Temperature control system for rechargeable food storage platforms

Abstract

This invention provides a temperature control system for a rechargeable food storage platform, belonging to the field of temperature control technology. The system includes: an acquisition module for collecting and acquiring basic parameter data of the food storage platform, including internal temperature data, ambient humidity parameters, power parameters of heating and cooling equipment, energy-related parameters of the platform, and historical data on the status of the platform's insulation cover; a control module for calculating energy balance based on the basic parameter data and selecting a corresponding control strategy; and a heating / cooling execution module for regulating the heating and cooling equipment according to the selected control strategy. This invention effectively solves the problems of inaccurate temperature control and uncontrolled energy consumption caused by frequent access and sudden environmental changes, achieving precise temperature control and efficient energy management in complex scenarios.

Description

Technical Field

[0001] This invention relates to the field of temperature control technology, and more specifically to a temperature control system for a rechargeable food storage platform. Background Technology

[0002] With the rapid growth in demand for mobile catering and self-service catering services, rechargeable food storage equipment has been widely used due to its portability and independent power supply. Existing technologies generally employ a dual-mode temperature control scheme combining a thermoelectric semiconductor module (TEC) with resistance heating elements, using a PID control algorithm to regulate the internal temperature of the enclosure. These systems typically rely on multiple temperature sensors to collect data and switch between heating and cooling modes based on preset thresholds to maintain a target temperature range. Regarding energy management, existing solutions often predict basic battery life by estimating a simple linear relationship between device power and battery capacity.

[0003] Traditional temperature control systems have significant drawbacks in practical applications: Traditional rechargeable catering temperature control systems mostly rely on a single internal temperature parameter for feedback control, which leads to insufficient temperature control accuracy and energy efficiency imbalance in complex usage scenarios. For example, frequent opening of the insulated lid to access food or switching between multiple environments can affect temperature control. At the same time, traditional control strategies lack collaborative analysis of the power parameters of heating / cooling equipment and the energy characteristics of the platform, making it difficult to quickly generate adaptive control commands in the event of sudden access or environmental changes. Summary of the Invention

[0004] This invention provides a temperature control system for a rechargeable food storage platform, which solves the problems of low temperature control accuracy and slow response speed caused by environmental disturbances and frequent operations in the prior art.

[0005] To achieve the above objectives, embodiments of the present invention provide a temperature control system for a rechargeable catering storage platform. The temperature control system includes: an acquisition module for collecting and acquiring basic parameter data of the catering storage platform, including internal temperature data, ambient humidity parameters, power parameters of heating and cooling equipment, energy-related parameters of the platform, and historical data on the status of the insulation cover of the catering storage platform; a control module for calculating energy balance based on the basic parameter data and selecting a corresponding control strategy; and a heating and cooling execution module for regulating the heating and cooling equipment according to the selected control strategy.

[0006] Optionally, the acquisition module includes multiple thermistor temperature sensors distributed on the catering storage platform to collect temperature data from various areas 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 median filtering technology to sort the data from the multiple temperature sensors according to their numerical values, selecting the median value as the preliminary processing result to remove abnormal data caused by sensor failure or sudden interference; based on the preliminary processing result, using moving average filtering technology to perform an arithmetic average of the data within a preset length of data window to obtain the final temperature data.

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

[0009] Optionally, the step of calculating energy balance using an energy balance algorithm based on the acquired internal temperature data and the power parameters of the heating and cooling equipment includes: using the product of the power parameters of the heating equipment and the operating time of the heating equipment as the input energy; calculating the energy lost through heat conduction using the heat conduction formula based on the surface area of ​​the food storage platform, the thermal conductivity coefficient, the temperature difference between the inside and outside of the platform, and the usage time; obtaining the output energy based on the calculated energy loss and the heat absorbed by the cooling equipment in the food storage space during operation; and calculating the energy balance based on the obtained output energy and the input energy.

[0010] Optionally, the step of selecting a corresponding preset control strategy based on the calculated energy balance includes: if the energy balance exceeds a first preset value and the temperature rise rate exceeds a preset rate, selecting a control strategy of reducing heating power or starting the cooling equipment; if the energy balance is lower than a second preset value and the temperature drop rate exceeds a preset rate, selecting to increase heating; if the energy balance is within the range of the first and second preset values, or the temperature change rate is less than a preset rate, selecting a control strategy of maintaining the current operating state of the equipment.

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

[0012] Optionally, the control module further includes a compensation coefficient generation unit, used to dynamically adjust the calculation parameters of the energy balance algorithm based on the historical data of the insulation cover's state.

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

[0014] Optionally, the generation of the dynamic compensation coefficient includes: establishing a mapping table of thermal insulation cover action-thermal disturbance relationship, and obtaining the heat loss benchmark value corresponding to the unit opening time under different seasonal modes; generating a frequency correction factor based on the ratio between the current thermal insulation cover opening frequency and the preset standard frequency, wherein the frequency correction factor increases with the increase of the thermal insulation cover opening frequency; generating a humidity compensation factor by combining the real-time environmental humidity parameter with the benchmark humidity difference under the corresponding seasonal mode, wherein the humidity compensation factor is adjusted as the humidity deviation increases; and coupling the heat loss benchmark value, the frequency correction factor, and the humidity compensation factor to generate the dynamic compensation coefficient acting on the energy dissipated by heat conduction.

[0015] The temperature control system for a rechargeable catering storage platform provided by this invention significantly enhances its anti-interference capability against frequent access operations and external temperature and humidity fluctuations through adaptive environment thermodynamic model reconstruction and real-time energy balance analysis, maintaining temperature field uniformity under complex operating conditions. Its innovative multi-source data fusion mechanism effectively improves the fault tolerance of sensor abnormal states, and combined with dynamic compensation strategies, it achieves precise hot and cold load distribution and simultaneously optimizes the collaborative efficiency of multiple temperature zones. At the same time, based on energy flow self-consistency intelligent control logic, it significantly reduces ineffective energy consumption and extends equipment battery life while ensuring core temperature control accuracy, making it particularly suitable for mobile catering service scenarios with high-frequency access and multiple environment switching. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in this invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0017] Figure 1 This is a structural diagram of the temperature control system provided in an embodiment of the present invention;

[0018] Figure 2 This is a flowchart of the energy balance algorithm provided in an embodiment of the present invention;

[0019] Figure 3This is a flowchart of the dynamic compensation mechanism provided in an embodiment of the present invention;

[0020] Figure 4 This is a flowchart of the operation of the control module provided in an embodiment of the present invention. Detailed Implementation

[0021] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0022] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application all comply with the relevant provisions of national laws and regulations. In the embodiments of this application, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0023] like Figures 1-4 As shown, this embodiment of the invention provides a temperature control system for a rechargeable food storage platform. The temperature control system includes: an acquisition module for collecting and acquiring basic parameter data of the food storage platform, including internal temperature data, ambient humidity parameters, power parameters of heating and cooling equipment, energy-related parameters of the platform, and historical data of the insulation cover status of the food storage platform; a control module for calculating energy balance based on the basic parameter data and selecting a corresponding control strategy; and a heating and cooling execution module for regulating the heating and cooling equipment according to the selected control strategy.

[0024] The temperature control system provided by this invention has an acquisition module that comprehensively collects historical data on the internal temperature, ambient humidity, power of heating and cooling equipment, platform energy-related parameters, and the status of the insulation cover of the food storage platform, providing a rich and necessary data foundation for the operation of the entire system. The control module, based on the data collected by the acquisition module, uses an energy balance algorithm to accurately calculate the energy balance and selects a corresponding control strategy from preset strategies according to the calculation results, thereby determining the operating mode of the heating and cooling equipment. The heating and cooling execution module performs specific control operations on the heating and cooling equipment according to the control strategy selected by the control module, thus achieving effective temperature control of the food storage platform. All modules cooperate to jointly construct a complete and efficient temperature control system.

[0025] The rechargeable food storage platform of this invention adopts a multi-layer composite structure design, with the main body consisting of a food-grade stainless steel inner liner, a polyurethane vacuum insulation layer, and an impact-resistant outer shell. The platform is equipped with multiple high-precision temperature sensor arrays, distributed in the top distributed air duct, the bottom condensation area, and the core storage compartment. Heating equipment (PTC ceramic discs) and cooling equipment (semiconductor cooling modules) are integrated into the side wall interlayer, achieving efficient heat exchange through an independent air duct system. It also features an insulated cover for heat preservation, allowing food to be stored and retrieved by opening the cover. Furthermore, it includes a switch detection module capable of detecting the opening frequency of the insulated cover and acquiring switch data, such as the duration of each opening.

[0026] Preferably, the control module is further configured to preprocess the received temperature data to ensure data accuracy. The preprocessing of the temperature data includes: using median filtering technology to sort the data from the multiple temperature sensors according to their numerical values, selecting the median value as the preliminary processing result to remove abnormal data caused by sensor failure or sudden interference; based on the preliminary processing result, using moving average filtering technology to perform an arithmetic average of the data within a preset length of data window to obtain the final temperature data.

[0027] In a preferred embodiment of the invention, the preprocessing process of temperature data by the control module is described. In this system, multiple temperature sensors are distributed throughout the food storage platform, and the collected temperature data is transmitted to the control module. The control module first uses median filtering to sort the received temperature sensor data by numerical value and selects the median value as the initial processing result. This step effectively eliminates abnormal data caused by sensor malfunctions, sudden external interference, etc., providing a relatively reliable data foundation for subsequent processing. Next, based on the preliminary processing result, the control module uses moving average filtering to perform an arithmetic average calculation on the data within a predefined data window, thereby obtaining the final temperature data. Through this processing, data fluctuations are smoothed, and data accuracy and stability are significantly improved, providing solid data support for subsequent energy expenditure calculations and control strategy selection, ensuring that the temperature control system can operate efficiently and stably based on more accurate temperature data.

[0028] Preferably, the control module is configured to: calculate energy balance using an energy balance algorithm based on the acquired internal temperature data and the power parameters of the heating and cooling devices; select a corresponding preset control strategy based on the calculated energy balance; and generate a corresponding control signal.

[0029] More preferably, the step of calculating energy balance using an energy balance algorithm based on the acquired internal temperature data and the power parameters of the heating and cooling equipment includes: using the product of the power parameters of the heating equipment and the operating time of the heating equipment as the input energy; calculating the energy lost through heat conduction using the heat conduction formula based on the surface area of ​​the food storage platform, the thermal conductivity coefficient, the temperature difference between the inside and outside of the platform, and the usage time; obtaining the output energy based on the calculated energy loss and the heat absorbed by the cooling equipment during operation within the food storage space; and calculating the energy balance based on the obtained output energy and the input energy. The energy lost through heat conduction can be expressed as:

[0030] (1)

[0031] in, This represents the energy lost through heat conduction. This indicates the surface area of ​​the food storage platform. Indicates the thermal conductivity coefficient. This indicates the temperature difference between the inside and outside of the platform. This indicates the usage time. Output energy can be expressed as:

[0032] (2)

[0033] in, Indicates the output energy. This indicates that the refrigeration equipment absorbs heat from the food storage space when it is working. The energy balance can be expressed as:

[0034] (3)

[0035] in, Indicates energy balance. This indicates the input energy.

[0036] In a preferred embodiment of the present invention, a method for calculating energy balance in a temperature control system is described in detail. This method is the core of the energy balance algorithm. First, the power parameters of the heating equipment are multiplied by the operating time to obtain the input energy. Next, based on the surface area of ​​the food storage platform, the thermal conductivity coefficient, the temperature difference between the inside and outside of the platform, and the usage time, the energy lost through heat conduction is calculated using the heat conduction formula. Then, combined with the heat absorbed by the refrigeration equipment in the food storage space during operation, the output energy is obtained. Finally, the input energy is subtracted from the output energy to calculate the energy balance, providing a crucial basis for the selection of subsequent control strategies.

[0037] Preferably, the step of selecting a corresponding preset control strategy based on the calculated energy balance includes: if the energy balance exceeds a first preset value and the temperature rise rate exceeds a preset rate, selecting a control strategy of reducing heating power or starting the cooling equipment; if the energy balance is lower than a second preset value and the temperature decrease rate exceeds a preset rate, selecting to increase heating; if the energy balance is within the range of the first and second preset values, or the temperature change rate is less than a preset rate, selecting a control strategy of maintaining the current operating state of the equipment.

[0038] In a preferred embodiment of the present invention, the temperature control system selects a control strategy based on energy balance and temperature change rate. When the calculated energy balance exceeds a first preset value and the temperature rise rate exceeds a preset rate, the system will choose to reduce the heating power or start the cooling equipment to suppress the temperature from rising too quickly. If the energy balance is lower than a second preset value and the temperature drop rate exceeds a preset rate, the system will choose to increase the heating power to avoid excessive temperature drop. When the energy balance is within the range of the first and second preset values, or the temperature change rate is less than the preset rate, the system will choose to maintain the current operating state of the equipment to ensure the temperature stability within the food storage platform.

[0039] like Figure 2 As shown, for example, suppose a catering storage platform has a heating device with a power of 1000 watts that has been working continuously for 3600 seconds. Its input energy is 1000 watts × 3600 seconds = 3,600,000 joules. The surface area of ​​the platform is 5 square meters, the thermal conductivity 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. According to formula (1), the energy lost through heat conduction is 5 square meters × 0.5 watts per meter Kelvin × 10 Kelvin × 3600 seconds = 90,000 joules. The cooling device absorbs 100,000 joules of heat. According to formula (2), the output energy is 90,000 joules + 100,000 joules = 190,000 joules. According to formula (3), the energy balance is 3,600,000 joules - 190,000 joules = 3,410,000 joules. This value exceeds the first preset value. Meanwhile, the temperature rise rate during this period was measured to be 0.5°C per minute, which also exceeded the preset rate. At this point, the temperature control system will choose to reduce the heating power or activate the cooling equipment to maintain a suitable temperature within the platform.

[0040] Preferably, the temperature control system further includes: a power management module for real-time monitoring of the battery status in the food storage platform and providing stable power to each module of the system; and a display module for displaying the operating status of the temperature control system.

[0041] In a preferred embodiment of the present invention, the temperature control system further includes: a power management module for real-time monitoring of the battery status in the food storage platform and providing stable power to each module of the system; and a display module for displaying the operating status of the temperature control system.

[0042] like Figure 3 As shown, preferably, the control module further includes a compensation coefficient generation unit, used to dynamically adjust the calculation parameters of the energy balance algorithm based on the historical data of the state of the heat insulation cover.

[0043] More preferably, the compensation coefficient generation unit is configured to: statistically analyze the opening frequency and single opening duration of the insulation cover within a preset time period; when the opening frequency of the insulation cover exceeds a first preset threshold, add a dynamic compensation coefficient positively correlated with the opening frequency of the insulation cover in the calculation of heat conduction energy loss; when the single opening duration exceeds a second preset threshold, trigger a power compensation mechanism after the insulation cover is closed to increase the output intensity of the heating or cooling equipment within a preset time period.

[0044] Further preferably, the generation of the dynamic compensation coefficient includes: establishing a mapping table of the action-thermal disturbance relationship of the insulation cover, and obtaining the heat loss benchmark value corresponding to the unit opening time under different seasonal modes; generating a frequency correction factor based on the ratio between the current opening frequency of the insulation cover and the preset standard frequency, wherein the frequency correction factor increases with the increase of the opening frequency of the insulation cover; generating a humidity compensation factor by combining the real-time environmental humidity parameter with the benchmark humidity difference under the corresponding seasonal mode, wherein the humidity compensation factor is adjusted as the humidity deviation increases; and coupling the heat loss benchmark value, the frequency correction factor, and the humidity compensation factor to generate the dynamic compensation coefficient acting on the energy lost through heat conduction. It can be represented as:

[0045] (4)

[0046] in, This represents the baseline value of heat loss corresponding to the unit operating time under different seasonal modes. This indicates the current frequency of opening of the insulation cover. Indicates the preset standard frequency. Indicates the ambient humidity parameter. Indicates the reference humidity. and A preset proportional coefficient indicating the correlation between material properties.

[0047] In a preferred embodiment of the present invention, a dynamic compensation mechanism based on multi-source data fusion is constructed: by real-time acquisition of the opening frequency of the insulation cover, the duration of a single opening, the ambient temperature and humidity, and seasonal mode parameters, the system first establishes a mapping table of the insulation cover action-thermal disturbance relationship, and generates an initial compensation amount based on the heat loss benchmark value per unit opening duration under different seasonal modes; then, combined with the deviation between the real-time opening frequency of the insulation cover and the preset standard frequency, a frequency correction factor is generated with a nonlinear increasing function, and a humidity compensation factor is constructed simultaneously based on the difference between the ambient humidity and the seasonal benchmark humidity; finally, the heat loss benchmark value, the frequency correction factor, and the humidity compensation factor are coupled and calculated in multiple dimensions to output a dynamic compensation coefficient that acts on the heat conduction energy loss of the energy balance algorithm, and triggers a short-term power enhancement mechanism linked to a single ultra-long opening event. This composite compensation system achieves adaptive matching between external disturbances (high-frequency access, extreme temperature and humidity) and the thermodynamic characteristics of the equipment (seasonal pattern differences, material hygroscopicity) through a collaborative mechanism of "baseline mapping - dynamic correction - multi-factor coupling - hierarchical response". This enables the system to complete the prediction of thermal disturbances and the calibration of compensation in a short time, suppressing temperature fluctuations caused by sudden access operations to a small range, while reducing ineffective compensation energy consumption, and significantly improving the temperature control reliability and energy utilization efficiency of mobile catering equipment in complex scenarios.

[0048] Taking a midday high-temperature delivery scenario in summer as an example, when delivery personnel frequently open the insulated cover of the food storage platform to store and retrieve food (e.g., each opening lasts about 8-10 seconds, accumulating 12 openings within 5 minutes), the system first captures the opening frequency and duration data through the insulated cover status sensor, combines the ambient humidity sensor detecting an external relative humidity of 85%, and combines the temperature to automatically determine the summer mode and call the corresponding heat loss benchmark value; the compensation coefficient generation unit generates a frequency correction factor (e.g., 1.4) based on the current opening frequency (12 times / 5 minutes) exceeding a preset threshold (e.g., 5 times / 5 minutes), and calculates a humidity compensation factor (e.g., 1.15) based on the humidity deviation (detected humidity 85% compared to the summer benchmark humidity 70%). The two are coupled with the summer benchmark value to generate a dynamic compensation coefficient of 1.61, which is then superimposed on the heat conduction energy loss; at the same time, for cases where the single opening duration exceeds the threshold (e.g., 7 seconds), a short-term power enhancement mechanism is triggered, increasing the cooling power to 130% of the normal value for 90 seconds after each insulated cover is closed. This collaborative compensation strategy keeps the internal temperature of the cabinet within the range of 5±0.6℃ during continuous storage and retrieval, reducing temperature fluctuation by 68% compared to traditional solutions. Furthermore, the additional energy consumption during the compensation phase accounts for only 9.3% of the overall cooling power consumption, which is significantly better than the 23% energy consumption of the fixed threshold compensation solution.

[0049] like Figure 4As shown, the operation flow of the control module in this system is as follows: Temperature data of each area, ambient temperature and humidity parameters, and the status information of the insulation cover are acquired in real time through the communication interface. First, the original temperature data is filtered by median to eliminate outliers, and then smoothed by moving average filtering to obtain an effective temperature dataset. Subsequently, the energy balance algorithm is called to calculate the input energy based on the power parameters of the heating / cooling equipment, and to calculate the energy lost through heat conduction by combining the platform's thermodynamic characteristics and real-time temperature difference. Simultaneously, the output energy of the cooling equipment is integrated to generate the current energy balance. The compensation coefficient generation unit operates simultaneously, generating compensation coefficients based on the opening frequency of the insulation cover, the duration of each opening, and ambient temperature and humidity data, using a preset thermal disturbance mapping table and dynamic correction rules to calibrate the energy lost through heat conduction in real time. Finally, the control strategy selector triggers tiered control commands (heating power adjustment, cooling start / stop, power enhancement mode) based on the compensated and corrected energy balance and the temperature change rate threshold, forming a closed-loop control chain of "data purification → energy modeling → disturbance compensation → strategy decision → execution feedback," achieving rapid response and precise temperature control under complex disturbances.

[0050] In summary, the temperature control system for a rechargeable catering storage platform provided by this invention constructs a multi-dimensional, interconnected intelligent temperature control system: First, through the deep integration of a dynamic compensation mechanism and an energy balance algorithm, the system's ability to suppress sudden thermal disturbances is significantly improved, effectively reducing temperature drift caused by frequent access and sudden environmental changes; Second, based on a thermodynamic model coupling the action characteristics of the insulation cover with multiple environmental parameters, precise matching between external disturbances and the thermal conduction characteristics of the equipment is achieved, enhancing the control adaptability under complex operating conditions; Simultaneously, the modular architecture design gives the system excellent scalability, and through the coordinated operation of abnormal data fault tolerance processing and hierarchical control strategies, continuous and stable operation is ensured under conditions of partial sensor failure or extreme temperature and humidity; Finally, the innovative dynamic energy consumption optimization mechanism significantly improves energy utilization efficiency while ensuring temperature control accuracy, providing technical support for the reliable operation of catering equipment around the clock.

[0051] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0052] Furthermore, the terms "system" and "network" are often used interchangeably in this paper. The term "and / or" in this paper merely describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Additionally, the character " / " in this paper generally indicates that the preceding and following related objects have an "or" relationship.

[0053] 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 based on A. However, it should also be understood that determining B based on A does not mean that B is determined solely based on A; B can also be determined based on A and / or other information.

[0054] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0055] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0056] In the embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the couplings or direct couplings or communication connections shown or discussed may be indirect couplings or communication connections through some interfaces, apparatuses, or units, or they may be electrical, mechanical, or other forms of connection.

[0057] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of the present invention, depending on actual needs.

[0058] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0059] From the above description of the embodiments, those skilled in the art will clearly understand that the present invention can be implemented in hardware, firmware, or a combination thereof. When implemented in software, the above-described functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of a computer program from one place to another. Storage media can be any available medium accessible to a computer. For example, but not limited to, computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code having the form of instructions or data structures and accessible to a computer. Furthermore, any connection can suitably be a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of the medium. As used in this invention, disk and disc include compressed optical discs (CDs), laser discs, optical discs, digital versatile discs (DVDs), floppy disks, and Blu-ray discs, wherein disks typically magnetically copy data, while discs optically copy data using lasers. The combinations described above should also be included within the scope of protection for computer-readable media.

[0060] In summary, the above description is merely a preferred embodiment of the technical solution of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A temperature control system for a rechargeable food storage platform, characterized in that, The temperature control system includes: The acquisition module is used to collect and acquire basic parameter data of the catering storage platform. The basic parameter data includes internal temperature data, environmental humidity parameters, power parameters of heating and cooling equipment, energy-related parameters of the platform, and historical data of the status of the insulation cover of the catering storage platform. The control module is used to calculate energy balance based on the basic parameter data and select the corresponding control strategy. The control module is configured to: calculate energy balance based on the acquired internal temperature data and the power parameters of the heating and cooling equipment through an energy balance algorithm; select the corresponding preset control strategy based on the calculated energy balance; and generate the corresponding control signal. The heating and cooling execution module is used to regulate the heating and cooling equipment according to the selected control strategy; The calculation of energy balance based on the acquired internal temperature data and the power parameters of the heating and cooling equipment, using an energy balance algorithm, includes: The product of the power parameters of the heating equipment and the operating time of the heating equipment is used as the input energy; Based on the surface area, thermal conductivity, temperature difference between the inside and outside of the food storage platform, and usage time, the energy lost through heat conduction is calculated using the heat conduction formula. Based on the calculated energy loss, combined with the heat absorbed by the refrigeration equipment in the food storage space during operation, the output energy is obtained; The energy balance is calculated based on the output energy and the input energy. Based on the calculated energy balance, select the corresponding preset control strategy, including: If the energy balance exceeds the first preset value and the temperature rise rate exceeds the preset rate, a control strategy of reducing heating power or starting the cooling equipment is selected. If the energy balance is lower than the second preset value and the temperature decrease rate exceeds the preset rate, then increase the heating rate. If the energy balance is within the range of the first preset value and the second preset value, or if the temperature change rate is less than the preset rate, a control strategy to maintain the current working state of the device is selected.

2. The temperature control system according to claim 1, characterized in that, The acquisition module includes multiple thermistor temperature sensors distributed on the catering storage platform to collect temperature data from various areas inside the platform.

3. The temperature control system according to claim 2, characterized in that, The control module is also used to preprocess the received temperature data to ensure data accuracy. The preprocessing of the temperature data includes: Median filtering is used to sort the data from the multiple temperature sensors according to their numerical values ​​and select the median value as the initial processing result to remove abnormal data caused by sensor failure or sudden interference. Based on the preliminary processing results, the data within a preset length of the data window is arithmetically averaged using the moving average filtering technique to obtain the final temperature data.

4. The temperature control system according to claim 1, characterized in that, The temperature control system also includes: The power management module is used to monitor the status of the batteries in the food storage platform in real time and provide stable power to all modules of the system. The display module is used to show the operating status of the temperature control system.

5. The temperature control system according to claim 1, characterized in that, The control module also includes a compensation coefficient generation unit, which is used to dynamically adjust the calculation parameters of the energy balance algorithm based on the historical data of the insulation cover status.

6. The temperature control system according to claim 5, characterized in that, The compensation coefficient generation unit is configured as follows: The frequency of opening of the insulation cover and the duration of each opening are statistically analyzed within a preset time period. When the frequency of opening of the insulation cover exceeds a first preset threshold, a dynamic compensation coefficient positively correlated with the frequency of opening of the insulation cover is added to the calculation of heat conduction energy loss. When the duration of a single opening exceeds the second preset threshold, a power compensation mechanism is triggered after the insulation cover is closed to increase the output intensity of the heating or cooling equipment within a preset time.

7. The temperature control system according to claim 6, characterized in that, The generation of the dynamic compensation coefficient includes: Establish a mapping table of thermal disturbances caused by the action of the insulation cover, and obtain the benchmark value of heat loss corresponding to the unit opening time under different seasonal modes. Based on the ratio between the current opening frequency of the insulation cover and the preset standard frequency, a frequency correction factor is generated, and the frequency correction factor increases with the increase of the opening frequency of the insulation cover. A humidity compensation factor is generated by combining the real-time environmental humidity parameters with the baseline humidity difference in the corresponding seasonal mode. The humidity compensation factor is adjusted as the humidity deviation increases. The heat loss reference value, the frequency correction factor, and the humidity compensation factor are coupled and calculated to generate the dynamic compensation coefficient that acts on the energy lost through heat conduction.

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