A method, system and apparatus for temperature regulation of a refrigerated cabinet
By processing the temperature data of the refrigerator using logical judgment and sliding window algorithms, the problems of temperature fluctuation and unevenness are solved, achieving efficient and stable temperature control within the refrigerator, reducing energy consumption and improving the reliability of the storage environment.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- 广东金绿食品科技有限公司
- Filing Date
- 2025-07-02
- Publication Date
- 2026-05-12
AI Technical Summary
The temperature field inside a refrigerator is easily affected by hot air entering when the door is opened and heat dissipation from items placed inside, resulting in drastic fluctuations and uneven distribution. This leads to frequent start-stop of the evaporator, increasing energy consumption and losses, and making it difficult to maintain a stable storage environment temperature.
A temperature data processing method combining logical judgment, sliding window algorithm, and weighted smoothing is adopted. By sensing the trend of temperature data change and setting fluctuation thresholds, the evaporator start-stop signal is dynamically adjusted to ensure the accuracy and stability of temperature control.
It achieves rapid response and stable temperature control inside the refrigerator, reduces ineffective operation of the evaporator, lowers energy consumption, and ensures accurate temperature control of the storage environment and efficient operation of the equipment.
Smart Images
Figure CN120627550B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of energy-saving technology for refrigerators, and more specifically, to a method, system, and device for temperature regulation of refrigerators. Background Technology
[0002] In modern life and business systems, refrigerated display cases, as core equipment for ensuring the safe storage of perishable food, medicine and highly sensitive items, have been deeply integrated into key areas such as home kitchens, supermarket retail, catering supply chains, medical warehousing and cold chain logistics. The accuracy and stability of their temperature control not only directly affect the freshness and quality safety of goods, but also have an impact on key indicators such as food spoilage rate, effectiveness of medical supplies and cold chain transportation efficiency.
[0003] With the iterative upgrade of electronic information technology, modern refrigerators are generally equipped with intelligent electronic temperature control systems. These systems use high-precision thermistors and other temperature sensors installed inside the refrigerator to collect real-time temperature data and dynamically compare it with the target temperature range set by the user. Once any temperature data is detected to deviate from the set temperature range, the intelligent electronic temperature control system will output a start signal to the control circuit to activate the evaporator to lower the temperature inside the refrigerator, thus achieving constant temperature protection for stored items throughout the entire life cycle.
[0004] However, in practical applications, the temperature field inside a refrigerator is subject to interference from factors such as opening the door to introduce hot air and placing items to dissipate heat, resulting in severe fluctuations and uneven distribution. On the one hand, operations such as opening the door and placing new items can cause significant changes in local temperature in a short period of time. The instantaneous fluctuations in the original temperature data can easily lead to frequent start-stop of the evaporator, which increases equipment energy consumption and wear and tear, and makes it impossible to maintain a stable storage environment temperature. On the other hand, when the temperature field is uneven, if local high or low temperatures are not effectively identified and handled, they will continue to affect the overall temperature control accuracy and threaten the quality of stored items (such as medicines becoming ineffective or food spoiling). In view of this, we propose a refrigerator temperature regulation method, system, and equipment. Summary of the Invention
[0005] The purpose of this invention is to solve the problem that the temperature field inside a refrigerator is easily affected by hot air entering when the door is opened and heat dissipation from placed items, resulting in drastic fluctuations and uneven distribution. Opening the door and placing items causes significant short-term changes in local temperature, and the instantaneous fluctuations in the original data easily lead to frequent start-stop cycles of the evaporator, increasing energy consumption and losses, and making it difficult to stabilize the temperature.
[0006] To achieve the above objectives, the present invention provides a method for adjusting the temperature of a refrigerator, comprising the following steps:
[0007] S1. Sensing temperature data and temperature range inside the refrigerator, and using logical judgment to determine whether a control signal needs to be output;
[0008] S2. A temperature data set is constructed using a sliding window algorithm, and the temperature data is processed by weighted smoothing. Then, it is replaced with the temperature data inside the refrigerator, and a temperature fluctuation threshold is set. If the temperature fluctuation amplitude is less than the threshold, the replacement is not performed.
[0009] S3. Analyze the temperature data change trend in the temperature dataset. If the trend is decreasing, reduce the number of data points when constructing the temperature dataset. If the trend is increasing, reduce the upper limit of the temperature range.
[0010] As a further improvement to this technical solution, in S1, the logical judgment method is as follows: if the collected temperature data equals the upper limit of the temperature range, then a start signal is output; if the collected temperature data equals the lower limit of the temperature range, then a stop signal is output.
[0011] The beneficial effect of the above-mentioned further solution is that, through logical judgment, when the collected temperature data reaches the upper limit of the temperature range, a start signal is output to turn on the evaporator, thus promptly suppressing the temperature rise; when the collected temperature data drops to the lower limit of the temperature range, a shut-off signal is output to turn off the evaporator, thus avoiding over-cooling. This method can precisely control the start and stop of the refrigeration system based on the temperature boundary, which can quickly respond to abnormal temperature fluctuations, maintain the stability of the storage environment temperature, avoid the ineffective operation of the refrigerator, reduce energy consumption and losses, and ensure that the temperature control of the refrigerator is efficient and reliable.
[0012] Based on the above technical solution, the present invention can be further improved as follows.
[0013] As a further improvement to this technical solution, the working principle of the sliding window algorithm in S2 to construct the temperature data set is as follows: sensing the cabinet door opening and closing signal, setting the number of temperature data to be selected n, selecting n temperature data collected by the temperature sensor after the cabinet door closes, and constructing a temperature data set according to the collection time order;
[0014] If the temperature fluctuation range is greater than or equal to the range threshold, then after collecting new temperature data, the earliest collected temperature data will be removed from the temperature data set and the new temperature data will be included to form a new temperature data set.
[0015] As a further improvement to this technical solution, the sliding window algorithm in S2 works by weighted smoothing of temperature data in the temperature dataset as follows: the temperature data in the temperature dataset is assigned weights from largest to smallest according to the time order of temperature data collection, and the sum of all weights is 1.
[0016] The temperature data is obtained by multiplying each temperature data point in the temperature dataset by its corresponding weight and then summing the results.
[0017] The beneficial effects of the above-mentioned further solutions are as follows: by setting a number of temperature data collected after the cabinet door is closed, a set is constructed; when the fluctuation exceeds the threshold, the earliest data is removed and the new data is added to update the set, which can dynamically adapt to temperature fluctuations and retain valid recent data; the weighted smoothing process assigns decreasing weights (summing to 1) according to the collection order, and the temperature data is multiplied by the weights and summed to obtain the result, which can weaken the interference of old temperature data, highlight the recent temperature trend, make the processed temperature data more stable and accurate, improve the temperature control logic's perception and response to the real temperature field, and ensure the stability of the cold storage environment.
[0018] Based on the above technical solution, the present invention can be further improved as follows.
[0019] As a further improvement to this technical solution, the temperature fluctuation amplitude is the absolute value of the temperature difference between two adjacent temperature data points in the temperature data set.
[0020] The beneficial effects of the above-mentioned further solutions are that by defining the temperature fluctuation amplitude as the absolute value of the difference between adjacent temperature data in the temperature dataset, the rate of temperature change can be quantified in a simple and direct way; by monitoring the difference between adjacent temperature data in real time, subtle fluctuations in the temperature field can be quickly identified, and the sliding window update mechanism can be precisely triggered (such as removing old temperature data and adding new temperature data when the absolute value of the difference exceeds a threshold), allowing the temperature dataset to dynamically adapt to actual fluctuations, avoiding weighted smoothing processing due to interference from lagging or redundant temperature data, improving the sensitivity of temperature data to changes in the temperature field, ensuring that the temperature control strategy is based on real and timely temperature conditions, and enhancing the temperature control accuracy and stability of the refrigerator.
[0021] Based on the above technical solution, the present invention can be further improved as follows.
[0022] As a further improvement to this technical solution, S3 analyzes the temperature data change trend: sensing each temperature data in the temperature data set, comparing the size of the temperature data, if each temperature data in the temperature data set gradually decreases, then it is determined that the temperature data change trend in the temperature data set is a decreasing trend.
[0023] If each temperature data point in the temperature dataset gradually increases, then the trend of temperature data change in the temperature dataset is determined to be an increasing trend.
[0024] As a further improvement to this technical solution, S3 reduces the number of data points when constructing a new temperature data set: based on the set number of temperature data points n, after S2 constructs the temperature data set for the first time according to the number of selected temperature data points, if the temperature data shows a decreasing trend at this time, then when constructing a new temperature data set for the second time, the number of selected temperature data points in the second temperature data set is one less than the number of selected temperature data points in the first time, and so on.
[0025] The S3 reduces the upper limit of the temperature range: the upper limit of the temperature range in S1 is sensed, and an adjustment coefficient is set: the reduced upper limit of the temperature range is the upper limit of the temperature range in S1 multiplied by the adjustment coefficient.
[0026] As a further improvement to this technical solution, if S1 determines that the temperature data after weighted smoothing is equal to the upper limit of the reduced temperature range, then S1 outputs a start signal to make the temperature data inside the refrigerator equal to the lower limit of the temperature range. At this time, the temperature data inside the refrigerator is the temperature data after weighted smoothing by S2.
[0027] The beneficial effects of the above-mentioned further solutions are that by analyzing the trend of temperature data changes, the dynamic changes of the temperature field inside the refrigerator can be accurately identified. When the temperature data gradually decreases and shows a decreasing trend, the number of data points when constructing a new temperature data set is gradually reduced. This can reduce data redundancy, improve computational efficiency, and avoid invalid calculations when the temperature field tends to stabilize. Conversely, when the temperature data gradually increases and shows an increasing trend, lowering the upper limit of the temperature range and combining it with dynamic optimization of the adjustment coefficient can trigger the start-up signal in advance, preventing the temperature from rising continuously and ensuring the stability of the temperature data.
[0028] When the weighted smoothed temperature data is determined to have reached the upper limit of the reduced temperature range, a start signal is output to reduce the temperature data to the lower limit. The weighted smoothed data is used as the temperature basis, which ensures that the temperature control decision is based on stable and reliable temperature data, achieves precise temperature control, improves the accuracy and stability of the refrigerator's temperature control and the energy efficiency of the equipment, and effectively protects the quality of stored items.
[0029] Based on the above technical solution, the present invention can be further improved as follows.
[0030] As a further improvement to this technical solution, a refrigerator temperature control system includes a temperature control execution decision module, a temperature data processing module, and a temperature control strategy optimization module, wherein:
[0031] The temperature control execution decision module senses the temperature data and temperature range inside the refrigerator, and uses a logical judgment method to determine whether a control signal needs to be output. If the collected temperature data equals the upper limit of the temperature range, a start signal is output; if the collected temperature data equals the lower limit of the temperature range, a stop signal is output.
[0032] The temperature data processing module constructs a temperature data set, uses a sliding window algorithm to perform weighted smoothing on the temperature data in the temperature data set, and replaces it with the temperature data in the temperature control execution decision module. A temperature fluctuation amplitude threshold is set. When the temperature fluctuation amplitude is less than the amplitude threshold, the temperature data collected in the temperature control execution decision module is compared with the temperature range.
[0033] The temperature control strategy optimization module analyzes the temperature data change trend in the temperature dataset. If the trend is decreasing, the number of data in the temperature dataset is reduced; if the trend is increasing, the upper limit of the temperature range is reduced. If it is determined that the weighted smoothed temperature data equals the reduced upper limit of the temperature range, the temperature control execution decision module outputs a start signal to make the temperature data inside the refrigerator equal to the lower limit of the temperature range. At this time, the temperature data inside the refrigerator is the temperature data after weighted smoothing by the temperature data processing module.
[0034] As a further improvement to this technical solution, a refrigerator temperature control device includes a refrigerator cabinet and a memory for storing temperature data.
[0035] In addition to the objectives, features, and advantages described above, the present invention has other objectives, features, and advantages. The invention will now be described in further detail with reference to the figures. Attached Figure Description
[0036] Figure 1 This is a schematic diagram illustrating the working steps of the refrigerator temperature adjustment method in this invention;
[0037] Figure 2 This is a flowchart illustrating the working steps of the refrigerator temperature adjustment method in this invention.
[0038] Figure 3 This is a schematic diagram of the various modules of the refrigerator temperature control system in this invention;
[0039] Figure 4 This is a flowchart illustrating the working principle of the refrigerator temperature control system in this invention.
[0040] Figure 5 This is a three-dimensional schematic diagram of the refrigerator cabinet body of the present invention;
[0041] Figure 6 This is a schematic diagram of the internal structure of the refrigerator cabinet of the present invention.
[0042] The meanings of the labels in the diagram are as follows:
[0043] 100. Temperature control execution decision module; 200. Temperature data processing module; 300. Temperature control strategy optimization module; 400. Refrigerated cabinet body. Detailed Implementation
[0044] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0045] refer to Figures 1-2 As shown: A method for adjusting the temperature of a refrigerator, including the following steps:
[0046] S1. The temperature sensor collects temperature data inside the refrigerator and senses the temperature range set by the user. It uses a logic judgment method to determine whether a control signal needs to be output. The specific working principle is as follows: If the collected temperature data is within the upper limit of the temperature range, a start signal is output to the control circuit to start the evaporator and reduce the temperature data inside the refrigerator until the temperature data inside the refrigerator is within the lower limit of the temperature range. Then, a shut-off signal is output to the control circuit to shut down the evaporator.
[0047] S2 senses the cabinet door opening / closing signal and uses a sliding window algorithm to perform weighted smoothing on the continuously collected temperature data in S1. The weighted smoothed temperature data is then replaced with the temperature data in S1. The specific working principle is as follows: The number of temperature data points to be selected is set to n. n temperature data points collected by the temperature sensor after the cabinet door closes are selected, and a temperature data set [x] is constructed according to the collection time. t-n+1 ,x t-n+2 ,…,x t ], where x t For the temperature data collected by the temperature sensor at time t, by setting the number of temperature data selected n, the sample size of the temperature data involved in the calculation is clarified, which provides a quantitative basis for the subsequent dynamic capture of temperature field change trends and the balance between data stability and real-time performance;
[0048] Assign corresponding weights w1, w2, ..., w to each temperature data point. n Furthermore, since the temperature data inside the refrigerator gradually stabilizes over time after the refrigerator door is closed, and newly collected temperature data more directly reflects the current temperature state, the weight of each temperature data point follows the rule that the more recent the collection time, the greater the weight. That is, the weight is assigned sequentially to the temperature data collected at each time point according to the logic of descending from the largest to the smallest (because newer temperature data reflects the current temperature state more directly and is more valuable), while satisfying w1 < w2 < ... < w n And w1 + w2 + ... + w n =1, so that the weighted smoothing process can more accurately reflect the temperature data inside the refrigerator; and then multiply the n temperature data by their corresponding weights and sum them to obtain the weighted smoothed temperature data:
[0049] By replacing the temperature data after weighted smoothing with the temperature data in S1, the instantaneous extreme temperature and large fluctuation data generated at the moment of door opening and during the heat dissipation stage of the item are effectively filtered out. This avoids S1 directly using unstable temperature data to compare with the temperature range, thereby preventing the evaporator from frequently starting and stopping due to misjudgment and solving the temperature control deviation problem caused by uneven temperature field in traditional temperature control.
[0050] A temperature fluctuation amplitude threshold is set. When the temperature fluctuation amplitude is less than the threshold, the temperature data collected in S1 is compared with the temperature range. The absolute value of the temperature difference between two adjacent temperature data in the temperature data set is the temperature fluctuation amplitude. When the temperature fluctuation amplitude is less than the threshold, it indicates that the temperature field inside the refrigerator has become stable. At this time, the temperature data in S1 is switched to make temperature control decisions. This can avoid the frequent start and stop of the evaporator due to the instability of the temperature data in S1 when the temperature fluctuates drastically, and can also ensure that the high accuracy of the temperature data in S1 can be used to achieve precise temperature control after the temperature stabilizes.
[0051] If the temperature fluctuation amplitude is greater than or equal to the amplitude threshold, then new temperature data x should be collected. t+1 Then, the earliest collected temperature data (x) is removed from the temperature data set. t-n+1 And incorporate the newly acquired temperature data x from the temperature sensor. t+1 This forms a new temperature data set [x] t-n+2 ,…,x t ,x t+1 ]; and retrieve the weights w1, w2, ..., w corresponding to each temperature data point in the previous temperature dataset. n Then, each temperature data point in the new temperature dataset is multiplied by its corresponding weight and summed to obtain the new temperature data after weighted smoothing. Then replace it with the temperature data in S1 until the temperature fluctuation amplitude is less than the amplitude threshold.
[0052] As time progresses after the refrigerator door is closed, the heat from the incoming hot air and newly placed items gradually diminishes with air circulation and heat exchange. The temperature field inside the refrigerator exhibits a dynamic trend of "weakening fluctuations and stabilizing." By collecting new temperature data from S1 and shifting the sliding window to the right, the oldest temperature data is systematically removed (because it is greatly affected by initial disturbances and has low representational value for the current stable temperature field), while the latest temperature data is included (which is closer to the current temperature state and can accurately reflect the temperature convergence trend in the later stages of heat exchange). This ensures that the temperature dataset used in the calculation always focuses on samples that are "newer and closer to the real temperature trend," filtering out historical interference from extreme disturbances at the beginning of opening the door. This ensures that the weighted calculation results continuously conform to the real temperature change pattern, guaranteeing that the S2's perception accuracy of the temperature field continuously improves over time before the temperature fluctuation amplitude reaches the threshold, providing reliable data support for S1's precise temperature control decisions.
[0053] If S1 determines that the temperature data after weighted smoothing by S2 is within the temperature range, S1 does not output start or stop signals, and the evaporator is not running. S3 senses each temperature data in the temperature data set and compares the magnitude of the temperature data. If each temperature data in the temperature data set gradually decreases, it indicates that the refrigerator has entered the stage of "temperature self-decline and gradual stabilization" through natural heat exchange such as air convection and thermal radiation (e.g., the hot air introduced by opening the door gradually mixes with the cold air, and the heat dissipation rate of newly placed items decreases). Therefore, it is determined that the temperature data in the temperature data set shows a decreasing trend. This indicates that the refrigerator has entered the stage of "temperature self-decline and gradual stabilization" through natural heat exchange (e.g., air convection and thermal radiation). At this time, the heat dissipation effect of the hot air introduced by opening the door and the heat dissipation of newly placed items gradually diminishes, the temperature field no longer fluctuates violently, and a small amount of data can accurately reflect the current temperature data in the refrigerator. Therefore, the number of temperature data n selected in S2 is reduced simultaneously: each time S2 constructs a new temperature data set, the number of temperature data selected is n-1. The corresponding iteration logic is as follows:
[0054] By reducing the number of temperature data points n selected in S2 through S3, the computational load of the weighted smoothing algorithm can be reduced (e.g., by reducing the number of multiplication and summation operations) without sacrificing the accuracy of temperature characterization. This allows S2 to complete temperature data processing faster and accelerates the response to temperature changes.
[0055] If each temperature data point in the temperature dataset gradually increases, it indicates that the temperature field inside the refrigerator is uneven. The localized high temperature generated when the refrigerator door is opened, along with the temperature of the placed items, will diffuse into the refrigerator through air convection and thermal radiation. Therefore, the trend of temperature data in the dataset is determined to be increasing; and the upper limit of the temperature range is lowered: T up-new =T up-old ·k, where T up-new T is the upper limit of the reduced temperature range. up-old S1 represents the upper limit of the temperature range, and k is the adjustment coefficient. By lowering the upper limit of the temperature range, S1 can output a start signal in advance, preventing the temperature inside the refrigerator from rising continuously and actively, ensuring that the temperature inside the refrigerator remains stable within a reasonable range, and improving the energy efficiency of the equipment and the reliability of the stored items.
[0056] If S1 determines that the temperature data after S2 weighted smoothing changes over time equals the upper limit of the temperature range after S3 reduction, then it outputs a start signal to the control circuit to start the evaporator, reducing the temperature data inside the refrigerator so that the temperature data inside the refrigerator equals the lower limit of the temperature range. At this time, the temperature data inside the refrigerator is the temperature data after S2 weighted smoothing.
[0057] refer to Figures 3-4As shown: A refrigerator temperature control system includes a temperature control execution decision module 100, a temperature data processing module 200, and a temperature control strategy optimization module 300, wherein:
[0058] The temperature control execution decision module 100 senses the temperature data and temperature range inside the refrigerator and uses a logical judgment method to determine whether a control signal needs to be output. If the collected temperature data equals the upper limit of the temperature range, a start signal is output; if the collected temperature data equals the lower limit of the temperature range, a stop signal is output. The temperature data processing module 200 constructs a temperature data set, uses a sliding window algorithm to perform weighted smoothing on the temperature data in the temperature data set, and replaces it with the temperature data in the temperature control execution decision module 100. A temperature fluctuation amplitude threshold is set. When the temperature fluctuation amplitude is less than the amplitude threshold, the temperature data collected in the temperature control execution decision module 100 is compared with the temperature range.
[0059] The temperature control strategy optimization module 300 analyzes the temperature data change trend in the temperature data set. If the trend is decreasing, the number of data in the temperature data set is reduced; if the trend is increasing, the upper limit of the temperature range is reduced. If it is determined that the temperature data after weighted smoothing equals the lower upper limit of the temperature range, the temperature control execution decision module 100 outputs a start signal to make the temperature data in the refrigerator equal to the lower limit of the temperature range. At this time, the temperature data in the refrigerator is the temperature data after weighted smoothing by the temperature data processing module 200.
[0060] refer to Figure 5 and Figure 6 As shown: A refrigerator temperature control device includes a refrigerator cabinet 400 and a memory for storing temperature data.
[0061] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.
Claims
1. A method for adjusting the temperature of a refrigerator, characterized in that, Includes the following steps: S1. Sensing temperature data and temperature range inside the refrigerator, and using logical judgment to determine whether a control signal needs to be output; S2. A temperature data set is constructed using a sliding window algorithm, and the temperature data is processed by weighted smoothing. Then, it is replaced with the temperature data inside the refrigerator, and a temperature fluctuation threshold is set. If the temperature fluctuation amplitude is less than the threshold, the replacement is not performed. S3. Analyze the temperature data change trend in the temperature dataset. If it is a decreasing trend, reduce the number of data points when constructing the temperature dataset. If it is an increasing trend, reduce the upper limit of the temperature range. In S1, the logical judgment method is as follows: if the collected temperature data equals the upper limit of the temperature range, then a start signal is output; if the collected temperature data equals the lower limit of the temperature range, then a stop signal is output. The working principle of the sliding window algorithm in S2 to construct the temperature data set is as follows: Sensing the cabinet door opening and closing signal, setting the number of temperature data to be selected n, selecting n temperature data collected by the temperature sensor after the cabinet door closes signal, and constructing a temperature data set according to the collection time order; If the temperature fluctuation amplitude is greater than or equal to the amplitude threshold, then after collecting new temperature data, the temperature data with the earliest collection time in the temperature data set will be removed and the new temperature data will be included to form a new temperature data set. The sliding window algorithm in S2 works by weighted smoothing the temperature data in the temperature dataset as follows: the temperature data in the dataset are assigned weights from largest to smallest according to the time sequence of temperature data collection, and the sum of all weights is 1. The temperature data is obtained by multiplying each temperature data point in the temperature dataset by its corresponding weight and then summing the results.
2. The method for adjusting the temperature of a refrigerator according to claim 1, characterized in that: The temperature fluctuation amplitude is the absolute value of the temperature difference between two adjacent temperature data points in the temperature data set.
3. The method for adjusting the temperature of a refrigerator according to claim 2, characterized in that: The S3 analysis of temperature data change trends: sensing each temperature data in the temperature data set, comparing the size of the temperature data, if each temperature data in the temperature data set gradually decreases, then it is determined that the temperature data change trend in the temperature data set is a decreasing trend; If each temperature data point in the temperature dataset gradually increases, then the trend of temperature data change in the temperature dataset is determined to be an increasing trend.
4. The method for adjusting the temperature of a refrigerator according to claim 3, characterized in that: S3 reduces the number of data points when constructing a new temperature data set: Based on the set number of temperature data points n, after S2 constructs the temperature data set for the first time according to the number of selected temperature data points, if the temperature data shows a decreasing trend at this time, then when constructing a new temperature data set for the second time, the number of selected temperature data points in the second temperature data set is one less than the number of selected temperature data points in the first time, and so on. The S3 reduces the upper limit of the temperature range: the upper limit of the temperature range in S1 is sensed, and an adjustment coefficient is set: the reduced upper limit of the temperature range is the upper limit of the temperature range in S1 multiplied by the adjustment coefficient.
5. The method for adjusting the temperature of a refrigerator according to claim 3, characterized in that: If S1 determines that the temperature data after weighted smoothing is equal to the upper limit of the reduced temperature range, then S1 outputs a start signal to make the temperature data inside the refrigerator equal to the lower limit of the temperature range. At this time, the temperature data inside the refrigerator is the temperature data after weighted smoothing by S2.
6. A refrigerator temperature control system, applied to the refrigerator temperature control method according to any one of claims 1-5, characterized in that, It includes a temperature control execution decision module (100), a temperature data processing module (200), and a temperature control strategy optimization module (300), wherein: The temperature control execution decision module (100) senses the temperature data and temperature range inside the refrigerator, and uses a logical judgment method to determine whether a control signal needs to be output. If the collected temperature data equals the upper limit of the temperature range, a start signal is output; if the collected temperature data equals the lower limit of the temperature range, a stop signal is output. The temperature data processing module (200) constructs a temperature data set, uses a sliding window algorithm to perform weighted smoothing on the temperature data in the temperature data set, and replaces it with the temperature data in the temperature control execution decision module (100). It sets a temperature fluctuation amplitude threshold. When the temperature fluctuation amplitude is less than the amplitude threshold, it compares the temperature data collected in the temperature control execution decision module (100) with the temperature range. The temperature control strategy optimization module (300) analyzes the temperature data change trend in the temperature data set. If the trend is decreasing, the number of data in the temperature data set is reduced. If the trend is increasing, the upper limit of the temperature range is reduced. If it is determined that the temperature data after weighted smoothing is equal to the upper limit of the reduced temperature range, the temperature control execution decision module (100) outputs a start signal to make the temperature data in the refrigerator equal to the lower limit of the temperature range. At this time, the temperature data in the refrigerator is the temperature data after weighted smoothing by the temperature data processing module (200).
7. A temperature control device for a refrigerator, characterized in that, Includes a refrigerator cabinet (400) used in the refrigerator temperature control method according to any one of claims 1-5, and a memory in the refrigerator cabinet (400) for storing temperature data.