causes wear and tear on the vehicle's powertrain in low-temperature environments.

[0027] With the development of automotive electronics technology, some vehicles are equipped with remote start-and-preheat functions. Users can start the vehicle in advance before getting in using a mobile application or remote control, and use the heating system to defrost the windows. However, such solutions typically rely on fixed-time triggers or manual user operation. The system itself lacks the ability to sense and judge the current ambient temperature and humidity, and cannot automatically decide whether to initiate defrosting based on the actual risk of icing. When the risk of icing is low, the system will still operate as planned, resulting in unnecessary energy consumption; while in cases of high icing risk where the user does not manually operate the system, defrosting may be delayed.

[0028] Another existing technology involves embedding or attaching electric heating elements within the car window glass. When electricity is applied, the glass is directly heated to melt existing frost. This method offers direct defrosting, but it operates by removing frost after it has formed, lacking a means to intervene in the frost formation process. Furthermore, when the frost is thick or the ambient temperature is extremely low, the time required to completely melt the frost is long, and the energy consumption during continuous heating is high.

[0029] The aforementioned solutions for dealing with car window frost generally focus on removing frost after it has formed, lacking the ability to anticipate and proactively intervene in the risk of icing. There is room for improvement in terms of intelligence and overall processing efficiency.

[0030] Therefore, a related technology has proposed a solution to determine the icing risk of a vehicle based on its current environmental information, and to implement timely frost prevention and control when the icing risk is high. However, since vehicle fogging and icing gradually form based on environmental changes, determining the icing risk based solely on current environmental information without considering historical environmental information only reflects the current icing state of the vehicle and cannot reflect the gradual process of fogging and icing. This leads to inaccurate determination of the icing risk and, consequently, inability to effectively prevent and remove vehicle frost.

[0031] To accurately predict vehicle icing risk and effectively prevent and remove vehicle frost, this invention proposes a method for preventing and removing vehicle window frost. When determining vehicle icing risk, this method considers not only the current risk but also the historical risk, resulting in a more accurate assessment of the vehicle's icing state. By weightedly fusing the current and historical icing risks, accurate prediction of vehicle icing risk is achieved, improving the accuracy of vehicle frost prevention and removal strategies. This solves the technical problem of inaccurate vehicle icing risk prediction that only considers current environmental information without considering the impact of historical environmental information.

[0032] The overall technical implementation of the vehicle window frost prevention and removal method proposed in this invention is as follows: First, the system collects real-time ambient temperature, humidity, and glass surface temperature information of the vehicle using a sensor module. Simultaneously, the system records the real-time risk of vehicle icing every 5 minutes, forming a historical risk profile for vehicle icing. Second, based on the real-time environmental information, the system calculates the difference between the ambient dew point temperature and the glass surface temperature, and combines this with a humidity weighting factor calculated from the ambient humidity to obtain the real-time risk of vehicle icing. Third, the system acquires the real-time risks corresponding to multiple previous times and uses these risks as historical risks. Finally, the system calculates the risk based on the time difference between the historical risk profile and the current time. The system calculates and determines the impact weight of risks at historical moments. It then multiplies the risk of vehicle icing at each historical moment by its corresponding impact weight and sums the results to obtain the historical risk of vehicle icing. Next, it uses the real-time risk at the current moment as the current risk of vehicle icing, and weights and merges the current risk with the historical risk according to a set weight ratio to obtain the final vehicle icing risk. Finally, based on the final vehicle icing risk, it determines the vehicle icing risk level. Based on this level, it triggers corresponding vehicle icing prevention and removal strategies, such as no action for low risk, spraying antifreeze for medium risk, or activating heater ventilation and piezoelectric vibration to clear icing when the user is about to use the vehicle for high risk. This achieves accurate prediction and early intervention for vehicle icing.

[0033] The real-time environmental information of the vehicle mentioned in this embodiment of the invention refers to physical quantities such as real-time dew point temperature, real-time ambient humidity, and real-time glass surface temperature that can be collected in real time by sensors. The ambient dew point temperature (Td) refers to the temperature at which water vapor in the air reaches saturation under the current atmospheric pressure. Its value is determined by calculating the ambient temperature (Ta) and ambient humidity (RH). Glass surface temperature (Ts) refers to the temperature measured on the inner surface of the windshield; Ambient humidity refers to the relative humidity of ambient air (RH), expressed as a percentage. The humidity weighting factor (H) is a coefficient that weights the risk of icing based on the ambient humidity. When the ambient humidity is higher than 70%, the H value increases linearly with humidity. The real-time risk of vehicle icing (R_current) refers to the real-time risk index of vehicle icing calculated based on the real-time environmental information of the vehicle. The current risk of vehicle icing (R_now) refers to the current risk index of vehicle icing calculated based on the environmental information of the vehicle at the current moment. Historical risk (R_acc) refers to the historical cumulative risk index calculated by combining the risks of each historical moment in the past 12 hours and their corresponding impact weights at the current moment. Vehicle icing risk (R) refers to the final comprehensive risk assessment value of vehicle icing obtained by weighting and integrating the current risk of vehicle icing with the historical risk of vehicle icing.

[0034] The following describes the application scenarios of the method for preventing and removing frost from car windows proposed in this embodiment of the invention.

[0035] The present invention provides a method for preventing and removing frost from vehicle windows, which is applied to intelligent electric vehicles equipped with a CAN bus network.

[0036] The intelligent electric vehicle consists of four parts: a sensing module, a control module (ECU), an execution module, and a user interaction module. These modules are interconnected via a CAN bus, an internal integrated circuit (I2C) bus, a local interconnect network (LIN) bus, and a Bluetooth communication interface to work together to prevent and remove frost from the windows.

[0037] The control module uses STMicroelectronics' SPC58EC80E5 microcontroller (ECU) as the control core. This microcontroller complies with the automotive-grade AEC-Q100 standard, has sufficient computing power, a CAN-FD interface, and abundant analog-to-digital converter (ADC) and digital input / output (DIO) resources.

[0038] The sensing module includes an ambient temperature and humidity sensor, a glass surface temperature sensor, and an optical frost sensor.

[0039] The ambient temperature and humidity sensor uses Sensirion's SHT40 automotive-grade digital sensor, which connects to the ECU via an I2C interface and is installed inside the exterior rearview mirror housing to monitor ambient temperature (Ta) and ambient humidity (RH). The glass surface temperature sensor uses a surface-mount PT1000 platinum resistance temperature sensor, which connects to the ECU via a high-precision ADC circuit and is attached to the lower center of the inner surface of the windshield to monitor the glass surface temperature (Ts). The optical frost sensor uses an infrared reflective sensor integrated with the automatic wiper system, which communicates with the ECU via a LIN bus to quantitatively detect the frost thickness (Ice_Th) on the glass surface, with a detection range of 0mm to 5mm.

[0040] The execution module includes a micro-atomized antifreeze spraying unit, a directional warm air guiding unit, and a glass surface micro-vibration unit.

[0041] The micro-atomizing antifreeze spraying unit includes a reservoir, a micro gear pump (model MGP25), and two ultrasonic atomizing nozzles. The reservoir contains glycol-based environmentally friendly antifreeze. The micro gear pump's speed and spray duration are controlled by the ECU via pulse width modulation (PWM) signals. The two ultrasonic atomizing nozzles are positioned at the base of the wiper arms to spray the antifreeze in atomized form onto the windshield surface. The directional heating air guiding unit includes an air guide plate located within the air conditioning unit, corresponding to the windshield air outlet duct, and a micro stepper motor that drives the air guide plate. The ECU communicates with the air conditioning unit via a CAN bus. The controller sends a command to the air conditioner to blow air towards the windshield at the highest setting and temperature, and simultaneously controls the stepper motor to rotate the air guide plate to the angle that is fully directed towards the glass. The glass surface micro-vibration unit uses a piezoelectric ceramic sheet (PZT) with a size of 40mm×20mm×1mm, which is attached to the inner edge of the windshield (located in the area covered by the interior panel) with epoxy resin adhesive. The ECU drives the piezoelectric ceramic sheet to vibrate by outputting an AC voltage signal with a frequency of 125Hz through the drive circuit based on the DRV2667 chip, so as to reduce the adhesion between frost and the glass surface.

[0042] The user interaction module includes a Bluetooth module (model CC2642R). The Bluetooth module establishes a Bluetooth connection with the user's mobile phone and detects the user's proximity by detecting the mobile phone signal strength. When the user's mobile phone is detected to be within the vehicle's effective Bluetooth detection range (usually 5m to 30m), it is determined that the user is about to use the vehicle.

[0043] Please refer to Figure 1 The diagram illustrates a flowchart of a method for preventing and removing frost from car windows, as shown in an exemplary embodiment of the present invention. (Reference) Figure 1 The present invention provides a method for preventing and removing frost from car windows, comprising: Step S101: Obtain real-time environmental information of the vehicle.

[0044] The real-time environmental information includes ambient dew point temperature (Td), glass surface temperature (Ts), and ambient humidity (RH).

[0045] The ambient dew point temperature (Td) is calculated based on the ambient temperature (Ta) and ambient humidity (RH), using the following formula: Td = Ta - ((100 - RH) / 5) (1) Where Td is the ambient dew point temperature in °C; Ta is the ambient temperature obtained by the temperature and humidity sensor in °C; and RH is the ambient humidity in °C.

[0046] Specifically, after the vehicle is turned off, the control module (ECU) enters a low-power cycle monitoring state, performing a data acquisition cycle every 60 seconds. During each acquisition cycle, the ECU reads the current ambient temperature (Ta) and ambient humidity (RH) of the vehicle from the ambient temperature and humidity sensor via the I2C interface. The measurement range of Ta is -40℃ to 125℃, and the measurement range of RH is 0% to 100%. It also reads the glass surface temperature (Ts) from the glass surface temperature sensor via the ADC circuit. The measurement range of Ts is -40℃ to 85℃. Finally, it reads the frost thickness (Ice_Th) on the glass surface from the optical frost sensor via the LIN bus.

[0047] The data is sampled once per second, and a moving average is calculated every 60 seconds. The moving average is used as the current valid real-time environmental information.

[0048] Meanwhile, the control module (ECU) maintains a risk history array, recording the current real-time risk (R_current) as a historical risk every 5 minutes and retaining historical data points from the past 12 hours to form historical data. This information acquisition mechanism ensures the smoothness of real-time environmental information and the temporal continuity of historical risks, providing a reliable data foundation for subsequent risk calculations.

[0049] Step S102: Calculate and determine the real-time risk of vehicle icing based on the real-time environmental information of the vehicle.

[0050] The real-time environmental information includes ambient dew point temperature, glass surface temperature, and ambient humidity. Calculate the difference between the glass surface temperature and the ambient dew point temperature as the temperature difference at the set time. The humidity weighting factor is calculated and determined based on the ambient humidity. The temperature difference is taken as a negative number and multiplied by the humidity weighting factor to calculate and determine the real-time risk of vehicle icing.

[0051] Specifically, based on the real-time ambient dew point temperature Td, ambient humidity RH, and glass surface temperature Ts obtained in step S101, the ECU calculates and determines the real-time risk R_current of vehicle icing according to the following process: First, calculate the real-time temperature difference ΔT. The real-time temperature difference is the difference between the glass surface temperature and the ambient dew point temperature, calculated according to formula (2): ΔT = Ts - Td (2) Where ΔT is the real-time temperature difference in °C, and Ts is the glass surface temperature in °C. The smaller ΔT is (closer to or lower than 0), the closer the glass temperature is to or lower than the dew point temperature, and the higher the risk of icing.

[0052] Next, the humidity weighting factor H is calculated. When the ambient humidity RH is greater than 70%, the humidity weighting factor increases linearly according to formula (3): H = 1 + (RH - 70) × 0.02 (3) Wherein, H is the humidity weighting factor, which is dimensionless; when RH is not greater than 70%, H is 1. The humidity weighting factor is used to positively correct the risk of vehicle icing in high humidity environments, so as to reflect the physical law that frost is more likely to form under high humidity conditions.

[0053] Finally, the real-time risk of vehicle icing, R_current, is calculated. The real-time risk of vehicle icing is calculated according to formula (4): R_current = (-ΔT)×H (4) Here, R_current represents the real-time risk of vehicle icing, which is dimensionless; a positive R_current indicates the presence of icing risk, with higher values ​​indicating greater risk. The above calculation method organically combines temperature difference information with humidity correction information, achieving a quantitative description of the icing risk at the current moment.

[0054] Step S103: Take the real-time risk corresponding to the current moment as the current risk of vehicle icing, take the real-time risks corresponding to the previous moments as the historical risks of vehicle icing, and perform weighted fusion of the current risk of vehicle icing and the historical risks of vehicle icing to obtain the final vehicle icing risk.

[0055] The process of determining the historical risk of vehicle icing includes: Obtain the real-time risks corresponding to multiple previous times at the current moment, and use the real-time risks corresponding to previously set times as historical time risks; The impact weight of the historical risk is calculated and determined based on the time difference between the corresponding time of the historical risk and the current time. The historical risk of vehicle icing is obtained by multiplying the risk of each historical moment of vehicle icing by its corresponding impact weight and then summing the results.

[0056] Specifically, the historical moment risk includes multiple historical moment risks recorded every 5 minutes over the past 12 hours. The ECU calculates the icing risk corresponding to each historical moment t_i based on the ambient temperature, ambient humidity, and glass surface temperature recorded at each historical moment t_i, according to formulas (1) to (4), i.e., the vehicle icing risk R_current_i at each historical moment, forming a historical risk array. The historical moment risks in the historical risk array reflect the accumulated icing risk experienced by the vehicle over the past period, providing data support for subsequent cumulative risk calculations.

[0057] For each historical time t_i in the historical risk array, the ECU calculates the time difference between the current time t_now and that historical time t_i, i.e., t_now - t_i, and calculates the impact weight w_i of the risk at that historical time according to formula (5): w_i = e^(-0.1×(t_now - t_i)) (5) Where w_i is the impact weight of the risk at historical time i, which is an exponential impact weight and is dimensionless; t_now is the current time in minutes; t_i is the time point corresponding to historical time i in minutes; and e is a natural constant.

[0058] The exponential decay weighting formula described above assigns a higher weight to the risk of historical moments closer to the current time, and a lower weight to the risk of historical moments further away from the current time, thus reasonably reflecting the stronger correlation between the risk of recent historical moments and the current icing risk.

[0059] The ECU multiplies the historical risk R_current_i of each time point in the past 12 hours with the corresponding influence weight w_i and then adds them together, and calculates the historical risk R_acc of vehicle icing according to formula (6): R_acc =Σ(R_current_i × w_i) =Σ(R_current_i × e^(-0.1×(t_now - t_i))) (6) Wherein, R_acc represents the historical risk of vehicle icing, which is dimensionless; the summation range covers all historical moments within the past 12 hours. The historical risk of vehicle icing comprehensively reflects the degree of icing risk accumulated by vehicles continuously exposed to icing conditions over a long period of time. It can effectively capture the cumulative effect of long-term low temperature and high humidity environment on icing risk, and make up for the historical accumulation factors that may be missed when relying solely on the real-time risk index.

[0060] Step S104: Weight and fuse the current risk of vehicle icing with the historical risk of vehicle icing to obtain the final vehicle icing risk.

[0061] Specifically, the ECU weights and fuses the current risk of vehicle icing R_now with the historical risk of vehicle icing R_acc according to formula (7) to obtain the final vehicle icing risk R: R = w_now× R_now + w_acc × R_acc (7) Where R represents the vehicle icing risk, which is dimensionless; w_now is the weighted average of the current vehicle icing risk, which can be set according to specific needs, such as 0.7; w_acc is the weighted average of the historical vehicle icing risk, which can also be set according to specific needs, such as 0.3. Both w_now and w_acc can be adjusted according to specific requirements. The vehicle icing risk assessment considers both the current risk of vehicle icing and the accumulated risk over historical periods. Compared to using a real-time risk index alone, it can more accurately reflect the actual icing risk of vehicle windows, reduce the false alarm rate, and solve the technical problem that current vehicle icing risk prediction only considers the environmental information at the current moment and does not consider the impact of historical environmental information on vehicle icing, leading to inaccurate predictions.

[0062] Step S106: Determine vehicle icing prevention and removal strategies based on the overall risk of vehicle icing.

[0063] Based on the risk of vehicle icing, determine vehicle icing prevention and removal strategies, including: Determine the vehicle icing risk level based on the vehicle's icing risk. When the vehicle icing risk level is medium, inhibit the further formation of vehicle frost; When the vehicle icing risk level is high, determine whether the user is about to use the vehicle; When it is determined that the user is about to use the vehicle, the system will control the vehicle to defrost the windows.

[0064] Among them, when the risk of vehicle icing is less than or equal to the set first risk threshold, the risk level of vehicle icing is determined to be low risk. When the risk of vehicle icing is less than or equal to the set second risk threshold, but greater than the set first risk threshold, the vehicle icing risk level is determined to be medium risk. When the risk of vehicle icing exceeds the set second risk threshold, the vehicle icing risk level is determined to be high risk.

[0065] Both the first and second risk thresholds can be modified and adjusted according to specific needs. Taking the selection of the first risk threshold R_low = 1.5 and the second risk threshold R_high = 3.5 as an example, the selection of vehicle frost prevention and removal strategies will be explained in detail.

[0066] Specifically, the ECU first determines the vehicle's icing risk level based on the vehicle's icing risk R: when the vehicle's icing risk R is less than or equal to the set first risk threshold (R_low = 1.5), the vehicle's icing risk level is determined to be low risk; when the vehicle's icing risk R is greater than the first risk threshold and less than or equal to the set second risk threshold (R_high = 3.5), the vehicle's icing risk level is determined to be medium risk; when the vehicle's icing risk R is greater than the second risk threshold, the vehicle's icing risk level is determined to be high risk.

[0067] When the vehicle's icing risk level is low, the ECU does not trigger any action, and the system maintains a low-power cycle monitoring state to continue the next round of data collection and risk calculation.

[0068] When the vehicle's icing risk level is medium, the ECU sends a control command to the micro-atomized antifreeze spraying unit. This command uses a PWM signal to control a micro-gear pump to operate at a set speed, driving glycol-based antifreeze to be sprayed onto the windshield surface in a mist form through two ultrasonic atomizing nozzles at the base of the wiper arms. The spraying duration is 500ms. The antifreeze forms a uniform liquid film on the glass surface, lowering the freezing point and thus inhibiting further frost formation, achieving preventative intervention.

[0069] When the vehicle's icing risk level is high, the ECU further determines whether the user is about to use the vehicle. The determination that the user is about to use the vehicle is based on one of the following two conditions: First, the Bluetooth module (CC2642R) detects that the user's mobile phone has entered the vehicle's effective Bluetooth sensing range, determining that the user is approaching the vehicle; Second, the T-Box receives the remote vehicle use command issued by the user through the mobile application via the vehicle network.

[0070] When the ECU detects that the user is about to use the vehicle, it triggers the active defrosting mode and controls the vehicle to defrost the windows. The ECU performs the following operations in sequence: First, it sends a command to the air conditioning controller via the CAN bus, controlling the air conditioning to blow air towards the windshield at the highest setting and temperature. Simultaneously, it controls a stepper motor to rotate the air deflector to a fully directed angle towards the glass, concentrating the warm air onto the windshield surface. At the same time, the ECU outputs a 125Hz AC voltage signal to the piezoelectric ceramic plate via a drive circuit based on the DRV2667 chip, driving the piezoelectric ceramic plate to generate micro-vibrations, reducing the adhesion between the frost and the glass surface, and assisting the warm air in accelerating the melting and removal of the frost. Every 10 seconds, the ECU reads the frost thickness (Ice_Th) output by the optical frost sensor via the LIN bus. When Ice_Th drops below 0.05mm, it determines that the frost removal is complete. The ECU then shuts down the piezoelectric ceramic plate drive circuit, restores the air deflector to its default position (50% opening), and sends a "Vehicle defrosting complete, ready to depart" notification to the user's mobile phone via a T-Box or Bluetooth module.

[0071] When it is determined that the user is not about to use the vehicle, the ECU only records the current high-risk status log and does not activate the high-power active clearing mode. The system continues to maintain a low-power cycle monitoring state to avoid unnecessary consumption of the vehicle's power battery when the user does not need to use the vehicle.

[0072] The following is a specific working example illustrating the implementation process of a method for preventing and removing frost from vehicle windows proposed in this embodiment of the invention. Assume the vehicle is parked at night, with initial measurements of Ta = -5℃, RH = 90%, and Ts = -4℃. According to formula (1), Td = -5 - ((100-90) / 5) = -7℃; according to formula (2), ΔT = -4 - (-7) = 3℃; according to formula (3), H = 1 + (90 - 70) × 0.02 = 1.4; and according to formula (4), R_current = (-3) × 1.4 = -4.2. Initially, R_current is negative, indicating a low risk of vehicle icing, and the system remains in a low-risk state. As the night deepens, Ts slowly decreases to -8℃. At this point, ΔT = -8 - (-7) = -1℃, and R_current = (-(-1)) × 1.4 = 1.4, increasing the risk of vehicle icing. After R_current remained within the range of 1.0 to 1.4 for three consecutive hours, R_acc increased significantly, and finally at 5:00 AM, the vehicle icing risk R exceeded R_high = 3.5, which the system judged as high risk. During the transition from low to high risk, the system automatically performed a medium-risk antifreeze spray operation when the risk was judged to be medium. At 6:45 AM, the Bluetooth module detected the user's mobile phone entering the sensing range. The system simultaneously met the conditions of "high risk" and "user about to use the vehicle," and immediately activated the active defrosting mode, controlling the vehicle to defrost the windows: the air conditioner blew air to the windshield at the highest setting, the air deflector was rotated to 100% of its guide angle, and the piezoelectric ceramic disc vibrated at a frequency of 125Hz. At 6:55 AM, the optical sensor detected that Ice_Th dropped below 0.05mm, the system stopped vibrating and guiding the air, and pushed a completion notification to the user's mobile phone.

[0073] The method for preventing and removing frost from car windows proposed in this invention has the following beneficial effects: (1) Based on the real-time environmental information of the vehicle, the real-time risk of vehicle icing is calculated and determined. The real-time risk corresponding to the current moment is taken as the current risk of vehicle icing, and the real-time risk corresponding to the previous moment is taken as the historical risk of vehicle icing. The current risk of vehicle icing and the historical risk of vehicle icing are weighted and fused to obtain the final vehicle icing risk. This achieves accurate prediction of the risk of vehicle window icing, thereby improving the accuracy of the determination of vehicle frost prevention and removal strategies and achieving effective prevention and removal of vehicle frost. It solves the technical problem that when predicting the current vehicle icing risk, only the environmental information at the current moment is considered, and the impact of historical environmental information on vehicle icing is not considered, which leads to inaccurate prediction of vehicle icing risk.

[0074] (2) By dividing the risk level of vehicle icing into three levels, namely low risk, medium risk and high risk, and corresponding to different treatment strategies, antifreeze is sprayed for preventive suppression when the risk is medium risk, and the warm air guide and glass micro-vibration are activated in conjunction when the risk is high risk and the user is about to use the vehicle to actively clear the ice. This achieves multi-mode collaborative operation of "prevention-clearing". Compared with the simple heating defrosting method, it has lower energy consumption and higher processing efficiency. Moreover, the defrosting work of the vehicle is completed before the user uses the vehicle, ensuring the timeliness of the user's vehicle use.

[0075] (3) By sensing the user's intention to use the vehicle, the high-power defrosting mode is triggered only, which avoids the system frequently starting the high-power execution unit when the user does not need to use the vehicle, effectively reducing the overall energy consumption and extending the service life of the vehicle's power battery.

[0076] (4) The system can automatically enter the low power consumption cycle monitoring state after the vehicle is turned off, without the need for manual intervention by the user. When the user gets in the car, the windows are already clean and usable, which significantly improves the convenience and driving safety of using the car in winter.

[0077] This invention also proposes a system for preventing and removing frost from car windows, comprising: The information acquisition unit is used to acquire real-time environmental information about the vehicle's location. The real-time risk calculation unit is used to calculate and determine the real-time risk of vehicle icing based on the real-time environmental information of the vehicle. The icing risk calculation unit is used to take the real-time risk corresponding to the current moment as the current risk of vehicle icing, take the real-time risk corresponding to the previous moment as the historical risk of vehicle icing, and perform weighted fusion of the current risk of vehicle icing and the historical risk of vehicle icing to obtain the final vehicle icing risk. The strategy determination unit is used to determine vehicle icing prevention and removal strategies based on the risk of vehicle icing.

[0078] In some embodiments, the real-time environmental information acquired by the information acquisition unit includes ambient dew point temperature, glass surface temperature, and ambient humidity. The real-time risk calculation unit is also used to calculate the difference between the glass surface temperature and the ambient dew point temperature as the temperature difference at a set time. The humidity weighting factor is calculated and determined based on the ambient humidity. The temperature difference is taken as a negative number and multiplied by the humidity weighting factor to calculate and determine the real-time risk of vehicle icing.

[0079] In some embodiments, the icing risk calculation unit is further configured to obtain the real-time risks corresponding to multiple previous times at the current time, and to use the real-time risks corresponding to previously set times as historical time risks; The impact weight of the historical risk is calculated and determined based on the time difference between the corresponding time of the historical risk and the current time. The historical risk of vehicle icing is obtained by multiplying the risk of each historical moment of vehicle icing by its corresponding impact weight and then summing the results.

[0080] In some embodiments, the strategy determining unit is further configured to determine a vehicle icing prevention and removal strategy based on the vehicle icing risk, including: Determine the vehicle icing risk level based on the vehicle's icing risk. When the vehicle icing risk level is medium, inhibit the further formation of vehicle frost; When the vehicle icing risk level is high, determine whether the user is about to use the vehicle; When it is determined that the user is about to use the vehicle, the system will control the vehicle to defrost the windows.

[0081] In some embodiments, the strategy determination unit is further configured to determine that the vehicle icing risk level is low risk when the vehicle icing risk is less than or equal to a set first risk threshold. When the risk of vehicle icing is less than or equal to the set second risk threshold, but greater than the set first risk threshold, the vehicle icing risk level is determined to be medium risk. When the risk of vehicle icing exceeds the set second risk threshold, the vehicle icing risk level is determined to be high risk.

[0082] It should be noted that the above-described window frost prevention and removal system is only illustrated by the division of the functional modules described above. In practical applications, the functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. Furthermore, the window frost prevention and removal system and the window frost prevention and removal method embodiment provided above belong to the same concept, and their specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0083] This invention proposes a vehicle window frost prevention and removal system. It includes an information acquisition unit to obtain real-time environmental information about the vehicle, a real-time risk calculation unit to calculate the real-time risk of vehicle icing based on this information, and an icing risk calculation unit that calculates the current real-time risk as the current icing risk and previous real-time risks as historical icing risks. The current and historical icing risks are weighted and fused to obtain the final vehicle icing risk, achieving accurate prediction of window icing risk. When the strategy determination unit determines the vehicle frost prevention and removal strategy based on this risk, the accuracy of the strategy determination is improved, achieving effective prevention and removal of vehicle frost. This system solves the technical problem that current vehicle icing risk prediction only considers the current environmental information and does not consider the impact of historical environmental information on vehicle icing, leading to inaccurate predictions.

[0084] The present invention also discloses a computer device, the device comprising: A processor, adapted to execute computer programs; A computer-readable storage medium storing a computer program, which, when executed by the processor, implements a method for preventing and removing frost from car windows disclosed in an embodiment of the present invention.

[0085] The computer device can be a portable mobile terminal, such as a smartphone, tablet, laptop, or desktop computer. Typically, a computer device includes a processor and memory.

[0086] A processor may include one or more processing cores, such as a core processor or a core processor. The processor may be implemented using at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array). The processor may also include a main processor and coprocessors. 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, the processor may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content required to be displayed on the screen. In some embodiments, the processor may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0087] The memory may include one or more computer-readable storage media, which may be non-transitory. The memory 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 are used to store at least one computer program, which is executed by a processor to implement the intelligent vehicle control method provided in the method embodiments of this application.

[0088] In some embodiments, the computer device may also optionally include: a peripheral device interface and at least one peripheral device. The processor, memory, and peripheral device interface can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface via a bus, signal line, or circuit board. Specifically, the peripheral device includes at least one of: radio frequency circuitry, a display screen, a camera assembly, audio circuitry, and a power supply.

[0089] Peripheral device interfaces can be used to connect at least one I / O (Input / Output) related peripheral device to the processor and memory. In some embodiments, the processor, memory, and peripheral device interface are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor, memory, and peripheral device interface can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0090] Radio frequency (RF) circuits are used to receive and transmit RF signals, also known as electromagnetic signals. RF circuits communicate with communication networks and other communication devices via electromagnetic signals. RF circuits convert electrical signals into electromagnetic signals for transmission, or convert received electromagnetic signals back into electrical signals. In some embodiments, the RF circuit includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, etc. The RF circuit can communicate with other terminals through at least one wireless communication protocol. These wireless communication protocols include, but are not limited to: the World Wide Web, metropolitan area networks, intranets, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and / or WiFi (Wireless Fidelity) networks. In some embodiments, the RF circuit may also include circuitry related to NFC (Near Field Communication), which is not limited in this application.

[0091] The present invention also discloses a computer-readable storage medium storing a computer program adapted to be loaded by a processor and executed by a method for preventing and removing frost from car windows as disclosed in the embodiments of the present invention.

[0092] The present invention also discloses a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements a method for preventing and removing frost from car windows disclosed in the embodiments of the present invention.

[0093] The method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor. The software modules can reside in readily available storage media in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, detailed descriptions are omitted here.

[0094] Those skilled in the art will recognize that the units and algorithm steps described in conjunction with the embodiments herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0095] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for preventing and removing frost from car windows, characterized in that, include: Obtain real-time environmental information of the vehicle; Based on the real-time environmental information of the vehicle, the real-time risk of vehicle icing is calculated and determined; The current real-time risk is taken as the current risk of vehicle icing, and the real-time risks corresponding to previous times are taken as the historical risks of vehicle icing. The current risk of vehicle icing and the historical risk of vehicle icing are weighted and merged to obtain the final risk of vehicle icing. Determine vehicle icing prevention and removal strategies based on the risk of vehicle icing.

2. The method for preventing and removing frost from car windows as described in claim 1, characterized in that, Real-time environmental information includes ambient dew point temperature, glass surface temperature, and ambient humidity; Calculate the difference between the glass surface temperature and the ambient dew point temperature as the temperature difference at the set time. The humidity weighting factor is calculated and determined based on the ambient humidity. The temperature difference is taken as a negative number and multiplied by the humidity weighting factor to calculate and determine the real-time risk of vehicle icing.

3. The method for preventing and removing frost from car windows as described in claim 2, characterized in that, The ambient dew point temperature is calculated based on the ambient temperature and humidity.

4. The method for preventing and removing frost from car windows as described in claim 1, characterized in that, Obtain the real-time risks corresponding to multiple previous times at the current moment, and use the real-time risks corresponding to previously set times as historical time risks; The impact weight of the historical risk is calculated and determined based on the time difference between the corresponding time of the historical risk and the current time. The historical risk of vehicle icing is obtained by multiplying the risk of each historical moment of vehicle icing by its corresponding impact weight and then summing the results.

5. The method for preventing and removing frost from car windows as described in claim 1, characterized in that, Based on the risk of vehicle icing, determine vehicle icing prevention and removal strategies, including: Determine the vehicle icing risk level based on the vehicle's icing risk. When the vehicle icing risk level is medium, inhibit the further formation of vehicle frost; When the vehicle icing risk level is high, determine whether the user is about to use the vehicle; When it is determined that the user is about to use the vehicle, the system will control the vehicle to defrost the windows.

6. The method for preventing and removing frost from car windows as described in claim 5, characterized in that, When the risk of vehicle icing is less than or equal to the set first risk threshold, the vehicle icing risk level is determined to be low risk. When the risk of vehicle icing is less than or equal to the set second risk threshold, but greater than the set first risk threshold, the vehicle icing risk level is determined to be medium risk. When the risk of vehicle icing exceeds the set second risk threshold, the vehicle icing risk level is determined to be high risk.

7. A system for preventing and removing frost from car windows, characterized in that, include: The information acquisition unit is used to acquire real-time environmental information about the vehicle's location. The real-time risk calculation unit is used to calculate and determine the real-time risk of vehicle icing based on the real-time environmental information of the vehicle. The icing risk calculation unit is used to take the real-time risk corresponding to the current moment as the current risk of vehicle icing, take the real-time risk corresponding to the previous moment as the historical risk of vehicle icing, and perform weighted fusion of the current risk of vehicle icing and the historical risk of vehicle icing to obtain the final vehicle icing risk. The strategy determination unit is used to determine vehicle icing prevention and removal strategies based on the risk of vehicle icing.

8. An electronic device, characterized in that, The device includes: A processor, adapted to execute computer programs; A computer-readable storage medium storing a computer program, which, when executed by the processor, implements a method for preventing and removing frost from car windows as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program adapted to be loaded by a processor and executed by a method for preventing and removing frost from car windows according to any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements a method for preventing and removing frost from car windows as described in any one of claims 1-6.

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