Meteorological self-adaptive based dynamic radiation cooling coating formula optimization method and system

Abstract

The application discloses a meteorological self-adaptive based dynamic radiation refrigeration coating formula optimization method and system, relates to the technical field of coating formula optimization, and comprises the following steps: extracting target area meteorological data to divide the refrigeration season and the heating season; taking the long-wave emissivity of the coating in the atmospheric window band and the reflectivity in the solar band as the material parameters to be optimized; subtracting the heat dissipation loss of the heating season from the heat dissipation benefit of the refrigeration season according to the climate distribution to obtain the annual energy-saving benefit; taking the material parameters as the decision variables and the maximum energy-saving benefit as the target to solve, and obtaining the optimal material parameters; and inversely solving the optimal material parameters into the matching ratio of the reflective cooling filler and the low emissivity filler according to a preset mapping relationship to obtain a recommended formula, so that the regional level recommended formula adapted to the climate distribution of the target region can be generated, and the problem that a fixed formula is difficult to consider the mutually opposite heat dissipation and heat preservation requirements of different regions can be solved.

Description

Technical Field

[0001] This invention relates to the field of coating formulation optimization technology, and in particular to a method and system for optimizing coating formulations based on meteorological adaptive dynamic radiation cooling. Background Technology

[0002] Dynamic radiative cooling coatings are a type of building energy-saving coating that combines radiative cooling and thermal insulation functions. They reduce surface heat absorption by reflecting sunlight through reflective cooling fillers, and achieve passive cooling by radiating heat to outer space through components with high infrared emissivity in the atmospheric window (8–13 μm) band. They also reduce heat loss through low emissivity fillers and thermal insulation fillers, and buffer temperature fluctuations by storing and releasing heat through phase change materials. The radiative cooling and thermal insulation performance of this type of coating depends on the type and amount of each component.

[0003] Existing radiant cooling coatings mostly use fixed formulas that are finalized at the factory. After determining a set of proportions that meet the requirements of coverage, insulation and relevant national standards during the research and development stage, they are mass-produced and supplied uniformly. This approach facilitates industrialized mass production and standardized construction, and can meet the general needs of decoration and basic insulation. However, in actual applications, the cooling and heating needs of buildings in different geographical regions vary greatly throughout the year. When fixed formulas are applied to different regions, they often fail to dissipate heat sufficiently in hot areas and lose too much heat in cold areas. They are difficult to fully realize their energy-saving effect under different climatic conditions. This difference stems from the inherent distribution characteristics of local climates. Fixed formulas are finalized at the factory and cannot take into account the conflicting heat dissipation and insulation needs of different regions. Summary of the Invention

[0004] In view of the aforementioned state of the prior art, this application is hereby proposed. Embodiments of this application provide a method and system for optimizing dynamic radiative cooling coating formulations based on weather adaptation. This method can generate regionally recommended formulations tailored to the climate distribution of a target area, solving the problem that fixed formulations cannot simultaneously address the conflicting heat dissipation and insulation needs of different regions.

[0005] According to one aspect of this application, a method for optimizing the formulation of a dynamic radiative cooling coating based on meteorological adaptation is provided. The coating includes a film-forming base material, a reflective cooling filler for reflecting sunlight, and a low-emissivity filler for reducing the infrared emissivity of the coating. The method includes: extracting meteorological data of a target area over many years to determine the climate distribution and dividing the region into cooling and heating seasons, the meteorological data including ambient temperature, ambient humidity parameters, and solar irradiance; using the long-wave emissivity of the coating in the atmospheric window band and the solar band reflectivity of the coating as material parameters to be optimized; and subtracting the heat dissipation gains of the cooling season from the heat dissipation losses of the heating season based on the climate distribution to obtain the annual energy-saving benefits of the target area; wherein, the... The heat dissipation benefit is determined based on the ambient temperature, solar irradiance, solar band reflectivity, and the net radiative heat dissipation of the coating in the atmospheric window band. The net radiative heat dissipation increases with increasing long-wave emissivity and decreases with increasing ambient humidity. The heat loss is determined based on the ambient temperature and the outward radiated heat of the coating in the atmospheric window band. The outward radiated heat increases with increasing long-wave emissivity. The optimal material parameters are obtained by solving a solution with the material parameters as decision variables and maximizing energy-saving benefits as the objective. Based on a preset mapping relationship, the optimal material parameters are inversely solved to obtain at least the ratio of the reflective cooling filler and the low-emissivity filler, resulting in a recommended formulation.

[0006] According to another aspect of this application, a dynamic radiative cooling coating formulation optimization system based on meteorological adaptation is provided, comprising: a meteorological extraction and analysis module for extracting meteorological data of a target area over many years to determine the climate distribution and divide the cooling season and heating season, wherein the meteorological data includes ambient temperature, ambient humidity parameters, and solar irradiance; a parameter construction module for constructing parameters to be optimized, wherein the long-wave emissivity of the coating in the atmospheric window band and the solar band reflectivity of the coating are used as material parameters to be optimized; and an energy-saving benefit calculation module for subtracting the heat dissipation gain in the cooling season from the heat dissipation loss in the heating season based on the climate distribution to obtain the annual energy-saving benefit of the target area; wherein the heat dissipation gain is based on the ambient temperature, the long-wave emissivity of the coating in the atmospheric window band, and the solar band reflectivity of the coating as material parameters to be optimized ... and an energy-saving benefit calculation module for subtracting the heat dissipation loss in the heating season from the heat dissipation gain in the cooling season based on the climate distribution to obtain the annual energy-saving benefit of the target area; wherein the heat dissipation gain is based on the ambient temperature, the long-wave emissivity of the coating in the atmospheric window band, and the solar band reflectivity of the coating in the heating season. The solar irradiance, the solar band reflectivity, and the net radiative heat dissipation of the coating in the atmospheric window band are determined. The net radiative heat dissipation increases with the increase of the long-wave emissivity and decreases with the increase of the ambient humidity parameter. The heat loss is determined based on the ambient temperature and the outward radiated heat of the coating in the atmospheric window band. The outward radiated heat increases with the increase of the long-wave emissivity. An optimization solution module is used to solve for the optimal material parameters with the material parameters as decision variables and the goal of maximizing energy-saving benefits. A formula inverse solution generation module is used to inversely solve the optimal material parameters into at least the ratio of the reflective cooling filler and the low emissivity filler according to a preset mapping relationship to obtain a recommended formula.

[0007] According to another aspect of this application, an electronic device is provided, including a memory and a processor, the memory being used to store computer-executable instructions, and the processor being used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the method described above.

[0008] According to another aspect of this application, a computer-readable storage medium is provided that stores computer-executable instructions thereon, which, when executed by a processor, implement the steps of the method described above.

[0009] Compared with existing technologies, the dynamic radiative cooling coating formulation optimization method and system based on meteorological adaptation according to the embodiments of this application can extract the climate distribution reflected by the multi-year meteorological data of the target area, construct the annual energy-saving benefit obtained by weighted subtraction of heat dissipation gains in the cooling season and heat dissipation losses in the heating season, and take into account the weakening effect of environmental humidity parameters on the net radiative heat dissipation capacity of the coating in the atmospheric window band when determining the heat dissipation gain. The optimal material parameters that maximize the annual energy-saving benefit are solved by using material parameters such as long-wave emissivity and solar band reflectivity as decision variables. Then, the recommended formulation is solved by back-solving according to the preset mapping relationship, so that regional-level formulations suitable for different climate distributions can be generated. This overcomes the problems of fixed formulations that are fixed at the factory, which have insufficient heat dissipation in hot areas, excessive heat loss in cold areas, and difficulty in taking into account the conflicting heat dissipation and heat preservation needs of different regions. Attached Figure Description

[0010] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of this application in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0011] Figure 1 This is a flowchart of the method for optimizing the formulation of dynamic radiation-cooling coatings based on weather adaptation, as described in this invention.

[0012] Figure 2 This is a block diagram of the dynamic radiation cooling coating formulation optimization system based on meteorological adaptation of the present invention.

[0013] Figure 3 This is a block diagram of an electronic device according to the present invention. Detailed Implementation

[0014] Hereinafter, exemplary embodiments according to this application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein.

[0015] Exemplary method:

[0016] This embodiment describes a specific implementation method for optimizing the formulation of dynamic radiation-cooling coatings based on meteorological adaptation.

[0017] Dynamic radiative cooling coatings simultaneously address both summer heat dissipation and winter insulation needs. However, once the coating is cured, its optical and thermal properties remain fixed and cannot be adjusted seasonally. Specifically, the long-wave emissivity of the coating in the atmospheric window band facilitates heat radiation into outer space during the cooling season, but in the heating season, it similarly dissipates accumulated indoor heat, exacerbating heat loss. In other words, the same long-wave emissivity has opposite energy-saving effects in the cooling and heating seasons. Conventional fixed formulations, when determining the proportions, often monotonously enhance or weaken radiative cooling capacity based on the ambient temperature of the region, failing to account for the opposite effects of the same long-wave emissivity in the two seasons, nor the impact of atmospheric humidity on the actual effectiveness of radiative cooling. Therefore, it is difficult to simultaneously achieve both heat dissipation and insulation throughout the year.

[0018] The method provided in this embodiment is based on the climate distribution reflected by multi-year meteorological data of the target area. It uses material parameters such as the long-wave emissivity and solar band reflectivity of the coating as variables to be optimized. It constructs the annual energy-saving benefit obtained by weighted subtraction of heat dissipation gains in the cooling season and heat dissipation losses in the heating season. When determining the heat dissipation gain, it takes into account the weakening effect of atmospheric humidity on the net radiation heat dissipation capacity of the coating in the atmospheric window band. Then, it solves for the material parameters that optimize the annual energy-saving benefit of the region. Based on the predetermined mapping relationship between the material parameters and the component dosage, it solves for the recommended formula, thereby generating regional formulas that are suitable for different regions and solving the problem that fixed formulas cannot meet the conflicting heat dissipation and heat preservation needs of different regions.

[0019] The dynamic radiation cooling coating described in this embodiment includes a film-forming base material, a phase change material, a thermal insulation filler, a reflective cooling filler for reflecting sunlight, and a low-emissivity filler for reducing the infrared emissivity of the coating. The film-forming base material refers to the resinous component in the coating that acts as a binder and forms the film, such as at least one of water-based synthetic resin emulsions like acrylic emulsion, silicone-acrylic emulsion, styrene-acrylic emulsion, and polyurethane. After the coating is applied and cured, it forms a continuous film and binds and fixes the fillers to the substrate surface. Because the molecular chains of this type of film-forming base material have strong infrared absorption and emission characteristics in the 8–13 μm atmospheric window band, it itself constitutes one of the main sources of the long-wave emissivity of the coating in the atmospheric window band. The reflective cooling filler refers to fillers with high reflectivity in the main bands of solar radiation, such as at least one of titanium dioxide, barium sulfate, silica microspheres, and aluminum silicate. It is used to reflect sunlight to reduce the absorption of solar heat by the coating surface. Simultaneously, this type of filler also has high infrared emission capability in the atmospheric window band, thus also contributing to the long-wave emissivity of the coating. Low-emissivity fillers refer to fillers used to reduce the infrared emissivity of the coating in the atmospheric window band, such as at least one of alumina, zinc oxide, metallic aluminum powder, and iron oxide. These fillers have low infrared emissivity in the atmospheric window band, and their incorporation into the coating can reduce the overall long-wave emissivity of the coating. The more low-emissivity fillers used, the greater the reduction in long-wave emissivity of the coating. Thermal insulation fillers refer to at least one of fillers containing closed air cavities and having low thermal conductivity, such as hollow glass microspheres and thermoplastic hollow microspheres. They are used to reduce the thermal conductivity of the coating and improve its ability to insulate heat through conduction and convection. Phase change materials refer to materials that undergo a solid-liquid phase change at a specific temperature and absorb or release latent heat during the phase change process, such as at least one of microencapsulated paraffin wax and fatty acid-based phase change materials. They are used to absorb or release heat to buffer temperature fluctuations when the coating temperature rises or falls. In some embodiments, the coating may further include conventional additives added to meet the needs of film formation, rheology, corrosion protection, etc., which will not be listed here. It should be noted that the types and amounts of the above components together determine the coating's long-wave emissivity, solar band reflectivity, equivalent thermal resistance, and other properties. The following text first uses long-wave emissivity and solar band reflectivity as material parameters to be optimized to illustrate the basic process of this method. Then, based on this, it further illustrates an example in which the equivalent thermal resistance provided by the thermal insulation filler and the phase change heat storage and release of the phase change material are also included in the optimization.

[0020] Figure 1 The illustration shows a method for optimizing the formulation of a dynamic radiative cooling coating based on weather adaptation according to an embodiment of this application, including steps S1 to S5.

[0021] like Figure 1 As shown, in step S1, meteorological data from multiple years of the target area are extracted to determine the climate distribution and to divide the cooling season and heating season. The meteorological data includes ambient temperature, ambient humidity parameters, and solar irradiance.

[0022] The target area refers to the geographical region where the building to be coated with the dynamic radiative cooling coating is located, such as a city or a region with similar climate conditions. Meteorological data refers to hourly or daily observation data reflecting the climate characteristics of the target area, which can be obtained from publicly available meteorological observation station records or meteorological reanalysis datasets. Among them, ambient temperature refers to the atmospheric temperature of the target area, and ambient humidity parameters refer to parameters characterizing the water vapor content in the atmosphere, such as relative humidity, or precipitable water content converted from relative humidity and temperature (precipitable water content refers to the equivalent liquid water height after all the water vapor contained in the atmospheric column per unit area is condensed, used to characterize the total amount of water vapor in the entire atmosphere), and solar irradiance refers to the solar radiation power received per unit area of ​​building surface.

[0023] "Multi-year period" refers to a series of consecutive years selected to eliminate the impact of individual year climate fluctuations, such as the past 5 to 10 years. "Climate distribution" refers to the statistical characteristics reflecting the climate patterns of the target area, obtained by statistically reducing the meteorological data from the multi-year period. Examples include the annual monthly or daily average values ​​and frequencies of ambient temperature, ambient humidity, and solar irradiance. "Division of cooling and heating seasons" refers to dividing the year into a cooling season (primarily for heat dissipation and cooling) and a heating season (primarily for heat preservation and heating) based on the actual cooling and heating needs of the target area. This can be done by using the local daily average outdoor temperature as a reference point for determining whether it is higher or lower than a preset heating / cooling boundary temperature, or by directly using the commonly used start and end months for local cooling and heating.

[0024] For example, for a target area with hot and humid summers and relatively mild winters, statistical analysis of its meteorological data over many years reveals the following: the cooling season is from May to October, during which ambient temperatures mostly range from 28 to 38°C, relative humidity mostly ranges from 75% to 90%, and solar irradiance at noon on sunny days can reach 800 to 950 W / m²; the heating season is from December to February of the following year, during which ambient temperatures mostly range from 5 to 12°C, and relative humidity mostly ranges from 60% to 75%. This statistical result constitutes the climate distribution of the target area and serves as the weighted basis for subsequent steps in constructing annual energy-saving benefits.

[0025] like Figure 1 As shown, in step S2, the long-wave emissivity of the coating in the atmospheric window band and the solar band reflectivity of the coating are used as material parameters to be optimized.

[0026] The atmospheric window band refers to the 8–13 μm band where the Earth's atmosphere exhibits high transmittance for infrared radiation. While atmospheric components such as water vapor and carbon dioxide absorb most infrared radiation, their absorption in the 8–13 μm band is relatively weak. This allows infrared radiation in this band to penetrate the atmosphere and reach the extremely cold outer space, thus becoming an effective channel for heat dissipation from the building surface. Long-wave emissivity refers to the average infrared emissivity of the coating in this 8–13 μm atmospheric window band; the higher the value, the stronger the coating's ability to radiate heat in this band. Solar band reflectivity refers to the average reflectivity of the coating in the 0.3–2.5 μm band, where solar radiation is mainly distributed; the higher the value, the stronger the coating's ability to reflect sunlight and reduce surface heat absorption.

[0027] The material parameters to be optimized refer to the parameters that characterize the optical and thermal properties of the coating, which are used as decision variables in the subsequent solution process and whose values ​​need to be determined through the solution. The long-wave emissivity of the coating is mainly provided by the infrared emission characteristics of the film-forming base material and the reflective cooling filler in the atmospheric window band, and can be reduced by adjusting the amount of the low-emissivity filler. The solar band reflectivity of the coating is mainly determined by the type and amount of the reflective cooling filler. The long-wave emissivity and solar band reflectivity are selected as the material parameters to be optimized because they respectively determine the coating's ability to radiate heat outward and its ability to reflect sunlight and reduce heat absorption, which are two fundamental performance parameters affecting the coating's annual energy-saving effect.

[0028] like Figure 1 As shown, in step S3, the heat dissipation gains during the cooling season and the heat dissipation losses during the heating season are weighted according to the climate distribution and then subtracted to obtain the annual energy-saving benefits of the target area. Among them, the heat dissipation gains are determined based on the ambient temperature, solar irradiance, solar band reflectivity, and the net radiative heat dissipation of the coating in the atmospheric window band. The net radiative heat dissipation increases with the increase of long-wave emissivity and decreases with the increase of the ambient humidity parameter. The heat dissipation losses are determined based on the ambient temperature and the outward radiated heat of the coating in the atmospheric window band. The outward radiated heat increases with the increase of long-wave emissivity.

[0029] Energy saving benefit refers to the comprehensive measure of building cooling and heating energy consumption saved by the coating compared to the baseline situation without the coating. Heat dissipation benefit refers to the energy savings during the cooling season due to the coating reducing building heat gain and lowering cooling energy consumption by reflecting sunlight and radiating heat outwards; heat dissipation loss refers to the energy consumption during the heating season due to the coating radiating heat outwards, increasing building heat loss and raising heating energy consumption. Since heat dissipation during the cooling season is beneficial for reducing cooling energy consumption, while heat dissipation during the heating season is detrimental to maintaining room temperature, the annual energy saving benefit is obtained by subtracting the heat dissipation benefit during the cooling season from the heat dissipation loss during the heating season. Furthermore, since the duration and frequency of different temperature, humidity, and solar irradiance conditions differ between the cooling and heating seasons, the heat dissipation benefit and heat dissipation loss need to be weighted according to the climate distribution obtained in step S1 before subtraction, so that the annual energy saving benefit reflects the actual distribution of climate conditions in the target area. The weighting can be performed as follows: Using the frequency or duration of occurrence of each combination of environmental temperature, humidity parameters, and solar irradiance values ​​in the climate distribution obtained in step S1 as weights, the heat dissipation gains and losses calculated under each value combination are weighted and summed. Then, the total heat dissipation gains obtained in the cooling season are subtracted from the total heat dissipation losses obtained in the heating season to obtain the annual energy-saving benefits of the target area. This embodiment does not limit the specific weighting method used.

[0030] The net radiative heat dissipation of the coating in the atmospheric window band refers to the net value after deducting the heat radiated outward by the coating from the downward radiative heat absorbed from the atmosphere in that band. It reflects the coating's actual heat dissipation capacity to outer space through the atmospheric window. During the cooling season, the heat dissipation benefit increases with the increase of this net radiative heat dissipation, which in turn increases with the increase of long-wave emissivity—the higher the long-wave emissivity, the stronger the coating's ability to radiate heat outward. Simultaneously, this net radiative heat dissipation decreases with the increase of ambient humidity—atmospheric water vapor is the main component absorbing infrared radiation in the 8–13 μm band. Higher water vapor content weakens the transmittance of the atmospheric window, resulting in stronger downward radiation returned to the coating from the atmosphere, thus offsetting more of the coating's outward heat dissipation and reducing the net radiative heat dissipation. Therefore, in high-temperature and high-humidity target areas, the actual heat dissipation benefit from simply increasing long-wave emissivity is weakened by higher humidity; this effect is taken into account when determining the heat dissipation benefit.

[0031] Specifically, the net radiative heat dissipation of the coating in the atmospheric window band can be calculated based on the fundamental principles of radiative heat transfer. The heat radiated outward by the coating in the atmospheric window band is determined by the integral of its long-wave emissivity in that band with the blackbody radiation intensity corresponding to the coating surface temperature within that band, and can be expressed as follows:

[0032] ;

[0033] In the formula, For long-wavelength emissivity, For temperature The blackbody spectral radiation intensity (given by Planck's blackbody radiation law). Let λ be the surface temperature of the coating and λ be the wavelength; the outward radiated heat varies with the long-wavelength emissivity. The amount of heat absorbed by the coating in the atmospheric window band increases with increasing ambient humidity. The amount of downward atmospheric radiation absorbed by the coating in that band is determined by the long-wave emissivity of the coating, the equivalent emissivity of the atmosphere in that band, and the blackbody radiation intensity corresponding to the ambient temperature, and increases with increasing ambient humidity. The net radiative heat dissipation of the coating in the atmospheric window band is the difference between the outward radiated heat and the absorbed downward atmospheric radiation. Coating surface temperature The surface energy balance can be determined by the ambient temperature, solar irradiance, and the solar band reflectivity of the coating, or approximated by the ambient temperature in engineering. The basic radiative heat transfer relationships such as Planck's blackbody radiation law and Stefan-Boltzmann law on which the above calculations are based are all physical relationships known in the art, and this embodiment does not limit the specific integral or approximate calculation form.

[0034] During the heating season, the heat radiated outward by the coating in the atmospheric window band constitutes part of the building's heat loss. Heat loss increases with the increase of this outward radiated heat, which in turn increases with the increase of longwave emissivity. Therefore, increasing longwave emissivity has a positive effect on heat loss benefits during the cooling season and a negative effect on heat loss during the heating season. In other words, the same longwave emissivity has opposite effects on annual energy savings during the cooling and heating seasons. Thus, a higher longwave emissivity is not necessarily more beneficial for annual energy savings; rather, there exists a value that maximizes annual energy savings, adapted to the climate distribution of the target area. It should be noted that both the heat loss benefits during the cooling season and the heat loss during the heating season involve the heat radiated outward by the coating, but they belong to different seasons and have opposite energy-saving effects—the outward radiation during the cooling season is included in the heat loss, while the outward radiation during the heating season is included in the heat loss. The two are weighted according to the climate distribution obtained in step S1 and then subtracted, without double counting.

[0035] In addition, the heat dissipation benefit is also determined by the ambient temperature, solar irradiance, and solar band reflectivity: the ambient temperature affects the intensity of radiative heat transfer between the coating and the atmosphere; the higher the solar irradiance and the lower the solar band reflectivity, the more solar heat the coating absorbs, which is less conducive to reducing cooling energy consumption. Therefore, the heat dissipation benefit decreases with the increase of solar irradiance and increases with the increase of solar band reflectivity.

[0036] like Figure 1 As shown, in step S4, the optimal material parameters are obtained by solving the problem with the material parameters as the decision variable and the goal of maximizing energy-saving benefits.

[0037] The solution, using material parameters as decision variables and aiming to maximize energy-saving benefits, refers to finding a set of material parameter values ​​that maximize the annual energy-saving benefits obtained in step S3 within the possible ranges of long-wave emissivity and solar reflectivity, and under the mutual constraints allowed by the material system. This set of values ​​is the optimal material parameter. The possible ranges and constraints are determined by the material system itself. For example, the values ​​of long-wave emissivity and solar reflectivity may not exceed their physical upper limits, or there may be a correlation between long-wave emissivity and solar reflectivity due to their shared contribution from the same filler material. The solution can be achieved using common constrained numerical optimization methods, such as grid search, gradient-based optimization, or swarm intelligence optimization. This embodiment does not limit the specific optimization method used for the solution.

[0038] As shown in step S3, since long-wave emissivity has an opposite effect on heat dissipation gains and losses, and the heat dissipation gains take into account the reduction of net radiative heat dissipation by environmental humidity, the optimal material parameters obtained vary depending on the climate distribution of the target area. For example, for a target area with high temperature and humidity in summer and mild winter, the high humidity reduces the heat dissipation gains from increasing long-wave emissivity, while increasing long-wave emissivity leads to heat dissipation losses in winter. Therefore, the solution tends not to maximize the long-wave emissivity, but rather to configure a moderate long-wave emissivity combined with a high solar band reflectivity, using solar reflection as the primary means of heat dissipation. Conversely, for a target area with dry and hot summers and low humidity, since humidity has a weaker effect on net radiative heat dissipation, increasing long-wave emissivity can yield more sufficient heat dissipation gains. The solution tends to configure a higher long-wave emissivity. Thus, the optimal material parameters obtained differ for target areas with different climate distributions, reflecting the characteristics of meteorological adaptability.

[0039] like Figure 1 As shown, in step S5, the optimal material parameters are solved inversely according to the preset mapping relationship to obtain the ratio of at least reflective cooling filler and low emissivity filler, thus obtaining the recommended formula.

[0040] The pre-established mapping relationship refers to a pre-established model characterizing the correspondence between the dosage of each component in the coating and the coating material parameters. Since the long-wave emissivity and solar reflectivity of the coating are jointly determined by the type and dosage of each component, a series of coating samples with different component dosages can be prepared and tested in advance. The corresponding long-wave emissivity and solar reflectivity of each sample can be measured, and then a mapping relationship from component dosage to material parameters can be established by fitting or interpolation. The inverse solution refers to using the reverse process of this mapping relationship to deduce the corresponding dosage of each component from the optimal material parameters obtained in step S4. Among these, the dosage of the reflective cooling filler mainly affects the solar reflectivity, while the dosage of the low-emissivity filler mainly affects the long-wave emissivity. The more low-emissivity filler is used, the more the long-wave emissivity of the coating is reduced. Therefore, the ratio of the reflective cooling filler and the low-emissivity filler can be deduced from the optimal material parameters.

[0041] The recommended formulation refers to a coating formulation derived from the proportions of the components obtained from the inverse kinematics solution and adapted to the climate distribution of the target region. For example, for the aforementioned target region with high temperature and humidity in summer and mild winter, the recommended formulation obtained from the inverse kinematics solution is configured with a higher amount of reflective cooling filler to obtain a higher solar band reflectivity, and an appropriate amount of low emissivity filler is configured to adjust the long-wave emissivity to a suitable value obtained from the solution; this recommended formulation is a regional-level recommended formulation for the climate of the target region.

[0042] In some embodiments, the method, based on the foregoing steps, further incorporates the equivalent thermal resistance of the coating provided by the insulating filler in the coating, as well as the attenuation of each material parameter over service time, into the optimization, so that the resulting recommended formulation can achieve better energy-saving effects throughout the entire service life of the coating. Specifically, after using the long-wave emissivity of the coating in the atmospheric window band and the solar band reflectivity of the coating as the material parameters to be optimized, the method further includes:

[0043] The equivalent thermal resistance of the coating is determined based on the insulating filler. Equivalent thermal resistance is a measure of the coating's ability to impede heat transfer via conduction and convection. A higher equivalent thermal resistance indicates less heat loss or gain through the coating via non-radiative means. As mentioned earlier, the insulating filler contains closed air cavities and has a low thermal conductivity; therefore, the equivalent thermal resistance of the coating increases with the amount of insulating filler used.

[0044] Energy-saving benefits are also determined based on the coating's equivalent thermal resistance; heat loss decreases as the equivalent thermal resistance increases. The reason for including the equivalent thermal resistance in the energy-saving benefits is that during the heating season, building heat loss includes not only radiative heat loss through atmospheric windows, but also conduction and convection heat loss through the coating. The higher the coating's equivalent thermal resistance, the less heat loss occurs in the latter part. Therefore, heat loss during the heating season decreases as the equivalent thermal resistance increases. Including the equivalent thermal resistance in the energy-saving benefits allows the resulting formula to more effectively suppress heat loss during the heating season.

[0045] Long-wave emissivity, solar reflectivity, and equivalent thermal resistance of the coating are used as parameters that vary with the service time of the coating. Different reduction functions with different attenuation rates are configured for each of these parameters. Service time refers to the time the coating has been exposed to outdoor use after application and curing. The reduction function describes the functional relationship between these parameters and their degradation over service time. Coatings exposed to UV radiation, humidity, acid rain, and other environmental factors for extended periods outdoors will gradually age, leading to a decline in their optical and thermal properties. For example, degradation of the film-forming base material and emissive components under UV irradiation will decrease long-wave emissivity; dust accumulation and pulverization on the surface of reflective cooling fillers will decrease solar reflectivity; and moisture absorption or microsphere rupture in insulating fillers will decrease equivalent thermal resistance. The reduction function characterizes this performance degradation over time and can be determined by the aging mechanism of each component or obtained by testing and fitting the performance retention rate of each parameter over time through accelerated aging tests.

[0046] Since long-wave emissivity, solar band reflectivity, and equivalent thermal resistance are dominated by different components and their respective aging mechanisms, their decay rates differ. Therefore, reduction functions with different decay rates are configured for each to characterize their respective decay patterns. For example, long-wave emissivity is mainly provided by film-forming materials and emissive components that are more sensitive to ultraviolet radiation, and its decay is relatively fast; solar band reflectivity is mainly provided by reflective cooling fillers with higher chemical stability, and its decay is relatively slow.

[0047] After configuring reduction functions for each material parameter, the objective of the solution is replaced with maximizing the cumulative benefit of the coating within its preset service life. The cumulative benefit is the accumulated amount of energy-saving benefits within the preset service life calculated based on the reduction functions. The preset service life refers to the pre-set service life for which the coating is expected to function, such as 5 or 10 years. Since each material parameter decays continuously over service time, the energy-saving benefit at any given moment should be calculated using the material parameters after reduction by the reduction functions at that moment. The overall benefit of the coating over the entire service life is the cumulative amount of energy-saving benefits at each moment over the service time. Specifically, the preset service life can be discretized into several moments or time periods. At each moment or time period, the energy-saving benefit at that moment or time period is calculated using the material parameters after reduction by their respective reduction functions in the aforementioned manner. Then, the energy-saving benefits at each moment or time period are summed over the service time, or equivalently integrated over the service time, to obtain the cumulative benefit within the preset service life. By replacing the goal of maximizing energy-saving benefits at a single moment with maximizing cumulative benefits over a preset service life, the optimal material parameters obtained can achieve overall optimality while taking into account the performance degradation of the coating throughout its service life, thus avoiding insufficient performance in the later stages of service due to only using the optimal configuration at the initial moment.

[0048] Accordingly, obtaining the recommended formula also includes: reversing the solution of the equivalent thermal resistance to the ratio of the insulation filler, that is, based on the correspondence between the equivalent thermal resistance and the amount of insulation filler in the preset mapping relationship, the amount of insulation filler is deduced from the optimal equivalent thermal resistance obtained by the solution.

[0049] Building upon the aforementioned embodiment that takes into account service life decay, the method further incorporates the load reduction effect of the phase change material during the cooling and heating seasons into the optimization. As previously mentioned, the melting point of a phase change material refers to the temperature at which it undergoes a solid-liquid phase transition. When the coating temperature rises above the melting point, the phase change material melts and absorbs heat, slowing down the temperature rise of the coating and building surface; when the coating temperature drops below the melting point, the phase change material solidifies and releases heat, slowing down the temperature drop.

[0050] Considering that the effective utilization of the heat storage and release functions of phase change materials depends on whether their melting point matches the ambient temperature distribution of the target area, this embodiment includes the melting point of the phase change material as a material parameter to be optimized, so as to determine a melting point value adapted to the climate of the target area through solution. That is, the material parameter to be optimized also includes the melting point of the phase change material. When obtaining the cumulative benefits, it also includes: determining the phase change heat storage and release of the phase change material in the cooling and heating seasons at each moment within the preset service cycle based on the temporal distribution characteristics of ambient temperature and the melting point, and configuring a reduction function for the phase change heat storage and release that varies with service time; adding the phase change heat storage and release after taking into account the reduction function to the heat dissipation benefits, and deducting it from the heat dissipation losses.

[0051] The temporal distribution characteristics of ambient temperature refer to the duration and frequency of ambient temperature occurrences in various temperature ranges throughout the year within the climate distribution obtained in step S1. Phase change heat storage refers to the cumulative heat absorbed by the phase change material during the cooling season and released during the heating season. Its value is determined by both the temporal distribution characteristics of ambient temperature and the melting point: when the melting point falls within the frequently occurring temperature range of the target area's ambient temperature, the coating temperature repeatedly crosses this melting point, resulting in more opportunities for the phase change material to repeatedly absorb and release heat, leading to a larger phase change heat storage; when the melting point deviates from the high-frequency range of ambient temperature, the coating temperature rarely exceeds the melting point, making it difficult for the phase change material to undergo phase change, resulting in a smaller phase change heat storage. Therefore, phase change heat storage does not change monotonically with the melting point, but rather achieves a larger value when the melting point matches the temperature distribution of the target area. This makes the melting point of the phase change material an optimal parameter that can be determined through calculation.

[0052] The heat storage of phase change materials (PCMs) during the cooling season helps reduce building heat gain, so this is added to the heat dissipation benefits as a gain. The heat release of PCMs during the heating season helps reduce building heat loss, so this is deducted from the heat dissipation losses as a reduction. Furthermore, due to repeated phase change cycles and outdoor aging, the microcapsules of PCMs may rupture, and their latent heat capacity may decrease. The stored and released heat also decreases with service time. Therefore, a reduction function is configured for the stored and released heat as a function of service time, and the stored and released heat, after incorporating the reduction function, is used in the calculation of energy-saving benefits at each time point. This ensures that the heat storage and release effects of PCMs are consistently included in the cumulative benefits throughout the entire service life.

[0053] Accordingly, obtaining the recommended formulation also includes: reversing the calculation of the melting point of the phase change material that maximizes cumulative benefits into the proportion of the phase change material. That is, based on the correspondence between the melting point of the phase change material and its type and dosage, the type of phase change material and its dosage are selected from the optimal melting point obtained by the solution. For example, for target regions where the high frequency range of ambient temperature is concentrated at higher temperatures, the optimal melting point obtained by the solution is correspondingly higher, and a type of phase change material with a matching melting point is selected during the reversal.

[0054] In the above embodiments that take service time degradation into account, considering that the degradation rates of different material parameters are different, the method can also be configured in the solution process as follows to compensate for the performance loss of material parameters with faster degradation rates in the later stages of service:

[0055] The decay rate of the reduction function corresponding to long-wave emissivity is greater than that corresponding to the reduction functions corresponding to solar band reflectivity and equivalent thermal resistance. As mentioned earlier, long-wave emissivity is mainly provided by the film-forming matrix and emissive components that are more sensitive to ultraviolet radiation, and its decay is relatively fast under outdoor exposure. In contrast, solar band reflectivity and equivalent thermal resistance are dominated by chemically stable reflective cooling fillers and insulating fillers, respectively, and their decay is relatively slow. Therefore, the decay rate of the reduction function corresponding to long-wave emissivity is the highest among the three. Because long-wave emissivity decays the fastest and is most prone to insufficient heat dissipation in the later stages of service, this embodiment makes the following compensatory settings for its initial value:

[0056] In the solution process, a positive bias term is applied to the initial value of the long-wavelength emissivity. This positive bias term increases with the decay rate of the reduction function corresponding to the long-wavelength emissivity, ensuring that the initial value of the obtained long-wavelength emissivity is higher than its average value over the service life. The initial value of the long-wavelength emissivity refers to the value of the coating during the initial stage of construction (i.e., when the service time is zero). The positive bias term is a correction term applied to the initial value of the long-wavelength emissivity when solving for the optimal material parameters, shifting its value in the direction of increase.

[0057] The reason for applying a positive bias term is that, since long-wave emissivity decays rapidly, if the initial value of long-wave emissivity is configured solely based on the value that maximizes energy-saving benefits at the initial moment, the long-wave emissivity will decrease rapidly over time, resulting in insufficient heat dissipation capacity of the coating in the later stages of service and impaired cumulative benefits. Therefore, a positive bias term is applied to the initial value of long-wave emissivity during the solution process, making its initial value appropriately higher. This allows the heat dissipation surplus in the early stages of service to compensate for the heat dissipation capacity lost due to the decay of long-wave emissivity in the later stages of service, resulting in better cumulative benefits throughout the entire service life. Furthermore, since the purpose of the bias is to compensate for decay, the positive bias term increases with the decay rate of the reduction function corresponding to long-wave emissivity; that is, the faster the decay, the higher the initial value needs to be. After applying the positive bias term, the initial value of the long-wave emissivity is no longer equal to the value that maximizes the energy saving effect at the initial moment. Instead, it is raised to a value higher than the average of the values ​​obtained by the decay of the long-wave emissivity over time throughout the entire service life. This is a quantitative difference from the value that is optimally configured at the initial moment when no bias term is applied.

[0058] The positive bias term can be applied in various ways. For example, in solving a problem aimed at maximizing cumulative benefits, a bonus term is added to the initial value of the long-wave emission rate within the objective function. This bonus term increases with the increase of the initial value of the long-wave emission rate and with the increase of the attenuation rate of the reduction function corresponding to the long-wave emission rate, thereby causing the initial value of the long-wave emission rate to be higher during the solution process. Alternatively, after obtaining the long-wave emission rate value that maximizes the energy-saving benefit at the initial moment, a positive correction is superimposed on this value. This positive correction increases with the increase of the attenuation rate of the reduction function corresponding to the long-wave emission rate, and the superimposed value is used as the initial value of the long-wave emission rate. This embodiment does not limit the specific functional form of the positive bias term. Any method that causes the initial value of the long-wave emission rate to shift in the increasing direction with the increase of its attenuation rate, and thereby compensates for the attenuation of the long-wave emission rate during the service life, falls within the scope of the positive bias term described in this embodiment.

[0059] For example, if the performance retention rate of a certain long-wave emissivity attenuation component decreases approximately linearly within a preset service period, and the initial value of the long-wave emissivity obtained by maximizing energy-saving benefits at the initial moment without applying a positive bias term is a certain benchmark value, then after applying the positive bias term, the initial value of the long-wave emissivity is raised to a value higher than the benchmark value, making the average value of the long-wave emissivity at each moment within the service period closer to the optimal heat dissipation capacity required by the region, thereby improving the cumulative benefits throughout the entire service period.

[0060] In some embodiments, the relationship between the aforementioned net radiative heat dissipation and the ambient humidity parameter can be specifically determined by introducing the effective transmittance of infrared radiation within the atmospheric window. Specifically, the net radiative heat dissipation is the difference between the outward radiated heat of the coating in the atmospheric window band and the downward radiated heat absorbed by the coating. The downward radiated heat absorbed by the coating refers to the portion of heat radiated downwards by the atmosphere itself and absorbed by the coating. This heat is in the opposite direction to the outward radiated heat of the coating, thus canceling out the heat dissipation of the coating. Therefore, the net radiative heat dissipation is the outward radiated heat of the coating minus the downward radiated heat absorbed by the coating.

[0061] In determining the downward atmospheric radiation heat, the effective transmittance of infrared radiation within the atmospheric window of the target area is determined based on the environmental humidity parameter. The equivalent emissivity of the atmosphere is then determined based on the effective transmittance, and the equivalent emissivity and effective transmittance are negatively correlated. Effective transmittance refers to the equivalent transmission capability of the atmosphere for infrared radiation in the 8–13 μm atmospheric window band. A higher effective transmittance indicates a stronger ability of infrared radiation in that band to penetrate the atmosphere, and a closer proximity to atmospheric transparency. Since infrared radiation within the atmospheric window is mainly absorbed by water vapor in the atmosphere, the effective transmittance decreases with increasing water vapor content as indicated by the environmental humidity parameter. It can be determined by a pre-calibrated relationship using the environmental humidity parameter. The equivalent emissivity of the atmosphere is a measure of its ability to radiate downwards in the atmospheric window band when the atmosphere is considered a gray body. According to Kirchhoff's laws, the emissivity of a medium corresponds to its absorption capacity, and the proportion of radiation absorbed by the atmosphere is complementary to the proportion of radiation penetrating the atmosphere. Therefore, the equivalent emissivity and effective transmittance of the atmosphere are negatively correlated; that is, the lower the effective transmittance (the higher the humidity), the higher the equivalent emissivity of the atmosphere, and the stronger the downward radiation sent back to the coating from the atmosphere.

[0062] The downward atmospheric radiative heat is determined based on ambient temperature, long-wave emissivity, and the equivalent emissivity of the atmosphere. The downward atmospheric radiative heat increases with increasing ambient temperature (higher temperatures result in stronger atmospheric radiation), increases with increasing long-wave emissivity (the coating's absorption capacity for incident radiation in the atmospheric window band corresponds to its emission capacity; higher long-wave emissivity means a stronger ability to absorb downward atmospheric radiation), and increases with increasing equivalent emissivity of the atmosphere. Therefore, an increase in ambient humidity, through a decrease in effective transmittance and an increase in equivalent emissivity, increases the downward atmospheric radiative heat, ultimately reducing net radiative heat dissipation. This is consistent with the decrease in net radiative heat dissipation with increasing ambient humidity in step S3, thus demonstrating the calculable weakening effect of humidity on the net effectiveness of radiative cooling.

[0063] Specifically, the effective transmittance of infrared radiation within the atmospheric window is recorded as... The equivalent emissivity of the atmosphere in this band It can be approximately determined by the complementary relationship between the two, for example:

[0064] ;

[0065] This demonstrates a negative correlation between equivalent emissivity and effective transmittance; where effective transmittance... The decrease in water vapor content, as characterized by the ambient humidity parameter, can be determined by a pre-calibrated relationship between the ambient humidity parameters. The downward radiant heat absorbed by the coating in the atmospheric window band can be further expressed as:

[0066] ;

[0067] In the formula, Long-wave emissivity (the coating’s ability to absorb incident radiation corresponds to its ability to emit it). ambient temperature The blackbody spectral radiation intensity under the following conditions The effective transmittance is determined by ambient temperature. As ambient humidity increases, the effective transmittance... Reduce, equivalent emissivity Increased, causing downward radiant heat from the atmosphere This increases the effective transmittance, thereby reducing the net radiative heat loss. This embodiment does not limit the specific calibration relationship between the effective transmittance and the ambient humidity parameter; for example, it can be pre-calibrated using statistical values ​​of local precipitable water through radiative transfer calculations or empirical fitting.

[0068] Building upon the aforementioned embodiment that incorporates effective transmittance, the method further incorporates radiative heat dissipation of the coating in the band outside the atmospheric window to more comprehensively characterize the coating's radiative heat transfer. Specifically, the material parameters to be optimized also include the out-of-window emissivity of the coating in the band outside the atmospheric window. The out-of-window band refers to the remaining thermal infrared band outside the 8–13 μm atmospheric window, and the out-of-window emissivity refers to the average infrared emissivity of the coating in this out-of-window band.

[0069] The heat dissipation gains and losses are also determined based on the net radiative heat dissipation of the coating in the wavelength band outside the atmospheric window. The reason for including radiative heat dissipation in the wavelength band outside the window is that the coating undergoes radiative heat exchange with the outside environment not only in the atmospheric window wavelength band but also in the wavelength band outside the window. Including radiative heat dissipation in the wavelength band outside the window makes the calculation of energy-saving benefits more complete. The net radiative heat dissipation in the wavelength band outside the atmospheric window is determined based on the emissivity outside the window and the downward radiative heat in that wavelength band.

[0070] It should be noted that in the band outside the atmospheric window, components such as water vapor and carbon dioxide in the atmosphere strongly absorb infrared radiation, and the atmosphere in this band is approximately a blackbody. Therefore, the downward atmospheric radiation heat in this band is mainly determined by the ambient temperature, and its determination method differs from that in the band inside the atmospheric window. In the band inside the atmospheric window, the downward atmospheric radiation heat is determined by the effective transmittance varying with the ambient humidity parameter, while in the band outside the atmospheric window, the downward atmospheric radiation heat is mainly controlled by the ambient temperature. Thus, there is a significant difference in the degree to which the band inside and outside the window is affected by the ambient humidity parameter, requiring separate calculations for the two.

[0071] Accordingly, obtaining the recommended formulation also includes: inverse solving the optimal material parameters, including the out-of-window emissivity, obtained by the solution to generate the recommended formulation. That is, during the inverse solution, the component ratio corresponding to the optimal out-of-window emissivity is determined based on the correspondence between the out-of-window emissivity and the corresponding component dosage.

[0072] In some embodiments, to further improve the accuracy of the generated recommended formula, after obtaining the recommended formula, a feedback correction step is further included to iteratively correct the relationship used in the aforementioned calculation using measured data, specifically including:

[0073] Obtain measured surface temperature data or measured building energy consumption data of the coating in the target area after application according to the recommended formula. That is, select a building in the target area that has been applied according to the recommended formula, and collect the measured temperature of its coating surface, or collect the measured cooling and heating energy consumption of the building.

[0074] The measured surface temperature data or measured building energy consumption data is compared with the corresponding predicted data obtained from the solution to obtain the comparison deviation. The corresponding predicted data refers to the predicted value of the coating surface temperature or building energy consumption corresponding to the measured value, calculated using the aforementioned relationship of net radiative heat dissipation and optimal material parameters; the comparison deviation refers to the difference between the measured value and the predicted value.

[0075] The mapping relationship for determining the effective transmittance is iteratively updated based on the comparison deviation; and / or the decay rate in the corresponding reduction function is iteratively updated based on the comparison deviation. Since the effective transmittance is determined by a pre-calibrated relationship using environmental humidity parameters, and the reduction function is obtained by fitting the component aging mechanism or accelerated aging test, both may deviate from the actual conditions of the target area. Therefore, the mapping relationship for determining the effective transmittance can be corrected based on the comparison deviation to better match the actual atmospheric conditions of the target area; and / or the decay rate in the reduction function can be corrected to better match the decay law of the coating under the actual environment of the target area. After such iterative correction, the re-solved recommended formulation can more accurately adapt to the actual climate and usage conditions of the target area and can be extended to other areas with similar climate conditions.

[0076] In summary, the meteorological adaptive dynamic radiation cooling coating formulation optimization method provided in this embodiment has the following technical advantages over the prior art:

[0077] First, by extracting the climate distribution reflected by the meteorological data of the target area over many years, the annual energy-saving benefit is constructed by weighted subtraction of the heat dissipation gain in the cooling season and the heat dissipation loss in the heating season. The optimal material parameters that maximize the annual energy-saving benefit are solved by using material parameters as decision variables. The solution is then used to generate recommended formulas, which can generate regional formulas that are suitable for different regions with different climate distributions. This solves the problem that fixed formulas that are designed before leaving the factory have insufficient heat dissipation in hot regions, excessive heat loss in cold regions, and difficulty in taking into account the conflicting heat dissipation and heat preservation needs of different regions.

[0078] Second, since the opposite effect of long-wave emissivity in heat dissipation gain during the cooling season and heat loss during the heating season is taken into account when constructing the annual energy-saving benefits, the optimal material parameters obtained can achieve a balance between heat dissipation during the cooling season and heat preservation during the heating season that is adapted to the climate distribution of the target area, thus avoiding the problem of simply strengthening or weakening radiative cooling based on temperature and failing to take into account the whole year.

[0079] Third, since the weakening effect of the ambient humidity parameter on the net radiative heat dissipation capability of the coating in the atmospheric window band is taken into account when determining the heat dissipation benefit, the optimal material parameters obtained can avoid the problem that the heat dissipation benefit is not as expected in high temperature and high humidity areas due to simply increasing the long-wave emissivity, making the obtained formula more in line with the actual radiative cooling benefits that can be obtained in the target area.

[0080] Fourth, in the embodiment that takes into account service time decay, by configuring reduction functions for each material parameter with different decay rates and taking the maximum cumulative benefit within the preset service period as the solution objective, the obtained formulation achieves overall optimization throughout the entire service period of the coating; in particular, by applying a positive bias term to the initial value of the long-wave emissivity with faster decay, the heat dissipation surplus in the early service period is used to compensate for the heat dissipation capacity lost due to decay in the later service period, thereby further improving the cumulative benefit throughout the entire service period.

[0081] Exemplary system:

[0082] Figure 2The figure illustrates a weather-adaptive dynamic radiative cooling coating formulation optimization system according to an embodiment of this application. The coating includes a film-forming base material, a phase change material, a thermal insulation filler, a reflective cooling filler for reflecting sunlight, and a low emissivity filler for reducing the infrared emissivity of the coating. The system is characterized by comprising: a weather extraction and analysis module for extracting multi-year weather data of a target area to determine climate distribution and classify the cooling and heating seasons; the weather data includes ambient temperature, ambient humidity parameters, and solar irradiance; a parameter construction module for constructing parameters to be optimized, using the long-wave emissivity of the coating in the atmospheric window band and the solar band reflectivity of the coating as material parameters to be optimized; and an energy-saving benefit calculation module for calculating the heat dissipation gains in the cooling season and the heat dissipation losses in the heating season according to climate distribution. The weighted average and subtraction yield the annual energy-saving benefits for the target area. Heat dissipation benefits are determined based on ambient temperature, solar irradiance, solar band reflectivity, and the net radiative heat dissipation of the coating in the atmospheric window band. Net radiative heat dissipation increases with increasing long-wave emissivity and decreases with increasing ambient humidity. Heat loss is determined based on ambient temperature and the outward radiated heat of the coating in the atmospheric window band; outward radiated heat increases with increasing long-wave emissivity. An optimization solution module is used to solve for the optimal material parameters with material parameters as decision variables and maximizing energy-saving benefits as the objective. A formula inverse solution generation module is used to inversely solve for the optimal material parameters based on a preset mapping relationship, converting them into the ratio of at least reflective cooling filler and low-emissivity filler, thus obtaining a recommended formula.

[0083] Exemplary electronic device:

[0084] Figure 3 A block diagram of an electronic device according to an embodiment of this application is illustrated.

[0085] like Figure 3 As shown, the electronic device includes one or more processors and memory.

[0086] A processor can be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and can control other components in an electronic device to perform desired functions.

[0087] The memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0088] In one example, the electronic device may also include input devices and output devices, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).

[0089] Of course, for the sake of simplicity, Figure 3 Only some of the components of the electronic device relevant to this application are shown in this illustration; components such as buses, input / output interfaces, etc., are omitted. In addition, the electronic device may include any other suitable components depending on the specific application.

[0090] Exemplary computer-readable media:

[0091] Embodiments of this application may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps described in the "Exemplary Methods" section above according to the various embodiments of this application.

[0092] Computer-readable storage media may take the form of any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may, for example, include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0093] The basic principles of this application have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this application are merely examples and not limitations, and should not be considered as essential features of each embodiment of this application. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not restrict the application from being implemented using the specific details described above.

[0094] The block diagrams of devices, apparatuses, devices, and systems involved in this application are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0095] It should also be noted that in the apparatus, equipment, and methods of this application, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered as equivalent solutions of this application.

[0096] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of this application. Therefore, this application is not intended to be limited to the aspects shown herein, but rather to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0097] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this application to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A method for optimizing the formulation of a weather-adaptive dynamic radiative cooling coating, wherein the coating comprises a film-forming base material, a phase change material, a thermal insulation filler, a reflective cooling filler for reflecting sunlight, and a low emissivity filler for reducing the infrared emissivity of the coating, characterized in that, The method includes: Extract meteorological data from the target area over many years to determine the climate distribution and divide the cooling season and heating season. The meteorological data includes ambient temperature, ambient humidity parameters, and solar irradiance. The long-wave emissivity of the coating in the atmospheric window band and the solar band reflectivity of the coating are used as material parameters to be optimized. The annual energy-saving benefit of the target area is obtained by subtracting the heat dissipation gains during the cooling season from the heat dissipation losses during the heating season, weighted according to the climate distribution. The heat dissipation gains are determined based on the ambient temperature, solar irradiance, solar reflectivity, and the net radiative heat dissipation of the coating in the atmospheric window band. The net radiative heat dissipation increases with increasing long-wave emissivity and decreases with increasing ambient humidity. The heat dissipation losses are determined based on the ambient temperature and the outward radiated heat of the coating in the atmospheric window band. The outward radiated heat increases with increasing long-wave emissivity. The optimal material parameters are obtained by solving the problem using the material parameters as decision variables and maximizing the energy-saving benefits. Based on the preset mapping relationship, the optimal material parameters are deduced into at least the ratio of the reflective cooling filler and the low emissivity filler to obtain the recommended formula.

2. The method for optimizing the formulation of dynamic radiative cooling coatings based on meteorological adaptation according to claim 1, characterized in that, After considering the long-wave emissivity of the coating in the atmospheric window band and the solar band reflectivity of the coating as the material parameters to be optimized, the following steps are also included: The equivalent thermal resistance of the coating is determined based on the thermal insulation filler. The energy-saving benefits are also determined based on the equivalent thermal resistance of the coating, and the heat loss decreases as the equivalent thermal resistance increases; The long-wave emissivity, the solar band reflectivity, and the coating equivalent thermal resistance are used as parameters that change with the service time of the coating, and reduction functions with different attenuation rates are configured for the long-wave emissivity, the solar band reflectivity, and the equivalent thermal resistance, respectively. The objective of the solution is replaced by maximizing the cumulative benefit of the coating within a preset service life, where the cumulative benefit is the cumulative amount of energy-saving benefits within the preset service life calculated based on the reduction function. The recommended formula further includes: resolving the equivalent thermal resistance obtained from the solution to obtain the proportion of the thermal insulation filler.

3. The method for optimizing the formulation of dynamic radiative cooling coatings based on meteorological adaptation according to claim 2, characterized in that, The material parameters to be optimized also include the melting point of the phase change material. When obtaining the cumulative benefits, the method further includes: determining the phase change heat storage and release of the phase change material in the cooling season and the heating season at each time point within the preset service cycle based on the time distribution characteristics of the ambient temperature and the melting point, and configuring a reduction function for the phase change heat storage and release that varies with the service time; adding the phase change heat storage and release after taking into account the reduction function to the heat dissipation benefits, and deducting it from the heat dissipation losses. The recommended formulation further includes: resolving the melting point of the phase change material that optimizes the cumulative benefits to the proportion of the phase change material.

4. The method for optimizing the formulation of dynamic radiative cooling coatings based on meteorological adaptation according to claim 2 or 3, characterized in that: The attenuation rate of the reduction function corresponding to the long-wave emissivity is greater than the attenuation rate of the reduction function corresponding to the solar band reflectivity and the equivalent thermal resistance. In the solution, a positive bias term is applied to the initial value of the long-wave emission rate. The positive bias term increases as the decay rate of the reduction function corresponding to the long-wave emission rate increases, so that the initial value of the obtained long-wave emission rate is higher than the average value of the long-wave emission rate during the service period.

5. The method for optimizing the formulation of dynamic radiative cooling coatings based on meteorological adaptation according to claim 2 or 3, characterized in that: The net radiative heat dissipation is the difference between the outward radiated heat of the coating in the atmospheric window band and the downward radiated heat absorbed by the coating from the atmosphere. Specifically, when determining the downward atmospheric radiative heat, the effective transmittance of infrared radiation in the target area within the atmospheric window is determined based on the environmental humidity parameter, and the equivalent emissivity of the atmosphere is determined based on the effective transmittance. The equivalent emissivity is negatively correlated with the effective transmittance. The downward atmospheric radiant heat is determined based on the ambient temperature, the long-wave emissivity, and the equivalent emissivity of the atmosphere.

6. The method for optimizing the formulation of dynamic radiative cooling coatings based on meteorological adaptation according to claim 5, characterized in that: The material parameters to be optimized also include the out-of-window emissivity of the coating in the band outside the atmospheric window; The heat dissipation gains and losses are also determined based on the net radiative heat dissipation of the coating in the band outside the atmospheric window. The net radiative heat dissipation of the band outside the atmospheric window is determined based on the emissivity outside the window and the downward radiative heat of the atmosphere in that band. The process of obtaining the recommended formulation further includes: performing an inverse solution on the optimal material parameters, including the out-of-window emissivity, obtained from the solution to generate the recommended formulation.

7. The method for optimizing the formulation of dynamic radiative cooling coatings based on meteorological adaptation according to claim 6, characterized in that, After obtaining the recommended formula, it also includes: Obtain measured surface temperature data or measured building energy consumption data of the coating in the target area after construction according to the recommended formula; The measured surface temperature data or the measured building energy consumption data is compared with the corresponding predicted data obtained by the solution to obtain the comparison deviation; The mapping relationship of the effective transmittance is determined by iterative updating based on the comparison deviation; and / or the attenuation rate in the corresponding reduction function is updated by iterative updating based on the comparison deviation.

8. A weather-adaptive dynamic radiative cooling coating formulation optimization system, wherein the coating comprises a film-forming base material, a phase change material, a thermal insulation filler, a reflective cooling filler for reflecting sunlight, and a low emissivity filler for reducing the infrared emissivity of the coating, characterized in that, The system includes: The meteorological extraction and analysis module is used to extract meteorological data of the target area over many years to determine the climate distribution and to divide the cooling season and heating season. The meteorological data includes ambient temperature, ambient humidity parameters and solar irradiance. The parameter construction module is used to construct parameters to be optimized, which uses the long-wave emissivity of the coating in the atmospheric window band and the solar band reflectivity of the coating as material parameters to be optimized. The energy-saving benefit calculation module is used to subtract the heat dissipation gains during the cooling season from the heat dissipation losses during the heating season, weighted according to the climate distribution, to obtain the annual energy-saving benefit of the target area. The heat dissipation gains are determined based on the ambient temperature, solar irradiance, solar band reflectivity, and the net radiative heat dissipation of the coating in the atmospheric window band. The net radiative heat dissipation increases with increasing long-wave emissivity and decreases with increasing ambient humidity. The heat dissipation losses are determined based on the ambient temperature and the outward radiated heat of the coating in the atmospheric window band. The outward radiated heat increases with increasing long-wave emissivity. The optimization solution module is used to solve for the optimal material parameters by taking the material parameters as decision variables and maximizing the energy-saving benefits as the objective. The formula inverse generation module is used to inversely generate the optimal material parameters according to a preset mapping relationship, which is to obtain at least the ratio of the reflective cooling filler and the low emissivity filler, thus obtaining a recommended formula.

9. An electronic device comprising a memory and a processor, characterized in that: The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the dynamic radiation cooling coating formulation optimization method based on meteorological adaptation as described in any one of claims 1 to 7.

10. A computer-readable storage medium having computer-executable instructions stored thereon, characterized in that: When the computer-executable instructions are executed by the processor, they implement the steps of the method for optimizing the formulation of dynamic radiation-cooling coatings based on weather adaptation as described in any one of claims 1 to 7.

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