Food material heat preservation method and system for catering truck

Abstract

The invention discloses a food material heat preservation method and system of a catering truck, and relates to the field of temperature control. The method is applied to a control unit, and comprises the following steps: acquiring in-cabin temperatures uploaded by a plurality of temperature sensors in a heat preservation cabin of the dining car; the temperature field gradient norm in the heat preservation cabin of the dining car is calculated according to the temperatures in the cabin of the multiple temperature sensors, and the temperature field gradient norm represents the uniformity of temperature distribution in the heat preservation cabin of the dining car; according to the preset target temperature of the heat preservation cabin of the dining car, the temperature field offset in the heat preservation cabin of the dining car is calculated, and the temperature field offset represents the deviation degree of the overall temperature in the heat preservation cabin of the dining car; based on the temperature field gradient norm and the temperature field offset, the target temperature control strength and the target temperature control speed of the dining car heat preservation cabin are determined; and adjusting the temperature control power and the internal circulation power of the temperature control module according to the target temperature control intensity and the target temperature control speed. Therefore, the problem that the heat preservation effect of the heat preservation cabin of the catering truck is poor due to the fact that the stacking state of the food materials is changed is solved.

Description

Technical Field

[0001] This application relates to the technical field of temperature control, specifically to a method and system for keeping food warm in a catering vehicle. Background Technology

[0002] Food carts, as a type of mobile catering facility, are widely used in scenic spots, parks and other open-air locations, greatly solving the dining needs of outdoor visitors.

[0003] Currently, to ensure the taste and safety of food during sales, food storage facilities typically include a food insulation chamber. This chamber is equipped with temperature sensors, a temperature control module, and a control unit, forming a basic constant temperature control system. The control unit receives feedback signals from the temperature sensors, compares them with a preset target temperature range, and then controls the temperature control module to maintain a stable temperature within the chamber.

[0004] However, unlike the kitchen equipment in a fixed restaurant, catering carts have the function of dynamic movement. During the movement, due to road bumps, the stacking state of the food in the insulated compartment changes, thereby changing the airflow circulation path and forming multiple discrete local temperature zones. This makes it difficult for the temperature control module to correctly determine the adjustment direction, resulting in poor heat preservation effect. Summary of the Invention

[0005] To address the issue of poor heat preservation in the food storage compartment of a catering truck due to changes in the stacking state of the food, this application provides a method and system for heat preservation of food in a catering truck.

[0006] In a first aspect, this application provides a method for keeping food warm in a catering vehicle, applied in a control unit, the method comprising:

[0007] Obtain the internal temperature of the food truck's insulated compartment from multiple temperature sensors;

[0008] Based on the cabin temperature from multiple temperature sensors, the temperature field gradient norm inside the food truck's insulated cabin is calculated, and the temperature field gradient norm characterizes the uniformity of the temperature distribution inside the food truck's insulated cabin.

[0009] Based on the preset target temperature of the food truck's insulated compartment, the temperature field offset within the food truck's insulated compartment is calculated, and the temperature field offset characterizes the degree of deviation of the overall temperature within the food truck's insulated compartment.

[0010] Based on the temperature field gradient norm and the temperature field offset, the target temperature control intensity and target temperature control speed of the food truck insulation compartment are determined.

[0011] Adjust the temperature control power and internal circulation power of the temperature control module according to the target temperature control intensity and the target temperature control speed.

[0012] Optionally, the step of calculating the temperature field gradient norm inside the food truck's insulated compartment based on the compartment temperatures from the multiple temperature sensors specifically involves:

[0013] Acquire historical temperature data from multiple temperature sensors within a preset historical time window;

[0014] Based on the historical temperature data of the multiple temperature sensors, calculate the temperature cross-correlation coefficients between the multiple temperature sensors;

[0015] Calculate the temperature difference between the multiple temperature sensors;

[0016] Based on the temperature cross-correlation coefficients and temperature differences between the multiple temperature sensors, the temperature field gradient norms of the multiple cabin temperatures are calculated.

[0017] Optionally, the step of calculating the temperature field gradient norm of the multiple cabin temperatures based on the temperature cross-correlation coefficients and temperature differences between the multiple temperature sensors specifically involves:

[0018]

[0019] Where t is the temperature field gradient norm, Let be the cross-correlation coefficient between the i-th temperature sensor and the j-th temperature sensor. Let be the temperature difference between the i-th temperature sensor and the j-th temperature sensor, and n be the total number of sensors.

[0020] Optionally, calculating the temperature field shift within the food truck's insulated compartment based on a preset target temperature specifically includes:

[0021] Based on a preset spatial topology order, the multiple temperature sensors are sorted to obtain a spatial sorting result;

[0022] Calculate the temperature difference between the cabin temperature detected by the multiple temperature sensors and the preset target temperature;

[0023] The temperature difference values ​​of multiple temperature sensors are sorted spatially to construct a temperature deviation curve;

[0024] Convert the temperature deviation curve into a temperature deviation frequency domain curve;

[0025] The low-frequency component is extracted from the temperature deviation frequency domain curve, and the low-frequency component is used as the temperature field offset.

[0026] Optionally, determining the target temperature control intensity and target temperature control speed of the food truck insulation compartment based on the temperature field gradient norm and the temperature field offset specifically involves:

[0027] The temperature field gradient norm and the temperature field offset are normalized to obtain the uniformity normalization index and the deviation normalization index.

[0028] The uniformity normalization index and the deviation normalization index are used to construct a two-dimensional feature vector;

[0029] Obtain the storage information of the food in the food truck's insulated compartment, including the type of food, storage time, and storage quantity;

[0030] Based on the storage information of the food ingredients, the temperature control accuracy of the food ingredients is obtained from the temperature control accuracy table;

[0031] If the temperature control accuracy of the food ingredient is greater than or equal to the preset temperature control accuracy threshold, then the two-dimensional feature vector is converted into polar coordinates.

[0032] The target temperature control intensity of the food truck's insulated compartment is determined based on the current temperature control intensity and the polar coordinates.

[0033] The target temperature control speed of the food truck's insulated compartment is determined based on the current temperature control speed and the polar coordinates.

[0034] Optionally, after obtaining the temperature control accuracy of the food from the temperature control accuracy table based on the food's storage information, the method further includes:

[0035] If the temperature control accuracy of the food ingredient is less than the preset temperature control accuracy threshold, then the weighted sum of the uniformity normalization index and the deviation normalization index is calculated to obtain the temperature control energy consumption index.

[0036] The temperature control energy consumption index is matched with the preset temperature control strategy table to obtain the target temperature control intensity domain and the target temperature control speed.

[0037] Secondly, this application provides a food warming system for a catering vehicle, wherein the system is a control unit, and the control unit includes an acquisition module, a processing module, and an output module, wherein:

[0038] The acquisition module is used to acquire the cabin temperature uploaded by multiple temperature sensors inside the food truck's insulated cabin;

[0039] The processing module is used to calculate the temperature field gradient norm inside the food truck's insulated compartment based on the compartment temperatures from multiple temperature sensors. The temperature field gradient norm characterizes the uniformity of the temperature distribution inside the food truck's insulated compartment.

[0040] Based on the preset target temperature of the food truck's insulated compartment, the temperature field offset within the food truck's insulated compartment is calculated, and the temperature field offset characterizes the degree of deviation of the overall temperature within the food truck's insulated compartment.

[0041] Based on the temperature field gradient norm and the temperature field offset, the target temperature control intensity and target temperature control speed of the food truck insulation compartment are determined.

[0042] The output module is used to adjust the temperature control power and internal circulation power of the temperature control module according to the target temperature control intensity and the target temperature control speed.

[0043] Thirdly, this application provides an electronic device including a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform the method as described in any one of the first aspects.

[0044] Fourthly, this application provides a computer-readable storage medium storing instructions that, when executed, perform the method described in any one of the first aspects.

[0045] In summary, one or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0046] First, temperature sensors placed at various locations within the food truck's insulated compartment simultaneously upload the detected interior temperature to the control unit, ensuring timely temperature adjustment. Then, based on the adjacency relationships of multiple temperature sensors, the temperature field gradient norm within the compartment is calculated, quantifying the uniformity of the temperature distribution. Next, based on the preset target temperature of the food truck's insulated compartment, the temperature field deviation is calculated, quantifying the overall temperature deviation. If the temperature distribution uniformity is low, the internal circulation power of the recirculation system can be increased to mix heat within the compartment using airflow, thus reducing localized temperature differences. If the overall temperature deviates, the operating power of the temperature control system can be adjusted to increase the temperature control intensity per unit time, quickly bringing the overall temperature back to normal. This ensures that the temperature within the compartment quickly recovers and stabilizes at the target temperature under uniform conditions, thereby improving the food insulation effect. Attached Figure Description

[0047] Figure 1 This is a flowchart illustrating a method for keeping food warm in a catering vehicle, as provided in an embodiment of this application.

[0048] Figure 2 This is a schematic diagram of the structure of a food warming system for a catering vehicle provided in an embodiment of this application.

[0049] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0050] Explanation of reference numerals in the attached drawings: 1. Acquisition module; 2. Processing module; 3. Output module; 300. Electronic device; 301. Processor; 302. Communication bus; 303. User interface; 304. Network interface; 305. Memory. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0052] This application provides a method for keeping food warm in a catering vehicle. This method is applied to a control unit, such as... Figure 1 As shown, the method includes steps S101 to S105, which are as follows:

[0053] S101. Obtain the cabin temperature uploaded by multiple temperature sensors inside the food truck's insulated compartment.

[0054] In the above steps, a temperature sensor array is deployed inside the food truck's insulated compartment. Specifically, based on the compartment's internal structure and food storage areas, multiple high-precision digital temperature sensors are fixedly installed at key temperature measurement points within the compartment. These key measurement points include, but are not limited to: areas near the air outlet of the internal circulation equipment, corner areas away from the air outlet, and the geometric center areas of different food storage zones. This constructs a sensor network capable of comprehensively sensing the three-dimensional temperature distribution within the compartment. All temperature sensors are connected to the main processor of the food truck's control unit via a single bus to simplify wiring and support unified data acquisition.

[0055] During normal operation of the catering truck, each temperature sensor synchronously detects the real-time temperature at its location and uploads the detected temperature data to the control unit. At this time, the control unit can obtain the temperature inside the insulated compartment of the catering truck at different locations.

[0056] S102. Based on the cabin temperature from multiple temperature sensors, calculate the temperature field gradient norm inside the food truck's insulated cabin. The temperature field gradient norm characterizes the uniformity of the temperature distribution inside the food truck's insulated cabin.

[0057] In the above steps, after the control unit obtains multiple cabin temperatures, it needs to first determine the uniformity of the temperature distribution within the food truck's insulated cabin to provide a basis for precise temperature adjustment in the subsequent food truck insulated cabin. Specifically:

[0058] Historical temperature data from multiple temperature sensors within a preset historical time window (e.g., the past 30 minutes) are acquired. Then, the Pearson correlation coefficient between the historical temperature data of each temperature sensor is calculated as the temperature cross-correlation coefficient. This quantifies the coordinated temperature changes in the areas detected by each temperature sensor. Based on the current cabin temperature detected by each temperature sensor, the temperature difference between the multiple temperature sensors is calculated to determine the temperature differences in the areas detected by each sensor. It should be noted that when the temperature inside the catering truck's insulated compartment is ideally uniform, the temperature cross-correlation coefficient between any two temperature sensors will be large, and the temperature difference will be small. If both the temperature cross-correlation coefficient and the temperature difference are large, it indicates that significant temperature differences still exist between two areas even with high temperature coordination, further suggesting the formation of localized temperature zones. In this case, the uniformity of temperature distribution inside the catering truck's insulated compartment will decrease. Therefore, this application further calculates the temperature field gradient norm of the multiple cabin temperatures based on the temperature cross-correlation coefficients and temperature differences between the multiple temperature sensors, as detailed below:

[0059]

[0060] Where t is the temperature field gradient norm, Let be the cross-correlation coefficient between the i-th temperature sensor and the j-th temperature sensor. Let be the temperature difference between the i-th temperature sensor and the j-th temperature sensor, and n be the total number of sensors.

[0061] In the above formula, the standard deviation between multiple temperature zones is calculated to determine the degree of temperature difference detected by each temperature sensor. Specifically, for two temperature sensors with a small cross-correlation coefficient, it indicates a low spatial correlation, and the temperature zone formed between them is not meaningful for analysis; therefore, [the following is omitted as it is not relevant to the calculation]. This reduces the impact of invalid data.

[0062] S103. Based on the preset target temperature of the food truck's insulated compartment, calculate the temperature field deviation within the insulated compartment. The temperature field deviation coefficient characterizes the degree of deviation of the overall temperature within the insulated compartment.

[0063] In the above steps, in addition to detecting the uniformity of temperature distribution within the food truck's insulated compartment, this application also needs to detect the overall deviation of the temperature of the entire temperature field within the compartment from the target temperature field. Specifically:

[0064] This application first sorts multiple temperature sensors according to a preset spatial topology order, then calculates the temperature difference between the cabin temperature detected by each temperature sensor and the preset target temperature. Based on the spatial sorting results of the multiple temperature sensors, the temperature difference corresponding to each temperature sensor is used to construct a temperature deviation curve. This temperature deviation curve can describe the temperature deviation at each detection point and also integrate the distribution characteristics of the temperature deviation in the spatial dimension. Then, the temperature deviation curve is subjected to Fourier transform to convert the temperature deviation curve from the spatial domain to the frequency domain, resulting in a temperature deviation frequency domain curve. Finally, the low-frequency component in the temperature deviation frequency domain curve is extracted. The low-frequency component corresponds to the overall change trend of the cabin temperature, which describes the degree to which the temperature of the entire cabin is consistently higher or lower than the target temperature. Therefore, it is used as the temperature field deviation coefficient to quantify the degree of deviation of the overall temperature inside the catering truck's insulated cabin.

[0065] S104. Based on the temperature field gradient norm and temperature field offset, determine the target temperature control intensity and target temperature control speed of the food truck insulation compartment.

[0066] In the above steps, after determining the temperature uniformity and overall deviation within the food insulation chamber, the types and states of the food loaded in the chamber are dynamically changing. For some foods that do not require high-precision temperature control, frequent and high-power adjustments not only increase energy consumption but also accelerate the aging of the temperature control equipment. Therefore, this application obtains the storage information of the food based on the entered food RFID tags. The storage information includes the food type, storage time, and storage quantity. Then, the food type, storage time, and storage quantity are matched with a temperature control accuracy table to obtain the corresponding temperature control accuracy for each of the three. The weighted sum of the corresponding temperature control accuracies is then calculated to obtain the temperature control accuracy of the food. If the temperature control accuracy of the food is greater than or equal to a preset temperature control accuracy threshold, it indicates that the current food quality is highly sensitive to temperature, and a high-precision insulation mode needs to be activated. Specifically:

[0067] First, the temperature field gradient norm and temperature field offset are normalized according to their maximum values ​​under typical operating conditions to obtain uniformity normalization index and deviation normalization index. Then, the uniformity normalization index and deviation normalization index are constructed into a two-dimensional feature vector in Cartesian coordinate system. It should be noted that the temperature control equipment adjusts the temperature in the chamber from two aspects: temperature control intensity and temperature control speed. Temperature control intensity can be understood as cooling / heating efficiency, and temperature control speed can be understood as the internal circulation speed in the chamber. The faster the internal circulation, the faster the air flow in the chamber, and the faster the heat dissipation. In the adjustment process, there is a certain synergistic efficiency between the two. For example, when the overall temperature deviation in the chamber is small, but the uniformity is poor, the adjustment of temperature control speed is the main focus, and the adjustment of temperature control intensity is the auxiliary focus. However, in a two-dimensional coordinate system, the uniformity normalization index and the deviation normalization index are superimposed and correlated, making it impossible to directly distinguish the core direction of the adjustment demand and the urgency of the demand. For example, when the uniformity normalization index is 0.8 and the deviation normalization index is 0.2, it can only be determined that the uniformity problem is more prominent, but it cannot quantify how much resource should be prioritized for temperature control speed. Currently, the commonly used method is to directly weight and sum the uniformity normalization index and the deviation normalization index to obtain a comprehensive index, and then map the comprehensive index to temperature control intensity and temperature control speed respectively. However, this scheme relies on subjective experience and is difficult to adapt to temperature control requirements. To improve the accuracy of temperature coordination between the two systems and address the dynamic changes in the temperature field, this application transforms the two-dimensional feature vector from Cartesian coordinates to polar coordinates (R, A). The polar angle A represents the dominant adjustment requirement of the current cabin temperature field. Specifically, the closer the polar angle A is to 0, the more the adjustment requirement is biased towards correcting the overall deviation of the cabin temperature; the closer the polar angle A is to 90 degrees, the more the adjustment requirement is biased towards correcting local temperature unevenness within the cabin. The radial distance R represents the urgency of the dominant adjustment requirement. At this point, the temperature control intensity compensation and temperature control speed compensation can be accurately quantified. Specifically, the temperature control intensity compensation... P represents the current temperature control intensity and the current temperature control speed compensation amount. v represents the current temperature control speed.

[0068] Finally, the target temperature control intensity is obtained by adding the current temperature control intensity compensation amount to the current temperature control intensity, and the target temperature control speed is obtained by adding the current temperature control speed compensation amount to the current temperature control speed. This improves the accuracy of temperature coordination between the two and avoids the situation where the temperature field deteriorates due to conflicting actions.

[0069] Then, if the temperature control accuracy of the food is less than the preset temperature control accuracy threshold, it indicates that the food is not sensitive to temperature fluctuations. In this case, energy efficiency and equipment lifespan should be given priority. Specifically:

[0070] The temperature control energy consumption index is obtained by calculating the weighted sum of the uniformity normalization index and the deviation normalization index. The weight values ​​of the uniformity normalization index and the deviation normalization index are determined by the unit energy consumption of the temperature control intensity and the unit energy consumption of the temperature control speed. Then, the temperature control energy consumption index is matched with the preset temperature control strategy table to obtain the target temperature control speed in the target temperature control intensity domain, thereby improving the energy efficiency of cabin temperature control.

[0071] S105. Adjust the temperature control power and internal circulation power of the temperature control module according to the target temperature control intensity and target temperature control speed.

[0072] In the above steps, after determining the precise target temperature control intensity and target temperature control speed, the control unit generates power conversion commands for the cooling / heating equipment and the internal circulation equipment, and sends the commands to the cooling / heating equipment and the internal circulation equipment to adjust the temperature control power and the internal circulation power, so that the insulation temperature in the cabin can be quickly restored to a stable state.

[0073] Reference Figure 2 This application also provides a food warming system for a catering vehicle. The system is a control unit, which includes an acquisition module, a processing module 2, and an output module 3, wherein:

[0074] Module 1 is used to acquire the internal temperature of the food truck's insulated compartment from multiple temperature sensors.

[0075] Processing module 2 is used to calculate the temperature field gradient norm inside the food truck's insulated compartment based on the temperature inside the compartment from multiple temperature sensors. The temperature field gradient norm characterizes the uniformity of the temperature distribution inside the food truck's insulated compartment.

[0076] Based on the preset target temperature of the food truck's insulated compartment, the temperature field offset within the insulated compartment is calculated. The temperature field offset characterizes the degree of deviation of the overall temperature within the insulated compartment.

[0077] Based on the temperature field gradient norm and temperature field offset, the target temperature control intensity and target temperature control speed of the food truck insulation compartment are determined.

[0078] Output module 3 is used to adjust the temperature control power and internal circulation power of the temperature control module according to the target temperature control intensity and target temperature control speed.

[0079] It should be noted that the above embodiments of the apparatus are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0080] This application also discloses an electronic device. (See reference...) Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application. The electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 305, and at least one communication bus 302.

[0081] The communication bus 302 is used to enable communication between these components.

[0082] The user interface 303 may include a display screen and a camera. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0083] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0084] The processor 301 may include one or more processing cores. The processor 301 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 305, and by calling data stored in memory 305. Optionally, the processor 301 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 301 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 301 and may be implemented as a separate chip.

[0085] The memory 305 may include random access memory (RAM) or read-only memory. Optionally, the memory 305 may include a non-transitory computer-readable storage medium. The memory 305 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 305 may also be at least one storage device located remotely from the aforementioned processor 301. (Refer to...) Figure 3 The memory 305, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for a method of keeping food warm in a catering vehicle.

[0086] exist Figure 3 In the illustrated electronic device 300, the user interface 303 is mainly used to provide an input interface for the user and to acquire user input data; while the processor 301 can be used to call an application stored in the memory 305 for a method of keeping food warm in a catering cart. When executed by one or more processors 301, the electronic device 300 performs one or more of the methods described in the above embodiments. It should be noted that, for the foregoing method embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0087] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0088] In the various embodiments provided in this application, it should be understood that the disclosed apparatus 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 coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between apparatuses or units may be electrical or other forms.

[0089] 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 this embodiment according to actual needs.

[0090] Furthermore, the functional units in the various embodiments of this application 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.

[0091] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0092] The above description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the specification and the disclosure of practical truths.

[0093] This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for keeping food warm in a catering cart, characterized in that, When applied in a control unit, the method includes: Obtain the internal temperature of the food truck's insulated compartment from multiple temperature sensors; Based on the cabin temperature from multiple temperature sensors, the temperature field gradient norm inside the food truck's insulated cabin is calculated, and the temperature field gradient norm characterizes the uniformity of the temperature distribution inside the food truck's insulated cabin. Based on the preset target temperature of the food truck's insulated compartment, the temperature field offset within the food truck's insulated compartment is calculated, and the temperature field offset characterizes the degree of deviation of the overall temperature within the food truck's insulated compartment. Based on the temperature field gradient norm and the temperature field offset, the target temperature control intensity and target temperature control speed of the food truck insulation compartment are determined. Adjust the temperature control power and internal circulation power of the temperature control module according to the target temperature control intensity and the target temperature control speed.

2. The method according to claim 1, characterized in that, The step of calculating the temperature field gradient norm inside the food truck's insulated compartment based on the temperatures from multiple temperature sensors is as follows: Acquire historical temperature data from multiple temperature sensors within a preset historical time window; Based on the historical temperature data of the multiple temperature sensors, calculate the temperature cross-correlation coefficients between the multiple temperature sensors; Calculate the temperature difference between the multiple temperature sensors; Based on the temperature cross-correlation coefficients and temperature differences between the multiple temperature sensors, the temperature field gradient norms of the multiple cabin temperatures are calculated.

3. The method according to claim 2, characterized in that, The temperature field gradient norm of the multiple cabin temperatures is calculated based on the temperature cross-correlation coefficients and temperature differences between the multiple temperature sensors, specifically as follows: Where t is the temperature field gradient norm, Let be the cross-correlation coefficient between the i-th temperature sensor and the j-th temperature sensor. Let be the temperature difference between the i-th temperature sensor and the j-th temperature sensor, and n be the total number of sensors.

4. The method according to claim 1, characterized in that, The step of calculating the temperature field shift within the food truck's insulated compartment based on a preset target temperature specifically includes: Based on a preset spatial topology order, the multiple temperature sensors are sorted to obtain a spatial sorting result; Calculate the temperature difference between the cabin temperature detected by the multiple temperature sensors and the preset target temperature; The temperature difference values ​​of multiple temperature sensors are sorted spatially to construct a temperature deviation curve; Convert the temperature deviation curve into a temperature deviation frequency domain curve; The low-frequency component is extracted from the temperature deviation frequency domain curve, and the low-frequency component is used as the temperature field offset.

5. The method according to claim 1, characterized in that, The determination of the target temperature control intensity and target temperature control speed of the food truck insulation compartment based on the temperature field gradient norm and the temperature field offset is specifically as follows: The temperature field gradient norm and the temperature field offset are normalized to obtain the uniformity normalization index and the deviation normalization index. The uniformity normalization index and the deviation normalization index are used to construct a two-dimensional feature vector; Obtain the storage information of the food in the food truck's insulated compartment, including the type of food, storage time, and storage quantity; Based on the storage information of the food ingredients, the temperature control accuracy of the food ingredients is obtained from the temperature control accuracy table; If the temperature control accuracy of the food ingredient is greater than or equal to the preset temperature control accuracy threshold, then the two-dimensional feature vector is converted into polar coordinates. The target temperature control intensity of the food truck's insulated compartment is determined based on the current temperature control intensity and the polar coordinates. The target temperature control speed of the food truck's insulated compartment is determined based on the current temperature control speed and the polar coordinates.

6. The method according to claim 5, characterized in that, After obtaining the temperature control accuracy of the food from the temperature control accuracy table based on the food's storage information, the method further includes: If the temperature control accuracy of the food ingredient is less than the preset temperature control accuracy threshold, then the weighted sum of the uniformity normalization index and the deviation normalization index is calculated to obtain the temperature control energy consumption index. The temperature control energy consumption index is matched with the preset temperature control strategy table to obtain the target temperature control intensity domain and the target temperature control speed.

7. A food warming system for a catering cart, characterized in that, The system is a control unit, which includes an acquisition module, a processing module (2), and an output module (3), wherein: The acquisition module (1) is used to acquire the cabin temperature uploaded by multiple temperature sensors in the food truck's insulated cabin; The processing module (2) is used to calculate the temperature field gradient norm inside the food truck's insulated compartment based on the temperature inside the compartment from the multiple temperature sensors. The temperature field gradient norm characterizes the uniformity of the temperature distribution inside the food truck's insulated compartment. Based on the preset target temperature of the food truck's insulated compartment, the temperature field offset within the food truck's insulated compartment is calculated, and the temperature field offset characterizes the degree of deviation of the overall temperature within the food truck's insulated compartment. Based on the temperature field gradient norm and the temperature field offset, the target temperature control intensity and target temperature control speed of the food truck insulation compartment are determined. The output module (3) is used to adjust the temperature control power and internal circulation power of the temperature control module according to the target temperature control intensity and the target temperature control speed.

8. An electronic device, characterized in that, The device includes a processor (301), a memory (305), a user interface (303), and a network interface (304). The memory (305) is used to store instructions. The user interface (303) and the network interface (304) are used to communicate with other devices. The processor (301) is used to execute the instructions stored in the memory (305) to cause the electronic device (300) to perform the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed, perform the method as described in any one of claims 1 to 6.

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