Refrigeration appliance, method of controlling a refrigeration appliance, and computer program product

Abstract

The application discloses a refrigeration equipment, a control method of the refrigeration equipment and a computer program product, relates to the technical field of refrigeration equipment, and the refrigeration equipment comprises a fresh-keeping chamber, a multi-color light source and a controller. The controller is configured to identify light illumination demand types corresponding to a plurality of food materials in the fresh-keeping chamber and food material fresh-keeping values of the food materials. When the plurality of light illumination demand types have conflict demands including a light demand type and a light-avoiding type at the same time, a basic light illumination strategy is determined based on the highest fresh-keeping priority in the food material fresh-keeping values of the food materials. When the plurality of light illumination demand types have other conflict demands not including the light demand type and the light-avoiding type at the same time, a time sequence isolation scheduling strategy is determined as the basic light illumination strategy. A light illumination scheduling strategy is generated by adjusting light illumination parameters in the basic light illumination strategy based on the food materials. The multi-color light source is controlled to operate based on the light illumination parameters in the light illumination scheduling strategy. The above refrigeration equipment can improve the overall fresh-keeping effect under the mixed storage condition of the plurality of food materials.

Description

Technical Field

[0001] This application relates to the technical field of refrigeration equipment, and in particular to a refrigeration device, a control method for the refrigeration device, and a computer program product. Background Technology

[0002] Light regulation is an effective means of post-harvest preservation of food. Specific wavelengths of light can regulate the physiological metabolism of fruits and vegetables, delay food aging, and improve nutrient retention. Short-wavelength light can also sterilize the surface of food. Integrating light-based preservation light sources into refrigeration equipment such as refrigerators has become a technological development direction in the field of food preservation.

[0003] In related technologies, the light preservation scheme of refrigeration equipment is usually preset with a fixed light mode, which is only suitable for food with a single light requirement. After the light parameters are configured, they will not be dynamically adjusted according to the changes in the combination of food in the chamber.

[0004] However, fixed lighting strategies cannot meet the preservation requirements of different ingredients, and the effectiveness of intelligent preservation equipment is limited. Summary of the Invention

[0005] This application provides a refrigeration device, a control method for the refrigeration device, and a computer program product, which can solve the problem that a fixed lighting strategy cannot meet the preservation requirements of different foods and that the intelligent preservation effect of the device is limited.

[0006] In a first aspect, a refrigeration device is provided, comprising: The preservation chamber is configured for storing food ingredients; A multi-color light source, located in the preservation chamber, is configured to emit light of multiple colors. The controller is configured as follows: Identify the different light requirements of various ingredients in the preservation chamber; Based on the characteristics of the ingredients, the preservation value of various ingredients was evaluated; the preservation value of ingredients was positively correlated with the preservation priority of ingredients. When multiple lighting requirements exist that conflict with each other, including light-demanding and light-avoiding requirements, the basic lighting strategy is determined based on the highest preservation priority between the food preservation value of the food corresponding to the light-demanding type and the food preservation value of the food corresponding to the light-avoiding type. When multiple lighting requirements exist that do not simultaneously include light-demanding and light-avoiding types, the preset time-series isolation scheduling strategy is determined as the basic lighting strategy; the time-series isolation scheduling strategy is a strategy to provide corresponding lighting to ingredients with different lighting requirements at different times; Based on the adjustment of lighting parameters in the basic lighting strategy for various ingredients in the preservation chamber, a lighting scheduling strategy is generated. The operation of multicolor light sources is controlled based on the lighting parameters in the lighting scheduling strategy.

[0007] In the aforementioned technical solution, the controller identifies the light requirements of various ingredients within the preservation chamber, distinguishing between differentiated and even mutually exclusive light preservation needs of different ingredients. This addresses the problem that traditional light preservation methods cannot adapt to the varying light requirements of different types of ingredients. Subsequently, the controller quantitatively evaluates the preservation value of each ingredient based on its characteristics and establishes a positive correlation between preservation value and preservation priority. This allows for differentiated preservation priorities based on the actual preservation needs of the ingredients, avoiding the unreasonable model of unpriority allocation and equal distribution of light resources. Furthermore, when multiple ingredients within the preservation chamber experience conflicting light requirements, for cases where multiple light requirement types simultaneously include both light-demanding and light-avoiding types, the basic lighting strategy is determined based on the highest preservation priority between the light-demanding and light-avoiding ingredients. Conversely, for cases where multiple light requirement types do not simultaneously include both light-demanding and light-avoiding types, a pre-defined time-series isolation scheduling strategy is used as the basic lighting strategy. The time-series isolation scheduling strategy provides corresponding lighting to ingredients with different lighting requirements at different times. Based on this, a comprehensive judgment is made by combining the light requirements of the ingredients, conflict scenarios, and personalized preservation priorities to generate a lighting scheduling strategy. This can replace the traditional fixed lighting scheme, which cannot autonomously resolve lighting conflicts and can only rely on manual partitioning by the user, achieving intelligent autonomous arbitration and adaptation of lighting conflicts. Finally, based on the generated intelligent lighting scheduling strategy, the lighting parameters of the multi-color light source are dynamically adjusted so that the lighting mode output by the multi-color light source always adapts to the current combination of ingredients in the chamber, effectively taking into account the preservation needs of different ingredients and improving the overall preservation effect under mixed-ingredient conditions.

[0008] Secondly, a control method for a refrigeration device is provided, applied to the refrigeration device of the first aspect. The control method for the refrigeration device includes: Identify the different light requirements of various ingredients in the preservation chamber; Based on the characteristics of the ingredients, the preservation value of various ingredients was evaluated; the preservation value of ingredients was positively correlated with the preservation priority of ingredients. When multiple lighting requirements exist that conflict with each other, including light-demanding and light-avoiding requirements, the basic lighting strategy is determined based on the highest preservation priority between the food preservation value of the food corresponding to the light-demanding type and the food preservation value of the food corresponding to the light-avoiding type. When multiple lighting requirements exist that do not simultaneously include light-demanding and light-avoiding types, the preset time-series isolation scheduling strategy is determined as the basic lighting strategy; the time-series isolation scheduling strategy is a strategy to provide corresponding lighting to ingredients with different lighting requirements at different times; Based on the adjustment of lighting parameters in the basic lighting strategy for various ingredients in the preservation chamber, a lighting scheduling strategy is generated. Illumination is applied to various food ingredients based on the illumination parameters in the illumination scheduling strategy.

[0009] Thirdly, a computer-readable storage medium is provided, which stores a computer program that, when run by a refrigeration device, causes the refrigeration device to perform the control method for the refrigeration device described in the second aspect.

[0010] Fourthly, a computer program product is provided, comprising: a computer program that, when run by a refrigeration device, causes the refrigeration device to execute the control method for the refrigeration device described in the second aspect.

[0011] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0012] Figure 1 The timing interaction diagram of a control method for a refrigeration device in some embodiments of this application is shown; Figure 2 This is a flowchart illustrating one implementation method for determining the basic preservation value in a control method for a refrigeration device provided in this application embodiment; Figure 3 This is a flowchart illustrating one implementation method for calculating feature scores in a control method for a refrigeration device provided in this application embodiment; Figure 4 This is a flowchart illustrating one implementation method for calculating the preservation value of food in a control method for a refrigeration device provided in this application embodiment; Figure 5 This is a flowchart illustrating one implementation method for calculating the state correction coefficient in a control method for a refrigeration device provided in this application embodiment; Figure 6 This is a flowchart illustrating an implementation method for calculating user preference correction coefficients in a control method for a refrigeration device provided in this application embodiment; Figure 7 This is a flowchart illustrating an implementation method for generating a basic illumination strategy in a control method for a refrigeration device provided in this application embodiment; Figure 8 This is a flowchart illustrating an implementation method for generating a basic illumination strategy in a control method for a refrigeration device provided in another embodiment of this application; Figure 9This is a flowchart illustrating an implementation method for generating a lighting scheduling strategy in a control method for a refrigeration device provided in this application embodiment; Figure 10 This is a flowchart illustrating one implementation method for generating target illumination parameters in a control method for a refrigeration device provided in this application embodiment. Detailed Implementation

[0013] In real-world household use, refrigerators and other food storage compartments typically store multiple types of food simultaneously. These different foods have significantly different light requirements, and some even have mutually exclusive properties. Table 1 below shows the light requirements, typical types, and light-affecting characteristics of different food types.

[0014] Table 1:

[0015] Table 1 above is a comparison table of the light requirements and quality effects of different ingredients. The ingredients are divided into four categories to distinguish the different light requirements of each type of ingredient and the quality effects of light on the ingredients.

[0016] When multiple ingredients with conflicting light requirements are placed together in the same preservation chamber, existing technologies lack effective intelligent solutions and can only rely on users to manually divide and store the ingredients, resulting in extremely poor ease of use and preservation adaptability.

[0017] In order to solve the above problems, one embodiment of this application provides a refrigeration device. Please refer to [link to relevant documentation]. Figure 1 , Figure 1 The following is a timing interaction diagram illustrating a control method for a refrigeration device in some embodiments of this application, such as... Figure 1 As shown, the preservation chamber is configured for storing food; a multi-color light source is located in the preservation chamber and configured to emit light of multiple colors; the controller is configured to execute the following steps: S101. Identify the light requirements of various ingredients in the preservation chamber.

[0018] In one embodiment, the aforementioned multicolor light source is installed within the preservation chamber and can output light of various wavelengths / colors. The wavelength, intensity, and duration of the light can be switched according to the preservation needs of different ingredients. On one hand, it can output visible light such as red and blue light for periodic illumination of light-demanding fruits and vegetables, regulating their metabolism and enriching their nutrients. On the other hand, it can output short-wavelength light for periodic high-dose surface sterilization of antibacterial meats. Simultaneously, the light source can be turned off to meet the light-protected storage requirements of light-sensitive ingredients.

[0019] The above-mentioned ingredients are those stored in the preservation chamber. Correspondingly, the light requirement type is a pre-defined ingredient attribute label based on the post-harvest physiological characteristics of various ingredients and the effect of light on ingredient quality, used to characterize the different light requirements of ingredients.

[0020] For example, lighting requirements can include the following types: Light-protected: Foods that will sprout, turn green, or produce harmful substances when exposed to light; these need to be stored away from light. Neutral type: Short-term lighting has no obvious positive or negative effects; acceptable lighting, no need for mandatory lighting; Sterilization type: requires high dose of short-wave light to sterilize the surface of food; requires periodic high dose of short-wave light irradiation.

[0021] When multiple types of food with different light requirements exist in the preservation chamber at the same time, light requirement conflicts will occur. Based on this classification and the food preservation priority, the controller generates a light scheduling strategy.

[0022] As an example, the controller can first identify the type of food, and then determine the type of lighting required for the food based on a preset mapping relationship between types and categories.

[0023] The identification of food types can be achieved through image recognition and assisted input recognition. For example, the refrigeration equipment includes a camera sensor that can acquire images of the preservation chamber in real time or at regular intervals. Deep learning algorithms are then used to detect and classify the food, determining its major or minor categories. Subsequently, the required lighting type is determined based on the aforementioned mapping relationship.

[0024] For example, the types of ingredients can be shown in Table 2 below: Table 2:

[0025] Table 2 presents the food identification and classification system, which is the food classification standard used by the image recognition algorithm in the perception layer. It is used to detect and classify food within the preservation chamber after the camera captures images. The table adopts a two-level classification structure: Major Categories: Divided into three main categories: Fruits and Vegetables, Root Vegetables, and Meats; Subcategories: Further subdivided under the major categories; Fruits and Vegetables include Berries, Flowering Vegetables, Leafy Vegetables, Solanaceous Vegetables, and Citrus Vegetables; Root Vegetables include Tubers and Bulbs; Meats include Livestock Meat, Poultry Meat, and Aquatic Products.

[0026] Furthermore, the mapping relationship can be shown in Table 3 below: Table 3:

[0027] Table 3 is used to map the corresponding lighting requirement type based on the type of food ingredient. It is a mapping rule table for the controller to make lighting strategy decisions. The table contains four types of lighting requirements, each including the decision rules, typical food ingredients, and lighting strategy direction.

[0028] In another embodiment, the controller can also obtain food information manually entered by the user (e.g., touch input, scanning a code to enter the food name), and directly look up the table to match the corresponding lighting requirement type based on the entered food name.

[0029] S102. Based on the characteristics of the ingredients, evaluate the preservation value of various ingredients respectively.

[0030] Among them, the preservation value of food is positively correlated with the preservation priority of food.

[0031] In one embodiment, the aforementioned food characteristics are used to quantify a set of various attribute parameters for evaluating the preservation value of food. These food characteristics include, but are not limited to, characteristics such as perishability, economic value, nutrient density, scarcity, shelf life, initial freshness, volume, weight, or quantity of the food, etc., without limitation.

[0032] As an example, the controller can acquire images of the food inside the preservation chamber through a camera sensor, and then use a deep learning algorithm to identify the food images to obtain the aforementioned food characteristics.

[0033] Alternatively, the controller can generate the above-mentioned food characteristics by having the user manually input information (e.g., purchase time, purchase price, etc.) through the interactive interface.

[0034] Alternatively, after identifying the type of food, the inherent characteristics of the type can be directly retrieved from the built-in food database to obtain the aforementioned food characteristics.

[0035] In this embodiment, the method of obtaining the characteristics of the ingredients is not limited.

[0036] The above-mentioned food preservation value is a quantitative score calculated based on the characteristics of the food, which is used to characterize the comprehensive value of the food that needs to be prioritized for protection in this preservation scheduling; the higher the food preservation value, the higher the corresponding preservation priority (the two are positively correlated).

[0037] As an example, a preset weight can be assigned to the food characteristics. When there are multiple food characteristics, the product of the food characteristics and the preset weight can be determined as the food preservation value. Alternatively, a fixed preservation value level can be pre-stored in the database for each type of food characteristic, and the food preservation value can be retrieved directly by looking up the table after the food characteristics are identified.

[0038] The aforementioned food preservation priority is a ranking derived from the food's preservation value, representing the priority order of light resource allocation. When different foods have conflicting light requirements or light resources are limited, the controller prioritizes ensuring the light preservation needs of foods with higher preservation priority. The higher the food's preservation value, the higher its preservation priority.

[0039] It should be noted that when there are conflicts in lighting requirements among multiple types of lighting needs, the controller can generate a lighting scheduling strategy based on the preservation priority corresponding to the various lighting requirements and the preservation value of the food.

[0040] In one embodiment, conflicting light requirements refer to situations where two or more types of food with different light requirements are stored simultaneously in the preservation chamber, and the requirements of each type of food for light parameters (light quality, light duration, irradiation period, and whether to avoid light) are contradictory. Typically, this occurs in scenarios where it is impossible to use the same set of light parameters to simultaneously meet the preservation requirements of all food items.

[0041] For example, a light-demanding food (blueberries) and a light-avoiding food (potatoes) are placed in the same preservation chamber. Turning on the light will damage the light-avoiding food, while turning off the light will fail to meet the preservation requirements of the light-demanding food. This scenario constitutes a light requirement conflict. Alternatively, sterilization-grade meat requires short-duration, high-dose, short-wavelength light, while the light-avoiding food in the same space cannot tolerate any light, which also constitutes a light requirement conflict.

[0042] The aforementioned lighting scheduling strategy is a set of control commands for multi-color light sources output by the controller in the event of a lighting demand conflict, which combines the lighting demand type of each food item in the preservation chamber and the food preservation priority. These commands specify the light source's on / off time, light quality (wavelength), light intensity, and duration of a single irradiation.

[0043] Among them, the lighting scheduling strategy is used to prioritize the preservation needs of high-priority ingredients when the lighting requirements of all ingredients cannot be met at the same time, while minimizing the adverse effects of lighting on low-priority ingredients; the strategy can be dynamically updated as ingredients are added or removed.

[0044] As an example, the controller can select the scheduling strategy corresponding to the light requirement of the food with the highest preservation priority, and determine it as the aforementioned light scheduling strategy. Alternatively, the controller database can pre-store arbitration rule tables corresponding to different combinations of light requirement types and different priority orders; after identifying the current combination of food in the preservation chamber and their respective preservation priorities, the controller can directly look up the table to retrieve the preset light scheduling strategy.

[0045] For example, the controller can generate a lighting scheduling strategy according to the following steps S103-105.

[0046] S103. When multiple lighting requirements exist, including both light-demanding and light-avoiding requirements, a basic lighting strategy is determined based on the highest preservation priority between the food preservation value of the food corresponding to the light-demanding type and the food preservation value of the food corresponding to the light-avoiding type.

[0047] For example, the controller can determine the lighting strategy based on the lighting type corresponding to the food with the highest preservation priority.

[0048] The aforementioned basic lighting strategy is a preliminary lighting scheduling scheme obtained by comparing two sets of representative priorities in the context of conflicting scenarios involving light-demanding and light-avoiding food ingredients. It includes basic lighting parameters such as whether the light source is turned on, target light intensity, wavelength, and lighting duration.

[0049] In this scenario, the basic lighting strategy can be either a preset light-demand scheduling strategy or a preset light-avoidance scheduling strategy, without any limitation.

[0050] It should be noted that since the types of lighting requirements include both light-demanding and light-avoiding types, the basic lighting strategies described above can be either standard light-demanding strategies or standard light-avoiding strategies.

[0051] S104. When multiple lighting demand types exist and there are other conflicting demands that do not simultaneously include light-demanding and light-avoiding types, the preset time-series isolation scheduling strategy is determined as the basic lighting strategy.

[0052] Among them, the time-series isolation scheduling strategy is a strategy that provides corresponding light to ingredients with different light requirements at different times.

[0053] In one embodiment, a scenario that does not simultaneously include light-requiring and light-avoiding types refers to a combination of light-requiring and light-avoiding food items stored in the preservation cavity, where there are no combinations of other light-requiring types, and such combinations also conflict with each other.

[0054] For example, it may include only light-requiring and sterilization-resistant ingredients (such as blueberries + raw pork); only sterilization-resistant and neutral ingredients (such as fish + apples); only light-requiring and neutral ingredients (such as spinach + oranges); and only light-avoiding and neutral ingredients (such as potatoes + grapefruits).

[0055] Among them, sterile food requires light sterilization, but the duration and wavelength of light exposure will affect the sterilization effect, which may conflict with the irradiation duration and wavelength required for light-requiring food. Neutral food can receive short-term light exposure, which may also conflict with the irradiation duration corresponding to sterile and light-requiring food.

[0056] Among them, the time-series isolation scheduling strategy refers to dividing the preservation chamber into different time periods under the premise of sharing the same light source, outputting light parameters that are adapted to different light requirements at different time periods, and providing corresponding light to different ingredients in a time-series manner.

[0057] For example, the preservation chamber simultaneously stores blueberries (light-requiring type) and pork (sterilization type); in the first period, the light source outputs the specific wavelength and intensity required by the blueberries to meet the light-requiring preservation needs; in another period, the light source switches to high-dose short-wavelength light to achieve sterilization of the meat surface; the light source is turned off during the remaining periods. The same set of light sources is reused in a time-sharing manner, and different lighting schemes are implemented in different periods, so that two mutually exclusive lighting schemes are not applied at the same time.

[0058] It should be noted that when there are light-requiring and light-avoiding types in different scenarios, there is no strong mutual contradiction in the lighting requirements of various food ingredients that "lighting will produce irreversible harmful reactions". By adopting the time-series isolation (time-sharing lighting) method, the lighting requirements of different food ingredients can be met at different times without the need to permanently turn off the light source or continuously fix a certain type of lighting.

[0059] As an example, taking the lighting demand types as including light-demanding and sterilization-demanding types, the time-series isolation scheduling strategy can be shown in Table 4 below: Table 4:

[0060] As shown in Table 4, the time-series isolation scheduling strategy divides a day into five time periods, T01 to T05, and switches the light type and parameters at different times to provide suitable lighting for different types of food. By adopting the time-series isolation approach of time-series scheduling, the wavelength and intensity of the light source are switched at different times. During non-conflicting time periods, the light requirements for preserving light-demanding fruits and vegetables and the short-wavelength light surface sterilization requirements for sterilizing meats are met. The light source is turned off during the remaining long periods, which can avoid the energy consumption and food quality deterioration caused by continuous light.

[0061] S105. Based on the adjustment of lighting parameters in the basic lighting strategy for various ingredients in the preservation chamber, a lighting scheduling strategy is generated.

[0062] It should be noted that the light intensity, wavelength, duration of illumination at different times, and start and end times of illumination in the above basic lighting strategy are all preset default values. However, these preset default values ​​do not take into account the real-time and individual differences of the food inside the preservation chamber.

[0063] Therefore, directly using the basic lighting strategy cannot match the actual preservation status of the food inside the cavity, easily leading to problems such as insufficient light, excessive light, energy waste, or unsatisfactory preservation results. Therefore, it is necessary to adjust the lighting parameters of the basic lighting strategy based on the current food conditions to generate a customized lighting scheduling strategy.

[0064] The controller can adjust various lighting parameters based on information such as food preservation priority, food type, storage time, freshness, food quantity, and user preferences. For example, it can adjust parameters such as light wavelength, light intensity, different irradiation periods, duration of each period, and irradiation frequency, without limitation.

[0065] It's important to note that when a conflict in the light requirements of food ingredients is detected, the conflict type is first distinguished. When both light-requiring and light-avoiding ingredients exist simultaneously, corresponding ingredient groups are formed, and a basic lighting strategy is determined based on the highest preservation priority of each group. When neither type of ingredient coexists, a time-series isolation scheduling strategy is directly adopted as the basic lighting strategy. Subsequently, the lighting parameters of the basic lighting strategy are adapted and adjusted based on the various ingredients actually stored in the preservation chamber. This allows for the initial determination of a reasonable macro-scheduling framework through group arbitration, followed by dynamic and refined adjustment of lighting parameters based on the actual attributes of the ingredients. This not only resolves the strong mutually exclusive lighting conflict caused by the coexistence of light-requiring and light-avoiding ingredients but also allows for time-sharing of the light requirements of different ingredients in non-strongly mutually exclusive scenarios. This enables differentiated allocation of lighting resources based on the preservation priority of ingredients, improving the overall preservation effect in scenarios where multiple ingredients are stored together.

[0066] S106. Control the operation of multicolor light sources based on the lighting parameters in the lighting scheduling strategy.

[0067] In one embodiment, the above-mentioned illumination parameters are operating parameters of the multicolor light source that can be adjusted by the controller, including: light quality (light wavelength / color), light intensity, duration of a single illumination, illumination start time, illumination interval period, and light source start / stop status.

[0068] Among them, light quality: visible light is selected for nutrient enrichment in light-demanding fruits and vegetables; short-wavelength light is selected for surface sterilization of antibacterial meats; and turning off the light source meets the light-avoidance requirements of light-sensitive foods. Light intensity: controls the intensity of the output light. Timing parameters: control when to turn the lights on, when to turn them off, the duration of illumination, and how often to perform illumination.

[0069] Understandably, the lighting scheduling strategy has clearly defined the lighting parameters required for each time period; therefore, the controller reads this strategy and adjusts the multi-color light source in real time so that the light source outputs matching lighting at the corresponding time.

[0070] It should be noted that in a conflict-free scenario, the controller can directly use fixed lighting parameters according to the uniform lighting requirements of the food in the preservation chamber; however, in a conflict scenario, the lighting parameters can be adjusted as shown in the example above to meet the lighting requirements of food with different priorities.

[0071] For example, the lighting scheduling strategy can be defined as follows: output blue light from 8:00 to 10:00 every day, and turn off the light source during the rest of the time. The controller reads this strategy, automatically turns on the blue light channel of the multi-color light source at 8:00 and sets the corresponding light intensity; turns off the light source at 10:00, completing the parameter adjustment and matching the strategy requirements.

[0072] In this embodiment, the controller identifies the light requirements of various ingredients within the preservation chamber, distinguishing between differentiated and even mutually exclusive light preservation needs of different ingredients. This addresses the problem that traditional light preservation methods cannot adapt to the varying light requirements of different types of ingredients. Subsequently, the controller quantitatively evaluates the preservation value of each ingredient based on its characteristics and establishes a positive correlation between preservation value and preservation priority. This allows for differentiated preservation priorities based on the actual preservation needs of the ingredients, avoiding the unreasonable model of undifferentiated priority and equal distribution of light resources. Furthermore, when multiple ingredients within the preservation chamber experience conflicting light requirements, for cases where multiple light requirement types simultaneously include both light-demanding and light-avoiding types, the basic lighting strategy is determined based on the highest preservation priority between the light-demanding and light-avoiding ingredients. Conversely, for cases where multiple light requirement types do not simultaneously include both light-demanding and light-avoiding types, a preset time-series isolation scheduling strategy is used as the basic lighting strategy. The time-series isolation scheduling strategy provides corresponding lighting to ingredients with different lighting requirements at different times. Based on this, a comprehensive judgment is made by combining the light requirements of the ingredients, conflict scenarios, and personalized preservation priorities to generate a lighting scheduling strategy. This can replace the traditional fixed lighting scheme, which cannot autonomously resolve lighting conflicts and can only rely on manual partitioning by the user, achieving intelligent autonomous arbitration and adaptation of lighting conflicts. Finally, based on the generated intelligent lighting scheduling strategy, the lighting parameters of the multi-color light source are dynamically adjusted so that the lighting mode output by the multi-color light source always adapts to the current combination of ingredients in the chamber, effectively taking into account the preservation needs of different ingredients and improving the overall preservation effect under mixed-ingredient conditions.

[0073] In another embodiment, the controller can be based on, for example... Figure 2 The steps S201-S204 shown here assess the preservation value of food ingredients, and are detailed below: S201. For any ingredient, calculate the feature score of the ingredient characteristics.

[0074] In one embodiment, the feature score is a quantitative score that transforms the qualitative description of food features into a preset range (e.g., 0~100, or 0~1) for unified dimension calculation.

[0075] The calculation methods for feature scores can differ depending on the characteristics of the ingredients. For example, the controller can pre-build a database to classify each feature of each ingredient category into levels and assign fixed scores. After identifying the ingredient type, it directly retrieves the preset score for the corresponding feature from the table.

[0076] Alternatively, a mapping function can be established between the original feature parameters and the feature scores. The collected original values ​​are input into the function, and the feature scores are output.

[0077] For example, when the ingredient characteristic is the unit price, feature scoring can be mapped using a linear function. For example, when the ingredient characteristic is the unit price, an ingredient unit price of 100 yuan / kg = 100 points, 50 yuan / kg = 50 points, and 10 yuan / kg = 10 points.

[0078] It should be noted that each ingredient feature can generate an independent feature score, eliminating the problem of inconsistent dimensions for different features and facilitating subsequent calculations.

[0079] S202. If the number of food characteristics is 1, then the characteristic score is determined as the basic preservation value.

[0080] S203. If there are multiple characteristics of the ingredients, the weighted sum of the scores of the multiple characteristics shall be used to determine the basic preservation value.

[0081] In one embodiment, when only one food feature is included in the evaluation, the score of that feature can be directly used as the basic preservation value; when there are multiple food features, the scores of all features can be weighted and summed to calculate the basic preservation value.

[0082] The weighting coefficients for different food characteristics can be the same or different, and there is no restriction on this.

[0083] S204. The basic preservation value is modified to obtain the food preservation value.

[0084] In one embodiment, the controller can add or multiply a correction factor to the basic preservation value to obtain the final food preservation value, reflecting the real-time status of the food after storage.

[0085] The correction factor can be determined based on the storage time of the food. For example, the longer the storage time, the higher the risk of spoilage, the larger the correction factor, thus increasing the final preservation value of the food and raising its priority. Alternatively, the correction factor can also be a preset fixed value.

[0086] In this embodiment, the method of modifying the basic preservation value is not limited.

[0087] In this embodiment, feature scores are obtained by quantifying the characteristics of ingredients. A basic preservation value is calculated based on the number of ingredient features using either direct assignment or weighted summation. This basic preservation value is then further adjusted to obtain the final food preservation value. This approach transforms multi-dimensional ingredient characteristics into comparable quantitative indicators. Furthermore, it supports not only simple evaluation of single ingredient features but also comprehensive evaluation of multiple ingredient features, and the adjustment of the basic preservation value ensures that the final food preservation value closely matches the actual preservation needs of the ingredients, improving the accuracy and flexibility of preservation priority determination.

[0088] As an example, the controller can be based on, for example... Figure 3 The steps S301-S304 shown below calculate the scores for each feature, and are described in detail below: S301. When the ingredient characteristic is the unit price of the ingredient, calculate the economic value score of the ingredient based on the unit price of the ingredient, and determine the feature score by multiplying the economic value score by the preset economic coefficient.

[0089] Among them, the economic value score is used to quantify the market economic value of ingredients.

[0090] In one embodiment, the unit price of the food ingredient refers to the market transaction price corresponding to the unit weight (e.g., yuan / kg) or unit volume of the food ingredient. It is the original basic data that characterizes the market economic value of the food ingredient and can be obtained by pre-storing in the database, querying online, or manually entering by the user.

[0091] Among them, the economic value score is used to quantify the economic value of food ingredients in the market. The controller can map the unit price of food ingredients to a uniform score range (such as 0~100 points) to achieve dimensional normalization. For example, the controller can first determine the upper and lower price thresholds and then linearly scale the unit price of the ingredients. For instance, the formula could be: Economic Value Score = (Unit Price of Ingredients) (Lowest unit price) / (Highest unit price) (Minimum unit price) × maximum score. The higher the unit price, the higher the economic value score.

[0092] Alternatively, a segmented grading method can be used: price ranges are pre-defined, and different ranges are assigned fixed scores. For example, if the unit price of an ingredient is >50 yuan / kg, the economic value score is 90; if the unit price of an ingredient is between 10 and 50 yuan / kg, the economic value score is 50; and if the unit price of an ingredient is <10 yuan / kg, the economic value score is 20.

[0093] For example, the method for determining the economic value score can be shown in Table 5 below: Table 5:

[0094] Table 5 above shows the rules for looking up the economic value score. The market price per kilogram of ingredients is used as the search condition. Multiple price ranges are divided, and each range is matched with a corresponding economic value score V1 and a typical ingredient. After the controller identifies the ingredient, it can look up V1 in this table and then multiply it by a preset economic coefficient to obtain the feature score corresponding to the unit price of the ingredient.

[0095] In another embodiment, the controller can perform a logarithmic transformation on the unit price of the ingredients and then linearly map it to a preset scoring range to obtain an economic value score.

[0096] Logarithmic transformation refers to taking the logarithm of the unit price of ingredients, which is a non-linear numerical transformation. It should be noted that human price perception exhibits diminishing marginal returns: a small price increase in the low-price range results in a significant change in perceived value; conversely, a 10 yuan increase in the high-price range yields only a slight increase in perceived value.

[0097] Therefore, directly using the original unit price for linear scoring will excessively amplify the scores of high-priced ingredients, severely squeezing the priority weight of ordinary ingredients. However, logarithmic transformation can compress the numerical differences in the high-price range and amplify the numerical differences in the low-price range, making the calculated economic value score more in line with people's subjective perception of the value of ingredients.

[0098] The preset scoring range can be set by the user, for example, it can be 10 to 100 points. This is the target score range after logarithmic transformation and linear normalization. The lower limit of 10 points corresponds to the lowest unit price of the ingredient, avoiding a score of 0; the upper limit of 100 points corresponds to the highest unit price of the ingredient. After logarithmic transformation, the unit price is linearly scaled so that all scores fall within this 10 to 100 score range, and the output result is the economic value score.

[0099] In this method, the logarithm is applied to the unit price of the ingredients, taking the natural logarithm ln(unit price). The logarithmic result is then linearly mapped to the scoring interval to obtain the economic value score. In this embodiment, the formula for the linear mapping is not limited.

[0100] As an example, if the unit price of an ingredient is 5 yuan / kg, ln5 is approximately 1.609, and the economic value score after linear mapping is approximately 31 points. Conversely, if the unit price of an ingredient is 15 yuan / kg, ln15 is approximately 2.708, and the economic value score after linear mapping is approximately 45 points. When the unit price of an ingredient increases from 5 to 15 yuan, the price increases by 10 yuan, and the score increases by approximately 14 points, demonstrating a significant perceived difference.

[0101] Furthermore, if the unit price of the ingredient is 80 yuan / kg, ln80 is approximately 4.382, and the economic value score after linear mapping is approximately 67 points. If the unit price of the ingredient is 90 yuan / kg, ln90 is approximately 4.499, and the economic value score after linear mapping is approximately 68.5 points. Increasing the unit price of the ingredient from 80 to 90 yuan, an increase of 10 yuan, only raises the score by about 1.5 points.

[0102] Based on the above example, it can be considered that the method of linearly mapping the unit price of ingredients to the preset scoring range after logarithmic transformation can reflect the diminishing marginal effect mentioned in the annotation: the score change caused by price changes in the low price range is much greater than that in the high price range.

[0103] In this embodiment, an economic value score is obtained by performing a logarithmic transformation on the unit price of ingredients and then linearly mapping it to a preset scoring range. This approach matches the diminishing marginal returns of people's perception of ingredient prices. Furthermore, it can sensitively distinguish the value differences of affordable ingredients in the low-price range, while compressing the score increase of high-priced ingredients. This prevents excessive amplification of the score for extremely high-priced ingredients from monopolizing the priority of preservation, ensuring that the economic value score aligns with the user's true value perception and guaranteeing a balanced and reasonable assessment of the preservation value of ingredients in scenarios where multiple ingredients are stored together.

[0104] In one embodiment, the aforementioned preset economic coefficient is a pre-configured weight adjustment parameter used to adjust the contribution ratio of the economic value dimension in the overall feature score; this coefficient can be fixed according to product design requirements or can be customized by the user, and there is no limitation on this.

[0105] The preset economic coefficient can control the degree of influence of economic value on the final feature score; the larger the coefficient, the higher the weight of economic value in the feature score.

[0106] S302. When the food ingredient characteristic is recommended storage time, calculate the perishability score of the food ingredient based on the recommended storage time, and determine the feature score by multiplying the perishability score by the preset perishability coefficient.

[0107] The perishability score is used to quantify the urgency of preserving food.

[0108] In one embodiment, the recommended storage time refers to the preset maximum storage time under the standard preservation environment of this refrigeration equipment, during which the food can maintain its edible quality. The unit can be days or hours. This data is pre-stored in the controller database and can be retrieved according to the type of food, or it can be updated online or manually entered by the user. The shorter the recommended storage time, the more easily the food spoils, and the higher the urgency of preservation.

[0109] Among them, the perishability score is used to quantify the urgency of food preservation. The controller can convert the recommended storage time into a quantitative score within a uniform range (0~100 points).

[0110] For example, the reciprocal of the recommended storage period is used as a basis, and then normalized and scaled. The shorter the storage period, the larger the reciprocal value, and the higher the perishability score. It can be understood that the urgency of preservation is inversely proportional to the recommended storage period; the shorter the storage window, the more important it is to prioritize light preservation.

[0111] Alternatively, recommended storage durations can be pre-defined, with each duration tied to a fixed perishability rating range.

[0112] For example, the method for determining the perishability score can be shown in Table 6 below: Table 6:

[0113] Table 6 shows the lookup rules for perishability scores. The recommended storage time of the ingredients is used as the retrieval condition to divide the ingredients into multiple time ranges. Each range is matched with a corresponding perishability score V2 and a typical ingredient. After the controller identifies the ingredient, it looks up V2 in this table and multiplies it by a preset perishability coefficient to obtain the feature score corresponding to the recommended storage time, which is used for the quantitative evaluation of the freshness value of the ingredients.

[0114] In another embodiment, the controller can input the recommended storage duration into a preset exponential decay function to obtain a perishability score.

[0115] The exponential decay function exhibits the following characteristics: the smaller the recommended storage time D (the less resistant the food is to storage), the higher the perishability score V2; as D increases, V2 decreases rapidly and exponentially. This mathematical model aligns with the spoilage patterns of fresh food: the shorter the shelf life, the more exponentially the urgency to preserve freshness increases; within the short shelf life range, even small changes in storage time can lead to significant changes in the V2 score, amplifying the differences in urgency to preserve freshness among extremely perishable foods; within the long shelf life range, as storage time continues to increase, the decline in the V2 score tends to level off, weakening the differences in scores among storable foods.

[0116] As an example, the exponential decay function can be: V2=100 e^(-0.05 D); V2 represents the perishability score, and D indicates the recommended storage period.

[0117] For example, when D=2, V2 is approximately 90 points; when D=4, V2 is approximately 82 points; when D=50, V2 is approximately 8 points; and when D=60, V2 is approximately 5 points.

[0118] Based on the above examples, when the recommended storage period increases from 2 days to 4 days, V2 decreases by about 8 points. For short-shelf-life foods, even a small change in storage time can lead to a significant difference in urgency. When the recommended storage period increases from 50 days to 60 days, V2 only decreases by about 3 points. For long-shelf-life foods, even with a large change in storage time, the freshness urgency score changes very little.

[0119] In this embodiment, the recommended storage duration is input into a preset exponential decay function to calculate the perishability score. This approach closely reflects the spoilage patterns of fresh ingredients, amplifies the differences in preservation urgency scores between ingredients with short storage durations, highlights the preservation priority of extremely perishable ingredients, and smooths out score changes for ingredients with long storage durations. Furthermore, this avoids storing more durable ingredients from consuming excessive light preservation resources, making the quantification of preservation urgency in mixed-ingredient scenarios more accurately reflect the actual spoilage risk of the ingredients.

[0120] In one embodiment, the aforementioned preset perishability coefficient is a pre-configured weight adjustment parameter used to adjust the contribution ratio of the perishability feature in the overall feature score; this coefficient can be set fixedly or can be customized by the user.

[0121] The larger the preset perishability coefficient, the stronger the influence of the perishability dimension on the final feature score.

[0122] S303. When the food ingredient characteristic is a nutritional grade, obtain the nutritional density score corresponding to the nutritional grade, and determine the product of the nutritional density score and the preset nutritional coefficient as the feature score.

[0123] Among them, the nutrient density score is used to quantify the overall nutrient richness of food ingredients.

[0124] In one embodiment, the aforementioned nutritional grade is a grade label that classifies the richness of the comprehensive nutrients in the food, and is pre-stored in the controller database. This nutritional grade can be classified by comprehensively considering the types and contents of nutrients such as vitamins, minerals, dietary fiber, and antioxidants contained in the food.

[0125] For example, the nutritional level can be high, medium, or low. A higher nutritional level indicates a richer overall nutrient content per unit mass of food. This level can be pre-stored, updated online, or manually entered by the user.

[0126] For example, spinach and blueberries are classified as high-nutrition-level; apples and tomatoes are classified as medium-nutrition-level; and potatoes and dried starchy foods are classified as low-nutrition-level.

[0127] The nutrient density score is used to quantify the richness of a food's overall nutrients, and the score is generally normalized to a range of 0-100. As an example, the controller can pre-establish a mapping relationship between nutrient levels and nutrient density scores, identify the type of food, retrieve its nutrient level, and directly obtain the corresponding nutrient density score from a table.

[0128] For example, the method for determining the nutrient density score can be shown in Table 7: Table 7:

[0129] Table 7 shows the rules for looking up the nutrient density score. Ingredients are divided into four nutrient levels: very high, high, medium, and low. Each level is matched with a corresponding nutrient density score V3, evaluation criteria, and typical ingredients. After the controller identifies the ingredient, it looks up V3 in this table and multiplies it by a preset nutrient coefficient to obtain the characteristic score corresponding to the nutrient level, which is used for the quantitative evaluation of the freshness value of the ingredients.

[0130] Alternatively, one can read the nutrient content data of the food, assign weights to different nutrients such as vitamins, polyphenols, minerals, and dietary fiber, and then normalize the weighted sum to a score range of 0-100 to obtain a nutrient density score. The more types and higher the content of nutrients, the higher the score.

[0131] In this embodiment, the method for determining the nutrient density score is not limited.

[0132] In one embodiment, the preset nutrient coefficient is a pre-configured weight adjustment parameter used to adjust the contribution ratio of the nutrient density feature in the overall feature score; the preset nutrient coefficient can be fixed or can be customized by the user.

[0133] The larger the preset nutrient coefficient, the stronger the influence of the nutrient density dimension on the final feature score.

[0134] As an example, taking blueberries as the ingredient, the nutritional level is identified as very high; the nutritional density score obtained from the table is 90 points; the preset nutritional coefficient is 0.15; the feature score is 90 × 0.15 = 13.5 points.

[0135] S304. When the characteristics of the ingredients are the ripening season and geographical distribution, determine the seasonality coefficient and regionality coefficient of the ingredients based on the ripening season and geographical distribution, calculate the scarcity score of the ingredients based on the seasonality coefficient and regionality coefficient, and determine the feature score by multiplying the scarcity score by the preset scarcity coefficient.

[0136] Among them, the scarcity score is used to quantify the degree to which regional conditions and seasonal factors constrain the availability of food supplies.

[0137] In one embodiment, the ripening season of the ingredients determines the production window of the ingredients in the natural environment. Ingredients in the off-season rely more on greenhouse cultivation and long-distance cold chain transportation, resulting in a decrease in supply and increased difficulty in obtaining them. Geographical distribution represents the original suitable planting area of ​​the ingredients. When the ingredients are far away from the original production area, the transportation cost is high and the circulation is limited.

[0138] Based on the above explanation, it can be considered that the availability of ingredients is jointly constrained by the ripening season and geographical distribution: the further away from the ripening season and the farther away from the original production area the ingredients are, the less market supply there is and the higher the scarcity of the ingredients; conversely, when the ingredients are in ripening season and located near the original production area, the supply of ingredients is sufficient and the scarcity is lower.

[0139] For example, the Chinese bayberry (Yangmei) is native to the Jiangnan region of my country, and its natural ripening season is June. Scenario: In the Jiangnan region, June is both the original production area and the ripening season, resulting in ample supply and low scarcity. Scenario: In the northern region, December is not the original production area and the ripening season; relying on cold chain or greenhouse cultivation, the supply is low, resulting in high scarcity.

[0140] Among them, the seasonality coefficient is a quantitative parameter that characterizes the degree to which food supply is affected by the season. When food is in its natural ripening season, the coefficient value is low. The further away from the ripening season, the higher the coefficient value, which means that the supply constraints brought by the season are stronger.

[0141] The regionality coefficient is a quantitative parameter that characterizes the degree to which food supply is affected by the region of origin. The coefficient is low when the food is in its original production area, and the coefficient is higher the farther away from the original production area, which means that the supply constraint brought by the region is stronger.

[0142] Based on the above explanation, it can be considered that the higher the values ​​of the seasonality coefficient and the regionality coefficient, the stronger the constraint of season / region on the availability of food supply, and the higher the scarcity of food.

[0143] As an example, the controller can pre-store the seasonal and regional price ranges for each type of ingredient, as well as the seasonal and regional coefficients associated with each price range. After identifying the type of ingredient, the controller, combined with the current time and the geographical location of the device, queries the database to directly retrieve the corresponding coefficients.

[0144] Alternatively, a continuous mapping function can be established to calculate the seasonality coefficient based on the time difference between the current date and the peak season for food ripening; and the regionality coefficient based on the geographical distance between the equipment location and the main production area of ​​the food; the greater the time difference and geographical distance, the higher the corresponding coefficient.

[0145] In this embodiment, the method for determining the seasonality coefficient and the regionality coefficient is not limited.

[0146] For example, the seasonality coefficient and the regionality coefficient can both range from [-1, +1]. Specifically, when the current time is off-season for the food, the seasonality coefficient S{season} = +1, indicating that the food is deviating from its natural ripening window, supply is decreasing, and seasonal supply constraints are strong. When the current time is in season for the food, the seasonality coefficient S{season} = 0, indicating that the food is in its natural ripening and harvesting period, local supply is sufficient, and there are no seasonal constraints. When the current time is past season for the food, the seasonality coefficient S{season} = -1, the natural production season has ended, market inventory is gradually decreasing, and supply constraints are weakest.

[0147] Furthermore, when the ingredients are not primarily produced locally, the regionality coefficient S{region} = +1, indicating that the ingredients rely on long-distance imports and transportation, resulting in strong regional supply constraints; when the ingredients are primarily produced locally, the regionality coefficient S{region} = -1, indicating that the ingredients have low circulation costs, ample supply, and the weakest regional constraints.

[0148] In one embodiment, the scarcity score can be obtained by multiplying a seasonality coefficient and a regionality coefficient, and then normalizing the product to the range of 0 to 100. Seasonal constraints and regional constraints are superimposed on each other; as either constraint increases, the scarcity score increases synchronously.

[0149] Alternatively, the seasonality coefficient and regionality coefficient can be combined to divide the data into multiple tiers, with each tier directly matched to the corresponding scarcity score.

[0150] As an example, the scarcity score can also be calculated as shown in Table 8 below: Table 8:

[0151] Table 8 shows the rules for looking up the scarcity score of ingredients. The availability of ingredients is divided into four scarcity levels: extremely scarce, scarce, normal, and sufficient. Each level is matched with a corresponding scarcity score V4, evaluation criteria, and typical ingredients. The controller combines the information of ingredient type, season, and region to look up V4 in this table, and then multiplies it by a preset scarcity coefficient to obtain the feature score corresponding to the scarcity dimension, which is used for the quantitative evaluation of the preservation value of ingredients.

[0152] In this embodiment, the method for calculating the scarcity score of ingredients is not limited.

[0153] In another embodiment, the controller can calculate the first product of the seasonality coefficient and the preset seasonal score, and the second product of the regionality coefficient and the preset regional score; finally, the first product, the second product and the basic scarcity score are summed to obtain the scarcity score.

[0154] In one embodiment, the preset seasonal score is a pre-set weight constant, representing the maximum contribution of seasonal factors to the scarcity score V4; the seasonality coefficient is multiplied by the preset seasonal score to obtain a first product, which is used to quantify the increase or decrease in scarcity caused by seasonal factors.

[0155] Furthermore, the aforementioned preset regional score is a pre-set weight constant, representing the maximum contribution magnitude of regional factors to the scarcity score V4; the regional coefficient multiplied by the preset regional score yields a second product, which is used to quantify the increase or decrease in scarcity brought about by regional factors.

[0156] The above-mentioned basic scarcity score is the baseline constant for the scarcity score. It is the basic score without the superposition of seasonal and regional disturbances. It serves as the baseline starting point for V4 calculation, ensuring that the final V4 falls within the effective range of 10 to 100.

[0157] For example, taking winter fresh blueberries (out-of-season + imported and scarce), with a preset seasonal score of 30, a preset regional score of 20, and a basic scarcity score of 50, S{season}=+1, S{region}=+1, V4=50+1×30+1×20=100.

[0158] In this embodiment, economic value scores, perishability scores, nutrient density scores, and scarcity scores are calculated for four categories of food characteristics: unit price, recommended storage time, nutritional grade, and seasonal and geographical distribution of food. These scores are then multiplied by corresponding preset economic, perishability, nutritional, and scarcity coefficients to obtain the feature scores for each dimension. This allows for the quantification of food value from multiple dimensions, including economic loss risk, urgency of preservation, nutritional quality, and difficulty of supply acquisition. This ensures that the assessment of food preservation priority takes into account multiple influencing factors, and the assessment results are more closely aligned with actual user scenarios. Furthermore, in scenarios involving mixed food storage with limited light preservation resources, this enables refined allocation of light resources, prioritizing the preservation of high-value, high-urgency foods.

[0159] It should be noted that the characteristics of the ingredients can be one or more of the following: unit price, recommended storage time, nutritional grade, harvest season, and geographical distribution. If the ingredients have multiple characteristics, then when weighting and summing the scores of multiple characteristics, a preset economic coefficient greater than a preset perishability coefficient, a preset perishability coefficient greater than a preset nutritional coefficient, and a preset nutritional coefficient greater than a preset scarcity coefficient can be set.

[0160] For example, the preset economic coefficient can be 0.4, the preset perishability coefficient can be 0.35, the preset nutritional coefficient can be 0.15, and the preset scarcity coefficient can be 0.10.

[0161] Among these factors, the most direct loss for users is the economic cost of purchasing ingredients. The higher the market price of ingredients, the greater the direct economic loss from spoilage. Therefore, economic value is the primary factor in priority judgment, and a maximum preset economic coefficient can be assigned. Furthermore, perishability directly determines the rate of spoilage and is a core indicator of the urgency of preservation. Under the same light preservation resources, ingredients with shorter shelf lives are more prone to rapid spoilage and require priority resource allocation; its importance is second only to economic value, hence the preset perishability coefficient is ranked second. Additionally, nutrient density reflects the nutritional value of ingredients and represents an inherent quality loss. Nutrient loss reduces the edible value of ingredients, but the rate of nutrient degradation is usually slower than spoilage and is not a primary consideration for users; therefore, the preset nutrient coefficient is lower than the preset perishability coefficient. Finally, scarcity reflects the difficulty of obtaining ingredient supply; scarce ingredients have high replacement costs, but scarcity itself does not necessarily mean rapid spoilage or a directly corresponding high purchase price. Therefore, this preset scarcity coefficient can be set to a minimum value.

[0162] In this embodiment, a basic value scoring model is constructed by configuring preset economic coefficients, preset perishability coefficients, preset nutritional coefficients, and preset scarcity coefficients in descending order, thus aligning with the actual food loss logic of users. Furthermore, in scenarios involving mixed food storage with limited light resources, a more reasonable preservation priority can be output, prioritizing the protection of high-priced, rapidly perishable ingredients, improving overall preservation benefits, and avoiding resource misallocation.

[0163] In another embodiment, the controller can be based on, for example... Figure 4 The steps S401-S404 shown here correct the basic preservation value, detailed below: S401. Obtain the freshness and storage time of the ingredients, as well as the user's historical behavior data regarding the ingredients.

[0164] In one embodiment, the above-mentioned freshness is an indicator that characterizes the degree of current quality degradation of the ingredients; the higher the freshness, the better the quality of the ingredients.

[0165] The controller can capture images of the food's appearance using built-in cameras in the preservation chamber, identifying characteristics such as color, wilting, mold, and spots. It then compares these images to a pre-set image sample library to output a freshness score. Alternatively, it can use gas sensors within the preservation chamber to detect ethylene and carbon dioxide concentrations, and infer the food's freshness based on changes in gas concentration. Alternatively, users can manually input the food's freshness level via the refrigeration equipment's interactive panel or a mobile app.

[0166] As an example, different visual characteristics can be extracted as a basis for judgment for different types of food. For example, for fruits and vegetables: color saturation, surface gloss, degree of wilting, and percentage of spots / browning area; for meat: color (gradually changing from bright red to dark red and then browning), surface moisture, and texture clarity; for root vegetables: skin integrity, signs of sprouting, and degree of skin wrinkling.

[0167] In this embodiment, the controller can classify the freshness of ingredients into four levels: extremely fresh, fresh, average, and not fresh, and set corresponding freshness factors for each range: the freshness factor for the extremely fresh level ranges from 1.3 to 1.5, and the identification characteristics are bright color, no blemishes, and plump shape; the freshness factor for the fresh level ranges from 1.0 to 1.3, and the identification characteristics are normal appearance of ingredients with slight marks; the freshness factor for the average level ranges from 0.8 to 1.0, and the identification characteristics are slight fading of ingredients with a few spots; the freshness factor for the not fresh level ranges from 0.5 to 0.8, and the identification characteristics are obvious fading of ingredients, wilting, and increased spots.

[0168] In one embodiment, the aforementioned storage time is the cumulative storage time from the time the food was placed in the preservation chamber to the current moment, which is used to calculate the storage time factor and participate in the correction of the storage compensation coefficient.

[0169] When the controller detects new food ingredients in the preservation chamber (image recognition / user input), it automatically records the entry timestamp and calculates the difference between the current entry time and the entry time in real time to obtain the storage time.

[0170] Alternatively, users can manually enter the time when the food was placed in the refrigerator, and the controller will start timing based on the entered time.

[0171] The aforementioned historical behavior data comprises users' historical operations and usage preferences related to this ingredient, used to assist in adjusting the ingredient's preservation value and lighting scheduling strategies. Examples include the time the user retrieves the ingredient, the frequency of retrieval, discard records, historical confirmation / modification operations regarding the ingredient's lighting scheme, and ingredient preference tags.

[0172] For example, if a user frequently eats strawberries, has manually increased the light parameters for strawberries, or has repeatedly discarded potatoes, this will be considered historical behavioral data.

[0173] The controller can record and store user operations on the local interactive panel of the refrigeration equipment, and directly read the locally stored historical operation logs. Alternatively, user operations on food management via the linked mobile app (entering ingredients, modifying lighting strategies, marking ingredients for discard) can be synchronized to the controller of the refrigeration equipment.

[0174] S402. Calculate the state correction factor for ingredients based on freshness and storage time.

[0175] In one embodiment, the aforementioned state correction coefficient is a parameter used to correct the basic preservation value, characterizing the degree of influence of the current storage state of the food on its preservation value; the lower the freshness of the food and the longer it has been stored, the smaller the state correction coefficient is usually, thereby reducing the final preservation value of the food.

[0176] As an example, the controller can pre-build a state correction coefficient lookup table, which stores the state correction coefficients corresponding to different freshness ranges and different storage duration ranges. After obtaining the freshness and storage duration of the ingredients, the controller directly matches the lookup table and reads the corresponding state correction coefficient.

[0177] S403. Generate user preference correction coefficients for food ingredients based on historical behavior data.

[0178] In one embodiment, the aforementioned user preference correction coefficient is a dimensionless correction parameter used to characterize the user's subjective emphasis on the current food ingredients, and is generated in combination with the user's historical behavior data.

[0179] The food preservation value is calculated by multiplying the user preference correction coefficient by the basic preservation value and the state correction coefficient. The more a user prefers a particular food and the more frequently they use it, the larger the user preference correction coefficient becomes, thus increasing the final preservation value and preservation priority of the food. If a user frequently discards the food or rarely uses it, the coefficient will be smaller, reducing its preservation value.

[0180] As an example, the controller can use the historical frequency of food consumption as input to match the corresponding user preference correction coefficient range. For instance, high-frequency consumption (≥3 times per week) corresponds to a user preference correction coefficient of 1.2~1.4; medium-frequency consumption (1~2 times per week) corresponds to a user preference correction coefficient of 1.0; low-frequency consumption (less than 1 time per month) corresponds to a user preference correction coefficient of 0.6~0.9; and if there are multiple discard records, the user preference correction coefficient is 0.4~0.6.

[0181] Alternatively, extract multi-dimensional historical behavior data, assign weights to each, and sum them up to obtain the user preference correction coefficient.

[0182] S404. Multiply the state correction coefficient, user preference correction coefficient, and basic preservation value to obtain the food preservation value.

[0183] In one embodiment, after obtaining the preservation value of the food, if the preservation value of the food is greater than a preset score, the preset score can be determined as the preservation value of the food. For example, the preset score can be 100.

[0184] In this embodiment, a state correction coefficient is calculated by combining the freshness of the ingredients and their storage time, and a user preference correction coefficient is generated based on historical user behavior data. The food preservation value is obtained by multiplying the state correction coefficient and the user preference correction coefficient by the basic preservation value. This approach simultaneously considers the objective degradation of the food's storage quality and the user's subjective eating preferences, enabling a dynamic and personalized quantitative assessment of the food preservation value. Consequently, the resulting preservation priority is more closely aligned with the actual state of the ingredients and user habits, thereby improving the rationality of the lighting scheduling strategy and the user experience.

[0185] In another embodiment, the controller can be based on, for example... Figure 5 The steps S501-S503 shown below determine the state correction coefficients, and are described in detail below: S501. Determine the freshness factor corresponding to freshness.

[0186] Among them, the freshness factor is positively correlated with freshness.

[0187] In one embodiment, the freshness factor is a dimensionless factor that characterizes the freshness of the appearance of food ingredients. The higher the freshness, the larger the value of the freshness factor, and the two are positively correlated. This factor is used as an input quantity to calculate the state correction coefficient.

[0188] The controller can determine the freshness factor through the content in S401 above, or, in combination with the type of food and storage time, calculate the freshness level of the food, and then query the preset mapping table to obtain the corresponding freshness factor.

[0189] In this embodiment, the method for determining the freshness factor is not limited.

[0190] S502. Determine the storage duration factor based on the ratio of the storage duration to the recommended storage duration corresponding to the food ingredients.

[0191] In one embodiment, the above-mentioned recommended storage time is the preset recommended maximum preservation storage time for the food ingredient, which is a reference time limit for the suitable storage of the food ingredient.

[0192] The recommended storage time can be pre-stored in the controller database, corresponding one-to-one with the type of food; it can also be obtained by reading the food traceability label or querying the online food database.

[0193] The storage duration factor mentioned above is a dimensionless correction factor that characterizes the freshness urgency of food based on its storage time. The closer the food is to being stored and the lower its proportion in the storage period, the larger the storage duration factor value, indicating a higher freshness urgency; the longer the food is stored and the closer it is to or beyond its shelf life, the smaller the storage duration factor.

[0194] As an example, the controller can calculate the ratio and match the corresponding ratio interval. Then, it determines the value range corresponding to the ratio interval and determines the storage duration factor from the value range. For example, a ratio range of 0-20% corresponds to a storage duration factor range of 1.3-1.5, indicating that the food has just been placed in the refrigerator and the urgency for preservation is the highest; a ratio range of 20%-40% corresponds to a storage duration factor range of 1.1-1.3, indicating that the food is in the early stage of storage; a ratio range of 40%-60% corresponds to a storage duration factor range of 0.9-1.1, indicating that the food is in the middle stage of storage; a ratio range of 60%-80% corresponds to a storage duration factor range of 0.7-0.9, indicating that the food is in the late stage of storage and the quality of the food begins to decline; a ratio range of 80%-100% corresponds to a storage duration factor range of 0.5-0.7, indicating that the food is close to the recommended storage duration; and a ratio range >100% corresponds to a storage duration factor range of 0.3-0.5, indicating that the food has exceeded the recommended storage duration.

[0195] S503. The freshness factor and storage duration factor are weighted and summed to obtain the state correction coefficient.

[0196] In one embodiment, the weights corresponding to the freshness factor and the storage duration factor may be the same or different, and there is no limitation on this.

[0197] For example, the freshness factor can be greater than the storage duration factor. For instance, the weight of the freshness factor can be 0.6, and the weight of the storage duration factor can be 0.4.

[0198] In this embodiment, a freshness factor positively correlated with freshness is first determined, and a storage duration factor is determined based on the ratio of the stored time to the recommended storage time. Then, the freshness factor and the storage duration factor are weighted and summed to obtain a state correction coefficient, which simultaneously considers both the real-time appearance quality of the food and the consumption of storage time. Furthermore, by differentiating the weights of the two indicators, a quantitative comprehensive assessment of the food's storage state is achieved, enabling the state correction coefficient to objectively reflect the current degree of freshness degradation of the food.

[0199] In another embodiment, the controller can be based on, for example... Figure 6 The steps S601-S602 shown below determine the user preference correction coefficients, which are detailed below: S601. Based on historical behavioral data, calculate the user's consumption frequency factor, user preference status factor, and food waste factor for food ingredients.

[0200] Among them, the consumption frequency factor is positively correlated with the purchase frequency of ingredients, the user preference status factor is positively correlated with the degree of user preference for ingredients, and the ingredient waste factor is positively correlated with the frequency of ingredient waste.

[0201] In one embodiment, the consumption frequency factor represents the frequency with which a user purchases / uses the food ingredient. This factor is positively correlated with the consumption frequency of the food ingredient. The more frequently a user takes or purchases the food ingredient, the higher the value of the consumption frequency factor, and the greater its contribution to the weighted calculation of the user preference correction coefficient.

[0202] The aforementioned user preference status factor represents the user's subjective liking for the food ingredient and is positively correlated with the user's preference level. Marking the food ingredient as a favorite and manually retaining the original lighting strategy for the food ingredient will increase the value of this factor. The higher the user's preference, the larger the value of this factor.

[0203] The aforementioned food waste factor represents the frequency with which users store food but discard it without eating it, and is positively correlated with the frequency of food waste. The more times food is placed in the preservation chamber and discarded without being eaten, the higher the waste factor value. This factor is generally set with a negative weight in the weighted calculation to lower the final user preference correction coefficient.

[0204] Specifically, for the consumption frequency factor, the controller can read the food retrieval and replenishment records recorded by the device sensors (weight sensor, door switch, image recognition), count the number of times food is taken within a unit period, and normalize and map to obtain the consumption frequency factor; or, it can read the food entry and purchase records of the mobile APP, count the purchase frequency within a period, and map to obtain the factor.

[0205] Regarding user preference status factors, users can manually mark their preferences as "liked," "neutral," or "disliked" on the device panel or in the app, and the controller will match the corresponding range to obtain the preference status factor. Alternatively, the system can track whether users manually adjust the lighting scheduling strategy for the food item or retain the recommended strategy, thus improving the preference status factor through positive actions.

[0206] To address food waste factors, the controller can use image recognition and weight sensors to identify food items that have been removed in their entirety but have no subsequent consumption record, thus determining them as discarded. It can then count the number of discards per unit period, calculate the waste frequency, and map it to the food waste factor. Alternatively, users can manually mark food items as discarded in the app / panel, and the controller can accumulate discard records and count the waste frequency.

[0207] As an example, the controller can categorize user consumption frequency into four levels: High frequency, consumed at least 3 times per week, with a consumption frequency factor ranging from 1.15 to 1.20, indicating that the user frequently consumes this ingredient and has a high demand for freshness; Medium frequency, consumed 1 to 2 times per week, with a consumption frequency factor ranging from 1.05 to 1.15, representing normal consumption; Low frequency, consumed 1 to 3 times per month, with a consumption frequency factor ranging from 0.95 to 1.05, representing occasional consumption; and Very low frequency, consumed less than once per month, with a consumption frequency factor ranging from 0.80 to 0.95, representing very little consumption.

[0208] Additionally, the controller can categorize user ratings into three levels: when a user rates "like", the user preference rating factor can be 1.2; when no rating is given, the user preference rating factor can be 1; and when a user rates "neutral", the user preference rating factor can be 0.9.

[0209] Furthermore, the controller can categorize historical waste rates into four levels: High waste rate, with a discard rate greater than 30%, and a food waste factor value ranging from 1.15 to 1.20, indicating that the food is prone to waste and requires enhanced preservation; Medium waste rate, with a discard rate of 10% to 30%, and a food waste factor value ranging from 1.05 to 1.15, which is within the normal range; Low waste rate, with a discard rate less than 10%, and a food waste factor value ranging from 0.95 to 1.05, indicating that waste occurs relatively rarely; Almost no waste, with a food waste factor value ranging from 0.85 to 0.95, indicating that users have good eating habits.

[0210] S602. The consumption frequency factor, user preference status factor, and food waste factor are weighted and summed to obtain the user preference correction coefficient.

[0211] In one embodiment, the weights corresponding to the consumption frequency factor, user preference status factor, and food waste factor can be the same or different, and there is no limitation on this.

[0212] For example, the weight of the consumption frequency factor can be greater than the weight of the user preference state factor, and the weight of the user preference state factor can be greater than the weight of the storage duration factor. For instance, the weight of the consumption frequency factor can be 0.5, the weight of the user preference state factor can be 0.3, and the weight of the storage duration factor can be 0.2.

[0213] In this embodiment, consumption frequency, user preference status, and food waste factors are statistically analyzed based on users' historical behavior data. The user preference correction coefficient is then obtained by weighted summation of these three factors. This multi-dimensional approach quantifies user preferences from multiple dimensions, including actual consumption frequency, subjective liking, and food waste, objectively integrating users' actual consumption habits with subjective preference information, thus avoiding the bias caused by single-dimensional evaluation. Based on this, the obtained user preference correction coefficient more closely reflects users' actual usage habits.

[0214] To facilitate understanding of the calculation method for the preservation value of the above-mentioned ingredients, this embodiment selects extremely fresh winter imported blueberries that have just been placed in the preservation chamber and seasonal local apples that have been stored for 5 days as examples to fully demonstrate the calculation process of the preservation value of ingredients.

[0215] Example 1: Freshly added blueberries (winter, imported). Calculate the basic shelf-life value S{base}, which includes four scoring dimensions: economic value V1, perishability V2, nutrient density V3, and scarcity V4. The unit price of the ingredient is 120 yuan / kg, with a score of 95, weighted at 0.40 × 95 = 38; the recommended storage time is 5 days, with a perishability score of 88, weighted at 0.35 × 88 = 30.8; the nutrient density is extremely high, with a score of 95, weighted at 0.15 × 95 = 14.25; the scarcity is due to being imported out of season, with a score of 90, weighted at 0.10 × 90 = 9. Summing the four weighted results, we get the basic shelf-life value S{base} = 92.05.

[0216] The following correction coefficients were determined: Freshness factor f{fresh} = 1.4, corresponding to extremely fresh; Storage time factor f{time} = 1.4, corresponding to just placed in the container; State correction coefficient K{state} = 1.4; Consumption frequency factor f{freq} = 1.15, indicating high-frequency consumption; Preference labeling factor f{pref} = 1.2, indicating the user has marked it as liked; Waste record factor f{waste} = 1.15, indicating a high historical waste rate; The weighted calculation yielded a user preference correction coefficient K{user} = 1.16. Multiplying the basic freshness value, state correction coefficient, and user preference correction coefficient, the final score S = 92.05 × 1.40 × 1.16 = 149.5 was obtained. Since the maximum score is 100 points, the final blueberry score was set to the maximum value of 100.

[0217] Example 2: For apples (seasonal, locally grown) stored for 5 days, calculate the basic preservation value S{base}, which includes four scoring dimensions: economic value V1, perishability V2, nutrient density V3, and scarcity V4. The unit price of the ingredient is 12 yuan / kg, with a score of 45, weighted at 0.40 × 45 = 18.0; the recommended storage period is 30 days, with a score of 22, weighted at 0.35 × 22 = 7.7; the nutrient density is moderate, with a score of 50, weighted at 0.15 × 50 = 7.5; and the scarcity is year-round availability, with a score of 30, weighted at 0.10 × 30 = 3. Summing the four weighted results, we get the basic preservation value S{base} = 36.2.

[0218] The following correction coefficients were determined: Freshness factor f{fresh} = 0.9, indicating slight signs of spoilage; Storage time factor f{time} = 0.9, with 5 days of storage accounting for approximately 17% of the recommended 30-day storage period; State correction coefficient K{state} = 0.9; Consumption frequency factor f{freq} = 1, indicating medium-frequency consumption; Preference marking factor f{pref} = 1, indicating no user preference marking; Waste record factor f{waste} = 0.95, indicating minimal waste; and a weighted user preference correction coefficient K{user} = 0.99 was obtained. Multiplying the basic freshness value, state correction coefficient, and user preference correction coefficient, the final apple score S = 36.2 × 0.90 × 0.99 = 32.3 was obtained. This value did not exceed the upper limit and was directly used as the final score.

[0219] A comparison of the two sets of examples shows that imported blueberries have higher basic preservation value and various correction coefficients, and their final preservation score is significantly higher than that of apples. When arbitrating the conflicting light requirements of various ingredients, blueberries have a higher preservation priority.

[0220] In another embodiment, the controller can be based on, for example... Figure 7 The steps S701-S702 shown below determine the basic lighting strategy, which are detailed below: S701. Determine the first food group corresponding to the light-requiring type and the second food group corresponding to the light-avoiding type.

[0221] S702. Determine the basic lighting strategy based on the first highest preservation priority of the first ingredient in the first ingredient group and the second highest preservation priority of the second ingredient in the second ingredient group.

[0222] In one embodiment, the first food group is a collection of all food items in the preservation chamber that require light. All food items in this group require light to maintain quality and accumulate nutrients, such as blueberries, strawberries, spinach, and broccoli. When multiple light-requiring food items are present in the preservation chamber, they are all grouped into the first food group.

[0223] Correspondingly, the second food group mentioned above is a collection of all food items in the preservation chamber that require light protection. Food items in this group must be stored away from light, as light can induce them to sprout, turn green, and produce harmful substances, such as potatoes, onions, sweet potatoes, and garlic; all light-protected food items in the preservation chamber are collectively classified into the second food group.

[0224] The highest preservation priority mentioned above is the maximum preservation priority among all ingredients in the first ingredient group. When there are multiple light-required ingredients in the same group, only the preservation priority of the ingredient with the highest priority is taken as the representative priority of the entire light-required ingredient group for inter-group arbitration.

[0225] Correspondingly, the second highest preservation priority is the maximum value among all preservation priorities of all ingredients in the second ingredient group. When there are multiple light-protected ingredients in the same group, only the preservation priority of the light-protected ingredient with the highest priority is taken as the representative priority of the entire light-protected ingredient group for inter-group arbitration.

[0226] It should be noted that multiple lighting requirements can include not only light-requiring and light-shielding types, but also other lighting requirements, such as sterilization type and neutral type, without limitation.

[0227] As an example, the controller can determine the basic lighting strategy through a pre-configured mapping table. The mapping table pre-establishes a correspondence between two sets of priority relationships and the basic lighting strategy. After obtaining the first highest preservation priority and the second highest preservation priority, the controller can look up the mapping table to obtain the corresponding basic lighting strategy.

[0228] In this embodiment, by dividing the food into a first food group consisting of light-requiring ingredients and a second food group consisting of light-avoiding ingredients, the highest preservation priority corresponding to each of the two food groups is extracted, and the basic lighting strategy is determined based on the two highest preservation priorities. In the event of a conflict between light-requiring and light-avoiding ingredients in the chamber, the highest preservation priority of each group is used as the decision-making basis. Thus, the preservation requirements of both types of ingredients can be taken into account, avoiding the strategy deviation caused by the priority determination of a single ingredient. This achieves refined intelligent arbitration of lighting conflicts, ensures the preservation effect of high-value ingredients, and improves the overall preservation benefits when multiple types of ingredients are mixed.

[0229] In another embodiment, the controller can be based on, for example... Figure 8 The steps S801-S805 shown below determine the illumination scheduling strategy, which are detailed below: S801. If the first highest preservation priority is different from the second highest preservation priority, then determine the target light demand type corresponding to the highest preservation priority among the first highest preservation priority and the second highest preservation priority.

[0230] S802. Determine the preset scheduling strategy corresponding to the target lighting demand type as the basic lighting strategy.

[0231] Specifically, when the target lighting demand type is light-demanding, the preset scheduling strategy is the light-demanding scheduling strategy; when the target lighting demand type is light-avoiding, the preset scheduling strategy is the light-avoiding scheduling strategy.

[0232] In one embodiment, the target light requirement type is the light requirement type corresponding to the group of food with the higher priority value when the first highest preservation priority and the second highest preservation priority are not equal. When the first highest preservation priority (light-required group) > the second highest preservation priority (light-avoided group), the target light requirement type is light-required; when the second highest preservation priority (light-avoided group) > the first highest preservation priority (light-required group), the target light requirement type is light-avoided.

[0233] It is understandable that, for the two sets of strongly mutually exclusive light demand types mentioned above, the light demand type of the food with higher preservation priority can be selected as the scheduling target.

[0234] The aforementioned preset light-demand scheduling strategy is a preset basic scheduling strategy used when the target light demand type is light-demanding. The overall framework of this strategy is to continuously apply light suitable for light-demanding ingredients, including preset default light parameters such as basic wavelength, basic light intensity, and daily basic light duration, in order to maintain the quality of light-demanding ingredients and promote nutrient enrichment.

[0235] As an example, the preset optical scheduling strategy can be shown in Table 9 below: Table 9:

[0236] Referring to Table 9 above, the preset light scheduling strategy divides 24 hours into 3 time periods: first, a 15-minute pre-irradiation is performed, followed by 7.75 hours of coordinated irradiation with red-blue 3:1 composite light, and finally, the light source is turned off for 16 hours.

[0237] In another embodiment, when the hardware of the refrigeration equipment supports independent light control for the preservation chamber, for scenarios where the lighting requirements include both light-demanding and light-avoiding types, since the hardware has independent light sources for each zone, the basic lighting strategy can be a preset zone lighting strategy.

[0238] Specifically, the zoned lighting strategy utilizes zoned hardware to independently control the lighting in different areas at the same time. While meeting the light-requiring food preservation needs, the areas where light-avoiding food is located are completely dark, avoiding the risks of sprouting and turning green caused by light. Unlike single-cavity single-light source, it does not sacrifice the preservation needs of a certain type of food.

[0239] For example, a partitioned lighting strategy can be shown in Table 10 below: Table 10:

[0240] Referring to Table 10, the preservation chamber is divided into Zone A for placing light-requiring ingredients and Zone B for placing light-sensitive ingredients. During time T01, Zone A is pre-illuminated while Zone B is off. During time T02, Zone A is assisted by illumination while Zone B is off. During time T03, the light sources in both zones are turned off. By relying on independent light sources in each zone, preservation lighting is provided to light-requiring ingredients at the same time, while the zone containing light-sensitive ingredients remains dark throughout the process, thus simultaneously meeting the preservation needs of two mutually exclusive types of ingredients.

[0241] The aforementioned preset light-avoidance scheduling strategy is a basic preset scheduling strategy used when the target lighting requirement is light-avoidance. The overall framework of this strategy is to turn off multi-color light sources and prevent the preservation chamber from outputting light, thereby avoiding light exposure to light-avoidance food from the source and preventing it from sprouting, turning green, or producing harmful substances. Once this framework is determined, the light source remains off, and there is no need to turn on the light.

[0242] As an example, the preset light-avoidance scheduling strategy can be shown in Table 11 below: Table 11:

[0243] Referring to Table 11, the preset light-avoidance scheduling strategy only includes one time period, T01, covering the entire day from 00:00 to 24:00, lasting 24 hours. The light type is set to off, controlling the multi-color light source to not emit light throughout the entire process, avoiding light exposure on light-avoidance food, and preventing light-avoidance food from sprouting and producing harmful substances.

[0244] In this embodiment, when light-demanding and light-avoiding ingredients coexist and cause light conflicts, the highest preservation priority of each group of ingredients is compared, and the light demand type corresponding to the higher preservation priority is selected as the target light demand type. Furthermore, a corresponding preset light-demand scheduling strategy or preset light-avoidance scheduling strategy is matched as the basic lighting strategy. This allows for conflict arbitration based on the preservation value of the ingredients, prioritizing the preservation needs of high-preservation-priority ingredients and preventing the light demands of low-priority ingredients from crowding out the preservation resources of high-value ingredients. This achieves a reasonable allocation of light resources under mutually exclusive light demands, improving the overall preservation benefits in scenarios where multiple ingredients are stored together.

[0245] It should be noted that the above steps S801-S802 are for scenarios where the first highest preservation priority and the second highest preservation priority are different. When the preservation priorities are different, the controller can determine the basic illumination strategy according to steps S803-S805, as detailed below: S803. If the first highest preservation priority is the same as the second highest preservation priority, then obtain the number of the first type of the first ingredient included in the first ingredient group and the number of the second type of the second ingredient included in the second ingredient group.

[0246] S804. If the quantity of the first type is greater than or equal to the quantity of the second type, then the preset light demand scheduling strategy corresponding to the light demand type is determined as the basic lighting strategy.

[0247] S805. If the number of the first type is less than the number of the second type, then the preset light-avoidance scheduling strategy corresponding to the light-avoidance type shall be determined as the basic lighting strategy.

[0248] In one embodiment, the quantity of the first type refers to the number of food types included in the first food group (light-requiring food group). For example, if the first food group includes blueberries, spinach, and strawberries, a total of 3 types, then the quantity of the first type = 3.

[0249] Correspondingly, the quantity of the second category is the number of food items included in the second food group (light-proof food group). For example, if the second food group includes potatoes and onions, a total of 2 items, then the quantity of the second category = 2.

[0250] It should be noted that when priority cannot be used for arbitration, the number of food types in each of the two groups is compared, and the basic lighting strategy is selected according to the number of types.

[0251] For example, the first food group is blueberries and spinach (number of first types = 2); the second food group is potatoes (number of second types = 1). The number of first types (2) is greater than or equal to the number of second types (1), and the basic lighting strategy selects the preset light scheduling strategy.

[0252] In this embodiment, when the highest preservation priority of the light-requiring first food group and the light-avoiding second food group is equal, and light conflict arbitration cannot be completed based on preservation priority, the controller can obtain the number of food types corresponding to the two food groups for judgment. When the number of the first type is greater than or equal to the number of the second type, a preset light-requiring scheduling strategy is adopted; otherwise, a preset light-avoiding scheduling strategy is adopted. By using the coverage of food types as a secondary arbitration basis, the arbitration logic under mutually exclusive light requirements is improved, prioritizing the preservation needs of more types of food and enhancing the completeness and rationality of the light scheduling scheme in scenarios where multiple types of food are stored together.

[0253] In another embodiment, the controller can also pre-execute a user reminder strategy before generating the lighting scheduling strategy. For example, when the lighting requirement type includes both light-requiring and light-avoiding types, or when sterilization-type and light-requiring foods are mixed together, or when too many foods cause light blockage, the controller can trigger corresponding reminders, push prompts to the user, inform them of the preservation conflicts and potential risks caused by the mixed storage of foods, and provide optimization suggestions such as separating the foods and adjusting the food arrangement.

[0254] In this embodiment, the controller executes the reminder strategy before generating the lighting scheduling strategy, which can be used to identify the risks of food storage in the preservation chamber in advance. When it detects that the lighting requirement type includes both light-requiring and light-avoiding types, a high-value light-avoiding conflict reminder can be triggered, prompting the user that the two types of food have conflicting lighting requirements and suggesting that they be stored separately; when it detects that the lighting requirement type includes both sterilization-type and light-requiring types mixed together, a sterilization safety reminder is triggered, indicating that the sterilization light intensity is too high and suggesting that fruits and vegetables be moved out; when it detects that too much food will cause light blockage, a space shortage reminder is triggered, prompting the user to adjust the food placement to avoid blocking light and weakening the light preservation effect.

[0255] It should be noted that after the reminder operation is executed, a preset response time period can be waited for the user to process various ingredients in the preservation chamber. Finally, the controller can re-execute steps S101-S106 above. It should be noted that, at this time, during the re-execution of the above steps, the reminder strategy can be skipped, and the determination method of the basic lighting strategy described above can be directly executed.

[0256] In another embodiment, the controller can be based on, for example... Figure 9 The steps S901-S906 shown generate the illumination scheduling strategy. Details are as follows: S901. When the basic illumination strategy is not the preset light avoidance scheduling strategy, for any food ingredient, the wavelength corresponding to the food ingredient in multiple irradiation stages is determined based on the food ingredient type.

[0257] The irradiation phase includes a pre-irradiation phase and a synergistic irradiation phase. The pre-irradiation phase is used to establish light signaling pathways in food ingredients, while the synergistic irradiation phase is used to regulate the physiological metabolism of food ingredients based on light signaling pathways.

[0258] In one embodiment, the aforementioned pre-irradiation stage is a preliminary stage for light preservation, using an appropriate specific wavelength of light for an appropriate duration. The purpose is to activate photoreceptor proteins in the food, establish light signal pathways within the food, and enable the food to sense subsequent light signals.

[0259] The aforementioned synergistic irradiation phase is performed after the pre-irradiation phase. At this time, the food's light signaling pathway has been established, and continuous irradiation with light of an appropriate wavelength is used to regulate the food's physiological metabolism through the light signaling pathway. For example, it can inhibit respiration, delay chlorophyll degradation, and promote the accumulation of functional nutrients, thereby achieving the preservation and quality improvement of fruits and vegetables.

[0260] As an example, the controller can pre-store a food type-stage-wavelength mapping table, and directly look up the preset standard wavelength based on the food type and the current irradiation stage. For example, 450nm blue light can be used for pre-irradiation of light-demanding fruits and vegetables, while a red-blue composite wavelength can be used for synergistic irradiation.

[0261] S902. Multiply the light intensity compensation coefficients corresponding to the multiple irradiation stages by the light intensity reference value of the food in the corresponding irradiation stage to obtain the light intensity corresponding to the multiple irradiation stages.

[0262] In one embodiment, the aforementioned light intensity reference value is a pre-stored reference light intensity, which is the basic light intensity reference value that meets the preservation requirements of a certain type of food under the corresponding irradiation stage. It is the standard light intensity without considering various influencing factors.

[0263] For example, the reference light intensity for the pre-irradiation stage and the reference light intensity for the synergistic irradiation stage of light-demanding fruits and vegetables can be pre-calibrated based on physiological experiments of the ingredients.

[0264] The aforementioned light intensity compensation coefficient is used to correct the reference light intensity value. Its value can be greater than 1, equal to 1, or less than 1. It is used to comprehensively compensate for various influencing factors. For example, factors such as food storage time, food preservation priority, degree of obstruction inside the cavity, ambient temperature, and light source attenuation can be used to amplify or reduce the reference light intensity.

[0265] It should be noted that the reference light intensity values ​​for different irradiation stages (pre-irradiation stage and coordinated irradiation stage) can be the same or different; the light intensity compensation coefficients corresponding to different irradiation stages can also be the same or different, and this scheme does not impose any hard restrictions on this.

[0266] For example, the light intensity reference value in the pre-irradiation stage can be 30 μmol and the light intensity compensation coefficient can be 1.45, while the light intensity reference value in the synergistic irradiation stage can be 150 and the light intensity compensation coefficient can be 1.45.

[0267] S903. Multiply the time reference values ​​corresponding to the multiple irradiation stages by the preset time compensation coefficient to obtain the irradiation time corresponding to the multiple irradiation stages.

[0268] In one embodiment, the aforementioned time reference value is a pre-calibrated and stored reference time, which serves as the basic reference time for meeting the preservation target in the corresponding irradiation stage (pre-irradiation stage, synergistic irradiation stage).

[0269] For example, the baseline value for the pre-irradiation stage of light-requiring fruits and vegetables can be 15 minutes, and the baseline value for the synergistic irradiation stage can be 8 hours.

[0270] The aforementioned duration compensation coefficient is a dimensionless coefficient that corrects the baseline duration value. Its value can be greater than 1, equal to 1, or less than 1. It can be dynamically determined by comprehensively considering factors such as food storage time, food preservation priority, degree of light shading inside the cavity, ambient temperature and humidity, and remaining food preservation period, and is used to amplify or shorten the baseline duration.

[0271] The above illumination duration is the final actual illumination duration performed by the light source after compensation calculation. It is used by the controller to drive the multi-color light source and control the duration of the light source being turned on in each illumination stage.

[0272] For each illumination stage, such as the pre-illumination stage and the coordinated illumination stage, the duration reference value corresponding to each illumination stage is multiplied by the preset duration compensation coefficient corresponding to that stage to calculate the final actual illumination duration of each illumination stage. The controller controls the on-time duration of the multicolor light source in each stage based on the calculation result. The duration reference value and duration compensation coefficient of different illumination stages can be configured independently, and can be the same or different, without mandatory restrictions.

[0273] S904. Based on the type of food, determine the ratio of red to blue light irradiation time for each food during the synergistic irradiation phase.

[0274] The red-blue light irradiation duration ratio is the ratio of the red light irradiation duration to the blue light irradiation duration within one irradiation cycle.

[0275] In one embodiment, the red-blue light irradiation duration ratio is the ratio of the red light irradiation duration to the blue light irradiation duration within one irradiation cycle, and is used to perform time-division control of the red and blue light sources during the coordinated irradiation phase.

[0276] For example, the red-blue light irradiation time ratio for blueberries can be 3:1, for tomatoes it can be 5:1, and for grapes it can be 1:1.

[0277] In one embodiment, the controller can pre-store a mapping table of food type and red-blue light irradiation time ratio, and directly retrieve the red-blue light irradiation time ratio after identifying the food type.

[0278] S905. For any type of lighting parameter, generate target lighting parameters based on the lighting parameters corresponding to multiple ingredients of the same type.

[0279] S906. Merge multiple types of target illumination parameters to generate illumination scheduling strategies.

[0280] In one embodiment, any of the above-mentioned illumination parameters are the same type of parameters as wavelength, light intensity, illumination duration, and red-blue light illumination duration ratio in the above steps, and will not be described further.

[0281] As an example, the controller can take the light parameters of each type of food as a basis, and use the priority coefficient corresponding to the preservation priority of each food as a weight to make a weighted average to obtain the target light parameters.

[0282] For example, the preservation chamber contains blueberries (red-blue light duration ratio 3:1, weight 0.7) and grapes (red-blue light duration ratio 1:1, weight 0.3), and the target red-blue light duration ratio is obtained by weighted fusion.

[0283] The methods for generating target lighting parameters for different types of lighting parameters can be the same or different, and there is no limitation on this.

[0284] In one embodiment, after obtaining the above-mentioned multiple types of target illumination parameters, each type of target illumination parameter can be determined as the illumination parameter in the above-mentioned illumination scheduling strategy.

[0285] In this embodiment, under a scenario where the basic illumination strategy is not a preset light-avoidance scheduling strategy, the wavelengths of the pre-illumination stage and the synergistic illumination stage are determined in stages. The target light intensity and illumination duration for each stage are calculated by combining the light intensity reference value and light intensity compensation coefficient, and the duration reference value and duration compensation coefficient. Furthermore, the ratio of red to blue light illumination duration in the synergistic illumination stage is determined based on the type of food. Then, the illumination parameters for multiple foods of the same type are fused to obtain the target illumination parameters. Finally, various target illumination parameters are integrated to generate an illumination scheduling strategy. This strategy can distinguish between the two stages of pre-illumination pathway awakening and synergistic illumination metabolic regulation, achieving refined, segmented illumination control and dynamically adapting to the light response characteristics of different foods. Moreover, in scenarios where multiple foods coexist, compatible illumination parameters are fused, enabling precise illumination preservation control when multiple foods are stored together, thus improving the preservation effect of the refrigeration equipment.

[0286] In one embodiment, during the pre-irradiation stage, the light intensity compensation coefficient includes a packaging compensation coefficient and a priority compensation coefficient; during the coordinated irradiation stage, the light intensity compensation coefficient includes a packaging compensation coefficient. The packaging compensation coefficient is used to compensate for the attenuation loss of light due to the food packaging. The priority compensation coefficient is positively correlated with the preservation priority. The duration compensation coefficient includes a storage compensation coefficient and a priority compensation coefficient. The duration baseline value during the pre-irradiation stage is less than the duration baseline value during the coordinated irradiation stage. The storage compensation coefficient is negatively correlated with the storage duration factor of the food, which is the ratio of the food's existing storage time to the recommended storage time corresponding to the food.

[0287] The aforementioned packaging compensation coefficient is used to compensate for the light attenuation loss caused by the absorption and scattering of light by the outer packaging of the food. The worse the light transmittance of the packaging, the larger the value of this coefficient, which is used to increase the output light intensity of the light source and offset the light loss caused by the packaging; the coefficient approaches 1 when the light transmittance of the packaging is good.

[0288] For example, the packaging compensation coefficient for PET boxes is 1.45.

[0289] The aforementioned priority compensation coefficient is positively correlated with the food preservation priority. The higher the preservation priority, the larger the priority compensation coefficient, which has a positive effect on light intensity and irradiation duration; the lower the priority, the smaller the coefficient.

[0290] For example, the priority compensation coefficient corresponding to high preservation priority can be 1.0.

[0291] The storage compensation coefficient mentioned above is negatively correlated with the storage duration factor; the storage duration factor = the storage time of the food ÷ the recommended storage time of the food. The longer the food is stored, the larger the storage duration factor and the smaller the storage compensation coefficient, thus reducing light parameters and avoiding strong light damage to the food in the later stages of aging.

[0292] For example, based on the storage duration factor, food ingredients can be divided into four storage stages: the stress activation stage corresponds to a storage duration factor of 0-20%, with a pre-irradiation coefficient ranging from 1.2 to 1.5 and a synergistic irradiation coefficient ranging from 1.1 to 1.3, used for high-intensity activation of newly added ingredients; the metabolic equilibrium stage corresponds to a storage duration factor of 20%-50%, with both the pre-irradiation coefficient and the synergistic irradiation coefficient ranging from 0.9 to 1.1, maintaining a baseline light level; the maturation and stabilization stage corresponds to a storage duration factor of 50%-80%, with both the pre-irradiation coefficient and the synergistic irradiation coefficient ranging from 0.6 to 0.9, gradually reducing the light dose; and the aging delay stage corresponds to a storage duration factor greater than 80%, with both the pre-irradiation coefficient and the synergistic irradiation coefficient ranging from 0.3 to 0.6, maintained using the lowest intensity light. As the storage duration factor increases, the storage compensation coefficient gradually decreases.

[0293] The above-mentioned baseline duration values ​​are shorter for the pre-irradiation phase than for the synergistic irradiation phase. For example, the baseline duration for the pre-irradiation phase is 15 minutes, and the baseline duration for the synergistic irradiation phase is 8 hours. The pre-irradiation phase is only used to activate the light signaling pathway and requires a short baseline time; the synergistic irradiation phase is used to continuously regulate metabolism and has a longer baseline duration.

[0294] As an example, the formula for calculating light intensity can be: Light intensity baseline value × Packaging compensation coefficient × Priority compensation coefficient. For instance, in the pre-irradiation stage, the light intensity baseline value is 30 μmol, the PET box packaging compensation coefficient is 1.45, and the high-preservation priority compensation coefficient is 1. Therefore, the final light intensity is: 30 × 1.45 × 1.0 = 43.5 μmol. In the synergistic irradiation stage, the light intensity baseline value is 150 μmol, so the final light intensity is: 150 × 1.45 = 217.5 μmol.

[0295] The duration calculation formula is: duration baseline value × priority compensation coefficient × storage compensation coefficient. For example, the baseline value for pre-irradiation duration is 15 minutes, the priority compensation coefficient is 1.0, and during the stress activation period, the storage compensation coefficient is 1.2; the final duration of the pre-irradiation phase is: 15 minutes × 1.0 × 1.2 = 18 minutes. The baseline value for co-irradiation duration can be 8 hours, and the final duration of the co-irradiation phase is: 8 hours × 1.0 × 1.2 = 9.6 hours.

[0296] In this embodiment, differentiated light intensity compensation coefficients are set for the pre-irradiation stage and the coordinated irradiation stage. A packaging compensation coefficient is used to compensate for light attenuation loss caused by food packaging. A priority compensation coefficient, positively correlated with preservation priority, is used to achieve priority adaptation of light intensity and duration. A storage compensation coefficient, negatively correlated with storage duration, is introduced. The irradiation duration is dynamically adjusted based on the existing storage duration. Simultaneously, the baseline value for the pre-irradiation stage duration is set to be less than the baseline value for the coordinated irradiation stage duration. Therefore, it is possible to match the different physiological targets of food photoresponse in the two stages, achieving multi-factor coupled staged light parameter correction and improving the accuracy of light preservation control in scenarios involving mixed storage of packaged food.

[0297] In another embodiment, for the above-mentioned multiple illumination parameters, the controller can, according to, such as Figure 10 The S1001-S1006 diagram shows the target illumination parameters generated. Details are as follows: S1001. When the illumination parameters are the wavelengths of the pre-irradiation stage, if there is an overlap in the irradiation wavelength ranges of various ingredients, the wavelengths located within the overlap shall be determined as the target wavelengths.

[0298] S1002. If the wavelength ranges of multiple ingredients do not overlap, then the target wavelength is determined separately from the irradiation wavelength ranges of the multiple ingredients.

[0299] In one embodiment, the wavelength range refers to a continuous wavelength interval in which a certain type of food can effectively activate its internal light signal pathway and achieve a pre-irradiation awakening effect during the pre-irradiation stage. It is the upper and lower limits of the acceptable effective wavelength of the food.

[0300] For example, the wavelength range for blueberries can be 400~420nm, and the wavelength range for grapes can be 280~350nm.

[0301] The intersection occurs when the pre-irradiation wavelength ranges of various ingredients overlap, and this overlapping wavelength range is the intersection of the wavelength ranges.

[0302] For example, the wavelength range of ingredient A can be 420~460nm, and the wavelength range of ingredient B can be 440~480nm. The overlapping range of the two is 440~460nm, which means there is an intersection.

[0303] It should be noted that the intersection itself is a continuous wavelength range. The target wavelength can be selected within this intersection range. The options include: taking the center wavelength of the intersection range as the single-point target wavelength; or selecting the optimal wavelength corresponding to the food with the highest preservation priority within the intersection range.

[0304] Furthermore, when the wavelength ranges of various ingredients do not overlap and it is impossible to select a unified common wavelength, the wavelength range corresponding to each ingredient can be used as the target wavelength, and the irradiation can be carried out in a time-sharing and alternating manner.

[0305] For example, when there is no overlap, time-sharing scheduling is adopted to switch different target wavelengths for segmented irradiation in turn; first, the target wavelength corresponding to the first type of food is used for irradiation for a preset duration, and then the target wavelength corresponding to the second type of food is switched to irradiate for a preset duration. Each target wavelength is executed in turn within a pre-irradiation cycle to meet the pre-irradiation wake-up requirements of each type of food.

[0306] In the coordinated irradiation phase, the target wavelength can be set to a pre-defined fixed value and may not participate in the above processing.

[0307] S1003. When the illumination parameter is the light intensity of the pre-irradiation stage, the maximum value of the light intensity corresponding to various ingredients is determined as the target light intensity.

[0308] In one embodiment, when the illumination parameter to be processed is the light intensity of the pre-illumination stage, the largest light intensity value can be selected from multiple light intensities as the final target light intensity of this stage.

[0309] It should be noted that during the pre-irradiation stage, the goal is to awaken the light signal pathways of all ingredients. Taking the maximum value ensures that the ingredients with the highest light requirements receive sufficient light intensity; other ingredients can complete the pathway awakening normally under this light intensity and will not fail due to insufficient light intensity.

[0310] S1004. When the illumination parameters are the illumination duration of the pre-irradiation stage and the synergistic irradiation stage, the maximum value among the illumination durations corresponding to various ingredients shall be determined as the target illumination duration.

[0311] In one embodiment, the maximum value among the irradiation duration values ​​corresponding to various ingredients is selected as the target irradiation duration for this stage. This ensures that the ingredient with the longest light requirement can receive sufficient light exposure time during this stage. Under this time condition, other ingredients can also complete the corresponding physiological regulation and will not experience the problem of insufficient light exposure leading to preservation failure.

[0312] For example, the preservation chamber can store both blueberries and grapes at the same time: Pre-irradiation stage: The pre-irradiation time for blueberries was calculated to be 12 minutes, and the pre-irradiation time for grapes was calculated to be 10 minutes; the maximum value of 12 minutes was taken as the target irradiation time for the pre-irradiation stage, and the pre-irradiation light source was continuously turned on for 12 minutes.

[0313] Co-irradiation phase: The calculated co-irradiation duration for blueberries is 8 hours, and for grapes it is 6 hours; the maximum value of 8 hours is taken as the target irradiation duration for the co-irradiation phase, and the co-irradiation light source is continuously turned on for 8 hours.

[0314] S1005. When the light parameters are the ratio of red to blue light irradiation time in the synergistic irradiation stage, the ratio of red to blue light irradiation time corresponding to the food with the highest preservation priority is determined as the target red to blue light irradiation time ratio.

[0315] In one embodiment, the goal of the coordinated irradiation phase is to prioritize the enrichment of nutrients and the inhibition of aging in high-preservation-value ingredients. The ratio of red to blue light irradiation duration, which has the highest preservation priority, is used as a unified scheduling standard to prioritize the metabolic regulation needs of high-value ingredients. Other low-priority ingredients can still receive basic preservation light under this ratio.

[0316] For example, the preservation chamber simultaneously stores blueberries (preservation priority P1) and grapes (preservation priority P2). Since blueberries have a higher preservation priority, a red-to-blue light irradiation time ratio of 3:1 is selected as the target ratio. That is, within one cycle of the synergistic irradiation phase, the ratio of red light irradiation time to blue light irradiation time is 3:1, and the light source outputs light according to this time ratio, prioritizing the preservation effect of the blueberries.

[0317] S1006. The target wavelength, target light intensity, target illumination duration, and target red-blue light illumination duration ratio are determined as target illumination parameters.

[0318] In one embodiment, after determining the illumination parameters corresponding to each type, the illumination parameters can be determined as the target illumination parameters.

[0319] In this embodiment, a differentiated fusion strategy is adopted for different types of illumination parameters. During the pre-illumination stage, wavelengths within the intersection are selected when there is overlap; otherwise, target wavelengths are determined separately. The pre-illumination intensity and the illumination duration of both stages are taken as the maximum values ​​of the parameters corresponding to multiple food items. During the coordinated illumination stage, the ratio of red to blue light illumination duration is selected based on the ratio corresponding to the food item with the highest preservation priority. By integrating various target illumination parameters, wavelength compatibility constraints and food preservation priorities can be balanced in scenarios where multiple food items are stored together. This ensures that each food item receives sufficient light dose, prioritizing the protection of high-preservation-value food items, achieving phased and parameter-type illumination scheduling, and improving the effect of simultaneous illumination preservation of multiple food items within the refrigeration equipment.

[0320] It's important to note that in refrigeration equipment usage scenarios, the food inside the preservation chamber may change due to removal, addition, or replacement. If the original lighting scheduling strategy is used after these changes, the old lighting parameters will not be compatible with the updated food combination, easily leading to lighting demand conflicts and mismatched lighting parameters. This, in turn, reduces the food preservation effect. Most related technologies generate a lighting scheduling strategy only once after initial food identification, failing to update the strategy in response to changes in food, making it difficult to adapt to the actual needs of households with dynamically increasing or decreasing food supplies.

[0321] In another embodiment, when controlling the multicolor light source in response to the adjusted illumination parameters, if changes are detected in various ingredients in the preservation chamber, the target step and the steps following the target step are re-executed; the target step includes identifying the illumination requirement type corresponding to each of the various ingredients in the preservation chamber.

[0322] It should be noted that changes in ingredients refer to changes in the combination of ingredients within the preservation chamber. Scenarios include situations where new ingredients are placed into the preservation chamber while the original ingredients are undergoing a lighting program; or where the original ingredients are removed, some ingredients are replaced, and multiple ingredients within the preservation chamber are altered.

[0323] When a change in the ingredients is detected, a global lighting plan rearrangement can be triggered, re-executing the target step and all subsequent processes. For example, the lighting requirements of each ingredient in the preservation chamber can be identified, and then the preservation value of the ingredients can be assessed, lighting conflict arbitration can be carried out, lighting parameters can be calculated, and target lighting parameters can be fused in sequence to regenerate a lighting scheduling strategy that is adapted to the new combination of ingredients.

[0324] It should be noted that historical lighting periods that have already been completed will not be changed; only lighting periods that have not yet been executed after the current time point will be re-planned. Compensation for already invested resources: for ingredients that have already met most of their lighting requirements for the day, their remaining lighting requirements will be prioritized during the rescheduling. Minimize disturbance: retain the original lighting plan as much as possible and adjust it only when necessary to reduce changes to the original lighting scheme for ingredients.

[0325] For example, at 08:00, spinach is placed in the preservation chamber. Spinach is a light-requiring food, with a preservation priority of P2. The controller controls a multi-color light source to perform 10 minutes of pre-irradiation, followed by 8 hours of synergistic irradiation. The original plan was to complete all irradiation by 16:00. At 14:00, chicken is added to the preservation chamber. Chicken is a sterilization-requiring food, with a preservation priority of P2. The change in food combination triggers an adjustment to the target irradiation parameters. At this point, the spinach has completed 6 hours of synergistic irradiation, leaving 2 hours of irradiation remaining until the target total of 8 hours. After the adjustment, from 14:00 to 14:30, the spinach's irradiation is paused, and high-dose short-wavelength blue light sterilization irradiation required by the chicken is inserted for 25 minutes. From 14:30 to 16:30, the synergistic irradiation of the spinach is restored, and the light intensity is increased to compensate for the loss of light dose caused by the interruption, completing the remaining 2 hours of irradiation for the spinach. After 16:30 until the next day, the light source in the preservation chamber is turned off.

[0326] In another embodiment, if a new food item with a light-requiring light requirement is detected in the preservation chamber, after generating a light scheduling strategy, the light parameters are compensated using a preset acceleration compensation coefficient within a preset time period to obtain the compensated light parameters; the operation of the multicolor light source is controlled based on the compensated light parameters.

[0327] In one embodiment, the aforementioned preset time period can be set according to actual conditions and is not limited thereto. For example, it can be the first 24 hours after new light-requiring ingredients are added. This period is the effective period of accelerated compensation for the newly added ingredients, and accelerated compensation of light parameters is only enabled within this time window; after 24 hours, the accelerated compensation coefficient is no longer used, and standard light parameters are switched to perform preservation.

[0328] The aforementioned acceleration compensation coefficient is used to amplify and adjust illumination parameters such as pre-irradiation duration, pre-irradiation light intensity, and synergistic irradiation duration, thereby increasing the light dose and accelerating activation.

[0329] For example, the acceleration compensation coefficient for pre-irradiation duration and pre-irradiation light intensity can be 0.5, which is 50% higher than the standard value; the acceleration compensation coefficient for co-irradiation duration can be 20% to 50%, which is any value between 20% and 50% higher than the standard co-irradiation duration.

[0330] As an example, a new batch of light-demanding spinach is placed in the soil, triggering accelerated compensation within a preset timeframe of 24 hours. Standard parameters: pre-irradiation duration 10 min, pre-irradiation light intensity 40 μmol, and co-irradiation duration 8 h. After applying the accelerated compensation coefficient, the pre-irradiation duration is: 10 min. (1+0.5)=15min, pre-irradiation light intensity: 40 (1+0.5)=60 μmol; Co-irradiation duration: Select a 30% compensation ratio, 8 (1+0.3)=10.4h. At this point, the compensated light parameters are: pre-irradiation duration 15min, pre-irradiation light intensity 60μmol, and synergistic irradiation duration 10.4h. The controller controls the operation of the multi-color light source based on these compensated light parameters. During the first 24 hours after the spinach is placed in the chamber, this accelerated light program is executed to quickly activate the physiological metabolism of the food, enabling the newly placed spinach to quickly reach a preservation level comparable to that of the original food in the chamber. After 24 hours, the accelerated compensation is canceled, and the original light parameters are switched back.

[0331] In this embodiment, when a new light-requiring ingredient is detected in the preservation chamber, the illumination parameters are compensated using an acceleration compensation coefficient within a preset time period. Based on the compensated illumination parameters, a multi-color light source is driven to operate, increasing the light dose to the newly added light-requiring ingredient and rapidly activating its photoresponsive physiological processes. This allows the new ingredient to reach a preservation level comparable to the existing ingredients in the chamber within a short time, eliminating differences in preservation progress caused by the order in which ingredients are added.

[0332] In another embodiment, after generating the lighting parameters in the lighting scheduling strategy and controlling the operation of the multi-color light source, the controller can automatically perform multi-dimensional plan verification. For example, the verification dimensions are as follows: Light coverage for high freshness priority (P1) food: The verification rule is that P1 priority food requires light-type food to have a daily light exposure time of no less than 80% of the baseline value; if the verification fails, a warning will be marked and the time period allocation will be adjusted.

[0333] Light-avoidance food protection time: The verification rule is that light-avoidance food with P1 / P2 priority must be protected from light for no less than 16 hours per day; if the verification fails, a warning will be marked and a user reminder will be triggered.

[0334] Sterilization frequency of sterilized food ingredients: The verification rule is that sterilized food ingredients must be sterilized with light at least once every 24 hours; if the verification fails, a warning will be marked and a sterilization light period will be inserted.

[0335] No overlapping time periods: The verification rule is that the illumination time periods of the same LED module do not overlap; if the verification fails, it is marked as a failure and the illumination time period is reassigned.

[0336] Light intensity safety limit: The verification rule is that the output light intensity shall not exceed the food's tolerance limit of 300μmol; if the verification fails, it shall be marked as a failure and the light intensity value shall be reduced.

[0337] Total illumination duration limit: The verification rule is that the total illumination duration on a single day shall not exceed 18 hours; a warning will be marked when the verification fails, and non-critical illumination periods will be compressed.

[0338] After verification, the data is processed in three categories based on the verification status: Verification status is passed: All verification items meet the requirements, and the generated lighting plan is executed directly.

[0339] The verification status is a warning: There are non-critical items that do not meet the verification rules. Continue to execute the lighting plan, record the warning log synchronously, and continuously optimize the lighting scheme.

[0340] Verification status is failed: There is a critical item that does not meet the verification rules. The controller will automatically adjust the parameters and re-verify, with a maximum of 3 retries. If the verification still fails after retries, a user reminder will be triggered.

[0341] In another embodiment, the refrigeration device may include one or more memories storing programs that can be run by a controller to generate instructions, causing the controller to execute the control method for the refrigeration device described in the above method embodiments according to the instructions.

[0342] This application also provides a computer program product that, when executed by a controller, implements the control method of a refrigeration device according to any method embodiment of this application.

[0343] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a computer, implements the control method of any of the method embodiments of this application.

[0344] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A refrigeration device, characterized in that, include: The preservation chamber is configured for storing food ingredients; A multi-color light source, located in the preservation chamber, is configured to emit light of multiple colors; The controller is configured as follows: Identify the light requirements of various ingredients in the preservation chamber; Based on the characteristics of the ingredients, the preservation value of various ingredients is evaluated; the preservation value of the ingredients is positively correlated with the preservation priority of the ingredients. When multiple lighting requirements exist that conflict with each other, including both light-demanding and light-avoiding requirements, a basic lighting strategy is determined based on the highest preservation priority between the food preservation value of the food corresponding to the light-demanding type and the food preservation value of the food corresponding to the light-avoiding type. When multiple lighting demand types have other conflicting demands that do not simultaneously include the light-demanding type and the light-avoiding type, the preset time-series isolation scheduling strategy is determined as the basic lighting strategy; The time-series isolation scheduling strategy is a strategy that provides corresponding light to ingredients with different light requirements at different times. Based on the various ingredients in the preservation chamber, the lighting parameters in the basic lighting strategy are adjusted to generate a lighting scheduling strategy. The operation of the multicolor light source is controlled based on the lighting parameters in the lighting scheduling strategy.

2. The refrigeration equipment according to claim 1, characterized in that, The controller, based on the food characteristics of the food ingredients, evaluates the food preservation value of various food ingredients and is configured to: For any of the ingredients, calculate a feature score for the characteristics of the ingredient; If the number of the food ingredient features is 1, then the feature score is determined as the basic preservation value; If there are multiple food characteristics, the weighted sum of the scores of the multiple characteristics is used to determine the basic preservation value; The basic preservation value is adjusted to obtain the preservation value of the food ingredient.

3. The refrigeration equipment according to claim 2, characterized in that, The controller calculates feature scores for the food ingredients and is configured as follows: When the ingredient characteristic is the unit price, the economic value score of the ingredient is calculated based on the unit price, and the product of the economic value score and a preset economic coefficient is determined as the characteristic score; the economic value score is used to quantify the market economic value of the ingredient. When the food ingredient is characterized by a recommended storage period, a perishability score is calculated based on the recommended storage period, and the product of the perishability score and a preset perishability coefficient is determined as the feature score. The perishability score is used to quantify the urgency of preserving the food. When the food ingredient is characterized as a nutritional grade, a nutrient density score corresponding to the nutritional grade is obtained, and the product of the nutrient density score and a preset nutrient coefficient is determined as the feature score; the nutrient density score is used to quantify the comprehensive nutrient richness of the food ingredient. When the characteristics of the ingredient are its ripening season and geographical distribution, the seasonality coefficient and regionality coefficient corresponding to the ingredient are determined based on the ripening season and geographical distribution. The scarcity score of the ingredient is calculated based on the seasonality coefficient and the regionality coefficient, and the product of the scarcity score and the preset scarcity coefficient is determined as the feature score. The scarcity score is used to quantify the degree of constraint of geographical conditions and seasonal factors on the availability of the ingredient supply.

4. The refrigeration equipment according to claim 3, characterized in that, When the food ingredient's characteristic is its unit price, the controller calculates the economic value score of the food ingredient based on that unit price, and is configured as follows: The unit price of the ingredients is logarithmically transformed and linearly mapped to a preset scoring range to obtain the economic value score.

5. The refrigeration equipment according to claim 3, characterized in that, The controller calculates a perishability score for the food based on the recommended storage duration, and is configured as follows: The recommended storage time is input into a preset exponential decay function to obtain the perishability score.

6. The refrigeration equipment according to claim 3, characterized in that, The controller calculates a scarcity score for the ingredient based on the seasonality coefficient and the regionality coefficient, and is configured as follows: Calculate the first product of the seasonality coefficient and the preset seasonal score, and the second product of the regionality coefficient and the preset regional score; The first product, the second product, and the basic scarcity score are summed to obtain the scarcity score.

7. The refrigeration equipment according to claim 3, characterized in that, The preset economic coefficient is greater than the preset perishability coefficient, the preset perishability coefficient is greater than the preset nutritional coefficient, and the preset nutritional coefficient is greater than the preset scarcity coefficient.

8. The refrigeration equipment according to claim 2, characterized in that, The controller modifies the basic preservation value to obtain the food preservation value, which is configured as follows: The freshness and storage time of the ingredients, as well as the user's historical behavior data regarding the ingredients, are obtained. Calculate the state correction coefficient of the food ingredient based on the freshness and the storage time; Generate a user preference correction coefficient for the food ingredient based on the historical behavior data; The food preservation value is obtained by multiplying the state correction coefficient, the user preference correction coefficient, and the basic preservation value.

9. The refrigeration equipment according to claim 8, characterized in that, The controller calculates a state correction coefficient for the food ingredient based on the freshness and the storage time, and is configured as follows: Determine a freshness factor corresponding to the freshness; the freshness factor is positively correlated with the freshness. The storage duration factor is determined based on the ratio of the existing storage duration to the recommended storage duration corresponding to the food ingredient. The state correction coefficient is obtained by weighted summation of the freshness factor and the storage duration factor.

10. The refrigeration equipment according to claim 8, characterized in that, The controller generates a user preference correction coefficient for the food ingredients based on the historical behavior data, and is configured as follows: Based on the historical behavior data, the consumption frequency factor, user preference status factor, and food waste factor of the user for the food are statistically analyzed. The consumption frequency factor is positively correlated with the purchase frequency of the ingredients; the user preference state factor is positively correlated with the user's preference for the ingredients; and the ingredient waste factor is positively correlated with the frequency of ingredient waste. The user preference correction coefficient is obtained by weighting and summing the consumption frequency factor, the user preference status factor, and the food waste factor.

11. The refrigeration equipment according to claim 1, characterized in that, When multiple lighting requirements exist that conflict, including both light-demanding and light-avoiding requirements, the controller determines a basic lighting strategy based on the highest preservation priority between the food preservation value of the food corresponding to the light-demanding type and the food preservation value of the food corresponding to the light-avoiding type. This strategy is configured as follows: Determine the first food group corresponding to the light-requiring type and the second food group corresponding to the light-avoiding type; The basic lighting strategy is determined based on the highest preservation priority of the first ingredient in the first ingredient group and the highest preservation priority of the second ingredient in the second ingredient group.

12. The refrigeration equipment according to claim 11, characterized in that, The controller determines a basic lighting strategy based on the first highest preservation priority of the first ingredient in the first ingredient group and the second highest preservation priority of the second ingredient in the second ingredient group, and is configured as follows: If the first highest preservation priority is different from the second highest preservation priority, then the target light demand type corresponding to the highest preservation priority among the first highest preservation priority and the second highest preservation priority is determined. The preset scheduling strategy corresponding to the target lighting demand type is determined as the basic lighting strategy; When the target illumination demand type is light-demanding, the preset scheduling strategy is a light-demanding scheduling strategy; when the target illumination demand type is light-avoiding, the preset scheduling strategy is a light-avoiding scheduling strategy.

13. The refrigeration equipment according to claim 11, characterized in that, The controller determines a basic lighting strategy based on the first highest preservation priority of the first ingredient in the first ingredient group and the second highest preservation priority of the second ingredient in the second ingredient group, and is configured as follows: If the first highest preservation priority is the same as the second highest preservation priority, then obtain the number of the first type of the first food included in the first food group and the number of the second type of the second food included in the second food group. If the number of the first type is greater than or equal to the number of the second type, then the preset light demand scheduling strategy corresponding to the light demand type is determined as the basic illumination strategy; If the number of the first type is less than the number of the second type, then the preset light-avoidance scheduling strategy corresponding to the light-avoidance type is determined as the basic illumination strategy.

14. The refrigeration equipment according to claim 1, characterized in that, The controller adjusts the lighting parameters in the basic lighting strategy based on the various ingredients in the preservation chamber, and generates a lighting scheduling strategy, which is configured as follows: When the basic illumination strategy is not a preset light avoidance scheduling strategy, for any one of the ingredients, the wavelengths corresponding to the ingredients in multiple irradiation stages are determined based on the type of ingredients. The irradiation stages include a pre-irradiation stage and a synergistic irradiation stage. The pre-irradiation stage is used to establish the light signal pathway in the ingredients, and the synergistic irradiation stage is used to regulate the physiological metabolism of the ingredients based on the light signal pathway. Multiply the light intensity compensation coefficients corresponding to the multiple irradiation stages by the corresponding light intensity reference values ​​to obtain the light intensity corresponding to the multiple irradiation stages. The duration reference value corresponding to each of the multiple irradiation stages is multiplied by a preset duration compensation coefficient to obtain the irradiation duration corresponding to the multiple irradiation stages. Based on the type of food ingredient, the ratio of red to blue light irradiation time corresponding to the food ingredient in the synergistic irradiation phase is determined; the ratio of red light irradiation time to blue light irradiation time within one irradiation cycle is the ratio of red light irradiation time to blue light irradiation time. For any type of lighting parameter, generate target lighting parameters based on the lighting parameters corresponding to multiple ingredients of the same type; The lighting scheduling strategy is generated by merging multiple types of target lighting parameters.

15. The refrigeration equipment according to claim 14, characterized in that, During the pre-irradiation stage, the light intensity compensation coefficient includes a packaging compensation coefficient and a priority compensation coefficient. During the coordinated irradiation stage, the light intensity compensation coefficient includes the packaging compensation coefficient. The packaging compensation coefficient is used to compensate for the attenuation loss of light due to food packaging. The priority compensation coefficient is positively correlated with the freshness preservation priority. The duration compensation coefficient includes a storage compensation coefficient and a priority compensation coefficient. The duration benchmark value under the pre-irradiation stage is less than the duration benchmark value under the coordinated irradiation stage. The storage compensation coefficient is negatively correlated with the storage duration factor of the food ingredient. The storage duration factor is the ratio of the storage duration of the food ingredient to the recommended storage duration of the food ingredient.

16. The refrigeration equipment according to claim 14, characterized in that, The controller generates target lighting parameters based on the lighting parameters corresponding to multiple ingredients of the same type, and is configured as follows: When the illumination parameter is the wavelength of the pre-irradiation stage, if the irradiation wavelength ranges of multiple ingredients overlap, the wavelength located within the overlap is determined as the target wavelength. If the irradiation wavelength ranges of the various ingredients do not overlap, then the target wavelength is determined from the irradiation wavelength ranges of the various ingredients respectively; When the illumination parameter is the light intensity of the pre-irradiation stage, the maximum value among the light intensities corresponding to the various ingredients is determined as the target light intensity; When the illumination parameters are the illumination durations of the pre-irradiation stage and the synergistic irradiation stage, the maximum value among the illumination durations corresponding to the various ingredients is determined as the target illumination duration. When the illumination parameter is the ratio of red to blue light irradiation time in the synergistic irradiation stage, the ratio of red to blue light irradiation time corresponding to the food with the highest preservation priority is determined as the target red to blue light irradiation time ratio. The target wavelength, the target light intensity, the target illumination duration, and the target red-blue light illumination duration ratio are determined as the target illumination parameters.

17. The refrigeration equipment according to any one of claims 1-16, characterized in that, The controller is also configured to: When the multicolor light source is controlled to respond to the adjusted illumination parameters, if changes are detected in various ingredients in the preservation chamber, the target step and the steps following the target step are re-executed; the target step includes identifying the illumination requirement type corresponding to each of the various ingredients in the preservation chamber.

18. The refrigeration equipment according to claim 17, characterized in that, The step of controlling the multicolor light source in response to the adjusted illumination parameters, wherein if changes are detected in various ingredients within the preservation chamber, the target step and subsequent steps are re-executed, is further configured as follows: If a new food ingredient with a light-required light type is detected in the preservation chamber, after generating the light scheduling strategy, the light parameters are compensated using a preset acceleration compensation coefficient within a preset time period to obtain the compensated light parameters. The operation of the multicolor light source is controlled based on the compensated illumination parameters.

19. A control method for a refrigeration device, characterized in that, The method for controlling refrigeration equipment includes: Identify the different light requirements of various ingredients in the preservation chamber; Based on the characteristics of the ingredients, the preservation value of various ingredients is evaluated; the preservation value of the ingredients is positively correlated with the preservation priority of the ingredients. When multiple lighting requirements exist that conflict with each other, including both light-demanding and light-avoiding requirements, a basic lighting strategy is determined based on the highest preservation priority between the food preservation value of the food corresponding to the light-demanding type and the food preservation value of the food corresponding to the light-avoiding type. When multiple lighting requirement types have conflicting requirements that do not simultaneously include the light-requiring type and the light-avoiding type, the preset time-series isolation scheduling strategy is determined as the basic lighting strategy; the time-series isolation scheduling strategy is a strategy of providing corresponding lighting to ingredients of different lighting requirement types at different time periods. Based on the various ingredients in the preservation chamber, the lighting parameters in the basic lighting strategy are adjusted to generate a lighting scheduling strategy. The various food ingredients are illuminated based on the illumination parameters in the illumination scheduling strategy.

20. A computer program product, characterized in that, When the computer program product is run on the refrigeration device, the refrigeration device executes the method as described in claim 19.

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