Vehicle window system, control method, vehicle and storage medium

Abstract

The invention relates to a vehicle window system which comprises vehicle window glass, a sensing subsystem, a control subsystem and an execution subsystem. The vehicle window glass comprises a plurality of functional modules; the sensing subsystem is used for collecting internal and external environment data; the control subsystem is used for determining a target mode through a preset strategy according to the internal and external environment data of the vehicle; analyzing through a preset analysis model according to the data of the environment inside and outside the vehicle and a rule of a target mode to obtain a control instruction for controlling an execution subsystem; a control instruction is sent to the execution subsystem; and the execution subsystem is used for responding to the control instruction so as to enable the plurality of function modules to execute operations corresponding to the control instruction. The invention further provides a control method, the vehicle and a storage medium. The functions of the vehicle window system are enriched, the control method of the vehicle window system is optimized, the regulation and control requirements of the vehicle window system in part of complex scenes can be better met, and the driving safety and the vehicle using experience are improved.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, specifically to a window system, control method, vehicle, and storage medium. Background Technology

[0002] Some vehicles are equipped with electrochromic glass in their window systems. While electrochromic glass can respond to changes in light intensity, it suffers from limited functionality. To enrich the functionality of the window system, some electrochromic glass systems have added heating wires to heat and defog the glass. However, existing window systems may have the following technical problems: Although electrochromic glass with an electric heating wire can defog and dim, it still has limited functionality. Existing window systems are unable to meet the needs of multi-parameter coordinated control in some complex scenarios, which negatively impacts the user experience. Moreover, in some complex scenarios, existing window systems often require drivers to manually adjust them frequently, which may distract the driver and negatively impact driving safety. In some scenarios, existing window systems struggle to adjust window parameters promptly, leading to driver exposure to strong ultraviolet radiation and glare, negatively impacting driving safety. Even with electrochromic glass in some window systems that can respond quickly and adjust light transmittance, sudden changes in the external environment can still significantly affect the driver. For example, when entering or exiting a tunnel, the drastic change in outside light can still cause glare for the driver, even if the window system adjusts its transmittance immediately upon detecting the change. Summary of the Invention

[0003] The purpose of this invention is to provide a window system, control method, vehicle, and storage medium to alleviate or eliminate at least one of the aforementioned technical problems.

[0004] The present invention provides a vehicle window system, comprising a window glass, a sensing subsystem, a control subsystem, and an execution subsystem; The vehicle window glass includes multiple functional modules; The sensing subsystem is used to collect data on the internal and external environment of the vehicle; The control subsystem is used to: determine a target mode based on the vehicle's internal and external environmental data using a preset strategy; analyze the target mode's internal and external environmental data using a preset analysis model according to the rules of the target mode to obtain control commands for controlling the execution subsystem; and send the control commands to the execution subsystem. The execution subsystem is used to: respond to the control command so that the plurality of functional modules perform operations corresponding to the control command.

[0005] Optionally, the control subsystem is further configured to: receive vehicle network data, analyze the vehicle internal and external environment data and the vehicle network data through the preset analysis model, and obtain control commands for controlling the execution subsystem at a future time.

[0006] Optionally, the preset analysis model is a quantized neural network model.

[0007] Optionally, the plurality of functional modules include an electric heating layer, an electrochromic layer, and a ventilation layer, wherein the ventilation layer is provided with microporous air ducts, which are adapted to constitute at least a portion of the vehicle's ventilation passage.

[0008] Optionally, the sensing subsystem includes a light intensity sensor, an ultraviolet (UV) sensor, a temperature sensor, a humidity sensor, an infrared human body sensor, and a carbon dioxide sensor. The light intensity sensor is used to collect outside light intensity data, the UV sensor is used to collect outside UV data, the temperature sensor is used to collect inside and / or outside temperature data, the humidity sensor is used to collect inside and / or outside humidity data, the infrared human body sensor is used to collect inside and / or outside occupant data, and the carbon dioxide sensor is used to collect inside carbon dioxide data.

[0009] The present invention also proposes a control method suitable for controlling the vehicle window system described in any of the above claims, the control method comprising the following steps: Acquire data on the vehicle's internal and external environment; Based on the vehicle's internal and external environmental data, a target mode is determined using a preset strategy; Based on the vehicle's internal and external environmental data, and in accordance with the rules of the target mode, the data is analyzed using a preset analysis model to obtain control commands for the control execution subsystem. The control command is sent to the execution subsystem to cause the plurality of functional modules to perform operations corresponding to the control command.

[0010] Optionally, the following steps may also be included: Acquire vehicle network data; Based on the vehicle's internal and external environmental data and the vehicle network data, the preset analysis model is used to analyze and obtain control commands for controlling the execution subsystem at a future time.

[0011] Optionally, the step of analyzing the vehicle's internal and external environmental data according to the rules of the target pattern using a preset analysis model includes the following steps: According to the degree of relevance with the target pattern, weights are assigned to each parameter in the vehicle interior and exterior environment data to obtain the data to be analyzed. The data to be analyzed is analyzed using the preset analysis model.

[0012] The present invention also proposes a vehicle including the window system described in any of the preceding claims.

[0013] The present invention also proposes a storage medium storing a computer program, which, when executed by a processor, implements the control method described in any of the preceding claims.

[0014] This invention enriches the functions of the vehicle window system, optimizes the control method of the vehicle window system, and can better meet the adjustment needs of the vehicle window system in some complex scenarios, which helps to improve driving safety and user experience. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the window system described in some embodiments; Figure 2 This is a schematic diagram of the structure of the vehicle window glass described in some embodiments; Figure 3 This is a schematic diagram of the ventilation layer of the vehicle window glass described in some embodiments; Figure 4 This is a flowchart of the control method described in some embodiments.

[0016] In the diagram, 1—window system, 2—sensing subsystem, 3—control subsystem, 4—execution subsystem, 5—window glass, 51—glass base layer, 52—ventilation layer, 53—electric heating layer, 54—electrochromic layer, 55—protective layer, 521—first edge, 522—second edge, 523—microporous air duct. Detailed Implementation

[0017] The embodiments of the present invention will be described below with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for illustrating the present invention and not for limiting the scope of protection of the present invention.

[0018] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. The illustrations only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0019] like Figure 1The vehicle window system 1 shown includes a window glass 5, a sensing subsystem 2, a control subsystem 3, and an execution subsystem 4; The car window glass 5 includes multiple functional modules; Perception subsystem 2 is used to collect data on the internal and external environment of the vehicle; The control subsystem 3 is used to: determine the target mode based on the vehicle's internal and external environmental data through a preset strategy; analyze the target mode based on the vehicle's internal and external environmental data through a preset analysis model according to the rules of the target mode to obtain control commands for controlling the execution subsystem 4; and send the control commands to the execution subsystem 4. The execution subsystem 4 is used to respond to control commands so that multiple functional modules perform operations corresponding to the control commands.

[0020] By adopting the above technical solution, the control subsystem 3 determines the target mode through a preset strategy and analyzes it through a preset analysis model to obtain control commands. The control commands are then used to control the execution subsystem 4 to adjust the state of multiple functional modules, thereby achieving multi-parameter coordinated control. This can improve the adaptability of the window system 1 to some complex environments, thereby improving driving safety and user experience.

[0021] In some embodiments, the control subsystem 3 is further configured to: receive vehicle network data, analyze the vehicle internal and external environment data and vehicle network data through a preset analysis model, and obtain control instructions for controlling the execution subsystem 4 at a future time.

[0022] By adopting the above technical solution, based on vehicle network data, the preset analysis model can predict possible scenarios during subsequent driving, and thus can adjust the state of the car window glass 5 in advance for possible scenarios, preventing the driver from being greatly affected by drastic changes in the external environment, which helps to improve driving safety.

[0023] In practical implementation, vehicles can receive vehicle-to-everything (V2X) data from the cloud through various wireless communication technologies, such as cellular, Wi-Fi, V2X, and satellite. The vehicle's onboard communication unit receives the wireless signals, processes them to obtain V2X data, and then sends the V2X data to the onboard gateway. The onboard gateway routes the V2X data to the control subsystem 3. V2X data typically includes map data, weather data, navigation data, and traffic data.

[0024] As a preferred example, the aforementioned future moment is the moment preceding a drastic change in the external environment. In practical implementation, a pre-defined analysis model can predict the moment of a drastic change in the external environment based on map data, weather data, navigation data, and traffic data, and then determine a moment preceding the drastic change as the future moment. The time interval between the future moment and the drastic change moment can be a preset value or a calculated value determined based on the time required for multiple functional modules to complete the corresponding operations of executing and controlling commands.

[0025] For example, the neural network model predicts based on vehicle network data that the vehicle will exit the tunnel at a moment of dramatic change, and that the external light will recover after exiting the tunnel. It will take 3 seconds to adjust the light transmittance of the window glass 5. The future moment is determined to be 3 seconds before the moment of dramatic change, and the light transmittance of the window glass 5 will be gradually changed at the future moment.

[0026] By adjusting the state of the car window glass 5 in advance, one can better cope with drastic changes in the external environment. Furthermore, by adjusting the state of the car window glass 5 in advance, a method that has less impact on the driver and passengers can be used. For example, the light transmittance of the car window glass 5 can be adjusted gradually, rather than abruptly, reducing the impact on the driver and passengers and allowing them to better adapt to changes in the environment.

[0027] In some embodiments, the preset analysis model is a quantized neural network model. Using a neural network model enables the aforementioned functions and meets the usage requirements of the vehicle window system 1. The quantized neural network model offers shorter analysis latency, requires fewer resources, and is easy to implement.

[0028] As a concrete example, the training and deployment process of a neural network model includes: collecting 1000 sets of real-world driving data, covering urban, highway, and extreme weather conditions, and labeling parameters such as light transmittance, heating power, and ventilation volume in the driving data as a dataset. The neural network model is then trained and validated using this dataset to obtain a satisfactory model. Next, the neural network model is quantized, compressing it to an 8-bit integer. The neural network model can be a TensorFlow Lite model; after quantization, RAM usage is ≤50KB and inference latency is ≤10ms.

[0029] In some embodiments, the multiple functional modules include an electrically heated layer 53, an electrochromic layer 54, and a ventilation layer 52. The ventilation layer 52 is provided with a microporous air duct 523, which is adapted to form at least a portion of the vehicle's ventilation channel. The microporous air duct 523 enables vehicle ventilation at the window glass 5, enriching the functionality of the window system 1.

[0030] As a specific example, such as Figure 3 As shown, the microporous air duct 523 extends from the first edge 521 to the second edge 522 of the ventilation layer 52, and multiple microporous air ducts 523 can be arranged within the ventilation layer 52. Preferably, the microporous air duct 523 extends from the upper edge to the lower edge of the ventilation layer 52. In specific implementations, the microporous air duct 523 can be laser-drilled micropores with a pore size ≤ 50 μm.

[0031] In some embodiments, such as Figure 2 As shown, the vehicle window glass 5 includes a glass base layer 51, a ventilation layer 52, an electric heating layer 53, an electrochromic layer 54, and a protective layer 55 arranged sequentially. The glass base layer 51 provides support, and the protective layer 55 enhances the protection of the ventilation layer 52, the electric heating layer 53, and the electrochromic layer 54.

[0032] As a specific example, the glass substrate 51 is tempered glass, the electrochromic layer 54 uses a WO3 / LiTaO3 scheme, the electric heating layer 53 includes a silver nanowire mesh, the ventilation layer 52 includes a laser micropore array, and the protective layer 55 is made of impact-resistant PC material. The integrated functions of the vehicle window glass 5 include: light transmittance adjustment from 10% to 90%, zoned heating with a power density of 0 to 100 W / m², and noiseless ventilation.

[0033] In practical implementation, the electrochromic layer 54 is realized as follows: a tungsten oxide thin film with a thickness of 200 nm can be deposited on the glass substrate 51 using magnetron sputtering. The tungsten oxide thin film has a thickness of 50 nm, and the ion conductor layer has a thickness of 50 nm. The electrodes can use ITO transparent conductive films with a sheet resistance of 8 Ω / □. The driving circuit of the electrochromic layer 54 can adopt an H-bridge topology, supporting bidirectional voltage output from 0 to 3V, a maximum current of 200 mA, and a transmittance adjustment response time ≤0.8 seconds.

[0034] In some embodiments, the sensing subsystem 2 includes a light intensity sensor, an ultraviolet (UV) sensor, a temperature sensor, a humidity sensor, an infrared human body sensor, and a carbon dioxide sensor. The light intensity sensor is used to collect outside light intensity data, the UV sensor is used to collect outside UV data, the temperature sensor is used to collect inside and / or outside temperature data, the humidity sensor is used to collect inside and / or outside humidity data, the infrared human body sensor is used to collect inside and / or outside occupant data, and the carbon dioxide sensor is used to collect inside carbon dioxide data. By employing the above technical solution, environmental data inside and outside the vehicle that meet the control requirements of the window system 1 can be collected, which helps to better control the window system 1.

[0035] As a specific example, light intensity and ultraviolet sensors are embedded in the four corner frames of the window and connected to the control subsystem 3 via a flexible circuit board; an infrared human body sensor is installed at the rearview mirror position and is used to detect the driver's head coordinates.

[0036] As a specific example, the infrared human body sensor can be the AMG8833 sensor, the light intensity sensor can be the TSL2561 sensor, the ultraviolet sensor can be the ML8511 sensor, the temperature and humidity sensor can be the DHT22 sensor, and the carbon dioxide sensor can be the MH-Z19B sensor. The sensor data fusion method can be: noise reduction based on the Kalman filter algorithm to construct a dynamic model of the vehicle's internal and external environment.

[0037] As a specific example, the hardware of control subsystem 3 can be an STM32H743 microcontroller, which supports communication with the vehicle ECU via CAN bus. The software functionality of control subsystem 3 includes a hybrid decision model, comprising a rule engine and a lightweight neural network model. The rule engine implements preset strategies; for example, the preset strategy prioritizes safety mode over comfort mode, and comfort mode over energy-saving mode. The rule engine can determine the target mode based on data from the vehicle's internal and external environments. The lightweight neural network model can use the TensorFlow Lite framework, taking sensor data as input and outputting transmittance, heating power, and ventilation level.

[0038] As a specific example, control subsystem 3 can also perform user adaptive learning, record user manual operation data, and dynamically update control parameters.

[0039] As a specific example, the execution subsystem 4 consists of a first execution module, a second execution module, and a third execution module. The first execution module is an electrochromic driving circuit corresponding to the electrochromic layer 54. The electrochromic driving circuit can adopt an H-bridge topology and can be electrically connected to the electrochromic layer 54. The second execution module is a zoned heating control circuit corresponding to the electric heating layer 53. The zoned heating control circuit can adopt a PWM voltage regulation scheme and can be electrically connected to the electric heating layer 53. The third execution module is a piezoelectric ceramic micro ventilation device corresponding to the ventilation layer 52. The piezoelectric ceramic micro ventilation device has a flow rate of 0.5 L / s and a noise level of <30 dB. The piezoelectric ceramic micro ventilation device can be connected to the ventilation layer 52 through a pipe or channel.

[0040] like Figure 4 As shown, in some embodiments, the present invention also proposes a control method suitable for controlling the window system 1 described in any of the above claims. The control method includes the following steps: S100: Acquires data on the internal and external environment of the vehicle; S200: Determines the target mode based on preset strategies using data from the vehicle's internal and external environment; S300: Based on the data of the vehicle's internal and external environment, and in accordance with the rules of the target mode, the system performs analysis through a preset analysis model to obtain control commands for the control execution subsystem 4; S400: Sends control commands to execution subsystem 4 to cause multiple functional modules to perform operations corresponding to the control commands.

[0041] By adopting the above technical solution, the target mode is determined by a preset strategy and analyzed by a preset analysis model to obtain control commands. The control commands are used to control the execution subsystem 4 to adjust the state of multiple functional modules, which can realize multi-parameter coordinated control, improve the adaptability of the window system 1 to some complex environments, and thus improve driving safety and user experience.

[0042] In practice, the control method described above can be executed by the control subsystem 3 of the window system 1. The control subsystem 3 can be composed of one or more vehicle control units.

[0043] In specific implementation, the operation of multiple functional modules in accordance with the control commands is as follows: the electrochromic layer 54 can linearly adjust the light transmittance through voltage, the heating layer uses a PID algorithm to control the temperature, and the piezoelectric ceramic micro ventilation device starts and stops in stages according to the carbon dioxide concentration in the vehicle.

[0044] In some embodiments, the control method further includes the following steps: Acquire vehicle network data; Based on data from the vehicle's internal and external environment and vehicle network data, the system analyzes the data using a pre-set analysis model to obtain control commands for controlling the execution subsystem 4 at future moments.

[0045] By adopting the above technical solution, based on vehicle network data, the preset analysis model can predict possible scenarios during subsequent driving, and thus can adjust the state of the car window glass 5 in advance for possible scenarios, preventing the driver from being greatly affected by drastic changes in the external environment, which helps to improve driving safety.

[0046] As a preferred example, the aforementioned future moment is a moment preceding a drastic change in the external environment. In specific implementation, the control method further includes the following steps: a preset analysis model predicts the moment of a drastic change in the external environment based on map data, weather data, navigation data, and traffic data, and determines a moment preceding the drastic change moment as the future moment. Furthermore, the time interval between the future moment and the drastic change moment can be a preset value or a calculated value determined based on the time required for multiple functional modules to complete the operations corresponding to the control commands.

[0047] In some embodiments, the analysis based on in-vehicle and out-of-vehicle environmental data, according to the rules of the target pattern, and using a preset analysis model includes the following steps: Weights are assigned to each parameter in the vehicle's internal and external environmental data according to their relevance to the target pattern in order to obtain the data to be analyzed. The data to be analyzed is analyzed using a pre-set analysis model.

[0048] By adopting the above technical solution and setting the weights of various parameters of the in-vehicle and out-of-vehicle environmental data according to different target modes, it is possible to obtain an in-vehicle glass condition solution that is more compatible with the target mode.

[0049] In practical implementation, after the perception subsystem 2 collects sensor data corresponding to the vehicle's internal and external environmental data, it can fuse and filter the sensor data to obtain the vehicle's internal and external environmental data. For example, after the sensor data is sampled by a 12-bit ADC, noise is eliminated through Kalman filtering. As a specific example, fusing and filtering the sensor data can eliminate interference from sudden changes in illumination in tunnel scenarios. After obtaining the vehicle's internal and external environmental data, a weight matrix of the vehicle's internal and external environmental data can be constructed according to the rules of the target mode. For example, the ultraviolet index accounts for 60% of the safety decision, and temperature accounts for 40% of the comfort decision.

[0050] In some embodiments, collecting data on the internal and external environment of the vehicle includes: cyclically collecting data on the internal and external environment of the vehicle according to a preset cycle. In specific implementation, signals from each sensor are collected simultaneously each time data on the internal and external environment of the vehicle is collected.

[0051] In some embodiments, the control method further includes the following steps: acquiring user interaction data and generating control instructions for controlling the execution subsystem 4 based on the user interaction data; Based on user interaction data, the system determines the user's window control habits and adjusts preset strategies and analysis models accordingly. For example, it adjusts the weighting rules for various parameters based on these habits. This adjustment ensures that the analyzed control commands better match the user's habits, improving the user's driving experience.

[0052] As a specific example, the control method includes the following steps: Data acquisition: Environmental parameters are collected synchronously at a 10ms cycle. The system determines the target mode as follows: when the ultraviolet radiation level is greater than 8 or the light intensity is greater than 80,000 lux, the target mode is determined to be the safety mode, and the light transmittance of the window glass 5 is forcibly controlled to be ≤20%; when the conditions for entering the comfort mode are met, the target mode is determined to be the comfort mode, and the state of the window glass 5 is adjusted according to the user's preset, such as adjusting the target position: light transmittance 40% + interior temperature 25℃; when the conditions for entering the energy-saving mode are met, the target mode is determined to be the energy-saving mode, and the light transmittance and air conditioning are adjusted in conjunction to maintain the interior temperature fluctuation ≤±2℃.

[0053] As a specific example, in a tunnel scenario, the control method includes the following steps: when the light intensity is detected to suddenly drop from 100,000 lux to 500 lux, it is determined that the vehicle has entered the tunnel; the rule engine triggers a safety mode, controlling the light transmittance of the window glass 5 to increase from 20% to 80%; the neural network model predicts that the light intensity will return to normal after the tunnel based on vehicle network data, and the neural network model predicts the time when the vehicle exits the tunnel, controlling the light transmittance of the window glass 5 to gradually change 3 seconds before the exit time to prevent glare.

[0054] As a specific example, in a rainy scenario, the control method includes the following steps: When the outside temperature is detected to be 10℃, the outside humidity is 95%, and the inside carbon dioxide concentration is 1500ppm, the entire heating layer is controlled to operate at 40W / m², and the piezoelectric ceramic micro-ventilation device is controlled to intermittently start and stop. The working cycle is 30s / 10s to maintain the inside carbon dioxide concentration ≤1000ppm, and the light transmittance of the window glass is controlled to maintain 70% to reduce glare from the headlights. Using the above solution, a balance between anti-fogging and energy efficiency in rainy weather can be achieved.

[0055] As a specific example, in a nighttime parking scenario, the control method includes the following steps: When the ambient light intensity is 5 lux and the infrared human body sensor detects a person approaching within 2 meters outside the vehicle, the light transmittance of the car window 5 is adjusted to 10%, switching to privacy mode; if there is no driver presence signal within 10 seconds, the vehicle alarm system is activated, triggering an audible and visual alarm. In practice, the user can remotely restore the light transmittance of the car window 5 to 50% and turn on the interior lighting via an app.

[0056] This invention provides a system and method that can sense multi-dimensional environmental parameters such as light, temperature, humidity, and human position in real time, and dynamically adjust the light transmittance of vehicle windows, interior temperature, and interior humidity through intelligent algorithms, which helps vehicles achieve safe, comfortable, and energy-saving adaptive optimization in all scenarios.

[0057] The present invention also proposes a vehicle including the window system 1 described in any of the preceding claims. The vehicle may be, but is not limited to, a pure electric vehicle (PEV / BEV), a hybrid electric vehicle (HEV), a range-extended electric vehicle (REEV), a plug-in hybrid electric vehicle (PHEV), a new energy vehicle, or a gasoline-powered vehicle.

[0058] The present invention also proposes a storage medium storing a computer program, which, when executed by a processor, implements the control method described in any of the above claims.

[0059] The above embodiments are merely preferred embodiments provided to fully illustrate the present invention, and the scope of protection of the present invention is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on the present invention are all within the scope of protection of the present invention. In the description of this specification, the reference to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., means that a specific feature, structure, material, or characteristic associated with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. Furthermore, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

Claims

1. A vehicle window system, characterized in that, It includes the car window glass (5), the sensing subsystem (2), the control subsystem (3) and the execution subsystem (4); The vehicle window glass (5) includes multiple functional modules; The sensing subsystem (2) is used to collect data on the internal and external environment of the vehicle; The control subsystem (3) is used to: determine the target mode based on the vehicle interior and exterior environment data through a preset strategy; analyze the vehicle interior and exterior environment data according to the rules of the target mode through a preset analysis model to obtain control instructions for controlling the execution subsystem (4); and send the control instructions to the execution subsystem (4). The execution subsystem (4) is used to: respond to the control command so that the plurality of functional modules perform operations corresponding to the control command.

2. The vehicle window system according to claim 1, characterized in that, The control subsystem (3) is also used to: receive vehicle network data, analyze the vehicle internal and external environment data and the vehicle network data through the preset analysis model, and obtain control instructions for controlling the execution subsystem (4) at a future time.

3. The vehicle window system according to claim 1, characterized in that, The preset analysis model is a quantized neural network model.

4. The vehicle window system according to claim 1, characterized in that, The multiple functional modules include an electric heating layer (53), an electrochromic layer (54), and a ventilation layer (52), wherein the ventilation layer (52) is provided with a microporous air duct (523), which is adapted to form at least a part of the vehicle's ventilation channel.

5. The vehicle window system according to claim 1, characterized in that, The sensing subsystem (2) includes a light intensity sensor, an ultraviolet sensor, a temperature sensor, a humidity sensor, an infrared human body sensor, and a carbon dioxide sensor. The light intensity sensor is used to collect light intensity data outside the vehicle, the ultraviolet sensor is used to collect ultraviolet data outside the vehicle, the temperature sensor is used to collect temperature data inside the vehicle and / or temperature data outside the vehicle, the humidity sensor is used to collect humidity data inside the vehicle and / or humidity data outside the vehicle, the infrared human body sensor is used to collect data on people inside the vehicle and / or people outside the vehicle, and the carbon dioxide sensor is used to collect carbon dioxide data inside the vehicle.

6. A control method, characterized in that, The control method is suitable for controlling a vehicle window system as described in any one of claims 1-5, and the control method includes the following steps: Acquire data on the vehicle's internal and external environment; Based on the vehicle's internal and external environmental data, a target mode is determined using a preset strategy; Based on the vehicle's internal and external environmental data, and in accordance with the rules of the target mode, the system performs analysis using a preset analysis model to obtain control commands for the control execution subsystem (4). The control command is sent to the execution subsystem (4) to cause the plurality of functional modules to perform operations corresponding to the control command.

7. The control method according to claim 6, characterized in that, It also includes the following steps: Acquire vehicle network data; Based on the vehicle's internal and external environmental data and the vehicle network data, the preset analysis model is used to analyze and obtain control commands for controlling the execution subsystem (4) at a future time.

8. The control method according to claim 6, characterized in that, The step of analyzing the vehicle's internal and external environmental data according to the rules of the target pattern using a preset analysis model includes the following steps: According to the degree of relevance with the target pattern, weights are assigned to each parameter in the vehicle interior and exterior environment data to obtain the data to be analyzed. The data to be analyzed is analyzed using the preset analysis model.

9. A vehicle, characterized in that, Includes the window system as described in any one of claims 1-5.

10. A storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the control method as described in any one of claims 6-8.

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