Refrigerator intelligent fresh-keeping operation control method and refrigerator

Abstract

The invention provides a refrigerator intelligent fresh-keeping operation control method and a refrigerator, and the method comprises the steps: collecting refrigerator compartment data in real time, analyzing a fresh-keeping mode, temperature and humidity parameters and food material type information set by a user, and generating an initial control strategy; based on the initial control strategy, a compressor and a fan are controlled to execute refrigeration operation; according to the refrigerator compartment data, the initial control strategy is dynamically optimized, and refrigeration operation parameters of a compressor and a draught fan are adjusted; and outputting the optimized initial control strategy, and uploading the optimized initial control strategy to a server for remote data synchronization. Based on the intelligent self-adaptive learning technology, multi-sensor cooperative control and a dynamic optimization strategy are combined, and precise control and remote management of the running state of the refrigerator are achieved. And the temperature and the humidity can be automatically adjusted and controlled according to the use habits of the user, the refrigeration control strategy of the refrigerator is adjusted in time, the temperature and the humidity can be kept constant, the application range is wider, and the purpose of parallel intelligent preservation is achieved.

Description

Technical Field

[0001] The present application relates to the technical field of household appliances, and more specifically to a refrigerator intelligent fresh-keeping operation control method and a refrigerator. Background Art

[0002] The main function of the refrigerator is to preserve food. Existing refrigerators provide cooling capacity to the compartments through the refrigeration system to maintain the temperature of the compartments for food preservation. The temperature control is mainly achieved by solidifying and storing temperature control instructions on the refrigerator control panel, and adjusting the compartment temperature by setting the temperature start and stop thresholds.

[0003] Writing temperature control instructions through the refrigerator control panel requires refrigerator development technicians to have certain professional knowledge of computers and refrigeration operation control. Usually, it is necessary to determine the control rules through prototype simulation operation in the laboratory, which requires technicians to have technical professional background in related fields. When the refrigerator enters the user's home, the refrigeration operation is performed according to the control program stored in the refrigerator control panel.

[0004] When the refrigerator leaves the factory, its refrigeration operation relies on the refrigerator compartment temperature sensor to sense the temperature changes in the compartment. The temperature control method inside the compartment is fixed and cannot make timely dynamic adjustments based on the type of food stored by the user and the rapid perception of temperature changes. In addition, since the compartment usually does not have a humidity sensor, it is impossible to achieve intelligent adjustment and control of temperature and humidity to extend the shelf life of food. Summary of the invention

[0005] The present application aims to solve the problem that the internal temperature control mode of the above compartment is rigid, and timely dynamic adjustment cannot be made according to the type of food stored by the user and the rapid perception of temperature changes, and the temperature and humidity cannot be intelligently adjusted. In a first aspect, a refrigerator intelligent fresh-keeping operation control method is provided, comprising the following steps:

[0006] Collect refrigerator compartment data in real time, the refrigerator compartment data includes: temperature data, food surface temperature data and humidity data;

[0007] Analyze the preservation mode, temperature and humidity parameters and food type information set by the user to generate an initial control strategy;

[0008] Based on the initial control strategy, controlling the compressor and the fan to perform refrigeration operation;

[0009] According to the refrigerator compartment data, dynamically optimize the initial control strategy and adjust the refrigeration operation parameters of the compressor and the fan;

[0010] The optimized initial control strategy is output and uploaded to the server for remote data synchronization.

[0011] In a feasible implementation, the step of generating an initial control strategy includes:

[0012] Collect the user's historical settings for fresh-keeping modes, temperature and humidity parameters, and food types to build a user habit database;

[0013] Combine the preset optimal food preservation parameter table to match the target temperature and humidity range corresponding to the current food type;

[0014] An initial cooling operation instruction is generated based on the matching result.

[0015] In a feasible implementation, the step of dynamically optimizing the initial control strategy includes:

[0016] When the real-time humidity is lower than the target humidity range, the fan speed is increased to improve the humidity uniformity of the room;

[0017] When the real-time temperature is higher than the target temperature range, extending the compressor operation time to reduce the temperature;

[0018] When abnormal surface temperature of food is detected, the refrigeration system is triggered for emergency cooling.

[0019] In a feasible implementation, the step of performing remote data synchronization includes:

[0020] The refrigerator compartment data and user operation records are uploaded to the server, and remote optimization instructions issued by the server are received.

[0021] On the other hand, the present application provides a refrigerator, including: a main control module, a compressor, a fan, a display module, a communication module and a sensor group, wherein the sensor group includes: a temperature sensor, an infrared sensor and a humidity sensor;

[0022] The main control module is electrically connected to the temperature sensor, infrared sensor, humidity sensor, compressor, fan, display module and communication module respectively;

[0023] The temperature sensor is installed on the inner wall of the refrigerator compartment to detect the compartment temperature;

[0024] The infrared sensor is installed on the top of the compartment, facing the storage compartment, and is used to detect the surface temperature of the food;

[0025] The humidity sensor is installed on the side wall of the compartment to detect the humidity of the compartment;

[0026] The main control module is integrated with an adaptive learning module and an intelligent algorithm module;

[0027] The main control module is configured as follows:

[0028] Analyze the preservation mode, temperature and humidity parameters and food type information set by the user to generate an initial control strategy;

[0029] Based on the initial control strategy, controlling the compressor and the fan to perform refrigeration operation;

[0030] Dynamically optimizing the initial control strategy and adjusting the refrigeration operation parameters of the compressor and the fan;

[0031] The display module is configured to: output the optimized initial control strategy;

[0032] The communication module is configured to upload the optimized control strategy, the refrigerator compartment data and the user operation record to the server, and receive the remote optimization instruction issued by the server to perform remote data synchronization.

[0033] In a feasible implementation, the main control module includes:

[0034] A temperature setting unit, used to receive a target temperature and humidity set by a user;

[0035] An adaptive learning unit, used for generating the initial control strategy according to historical operation data of the user;

[0036] An intelligent algorithm unit is used to optimize the refrigeration operation parameters in real time.

[0037] In a feasible implementation, the display module is a touch screen integrated on the outside of the refrigerator door, for displaying the current temperature and humidity, preservation mode and recommended storage parameters for ingredients, and receiving setting instructions input by the user.

[0038] In a feasible implementation, the communication module is connected to the server via a local area network router. The server performs deep learning based on the uploaded sensor data and user habits, generates optimization instructions and feeds them back to the main control module.

[0039] In a feasible implementation, the main control module further includes: an operation control unit;

[0040] The operation control unit is used to perform refrigeration control on the compressor and the fan;

[0041] The refrigeration control logic includes:

[0042] When the compartment temperature is higher than a set threshold, the main control module starts the compressor and the fan at the same time;

[0043] When the compartment temperature reaches a set threshold, the main control module turns off the compressor and maintains the fan running at a low speed to balance the humidity.

[0044] In a feasible implementation, the main control module further includes: a fresh-keeping mode setting unit;

[0045] The fresh-keeping mode setting unit is used to receive the fresh-keeping mode set by the user;

[0046] Among them, the preservation modes include fruit and vegetable mode, refrigeration mode, mother and baby mode, freezing mode, iced mode, ice temperature mode and slightly frozen mode. Each of the preservation modes has corresponding preset temperature and humidity parameters and the compressor operating frequency range.

[0047] From the above content, it can be seen that the present application provides a refrigerator intelligent fresh-keeping operation control method and a refrigerator, which can realize the adaptive learning function and can automatically adjust and control the temperature and humidity according to the user's usage habits; and detect the temperature and humidity changes in the compartment after the food load is placed in the compartment through the infrared sensor and the temperature and humidity sensor inside the compartment, and adjust the refrigerator refrigeration control strategy in time, which is more conducive to maintaining constant temperature and humidity, has a wider range of applications, and achieves the purpose of parallel intelligent preservation. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The accompanying drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the implementation of the present invention, and together with the specification are used to explain the principles of the embodiments of the present invention. Obviously, the accompanying drawings described below are only some embodiments of the implementation of the present invention, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0049] Figure 1 It is a flowchart of a refrigerator intelligent fresh-keeping operation control method shown in an embodiment of the present application;

[0050] Figure 2 It is a schematic diagram of the structure of a refrigerator shown in an embodiment of the present application. DETAILED DESCRIPTION

[0051] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the embodiments of the present invention will be more comprehensive and complete and fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, many specific details are provided to provide a full understanding of the implementation of the embodiments of the present invention.

[0052] As people's living standards improve, refrigerators are essential household appliances, and their fresh-keeping performance has become an important aspect of concern to consumers. Traditional refrigerators mostly use a fixed temperature control mode, which cannot be automatically adjusted according to the user's usage habits and food characteristics, resulting in poor fresh-keeping effects and serious food waste. The present invention aims to achieve intelligent control of refrigerator fresh-keeping operations through intelligent adaptive learning technology, improve fresh-keeping effects, and reduce food waste.

[0053] In order to solve the above problems, the first aspect of the embodiment of the present application provides a refrigerator intelligent fresh-keeping operation control method, referring to Figure 1 As shown, the following steps are included:

[0054] S100: Collect refrigerator compartment data in real time, where the refrigerator compartment data includes: temperature data, food surface temperature data, and humidity data.

[0055] Continuously monitor the temperature, humidity and surface temperature of the refrigerator. The frequency of data collection can be adjusted dynamically according to the stability of the environment. For example, when the temperature change exceeds the preset threshold, the sampling rate is increased to once per second to ensure the real-time data. Provide basic data for the control strategy, directly reflect the internal environment status of the refrigerator, and avoid control deviations caused by data lag.

[0056] S200: Analyze the preservation mode, temperature and humidity parameters and food type information set by the user to generate an initial control strategy; provide basic data for intelligent control to ensure the accuracy and real-time nature of control.

[0057] Combine the input fresh-keeping mode, target temperature and humidity range, and food type information. Combine with the pre-stored food preservation database, generate the initial control strategy through algorithm matching, and set the basic operating parameters of the compressor and fan. Convert user needs into executable equipment operation instructions to ensure that the control strategy is consistent with the user's goals, providing an initial basis for precise control.

[0058] S300: Based on the initial control strategy, control the compressor and the fan to perform cooling operation.

[0059] The compressor and fan are started according to the initial strategy, and the refrigerant circulation rate and cold air distribution are controlled by adjusting the compressor operating frequency and fan speed, so that the refrigerator compartment quickly reaches the temperature and humidity range set by the user. The initial stability of the refrigerator internal environment is achieved, providing basic conditions for subsequent dynamic optimization.

[0060] S400: Dynamically optimize the initial control strategy based on the refrigerator compartment data and adjust the refrigeration operation parameters of the compressor and fan.

[0061] Continuously compare the real-time collected data with the initial target value, predict the trend of environmental changes, and dynamically adjust the working parameters of the compressor and fan. For example, when the humidity is detected to be low, the fan running time is automatically increased to promote cold air circulation; if the surface temperature of the food is abnormal, the compressor power is fine-tuned to avoid local overcooling. Through the closed-loop feedback mechanism, the control strategy is corrected in real time, the control accuracy is improved, and the problems of high energy consumption and poor preservation effect caused by fixed control logic in traditional refrigerators are solved.

[0062] S500: Output the optimized initial control strategy and upload it to the server for remote data synchronization.

[0063] The optimized control strategy is converted into executable instructions for the device and uploaded to the cloud server. Users can view refrigerator operation data, receive freshness-keeping suggestions, and even adjust control parameters remotely through the mobile phone APP. Cloud data can also be used for system upgrades, such as optimizing algorithm models through big data analysis. It realizes two-way interaction between devices and users, and devices and servers, enhances user experience, and provides data support for subsequent algorithm iterations.

[0064] The embodiment of the present application avoids food spoilage caused by temperature and humidity fluctuations in traditional refrigerators through real-time monitoring and dynamic optimization of multiple parameters. Furthermore, the equipment parameters are dynamically adjusted to reduce unnecessary refrigeration cycles and improve energy efficiency. At the same time, remote data synchronization and mobile terminal control enhance the user experience and provide personalized preservation solutions.

[0065] In some embodiments of the present application, the step of generating an initial control strategy includes:

[0066] S210: Collect the user's historical settings of the preservation mode, temperature and humidity parameters, and food types, and establish a user habit database.

[0067] Continuously collect the fresh-keeping modes set by users in the past, the temperature and humidity parameters manually adjusted, and the types of food frequently stored, and store them in a local or cloud database by category. Build a personalized user usage model to provide a data basis for predicting user preferences and generating adaptive control strategies, solving the limitations of the single control logic of traditional refrigerators.

[0068] S220: Matching the target temperature and humidity range corresponding to the current food type in combination with the preset optimal food preservation parameter table.

[0069] When the user puts in new ingredients, the type of ingredients is identified through image recognition or RFID tag scanning. The system queries the built-in optimal preservation parameter table for ingredients and matches the temperature and humidity range corresponding to the current ingredients. For example, after identifying "strawberries", the optimal storage conditions for "berries" are automatically retrieved, such as: temperature 1°C ~ 3°C, humidity 90% ~ 95%. This step combines the scientific preservation standards of ingredients with the actual needs of users to improve the accuracy of preservation.

[0070] S230: Generate an initial cooling operation instruction based on the matching result.

[0071] According to the matched target temperature and humidity range, the temperature and humidity differences are calculated in combination with the actual current environment data of the refrigerator, and the initial operation instructions of the compressor and the fan are generated. For example, the compressor is set to run at high frequency for 10 minutes to quickly cool down, and the fan is set to run at medium speed to promote uniform distribution of cold air. This ensures that the refrigerator responds quickly to food storage needs, shortens the time to reach the target environment, and reduces energy waste caused by slow adjustment.

[0072] This embodiment solves the problem that traditional refrigerators require users to manually set parameters, but most users lack professional knowledge. By automatically identifying ingredients and matching parameters, the threshold for use is lowered. Further dynamic adjustment strategies are made to improve the preservation effect. In addition, user behavior is predicted through historical data, and the operating status of the refrigerator is adjusted in advance to avoid a surge in energy consumption caused by temporary high-load operation.

[0073] In some embodiments of the present application, the step of dynamically optimizing the initial control strategy includes:

[0074] S410: When the real-time humidity is lower than the target humidity range, the fan speed is increased to improve the humidity uniformity of the room.

[0075] Specifically, when the humidity sensor monitors the humidity in the compartment in real time, when it detects that the humidity value is lower than the target range, the system sends a speed adjustment instruction to the fan. The fan speed gradually increases, and the specific increment is dynamically calculated based on the humidity difference. For example, for every 1% below the target humidity, the speed increases by 5% until the humidity is restored or the maximum speed limit of the fan is reached. By increasing the air flow rate, the moisture in the compartment is evenly distributed, avoiding local drying and dehydration of food. At the same time, the circulation of wet and cold air near the evaporator is accelerated to improve the overall humidity regulation efficiency.

[0076] S420: When the real-time temperature is higher than the target temperature range, extend the compressor operation time to reduce the temperature.

[0077] Specifically, the temperature sensor monitors the compartment temperature. When the temperature exceeds the target upper limit, the system extends the compressor operation cycle. For example, the original default compressor stops for 10 minutes every 20 minutes of operation, and now it is adjusted to stop for 5 minutes after 30 minutes of operation. If the temperature continues to be high, the operation time is further increased or the compressor frequency is increased. By increasing the refrigerant circulation volume, the heat absorption per unit time is increased, and the compartment temperature is quickly reduced. Avoid food spoilage due to high temperature environment, and reduce energy consumption fluctuations caused by frequent start and stop of compressors.

[0078] S430: When an abnormal surface temperature of food is detected, the refrigeration system is triggered to perform emergency cooling.

[0079] Specifically, if the local temperature is detected to be significantly higher than the average temperature of the compartment, the compressor will immediately switch to the maximum operating frequency, and the fan will simultaneously increase the speed to the maximum gear. Emergency cooling will continue until the surface temperature of the food drops below the safety threshold. This prevents the quality of the food from deteriorating due to local overheating, which is especially suitable for highly sensitive food. Through the rapid response mechanism, the potential risk of freshness preservation is minimized.

[0080] This application optimizes the airflow path and improves humidity uniformity by dynamically adjusting the fan speed. The traditional fixed compressor start-stop logic is difficult to cope with sudden temperature rise. Extending the running time or increasing the frequency can quickly compensate for the cooling capacity and shorten the temperature recovery time. Generally, the opening and closing of the door or the placement of the food may cause abnormal local temperature zones, and targeted protection is provided through the emergency cooling mechanism.

[0081] In some embodiments of the present application, the steps of performing remote data synchronization include:

[0082] Upload refrigerator compartment data and user operation records to the server, and receive remote optimization instructions issued by the server.

[0083] In the implementation of remote data synchronization, two-way communication between the refrigerator and the server can be achieved.

[0084] The built-in temperature sensor, humidity sensor and user operation log system of the refrigerator collect room environment data and user operation records in real time. Transmit to the server via Wi-Fi or Ethernet. The upload frequency is dynamically adjusted according to the data type, and the operation records are uploaded in real time. The server analyzes the refrigerator operation efficiency, user habits and food preservation status based on the uploaded data. The generated optimization instructions may include: control parameter adjustment, strategy library update and fault diagnosis instructions, etc.

[0085] This embodiment uses the refrigerator as an edge device to collect raw data, and the server as a central node to process data and generate policies, which solves the problem that the traditional refrigerator control logic is rigid and difficult to adapt to new ingredients or user changes. The server continuously updates the policy library to solve the local storage and computing resource limitations.

[0086] A second aspect of the present application provides a refrigerator, referring to Figure 2 As shown, the refrigerator includes a main control module, a compressor, a fan, a display module, a communication module and a sensor group. The sensor group includes a temperature sensor, an infrared sensor and a humidity sensor.

[0087] The main control module is electrically connected to the temperature sensor, the infrared sensor, the humidity sensor, the compressor, the fan, the display module and the communication module respectively.

[0088] The main control module is responsible for receiving data collected by sensors, analyzing the preservation mode, temperature and humidity parameters and food type information set by the user, generating the initial control strategy, and controlling the compressor and fan to perform refrigeration operation.

[0089] The compressor is electrically connected to the main control module and is started or stopped according to the control instruction of the main control module to realize the refrigeration cycle.

[0090] The fan is electrically connected to the main control module and adjusts its speed according to the control instructions of the main control module to promote air flow in the room and achieve uniform cooling.

[0091] The display module is electrically connected to the main control module, and is used for outputting the optimized initial control strategy and receiving the setting instructions input by the user.

[0092] The communication module is electrically connected to the main control module, and is used to upload refrigerator compartment data and user operation records to the server, and receive remote optimization instructions issued by the server.

[0093] The temperature sensor is installed on the inner wall of the refrigerator compartment to detect the compartment temperature and transmit the data to the main control module in real time.

[0094] The infrared sensor is installed on the top of the compartment, facing the storage compartment, to detect the surface temperature of the food and transmit the data to the main control module in real time.

[0095] The humidity sensor is installed on the side wall of the compartment to detect the humidity of the compartment and transmit the data to the main control module in real time.

[0096] Specifically, in combination with the aforementioned refrigerator intelligent fresh-keeping operation control method, the specific operation process of the refrigerator is as follows:

[0097] Real-time collection of refrigerator compartment data, the temperature sensor is installed on the inner wall of the refrigerator compartment to detect the compartment temperature in real time; the infrared sensor is installed on the top of the compartment, facing the storage compartment, to detect the surface temperature of the food; the humidity sensor is installed on the side wall of the compartment to detect the humidity of the compartment. Each sensor transmits data to the main control module in real time.

[0098] The main control module receives the preservation mode (such as refrigeration mode, freezing mode, etc.), target temperature and humidity parameters and food type information input by the user through the display module. The main control module matches the target temperature and humidity range corresponding to the current food type according to the preset optimal preservation parameter table of food. For example: for the fruit and vegetable mode, the target temperature range is 2°C to 8°C, and the target humidity range is 85%RH to 95%RH. The main control module generates the initial refrigeration operation instructions based on the matching results, including parameters such as compressor start frequency and fan speed.

[0099] The main control module sends control instructions to the compressor and fan. The compressor starts according to the instructions and begins the refrigeration cycle; the fan adjusts its speed according to the instructions to promote air flow in the room and achieve uniform cooling.

[0100] The main control module monitors the refrigerator compartment data in real time. When the real-time humidity is lower than the target humidity range, the fan speed is increased to improve the uniformity of compartment humidity. When the real-time temperature is higher than the target temperature range, the compressor running time is extended to lower the temperature. When the infrared sensor detects abnormal surface temperature of the food (such as excessively high local temperature), the refrigeration system is triggered for emergency cooling, increasing the compressor operating frequency and fan speed.

[0101] The main control module sends the optimized control strategy to the display module, and the user can view the current control strategy and refrigerator operation status through the display module. The refrigerator compartment data and user operation records are uploaded to the server through the communication module. The server performs deep learning based on the uploaded data, generates optimization instructions and feeds them back to the main control module.

[0102] This embodiment realizes precise control and remote management of the refrigerator operation status through reasonable module division and connection relationship design. The modules work together to significantly improve the preservation effect, reduce energy consumption, and provide users with a more convenient and intelligent refrigerator experience. Through intelligent adaptive learning technology, combined with multi-sensor collaborative control and dynamic optimization strategies, precise control and remote management of the refrigerator operation status are realized. Compared with traditional refrigerators, the present invention can significantly improve the preservation effect, reduce energy consumption, and provide users with a more convenient and intelligent refrigerator experience.

[0103] In some embodiments of the present application, the main control module includes: a temperature setting unit, an adaptive learning unit and an intelligent algorithm unit.

[0104] Among them, the temperature setting unit is used to receive the target temperature and humidity set by the user, and send the set values ​​to the adaptive learning unit and the intelligent algorithm unit. The adaptive learning unit is used to generate an initial control strategy based on the user's historical operation data. The adaptive learning unit uses a machine learning algorithm to analyze and learn the user's historical operation data to generate an initial control strategy that conforms to the user's habits. The intelligent algorithm unit is used to optimize the refrigeration operation parameters in real time. The intelligent algorithm unit uses an optimization algorithm to dynamically optimize the initial control strategy based on the real-time collected refrigerator compartment data to generate more accurate control instructions.

[0105] This embodiment realizes accurate control and optimization of the refrigerator operation status through the internal structure design of the main control module. The introduction of the adaptive learning unit and the intelligent algorithm unit enables the refrigerator to understand user needs more accurately, improve the preservation effect, and reduce energy consumption.

[0106] In some embodiments of the present application, the display module is a touch screen integrated on the outside of the refrigerator door. The display module displays the current temperature, humidity, preservation mode and other information of the refrigerator compartment in real time, making it convenient for users to understand the operating status of the refrigerator.

[0107] The display module queries the preset optimal food preservation parameter table according to the current food type, displays the recommended food storage parameters (such as target temperature and humidity range, etc.), and provides storage suggestions for users. Users can input setting instructions such as preservation mode, target temperature and humidity parameters, and food type through the touch screen. The setting instructions adopt a graphical interface design, which is easy and intuitive to operate.

[0108] This embodiment realizes intuitive display and convenient operation of the refrigerator operating status through the design of the touch screen display module. Compared with the traditional method, the present invention can significantly improve the user experience, allowing users to more intuitively understand the refrigerator operating status and perform convenient operations.

[0109] In some embodiments of the present application, the communication module is connected to the server via a LAN router. The server performs deep learning based on the uploaded sensor data and user habits, generates optimization instructions and feeds them back to the main control module.

[0110] Specifically, the communication module uploads refrigerator compartment data (such as temperature data, humidity data, infrared sensor data, etc.) and user operation records (such as fresh-keeping mode settings, temperature and humidity parameter settings, etc.) to the server. The uploaded data can be transmitted in an encrypted manner to ensure data security. The communication module receives the remote optimization instructions issued by the server and sends the instructions to the main control module. The remote optimization instructions can be in JSON format to facilitate parsing and execution by the main control module.

[0111] This embodiment realizes remote management and optimization of the refrigerator operation status by connecting the LAN router to the server. Compared with the traditional method, the present invention can make full use of the powerful computing power of the server to generate more accurate optimization instructions, improve the preservation effect, and provide users with a more convenient and intelligent refrigerator use experience.

[0112] In some embodiments of the present application, the main control module further includes: an operation control unit; the operation control unit is used to perform refrigeration control on the compressor and the fan, and the refrigeration control logic includes:

[0113] When the compartment temperature is higher than the set threshold: the main control module starts the compressor and the fan at the same time. After the compressor starts, the refrigeration cycle begins, and the fan adjusts the speed to promote air flow in the compartment to achieve uniform cooling.

[0114] When the compartment temperature reaches the set threshold: the main control module turns off the compressor and maintains the fan running at a low speed. After the compressor stops running, the compartment temperature gradually stabilizes; the fan running at a low speed can continue to promote air flow in the compartment and maintain humidity uniformity.

[0115] This embodiment realizes accurate control of the refrigerator operation state through reasonable refrigeration control logic design. Compared with the traditional method, the present invention can respond to the change of compartment temperature more quickly, improve the preservation effect, and avoid the increase of energy consumption caused by frequent startup of the compressor.

[0116] In some embodiments of the present application, the main control module further includes: a fresh-keeping mode setting unit; the fresh-keeping mode setting unit is used to receive the fresh-keeping mode set by the user.

[0117] The user can select a preset fresh-keeping mode through the display module, such as refrigeration mode, freezing mode, mother-infant mode, etc. Each fresh-keeping mode has corresponding preset temperature and humidity parameters and compressor operating frequency range. The fresh-keeping mode setting unit sends the fresh-keeping mode set by the user to the main control module, and the main control module adjusts the refrigerator operation state according to the received fresh-keeping mode setting value.

[0118] This embodiment realizes convenient control of the refrigerator operation state through the design of the fresh-keeping mode setting unit. Users can select a preset fresh-keeping mode according to actual needs, and the refrigerator automatically adjusts to the optimal operation state to improve the fresh-keeping effect and reduce energy consumption.

[0119] This application is based on intelligent adaptive learning technology, combined with multi-sensor collaborative control and dynamic optimization strategies, to achieve precise control and remote management of the refrigerator's operating status. By collecting historical user operation data, establishing a user habit database, and combining the preset optimal food preservation parameter table, an initial control strategy is generated; using temperature sensors, infrared sensors and humidity sensors, the refrigerator compartment environment and food status are sensed in real time; through dynamic optimization strategies, the operating parameters of the compressor and fan are adjusted according to the real-time collected refrigerator compartment data; finally, through the remote data synchronization function, remote management and optimization of the refrigerator's operating status are achieved.

[0120] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the disclosure herein. This application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

Claims

1. A refrigerator intelligent fresh-keeping operation control method, characterized in that: The following steps are involved: Collect refrigerator compartment data in real time, the refrigerator compartment data includes: temperature data, food surface temperature data and humidity data; Analyze the preservation mode, temperature and humidity parameters and food type information set by the user to generate an initial control strategy; Based on the initial control strategy, controlling the compressor and the fan to perform refrigeration operation; According to the refrigerator compartment data, dynamically optimize the initial control strategy and adjust the refrigeration operation parameters of the compressor and the fan; The optimized initial control strategy is output and uploaded to the server for remote data synchronization.

2. The refrigerator intelligent fresh-keeping operation control method according to claim 1, characterized in that: The step of generating an initial control strategy comprises: Collect the user's historical settings for fresh-keeping modes, temperature and humidity parameters, and food types to build a user habit database; Combine the preset optimal food preservation parameter table to match the target temperature and humidity range corresponding to the current food type; An initial cooling operation instruction is generated based on the matching result.

3. The refrigerator intelligent fresh-keeping operation control method according to claim 1, characterized in that: The step of dynamically optimizing the initial control strategy comprises: When the real-time humidity is lower than the target humidity range, the fan speed is increased to improve the humidity uniformity of the room; When the real-time temperature is higher than the target temperature range, extending the compressor operation time to reduce the temperature; When abnormal surface temperature of food is detected, the refrigeration system is triggered for emergency cooling.

4. The refrigerator intelligent fresh-keeping operation control method according to claim 1, characterized in that: The steps of performing remote data synchronization include: The refrigerator compartment data and user operation records are uploaded to the server, and remote optimization instructions issued by the server are received.

5. A refrigerator, characterized in that: include: A main control module, a compressor, a fan, a display module, a communication module and a sensor group, wherein the sensor group includes: a temperature sensor, an infrared sensor and a humidity sensor; The main control module is electrically connected to the temperature sensor, infrared sensor, humidity sensor, compressor, fan, display module and communication module respectively; The temperature sensor is installed on the inner wall of the refrigerator compartment to detect the compartment temperature; The infrared sensor is installed on the top of the compartment, facing the storage compartment, and is used to detect the surface temperature of the food; The humidity sensor is installed on the side wall of the compartment to detect the humidity of the compartment; The main control module is integrated with an adaptive learning module and an intelligent algorithm module; The main control module is configured as follows: Analyze the preservation mode, temperature and humidity parameters and food type information set by the user to generate an initial control strategy; Based on the initial control strategy, controlling the compressor and the fan to perform refrigeration operation; Dynamically optimizing the initial control strategy and adjusting the refrigeration operation parameters of the compressor and the fan; The display module is configured to: output the optimized initial control strategy; The communication module is configured to upload the optimized control strategy, the refrigerator compartment data and the user operation record to the server, and receive the remote optimization instruction issued by the server to perform remote data synchronization.

6. The refrigerator according to claim 5, characterized in that: The main control module comprises: A temperature setting unit, used to receive a target temperature and humidity set by a user; An adaptive learning unit, used for generating the initial control strategy according to the user's historical operation data; An intelligent algorithm unit is used to optimize the refrigeration operation parameters in real time.

7. The refrigerator according to claim 5, characterized in that: The display module is a touch screen integrated on the outside of the refrigerator door, used to display the current temperature and humidity, fresh-keeping mode and recommended storage parameters for ingredients, and receive setting instructions input by the user.

8. The refrigerator according to claim 5, characterized in that: The communication module is connected to the server via a LAN router. The server performs deep learning based on the uploaded sensor data and user habits, generates optimization instructions and feeds them back to the main control module.

9. The refrigerator according to claim 5, characterized in that: The main control module also includes: an operation control unit; The operation control unit is used to perform refrigeration control on the compressor and the fan; The refrigeration control logic includes: When the compartment temperature is higher than a set threshold, the main control module starts the compressor and the fan at the same time; When the compartment temperature reaches a set threshold, the main control module turns off the compressor and maintains the fan running at a low speed to balance the humidity.

10. The refrigerator according to claim 5, characterized in that: The main control module also includes: a fresh-keeping mode setting unit; The fresh-keeping mode setting unit is used to receive the fresh-keeping mode set by the user; Among them, the preservation modes include fruit and vegetable mode, refrigeration mode, mother and baby mode, freezing mode, iced mode, ice temperature mode and slightly frozen mode. Each of the preservation modes has corresponding preset temperature and humidity parameters and the compressor operating frequency range.

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