A color intelligent control method and system based on electrochromic glass

Abstract

The present invention discloses a method and system for intelligent color control based on electrochromic glass, which relates to the field of electrochromic technology. The method comprises the following steps: collecting spectral data of the current environment in real time; analyzing the solar energy conversion efficiency using the spectral data and calculating the current electric energy value available for control; analyzing historical environmental data and historical user control data using a self-learning algorithm in combination with the available electric energy value to predict user preferences; generating an intelligent glass color control scheme based on the user preference prediction results and the spectral data; and applying dynamic voltage to each area through a distributed circuit based on the intelligent glass color control scheme to control the color. By embedding a multispectral sensor and calculating the current available electric energy value in combination with the solar energy conversion efficiency, and dynamically calculating the driving voltage for each area based on user preferences and environmental spectral data, the problem of control deviation caused by material aging or uneven voltage distribution is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of electrochromic technology, and in particular to a method and system for intelligently controlling the color of electrochromic glass. Background Art

[0002] With the increasing demand for intelligent and energy-efficient architecture and the automotive industry, electrochromic glass technology has garnered widespread attention. However, traditional electrochromic glass control methods typically rely on fixed preset adjustment parameters or simple environmental feedback mechanisms, making them difficult to adapt to changing lighting conditions and personalized user needs, resulting in unsatisfactory control effects.

[0003] Existing technologies have the following shortcomings in intelligent control: First, they lack a comprehensive analysis of environmental spectral data and rely solely on light intensity or light information in a single band, making it difficult to accurately reflect the actual environment's requirements for glass color and transmittance; second, they fail to optimize based on user historical preferences and real-time power constraints, making it impossible to achieve a balance between user experience and energy efficiency. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a color intelligent control method based on electrochromic glass to solve the problem that the existing electrochromic glass technology cannot simultaneously take into account complex environmental changes, user personalized needs and power utilization efficiency.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a method for intelligent color control based on electrochromic glass, which comprises collecting spectral data of the current environment in real time through a multispectral sensor embedded in the electrochromic glass;

[0008] Use spectral data to analyze solar energy conversion efficiency and calculate the current amount of electrical energy available for regulation;

[0009] Combined with the available electric energy value, the self-learning algorithm analyzes historical environmental data and historical user control data to predict user preferences;

[0010] Generate intelligent glass color control solutions based on user preference prediction results and spectral data;

[0011] Based on the intelligent glass color control solution, dynamic voltage is applied to each area through distributed circuits to control the color.

[0012] As a preferred solution of the color intelligent control method based on electrochromic glass of the present invention, wherein: the multispectral sensor includes an ultraviolet sensor, a visible light sensor, an infrared sensor, a light angle sensor, a thermal sensor and an ambient light sensor;

[0013] The spectral data includes ultraviolet light intensity, visible light intensity, infrared light intensity, sunlight incident angle, ambient brightness and ambient temperature.

[0014] As a preferred solution of the color intelligent control method based on electrochromic glass of the present invention, the effective intensity of the incident light is calculated using spectral data and expressed as:

[0015] ;

[0016] in, represents the effective intensity of incident light, Indicates the comprehensive value of ultraviolet light intensity, visible light intensity and infrared light intensity. Indicates the angle of incidence of sunlight.

[0017] As a preferred solution of the color intelligent control method based on electrochromic glass described in the present invention, wherein: using the effective intensity of incident light to analyze the solar energy conversion efficiency and calculate the current electric energy value available for control, the method includes the following steps:

[0018] Based on the effective intensity of the incident light, the conversion power per unit area is calculated and expressed as,

[0019] ;

[0020] in, represents the conversion power per unit area, Represents the average photoelectric conversion efficiency of the photovoltaic layer;

[0021] Based on the conversion power per unit area, the total power generation is calculated and expressed as,

[0022] ;

[0023] in, Indicates the total generated power, represents the total effective area of the photovoltaic layer;

[0024] The total generated power is divided into two parts, one part is used for the glass drive unit, and the other part enters the energy storage unit;

[0025] The electrical energy of the glass drive unit is expressed as,

[0026] ;

[0027] in, Indicates the electrical energy supplied to the glass drive unit. Indicates the electrical energy required for current electrochromic glass regulation;

[0028] The electrical energy of the energy storage unit is expressed as,

[0029] ;

[0030] in, Indicates the electrical energy supplied to the energy storage unit.

[0031] As a preferred solution of the color intelligent control method based on electrochromic glass described in the present invention, the method includes the following steps: combining the available electric energy value, analyzing historical environmental data and user historical control data through a self-learning algorithm, and predicting user preferences.

[0032] Collect users' historical environment data and historical user control data, and perform normalization processing;

[0033] Based on the long short-term memory network, the user preference prediction model is obtained by inputting historical environment data and user historical control data for training;

[0034] Input the user's historical control data and current environment data into the trained user preference prediction model, and output the user's target light transmittance and color depth change target;

[0035] When the power of the glass drive unit meets the control requirements of the target transmittance and color change, it operates normally;

[0036] When the power of the glass drive unit is insufficient, the target light transmittance is reduced and the range of the color depth change target is adjusted.

[0037] As a preferred solution of the color intelligent control method based on electrochromic glass described in the present invention, wherein: generating a glass color intelligent control solution based on user preference prediction results and spectral data includes the following steps:

[0038] According to the target transmittance and ambient light intensity, the driving voltage to be applied is calculated and expressed as:

[0039] ;

[0040] in, Indicates the driving voltage that needs to be applied, represents the photoelectric response coefficient of the electrochromic material, Indicates the target transmittance;

[0041] According to the target color value, the voltage distribution of each area is calculated to achieve uniform color change, which is expressed as,

[0042] ;

[0043] in, represents the driving voltage of the corresponding area, represents the minimum driving voltage of the electrochromic material, represents the maximum driving voltage of the electrochromic material, Indicates the maximum value of brightness, Indicates the target brightness value, Represents the nonlinear tuning parameter of the response curve.

[0044] As a preferred solution of the color intelligent control method based on electrochromic glass of the present invention, wherein: based on the glass color intelligent control solution, dynamic voltage is applied to each area through a distributed circuit to perform color control, including the following steps:

[0045] Using a distributed circuit, the calculated driving voltage is applied to the electrochromic material of the glass;

[0046] Use a light sensor to monitor the actual light transmittance of each area and compare it with the target light transmittance. If the deviation exceeds the allowable range of light transmittance, adjust the driving voltage to compensate for the deviation.

[0047] A color sensor is used to detect the actual color value of each area and compare it with the target color. When the deviation exceeds the color allowable range, the voltage of the corresponding area is dynamically adjusted.

[0048] In a second aspect, the present invention provides a color intelligent control system based on electrochromic glass, comprising a multispectral data acquisition module responsible for collecting spectral data of the current environment in real time through a multispectral sensor embedded in the electrochromic glass;

[0049] The electric energy calculation module is responsible for using spectral data to analyze the solar energy conversion efficiency and calculate the current electric energy value available for regulation;

[0050] The user preference prediction module is responsible for combining the available electric energy value with historical environmental data and user historical control data through self-learning algorithms to predict user preferences;

[0051] The intelligent control scheme generation module is responsible for generating an intelligent glass color control scheme based on user preference prediction results and spectral data;

[0052] The dynamic voltage distribution and control module is responsible for applying dynamic voltage to each area through distributed circuits to perform color control based on the intelligent glass color control solution.

[0053] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the color intelligent control method based on electrochromic glass as described in the first aspect of the present invention is implemented.

[0054] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the method for intelligent color control based on electrochromic glass as described in the first aspect of the present invention is implemented.

[0055] The present invention achieves the following beneficial effects: by embedding a multispectral sensor to collect real-time environmental spectral data (including ultraviolet, visible light, infrared intensity, and illumination angle), and combining it with solar energy conversion efficiency to calculate the current available electrical energy value, precise energy management is achieved for electrochromic glass control. An AI self-learning algorithm analyzes historical user control data and environmental data, predicts user preferences, and generates personalized glass color control solutions, effectively improving the user experience. Furthermore, the driving voltage for each zone is dynamically calculated based on user preferences and environmental spectral data. Distributed circuits are used for precise control, and interpolation algorithms and compensation voltage mechanisms are employed to ensure smooth and uniform color changes, addressing control deviations caused by material aging or uneven voltage distribution. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0057] Figure 1 This is a flow chart of the color intelligent control method based on electrochromic glass in Example 1.

[0058] Figure 2 Schematic diagram of the color intelligent control system based on electrochromic glass in Example 1. DETAILED DESCRIPTION

[0059] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0060] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0061] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0062] Example 1, with reference to Figure 1 and Figure 2 , which is the first embodiment of the present invention, provides a color intelligent control method based on electrochromic glass, comprising the following steps:

[0063] S1. Using a multispectral sensor embedded in the electrochromic glass, the spectrum data of the current environment is collected in real time, including the following steps:

[0064] Multispectral sensors include ultraviolet sensors, visible light sensors, infrared sensors, light angle sensors, thermal sensors, and ambient light sensors;

[0065] Spectral data includes ultraviolet light intensity, visible light intensity, infrared light intensity, sunlight incident angle, ambient brightness and ambient temperature.

[0066] It should be noted that through multi-dimensional spectral data collection, environmental parameters that have a direct impact on the regulation of electrochromic glass can be accurately obtained, avoiding the problem of insufficient environmental information caused by the traditional single sensor collection method, and providing a detailed foundation for the calculation of solar energy conversion efficiency, user preference analysis and generation of intelligent control solutions in subsequent steps. At the same time, it can dynamically adapt to complex lighting environments, improve the comprehensiveness and real-time nature of environmental data collection, and provide accurate environmental input for intelligent glass control, thereby improving the system's response efficiency to environmental changes and the control accuracy.

[0067] S2. Analyze the solar energy conversion efficiency using spectral data and calculate the current electric energy value available for regulation, including the following steps:

[0068] Using the spectral data, the effective intensity of the incident light is calculated and expressed as,

[0069] ;

[0070] in, represents the effective intensity of incident light, Indicates the combined value of ultraviolet light intensity (unit: mW / cm²), visible light intensity (unit: mW / cm² / nm), and infrared light intensity (unit: mW / cm²). Indicates the incident angle of sunlight (unit: degree).

[0071] Based on the effective intensity of the incident light, the conversion power per unit area is calculated and expressed as,

[0072] ;

[0073] in, represents the conversion power per unit area, It represents the average photoelectric conversion efficiency of the photovoltaic layer (unit:%), which is the average efficiency of the photovoltaic layer within the working wavelength range, expressed as , and They are the working wavelength range of the photovoltaic layer (such as 400-750nm), Indicates the wavelength of visible light The light intensity at The wavelength range is 380-750nm, which is the light intensity distribution of different wavelengths. Indicates the photoelectric conversion efficiency, which is the long interval that the photovoltaic layer can absorb and convert into electrical energy;

[0074] Based on the conversion power per unit area, the total power generation is calculated and expressed as,

[0075] ;

[0076] in, Indicates the total generated power, Represents the total effective area of the photovoltaic layer (unit: m²), which refers to the area of the photovoltaic layer exposed to ambient light;

[0077] The total generated power is divided into two parts. One part is used for the glass drive unit, which drives the color control of the electrochromic glass, and the other part goes to the energy storage unit, which stores the remaining power for future use.

[0078] The electrical energy of the glass drive unit is expressed as,

[0079] ;

[0080] in, Indicates the power supplied to the glass drive unit (unit: W), Indicates the current electric energy required for electrochromic glass control (unit: W), The value is determined by the current state and target state of the glass. If the glass needs to significantly change its transmittance or color depth, Higher, if the glass state is close to the target state, then Lower;

[0081] When the total power When it is large enough, it will give priority to meeting the needs of the glass drive unit;

[0082] when When the power is turned off, all available power generation will be supplied to the glass drive unit first;

[0083] The electrical energy of the energy storage unit is expressed as,

[0084] ;

[0085] in, Indicates the electrical energy supplied to the energy storage unit (unit: W);

[0086] when ,but , the energy storage unit cannot obtain electrical energy;

[0087] when , the excess electrical energy is stored in the energy storage unit.

[0088] It should be noted that by calculating the effective intensity of incident light using spectral data and combining it with the photovoltaic layer's photoelectric conversion efficiency, the total generated power is further calculated and energy is rationally distributed to the glass drive unit and energy storage unit. This enables refined management from environmental spectral data to energy distribution, ensuring the continuity and reliability of glass regulation. Even in low-light conditions or high power consumption, basic functions can be maintained through a priority allocation mechanism. Through dynamic energy calculation and distribution, energy utilization efficiency is optimized, power waste or regulation interruptions are avoided, and the system's energy efficiency and stability are improved, providing sufficient and reliable power support for subsequent regulation.

[0089] S3, combining the available electric energy value, analyzing historical environmental data and user historical control data through self-learning algorithm, and predicting user preferences, including the following steps:

[0090] Collect the user's historical environment data and user historical control data, and normalize them to adapt them to the input format of the long short-term memory network model;

[0091] Based on the long short-term memory network, the user preference prediction model is obtained by inputting historical environmental data (such as real-time environmental parameters such as light intensity, indoor and outdoor temperature) and historical user control data (such as controlled transmittance and color change parameters) for training;

[0092] Input the user's historical control data and current environment data into the trained user preference prediction model, and output the user's target light transmittance and color depth change target;

[0093] It should be noted that the target light transmittance of the glass is automatically predicted based on the user's historical preferences and the current environment. For example, when the sun is strong, a lower light transmittance may be predicted to reduce glare, while at night, a higher light transmittance may be predicted to increase indoor lighting. The target value of the glass color is predicted to reflect the user's color preference. For example, on a sunny day, a light color (such as light blue) may be predicted to reduce heat absorption, and on a cloudy day, a dark color may be predicted to improve visual comfort.

[0094] When the power of the glass drive unit meets the control requirements of the target transmittance and color change, it operates normally;

[0095] When the power of the glass drive unit is insufficient, the target light transmittance is appropriately reduced and the range of the color depth change target is adjusted.

[0096] It should be noted that by normalizing historical data and using an LSTM model to train a user preference prediction model, the system can automatically adjust the glass's light transmittance and color changes under varying lighting and temperature conditions, thereby meeting individual user needs. This system not only dynamically responds to real-time environmental changes but also gradually optimizes control strategies through self-learning, enhancing the user experience. This is particularly true in high-frequency usage scenarios, reducing the need for manual adjustments. This intelligent upgrade from "passive response" to "active prediction" significantly improves control personalization and user satisfaction. Furthermore, in the event of insufficient power, the system adjusts the target value's fluctuation range, further achieving a balance between user experience and energy efficiency.

[0097] S4. Generate a glass color intelligent control solution based on the user preference prediction results and spectral data, including the following steps:

[0098] According to the target transmittance and ambient light intensity, the driving voltage required to control the glass transmittance is calculated and expressed as:

[0099] ;

[0100] in, Indicates the driving voltage that needs to be applied, It represents the photoelectric response coefficient of the electrochromic material, in volts (V), obtained through experimental calibration. Indicates the target light transmittance in percentage (%);

[0101] It should be noted that if the glass has a zone control function (such as different light transmittance in different zones), the corresponding driving voltage will be calculated for each zone separately. The maximum and minimum driving voltages are limited by the glass material to ensure that the driving voltage is within a safe range. If the calculated driving voltage exceeds the allowable range of the material, it will be limited to the maximum or minimum value.

[0102] According to the target color value, the voltage distribution of each area is calculated to achieve uniform color change, which is expressed as,

[0103] ;

[0104] in, Indicates the driving voltage of the corresponding area, in volts (V), Indicates the minimum driving voltage of the electrochromic material (corresponding to the maximum brightness, such as completely transparent state), Indicates the maximum driving voltage of the electrochromic material (corresponding to the minimum brightness of 0, such as completely opaque state), Indicates the maximum brightness, usually 255, corresponding to pure white. Indicates the target brightness value (converted from the target color, ranging from 0 to 255). ,in, 、 、 are the values of the red, green, and blue components (range 0-255), It represents the nonlinear adjustment parameter of the response curve, which is calibrated by experiments and usually ranges from 1.0 to 3.0. is a linear relationship, The color change response is steeper due to nonlinear relationship. The voltage transition between adjacent areas is calculated through interpolation algorithm to ensure smooth and uniform color change. If some areas have uneven response due to material aging or environmental factors, compensation voltage is provided.

[0105] It should be noted that the required driving voltage is calculated based on the target transmittance and color values, combined with the ambient light intensity, and the voltage distribution is optimized through interpolation algorithms and compensation mechanisms. Precise calculations and a zoning control mechanism improve the uniformity of glass transmittance and color changes, making it particularly suitable for electrochromic glass with zoning control capabilities, and particularly effective in large-scale applications. The dynamic generation of intelligent control solutions not only achieves precise matching of target transmittance and color, but also solves the problem of uneven control caused by material aging or environmental factors, further improving the aesthetics and practicality of the glass.

[0106] S5. Based on the intelligent glass color control solution, dynamic voltage is applied to each area through a distributed circuit to control the color, including the following steps:

[0107] Using a distributed circuit, the calculated driving voltage is applied to the electrochromic material of the glass;

[0108] Use a light sensor to monitor the actual light transmittance of each area and compare it with the target light transmittance. If the deviation exceeds the allowable range of light transmittance (such as 5%), adjust the driving voltage to compensate for the deviation.

[0109] Use a color sensor to detect the actual color value of each area and compare it with the target color. When the deviation exceeds the color tolerance range (such as 10 for RGB components), the voltage of the corresponding area is dynamically adjusted.

[0110] Furthermore, the circuit operating status of each area is detected (such as whether there is a short circuit, open circuit or voltage abnormality). If an abnormal area is found, it is recorded and an alarm signal is issued. At the same time, the voltage application to the abnormal area is stopped. Combined with the ambient light intensity and temperature data, it is determined whether the target value needs to be dynamically adjusted (such as appropriately increasing the transmittance when cloud cover is blocked or the ambient light changes).

[0111] It should be noted that the distributed circuit precisely applies the driving voltage and monitors the control effect through light and color sensors. When deviations exceed the allowable range, the voltage is dynamically adjusted through a compensation mechanism. Simultaneously, through anomaly detection functions such as short circuits and open circuits, the target value is automatically optimized in combination with ambient light intensity. This achieves refined control and dynamic compensation of the glass area, ensuring the reliability and safety of the control effect. This is especially true for large glass areas or complex lighting conditions, effectively avoiding control failures or anomalies. The distributed dynamic voltage application and monitoring mechanism not only improves the accuracy and uniformity of glass control, but also enhances safety and stability, ensuring normal operation in various environmental conditions.

[0112] This embodiment also provides a color intelligent control system based on electrochromic glass, including: a multispectral data acquisition module responsible for collecting spectral data of the current environment in real time through a multispectral sensor embedded in the electrochromic glass;

[0113] The electric energy calculation module is responsible for using spectral data to analyze the solar energy conversion efficiency and calculate the current electric energy value available for regulation;

[0114] The user preference prediction module is responsible for combining the available electric energy value with historical environmental data and user historical control data through self-learning algorithms to predict user preferences;

[0115] The intelligent control scheme generation module is responsible for generating an intelligent glass color control scheme based on user preference prediction results and spectral data;

[0116] The dynamic voltage distribution and control module is responsible for applying dynamic voltage to each area through distributed circuits to perform color control based on the intelligent glass color control solution.

[0117] This embodiment also provides a computer device, which is suitable for the case of a color intelligent control method based on electrochromic glass, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the color intelligent control method based on electrochromic glass proposed in the above embodiment.

[0118] The computer device may be a terminal, comprising a processor, memory, a communication interface, a display, and an input device connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system and computer programs. The internal memory provides an environment for the operating system and computer programs stored in the non-volatile storage media. The communication interface of the computer device is used to communicate with external terminals via wired or wireless communication. Wireless communication may be achieved via Wi-Fi, a carrier network, NFC (near-field communication), or other technologies. The display of the computer device may be a liquid crystal display or an electronic ink display. The input device may be a touchscreen overlay on the display, buttons, a trackball, or a touchpad on the computer device housing, or an external keyboard, touchpad, or mouse.

[0119] This embodiment also provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the color intelligent control method based on electrochromic glass proposed in the above embodiment; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0120] In summary, this invention achieves precise energy management for electrochromic glass control by embedding a multispectral sensor to collect real-time ambient spectral data (including ultraviolet, visible light, infrared intensity, and illumination angle), and calculating the current available electrical energy value based on solar energy conversion efficiency. An AI self-learning algorithm analyzes historical user control data and environmental data, predicts user preferences, and generates personalized glass color control solutions, effectively improving the user experience. Furthermore, the driving voltage for each zone is dynamically calculated based on user preferences and ambient spectral data. Distributed circuits are used for precise control, and interpolation algorithms and compensation voltage mechanisms are employed to ensure smooth and uniform color changes. This addresses control deviations caused by material aging or uneven voltage distribution.

[0121] Example 2, referring to Table 1, Table 2 and Table 3, is the second embodiment of the present invention. In order to further verify the technical solution of the present invention, experimental simulation data of the color intelligent control method based on electrochromic glass are provided.

[0122] This experiment aimed to verify the performance advantages of electrochromic glass by embedding multispectral sensors to collect environmental spectral data in real time and intelligently control light transmittance and color. The experiment was divided into an experimental group and a control group.

[0123] The control group used a single sensor (visible light sensor only) to collect environmental data, which failed to fully reflect the actual lighting conditions. It used a fixed algorithm to control the glass transmittance and color changes, and did not configure the dynamic zoning control function.

[0124] The experiments were conducted in a simulated environmental laboratory, simulating three lighting conditions: a sunny day (high light intensity, low angle of incidence), a cloudy day (low light intensity, high angle of incidence), and a partly cloudy day (moderate light intensity, variable angle of incidence). Experimental and control groups were tested under these conditions. Spectral data was collected, and calculations of power generation and energy distribution were performed for each group, along with actual transmittance and color response. All experiments were repeated three times under controlled conditions to ensure the reliability of the results.

[0125] The experimental group used the electrochromic glass system of the present invention, which is embedded with ultraviolet sensors, visible light sensors, infrared sensors, ambient light sensors, light angle sensors and thermal sensors. It can collect multi-dimensional data such as ultraviolet intensity, visible light intensity, infrared intensity, sunlight incident angle, ambient brightness and temperature in real time.

[0126] The details are shown in Table 1 below:

[0127] Table 1

[0128] condition UV intensity (mW / cm²) Visible light intensity (mW / cm² / nm) Infrared intensity (mW / cm²) Angle of incidence (°) Ambient brightness (Lux) Ambient temperature (°C) Sunny day-experimental group 2.8 1.9 3.5 30 86000 35 Sunny day-control group 1.3 1.3 - 30 86000 35 Cloudy day-experimental group 1.2 0.8 1.6 60 27000 22 Cloudy day-control group 0.5 0.5 - 60 27000 22 Multi-cloud-experimental group 2.1 1.4 2.7 45 59000 28 Cloudy-control group 1.0 1.0 - 45 59000 28 ;

[0129] Based on the collected data, using the formula Calculate the effective intensity of incident light and combine it with the average photoelectric conversion efficiency of the photovoltaic layer , calculate the total power generation , achieving rational distribution of electrical energy. Furthermore, the Long Short-Term Memory (LSTM) network within artificial intelligence analyzes user preferences and predicts target transmittance and color changes. Once the glass partitioning control plan is generated, dynamic voltage is applied through distributed circuits to adjust color and transmittance.

[0130] Example of calculation of comprehensive light intensity (sunny day - experimental group):

[0131] Assuming the visible light wavelength range ;

[0132] ;

[0133] Example of calculating the effective intensity of incident light (sunny day - experimental group):

[0134] ;

[0135] Example of calculation of conversion power per unit area (sunny day - experimental group):

[0136] Assuming conversion efficiency ;

[0137] ;

[0138] Example of calculating total generated power (sunny day - experimental group):

[0139] Assuming the photovoltaic layer area ;

[0140] ;

[0141] The data obtained from the experimental calculation are shown in Table 2 below:

[0142] Table 2

[0143] condition Comprehensive light intensity (mW / cm²) Effective intensity of incident light (mW / cm²) Conversion power per unit area (W / m²) Total power generation (W) Sunny day-experimental group 709.3 614.3 2.15 43.0 Sunny day-control group 482.3 417.7 1.46 29.2 Cloudy day-experimental group 298.8 149.4 0.52 10.4 Cloudy day-control group 185.5 92.8 0.33 6.6 Multi-cloud-experimental group 522.8 369.5 1.29 25.8 Cloudy-control group 371.0 262.3 0.92 18.4 ;

[0144] The calculation results in Table 2 were analyzed, the glass driving power and energy storage unit power were recorded, and the performance differences between the experimental group and the control group were summarized.

[0145] The details are shown in Table 3:

[0146] Table 3

[0147] pieces Total power generation (W) Driving power requirement (W) Glass driving power (W) Energy storage unit power (W) Sunny day-experimental group 43.0 30 30 13 Sunny day-control group 29.2 30 29.2 0 Cloudy day-experimental group 10.4 30 10.4 0 Cloudy day-control group 6.6 30 6.6 0 Multi-cloud-experimental group 25.8 30 25.8 0 Cloudy-control group 18.4 30 18.4 0 ;

[0148] From the analysis of Table 3, we can see that:

[0149] Under sunny conditions, the multispectral sensor of the experimental group captured the combined light intensity of ultraviolet light, visible light and infrared light, and the power generation efficiency was significantly higher than that of the control group, and energy storage was achieved ( );

[0150] Under cloudy conditions, due to the overall low light intensity, the power generation of the experimental and control groups dropped significantly, but the experimental group was still able to maintain basic driving functions, while the control group's performance was even worse;

[0151] Under cloudy conditions, the power generation of the experimental group was close to meeting the driving demand and performed better than the control group, demonstrating the adaptability of the multispectral sensor under complex lighting conditions.

[0152] In summary, this invention achieves precise energy management for electrochromic glass control by embedding a multispectral sensor to collect real-time ambient spectral data (including ultraviolet, visible light, infrared light intensity, and illumination angle). This data is then combined with solar energy conversion efficiency to calculate the current available electrical energy. A self-learning algorithm analyzes historical user control data and environmental data, predicts user preferences, and generates personalized glass color control solutions, effectively enhancing the user experience. Furthermore, the driving voltage for each zone is dynamically calculated based on user preferences and ambient spectral data. Distributed circuitry is employed for precise control, and an interpolation algorithm and voltage compensation mechanism are employed to ensure smooth and uniform color changes. This addresses control deviations caused by material aging or uneven voltage distribution.

[0153] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A color intelligent control method based on electrochromic glass, characterized by: include, The multispectral sensor embedded in the electrochromic glass collects the spectral data of the current environment in real time; Using spectral data, we analyze the solar energy conversion efficiency and calculate the current electric energy value available for regulation, including the following steps: Calculate the effective intensity of incident light using spectral data; Using the effective intensity of incident light, we analyze the solar energy conversion efficiency and calculate the current electric energy value available for regulation, including the following steps: Calculate the conversion power per unit area based on the effective intensity of the incident light; Calculate the total power generation based on the conversion power per unit area; The total generated power is divided into two parts, one part is used for the glass drive unit, and the other part enters the energy storage unit; Combined with the available electric energy value, the self-learning algorithm analyzes historical environmental data and user historical control data to predict user preferences, including the following steps: Collect users' historical environment data and historical user control data, and perform normalization processing; Based on the long short-term memory network, the user preference prediction model is obtained by inputting historical environment data and user historical control data for training; Input the user's historical control data and current environment data into the trained user preference prediction model, and output the user's target light transmittance and color depth change target; Generate intelligent glass color control solutions based on user preference prediction results and spectral data; Based on the intelligent glass color control solution, dynamic voltage is applied to each area through distributed circuits to control the color.

2. The method for intelligently controlling color of electrochromic glass according to claim 1, wherein: The multispectral sensor includes an ultraviolet sensor, a visible light sensor, an infrared sensor, a light angle sensor, a thermal sensor and an ambient light sensor; The spectral data includes ultraviolet light intensity, visible light intensity, infrared light intensity, sunlight incident angle, ambient brightness and ambient temperature.

3. The method for intelligent color control based on electrochromic glass according to claim 2, characterized in that: Using the spectral data, the effective intensity of the incident light is calculated and expressed as, ； in, represents the effective intensity of incident light, Indicates the comprehensive value of ultraviolet light intensity, visible light intensity and infrared light intensity. Indicates the angle of incidence of sunlight.

4. The method for intelligently controlling color of electrochromic glass according to claim 3, wherein: Using the effective intensity of incident light, we analyze the solar energy conversion efficiency and calculate the current electric energy value available for regulation, including the following steps: Based on the effective intensity of the incident light, the conversion power per unit area is calculated and expressed as, ； in, represents the conversion power per unit area, Represents the average photoelectric conversion efficiency of the photovoltaic layer; Based on the conversion power per unit area, the total power generation is calculated and expressed as, ； in, Indicates the total generated power, represents the total effective area of the photovoltaic layer; The total generated power is divided into two parts, one part is used for the glass drive unit, and the other part enters the energy storage unit; The electrical energy of the glass drive unit is expressed as, ； in, Indicates the electrical energy supplied to the glass drive unit. Indicates the electrical energy required for current electrochromic glass regulation; The electrical energy of the energy storage unit is expressed as, ； in, Indicates the electrical energy supplied to the energy storage unit.

5. The method for intelligently controlling color of electrochromic glass according to claim 4, characterized in that: Combined with the available electric energy value, the self-learning algorithm analyzes historical environmental data and user historical control data to predict user preferences, including the following steps: Collect users' historical environment data and historical user control data, and perform normalization processing; Based on the long short-term memory network, the user preference prediction model is obtained by inputting historical environment data and user historical control data for training; Input the user's historical control data and current environment data into the trained user preference prediction model, and output the user's target light transmittance and color depth change target; When the power of the glass drive unit meets the control requirements of the target transmittance and color change, it operates normally; When the power of the glass drive unit is insufficient, the target light transmittance is reduced and the range of the color depth change target is adjusted.

6. The method for intelligently controlling color of electrochromic glass according to claim 5, wherein: Based on the user preference prediction results and spectral data, an intelligent glass color control solution is generated, including the following steps: According to the target transmittance and ambient light intensity, the driving voltage to be applied is calculated and expressed as: ； in, Indicates the driving voltage that needs to be applied, represents the photoelectric response coefficient of the electrochromic material, Indicates the target transmittance; According to the target color value, the voltage distribution of each area is calculated to achieve uniform color change, which is expressed as, ; in, represents the driving voltage of the corresponding area, represents the minimum driving voltage of the electrochromic material, represents the maximum driving voltage of the electrochromic material, Indicates the maximum value of brightness, Indicates the target brightness value, Represents the nonlinear tuning parameter of the response curve.

7. The method for intelligently controlling color of electrochromic glass according to claim 6, wherein: Based on the intelligent glass color control solution, dynamic voltage is applied to each area through a distributed circuit to control the color, including the following steps: Using a distributed circuit, the calculated driving voltage is applied to the electrochromic material of the glass; Use a light sensor to monitor the actual light transmittance of each area and compare it with the target light transmittance. If the deviation exceeds the allowable range of light transmittance, adjust the driving voltage to compensate for the deviation. A color sensor is used to detect the actual color value of each area and compare it with the target color. When the deviation exceeds the color allowable range, the voltage of the corresponding area is dynamically adjusted.

8. A color intelligent control system based on electrochromic glass, based on the color intelligent control method based on electrochromic glass according to any one of claims 1 to 7, characterized in that: include, The multispectral data acquisition module is responsible for collecting the spectral data of the current environment in real time through the multispectral sensor embedded in the electrochromic glass; The electric energy calculation module is responsible for using spectral data to analyze the solar energy conversion efficiency and calculate the current electric energy value available for regulation; The user preference prediction module is responsible for combining the available electric energy value with historical environmental data and user historical control data through self-learning algorithms to predict user preferences; The intelligent control scheme generation module is responsible for generating an intelligent glass color control scheme based on user preference prediction results and spectral data; The dynamic voltage distribution and control module is responsible for applying dynamic voltage to each area through distributed circuits to perform color control based on the intelligent glass color control solution.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the color intelligent control method based on electrochromic glass according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the color intelligent control method based on electrochromic glass according to any one of claims 1 to 7 are implemented.

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