Energy-saving refrigerator and intelligent partition self-adaptive control method

Abstract

The invention relates to the technical field of energy-saving refrigerators, in particular to an energy-saving refrigerator and an intelligent partition self-adaptive control method. According to the method, the heat response change is adjusted according to the response condition of the temperature in the refrigerator and the food material space proportion condition, and the endogenous heat load is analyzed; the exogenous thermal load is analyzed based on the temperature difference trend and the temperature and humidity level of the external environment in the refrigerator door opening state; dominant factors generating influences are dynamically analyzed, and weight endowing of endogenous and exogenous heat loads is adaptively adjusted, so that operation adjustment for the partitions better meets actual requirements. According to the method, internal and external common heat influence analysis is carried out on the refrigerator partition, the weight is dynamically adjusted according to the dominant influence to obtain the adjustment coefficient, dynamic balance of refrigeration output and thermal load is met, and the control efficiency of a refrigeration system of the refrigeration cabinet is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy-saving refrigerators, in particular to an energy-saving refrigerator and an intelligent partition adaptive control method. BACKGROUND

[0002] Refrigerators are widely used in households, supermarkets, cold chain warehouses and other scenarios. To meet the preservation needs of different foodstuffs, most refrigerators have adopted partition design, realizing different temperature and humidity control through division of refrigeration area, freezing area and variable temperature area, etc. The temperature control methods mainly include mechanical manual temperature control, electronic temperature control based on preset parameters, and simple frequency conversion temperature control, etc. Meanwhile, the existing technology also improves energy-saving effect through optimization of refrigeration system loop structure, use of high-efficiency insulation materials, improvement of compressor working mode, etc.

[0003] However, the partition control of the existing refrigerator does not consider the dynamic factors such as the change of foodstuff loading capacity in the partition of the refrigerator and the influence of opening the door on the environment, resulting in overcooling or insufficient cooling in some refrigerator partitions, causing energy waste or affecting the preservation quality of foodstuffs, and leading to low matching degree between the operation state of the refrigeration system and the actual refrigeration demand of each partition. SUMMARY

[0004] In order to solve the technical problems that the existing technology does not consider the dynamic factors such as the change of foodstuff loading capacity in the partition of the refrigerator and the influence of opening the door on the environment, resulting in overcooling or insufficient cooling in some refrigerator partitions, and leading to low matching degree between the operation state of the refrigeration system and the actual refrigeration demand of each partition, the purpose of the present application is to provide an energy-saving refrigerator and an intelligent partition adaptive control method, and the technical solutions adopted are as follows: The present application provides an intelligent partition adaptive control method for an energy-saving refrigerator, which comprises: For a single partition in the refrigerator, obtain the foodstuff space proportion and the temperature data in the refrigerator, as well as the temperature data and humidity data of the environment outside the refrigerator; Determine the internal heat source basic intensity value according to the response rate of the temperature data change in the refrigerator to refrigeration adjustment and the foodstuff space proportion, analyze the historical deviation of the foodstuff space distribution compactness, and adjust the internal heat source basic intensity value to obtain the internal heat load value; During the monitoring period after the refrigerator door is opened, determine the external heat source basic intensity value according to the door opening time, analyze the difference change trend of the temperature data inside and outside the refrigerator, as well as the temperature and humidity distribution and fluctuation level of the environment outside the refrigerator, adjust the external heat source basic intensity value to obtain the external heat load value; Determine the dominant factor between the endogenous heat load value and the exogenous heat load value based on the analysis of the correlation of the change of the temperature data in the cabinet during the monitoring period according to the opening state of the door body; determine the refrigeration adjustment coefficient by weighting the endogenous heat load value and the exogenous heat load value through the dominant factor and combining the heat load benchmark of the partition; Perform operation control according to the dominant factor and the refrigeration adjustment coefficient.

[0005] Further, the method for obtaining the endogenous heat basic intensity value comprises: Determine the feedback response rate by adjusting the closeness between the temperature change amount and the expected adjustment amount during the adjustment period; Obtain the endogenous heat basic intensity by combining the food material space proportion in the partition and the feedback response rate, and the feedback response rate is negatively correlated with the endogenous heat basic intensity value.

[0006] Further, the method for obtaining the endogenous heat load value comprises: Obtain the boundary of the food material distribution in the partition, obtain the food material surrounding proportion of the partition according to the boundary, and obtain the compactness evaluation degree through the proportion of the food material space proportion in the food material surrounding proportion; Determine the influence accumulation coefficient through the deviation between the compactness evaluation degree and the expected minimum compactness evaluation degree, compensate and correct the endogenous heat basic intensity value based on the influence accumulation coefficient, and obtain the endogenous heat load value.

[0007] Further, the method for obtaining the exogenous heat basic intensity value comprises: In each monitoring period after the door body is opened, the ratio of the door body opening time to the monitoring period is taken as the exogenous heat basic intensity value.

[0008] Further, the method for obtaining the exogenous heat load value comprises: In each monitoring period, the difference between the temperature data in the cabinet at each time and the temperature data of the environment is taken as the internal and external temperature difference at each time, and the temperature difference change trend degree is obtained according to the numerical size and range of all internal and external temperature differences during the monitoring period; In each monitoring period, the numerical distribution index is obtained by combining the numerical size of the temperature data and the humidity data of the environment at all times, the fluctuation amplitude index is obtained by analyzing the range change degree of the temperature data and the range change degree of the humidity data of the environment during the monitoring period, and the environment additional coefficient is obtained by combining the numerical distribution index and the fluctuation amplitude index; Combine the temperature difference change trend degree, the environment additional coefficient and the exogenous heat basic intensity value to obtain the exogenous heat load value of each monitoring period.

[0009] Further, the method for determining the dominant factor between the endogenous heat load value and the exogenous heat load value comprises: In the non-monitoring period, the endogenous heat load value is taken as the dominant factor; On each monitoring period, when the temperature difference change trend degree and the cabinet temperature data both have a growth trend, it is recorded as an exogenous correlation; when the food material space proportion and the cabinet temperature data both have a growth area, it is recorded as an endogenous correlation; When only the exogenous correlation exists, the exogenous heat load value is the dominant factor; when only the endogenous correlation exists, the endogenous heat load value is the dominant factor; otherwise, both the endogenous heat load value and the exogenous heat load value are dominant factors.

[0010] Further, the method for obtaining the refrigeration adjustment coefficient comprises: When the dominant factor is the endogenous heat load value, a preset high weight value is taken as the weight of the endogenous heat load value, and a preset low weight value is taken as the weight of the exogenous heat load value for weighted summation to obtain a total heat load value; When the dominant factor is the exogenous heat load value, a preset high weight value is taken as the weight of the exogenous heat load value, and a preset low weight value is taken as the weight of the endogenous heat load value for weighted summation to obtain a total heat load value; When both the endogenous heat load value and the exogenous heat load value are dominant factors, the endogenous heat load value and the exogenous heat load value are weighted and summed with the same weight to obtain a total heat load value; the weight sum of the endogenous heat load value and the exogenous heat load value is a value of 1; The ratio of the total heat load value to the standard heat load benchmark of the partition is taken as the refrigeration adjustment coefficient.

[0011] Further, the operation control according to the dominant factor and the refrigeration adjustment coefficient comprises: The frequency of the compressor is updated according to the reference frequency of the compressor and the refrigeration adjustment coefficient, and the opening degree of the refrigeration valve is updated according to the reference opening degree of the refrigeration valve and the refrigeration adjustment coefficient; When the dominant factor is the endogenous heat load value, the speed of the fan is updated according to the reference speed of the fan, the refrigeration adjustment coefficient and a preset endogenous adjustment coefficient; when the dominant factor is the exogenous heat load value, the speed of the fan is updated according to the reference speed of the fan, the refrigeration adjustment coefficient and a preset exogenous adjustment coefficient; otherwise, the speed of the fan is updated according to the reference speed of the fan and the refrigeration adjustment coefficient.

[0012] Further, the length of the monitoring period is a preset influence length, and if there is no door closing state in the monitoring period or the monitoring period ends when the door is open, a new monitoring period is obtained after the corresponding monitoring period.

[0013] The application further provides an energy-saving refrigerator, which comprises a control system, the control system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the intelligent partition adaptive control method of the energy-saving refrigerator when executing the computer program.

[0014] The present application has the following beneficial effects: The present application considers the heat conduction influence of the food material participating in the respiratory heat generation, adjusts the heat response change through the food material space ratio, analyzes the endogenous heat load, and evaluates the heat burden in the refrigerator. Meanwhile, considering that the environmental factors will also have a certain influence on the temperature in the refrigerator when the refrigerator is in the open door state, based on the temperature difference trend and the temperature and humidity level of the external environment, the exogenous heat load is analyzed. According to the temperature change correlation state of the refrigerator partition, the dominant factor of the heat input influence is dynamically analyzed, and the weight assignment of the endogenous and exogenous heat load is adaptively adjusted, so that the operation adjustment for the partition is more in line with the actual demand. The present application analyzes the internal and external heat influence of the refrigerator partition, dynamically adjusts the weight according to the dominant influence to obtain an adjustment coefficient, satisfies the dynamic balance of the refrigeration output and the heat load, and improves the control efficiency of the refrigeration system of the refrigerator. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can also obtain other drawings according to these drawings without creative labor.

[0016] Figure 1 A flow chart of an intelligent partition adaptive control method of an energy-saving refrigerator provided by an embodiment of the present application. DETAILED DESCRIPTION

[0017] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the specific implementation, structure, features and effects of the energy-saving refrigerator and the intelligent partition adaptive control method according to the present application are described in detail as follows by combining with the drawings and the preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0019] The specific scheme of the energy-saving refrigerator and the intelligent partition adaptive control method provided by the present application is specifically described below in combination with the drawings.

[0020] The embodiment of the application provides an energy-saving refrigerator and an intelligent partition adaptive control method Figure 1 , which shows an intelligent partition adaptive control method flow chart of an energy-saving refrigerator provided by an embodiment of the application. The method comprises the following steps: S1: For a single partition in the refrigerator, obtain the food material space proportion and the refrigerator internal temperature data, and the temperature data and humidity data of the external environment of the refrigerator.

[0021] In the embodiment of the application, the temperature sensing unit and the space occupation sensing unit arranged inside each partition of the refrigerator cover the key areas of food material storage and the key nodes of environmental interaction in the partition, so as to ensure the data collection quality. The temperature sensing unit and the space occupation sensing unit include a temperature sensor and an ultrasonic sensor, which collect the internal temperature data of the refrigerator and the food material space proportion. The food material space proportion is obtained by the ratio of the food material volume in the partition to the total volume of the partition through the space occupation sensing unit.

[0022] Considering the external influence of opening and closing the refrigerator door, in the embodiment of the application, the temperature data and humidity data of the external environment and the door opening and closing state are synchronously obtained through the externally arranged environmental temperature and humidity sensing unit and the door state sensing unit. In order to ensure the timely regulation and control of the heat input of the refrigerator, in one specific embodiment of the application, the heat load analysis and regulation are performed at a fixed interval of every 5 minutes when the door state is unchanged. If there is a change in the door state, the analysis interval is updated to 2 minutes, and the fixed interval is restored 10 minutes after the door is closed.

[0023] It can be understood that the monitored data is preprocessed, which can include data standardization processing and time scale regularization of the data, so as to facilitate unified data analysis and remove the dimension influence. It should be noted that data preprocessing is a technical means familiar to those skilled in the art, and the implementer of the frequency and collection frequency of regulation and analysis can control it by himself / herself, such as setting the collection frequency to 1 Hz, which is not described and limited here.

[0024] S2: Determine the internal heat source basic intensity value according to the response rate of the refrigerator internal temperature data change to the refrigeration adjustment and the food material space proportion; analyze the historical deviation of the food material space distribution compactness, and adjust the internal heat source basic intensity value to obtain the internal heat load value.

[0025] The internal heat input is one of the core sources of the heat load of the refrigerator partition, which is directly related to the characteristics of the food material itself, such as fresh properties, respiratory intensity and placement state. The analysis of the food material space proportion reflects the basic scale of respiratory heat, and the heat conduction response rate can reflect the fresh degree of the food material. The slower the response is, the stronger the fresh properties are, and the higher the respiratory heat is. The respiratory heat basic intensity is quantified through the response and the food material space proportion, and the internal heat source basic intensity value is determined.

[0026] In the embodiment of the present application, the feedback response rate is determined by adjusting the closeness of the temperature change amount in the time period to the expected adjustment amount, and the temperature change in the adjustment time period can reflect the feedback rate of the system to the adjustment instruction. The closer the change amount is to the expected adjustment amount, the faster the feedback.

[0027] In one specific embodiment of the present application, for a single partition, the most recent time sequence refrigeration adjustment amount instruction is taken as the expected adjustment amount, and the expected adjustment amount is the size of the temperature data expected to be adjusted by the system. The time length between the adjacent two time points after the start of adjustment is taken as the adjustment time period, the temperature data difference in the adjustment time period is taken as the temperature change amount, and the ratio of the temperature change amount to the expected adjustment amount is taken as the feedback response rate. The smaller the response rate is, the slower the heat conduction response is, the stronger the fresh food attribute of the food is, and the more vigorous the respiration is. The difference is obtained as the absolute value of the difference of the temperature data, and the index is not taken here.

[0028] Therefore, the endogenous heat basic intensity is obtained by combining the food space proportion in the partition and the feedback response rate. The feedback response rate and the endogenous heat basic intensity value are negatively correlated. The larger the endogenous heat basic intensity is, the higher the food space proportion is and the slower the heat conduction response is. Even if the temperature rise rate is gentle, it also indicates that the total heat load is large. On the contrary, it indicates that the food space proportion is low and the heat conduction response is fast. The temperature rise rate is fast but the duration is short, which indicates that the total heat load is not large and has a short-term pulse characteristic.

[0029] In one specific embodiment of the present application, the product of the value of the feedback response rate negatively correlated mapping and the food space proportion is taken as the endogenous heat basic intensity. The negative correlation mapping can be mapped in the form of inverse proportion. It should be noted that the negative correlation mapping is a technology known to those skilled in the art, and can be selected in the form of negative exponential power or negative linear function, etc. Here, it is not described and limited.

[0030] Considering that the bulk density will affect the emission efficiency of respiratory heat, in order to avoid the existence of deviation judgment between the actual heat load and the basic intensity due to heat accumulation, the correction of the compactness of the food distribution is analyzed to obtain more accurate endogenous heat load of the refrigerator. In the embodiment of the present application, the method for obtaining the endogenous heat load value comprises: The boundary of the food distribution in the partition is obtained by the ultrasonic sensor in the space occupation sensing unit, that is, the outer contour line of the overall distribution position of the food in the partition. The food surrounding proportion of the partition is obtained according to the boundary, and the overall volume size occupied by the food is determined by the surrounding condition of the outer boundary contour.

[0031] Further, a compact evaluation degree is obtained by the proportion of the food material space proportion in the food material surrounding proportion, reflecting the existence degree of the food material gap in the partition, in the embodiment of the present application, the ratio of the food material space proportion and the food material surrounding proportion is taken as the compact evaluation degree, when the compact evaluation degree is larger, that is, closer to 1, it is indicated that the distribution is more compact.

[0032] Further, the influence accumulation coefficient is determined by the deviation of the compact evaluation degree and the expected minimum compact evaluation degree, taking the most loose historical distribution as the reference, when the deviation is larger, it is indicated that the food material accumulation is more dense, the food material gap is smaller, the air circulation is worse, the respiratory heat is more difficult to dissipate through the cold air circulation, and the local heat accumulation is easy to form, so the actual heat load should be higher than the basic intensity. On the contrary, it is indicated that the food material accumulation is loose, the heat dissipation is smooth, the accumulation effect is weak, and the actual heat load is close to the basic intensity. In the embodiment of the present application, the expected minimum compact evaluation degree is the minimum value of the compact evaluation degree in the historical storage data, and the difference value between the compact evaluation degree and the expected minimum compact evaluation degree is taken as the influence accumulation coefficient.

[0033] Therefore, the endogenous heat load value is obtained by compensating and correcting the endogenous heat basic intensity value based on the influence accumulation coefficient, in the embodiment of the present application, the product of the influence accumulation coefficient and the endogenous heat basic intensity value is taken as the correction degree, and the sum value of the endogenous heat basic intensity value and the correction degree is taken as the endogenous heat load value, so as to compensate the influence of the accumulation effect of heat dissipation on the heat load.

[0034] S3: In the monitoring period after the opening of the refrigerator door body, the exogenous heat basic intensity value is determined according to the door opening time, the difference change trend of the temperature data inside and outside the refrigerator is analyzed, and the temperature and humidity distribution and fluctuation level of the external environment of the refrigerator are analyzed, and the exogenous heat basic intensity value is adjusted to obtain the exogenous heat load value.

[0035] The exogenous heat input is an important dynamic variable of the refrigerator partition heat load, which is influenced by the door interaction behavior and the external environment characteristics. In the dynamic factor analysis, the heat air invasion analysis caused by the door opening is quantified more accurately by balancing the data stability and real-time through setting the monitoring period. In one specific embodiment of the present application, the length of the monitoring period is the preset influence time, if there is no door closing state in the monitoring period or the end time of the monitoring period is the opening state, that is, the door is continuously opened or there is frequent opening in the corresponding monitoring period, a new monitoring period is obtained after the corresponding monitoring period, and multiple monitoring periods are continuously analyzed to ensure the analysis completeness of the exogenous heat input, wherein the preset influence time is set to 30 seconds, and the specific value can be adjusted by the implementer, which is not limited herein.

[0036] Since the direct factor of exogenous heat input is door opening, the higher the proportion of door opening time is, the more the total amount of external air entering the partition is, and the larger the basic scale of exogenous heat input is. Therefore, in the embodiment of the present application, the ratio of door opening time to monitoring period is taken as the exogenous heat basic intensity value in each monitoring period after the door is opened.

[0037] Since the temperature difference itself has a certain wall heat penetration effect when the door is not opened, in order to more accurately evaluate the influence degree of exogenous input and avoid the quantitative deviation caused by only counting the door opening time, the environmental temperature and humidity level is analyzed in combination with the change trend of the internal and external temperature difference, and the characteristics that environmental temperature and humidity directly affect the air heat carrying capacity and heat exchange efficiency are comprehensively considered, so as to more accurately quantify the exogenous heat load.

[0038] Preferably, in the embodiment of the present application, the exogenous heat load value acquisition method comprises: Firstly, in each monitoring period, the difference between the temperature data in the cabinet at each time and the temperature data of the environment is taken as the internal and external temperature difference at each time, which reflects the heat penetration ability of the internal and external environment itself through the temperature difference. The greater the temperature difference is, the stronger the penetration ability is.

[0039] Further, according to the numerical size and range of all internal and external temperature differences in the monitoring period, the temperature difference change trend degree is obtained. In one specific embodiment of the present application, the mean value of all internal and external temperature differences at all times in the monitoring period is taken as the temperature difference numerical distribution degree, which reflects the overall temperature difference level. Further, the difference between the maximum internal and external temperature difference and the minimum internal and external temperature difference in the monitoring period is taken as the temperature difference range distribution degree, which reflects the change influence degree of heat input. Finally, the product of the temperature difference numerical distribution degree and the temperature difference range distribution degree is taken as the temperature difference change trend degree. The greater the temperature difference change trend degree is, the more significant the dynamic change of exogenous heat load is.

[0040] The heat exchange potential is evaluated by the influence of environmental temperature and humidity. The higher the environmental temperature is, the more heat the air carries, the greater the heat exchange potential between the environment and the partition is, and the higher the environmental humidity is, the greater the specific heat capacity of the air is, the more heat is released in the heat exchange process, so the exogenous heat load in this case is higher.

[0041] Further, in each monitoring period, the numerical distribution index is obtained in combination with the numerical size of the temperature data and humidity data of the environment at all times. In the embodiment of the present application, the two mean values of the mean value of the temperature data and the mean value of the humidity data at all times are averaged and normalized to obtain the numerical distribution index, which reflects the overall distribution level of the environmental numerical value. The greater the numerical distribution index is, the stronger the exogenous heat input capacity is.

[0042] It should be noted that normalization is a technique well known to those skilled in the art, and the selection of normalization can be linear normalization or standard normalization, etc., such as using hyperbolic tangent function, and the specific normalization method is not limited herein.

[0043] At the same time, the range variation degree of the temperature data and the range variation degree of the humidity data of the environment in the monitoring period are analyzed to obtain a fluctuation amplitude index. In the embodiment of the present application, the two ranges of the temperature data range and the humidity data range in the monitoring period are averaged and normalized to obtain the fluctuation amplitude index, which reflects the numerical fluctuation amplitude. When the fluctuation amplitude is larger, it means that the amplitude is more obvious, the external thermal environment is unstable, the fluctuation risk of exogenous heat input is higher, and the impact is greater.

[0044] Therefore, the numerical distribution index and the fluctuation amplitude index are combined to obtain an environmental additional coefficient. Through the dual coupling of the number and the fluctuation, in the embodiment of the present application, the product of the numerical distribution index and the fluctuation amplitude index is taken as the environmental additional coefficient, which is used to analyze the influence level of the external additional heat input on the internal heat input. The greater the environmental additional coefficient is, the higher the influence degree is.

[0045] Finally, the exogenous heat load value of each monitoring period is obtained by combining the temperature difference change trend degree, the environmental additional coefficient, and the exogenous heat basic intensity value. The exogenous heat load value is obtained by comprehensively correcting the temperature difference change trend and the environmental temperature and humidity level. In the embodiment of the present application, the sum of the temperature difference change trend degree and the exogenous heat basic intensity value is taken as the corrected heat basic intensity value, and the sum of the corrected heat basic intensity value and the environmental additional coefficient is taken as the exogenous heat load value. The influence of the external thermal environment itself on the heat input is corrected, and the exogenous heat load is more accurately evaluated.

[0046] S4: Based on the door opening state, the change correlation of the temperature data in the cabinet in the monitoring period is analyzed to determine the dominant factor between the endogenous heat load value and the exogenous heat load value; the endogenous heat load value and the exogenous heat load value are weighted through the dominant factor, and the refrigeration adjustment coefficient is determined in combination with the partition heat load benchmark.

[0047] The total heat load intensity of each partition is quantitatively superimposed by the endogenous and exogenous. Since the door opening state is different, the dominant heat input may be different. The exogenous heat input is only significant after the door is opened, but there may be a large amount of food material state change after the door is opened, such as adding a large amount of fresh food materials. At this time, the external environment state influence is not high, and the heat load is still endogenous heat input. When the total heat load is superimposed, the endogenous heat load should also be paid more attention to. Through the analysis of the dominant relationship, the total heat load intensity more accurately reflects the core heat load source of the current partition, and the subsequent adjustment better adapts to different heat invasion situations.

[0048] Therefore, the temperature change correlation of the door body in the open state is determined to determine different dominant factors under dynamic influence.

[0049] Further, in each monitoring period, when the temperature difference change trend degree and the cabinet temperature data both have a growth trend, it is recorded as an external source correlation, that is, when the temperature difference change trend degree and the slope of the cabinet temperature data are both positive in the time sequence of the monitoring period, it is recorded as an external source correlation.

[0050] When the food material space ratio and the cabinet temperature data both have a growth area, it is recorded as an internal source correlation, that is, when the slope of the food material space ratio and the cabinet temperature data is both positive in the time sequence of the monitoring period, it is recorded as an internal source correlation.

[0051] At this time, when there is only external source correlation, the external source heat load value is the dominant factor, indicating that the external dynamic influence is dominant at this time, and more attention should be paid to external heat input when subsequent total heat load is superimposed. When there is only internal source correlation, the internal source heat load value is the dominant factor, indicating that the influence of internal source heat input is significant at this time, and is the main cause of the change of the cabinet temperature, and the interference influence of the external dynamic environment is weak, and more attention should be paid to the internal source heat input.

[0052] Otherwise, that is, when there is both external source correlation and internal source correlation, or there is no external source correlation and internal source correlation, it indicates that there is no significant difference between the two, and it is in a balanced state, so the internal source heat load value and the external source heat load value are both dominant factors.

[0053] By different dominant factors, different weights of internal source and external source are given, and the total heat load is superimposed in the partition. In the embodiment of the present application, when the dominant factor is the internal source heat load value, a preset high weight value is taken as the weight of the internal source heat load value, and a preset low weight value is taken as the weight of the external source heat load value for weighted summation to obtain the total heat load value, and the weight of the internal source heat load is increased for weighted superposition.

[0054] When the dominant factor is the external source heat load value, a preset high weight value is taken as the weight of the external source heat load value, and a preset low weight value is taken as the weight of the internal source heat load value for weighted summation to obtain the total heat load value, and the weight of the external source heat load is increased for weighted superposition.

[0055] When the endogenous heat load value and the exogenous heat load value are both dominant factors, the endogenous heat load value and the exogenous heat load value are weighted and summed with the same weight to obtain a total heat load value, and if both are dominant factors, it means that it is in a balanced state, and the weight proportion is the same. In the embodiment of the present application, the weight assignment needs to satisfy that the weight sum of the endogenous heat load value and the exogenous heat load value is a value of 1, so the preset high weight value is set to 0.7, the preset low weight value is set to 0.3, when the weighted sum needs to be weighted with the same weight, the same weight is 0.5, and the weight assignment size can be adjusted by the implementer, which is not limited here.

[0056] Through the total heat load value, the refrigeration demand matching can be performed, and the refrigeration output and the heat load are dynamically balanced by controlling through the heat load intensity analysis. Taking the standard heat load benchmark in the rated operating state of each partition as a reference, the ratio of the total heat load value to the standard heat load benchmark of the partition is taken as a refrigeration adjustment coefficient through the relative situation of the total heat load value.

[0057] S5: operating control according to the dominant factor and the refrigeration adjustment coefficient.

[0058] In each partition, there is a baseline representing the refrigeration capacity of each core component of the refrigeration system, which is determined by inherent properties such as partition volume, refrigeration circuit layout, and insulation performance, such as compressor reference frequency, fan reference speed, and refrigeration valve reference opening, which represent the optimal operating parameters of the partition under standard heat load.

[0059] Therefore, the operating parameters are controlled according to the refrigeration adjustment coefficient. In the embodiment of the present application, the reference frequency of the compressor is updated with the refrigeration adjustment coefficient, and in one specific embodiment of the present application, the product of the reference frequency of the compressor and the refrigeration adjustment coefficient is taken as the updated frequency, and the compressor is operated at the updated frequency. It should be noted that the updated frequency after adjustment does not exceed the upper and lower limits of the rated frequency range, and if it exceeds the range, it is operated at the nearest boundary value to avoid exceeding the physical operating range.

[0060] Further, the reference opening of the refrigeration valve is updated with the refrigeration adjustment coefficient, and in the embodiment of the present application, the product of the reference opening of the refrigeration valve and the refrigeration adjustment coefficient is taken as the updated opening, which is adjusted with the updated opening, and at the same time, it is ensured that the updated opening does not exceed the rated range.

[0061] When the dominant factor is the endogenous heat load value, the reference speed of the fan speed, the refrigeration adjustment coefficient, and the preset endogenous adjustment coefficient are used to update the fan speed, and in the embodiment of the present application, the preset endogenous adjustment coefficient is set to 0.95, which is reduced in the endogenous dominant adjustment to smoothly adapt to the continuous heat load. The product of the reference speed of the fan speed, the refrigeration adjustment coefficient, and the preset endogenous adjustment coefficient is taken as the updated fan speed, and the fan is operated at the updated fan speed.

[0062] Similarly, when the dominant factor is the exogenous heat load value, the fan speed is updated based on the reference speed of the fan speed, the refrigeration adjustment coefficient and the preset exogenous adjustment coefficient, in the embodiment of the present application, the preset exogenous adjustment coefficient is set to 1.05, and when the exogenous dominant adjustment is improved, the adjustment ratio is improved to strengthen the cycle response to sudden heat invasion, and the product of the reference speed of the fan speed, the refrigeration adjustment coefficient and the preset exogenous adjustment coefficient is taken as the updated fan speed, so as to update the fan speed.

[0063] Otherwise, that is, there is no obvious bias in the dominant factor, and the reference speed of the fan speed and the refrigeration adjustment coefficient are used to update the fan speed, in the embodiment of the present application, the product of the reference speed of the fan speed and the refrigeration adjustment coefficient is taken as the updated fan speed, so as to update the fan speed, and the updated fan speed also needs to be ensured not to exceed the rated range.

[0064] In the embodiment of the present application, when there is a dominant factor bias, response delay setting can also be performed to ensure the adjustment adaptability of the refrigeration coefficient, when the dominant factor is the exogenous heat load value, the response delay is fixed at 0.3s to adapt to sudden load, and when the dominant factor is the endogenous heat load value, the response delay is fixed at 1s to adapt to smooth load.

[0065] In summary, the present application considers the heat conduction influence of the food material participating in the respiratory heat generation by responding to the temperature in the refrigerator, adjusts the heat response change according to the space proportion of the food material, analyzes the endogenous heat load, and evaluates the heat burden in the refrigerator. At the same time, considering that the environmental factors will also have a certain influence on the temperature in the refrigerator when the refrigerator is in the open door state, based on the temperature difference trend and the temperature and humidity level of the external environment, the exogenous heat load is analyzed. According to the temperature change correlation state of the refrigerator partition, the dominant factor influencing is dynamically analyzed, and the weight of the endogenous and exogenous heat load is adaptively adjusted, so that the operation adjustment of the partition is more in line with the actual demand. The present application analyzes the internal and external heat influence of the refrigerator partition, adjusts the weight dynamically according to the dominant influence to obtain the adjustment coefficient, satisfies the dynamic balance of the refrigeration output and the heat load, and improves the control efficiency of the refrigeration system of the refrigerator.

[0066] The present application also provides an energy-saving refrigerator, which comprises a control system, the control system comprising a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the intelligent partition adaptive control method of the energy-saving refrigerator.

[0067] It is to be noted that the sequential order of the above-described embodiments of the present application only for the purpose of description, but not the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0068] Each of the embodiments in the specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the difference from other embodiments.

Claims

1. A method for intelligent zone adaptive control of an energy-saving freezer, characterized in that, The method includes: For a single section inside the freezer, obtain the food space ratio and internal temperature data, as well as the temperature and humidity data of the external environment. Based on the response rate of the cabinet temperature data to the refrigeration adjustment and the food space ratio, the intrinsic heat source basic intensity value is determined; the historical deviation of the compactness of the food space distribution is analyzed, and the intrinsic heat source basic intensity value is adjusted to obtain the intrinsic heat load value. During the monitoring period after the freezer door is opened, the external heat source basic intensity value is determined based on the duration of door opening; the difference and change trend of temperature data inside and outside the freezer, as well as the temperature and humidity distribution and fluctuation level of the external environment of the freezer, are analyzed, and the external heat source basic intensity value is adjusted to obtain the external heat load value. Based on the door opening status analysis, the correlation between the changes in the temperature data inside the cabinet during the monitoring period is determined, and the dominant factors between the endogenous heat load value and the exogenous heat load value are identified. The endogenous heat load value and the exogenous heat load value are weighted according to the dominant factors, and the cooling adjustment coefficient is determined in combination with the heat load benchmark of the zone. Operation is regulated based on the dominant factors and the refrigeration adjustment coefficient.

2. The intelligent partition adaptive control method for an energy-saving freezer according to claim 1, characterized in that, The method for obtaining the intrinsic thermal fundamental strength value includes: The feedback response rate is determined by how close the temperature change over a time period is to the expected adjustment amount. By combining the food space ratio within the partition with the feedback response rate, the intrinsic heat base intensity is obtained. The feedback response rate is negatively correlated with the intrinsic heat base intensity value.

3. The intelligent partition adaptive control method for an energy-saving freezer according to claim 1, characterized in that, The method for obtaining the endogenous heat load value includes: Obtain the boundaries of food distribution within the partition, and obtain the food enclosure ratio of the partition based on the boundaries; obtain the compactness assessment by the ratio of food space ratio to food enclosure ratio. The influence accumulation coefficient is determined by the deviation between the compactness assessment degree and the expected minimum compactness assessment degree; the endogenous heat load value is obtained by compensating and correcting the endogenous heat base strength value based on the influence accumulation coefficient.

4. The intelligent partition adaptive control method for an energy-saving freezer according to claim 1, characterized in that, The method for obtaining the external thermal foundation strength value includes: In each monitoring period after the door is opened, the ratio of the door opening duration to the monitoring period is used as the external heat source basic intensity value.

5. The intelligent zone adaptive control method for an energy-saving freezer according to claim 1, characterized in that, The method for obtaining the exogenous heat load value includes: In each monitoring period, the difference between the temperature data inside the cabinet and the temperature data in the environment at each moment is taken as the internal and external temperature difference at each moment; based on the magnitude and range of all internal and external temperature differences in the monitoring period, the trend of temperature difference change is obtained. For each monitoring period, the numerical distribution index is obtained by combining the temperature and humidity data of the environment at all times; the fluctuation amplitude index is obtained by analyzing the degree of variation of the temperature and humidity data of the environment during the monitoring period; and the environmental additional coefficient is obtained by combining the numerical distribution index and the fluctuation amplitude index. By combining the temperature difference change trend, environmental additional coefficient, and external heat source basic intensity value, the external heat load value for each monitoring period is obtained.

6. The intelligent partition adaptive control method for an energy-saving freezer according to claim 5, characterized in that, The dominant factors determining the relationship between endogenous and exogenous heat load values ​​include: During non-monitoring periods, the intrinsic heat load value is the dominant factor; In each monitoring period, if both the temperature difference change trend and the cabinet temperature data show an increasing trend, it is recorded as an external correlation; if both the food space ratio and the cabinet temperature data show an increasing area, it is recorded as an internal correlation. When only external heat load exists, the external heat load value is the dominant factor; when only internal heat load exists, the internal heat load value is the dominant factor; otherwise, both internal and external heat load values ​​are dominant factors.

7. The intelligent zone adaptive control method for an energy-saving freezer according to claim 1, characterized in that, The method for obtaining the cooling adjustment coefficient includes: When the dominant factor is the endogenous heat load value, the preset high weight is used as the weight of the endogenous heat load value and the preset low weight is used as the weight of the exogenous heat load value, and the weighted sum is obtained to obtain the total heat load value. When the dominant factor is the external heat load value, the preset high weight is used as the weight of the external heat load value and the preset low weight is used as the weight of the internal heat load value, and the weighted sum is obtained to obtain the total heat load value. When both endogenous and exogenous heat load values ​​are dominant factors, the endogenous and exogenous heat load values ​​are weighted and summed with equal weights to obtain the total heat load value; the weighted sum of the endogenous and exogenous heat load values ​​is a value of 1. The ratio of the total heat load value to the standard heat load benchmark for the zone is used as the cooling adjustment coefficient.

8. The intelligent zone adaptive control method for an energy-saving freezer according to claim 1, characterized in that, The operation control based on the dominant factors and refrigeration adjustment coefficient includes: The compressor frequency is updated using the compressor's reference frequency and refrigeration adjustment coefficient; the refrigeration valve opening is updated using the refrigeration valve's reference opening and refrigeration adjustment coefficient. When the dominant factor is the endogenous heat load value, the fan speed is updated with the base fan speed, the cooling adjustment coefficient, and the preset endogenous adjustment coefficient. When the dominant factor is the exogenous heat load value, the fan speed is updated with the base fan speed, the cooling adjustment coefficient, and the preset exogenous adjustment coefficient. Otherwise, the fan speed is updated with the base fan speed and the cooling adjustment coefficient.

9. The intelligent zone adaptive control method for an energy-saving freezer according to claim 1, characterized in that, The duration of the monitoring period is a preset influence duration. If there is no closed door during the monitoring period or the door is open at the end of the monitoring period, a new monitoring period will be obtained after the corresponding monitoring period.

10. An energy-saving freezer, characterized in that, The system includes a control system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the intelligent partition adaptive control method for an energy-saving freezer as described in any one of claims 1 to 9.

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