Energy consumption optimization method, device and storage medium for intelligent temperature control variable frequency refrigeration and preservation equipment

Abstract

The present invention discloses an energy consumption optimization method for intelligent temperature-controlled variable-frequency refrigeration and fresh-keeping equipment, comprising the following steps: S1, installing a camera on a refrigerator door, and installing a temperature and humidity sensor in the refrigerator; S2, partitioning each refrigerator compartment of the refrigerator, partitioning according to the upper and lower order of storage space, and installing an air outlet in each partition; S3, collecting temperature and humidity data in the refrigerator compartment, and establishing a data table; S4, analyzing objects and storage partitions placed in the refrigerator through image recognition; S5, calculating the temperature change of the partition through the analysis result of step S4, comparing the temperature change with a preset refrigerator temperature threshold, and obtaining a difference V0; the present invention solves the problem of high energy consumption of the control method of the refrigerator in the prior art, and at the same time achieves the purpose of uniform temperature distribution of the refrigerator, and the present invention can accurately analyze the temperature change of objects and partitions through the cooperation of the camera and the temperature and humidity sensor, accurately calculate the cooling demand of each partition and reasonably distribute it.

Description

Technical Field

[0001] The present invention relates to the technical field of refrigerators, and in particular to an energy consumption optimization method, equipment and storage medium for intelligent temperature-controlled variable-frequency refrigeration and fresh-keeping equipment. Background Art

[0002] At present, most refrigerators have the problem of uniform temperature distribution. Factors such as the shelf structure of the refrigerator and the porosity of the leeward plate will affect the uniform temperature distribution inside the refrigerator.

[0003] The distance between the leeward plate air outlet and the food may increase the temperature difference between the inner and outer food packages. The size and position of the shelf and the way the food is placed may also affect the air flow and temperature distribution. The stacking density of the food on the shelf will affect the air flow and temperature distribution. If the food is placed too densely, it will be difficult for the cold air to flow between the food, which will cause the local temperature to rise. On a shelf, if the fruits are stacked closely together, the temperature inside the fruit may be 2-3℃ higher than the surrounding air temperature, which is not conducive to the preservation of the fruit.

[0004] Stacking different types of food together will also affect the temperature. For example, putting vegetables with high water content and meat together will increase the local humidity and temperature due to the respiration and evaporation of water from the vegetables, affecting the preservation of the meat.

[0005] The direction of food placement will also affect the temperature distribution. If the long axis of the food is perpendicular to the direction of cold air flow, it will increase the resistance to air flow, making it difficult for cold air to flow around the food. For example, placing long strips of vegetables (such as cucumbers) horizontally on the shelf will be more unfavorable to the flow of cold air than placing them vertically, which may cause the temperature around the vegetables to rise.

[0006] At present, the technical means to solve this problem is to use the highest temperature area as the cooling reference threshold. Assuming that the fresh-keeping room in the refrigerator has three areas, namely A, B and C, and the temperature in area A is the highest, then the control system of the refrigerator must use the temperature of area A as the detection temperature and reduce the temperature of area A to the threshold range. However, the temperatures of areas B and C originally meet the threshold range values ​​and also need to be covered by cooling at the same time. The energy consumption of this control method is relatively high, resulting in high energy consumption of refrigerators, especially refrigerators. Therefore, there is an urgent need for an energy consumption optimization method for intelligent temperature control variable frequency refrigeration and preservation equipment that can achieve uniform temperature distribution while reducing the energy consumption of refrigerators. Summary of the invention

[0007] In order to solve the above-mentioned technical problems, the present invention provides an energy consumption optimization method, equipment and storage medium for intelligent temperature-controlled variable-frequency refrigeration and preservation equipment.

[0008] The technical solution of the present invention is achieved in this way:

[0009] An energy consumption optimization method for intelligent temperature-controlled variable-frequency refrigeration and fresh-keeping equipment comprises the following steps:

[0010] S1, install the camera on the refrigerator door and install the temperature and humidity sensor inside the refrigerator;

[0011] S2, partitioning each refrigerating chamber of the refrigerator according to the upper and lower order of the storage space, and installing an air outlet in each partition;

[0012] S3, collect temperature and humidity data in the cold storage room and create a data table;

[0013] S4, analyzing the items placed in the refrigerator and the storage partitions through image recognition;

[0014] S5, calculating the partition temperature change through the analysis result of step S4, comparing the temperature change with the preset refrigerator temperature threshold, and obtaining the difference V0;

[0015] S6, based on V0 obtained in step S5, calculate the temperature change of the adjacent zones associated with the zone, and obtain the difference V1; S7, based on V0 and V1, calculate the cooling capacity V2 required for each zone of the refrigerator;

[0016] S8, distributes cooling capacity to each partition according to V2.

[0017] Preferably, steps S3-S8 are initiated each time the refrigerator door is opened.

[0018] Preferably, in step S4, all space parameters of each refrigerator partition are first collected, and the volume of the items placed therein is calculated through image recognition analysis, and the difference between the former and the latter is the parameter value of the existing space.

[0019] Preferably, in step S1, there are several temperature and humidity sensors, which are located at different heights.

[0020] Preferably, in step S2, after dividing into zones, each zone has a preset conventional temperature threshold and a cooling time threshold, and cooling is required when the temperature is higher than the temperature threshold. An extreme temperature threshold is also preset, and the cooling time threshold of the preset extreme temperature threshold is the same as the cooling time threshold of the conventional temperature threshold.

[0021] A device includes at least one processor, at least one memory, and computer program instructions stored in the memory, and when the computer program instructions are executed by the processor, the energy consumption optimization method of the above-mentioned intelligent temperature-controlled variable-frequency refrigeration and fresh-keeping equipment is implemented. A storage medium stores computer program instructions, characterized in that when the computer program instructions are executed by the processor, the energy consumption optimization method of the above-mentioned intelligent temperature-controlled variable-frequency refrigeration and fresh-keeping equipment is implemented.

[0022] The present invention solves the problem of high energy consumption in the control method of the refrigerator in the prior art, and at the same time achieves the purpose of uniform temperature distribution of the refrigerator. The present invention cooperates with the camera and the temperature and humidity sensor to accurately analyze the temperature changes of the objects and partitions, accurately calculate the cooling demand of each partition and reasonably distribute it, ensure that the temperature of each partition is accurately maintained in an appropriate range, effectively preserve freshness, and calculate the cooling capacity according to the actual situation of the partition to avoid over-refrigeration. After the cabinet door is opened, the relevant steps are started, and adjustments can be made in time according to environmental changes to reduce unnecessary energy consumption and achieve energy consumption optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a schematic diagram of an energy consumption optimization method of an intelligent temperature-controlled variable-frequency refrigeration and preservation device of the present invention. DETAILED DESCRIPTION

[0024] In order to further explain the technical means and effects taken by the present invention to achieve the predetermined invention purpose, exemplary embodiments will be described in detail here, and examples thereof are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are only examples of methods and systems consistent with some aspects of the present application as detailed in the attached claims.

[0025] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit the present application. The singular forms "a", "the", and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0026] Example 1

[0027] like Figure 1 As shown, the present invention provides an energy consumption optimization method for intelligent temperature-controlled variable-frequency refrigeration and fresh-keeping equipment, comprising the following steps: S1, installing a camera on the door of a refrigerator, and installing a temperature and humidity sensor in the refrigerator;

[0028] In step S1, there are several temperature and humidity sensors, which are located at different heights, so as to realize more comprehensive and detailed monitoring of the internal environment of the refrigerator. Due to factors such as air flow, item placement and working mode of the refrigeration system in the refrigerator, the temperature and humidity conditions at different heights may be different. For example, the upper area near the refrigeration outlet may have relatively low temperature and low humidity, while the lower area near the drain or where more items are piled up may have more complex changes in temperature and humidity. By arranging sensors at different heights, the temperature and humidity information at these different levels can be accurately captured to form a three-dimensional temperature and humidity data network, so as to more accurately understand the real state of the environment in the refrigerator, and the subsequent partition settings (such as the partitions in the upper and lower order in step S2), the temperature and humidity data at different heights can provide a strong basis for the precise temperature control of each partition. Each partition covers a different height range, and the data collected by the temperature and humidity sensors at each height can reflect the gradient changes of temperature and humidity in the partition. This helps to more accurately calculate the temperature change of each zone (such as step S5) based on the actual temperature and humidity differences within the zone, and then reasonably calculate the cooling capacity required for each zone (such as step S7) and accurately distribute the cooling capacity (such as step S8).

[0029] S2, partition each refrigerating chamber of the refrigerator according to the upper and lower order of the storage space, and install an air outlet in each partition; in the step S2, after the partition is divided, each partition is preset with a conventional temperature threshold and a cooling time threshold, and cooling is required when the temperature is higher than the temperature threshold, and a limit temperature threshold is also preset, and the cooling time threshold of the preset limit temperature threshold is the same as the cooling time threshold of the conventional temperature threshold. Due to the natural flow characteristics of the cold air in the refrigerator (usually flowing from top to bottom), this partitioning method is convenient for targeted temperature control according to the temperature characteristics of different height areas. The upper area is relatively more susceptible to the direct impact of the cold air blown out by the refrigeration system, and the temperature may be relatively low and relatively stable; the lower area may have slightly different temperature changes due to factors such as heat exchange during the sinking of the cold air. Through partitioning, the temperature of each layer can be better grasped and adjusted to meet the fresh-keeping requirements of different items. The cooling time threshold of the preset limit temperature threshold is the same as the cooling time threshold of the conventional temperature threshold. The advantage of this setting is that it ensures that under different temperature abnormalities, the cooling treatment of each partition by the refrigeration system can be performed according to a relatively consistent time standard. This can avoid problems such as slow cooling that damages items or too fast cooling that wastes energy when facing different degrees of temperature rise. For example, whether cooling starts from the normal temperature threshold of 3°C or the extreme temperature threshold of 8°C, the temperature must be lowered to the appropriate range within the same specified time (e.g., within 10 minutes), thereby ensuring the stability of item preservation and the standardization of refrigeration system operation;

[0030] S3, collect temperature and humidity data in the cold storage room and create a data table;

[0031] S4, analyze the items and storage partitions placed in the refrigerator through image recognition. In step S4, first collect all the space parameters of each refrigerator partition, calculate the volume of the items placed through image recognition analysis, and the difference between the former and the latter is the parameter value of the existing space. The parameter value of the existing space will also affect the temperature control and preservation effect of the refrigerator. Generally speaking, when the items in the partition are sparsely placed and the remaining space is large, the circulation of cold air in the partition will be relatively smooth, and the temperature distribution will be more uniform, which is conducive to the preservation of the items. On the contrary, when the items are densely placed and the remaining space is small, the circulation of cold air may be hindered, resulting in uneven local temperature increase or decrease, thereby affecting the preservation effect of the items. By calculating the parameter values ​​of the existing space in real time and combining other information such as temperature monitoring data, the temperature control and preservation of the refrigerator can be more accurately evaluated, and then corresponding measures can be taken to optimize the placement of items or temperature control strategies. The space utilization in the refrigerator partition and the storage status of the items can be fully and accurately understood, providing strong data support for better management of temperature control, item preservation and space optimization in the refrigerator;

[0032] S5, calculating the partition temperature change through the analysis result of step S4, comparing the temperature change with the preset refrigerator temperature threshold, and obtaining the difference V0;

[0033] S6, based on V0 obtained in step S5, calculate the temperature change of the nearby partitions associated with the partition to obtain the difference V1;

[0034] S7, calculating the cooling capacity V2 required for each sub-area of ​​the refrigerator according to V0 and V1;

[0035] S8, distributes cooling capacity to each partition according to V2.

[0036] Preferably, steps S3-S8 are initiated each time the refrigerator door is opened.

[0037] Preferably, the calculation formula of step S5 is:

[0038] T i (t): The actual temperature of the ith partition at time t, obtained by collecting data and analyzing the temperature and humidity sensors. Here, the impact of temperature on cooling demand, humidity is not involved in this part of the temperature calculation.

[0039] T set,i : The preset temperature threshold of the i-th partition.

[0040] ΔT i (t): Temperature change of the i-th partition at time t, ΔTi (t) = T i (t)-T set，i .

[0041] C i : The heat capacity of the i-th partition is related to factors such as the material, volume, and items of the partition, and can be estimated through experiments or empirical data.

[0042] Q i (t): the cooling capacity required by the ith zone at time t;

[0043] For each partition i, according to the partition analyzed in step S4 and the collected temperature data, the difference V between the partition temperature change and the preset temperature threshold is calculated. 0，i (t), V 0，i (t) = ΔT i (t) = T i (t)-T set，i ;

[0044] Assume that there are n associated partitions near partition i, denoted as j = 1, 2…, n, and the temperature change of the nearby partitions is linearly related to the temperature change of the current partition, with a proportional coefficient of k. ij , then calculate the temperature change difference V of the nearby partition j associated with partition i 1，ij , V 1，ij (t) = k ij ×V 0，i (t);

[0045] 1.1.1 In step S7, the cooling capacity V2 required for each sub-area of ​​the refrigerator is calculated according to the heat calculation formula:

[0046] 1.1.2 Q=CΔT,For each partition i, considering its own temperature change V 0，i And the impact of temperature changes in nearby zones on their cooling demand, calculate the cooling capacity V required for the zone 2，i ,

[0047]

[0048] V 1，ij (t) = k ij ×V 0，i Substituting (t) into the above formula, we can get:

[0049]

[0050]

[0051] 1.1.3 Refrigeration system based on the calculated cooling capacity V required for each zone i 2，i, cooling capacity is distributed to each partition so that each partition can reach or approach the preset temperature threshold. The specific distribution method depends on the working mechanism of the refrigeration system, for example, the cooling capacity can be distributed by adjusting the refrigerant flow rate, fan speed, etc.

[0052] A device includes at least one processor, at least one memory, and computer program instructions stored in the memory, and when the computer program instructions are executed by the processor, the energy consumption optimization method of the above-mentioned intelligent temperature-controlled variable-frequency refrigeration and fresh-keeping equipment is implemented. A storage medium stores computer program instructions, characterized in that when the computer program instructions are executed by the processor, the energy consumption optimization method of the above-mentioned intelligent temperature-controlled variable-frequency refrigeration and fresh-keeping equipment is implemented.

[0053] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A method for optimizing energy consumption of intelligent temperature-controlled variable-frequency refrigeration and fresh-keeping equipment, characterized in that: The steps include: S1, install the camera on the refrigerator door and install the temperature and humidity sensor inside the refrigerator; S2, partitioning each refrigerating chamber of the refrigerator according to the upper and lower order of the storage space, and installing an air outlet in each partition; S3, collect temperature and humidity data in the cold storage room and create a data table; S4, analyzing the items placed in the refrigerator and the storage partitions through image recognition; S5, through the analysis result of step S4, the temperature change of the partition is calculated, and the temperature change is compared with the preset refrigerator temperature threshold to obtain the difference V0; the calculation formula is as follows: T i (t): The actual temperature of the ith partition at time t, obtained by collecting data from the temperature and humidity sensors and analyzing them. Here, the temperature affects the cooling demand. Humidity is not involved in the temperature calculation for the time being; T set，i : The preset temperature threshold of the i-th partition; ΔT i (t): Temperature change of the i-th partition at time t, ΔT i (t) = T i (t)-T set，i ; C i : The heat capacity of the i-th partition is related to the material, volume, items and other factors of the partition, and can be estimated through experiments or empirical data; Q i (t): the cooling capacity required by the ith zone at time t; For each partition i, according to the partition analyzed in step S4 and the collected temperature data, the difference V between the partition temperature change and the preset temperature threshold is calculated. 0，i (t), V 0，i (t)=ΔT i (t)=T i (t)-T set，i ; S6, based on V0 obtained in step S5, calculate the temperature change of the nearby partitions associated with the partition to obtain the difference V1; S7, calculate the cooling capacity V2 required for each sub-area of ​​the refrigerator based on V0 and V1, and according to the heat calculation formula: Q = CΔT, for each partition i, taking into account its own temperature change V 0，i And the impact of temperature changes in nearby zones on their cooling demand, calculate the cooling capacity V required for the zone 2，i , V 1，ij (t) = k ij ×V 0，i Substituting (t) into the above formula, we can get: S8, distributes cooling capacity to each partition according to V2.

2. The energy consumption optimization method of the intelligent temperature control variable frequency refrigeration and fresh-keeping equipment according to claim 1 is characterized in that: The steps S3-S8 are started each time the refrigerator door is opened.

3. The energy consumption optimization method of an intelligent temperature-controlled variable-frequency refrigeration and fresh-keeping equipment according to claim 1 is characterized in that: In step S4, all space parameters of each refrigerator partition are first collected, and the volume of the items placed therein is calculated through image recognition analysis. The difference between the former and the latter is the parameter value of the existing space.

4. The energy consumption optimization method of the intelligent temperature-controlled variable-frequency refrigeration and fresh-keeping equipment according to claim 1 is characterized in that: In the step S1, there are a plurality of temperature and humidity sensors, which are located at different heights.

5. The energy consumption optimization method of the intelligent temperature-controlled variable-frequency refrigeration and fresh-keeping equipment according to claim 1 is characterized in that: In step S2, after the partitions are divided, each partition is preset with a regular temperature threshold and a cooling time threshold. If the temperature is higher than the threshold, cooling is required. An extreme temperature threshold is also preset, and the cooling time threshold of the preset extreme temperature threshold is the same as the cooling time threshold of the regular temperature threshold.

6. A device comprising at least one processor, at least one memory and computer program instructions stored in the memory, wherein when the computer program instructions are executed by the processor, the method of any one of claims 1 to 5 is implemented.

7. A storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the method of any one of claims 1 to 5 is implemented.

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