Refrigeration air conditioner control method and system based on dynamic adjustment algorithm

Abstract

The invention relates to a refrigeration air conditioner control method and system based on a dynamic adjusting algorithm, a low-pressure area and a high-pressure area in a cold-chain logistics transportation cabinet are judged through real-time reference air pressure data of a barometer, and the real-time reference air pressure data of the barometer can be received and analyzed. A sliding window is established, based on the sliding window, a parameter diagram of real-time reference air pressure data is segmented, real-time pressure data in the sliding window is obtained, when the conveying amount of cold air is too large, a low-pressure area can be formed in the cold-chain logistics transportation cabinet, and then more wet hot air is absorbed, so that the interior of the cold-chain logistics transportation cabinet is frosted and frozen; and more effective energy can be consumed. When the conveying amount of the cold air is too small, a high-pressure area can be formed in the cold-chain logistics transportation cabinet, and the preset temperature cannot be reached. Through the air pressure data, the temperature in the cold-chain logistics transportation cabinet can be accurately obtained.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a refrigeration air conditioning control method and system based on a dynamic adjustment algorithm. Background Art

[0002] In cold chain logistics, maintaining a constant temperature is an effective way to save costs. Traditional cold chain logistics insulation methods are mostly to set a temperature, and deliver cold air in the cold chain logistics transport cabinet at a regular and quantitative rate according to the volume, loading volume, sealing and other parameters of the cold chain logistics transport cabinet. This method of maintaining temperature is often difficult to ensure that the temperature inside the cold chain logistics transport cabinet is constant during transportation. When the amount of cold air delivered is too much, a low-pressure area will form inside the cold chain logistics transport cabinet, which will absorb more moist hot air, which will cause frost and ice inside the cold chain logistics transport cabinet, and will also consume more effective energy. When the amount of cold air delivered is too little, the temperature inside the cold chain logistics transport cabinet is difficult to reach the preset target. For this reason, it is necessary to address the defect of traditional cold chain logistics insulation methods that it is difficult to accurately adjust the temperature inside the cold chain logistics transport cabinet, and propose a refrigeration air conditioning control method and system based on a dynamic adjustment algorithm. Summary of the Invention

[0003] Based on this, it is necessary to propose a refrigeration air conditioning control method and system based on a dynamic adjustment algorithm to address the defect of traditional cold chain logistics insulation methods that are difficult to accurately adjust the temperature inside the cold chain logistics transport cabinet.

[0004] The present application provides a refrigeration air conditioning control method based on a dynamic adjustment algorithm, comprising: Receive real-time reference air pressure data from the barometer; Create a sliding window; Segment the parameter map of the real-time reference pressure data based on a sliding window; Select a sliding window of time; Based on the selected sliding window, determining whether the real-time reference air pressure data within the sliding window is within a target threshold; If the real-time reference air pressure data within the sliding window is within the target threshold range, it is determined that the temperature inside the cold chain logistics cabinet is at the target temperature; If the real-time reference air pressure data within the sliding window is less than the lower limit of the target threshold range, the ventilation procedure is executed; If the real-time reference air pressure data within the sliding window is greater than the upper limit of the target threshold range, the cooling air delivery procedure is executed.

[0005] Furthermore, a parameter map of real-time reference pressure data is established; Define the horizontal axis of the parameter graph as time; The vertical axis of the parameter diagram is defined as the reference air pressure; Receive real-time reference air pressure data from the barometer; The received real-time reference air pressure is incorporated into the parameter map based on the timestamp of the real-time reference air pressure data.

[0006] Furthermore, the length of the time interval of a sliding window is selected; Fit one side of the selected sliding window to the coordinate intersection of the parameter graph; Calculate the mean of the real-time reference air pressure within the sliding window; Obtain the average of the real-time reference air pressure within the sliding window; The length of the time interval of the selected sliding window is returned until the length of the time interval to be selected is completed.

[0007] Furthermore, a correspondence table between the time interval of the sliding window and the mean value of the real-time reference air pressure is generated; Select a sliding window time interval; Receive the average value of the real-time reference air pressure corresponding to the selected time interval; The average value of the selected time interval and real-time reference pressure is included in the corresponding table; Return to the process of selecting a time interval for a sliding window until the length of the time interval to be selected is completed.

[0008] Further, receiving real-time temperature data from a temperature sensor; Based on the temperature threshold target, determining a time period that meets the temperature threshold target; Define the time period that meets the temperature threshold target as the effective time period; Find the valid time period in the parameter graph; Determine the mean of the real-time reference pressure for the valid time period in the parameter graph.

[0009] Further, the corresponding table is called; Based on the mean of the real-time reference pressure in the valid time period in the parameter graph, find the time interval of the sliding window in the corresponding table; Based on the search results, determine whether the time interval of the sliding window is greater than or equal to 1; If the time interval of the sliding window is greater than or equal to 1, the time interval of the sliding window with the longest time interval among the time intervals of the sliding window is selected; If the time interval of the sliding window is less than 1, the length of the time interval is reduced, and the length of the time interval of the selected sliding window is returned until the time interval of the sliding window is greater than or equal to 1.

[0010] Further, the step size of the real-time reference air pressure data is determined; Determine the segmentation step size of the parameter map based on the step size of the real-time reference air pressure data; Segment the parameter map using the segmentation step of the parameter map; Arrange the divided sliding windows in sequence based on the order of the horizontal axis of the parameter graph.

[0011] Further, call the system time; Select a sliding window of time; Based on the split step, determine whether the time difference between the system time and the time point on the side of the sliding window close to the origin is less than or equal to the split step time length; If the time difference between the system time and the time point on the side of the sliding window close to the origin is less than or equal to the time length of the split step, the average value of the real-time reference air pressure in the valid time period in the parameter diagram is called; If the time difference between the system time and the time point on the side of the sliding window close to the origin is greater than the time length of the segmentation step, the sliding window of the selected moment is returned until the average value of the real-time reference air pressure of the valid time period in the parameter diagram is called.

[0012] Furthermore, the length of the time interval of the sliding window is called; Calculate the reference air pressure of the sliding window and the integral value of the time interval of the sliding window; Obtain the time-integrated total amount of the reference pressure; Calculate the quotient of the total time integral of the reference pressure and the time interval of the sliding window; Get real-time reference air pressure data for a sliding window at a selected moment.

[0013] The present application provides a refrigeration and air conditioning control system based on a dynamic adjustment algorithm, comprising: A host computer, configured to execute the refrigeration air conditioning control method based on the dynamic adjustment algorithm; A barometer, communicatively connected to the host computer; A temperature sensor is communicatively connected to the host computer.

[0014] The present application relates to a refrigerated air conditioning control method and system based on a dynamic adjustment algorithm. The real-time reference air pressure data of the barometer is used to determine the low-pressure and high-pressure areas in the cold chain logistics transport cabinet, and the real-time reference air pressure data of the barometer can be received and analyzed. A sliding window is established, and based on the sliding window, the parameter diagram of the real-time reference air pressure data is segmented to obtain the real-time pressure data in the sliding window. When the delivery volume of cold air is too much, a low-pressure area will be formed in the cold chain logistics transport cabinet, and then more moist hot air will be absorbed, which will cause frost and ice inside the cold chain logistics transport cabinet, and will also consume more effective energy. When the delivery volume of cold air is too little, a high-pressure area will be formed in the cold chain logistics transport cabinet, and the preset temperature cannot be reached. Through the air pressure data, the overall temperature in the cold chain logistics transport cabinet can be obtained more accurately. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A structural flow diagram of a refrigeration air conditioning control method based on a dynamic adjustment algorithm provided in one embodiment of the present application.

[0016] Figure 2 This is a structural connection diagram of a refrigeration and air conditioning control system based on a dynamic adjustment algorithm provided in one embodiment of the present application.

[0017] Reference numerals: 100-host computer; 200-barometer; 300-temperature sensor. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of this application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0019] The present application provides a refrigeration air conditioning control method based on a dynamic adjustment algorithm.

[0020] like Figure 1 As shown, in one embodiment of the present application, a refrigeration air conditioner control method based on a dynamic adjustment algorithm includes: S100, receiving real-time reference air pressure data from a barometer.

[0021] Specifically, when the cold air delivery rate is too high, a low-pressure area will form inside the cold chain logistics transport cabinet, which will absorb more moist hot air, causing frost and ice to form inside the cold chain logistics transport cabinet, and also consuming more effective energy. When the cold air delivery rate is too low, a high-pressure area will form inside the cold chain logistics transport cabinet, and the preset temperature cannot be reached.

[0022] S200: Establish a sliding window.

[0023] Specifically, sliding window is a technique commonly used to solve sub-problems in data structures such as arrays and strings, which processes data efficiently by maintaining a fixed or variable size window.

[0024] The sliding window algorithm maintains a window and solves the problem by moving the two boundaries of the window, usually the left and right pointers.

[0025] S300 , segmenting the parameter map of the real-time reference air pressure data based on the sliding window.

[0026] Specifically, in this embodiment, the sliding window is fixed in the parameter graph and does not move, and changes in the air pressure data in the parameter graph over time are recorded in the parameter graph.

[0027] S400: Select a sliding window at a moment.

[0028] Specifically, since the changes of the air pressure data in the parameter graph over time are recorded in the parameter graph, the air pressure data in the sliding window at each moment is different.

[0029] S500 , based on the selected sliding window, determining whether the real-time reference air pressure data within the sliding window is within a target threshold.

[0030] S600: If the real-time reference air pressure data in the sliding window is within the target threshold range, it is determined that the temperature in the cold chain logistics cabinet is at the target temperature.

[0031] S700: If the real-time reference air pressure data within the sliding window is less than the lower limit of the target threshold range, the ventilation procedure is executed.

[0032] S800: If the real-time reference air pressure data within the sliding window is greater than the upper limit of the target threshold range, the cold air delivery program is executed.

[0033] This embodiment relates to a refrigerated air conditioning control method based on a dynamic adjustment algorithm. Low-pressure and high-pressure areas within a cold chain logistics transport cabinet are determined using real-time reference pressure data from a barometer. The real-time reference pressure data from the barometer can be received and analyzed. A sliding window is established, and based on the sliding window, a parameter graph of the real-time reference pressure data is segmented. The real-time pressure data within the sliding window is obtained. When the amount of cold air delivered is excessive, a low-pressure area forms within the cold chain logistics transport cabinet, which in turn absorbs more moist heat, causing frost and ice to form inside the cold chain logistics transport cabinet and consuming more effective energy. When the amount of cold air delivered is too low, a high-pressure area forms within the cold chain logistics transport cabinet, preventing it from reaching the preset temperature. The pressure data allows for a relatively accurate determination of the overall temperature within the cold chain logistics transport cabinet. Temperature adjustment of the cold chain logistics transport cabinet is then achieved by executing a ventilation program or a cold air delivery program.

[0034] In one embodiment of the present application, S100 includes: S110, establishing a parameter map of real-time reference air pressure data.

[0035] S120, defining the horizontal axis of the parameter graph as time.

[0036] S130, defining the vertical coordinate of the parameter graph as the reference air pressure.

[0037] S140: Receive real-time reference air pressure data from a barometer.

[0038] S150 , incorporating the received real-time reference air pressure into a parameter map based on the timestamp of the real-time reference air pressure data.

[0039] Specifically, starting from the origin, draw a horizontal line to the right as the horizontal axis and label it time. Starting from the origin, draw a vertical line upward as the vertical axis and label it reference pressure. Markings are placed on both the horizontal and vertical axes to facilitate measurement and location. The spacing of the markings can be adjusted as needed, but is typically kept evenly spaced for ease of reading and calculation. The two axes are perpendicular to each other and share a common origin.

[0040] In one embodiment of the present application, S200 includes: S211: Select the length of a time interval of a sliding window.

[0041] Specifically, since the horizontal axis of the parameter graph is time, the length of the sliding window is also the time interval.

[0042] S212: aligning one side of the selected sliding window with the coordinate intersection of the parameter graph.

[0043] Specifically, the side of the sliding window close to the coordinate intersection of the parameter graph is aligned with the coordinate intersection of the parameter graph to maintain relative stability.

[0044] S213: Calculate the average of the real-time reference air pressure within the sliding window.

[0045] S214: Obtain an average of the real-time reference air pressure within the sliding window.

[0046] S215 , returning to the length of the time interval of selecting a sliding window until the lengths of the time intervals to be selected are all selected.

[0047] Simply put, in the process of receiving the real-time reference pressure data from the barometer, a sliding window with a time interval length can receive pressure data for more time periods.

[0048] By calculating the mean of the real-time reference pressure within the sliding window, you can obtain a stable and accurate mean pressure value for the selected time interval. Using multiple stable and accurate mean pressure values within the sliding window of the same time interval, you can determine whether the selected time interval length is appropriate.

[0049] In one embodiment of the present application, after S200, the method further includes: S221: Generate a correspondence table between the time interval of the sliding window and the average value of the real-time reference air pressure.

[0050] S222: Select a time interval of a sliding window.

[0051] S223: Receive the average value of the real-time reference air pressure corresponding to the selected time interval.

[0052] S224, adding the average of the selected time interval and the real-time reference air pressure into a corresponding table.

[0053] S225 , returning to the process of selecting a time interval of a sliding window until the length of the time interval to be selected is completed.

[0054] Specifically, a sliding window's time interval can correspond to the average of multiple real-time reference pressures. Each sliding window of the same time interval requires a sliding step size when facing a real-time pressure data stream.

[0055] In one embodiment of the present application, after S200, the method further includes: S231, receiving real-time temperature data from a temperature sensor.

[0056] S232: Based on the temperature threshold target, determine a time period that meets the temperature threshold target.

[0057] S233: Define a time period that meets the temperature threshold target as a valid time period.

[0058] S234, searching for a valid time period in the parameter diagram.

[0059] S235 , determining the average value of the real-time reference air pressure in the valid time period in the parameter graph.

[0060] Specifically, based on the real-time temperature data from the temperature sensor, determine the time period that meets the target temperature threshold. These time periods are considered valid time periods. During actual testing, the length of valid time periods may vary, and the number of valid time periods may not be unique. Find the valid time period in the parameter map. Determine the average real-time reference pressure for the valid time periods in the parameter map.

[0061] Simply put, the valid time period is a time interval based on real time.

[0062] In one embodiment of the present application, before S300, the method further includes: S310, calling the corresponding table.

[0063] S320 , searching for a time interval of the sliding window in the corresponding table based on the average value of the real-time reference air pressure in the valid time period in the parameter graph.

[0064] S330: Based on the search result, determine whether the time interval of the sliding window is greater than or equal to 1.

[0065] S340: If the time interval of the sliding window is greater than or equal to 1, select the time interval of the sliding window with the longest time interval among the time intervals of the sliding window.

[0066] S350: If the time interval of the sliding window is less than 1, reduce the length of the time interval and return to the length of the time interval of the selected sliding window until the time interval of the sliding window is greater than or equal to 1.

[0067] By searching the time interval of the sliding window in a corresponding table, the time interval of the sliding window having the longest time interval among the time intervals of the sliding window can be obtained.

[0068] For example, suppose there is a main string "s = "thisisastringexample"", and we want to find the substring "t = "string"". We can use a sliding window to solve this problem. Initialize the left pointer left to point to the starting position of the main string, and the right pointer right also points to the starting position. Then move the right pointer to the right to expand the window range until the length of the substring in the window is equal to the length of the substring to be found. After each move, compare the substring in the window with the target substring t. If they are equal, the substring is found, otherwise continue to move the right pointer. When the right pointer reaches the end of the main string and is still not found, it means that the main string does not contain the substring t.

[0069] In one embodiment of the present application, S300 includes: S360: Determine the step size of the real-time reference air pressure data.

[0070] S370 , determining a segmentation step length of the parameter map based on the step length of the real-time reference air pressure data.

[0071] S380: Segment the parameter map using the segmentation step of the parameter map.

[0072] S390 , arranging the divided sliding windows in sequence based on the order of the horizontal axis of the parameter graph.

[0073] Data is processed item by item. In time series data analysis, suppose we have a series of pressure data arranged in chronological order and want to observe the pressure trend. If we set the sliding window size to 3 (considering data from three consecutive time points) and the step size to 1, the window will slide sequentially, for example, first considering the data from time points 1, 2, and 3, then the data from time points 2, 3, and 4, and so on. This allows for detailed analysis of the relationship between each adjacent data point, making it less likely to miss any important changes.

[0074] It can process data in detail without missing any important details. It is very useful when comprehensive and in-depth data analysis is required, such as analyzing the changes in each data point in pressure data processing.

[0075] Since the window moves only one unit at a time, data at boundary values or key locations can be accurately included in the window for processing, which helps improve processing accuracy. For example, in image edge detection, a step size of 1 ensures that every pixel on the edge is correctly identified.

[0076] In one embodiment of the present application, S400 includes: S410, calling the system time.

[0077] S420: Select a sliding window at a moment.

[0078] S430: Based on the segmentation step, determine whether the time difference between the system time and the time point on the side of the sliding window close to the origin is less than or equal to the time length of the segmentation step.

[0079] S440: If the time difference between the system time and the time point on the side of the sliding window close to the origin is less than or equal to the time length of the segmentation step, the average value of the real-time reference air pressure in the valid time period in the parameter diagram is called.

[0080] S450, if the time difference between the system time and the time point on the side of the sliding window close to the origin is greater than the time length of the segmentation step, return to the sliding window selected at a moment until the average value of the real-time reference air pressure of the valid time period in the parameter diagram is called.

[0081] Specifically, a hash set is used to store the elements that have been traversed. Initialize an empty set seen and the left pointer left of the sliding window to the starting position of the array, and the right pointer right to the starting position of the array. Then move the right pointer to the right, and for each new element numsright, determine whether it is already in the set seen. If not, add it to the set. If it already exists, it means that a duplicate element has been found, and true is returned. At the same time, each time the right pointer is moved, the corresponding element is removed from the set. If additional information such as the number of times the element appears needs to be recorded, it can be left unremoved. When the right pointer traverses the entire array, if no duplicate elements are found, false is returned.

[0082] In one embodiment of the present application, after S400, the method further includes: S461, calling the length of the time interval of the sliding window.

[0083] S462: Calculate the reference air pressure of the sliding window and the integral value of the time interval of the sliding window.

[0084] S463, obtaining the time integral total of the reference air pressure.

[0085] S464, calculating the quotient of the total time integral of the reference air pressure and the time interval of the sliding window.

[0086] S465: Obtain real-time reference air pressure data of the sliding window at the selected moment.

[0087] Computing the mean of a sliding window is a common data processing operation that can be implemented in a variety of ways. An integration algorithm can be implemented using nested loops. Given an array arr and a window size k, two loops are used to compute the mean of each window. The outer loop controls the starting position i of the window, from 0 to len(arr) - k. The inner loop calculates the sum of the elements in each window and then divides this sum by k to obtain the mean.

[0088] The present application provides a refrigeration and air conditioning control system based on a dynamic adjustment algorithm.

[0089] like Figure 1 As shown, in one embodiment of the present application, a refrigeration air conditioning control system based on a dynamic adjustment algorithm includes: The host computer 100 is used to execute the refrigeration air conditioning control method based on the dynamic adjustment algorithm.

[0090] The barometer 200 is communicatively connected to the host computer 100 .

[0091] The temperature sensor 300 is communicatively connected to the host computer 100 .

[0092] This embodiment relates to a refrigeration air conditioning control method based on a dynamic adjustment algorithm. The upper computer 100 determines the low-pressure area and high-pressure area in the cold chain logistics transport cabinet through the real-time reference air pressure data of the barometer 200, and can receive and analyze the real-time reference air pressure data of the barometer. A sliding window is established, and based on the sliding window, the parameter diagram of the real-time reference air pressure data is segmented to obtain the real-time pressure data in the sliding window. When the delivery volume of cold air is too much, a low-pressure area will form in the cold chain logistics transport cabinet, and then absorb more moist hot air, which will cause frost and ice inside the cold chain logistics transport cabinet, and will also consume more effective energy. When the delivery volume of cold air is too little, a high-pressure area will form in the cold chain logistics transport cabinet, and the preset temperature cannot be reached. The overall temperature in the cold chain logistics transport cabinet can be obtained more accurately by combining the air pressure data with the temperature sensor 300.

[0093] The various technical features of the above-described embodiments can be combined arbitrarily, and the execution order of the method steps is not restricted. In order to make the description concise, not all possible combinations of the various technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0094] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A refrigeration air conditioning control method based on a dynamic adjustment algorithm, characterized in that: include: Receive real-time reference air pressure data from the barometer; Create a sliding window; Segment the parameter map of the real-time reference pressure data based on a sliding window; Select a sliding window of time; Based on the selected sliding window, determining whether the real-time reference air pressure data within the sliding window is within a target threshold; If the real-time reference air pressure data within the sliding window is within the target threshold range, it is determined that the temperature inside the cold chain logistics cabinet is at the target temperature; If the real-time reference air pressure data within the sliding window is less than the lower limit of the target threshold range, the ventilation procedure is executed; If the real-time reference air pressure data within the sliding window is greater than the upper limit of the target threshold range, the cooling air delivery procedure is executed.

2. The refrigeration air conditioning control method based on the dynamic adjustment algorithm according to claim 1, characterized in that: The receiving of real-time reference air pressure data from the barometer includes: Establish parametric maps of real-time reference pressure data; Define the horizontal axis of the parameter graph as time; The vertical axis of the parameter diagram is defined as the reference air pressure; Receive real-time reference air pressure data from the barometer; The received real-time reference air pressure is incorporated into the parameter map based on the timestamp of the real-time reference air pressure data.

3. The refrigeration air conditioning control method based on the dynamic adjustment algorithm according to claim 2, characterized in that: The step of establishing a sliding window comprises: Choose the length of the sliding window time interval; Fit one side of the selected sliding window to the coordinate intersection of the parameter graph; Calculate the mean of the real-time reference air pressure within the sliding window; Obtain the average of the real-time reference air pressure within the sliding window; The length of the time interval of the selected sliding window is returned until the length of the time interval to be selected is completed.

4. The refrigeration air conditioning control method based on the dynamic adjustment algorithm according to claim 3 is characterized in that: After establishing the sliding window, the method further includes: Generate a correspondence table between the time interval of the sliding window and the mean value of the real-time reference air pressure; Select a sliding window time interval; Receive the average value of the real-time reference air pressure corresponding to the selected time interval; The average value of the selected time interval and real-time reference pressure is included in the corresponding table; Return to the process of selecting a time interval for a sliding window until the length of the time interval to be selected is completed.

5. The refrigeration air conditioning control method based on the dynamic adjustment algorithm according to claim 4 is characterized in that: After establishing the sliding window, the method further includes: Receive real-time temperature data from the temperature sensor; Based on the temperature threshold target, determining a time period that meets the temperature threshold target; Define the time period that meets the temperature threshold target as the effective time period; Find the valid time period in the parameter graph; Determine the mean of the real-time reference pressure for the valid time period in the parameter graph.

6. The refrigeration air conditioning control method based on the dynamic adjustment algorithm according to claim 5, characterized in that: Before segmenting the parameter map of the real-time reference air pressure data based on the sliding window, the method further includes: Call the corresponding table; Based on the mean of the real-time reference pressure in the valid time period in the parameter graph, find the time interval of the sliding window in the corresponding table; Based on the search results, determine whether the time interval of the sliding window is greater than or equal to 1; If the time interval of the sliding window is greater than or equal to 1, the time interval of the sliding window with the longest time interval among the time intervals of the sliding window is selected; If the time interval of the sliding window is less than 1, the length of the time interval is reduced, and the length of the time interval of the selected sliding window is returned until the time interval of the sliding window is greater than or equal to 1.

7. The refrigeration air conditioning control method based on the dynamic adjustment algorithm according to claim 6, characterized in that: The segmentation of the parameter map of the real-time reference pressure data based on the sliding window includes: Determine the step size of the real-time reference air pressure data; Determine the segmentation step size of the parameter map based on the step size of the real-time reference air pressure data; Segment the parameter map using the segmentation step of the parameter map; Arrange the divided sliding windows in sequence based on the order of the horizontal axis of the parameter graph.

8. The refrigeration air conditioning control method based on the dynamic adjustment algorithm according to claim 7, characterized in that: The step of selecting a sliding window at a moment includes: Call system time; Select a sliding window of time; Based on the split step, determine whether the time difference between the system time and the time point on the side of the sliding window close to the origin is less than or equal to the split step time length; If the time difference between the system time and the time point on the side of the sliding window close to the origin is less than or equal to the time length of the split step, the average value of the real-time reference air pressure in the valid time period in the parameter diagram is called; If the time difference between the system time and the time point on the side of the sliding window close to the origin is greater than the time length of the segmentation step, the sliding window of the selected moment is returned until the average value of the real-time reference air pressure of the valid time period in the parameter diagram is called.

9. The refrigeration air conditioning control method based on the dynamic adjustment algorithm according to claim 8, characterized in that: After selecting a sliding window at a time, the method further includes: The length of the time interval for calling the sliding window; Calculate the reference air pressure of the sliding window and the integral value of the time interval of the sliding window; Obtain the time-integrated total amount of the reference pressure; Calculate the quotient of the total time integral of the reference pressure and the time interval of the sliding window; Get real-time reference air pressure data for a sliding window at a selected moment.

10. A refrigeration air conditioning control system based on a dynamic adjustment algorithm, characterized in that: include: A host computer, configured to execute the refrigeration air conditioning control method based on the dynamic adjustment algorithm according to any one of claims 1 to 9; A barometer, communicatively connected to the host computer; A temperature sensor is communicatively connected to the host computer.

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