Temperature control system for rechargeable catering storage platform

Abstract

The invention provides a temperature control system for a rechargeable catering storage platform, and belongs to the technical field of temperature control. The system comprises an acquisition module used for acquiring and acquiring basic parameter data of a catering storage platform, the basic parameter data including internal temperature data, environment humidity parameters, power parameters of heating equipment and refrigeration equipment, energy related parameters of the platform and historical state data of a heat preservation cover body of the catering storage platform; the control module is used for calculating energy revenue and expenditure according to the basic parameter data and selecting a corresponding control strategy; and the heating and refrigerating execution module is used for regulating and controlling the heating equipment and the refrigerating equipment according to the selected control strategy. According to the invention, the problems of temperature control misalignment and out-of-control energy consumption caused by frequent access and sudden environment change are effectively solved, and accurate temperature control and efficient energy management in a complex scene are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of temperature control, and particularly to a temperature control system for a rechargeable food storage platform. Background Art

[0002] With the rapid growth of service demands such as mobile catering and self-service catering, rechargeable food storage devices have been widely used due to their portability and independent power supply characteristics. The existing technology generally adopts a dual-mode temperature control scheme combining a semiconductor thermoelectric module (TEC) and a resistance heating sheet, and adjusts the internal temperature of the box through a PID control algorithm. Such systems usually rely on multi-point temperature sensors to collect data, and switch the heating or cooling mode based on preset thresholds to maintain the target temperature range. In terms of energy management, existing solutions mostly predict the basic battery life by estimating the simple linear relationship between the device power and the battery capacity.

[0003] Traditional temperature control systems have significant defects in practical applications: traditional rechargeable food temperature control systems mostly rely on a single internal temperature parameter for feedback control, resulting in problems such as insufficient temperature control accuracy and energy efficiency imbalance in complex usage scenarios, such as frequently opening the insulation cover to access food and multi-environment switching affecting temperature control. At the same time, due to the lack of coordinated analysis of the power parameters of heating / cooling devices and the energy characteristics of the platform, traditional control strategies are difficult to quickly generate adaptive control instructions in case of sudden access or environmental changes. Summary of the Invention

[0004] The present invention provides a temperature control system for a rechargeable food storage platform to solve the problems of low temperature control accuracy and slow response speed caused by environmental disturbances and frequent operations in the existing technology.

[0005] To achieve the above object, an embodiment of the present invention provides a temperature control system for a rechargeable food storage platform, the temperature control system comprising: an acquisition module for collecting and obtaining the basic parameter data of the food storage platform, the basic parameter data including internal temperature data, environmental humidity parameters, power parameters of heating and cooling devices, energy-related parameters of the platform, and historical data of the state of the insulation cover of the food storage platform; a control module for calculating the energy income and expenditure according to the basic parameter data and selecting a corresponding control strategy; a heating and cooling execution module for regulating the heating and cooling devices according to the selected control strategy.

[0006] Optionally, the acquisition module includes a plurality of thermistor temperature sensors distributed on the food storage platform to collect temperature data of each area inside the platform.

[0007] Optionally, the control module is further configured to preprocess the received temperature data to ensure data accuracy. The preprocessing of the temperature data includes: using the median filtering technique to sort the data from multiple temperature sensors received according to the numerical value, and selecting the median value as the preliminary processing result to remove abnormal data caused by sensor failures or sudden interferences; based on the preliminary processing result, using the moving average filtering technique to perform arithmetic averaging on the data within a data window of a preset length to obtain the final temperature data.

[0008] Optionally, the control module is configured to: calculate the energy income and expenditure through an energy balance algorithm based on the acquired internal temperature data and the power parameters of the heating device and the refrigeration device; select a corresponding preset control strategy according to the calculated energy income and expenditure, and generate a corresponding control signal.

[0009] Optionally, the calculating the energy income and expenditure through an energy balance algorithm based on the acquired internal temperature data and the power parameters of the heating device and the refrigeration device includes: taking the product of the power parameter of the heating device and the operation time of the heating device as the input energy; calculating the energy dissipated through heat conduction according to the surface area, heat conduction coefficient, temperature difference inside and outside the platform, and usage time of the food storage platform through the heat conduction formula; based on the calculated dissipated energy, combining the heat absorbed by the refrigeration device when working in the food storage space, to obtain the output energy; calculating the energy income and expenditure according to the obtained output energy and the input energy.

[0010] Optionally, the selecting a corresponding preset control strategy according to the calculated energy income and expenditure includes: if the energy income and expenditure exceeds a first preset value and the temperature rising rate exceeds a preset rate, selecting a control strategy of reducing the heating power or starting the refrigeration device; if the energy income and expenditure is lower than a second preset value and the temperature decreasing rate exceeds a preset rate, selecting to increase the heating; if the energy income and expenditure is within the range of the first preset value and the second preset value, or the temperature change rate is less than the preset rate, selecting a control strategy of maintaining the current working state of the device.

[0011] Optionally, the temperature control system further includes: a power management module for real-time monitoring the state of the battery in the food storage platform and providing a stable power supply for each module of the system; a display module for displaying the operating state of the temperature control system.

[0012] Optionally, the control module further includes a compensation coefficient generation unit for dynamically adjusting the calculation parameters of the energy balance algorithm according to the historical data of the thermal insulation cover state.

[0013] Optionally, the compensation coefficient generating unit is configured to: count the opening frequency of the heat preservation cover body and the single opening duration within a preset time period; when the opening frequency of the heat preservation cover body exceeds a first preset threshold, add a dynamic compensation coefficient positively correlated with the opening frequency of the heat preservation cover body to the calculation of the heat conduction and dissipation energy; when the single opening duration exceeds a second preset threshold, trigger a power compensation mechanism after the heat preservation cover body is closed, and increase the output intensity of the heating or cooling device within a preset time.

[0014] Optionally, the generation of the dynamic compensation coefficient includes: establishing a mapping relationship table between the actions of the heat preservation cover body and thermal disturbances, and obtaining the heat loss reference value corresponding to the unit opening duration under different season modes; generating a frequency correction factor based on the proportional relationship between the current opening frequency of the heat preservation cover body and the preset standard frequency, and the frequency correction factor increases with the increase of the opening frequency of the heat preservation cover body; generating a humidity compensation factor by combining the real-time environmental humidity parameter and the humidity difference from the reference humidity under the corresponding season mode, and the humidity compensation factor is adjusted with the increase of the humidity deviation; coupling and calculating the heat loss reference value, the frequency correction factor and the humidity compensation factor to generate the dynamic compensation coefficient acting on the heat conduction and dissipation energy.

[0015] The temperature control system for a rechargeable food storage platform provided by the present invention significantly enhances the anti-interference ability against frequent access operations and external temperature and humidity fluctuations, and maintains the uniformity of the temperature field under complex working conditions through the reconstruction of the thermodynamic model adapting to the environment and the real-time energy income and expenditure analysis; its innovative multi-source data fusion mechanism effectively improves the fault tolerance of abnormal sensor states, realizes accurate cold and heat load distribution in combination with the dynamic compensation strategy, and synchronously optimizes the multi-temperature zone cooperation efficiency; at the same time, the intelligent control logic based on the self-consistency of the energy flow significantly reduces the ineffective energy consumption and prolongs the equipment battery life on the premise of ensuring the core temperature control accuracy, and is especially suitable for mobile food service scenarios with high-frequency access and multi-environment switching. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. In the drawings: Figure 1 is the structural diagram of the temperature control system provided by the embodiment of the present invention; Figure 2 is the flowchart of the energy balance algorithm provided by the embodiment of the present invention; Figure 3 is the flowchart of the dynamic compensation mechanism provided by the embodiment of the present invention; Figure 4It is the operation flowchart of the control module provided by the embodiment of the present invention. Detailed Implementation Manner

[0017] The following will describe in detail the detailed implementation manner of the embodiment of the present invention in conjunction with the accompanying drawings. It should be understood that the detailed implementation manner described herein is only used to illustrate and explain the embodiment of the present invention, and is not used to limit the embodiment of the present invention.

[0018] It should be noted that the acquisition, transmission, storage, use, processing, etc. of data in the technical solution of this application all comply with the relevant regulations of national laws and regulations. In the embodiment of this application, some existing industry solutions such as software, components, models, etc. may be mentioned. They should be regarded as exemplary, and their purpose is only to illustrate the feasibility in the implementation of the technical solution of this application, but it does not mean that the applicant has already or necessarily used this solution.

[0019] As Figures 1 - 4 shown, the embodiment of the present invention provides a temperature control system for a rechargeable food storage platform. The temperature control system includes: an acquisition module for collecting and obtaining the basic parameter data of the food storage platform, where the basic parameter data includes internal temperature data, ambient humidity parameters, power parameters of heating and cooling devices, energy-related parameters of the platform, and historical data of the state of the heat preservation cover of the food storage platform; a control module for calculating the energy income and expenditure according to the basic parameter data and selecting a corresponding control strategy; a heating and cooling execution module for regulating the heating and cooling devices according to the selected control strategy.

[0020] For the temperature control system provided by the present invention, the acquisition module provides a rich and necessary data basis for the operation of the entire system by comprehensively collecting the internal temperature of the food storage platform, ambient humidity, power of heating and cooling devices, energy-related parameters of the platform, and historical data of the state of the heat preservation cover. The control module then accurately calculates the energy income and expenditure situation based on the data collected by the acquisition module, and selects a corresponding control strategy from the preset strategies according to the calculation results to determine the working mode of the heating and cooling devices. The heating and cooling execution module performs specific regulation operations on the heating and cooling devices according to the control strategy selected by the control module, so as to effectively control the temperature of the food storage platform. Each module cooperates with each other to jointly build a complete and efficient temperature control system.

[0021] The rechargeable catering storage platform described in the present invention adopts a multi-layer composite structure design, and the main body is composed of a food-grade stainless steel liner, a polyurethane vacuum insulation layer and an impact-resistant outer shell. Multiple groups of high-precision temperature sensor arrays are arranged inside the platform, which are placed in the top distributed air duct, the bottom condensation area and the core area of the storage bin; the heating equipment (PTC ceramic sheet) and the refrigeration equipment (semiconductor refrigeration module) are integrated in the side wall interlayer, and efficient heat exchange is achieved through an independent air duct system. There is also a heat preservation cover for heat preservation, which can be opened to store and access food; there is also a switch detection module, which can detect the opening frequency of the heat preservation cover and obtain switch data, such as single opening duration data.

[0022] Preferably, the control module is also used to preprocess the received temperature data to ensure the accuracy of the data, and the preprocessing of the temperature data includes: using the median filtering technology to sort the received data of the multiple temperature sensors according to the numerical value, and selecting the middle value as the preliminary processing result to remove abnormal data caused by sensor failure or sudden interference; based on the preliminary processing result, using the sliding average filtering technology, the data in the data window of preset length is arithmetic averaged to obtain the final temperature data.

[0023] In the preferred embodiment of the present invention, the preprocessing process of the temperature data by the control module is introduced. In this system, multiple temperature sensors are distributed throughout the catering storage platform, and the collected temperature data will be transmitted to the control module. The control module first uses the median filtering technology to sort the received multiple temperature sensor data according to the numerical value, and selects the middle value as the preliminary processing result. This step can effectively eliminate abnormal data caused by factors such as sensor failure and external sudden interference, and provide a relatively reliable data basis for subsequent processing. Then, based on the results after preliminary processing, the control module uses the sliding average filtering technology to perform arithmetic averaging on the data within a data window of a set length, thereby obtaining the final temperature data. Through this processing, data fluctuations are smoothed, and data accuracy and stability are greatly improved, providing solid data support for subsequent energy balance calculations and control strategy selection, ensuring that the temperature control system can operate efficiently and stably based on more accurate temperature data.

[0024] Preferably, the control module is configured to: calculate energy income and expenditure through an energy balance algorithm based on the acquired internal temperature data and power parameters of the heating device and the refrigeration device; select a corresponding preset control strategy according to the calculated energy income and expenditure, and generate a corresponding control signal.

[0025] Further preferably, calculating the energy balance by an energy balance algorithm based on the obtained internal temperature data and the power parameters of the heating device and the refrigeration device includes: taking the product of the power parameter of the heating device and the operating time of the heating device as the input energy; calculating the energy dissipated by heat conduction according to the surface area, heat conduction coefficient, temperature difference inside and outside the platform, and usage time of the food storage platform through the heat conduction formula; obtaining the output energy based on the calculated dissipated energy and the heat absorbed by the refrigeration device when it is working in the food storage space; calculating the energy balance according to the obtained output energy and the input energy. The energy dissipated by heat conduction can be expressed as: (1) Wherein, represents the energy dissipated by heat conduction, represents the surface area of the food storage platform, represents the heat conduction coefficient, represents the temperature difference inside and outside the platform, represents the usage time. The output energy can be expressed as: (2) Wherein, represents the output energy, represents the heat absorbed by the refrigeration device when it is working in the food storage space. The energy balance can be expressed as: (3) Wherein, represents the energy balance, represents the input energy.

[0026] In a preferred embodiment of the present invention, the calculation method of the energy balance in the temperature control system is described in detail, and this method is the core of the energy balance algorithm. First, multiply the power parameter of the heating device by the operating time to obtain the input energy; then, calculate the energy dissipated by heat conduction through the heat conduction formula according to the surface area, heat conduction coefficient, temperature difference inside and outside the platform, and usage time of the food storage platform; then, combine the heat absorbed by the refrigeration device when it is working in the food storage space to obtain the output energy; finally, subtract the output energy from the input energy to calculate the energy balance, providing a key basis for the selection of subsequent control strategies.

[0027] Preferably, selecting a corresponding preset control strategy according to the calculated energy balance includes: if the energy balance exceeds a first preset value and the temperature rising rate exceeds a preset rate, selecting a control strategy of reducing the heating power or starting the refrigeration device; if the energy balance is lower than a second preset value and the temperature decreasing rate exceeds a preset rate, selecting to increase the heating; if the energy balance is within the range of the first preset value and the second preset value, or the temperature change rate is less than the preset rate, selecting a control strategy of maintaining the current working state of the device.

[0028] In a preferred embodiment of the present invention, the temperature control system selects a control strategy based on the energy balance and the temperature change rate. When the calculated energy balance exceeds the first preset value and the temperature rising rate exceeds the preset rate, the system will select a strategy of reducing the heating power or starting the refrigeration device to inhibit the rapid rise of temperature; if the energy balance is lower than the second preset value and the temperature decreasing rate exceeds the preset rate, the system will select to increase the heating intensity to avoid excessive temperature drop; and when the energy balance is within the range of the first preset value and the second preset value, or the temperature change rate is less than the preset rate, the system will select to maintain the current working state of the device to ensure the stability of the temperature in the food storage platform.

[0029] As Figure 2 shown, for example, assume that in a food storage platform, the heating device has a power of 1000 watts and works continuously for 3600 seconds. The input energy is 1000 watts × 3600 seconds = 3600000 joules. The surface area of the platform is 5 square meters, the heat transfer coefficient is 0.5 watts per meter kelvin, the temperature difference between the inside and outside of the platform is 10 kelvin, and the usage time is also 3600 seconds. Calculated by formula (1), the heat transfer dissipated energy is 5 square meters × 0.5 watts per meter kelvin × 10 kelvin × 3600 seconds = 90000 joules, and the heat absorbed by the refrigeration device during operation is 100000 joules. Then, calculated by formula (2), the output energy is 90000 joules + 100000 joules = 190000 joules. Calculated by formula (3), the energy balance is 3600000 joules - 190000 joules = 3410000 joules, and this value exceeds the first preset value. At the same time, during this period, the measured temperature rising rate is 0.5 °C per minute, which also exceeds the preset rate. At this time, the temperature control system will select a control strategy of reducing the heating power or starting the refrigeration device to maintain a suitable temperature inside the platform.

[0030] Preferably, the temperature control system further includes: a power management module for real-time monitoring of the status of the battery in the food storage platform and providing a stable power supply for each module of the system; a display module for displaying the operating status of the temperature control system.

[0031] In a preferred embodiment of the present invention, the temperature control system further includes: a power management module for real-time monitoring of the status of the battery in the food storage platform and providing stable power for each module of the system; a display module for displaying the operating status of the temperature control system.

[0032] As Figure 3 shown, preferably, the control module further includes a compensation coefficient generation unit for dynamically adjusting the calculation parameters of the energy balance algorithm according to the historical data of the heat preservation cover body state.

[0033] Further preferably, the compensation coefficient generation unit is configured to: count the opening frequency and single-opening duration of the heat preservation cover body within a preset time period. When the opening frequency of the heat preservation cover body exceeds a first preset threshold, a dynamic compensation coefficient positively correlated with the opening frequency of the heat preservation cover body is added to the calculation of the heat conduction loss energy; when the single-opening duration exceeds a second preset threshold, a power compensation mechanism is triggered after the heat preservation cover body is closed, and the output intensity of the heating or cooling device is increased within a preset time.

[0034] Further preferably, the generation of the dynamic compensation coefficient includes: establishing a mapping relationship table between the actions of the heat preservation cover body and heat disturbances, and obtaining the heat loss reference value corresponding to the unit opening duration under different season modes; generating a frequency correction factor based on the proportional relationship between the current opening frequency of the heat preservation cover body and the preset standard frequency, and the frequency correction factor increases with the increase of the opening frequency of the heat preservation cover body; generating a humidity compensation factor by combining the real-time environmental humidity parameter and the difference between the reference humidity under the corresponding season mode, and the humidity compensation factor is adjusted with the increase of the humidity deviation; coupling and calculating the heat loss reference value, the frequency correction factor and the humidity compensation factor to generate the dynamic compensation coefficient acting on the heat conduction loss energy. The dynamic compensation coefficient can be expressed as: (4) Wherein, represents the heat loss reference value corresponding to the unit opening duration under different season modes, represents the current opening frequency of the heat preservation cover body, represents the preset standard frequency, represents the environmental humidity parameter, represents the reference humidity, and represents a preset proportional coefficient related to the material characteristics.

[0035] In a preferred embodiment of the present invention, a dynamic compensation mechanism based on multi-source data fusion is constructed: by collecting the opening frequency of the thermal insulation cover body, the single opening duration, the ambient temperature and humidity, and the season mode parameters in real time, the system first establishes a mapping relationship table between the actions of the thermal insulation cover body and thermal disturbances, and generates an initial compensation amount according to the heat loss benchmark value per unit opening duration under different season modes; then, in combination with the deviation between the real-time opening frequency of the thermal insulation cover body and the preset standard frequency, a frequency correction factor is generated by a non-linear increasing function, and a humidity compensation factor is constructed according to the difference between the ambient humidity and the season benchmark humidity; finally, the heat loss benchmark value, the frequency correction factor, and the humidity compensation factor are subjected to multi-dimensional coupling calculation, and a dynamic compensation coefficient for the heat conduction and dissipation energy acting on the energy balance algorithm is output, and a short-term power strengthening mechanism linked to a single ultra-long opening event is triggered. Through the collaborative mechanism of "benchmark mapping - dynamic correction - multi-factor coupling - hierarchical response", the composite compensation system realizes the adaptive matching of external disturbances (high-frequency access, extreme temperature and humidity) and the thermodynamic characteristics of the equipment (season mode differences, material hygroscopicity), enables the system to complete the pre-judgment of thermal disturbances and the calibration of compensation amounts within a short time, suppresses the temperature fluctuations caused by sudden access operations within a small range, reduces the ineffective compensation energy consumption at the same time, and significantly improves the temperature control reliability and energy utilization efficiency of mobile catering equipment in complex scenarios.

[0036] Taking the high-temperature delivery scenario at noon in summer as an example, when the delivery person frequently opens the thermal insulation cover of the food storage platform to pick up and deliver meals (for example, the single opening duration is about 8-10 seconds, and the cumulative opening is 12 times within 5 minutes), the system first captures the opening frequency and duration data through the thermal insulation cover body state sensor, combines the external relative humidity of 85% detected by the ambient humidity sensor, and combines the air temperature, and automatically determines it as the summer mode and calls the corresponding heat loss benchmark value; based on the fact that the current opening frequency (12 times / 5 minutes) exceeds the preset threshold (for example, 5 times / 5 minutes), the compensation coefficient generation unit generates a frequency correction factor (for example, 1.4), and at the same time calculates the humidity compensation factor (for example, 1.15) according to the humidity deviation (the detected humidity of 85% compared with the summer benchmark humidity of 70%), and performs a coupling calculation with the summer benchmark value to generate a dynamic compensation coefficient of 1.61 and superimpose it on the heat conduction and dissipation energy; at the same time, for the case where the single opening duration exceeds the threshold (for example, 7 seconds), the short-term power strengthening mechanism is triggered, and the refrigeration power is increased to 130% of the normal value and maintained for 90 seconds after each thermal insulation cover body is closed. This collaborative compensation strategy keeps the temperature inside the box within the range of 5±0.6°C during continuous access, reducing the temperature fluctuation amplitude by 68% compared with the traditional solution, and the additional energy consumption during the compensation stage only accounts for 9.3% of the overall refrigeration power consumption, which is significantly better than the 23% energy consumption ratio of the fixed threshold compensation solution.

[0037] Such as Figure 4As shown in the figure, the operation process of the control module in this system is as follows: real-time obtain the temperature data of each area, the environmental temperature and humidity parameters, and the status information of the heat preservation cover body through the communication interface. First, perform median filtering on the original temperature data to eliminate outliers, and then perform smoothing processing through moving average filtering to obtain an effective temperature data set; Subsequently, call the energy balance algorithm, calculate the input energy based on the power parameters of the heating / cooling equipment, combine the thermodynamic characteristic parameters of the platform and the real-time temperature difference to calculate the heat conduction loss energy, and synchronously integrate the output energy of the cooling equipment to generate the current energy income and expenditure status; The compensation coefficient generation unit operates simultaneously. Based on the opening frequency of the heat preservation cover body, the single opening duration, and the environmental temperature and humidity data, generate a compensation coefficient through a preset heat disturbance mapping table and dynamic correction rules to calibrate the heat conduction loss energy in real time; Finally, the control strategy selector triggers hierarchical control instructions (heating power adjustment, cooling start / stop, power enhancement mode) based on the compensated and corrected energy income and expenditure value and the temperature change rate threshold, forming a full closed-loop control chain of "data purification → energy modeling → disturbance compensation → strategy decision-making → execution feedback" to achieve fast response and precise temperature control under complex disturbances.

[0038] In summary, a temperature control system for a rechargeable food storage platform provided by the present invention constructs a multi-dimensional and linked intelligent temperature control system: First, through the deep integration of the dynamic compensation mechanism and the energy balance algorithm, significantly improve the system's ability to suppress sudden thermal disturbances, and effectively reduce the temperature drift caused by frequent access and environmental mutations; Secondly, based on the thermodynamic model coupled with the action characteristics of the heat preservation cover body and multi-environment parameters, achieve precise matching of external disturbances and equipment heat conduction characteristics, and enhance the control adaptability under complex working conditions; At the same time, the modular architecture design endows the system with excellent scalability. Through the coordinated operation of abnormal data fault tolerance processing and hierarchical control strategies, ensure continuous and stable operation under local sensor failure or extreme temperature and humidity conditions; Finally, the innovative dynamic energy consumption optimization mechanism significantly improves the energy utilization efficiency while ensuring temperature control accuracy, providing technical support for the all-weather reliable operation of food equipment.

[0039] It should be understood that in various embodiments of the present invention, the magnitudes of the sequence numbers of the above processes do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0040] In addition, the terms "system" and "network" are often used interchangeably in this article. The term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after.

[0041] It should be understood that in the embodiments of the present invention, "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information.

[0042] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the composition and steps of the examples have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0043] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be described herein again.

[0044] In several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual coupling, direct coupling, or communication connection can be an indirect coupling or communication connection through some interfaces, devices, or units, and can also be in the form of electrical, mechanical, or other connections.

[0045] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiments of the present invention.

[0046] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0047] Through the description of the above embodiments, those skilled in the art can clearly understand that the present invention can be implemented by hardware, or by firmware, or by a combination thereof. When implemented in software, the above functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. The computer-readable medium includes computer storage media and communication media, where the communication media includes any medium that facilitates the transfer of a computer program from one place to another. The storage media can be any available medium that can be accessed by a computer. By way of example but not limitation: the computer-readable medium can include RAM, ROM, EEPROM, CD-ROM or other optical disc storage, magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer. In addition, any connection can suitably be a computer-readable medium. For example, if the software is transmitted using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL) or wireless technologies such as infrared, radio and microwave from a website, server or other remote source, then the coaxial cable, fiber optic cable, twisted pair, DSL or wireless technologies such as infrared, wireless and microwave are included in the definition of the medium. As used in the present invention, disk and disc include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc, where disks generally reproduce data magnetically, while discs reproduce data optically with a laser. The above combinations should also be included within the scope of protection of the computer-readable medium.

[0048] In summary, the above description is only a preferred embodiment of the technical solution of the present invention and is not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A temperature control system for a rechargeable food storage platform, characterized in that, The temperature control system includes: An acquisition module, configured to collect and obtain the basic parameter data of the food storage platform, where the basic parameter data includes internal temperature data, environmental humidity parameters, power parameters of heating and refrigeration devices, energy-related parameters of the platform, and historical data of the state of the heat preservation cover of the food storage platform; A control module, configured to calculate the energy balance based on the basic parameter data and select a corresponding control strategy; A heating and refrigeration execution module, configured to regulate the heating and refrigeration devices according to the selected control strategy.

2. The temperature control system according to claim 1, characterized in that, The acquisition module includes a plurality of thermistor temperature sensors distributed on the food storage platform to collect temperature data of each area inside the platform.

3. The temperature control system according to claim 2, wherein The control module is further configured to preprocess the received temperature data to ensure data accuracy. The preprocessing of the temperature data includes: Using the median filtering technique, sorting the data of the plurality of received temperature sensors according to the numerical size, and selecting the median value as the preliminary processing result to remove abnormal data caused by sensor failures or sudden interferences; Based on the preliminary processing result, using the moving average filtering technique, performing arithmetic averaging on the data within a preset-length data window to obtain the final temperature data.

4. The temperature control system according to claim 1, characterized in that, The control module is configured as: Calculating the energy balance through an energy balance algorithm based on the acquired internal temperature data and the power parameters of the heating and refrigeration devices; Selecting a corresponding preset control strategy according to the calculated energy balance and generating a corresponding control signal.

5. The temperature control system according to claim 4, characterized in that, The calculating the energy balance through an energy balance algorithm based on the acquired internal temperature data and the power parameters of the heating and refrigeration devices includes: Taking the product of the power parameter of the heating device and the operating time of the heating device as the input energy; Calculating the energy dissipated through heat conduction according to the surface area, heat conduction coefficient, temperature difference inside and outside the platform, and usage time of the food storage platform through the heat conduction formula; Based on the calculated dissipated energy, combining the heat absorbed by the refrigeration device when working in the food storage space, to obtain the output energy; Calculating the obtained energy balance according to the output energy and the input energy.

6. The temperature control system according to claim 4, wherein, The selecting a corresponding preset control strategy according to the calculated energy balance includes: If the energy balance exceeds a first preset value and the temperature rising rate exceeds a preset rate, selecting a control strategy of reducing the heating power or starting the refrigeration device; If the energy balance is lower than a second preset value and the temperature decreasing rate exceeds a preset rate, selecting to increase the heating; If the energy balance is within the range of the first preset value and the second preset value, or the temperature change rate is less than the preset rate, selecting a control strategy of maintaining the current working state of the device.

7. The temperature control system according to claim 4, characterized in that The temperature control system further includes: A power management module, configured to monitor the state of the battery in the food storage platform in real time and provide a stable power supply for each module of the system; A display module, configured to display the operating state of the temperature control system.

8. The temperature control system according to claim 4, characterized in that, The control module further includes a compensation coefficient generation unit, configured to dynamically adjust the calculation parameters of the energy balance algorithm according to the historical data of the state of the heat preservation cover.

9. The temperature control system according to claim 8, characterized in that, The compensation coefficient generation unit is configured as: Statistically calculate the opening frequency and single - opening duration of the heat - preservation cover within a preset time period. When the opening frequency of the heat - preservation cover exceeds the first preset threshold, a dynamic compensation coefficient that is positively correlated with the opening frequency of the heat - preservation cover is added to the calculation of the energy dissipated by heat conduction; When the single - opening duration exceeds the second preset threshold, a power compensation mechanism is triggered after the heat - preservation cover is closed, and the output intensity of the heating or cooling equipment is increased within a preset time.

10. The temperature control system according to claim 8, characterized in that, The generation of the dynamic compensation coefficient includes: Establish a mapping relationship table between the actions of the heat - preservation cover and heat disturbances, and obtain the heat - loss reference values corresponding to the unit opening duration under different seasonal modes; Generate a frequency correction factor based on the proportional relationship between the current opening frequency of the heat - preservation cover and the preset standard frequency. The frequency correction factor increases as the opening frequency of the heat - preservation cover increases; Generate a humidity compensation factor by combining the real - time environmental humidity parameter and the humidity difference from the reference humidity under the corresponding seasonal mode. The humidity compensation factor is adjusted as the humidity deviation increases; Couple - calculate the heat - loss reference value, the frequency correction factor, and the humidity compensation factor to generate the dynamic compensation coefficient acting on the energy dissipated by heat conduction.

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