Intelligent energy-saving method and system for refrigerator

Abstract

The application relates to an intelligent energy-saving method and system for a refrigerator, and relates to the field of energy-saving electrical appliances. The method comprises the following steps: acquiring refrigerator registration categories and corresponding category occupation capacities; constructing a history interval and determining similar time points in the history interval according to the refrigerator registration categories and the corresponding category occupation capacities at each time point; determining a time similarity value according to a current time point and the similar time points, and defining the similar time points with the time similarity value greater than a demand similarity value as reference time points; constructing a detection interval and determining an article adding state in the detection interval; defining the detection interval with the article adding state consistent with a preset effective adding state as an adding interval, and performing calculation and analysis according to the adding interval and the detection interval to determine an adding proportion; and controlling the temperature of the refrigerator to decrease by a preset pre-adjustment temperature when the adding proportion is greater than a preset change proportion. The application has the effect of reducing energy waste caused by the use of the refrigerator.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of energy-saving electric appliance technology, in particular to an intelligent energy-saving method and system for a refrigerator. BACKGROUND

[0002] At present, most of the refrigerators on the market, including some products using frequency conversion technology, still use the basic control logic based on the fixed temperature value set by the user. The temperature sensor monitors the temperature in the box, and when the monitored temperature is higher than the upper limit of the set value, the compressor starts to cool until the temperature drops to the lower limit of the set value and stops.

[0003] This "on-off" or "fixed-point" control method based on a fixed temperature threshold, although the control logic is simple and the implementation cost is low, but in actual application, there are obvious energy-saving defects. Especially when the user comes back from shopping and puts a large amount of food that has not been cooled and is at room temperature or even higher temperature into the refrigerator at one time, these newly put food will carry a lot of heat, causing the temperature inside the refrigerator to rise sharply and greatly in a short time. At this time, the control system will detect that the temperature deviates from the set value, and the compressor will be forced to start and run at maximum power or high frequency to quickly pull the temperature back to the set range. However, when the compressor operates in this condition, the energy efficiency ratio will decrease significantly, and more energy is needed to reduce the temperature to the target temperature, resulting in energy waste. SUMMARY

[0004] In order to reduce the energy waste caused by the use of the refrigerator, the present application provides an intelligent energy-saving method and system for a refrigerator.

[0005] In a first aspect, the present application provides an intelligent energy-saving method for a refrigerator, which adopts the following technical solution:

[0006] An intelligent energy-saving method for a refrigerator, comprising:

[0007] Obtaining the registered product category of the refrigerator and the corresponding product category occupied capacity;

[0008] Constructing a historical interval with the current time point as the rear end point and the width being a preset historical length on a preset time axis, and determining the similar time points in the historical interval according to the registered product category of the refrigerator at each time point and the corresponding product category occupied capacity;

[0009] Calculating and analyzing according to the current time point and the similar time points to determine the time similarity value, and defining the similar time points with the time similarity value greater than a preset demand similarity value as the reference time points;

[0010] A detection interval with a preset detection duration is constructed with a reference time point as a front end point, and an item adding state is determined in the detection interval;

[0011] A detection interval in which the item adding state is consistent with a preset valid adding state is defined as an adding interval, and calculation analysis is performed according to the adding interval and the detection interval to determine an adding proportion;

[0012] When the adding proportion is greater than a preset change proportion, the temperature of the refrigerator is controlled to decrease by a preset pre-adjustment temperature.

[0013] Optionally, the step of determining the similar time point in the historical interval according to the refrigerator registered categories and the corresponding category occupied capacity at each time point comprises:

[0014] Two refrigerator registered categories are randomly selected for combination to determine a food category combination;

[0015] The category occupied capacity corresponding to each refrigerator registered category in the food category combination is differentially calculated with the category occupied capacity corresponding to the refrigerator registered category at the current time point to determine a single deviation capacity;

[0016] The single deviation capacity is used for mean value calculation in the food category combination to determine a combination deviation capacity;

[0017] The combination correlation coefficient corresponding to the food category combination is determined according to a preset correlation matching relationship, and the local similarity parameter is determined by calculation according to the combination correlation coefficient and the combination deviation capacity;

[0018] The overall similarity parameter is determined by mean value calculation according to all the local similarity parameters, and the time point at which the overall similarity parameter is greater than a preset reasonable similarity parameter is defined as the similar time point.

[0019] Optionally, the step of constructing the correlation matching relationship comprises:

[0020] A unit interval is constructed according to a preset unit time length in the historical interval, and the unit change capacity is determined by differential calculation of the category occupied capacity of the same refrigerator registered category at two end points in the unit interval;

[0021] When the unit change capacity is not in a preset stable maintenance interval, the corresponding refrigerator registered category is defined as a capacity change category, and the capacity change direction is determined according to the unit change capacity;

[0022] In the food category combination, the refrigerator registered categories other than the capacity change category are defined as capacity following categories, and the capacity following direction is determined according to the capacity following categories;

[0023] output a synchronous signal when the capacity change direction is consistent with the capacity following direction, and output an asynchronous signal when the capacity change direction is inconsistent with the capacity following direction, and calculate according to the synchronous signal and the asynchronous signal to determine the synchronous proportion;

[0024] According to the preset influence matching relationship, the combination correlation coefficient corresponding to the synchronous proportion is determined, and the correlation matching relationship is constructed according to the current food category combination and the combination correlation coefficient.

[0025] Optionally, after the synchronous proportion is determined, the intelligent energy-saving method for the refrigerator further includes:

[0026] Under the synchronous signal, the unit change capacity of the refrigerator registered category in the food category combination is calculated to determine the change relative ratio;

[0027] Among all the change relative ratios, a change relative ratio is randomly selected, and a ratio proximity range is constructed according to a preset proximity parameter, and the change relative ratios within the ratio proximity range are counted to determine the internal range quantity;

[0028] The overall synchronous quantity is counted according to the synchronous signal, and the aggregation proportion is calculated according to the maximum internal range quantity and the overall synchronous quantity;

[0029] According to the preset correction matching relationship, the synchronous correction parameter corresponding to the aggregation proportion is determined, and the synchronous proportion is updated according to the synchronous correction parameter.

[0030] Optionally, after the similar time point is determined, the intelligent energy-saving method for the refrigerator further includes:

[0031] The continuous and uninterrupted similar time points are combined to determine a similar time set;

[0032] Under the similar time set, the time similarity value is calculated and analyzed according to each similar time point and the current time point;

[0033] In the similar time set, the similar time point corresponding to the maximum time similarity value is retained, and the remaining similar time points are removed.

[0034] Optionally, it further includes a determination step of pre-adjusting the temperature, which includes:

[0035] Under the addition interval, the single addition capacity is obtained according to each refrigerator registered category;

[0036] Under the same refrigerator registered category, one of all the single addition capacities is randomly selected as the main addition capacity, and the remaining single addition capacities are defined as the secondary addition capacity;

[0037] According to the main adding capacity and all the secondary adding capacities, the adding representative coefficient is calculated to determine the adding representative coefficient;

[0038] According to the preset ranking rule, the adding representative coefficient with the maximum value is determined, and the main adding capacity corresponding to the adding representative coefficient is defined as the representative adding capacity;

[0039] According to the representative adding capacity and the preset effective variation parameter, the representative effective range is constructed, and the mean value is calculated according to the single adding capacity in the representative effective range to determine the category adding capacity;

[0040] According to the preset heat matching relationship, the demand adjustment temperature corresponding to the refrigerator registered category and the category adding capacity is determined, and the sum is calculated according to all the demand adjustment temperatures to determine the pre-adjustment temperature.

[0041] Optionally, after the category adding capacity is determined, the intelligent energy-saving method for the refrigerator further comprises:

[0042] According to the single adding capacity in the representative effective range and all the single adding capacities, the capacity trust proportion is calculated;

[0043] According to all the category adding capacities, the target capacity combination is determined, and according to the single adding capacity at the reference time point, the reference capacity combination is determined;

[0044] According to the target capacity combination and all the reference capacity combinations, the combination rationality parameter is determined by comparison and analysis;

[0045] It is judged whether the combination rationality parameter is greater than the preset combination demand parameter;

[0046] If the combination rationality parameter is greater than the combination demand parameter, the pre-adjustment temperature is determined according to the category adding capacity corresponding to the current target capacity combination;

[0047] If the combination rationality parameter is not greater than the combination demand parameter, the category adding capacity of the refrigerator registered category corresponding to the smallest capacity trust proportion is corrected according to the preset unit adjustment capacity to update, and the corresponding capacity trust proportion is updated according to the preset unit trust proportion, until the combination rationality parameter is greater than the combination demand parameter.

[0048] In the second aspect, the present application provides an intelligent energy-saving system for a refrigerator, which adopts the following technical solution:

[0049] An intelligent energy-saving system for a refrigerator, comprising:

[0050] An acquisition module for acquiring the refrigerator registered category and the corresponding category occupied capacity;

[0051] The processing module is connected with the acquisition module and the judgment module, and is used for information storage and processing.

[0052] The judgment module is connected with the acquisition module and the processing module, and is used for information judgment.

[0053] The processing module constructs a history interval with a current time point as a rear end point and a preset history length as a width on a preset time axis, and determines similar time points in the history interval according to the refrigerator registration category and the corresponding category occupation capacity at each time point.

[0054] The processing module performs calculation and analysis according to the current time point and the similar time points to determine a time similarity value, and defines a similar time point with a time similarity value greater than a preset demand similarity value as a reference time point.

[0055] The processing module constructs a detection interval with a width of a preset detection length with the reference time point as a front end point, and determines an article addition state in the detection interval.

[0056] The processing module defines a detection interval with an article addition state determined by the judgment module consistent with a preset effective addition state as an addition interval, and performs calculation and analysis according to the addition interval and the detection interval to determine an addition proportion.

[0057] The processing module controls the temperature of the refrigerator to decrease by a preset pre-adjustment temperature when the judgment module determines that the addition proportion is greater than a preset change proportion.

[0058] In summary, the present application includes at least one of the following beneficial technical effects:

[0059] During the use of the refrigerator, the situation of adding food in the refrigerator by the user can be predicted to perform cooling treatment in advance before the user adds food, thereby reducing the subsequent short-time cooling operation and reducing the energy waste caused by the use of the refrigerator;

[0060] The association situation is determined through the addition and taking situation between each food category, thereby improving the accuracy of data analysis.

[0061] The appropriate temperature for cooling treatment can be set according to the situation of the food to be added, thereby improving the energy saving of the refrigerator. BRIEF DESCRIPTION OF DRAWINGS

[0062] Figure 1 is a flowchart of the intelligent energy-saving method for the refrigerator.

[0063] Figure 2 is a flowchart of the similar time point determination method.

[0064] Figure 3 is a flowchart of the association matching relationship construction method.

[0065] Figure 4 This is a flowchart of the synchronous percentage update method.

[0066] Figure 5 This is a flowchart of the method for eliminating similar time points.

[0067] Figure 6 This is a flowchart of the method for pre-adjusting and determining the temperature.

[0068] Figure 7 This is a flowchart of the method for adding and updating the capacity of product categories.

[0069] Figure 8 This is a flowchart of a smart energy-saving method for refrigerators. Detailed Implementation

[0070] To make the purpose, technical solution, and advantages of this application clearer, the following is combined with Figures 1-8 The present application will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the application.

[0071] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0072] This application discloses an intelligent energy-saving method for refrigerators, referring to... Figure 1 The method flow for intelligent energy saving in refrigerators includes the following steps:

[0073] Step S100: Obtain the refrigerator registration category and the corresponding category's occupied capacity.

[0074] The registered food categories refer to the types of food that will be stored in the refrigerator, such as vegetables, fresh meat, frozen meat, frozen food (ice cream), etc. The specific categories can be determined according to the refrigerator model. The category-occupied capacity refers to the capacity occupied by the registered food categories in the refrigerator. This can be determined by detecting the space occupied when food is placed in the refrigerator. The space occupied inside the refrigerator can be detected by installing corresponding sensors with anti-cold function inside the refrigerator. This is not the core point of this application and is a conventional technical means for those skilled in the art, so it will not be described in detail here.

[0075] Step S101: Construct a historical interval on the preset timeline with the current time point as the end point and the width as the preset historical duration, and determine similar time points in the historical interval based on the refrigerator registration categories and the corresponding category occupancy capacity at each time point.

[0076] The time axis is a coordinate axis formed by combining each time point, the time axis points from the time point that has passed to the time point that has not arrived, wherein the direction where the time point that has passed is located is defined as the front; the historical length is a length set by the staff that can effectively obtain data of the food placement condition of the current refrigerator, for example, half a year, the historical interval is constructed to facilitate the acquisition and analysis of data in the historical length; the similar time point is a time point when the capacity of each food category in the refrigerator is similar to the current situation, which can be determined by one-to-one comparison of each category, and specific reference steps S200-S204 are referred to.

[0077] Step S102: calculating and analyzing according to the current time point and the similar time point to determine the time similarity value, and defining the similar time point with the time similarity value greater than the preset demand similarity value as the reference time point.

[0078] The time similarity value is a parameter value reflecting the similarity of two time points, for example, on the same day in a week, for example, in the same period in a day, etc., in this application, the same day is the first consideration element, and the same period is the second consideration element, wherein the weight of the first consideration element is greater than the weight of the second consideration element, and the time similarity value is determined by adding the weights of the two; the demand similarity value is the minimum time similarity value required when the staff identifies that the time condition is similar to the current situation, the reference time point is defined to identify the time point similar to the current situation, which is convenient for subsequent analysis.

[0079] Step S103: constructing a detection interval with a preset detection length from the reference time point as the front end point, and determining the article adding state in the detection interval.

[0080] The detection length is a length that can make the refrigerator reflect and analyze in advance, for example, 3 hours; the detection interval is constructed to identify the condition of a certain length after the reference time point, the article adding state is whether the food supplement treatment is performed in the refrigerator, which can be determined by monitoring the capacity change of each food before and after the detection interval.

[0081] Step S104: defining the detection interval with the article adding state consistent with the preset effective adding state as the adding interval, and calculating and analyzing the adding interval and the detection interval to determine the adding proportion.

[0082] The effective adding state is the article adding state set by the staff when the user adds food in the refrigerator, the adding interval is defined to identify the detection interval where food is added, which is convenient for subsequent analysis; the adding proportion is the ratio of the adding interval to all detection intervals, which can be determined by dividing the number of adding intervals by the number of detection intervals.

[0083] Step S105: controlling the temperature of the refrigerator to decrease by a preset pre-adjustment temperature when the adding proportion is greater than the preset change proportion.

[0084] The change proportion is the minimum adding proportion required when the staff sets that there is a high probability of food adding in the future. When the adding proportion is greater than the change proportion, it means that there is a high probability of food adding in the future. At this time, in order to reduce the situation that the compressor needs to be started with high power after food adding, the temperature of the refrigerator is decreased by a pre-adjustment temperature in advance, so that the temperature does not need to be decreased too much in a short time in the future, thereby reducing the situation that part of energy is wasted. The pre-adjustment temperature can be a fixed value, or can be determined by referring to steps S600-S605.

[0085] The step of determining similar time points in the historical interval according to the refrigerator registered categories and the corresponding category occupied capacities at each time point comprises:

[0086] Referring to Figure 2 Step S200: randomly selecting two refrigerator registered categories to combine to determine a food category combination.

[0087] The food category combination is a combination composed of two refrigerator registered categories.

[0088] Step S201: calculating the difference between the category occupied capacity corresponding to each refrigerator registered category in the food category combination and the category occupied capacity corresponding to the refrigerator registered category at the current time point to determine a single deviation capacity.

[0089] The single deviation capacity is the difference between the category occupied capacities of a single refrigerator registered category at two time points, which is an absolute value.

[0090] Step S202: calculating the mean of the single deviation capacities in the food category combination to determine a combination deviation capacity.

[0091] The combination deviation capacity is the average of the single deviation capacities determined in a single food category combination.

[0092] Step S203: determining the combination correlation coefficient corresponding to the food category combination according to the preset correlation matching relationship, and calculating the local similarity parameter according to the combination correlation coefficient and the combination deviation capacity.

[0093] The combination correlation coefficient is a parameter value reflecting the correlation between the current two food category combinations. The larger the value, the stronger the correlation between the two food categories. For example, some users will add meat when cooking. Therefore, the addition and taking of vegetables and meat are strongly correlated. The correlation matching relationship between the two can be determined by the staff in advance or constructed through steps S300-S304. The local similarity parameter is a similarity value at two time points for the current food category combination, which is determined by dividing the combination correlation coefficient by the combination deviation capacity.

[0094] Step S204: Calculate the average of all local similarity parameters to determine the overall similarity parameter, and define the time point when the overall similarity parameter is greater than the preset reasonable similarity parameter as the similar time point.

[0095] The overall similarity parameter is the average of the local similarity parameters determined for all food category combinations. The reasonable similarity parameter is the minimum overall similarity parameter that the staff needs to set to determine that the remaining food at the two time points is relatively similar. Therefore, when the overall similarity parameter is greater than the reasonable similarity parameter, the time point is defined as the similar time point.

[0096] Reference Figure 3 The method also includes a correlation matching relationship construction step, which includes:

[0097] Step S300: Construct a unit interval in the historical interval according to a preset unit time length, and calculate the difference between the category occupation capacities of the same refrigerator registered category at the two endpoints in the unit interval to determine the unit change capacity.

[0098] The unit time length is the interval time length for analyzing and processing the food in the refrigerator, for example, 1 hour of analysis. The corresponding unit time length is 1 hour. The unit change capacity is the change value of the category occupation capacity of the same refrigerator registered category before and after the unit interval, which is determined by subtracting the value at the later endpoint from the value at the earlier endpoint. A positive value indicates food consumption, and vice versa.

[0099] Step S301: Define the corresponding refrigerator registered category as a capacity change category when the unit change capacity is not in the preset stable maintenance interval, and determine the capacity change direction according to the unit change capacity.

[0100] The stable maintenance interval is an interval range in which the allowed unit change capacity of the food of the identified single category is located when the food is not used or added, and is not set to 0 to reduce the occurrence of misjudgment; when the unit change capacity is not in the stable maintenance interval, it indicates that the food of the current category is used or added, and therefore the capacity change category is defined to identify and distinguish different refrigerator registered categories for subsequent analysis; the capacity change direction reflects the direction of use or addition of the food, which can be determined by the positive or negative of the unit change capacity.

[0101] Step S302: defining the refrigerator registered categories other than the capacity change category as the capacity following categories in the food category combination, and determining the capacity following direction according to the capacity following categories.

[0102] By defining the capacity following categories to distinguish different refrigerator registered categories, the capacity following direction at this time is the change direction when the capacity following categories are used or added.

[0103] Step S303: outputting a synchronous signal when the capacity change direction is consistent with the capacity following direction, and outputting an asynchronous signal when the capacity change direction is inconsistent with the capacity following direction, and calculating according to the synchronous signal and the asynchronous signal to determine the synchronous proportion.

[0104] When the capacity change direction is consistent with the capacity following direction, it indicates that there is a synchronous use or addition between the two categories, and therefore a synchronous signal is output to identify this situation, and similarly, an asynchronous signal can be output to analyze the relationship between different foods; the synchronous proportion is the ratio of the number of times of outputting the synchronous signal to the total number of times of outputting the synchronous signal and the asynchronous signal.

[0105] Step S304: determining the combination correlation coefficient corresponding to the synchronous proportion according to the preset influence matching relationship, and constructing the correlation matching relationship according to the current food category combination and the combination correlation coefficient.

[0106] When the synchronous proportion is larger, it indicates that the synchronous use or addition of the food of the two categories is more, that is, the correlation between the two is stronger, and therefore the corresponding combination correlation coefficient is larger, and the influence matching relationship between the two can be determined by the worker in advance through multiple tests, and the correlation matching relationship determined by this method can more objectively reflect the relationship between the foods, thereby improving the accuracy of data analysis.

[0107] Reference Figure 4 After the synchronous proportion is determined, the intelligent energy-saving method for the refrigerator further includes:

[0108] Step S400: calculating according to the unit change capacity of the refrigerator registered categories in the food category combination under the synchronous signal to determine the change relative ratio.

[0109] The relative change ratio is the ratio of one refrigerator category in the food category portfolio to another refrigerator category in terms of unit change capacity, with the larger value being the denominator.

[0110] Step S401: Randomly select a relative ratio from all the relative ratios and construct a range of similar ratios using a preset similar parameter, and count the relative ratios within the range to determine the number of values ​​within the range.

[0111] The similarity parameter is the maximum allowable difference set by the staff when two relative change values ​​are considered to be close. The similarity range is the range of values ​​that the relative change values ​​that are close to the selected relative change values ​​need to be in, which is determined by adding and subtracting the similarity parameter from the relative change values ​​respectively. The number within the range is the number of relative change values ​​that are within the similarity range.

[0112] Step S402: Count according to the synchronization signal to determine the total number of synchronizations, and calculate the aggregation ratio based on the maximum number of synchronizations within the range and the total number of synchronizations.

[0113] The total number of synchronizations is the number of all identifiable relative changes. The clustering ratio is the value of the largest number within the range divided by the total number of synchronizations, which is also the proportion of the most frequently occurring relative change ratios between two food categories under the current food category combination.

[0114] Step S403: Determine the synchronization correction parameter corresponding to the aggregation ratio according to the preset correction matching relationship, and update the synchronization ratio according to the synchronization correction parameter.

[0115] The synchronization correction parameter is a parameter value used to correct and update the synchronization ratio. The larger the aggregation ratio, the more stable the relationship between the two under the current combination. In this case, the larger the synchronization correction parameter, the better the synchronization ratio can be updated by adding the synchronization correction parameter to the synchronization ratio. The correction matching relationship is determined in advance by the staff, and it is necessary to ensure that the larger the aggregation ratio, the larger the corresponding synchronization correction parameter.

[0116] Reference Figure 5 Once similar time points are determined, intelligent energy-saving methods for refrigerators also include:

[0117] Step S500: Combine consecutive and uninterrupted similar time points to determine a set of similar times.

[0118] The similar time set is the set of continuous and uninterrupted similar time points at each time point when the refrigerator situation is analyzed.

[0119] Step S501: Calculate and analyze according to each similar time point and the current time point to determine the time similarity value under the similar time set.

[0120] At this time, the most significant similar time point for analysis can be determined by analyzing the time similarity value.

[0121] Step S502: In the similar time set, the similar time point corresponding to the maximum time similarity value is retained, and the remaining similar time points are removed.

[0122] By retaining the similar time point corresponding to the maximum time similarity value and removing the remaining similar time points in the similar time set, the number of analyses under the same condition is reduced, the occurrence of repeated analysis is reduced, and the accuracy of data analysis is improved.

[0123] Reference Figure 6 It also includes a pre-adjusted temperature determination step, which includes:

[0124] Step S600: Obtain the single addition capacity according to each refrigerator registered category under the addition interval.

[0125] The single addition capacity is the capacity value added by a single refrigerator registered category in the addition interval.

[0126] Step S601: Randomly select one as the main addition capacity under the same refrigerator registered category according to all single addition capacities, and define the remaining single addition capacities as secondary addition capacities.

[0127] By defining the main addition capacity and the secondary addition capacity, different single addition capacities can be distinguished, which is convenient for subsequent analysis.

[0128] Step S602: Calculate to determine the addition representative coefficient according to the main addition capacity and all secondary addition capacities.

[0129] The addition representative coefficient is a parameter value reflecting the feasibility of the current main addition capacity representing the remaining secondary addition capacities, that is, the possibility value of the main addition capacity being the capacity that the refrigerator registered category will add in the theoretical case when adding food, which is determined by subtracting the secondary addition capacity from the main addition capacity and adding the absolute value to take the reciprocal.

[0130] Step S603: Determine the addition representative coefficient with the largest value according to the preset sorting rule, and define the main addition capacity corresponding to the addition representative coefficient as the representative addition capacity.

[0131] The sorting rule is a method for sorting the size of the value set by the staff, such as bubble method, and the maximum value of the value can be determined by the sorting rule. The representative coefficient is added, that is, the current main addition capacity can better reflect the general situation of the current food category in the capacity addition, so the representative addition capacity is defined to identify and distinguish, which is convenient for subsequent analysis.

[0132] Step S604: According to the representative addition capacity and the preset effective variation parameter, the representative effective range is constructed, and the mean value of the single addition capacity in the representative effective range is calculated to determine the category addition capacity.

[0133] The effective variation parameter is the maximum difference allowed when two capacity values are close to each other. The representative effective range reflects the range required by the remaining parameters close to the representative addition capacity. It can be determined by adding and subtracting the effective variation parameter from the representative addition capacity. The category addition capacity is the average value of the single addition capacity in the representative effective range, that is, the value of the food addition capacity of the current category.

[0134] Step S605: According to the preset heat matching relationship, the demand adjustment temperature corresponding to the registered category and the category addition capacity of the refrigerator is determined, and the sum of all demand adjustment temperatures is calculated to determine the pre-adjustment temperature.

[0135] The demand adjustment temperature is the parameter value required to be adjusted in advance in order to facilitate the subsequent large energy consumption in a short time when the food of the category is added. Under different food categories, the demand adjustment temperature corresponding to different category addition capacities is different. The heat matching relationship between the three is determined by the staff through multiple tests in advance. At this time, the sum of all demand adjustment temperatures is calculated to obtain the required pre-adjustment temperature.

[0136] Reference Figure 7 After the category addition capacity is determined, the intelligent energy-saving method for the refrigerator further includes:

[0137] Step S700: Calculate the capacity trust proportion according to the single addition capacity in the representative effective range and all single addition capacities.

[0138] The capacity trust proportion is a parameter value reflecting the reliability of the currently determined category addition capacity. The number of single addition capacities in the representative effective range under a single registered category of the refrigerator is divided by the number of all single addition capacities. The larger the value, the higher the data reliability when the category addition capacity is determined, that is, the data is more trusted.

[0139] Step S701: combine all the category adding capacities to determine a target capacity combination, and combine the monomer adding capacities at the reference time point to determine a reference capacity combination.

[0140] By determining the target capacity combination and the reference capacity combination, the combinations in different food adding situations are distinguished, which facilitates subsequent analysis.

[0141] Step S702: compare and analyze the target capacity combination and all the reference capacity combinations to determine a combination rationality parameter.

[0142] The combination rationality parameter is a parameter value reflecting whether the currently determined target capacity combination meets the daily food adding rule of the user. The larger the value, the more consistent it is. The score can be evaluated by one-to-one comparison of the target capacity combination and the reference capacity combination for each category of food, and the smaller the capacity deviation, the higher the score. Then, the comparison score between the two is obtained by adding all the scores. When the comparison score is greater than the set reasonable score, a reasonable mark is output in the comparison between the current target capacity combination and the reference capacity combination. The reasonable proportion value can be determined by dividing the number of reasonable marks by the total number of comparisons. Then, the corresponding combination rationality parameter is converted according to the proportion value.

[0143] Step S703: determine whether the combination rationality parameter is greater than a preset combination requirement parameter.

[0144] The combination requirement parameter is the minimum combination rationality parameter that needs to be reached when the staff sets to determine that the current target capacity combination meets the current user's daily food adding rule. The purpose of the judgment is to know whether the currently determined target capacity combination is correct, so as to improve the accuracy of subsequent pre-adjustment temperature determination.

[0145] Step S7031: if the combination rationality parameter is greater than the combination requirement parameter, the pre-adjustment temperature determination is performed according to the category adding capacity corresponding to the current target capacity combination.

[0146] When the combination rationality parameter is greater than the combination requirement parameter, it means that the currently determined target capacity combination meets the current user's daily food adding rule. At this time, the pre-adjustment temperature determination can be performed according to the determined category adding capacity.

[0147] Step S7032: if the combination rationality parameter is not greater than the combination requirement parameter, the category adding capacity of the refrigerator registered category corresponding to the smallest capacity trust proportion is corrected according to the preset unit adjustment capacity to update, and the corresponding capacity trust proportion is updated according to the preset unit trust proportion, until the combination rationality parameter is greater than the combination requirement parameter.

[0148] When the combination reasonable parameter is not greater than the combination demand parameter, it indicates that the current determined target capacity combination does not conform to the daily food adding rule, at this time, the category adding capacity reliability of the refrigerator registered category corresponding to the smallest capacity trust proportion is the lowest, therefore, the category adding capacity can be updated by adding or subtracting the unit adjustment capacity, so as to re-analyze and process, and the capacity trust proportion plus the unit trust proportion can reduce the frequent adjustment of a single category, so as to better determine the required target capacity combination; wherein the unit adjustment capacity and the unit trust proportion are both fixed values determined in advance, and when the unit adjustment capacity is used to adjust the category adding capacity, the unit adjustment capacity is first added for analysis, if it does not conform, the unit adjustment capacity is subtracted for analysis, if it still does not conform, the capacity trust proportion is updated to continue analysis, until the required target capacity combination is determined.

[0149] Referring to Figure 8 , based on the same inventive concept, the embodiment of the present application provides an intelligent energy-saving system for a refrigerator, comprising:

[0150] An acquisition module is configured to acquire refrigerator registered categories and corresponding category occupied capacities;

[0151] A processing module is connected with the acquisition module and the judgment module, and is configured to store and process information;

[0152] A judgment module is connected with the acquisition module and the processing module, and is configured to judge information;

[0153] The processing module constructs a historical interval with a current time point as a rear end point and a preset historical length as a width on a preset time axis, and determines similar time points in the historical interval according to the refrigerator registered categories and corresponding category occupied capacities at each time point;

[0154] The processing module performs calculation and analysis according to the current time point and the similar time points to determine a time similarity value, and defines the similar time points with a time similarity value greater than a preset demand similarity value as reference time points;

[0155] The processing module constructs a detection interval with a reference time point as a front end point and a preset detection length as a width, and determines an article adding state in the detection interval;

[0156] The processing module defines the detection interval with the article adding state determined by the judgment module consistent with a preset effective adding state as an adding interval, and performs calculation and analysis according to the adding interval and the detection interval to determine an adding proportion;

[0157] The processing module controls the temperature of the refrigerator to decrease by a preset pre-adjustment temperature when the judgment module determines that the adding proportion is greater than a preset change proportion;

[0158] A similar time point determination module is configured to determine the similar time points.

[0159] An association matching relationship construction module is configured to construct the association matching relationship between the food categories.

[0160] A synchronous proportion updating module is configured to update the synchronous proportion.

[0161] A similar time point elimination module is configured to eliminate some similar time points with the same meaning.

[0162] A pre-adjustment temperature determination module is configured to determine the pre-adjustment temperature required by the refrigerator.

[0163] A category addition capacity updating module is configured to update the category addition capacity of each food category based on the actual food addition situation.

[0164] Those skilled in the art can clearly understand that, for the convenience and brevity, only the division of the above functional modules is taken as an example for description, and in actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

Claims

1. A smart energy saving method for a refrigerator, characterized in that, The method comprises the following steps: acquiring refrigerator registration categories and corresponding category occupation capacities; constructing a history interval with a current time point as a rear end point and a preset history length as a width on a preset time axis, and determining similar time points in the history interval according to the refrigerator registration categories and corresponding category occupation capacities at each time point; performing calculation and analysis according to the current time point and the similar time points to determine a time similarity value, and defining a similar time point with a time similarity value greater than a preset demand similarity value as a reference time point; constructing a detection interval with the reference time point as a front end point and a preset detection length as a width, and determining an article addition state in the detection interval; defining a detection interval with an article addition state consistent with a preset effective addition state as an addition interval, and performing calculation and analysis according to the addition interval and the detection interval to determine an addition proportion; controlling the temperature of the refrigerator to decrease by a preset pre-adjustment temperature when the addition proportion is greater than a preset change proportion.

2. The intelligent energy saving method for a refrigerator according to claim 1, characterized in that, The step of determining similar time points in the history interval according to the refrigerator registration categories and corresponding category occupation capacities at each time point comprises the following steps: randomly selecting two refrigerator registration categories to combine to determine a food category combination; performing difference calculation on the category occupation capacities corresponding to each refrigerator registration category in the food category combination and the category occupation capacities corresponding to the refrigerator registration categories at the current time point to determine individual deviation capacities; performing mean calculation on the individual deviation capacities in the food category combination to determine a combination deviation capacity; determining a combination correlation coefficient corresponding to the food category combination according to a preset correlation matching relationship, and performing calculation according to the combination correlation coefficient and the combination deviation capacity to determine a local similarity parameter; performing mean calculation on all local similarity parameters to determine an overall similarity parameter, and defining a time point with an overall similarity parameter greater than a preset reasonable similarity parameter as a similar time point.

3. The intelligent energy saving method for a refrigerator according to claim 2, characterized in that, The method further comprises a construction step of a correlation matching relationship, which comprises the following steps: constructing a unit interval according to a preset unit length in the history interval, and performing difference calculation on the category occupation capacities of the same refrigerator registration category at two end points in the unit interval to determine a unit change capacity; defining a corresponding refrigerator registration category as a capacity change category when the unit change capacity is not in a preset stable maintenance interval, and determining a capacity change direction according to the unit change capacity; defining a refrigerator registration category other than the capacity change category as a capacity following category in the food category combination, and determining a capacity following direction according to the capacity following category; outputting a synchronous signal when the capacity change direction is consistent with the capacity following direction, and outputting an asynchronous signal when the capacity change direction is inconsistent with the capacity following direction, and performing calculation according to the synchronous signal and the asynchronous signal to determine a synchronous proportion; determining a combination correlation coefficient corresponding to the synchronous proportion according to a preset influence matching relationship, and constructing a correlation matching relationship according to the current food category combination and the combination correlation coefficient.

4. The intelligent energy saving method for a refrigerator according to claim 3, characterized in that, After the synchronous proportion is determined, the intelligent energy-saving method for the refrigerator further comprises the following steps: performing calculation on the unit change capacities of the refrigerator registration categories in the food category combination to determine a change relative ratio under the synchronous signal; Randomly select one of the change relative ratios and the preset similar parameter to construct a ratio similar range, and count the change relative ratios within the ratio similar range to determine the range internal quantity; Count the overall synchronization quantity according to the synchronization signals, and calculate the aggregation proportion according to the maximum range internal quantity and the overall synchronization quantity; Determine the synchronization correction parameter corresponding to the aggregation proportion according to the preset correction matching relationship, and update the synchronization proportion according to the synchronization correction parameter.

5. The intelligent energy saving method for a refrigerator according to claim 2, characterized in that, After the similar time points are determined, the intelligent energy-saving method for the refrigerator further includes: Combine the continuous and uninterrupted similar time points to determine a similar time set; Calculate and analyze the time similarity value according to each similar time point and the current time point in the similar time set; In the similar time set, retain the similar time point corresponding to the maximum time similarity value, and eliminate the remaining similar time points.

6. The intelligent energy saving method for a refrigerator according to claim 1, wherein, Further comprising a determination step of pre-adjusting the temperature, which includes: Obtain the single addition capacity according to each refrigerator registered category in the addition interval; Randomly select one of all the single addition capacities as the main addition capacity under the same refrigerator registered category, and define the remaining single addition capacities as the secondary addition capacities; Calculate the addition representative coefficient according to the main addition capacity and all the secondary addition capacities; Determine the addition representative coefficient with the maximum value according to the preset sorting rule, and define the main addition capacity corresponding to the addition representative coefficient as the representative addition capacity; Construct a representative effective range according to the representative addition capacity and the preset effective variation parameter, and calculate the mean value of the single addition capacities within the representative effective range to determine the category addition capacity; Determine the demand adjustment temperature corresponding to the refrigerator registered category and the category addition capacity according to the preset heat matching relationship, and calculate the sum of all the demand adjustment temperatures to determine the pre-adjustment temperature.

7. The intelligent energy saving method for a refrigerator according to claim 6, characterized in that, After the category addition capacity is determined, the intelligent energy-saving method for the refrigerator further includes: Calculate the capacity trust proportion according to the single addition capacity within the representative effective range and all the single addition capacities; Combine all the category addition capacities to determine a target capacity combination, and combine the single addition capacities of the reference time point to determine a reference capacity combination; Compare and analyze the target capacity combination and all the reference capacity combinations to determine a combination reasonable parameter; Determine whether the combination reasonable parameter is greater than a preset combination demand parameter; If the combination reasonable parameter is greater than the combination demand parameter, determine the pre-adjustment temperature according to the category addition capacity corresponding to the current target capacity combination; If the combination reasonable parameter is not greater than the combination demand parameter, correct the category addition capacity of the refrigerator registered category corresponding to the smallest capacity trust proportion according to the preset unit adjustment capacity to update, and update the corresponding capacity trust proportion according to the preset unit trust proportion, until the combination reasonable parameter is greater than the combination demand parameter.

8. A smart energy saving system for a refrigerator, characterized in that, It includes: The acquisition module is used for acquiring the refrigerator registered category and the corresponding category occupied capacity; The processing module is connected with the acquisition module and the judgment module, and is used for information storage and processing. The judgment module is connected with the acquisition module and the processing module, and is used for information judgment. The processing module constructs a history interval with a current time point as a rear end point and a preset history length as a width on a preset time axis, and determines similar time points in the history interval according to refrigerator registration categories and corresponding category occupation capacities at each time point. The processing module performs calculation and analysis according to the current time point and the similar time points to determine a time similarity value, and defines a similar time point with a time similarity value greater than a preset demand similarity value as a reference time point. The processing module constructs a detection interval with a width of a preset detection length with the reference time point as a front end point, and determines an article addition state in the detection interval. The processing module defines a detection interval with an article addition state determined by the judgment module consistent with a preset effective addition state as an addition interval, and performs calculation and analysis according to the addition interval and the detection interval to determine an addition proportion. The processing module controls the temperature of the refrigerator to decrease by a preset pre-adjustment temperature when the judgment module determines that the addition proportion is greater than a preset change proportion.

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