Air conditioner control method for airport zone control

Abstract

The invention discloses an air conditioner control method for airport zone control, particularly relates to the technical field of terminal air conditioner ventilation control, and aims to solve the problem that comfort and energy consumption are difficult to consider due to synchronous imbalance of heat and humidity loads caused by passenger flow pulse and external meteorological disturbance. Passenger flow behaviors and meteorological disturbance are jointly projected to a unified space basis, synchronous perception of an air conditioner and a ventilation adjustment object is achieved, two parameters of thermal impulsion and humidity hysteresis amplitude are introduced on the basis, and the homonymy of thermal and humidity disturbance is described through included angle cosine, so that adjustment logic pays attention to the change degree and is also sensitive to impact collaboration, and the overall performance of the air conditioner and the ventilation adjustment object is improved. Adjustment priority screening is completed before an adjustment strategy is generated, and resources are prevented from being dispersed in a non-key area; a subsequent adjustment result acts on a prediction kernel weight through heat and humidity deviation feedback of a breathing area, continuous transition from sensing to decision making to correction is achieved, and adaptability and adjustment efficiency under sudden passenger flow change and meteorological disturbance are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of terminal air conditioning and ventilation control, and more particularly to an air conditioning control method for terminal partition control. BACKGROUND

[0002] The passenger flow in the terminal presents a wave peak flow, and the activities of waiting, boarding, catering and passing push heat, humidity and carbon dioxide to the space picture that changes in an instant. The air conditioning supply is borne by the partition unit, and the ventilation is completed by the fresh air unit and the return air pipeline in cooperation, and both of them should theoretically respond to the load jump simultaneously. However, the operation practice shows that the control core is still driven by the single-point deviation of temperature, and the real-time fluctuations of humidity and air quality are ignored, and when the external wet-bulb temperature is high or low or the passenger flow prediction is short-term inaccurate, the supply and ventilation will be in different rhythms, forming a double pull and saw of comfort and energy consumption.

[0003] The existing public scheme CN115854501A "Airport terminal room temperature large lag prediction control method based on passenger flow prediction" is just such a single-target representative: the algorithm injects the passenger flow prediction into the temperature model, and then uses the model predictive control to seek the optimal temperature trajectory, but does not put carbon dioxide and relative humidity into the same optimization framework. When the passenger flow suddenly increases, the human body heat dissipation and exhaust increase sharply, and the temperature model still steadily outputs the original set supply strategy; the on-duty personnel are forced to temporarily increase the fresh air volume to lower the carbon dioxide, which instantly destroys the temperature balance, and the system immediately compensates by heating or cooling, and the supply and ventilation constantly offset each other. The three curves of temperature, humidity and air quality deviate alternately due to the lack of a unified target, the energy consumption line rises linearly, and the passenger's physical sensation jumps between dry and cold wind and hot and humid, which reveals the core gap of the lack of intelligent linkage of air conditioning and ventilation, which is the key problem to be solved by the present application. In order to solve the above problems, a technical scheme is provided. SUMMARY

[0004] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present application provide an air conditioning control method for terminal partition control, which projects the passenger flow behavior and meteorological disturbance onto a unified space basis by constructing a thermal-humidity contour surface and a thermal pulse index map, realizes the synchronous perception of the air conditioning and ventilation adjustment objects, introduces two parameters of thermal impulse and humidity lag amplitude on this basis, describes the same direction of thermal-humidity disturbance through the cosine of the angle, makes the adjustment logic not only pay attention to the change degree, but also be sensitive to the impact coordination, and then completes the adjustment priority selection before the generation of the adjustment strategy, so as to avoid the dispersion of resources in non-key areas; the subsequent adjustment result is affected by the thermal-humidity deviation of the breathing area to the prediction kernel weight, realizing the continuous transition from perception to decision to correction, so as to solve the problems proposed in the background art.

[0005] To achieve the above object, the present application provides the following technical scheme: S1: Passenger flow line, air flow and outdoor meteorological field are fused into the same space-time grid, and the terminal heat and humidity contour is drawn in real time; S2: The heat and humidity gradient curvature is calculated between the continuous grids, and the heat pulse index map is generated, and the heat impulse and humidity lag amplitude of each grid is calculated, and if the cosine coefficient of the two parameters is higher than the threshold, the priority adjustment weight is marked in the heat pulse index map; S3: According to the marked heat pulse index map, the partition enthalpy-wind adjustment instruction is automatically generated, which gives the supply air enthalpy offset, air volume transfer path and fresh air mixing ratio at one time, and maintains the supply and return air pressure difference balance before issuing the execution end; S4: After the execution end completes the adjustment, the actual heat and humidity offset is collected through the breathing area sentinel sensing layer, the comfort deviation map is summarized and returned to the analysis module; S5: The analysis module corrects the heat impulse and humidity lag amplitude calculation smoothing coefficient with the comfort deviation map, and refreshes the next time period grid initial value, so that the subsequent heat pulse index map is closer to the heat and humidity dynamic change on site.

[0006] In a preferred embodiment, step S1 includes the following processing logic: Collect passenger flow line data, air flow data and outdoor meteorological field data, record the number of passengers and the length of stay in the space-time grid unit through an infrared sensor array, record the wind speed vector and direction through a partitioned wind speed sensor and an air conditioning air outlet monitor, and record the temperature, humidity and wind direction through an external meteorological station sensor; The passenger flow line data, air flow data and outdoor meteorological field data are fused into the space-time grid unit divided at fixed intervals in a three-dimensional coordinate system, and the fused heat and humidity contribution value is calculated as a unified quantitative representation of multi-source data.

[0007] In a preferred embodiment, step S1 further includes the following processing logic: The heat and humidity gradient is calculated on the fused space-time grid unit, and the heat and humidity contour is generated using a spline function interpolation based on the heat and humidity gradient value, and the heat and humidity contour represents the continuous spatial view of the heat and humidity distribution in the terminal in the form of contour lines.

[0008] In a preferred embodiment, step S2 includes the following processing logic: The heat and humidity gradient curvature is calculated between the continuous grids on the heat and humidity contour, and the heat pulse index map is generated by a grid aggregation method to represent the pulse intensity distribution of heat and humidity changes in the form of color scale; The heat impulse and humidity lag amplitude of each grid is calculated as a quantitative index of heat propagation rate and humidity decay lag; The heat impulse and humidity lag amplitude is constructed into a vector in polar coordinates, and the cosine coefficient is calculated as a judgment coefficient, and if the cosine coefficient is higher than the threshold, the priority adjustment weight is marked in the heat pulse index map in the form of numerical label superimposed on the corresponding grid.

[0009] In a preferred embodiment, step S2 further comprises the following processing logic: The heat impulse acquisition logic first calculates the total heat increase per unit area by differencing two infrared thermal images to quantify the heat change amplitude, then divides the corresponding passenger flow stay duration to calculate the instantaneous heat power to reflect the heat dissipation rate, and finally accumulates the instantaneous heat power along the main direction of the air conditioning airflow to form a single numerical index to reflect the dynamic characteristics of heat propagation.

[0010] In a preferred embodiment, step S2 further comprises the following processing logic: The wet hysteresis amplitude acquisition logic first determines the local humidity surge degree by extracting the difference between the maximum value and the average value from the two absolute humidity fields, then estimates the hysteresis persistence based on the ventilation air change prediction curve to evaluate the hysteresis persistence, and finally multiplies the local humidity surge value to generate a single numerical index to characterize the hysteresis amplitude of humidity fluctuation.

[0011] In a preferred embodiment, step S3 comprises the following processing logic: According to the labeled heat pulse index map, the supply enthalpy offset is generated to match the heat disturbance dominated by the heat impulse, the air volume transfer path is calculated to realize the dynamic transfer of air volume from low priority areas to high priority areas and balance the partition air volume distribution, the fresh air mixing ratio is determined to coordinate the humidity disturbance dominated by the wet hysteresis amplitude and synchronize ventilation and supply air, and the pressure difference correction factor is integrated with the supply enthalpy offset, air volume transfer path and fresh air mixing ratio to maintain the balance of supply and return air pressure difference after the partition enthalpy-air regulation instruction is issued to the execution end.

[0012] In a preferred embodiment, step S4 comprises the following processing logic: After the execution end completes the regulation, the actual heat and humidity offset is collected by the breathing zone sentinel sensing layer to quantify the difference from the expected comfort level and verify the execution effect, the actual heat and humidity offset is summarized into a comfort deviation map to visualize the partition deviation distribution and map the post-regulation pattern, and the comfort deviation map is sent back to the analysis module to transmit feedback information and support dynamic adjustment of heat impulse and wet hysteresis amplitude calculation.

[0013] In a preferred embodiment, step S5 comprises the following processing logic: The analysis module corrects the calculation smoothing coefficient of the heat impulse and the wet hysteresis amplitude with the comfort deviation map to integrate the regulation feedback and adjust the parameter calculation sensitivity, refreshes the grid initial value of the next period to bridge the current feedback and the next prediction and initializes the space-time grid, ensures that the subsequent heat pulse index map is close to the field heat and humidity dynamic changes, and improves the response accuracy to sudden disturbances.

[0014] The technical effects and advantages of the airport partition control air conditioning control method of the present application are: The application realizes the synchronous perception of the air conditioner and the ventilation regulation object by constructing the thermal-wet profile and the thermal pulse index map, projecting the passenger flow behavior and the meteorological disturbance on the unified space basis, introducing the thermal impulse and the wet lag amplitude two parameters, and using the cosine of the angle to describe the same direction of the thermal-wet disturbance, so that the regulation logic not only pays attention to the change degree, but also is sensitive to the impact coordination, and then the regulation priority screening is completed before the generation of the regulation strategy, so as to avoid the dispersion of resources in the non-key area; the subsequent regulation result is affected by the thermal-wet deviation of the breathing area to the prediction core weight, so as to realize the continuous transition from perception to decision to correction; the whole technical path takes the stable transmission of information among the prediction-response-feedback as the core, takes the spatial form and dynamic trend of the regulation signal as the driving logic, and improves the adaptability and regulation efficiency of the terminal building partition control under the mutation passenger flow and meteorological disturbance. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 It is a flowchart of an airport partition control air conditioning control method. DETAILED DESCRIPTION

[0016] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the application.

[0017] Embodiment 1: Figure 1 An airport partition control air conditioning control method is given, which comprises: S1: The passenger flow line, air flow and outdoor meteorological field are fused into the same space-time grid, and the thermal-wet profile of the terminal building is drawn in real time.

[0018] S2: The thermal-wet gradient curvature is calculated between the continuous grids to generate the thermal pulse index map, and the thermal impulse and the wet lag amplitude are calculated for each grid. If the cosine coefficient of the two parameters is higher than the threshold value, the priority regulation weight is marked in the thermal pulse index map.

[0019] S3: The partition enthalpy-wind regulation instruction is automatically generated according to the marked thermal pulse index map, the air supply enthalpy value offset, the air volume transfer path and the fresh air mixing ratio are given at one time, and the regulation is executed after the balance of the supply and return air pressure difference.

[0020] S4: After the execution end completes the regulation, the actual thermal-wet offset is collected through the sentinel sensing layer of the breathing area, the comfort deviation map is formed and is sent back to the analysis module.

[0021] S5: The analysis module corrects the calculation smoothing coefficient of the heat flux and the moisture amplitude with the comfort deviation map, and then refreshes the grid initial value of the next period, so that the subsequent heat pulse index map is closer to the on-site heat and moisture dynamic changes.

[0022] In the airport terminal, the passenger flow presents a wave peak flow, resulting in a transient distribution of heat, humidity and carbon dioxide concentration. The air conditioning supply is responsible by the partition unit, while the ventilation is completed by the fresh air unit and the return air pipeline. Both of them need to respond to the load changes synchronously to maintain comfort and energy saving.

[0023] The existing scheme only drives the regulation and control with a single point temperature deviation, ignoring the real-time fluctuations of humidity and air quality. However, step S1 integrates the passenger flow line, air flow and outdoor meteorological field into the same space-time grid, and real-time draws the terminal heat and humidity profile, so as to realize the unified spatial perception basis of heat and humidity disturbance.

[0024] The specific processing technology logic of step S1 is as follows: 1-1. Data acquisition.

[0025] To ensure the real-time and accuracy of the fused data, collect multi-source information from the source to capture the original data of passenger flow behavior, internal air dynamics and external environmental influence in the terminal, so as to avoid information loss or deviation in the subsequent fusion process.

[0026] Collect passenger flow line data, air flow data and outdoor meteorological field data. The passenger flow line data is obtained by installing infrared sensor array in key areas of the terminal, recording the number and residence time of passengers in each space-time grid. The air flow data is obtained by partition wind speed sensor and air conditioning air inlet monitor, recording the wind speed vector and direction in each space-time grid. The outdoor meteorological field data is obtained by external meteorological station sensor, recording temperature, humidity and wind direction and other boundary conditions.

[0027] Through collection, a complete original data set is formed to ensure the space-time correspondence of passenger flow line data, air flow data and outdoor meteorological field data, so that the fusion process is directly based on reliable input for unified processing.

[0028] 1-2. Data fusion.

[0029] In order to project multi-source data to the same reference frame, perform fusion calculation to quantify the comprehensive influence of each data on heat and humidity, avoid spatial inconsistency caused by independent processing, and directly map to the space-time grid.

[0030] The passenger flow line data, air flow data and outdoor meteorological field data collected are fused into the same space-time grid, the space-time grid is a cubic unit divided at fixed intervals in a three-dimensional coordinate system, and the fusion process adopts a vector superposition method: for each space-time grid unit, a fused heat and humidity contribution value is calculated, which is obtained by adding the product of the passenger flow line contribution and the air flow contribution to the outdoor meteorological field contribution, wherein the passenger flow line contribution is the logarithm of the product of the number of passengers and the stay time to quantify the heat dissipation intensity; the air flow contribution is the modulus of the wind speed vector multiplied by the direction cosine to quantify the flow propulsion; and the outdoor meteorological field contribution is the product of the external temperature and humidity difference to quantify the boundary penetration influence.

[0031] Through the fusion calculation, the fused heat and humidity contribution value of each space-time grid unit is generated, the unified quantitative representation of multi-source data is realized, and thus the heat and humidity contour surface can be accurately spatially mapped based on the continuous and calculable grid data.

[0032] 1-3. Heat and humidity contour surface drawing.

[0033] In order to generate a continuous spatial distribution from discrete fused heat and humidity contribution values, the gradient is calculated and interpolated to capture the dynamic trend of heat and humidity changes, thereby avoiding the local blind area caused by relying only on grid point data.

[0034] The heat and humidity contour surface is calculated in real time on the fused space-time grid, and a curved surface interpolation algorithm is used to generate a continuous surface: for adjacent space-time grid units, the heat and humidity gradient is calculated, which is obtained by dividing the difference between the fused heat and humidity contribution values by the Euclidean distance between the grid units, and then multiplying by the cosine value of the included angle between the air flow direction and the grid connection; then, based on all the heat and humidity gradient values, a spline function is used to interpolate to generate a heat and humidity contour surface, which represents the continuous spatial picture of heat and humidity distribution in the form of contour lines.

[0035] Through this drawing method, a continuous heat and humidity contour surface is generated, which accurately reflects the space-time dynamics of heat and humidity distribution in the terminal building, so that the generation of the heat pulse index map can be based on the unified contour surface data to identify the heat and humidity disturbance synchronously.

[0036] After the completion of step S1, a unified heat and humidity contour surface is formed as the input basis for subsequent heat pulse index map generation, ensuring that the calculation of heat propagation rate and humidity decay lag can directly refer to the fused data in the space-time grid, and realizing the accurate spatial mapping of sudden passenger flow and meteorological disturbance in the terminal building.

[0037] Step S2 calculates the heat and humidity gradient curvature between the continuous grids and generates the heat pulse index map, and at the same time, the heat impulse and humidity lag amplitude of each grid are calculated, and if the cosine coefficient of the two parameters is higher than the threshold, the priority adjustment weight is marked in the heat pulse index map, so as to capture the dynamic synergy of heat and humidity disturbance to preferentially identify the spatial area that needs high-intensity adjustment.

[0038] The specific processing technique logic of step S2 is as follows: 2-1. Hot-wet gradient curvature calculation and hot pulse index map generation.

[0039] To quantify the bending degree on the hot-wet contour surface to identify the local intensity of hot pulse propagation, the curvature between consecutive grids is calculated, so as to generate a spatial index map reflecting the rate of hot-wet change, avoiding excessive attention to flat areas.

[0040] The hot-wet gradient curvature between consecutive grids on the hot-wet contour surface is calculated, and for adjacent grid cells, the hot-wet gradient curvature is calculated, which is obtained by taking the absolute value of the difference between the hot-wet gradient between adjacent grid cells and the hot-wet gradient of another adjacent grid cell, divided by the sum of the Euclidean distance between the two grid cells, and then multiplied by the sine value of the grid line angle, wherein the hot-wet gradient is the calculation result of the difference between the hot-wet contribution value divided by the distance multiplied by the direction cosine; then based on all hot-wet gradient curvature values, a grid aggregation method is used to generate a hot pulse index map, and the hot pulse index map represents the pulse intensity distribution of hot-wet change in the form of color scale. Through this calculation and generation, the hot pulse index map is formed, which accurately maps the propagation path of hot-wet disturbance in the terminal building, so that the parameter calculation directly focuses on the high curvature area for focused analysis to improve the perturbation discrimination.

[0041] The hot pulse index map maps the propagation intensity distribution of hot-wet disturbance by quantifying the hot-wet gradient curvature, and its acquisition aims to identify the local pulse area of hot-wet change in the terminal building, so as to provide a spatial reference for adjustment priority, avoid invalid intervention on uniform areas, and ensure the targeted allocation of air conditioning and ventilation resources to improve the overall system response efficiency. The meaning of the hot pulse index map is that it serves as a visualization tool to represent the aggregation results of the bending degree of hot-wet gradient between consecutive grids in the form of color scale or contour, accurately depicting the dynamic path of hot-wet dynamics.

[0042] 2-2. Hot impulse and wet lag amplitude calculation.

[0043] To complement the capture of heat propulsion rate and humidity decay lag, the hot impulse and wet lag amplitude of each grid are calculated, so as to quantify the independent dynamic characteristics of hot-wet impact and avoid disturbance omission caused by a single parameter.

[0044] The hot impulse and wet lag amplitude of each grid are calculated, first, the hot impulse is calculated, which is defined as the integral value of the difference between the current frame and the previous frame of thermal image pixel value to represent the heat increment; then divided by the corresponding passenger flow residence time to obtain the instantaneous heat work; then the heat work is accumulated along the main direction of air flow, which is defined as the path integral of the instantaneous heat work values of multiple consecutive grids to form a single value quantifying the heat propulsion rate, wherein the path integral is accumulated along the differential path length in the direction of air flow.

[0045] The heat impulse is evaluated by accumulating the instantaneous heat work to assess the rate of heat propagation along the airflow direction, and its acquisition aims to capture the dynamic characteristics of the heat increase induced by the passenger flow, thereby complementing the humidity parameter to form an independent quantification of the heat disturbance propagation force, supporting the synchronicity judgment to optimize the adjustment intensity, reduce energy waste, and maintain temperature balance. The meaning of the heat impulse lies in its representation as a single numerical indicator, which is the integral value of the heat increase per unit area divided by the residence time along the main direction of the air conditioning airflow, embodying the rate characteristics of heat propagation.

[0046] Secondly, the humidity lag amplitude is calculated, which is the difference between the maximum value and the average value of the absolute humidity field of two frames, obtaining the local humidity surge; then the remaining humidity decay time is calculated by back calculation with the ventilation prediction curve, defined as the reciprocal of the exponential decay constant fitted by the prediction curve; multiplied by the local humidity surge value to generate a single value.

[0047] The humidity lag amplitude measures the humidity lag effect by multiplying the local humidity surge and the decay time, and its acquisition aims to quantify the response delay of ventilation to humidity fluctuations, thereby combining with the heat parameter to identify the synergistic impact area, achieve accurate perception of humidity disturbance, avoid mutual offset in adjustment, and promote the dual coordination of comfort and energy consumption. The meaning of the humidity lag amplitude lies in its representation as a single numerical indicator, which is the calculation result of the difference between the maximum value and the average value of the absolute humidity field multiplied by the prediction decay time, embodying the lag amplitude of humidity change.

[0048] Through this acquisition, the numerical pair of heat impulse and humidity lag amplitude of each grid is generated, realizing independent quantification of heat and humidity dynamic changes, so that the calculation of the cosine coefficient is based on the synchronicity evaluation of these parameter vectors to enhance the sensitivity of the adjustment logic.

[0049] 2-3. Cosine coefficient calculation and priority adjustment weight labeling.

[0050] To measure the synchronicity of heat impulse and humidity lag amplitude to identify the priority adjustment space, calculate the cosine coefficient of the two parameters and label the weight, thereby highlighting the synergistic impact area in the heat pulse index map and avoiding the dispersion of resources in non-key areas.

[0051] The heat impulse and humidity lag amplitude are constructed into vectors in polar coordinates, and the cosine of the included angle is used as the judgment coefficient. For each grid, the cosine coefficient is calculated by the dot product of the heat impulse vector component and the humidity lag amplitude vector component divided by the product of the heat impulse vector module and the humidity lag amplitude vector module, where the heat impulse vector component is the projection of the heat impulse value along the radial direction of the polar coordinate, and the humidity lag amplitude vector component is the projection of the humidity lag amplitude value along the angular direction of the polar coordinate; if the cosine coefficient is higher than the preset threshold, the priority adjustment weight is labeled in the heat pulse index map, and the priority adjustment weight is superimposed on the corresponding grid of the heat pulse index map in the form of a numerical label.

[0052] Through this calculation and marking, the synchronization of heat and humidity impact is accurately identified, so that the generation of zoned enthalpy-air regulation instructions is optimized for the marked area to improve the overall regulation efficiency.

[0053] The heat impact and humidity lag amplitude are constructed as vectors in polar coordinates, and the cosine of the included angle is used as the judgment coefficient. The process of calculating each grid aims to capture the directional consistency between the two parameters through vector representation, thereby quantifying the degree of coordination of heat and humidity disturbance. Specifically, the heat impact value is projected as the radial component in polar coordinates to reflect the strength dimension of heat advancement, while the humidity lag value is projected as the angular component to reflect the phase characteristics of humidity lag. This vector construction method ensures the geometric expression of the parameters, facilitating subsequent angle analysis and avoiding the relative relationship ignored by simple numerical comparison. By calculating the cosine coefficient, that is, the dot product of the heat impact vector component and the humidity lag vector component divided by the product of their vector lengths, a standardized index is obtained, which ranges from -1 to 1. The higher the positive value, the smaller the vector angle, indicating that the impact direction of heat impact and humidity lag tends to be synchronized, which is used as a threshold judgment basis to mark the priority regulation weight. This calculation method improves the sensitivity of the regulation logic to the coordination of heat and humidity impact, ensuring that the air conditioning and ventilation system only allocates resources to high-synchronization areas in the presence of passenger flow mutations or meteorological disturbances, thereby reducing ineffective regulation operations and optimizing energy utilization and comfort balance.

[0054] After step S2 is processed, the marked heat pulse index map is formed as the input basis for subsequent zoned enthalpy-air regulation instruction generation, ensuring that the calculation of enthalpy value offset, air volume transfer path, and fresh air mixing ratio can directly reference the priority regulation weight in the heat pulse index map, achieving a targeted response to heat and humidity coordinated disturbance in the terminal building.

[0055] Step S3 generates zoned enthalpy-air regulation instructions based on the marked heat pulse index map, which gives the supply air enthalpy value offset, air volume transfer path, and fresh air mixing ratio in one go, and is executed after maintaining the supply and return air pressure difference balance, thereby realizing a unified response strategy for heat and humidity coordinated disturbance to optimize resource allocation.

[0056] The specific processing technology logic of step S3 is as follows: 3-1. Enthalpy value offset generation.

[0057] To adjust the supply air enthalpy value for the heat and humidity impact intensity of the marked area, the offset is calculated based on the heat pulse index map, thereby matching the heat disturbance dominated by heat impact, and avoiding the energy consumption increase caused by temperature overcompensation.

[0058] Based on the annotated thermal pulse index map, the supply air enthalpy offset is generated. For the grid area with priority adjustment weight, the enthalpy offset is calculated by multiplying the thermal impulse by the natural logarithm of the pulse index value. The thermal impulse is the instantaneous heat work accumulated along the airflow direction to quantify the thermal propulsion rate, and the pulse index value is the aggregated result of the thermal and humid gradient curvature to reflect the local intensity. Then, all enthalpy offsets are summarized into the partitioned enthalpy offset command part.

[0059] This calculation and aggregation generates an accurate supply air enthalpy offset, ensuring that enthalpy regulation directly responds to heat-dominant disturbances. This allows the calculation of airflow transfer paths to seamlessly reference the enthalpy offset to coordinate the overall airflow distribution and improve the accuracy of temperature balance.

[0060] 3-2. Calculation of air volume transfer path.

[0061] To achieve dynamic transfer of air volume from low-priority areas to high-priority areas, the transfer path is calculated to balance the air volume distribution in each zone and avoid comfort fluctuations caused by uneven local wind speeds.

[0062] Based on the labeled heat pulse index map, the air volume transfer path is calculated. For adjacent grid areas, if the priority adjustment weight of one grid area is higher than that of another grid area, the transfer path vector is obtained by multiplying the difference in priority adjustment weights by the cosine of the angle between the grid line and the main direction of the air conditioning airflow. The priority adjustment weight is a labeled value based on the cosine coefficient threshold to quantify the adjustment priority. Then, based on all transfer path vectors, the path optimization algorithm is used to generate the air volume transfer path. The air volume transfer path is represented as a vector chain in the form of a redirection sequence of the air volume of the zone.

[0063] This calculation and generation process creates an optimized airflow transfer path, enabling targeted redistribution of air resources. This allows the determination of the fresh air mixing ratio to directly integrate airflow transfer path information to maintain ventilation efficiency and reduce airflow turbulence.

[0064] 3-3. Determining the fresh air mixing ratio.

[0065] To coordinate the introduction of fresh air to cope with humidity disturbances dominated by hygroscopic amplitude, a mixing ratio is determined to synchronize ventilation and air supply, thereby avoiding excessive introduction of fresh air that could disrupt enthalpy balance.

[0066] The fresh air mixing ratio is determined based on the labeled heat pulse index map. For the grid area with priority adjustment weight, the mixing ratio is calculated by dividing the wet hysteresis amplitude by an exponential function value with a negative pulse index value. The wet hysteresis amplitude is a single value of humidity surge multiplied by decay time to quantify the hysteresis amplitude, and the pulse index value is the aggregated result of thermal and humidity gradient curvature to reflect local intensity. Then, all mixing ratios are summarized into the zonal mixing instruction part.

[0067] Through this calculation and summary, the accurate fresh air mixing ratio is generated to ensure the coordination of humidity adjustment and thermal response, so that the differential pressure balance calculation can seamlessly reference the mixing ratio to stabilize the overall air flow circulation and optimize the responsiveness of humidity control.

[0068] 3-4. Differential pressure balance and instruction issuance.

[0069] To prevent the differential pressure imbalance of return air caused by the execution of adjustment instructions, the balance adjustment is performed before issuance to ensure the stable operation of zone units and fresh air units, avoiding the increase of energy consumption caused by air flow reversal.

[0070] After maintaining the differential pressure balance of return air, the zone enthalpy-air adjustment instruction is issued, first integrating the enthalpy offset of supply air, the air volume transfer path, and the fresh air mixing ratio, calculating the differential pressure correction factor, which is the sum of the zone total of enthalpy offset divided by the total number of zones, where the zone total of enthalpy offset is the accumulation of all grid enthalpy offsets to quantify the overall enthalpy change, the vector sum of the air volume transfer path is the length sum of the transfer vector to quantify the air volume redirection scale, and the average value of the fresh air mixing ratio is the arithmetic mean of all grid ratios to quantify the ventilation introduction level; then if the differential pressure correction factor exceeds the preset range, a signal is issued to uniformly adjust the instruction parameters to restore balance, and is issued to the execution end.

[0071] Through this calculation and adjustment, the adjustment instruction issuance of differential pressure balance is realized to ensure the reliability of instruction execution, so that the actual thermal and humidity offset can be collected based on a stable air flow environment for feedback optimization and improve the overall adaptability of the system.

[0072] After the completion of step S3, the zone enthalpy-air adjustment instruction is formed as the input basis for subsequent execution end operations, ensuring that the implementation of enthalpy offset, air volume transfer path, and fresh air mixing ratio can directly respond to the labeling of thermal pulse index map, realizing unified and efficient regulation and control of thermal and humidity disturbance in the terminal.

[0073] Step S4 collects the actual thermal and humidity offset using the sentinel sensing layer of the breathing zone after the adjustment is completed by the execution end, summarizes the comfort deviation map and returns it to the analysis module, thereby realizing real-time feedback of the adjustment effect to correct subsequent calculations, ensuring the closed-loop adaptation of thermal and humidity dynamics.

[0074] The specific processing technology logic of step S4 is as follows: 4-1. Actual thermal and humidity offset collection.

[0075] To verify the execution effect of the zone enthalpy-air adjustment instruction and capture residual disturbance, the actual thermal and humidity offset is collected at the breathing zone position, thereby quantifying the gap with the expected comfort level, avoiding the decline in comfort caused by adjustment deviation accumulation.

[0076] After the completion of the adjustment, the actual heat and humidity deviation is collected by the sentinel sensing layer of the breathing area. For each grid point of the breathing area, the heat and humidity deviation is calculated by subtracting the expected temperature value from the actual temperature value and multiplying the actual humidity value by the exponential function value of the expected humidity value, where the actual temperature value is the current temperature measured by the sentinel sensor to reflect the heat state after adjustment, the expected temperature value is the target temperature corresponding to the enthalpy deviation as a reference, the actual humidity value is the current humidity measured by the sentinel sensor to reflect the humidity state after adjustment, and the expected humidity value is the target humidity corresponding to the fresh air mixing ratio as a reference. Then all the heat and humidity deviations are taken as the original deviation data set.

[0077] The accurate actual heat and humidity deviation data set is generated by this process, ensuring that the deviation is quantified and integrated into both heat and humidity dimensions, so that the summary of the comfort deviation map can directly reference the actual heat and humidity deviation to form the basis of feedback and improve the accuracy of the deviation mapping.

[0078] 4-2. Summary of the comfort deviation map.

[0079] In order to convert discrete deviations into a spatially continuous representation, the actual heat and humidity deviation is summarized into a comfort deviation map, so that the partition deviation distribution can be visualized, and the influence of local blind areas on the overall correction can be avoided.

[0080] Based on the actual heat and humidity deviation data set, the comfort deviation map is summarized, and for adjacent grid points, the deviation connectivity value is calculated by adding the heat and humidity deviation of one grid point to the heat and humidity deviation of another grid point multiplied by the sine value of the angle between the connecting line and the air volume transfer path direction, where the heat and humidity deviation is the exponential adjustment value of the actual and expected heat and humidity difference to quantify the local deviation. Then, based on all the deviation connectivity values, a surface fitting algorithm is used to generate the comfort deviation map, which represents the continuous spatial distribution of heat and humidity deviation in the form of a color scale surface.

[0081] By this process, a complete comfort deviation map is formed, which accurately maps the deviation pattern after adjustment in the terminal building, so that the map return can directly provide the feedback data required by the analysis module to optimize parameter correction and enhance the stability of closed-loop control.

[0082] 4-3. Comfort deviation map return.

[0083] In order to close-loop transmit feedback information, the comfort deviation map is returned to the analysis module, so as to support dynamic adjustment of the calculation of heat surge and humidity hysteresis, and avoid the disconnection between the prediction model and the field.

[0084] The generated comfort deviation map is sent back to the analysis module. First, the integrity of the deviation map is verified by checking the coverage of all grid points to ensure that there are no missing areas. Then, the comfort deviation map is packaged in a digital package, including the color step surface data and offset metadata, and sent back to the analysis module. Through this verification and return, reliable transmission of feedback information is realized, ensuring that the analysis module can seamlessly reference the comfort deviation map to correct the calculation of the smoothing coefficient, thereby improving the fit of the thermal pulse index map to the on-site thermal and moisture dynamics and improving the system's adaptability to disturbances.

[0085] After step S4 is completed, the comfort deviation map is formed as the input basis for the subsequent analysis module correction, ensuring that the smoothing coefficient adjustment of the thermal impulse and moisture hysteresis calculation can directly respond to the actual offset, realizing closed-loop optimization of the adjustment effect in the terminal building.

[0086] Step S5 corrects the calculation of the smoothing coefficient of the thermal impulse and moisture hysteresis through the analysis module with the comfort deviation map, and then refreshes the next period grid initial value, so that the subsequent thermal pulse index map is closer to the on-site thermal and moisture dynamics, thereby realizing feedback closed-loop adaptive optimization to improve the response accuracy to sudden disturbances.

[0087] The specific processing technology logic of step S5 is as follows: 5-1. Calculate the smoothing coefficient correction.

[0088] To integrate the actual adjustment feedback to adjust the sensitivity of parameter calculation, the calculation of the smoothing coefficient of the thermal impulse and moisture hysteresis is corrected with the comfort deviation map, thereby reducing the prediction error and avoiding adjustment errors caused by continuous deviation.

[0089] The analysis module corrects the calculation of the smoothing coefficient of the thermal impulse and moisture hysteresis with the comfort deviation map. First, for the thermal impulse calculation smoothing coefficient, the initial smoothing coefficient is multiplied by the deviation value of the corresponding grid in the comfort deviation map divided by the global maximum deviation value of the comfort deviation map, where the initial smoothing coefficient is a preset empirical value to control the filtering strength of the thermal impulse calculation, the deviation value of the corresponding grid in the comfort deviation map is the surface fitting result of the thermal and moisture offset to quantify the actual and expected deviation, and the global maximum deviation value of the comfort deviation map is the peak value of all grid deviations to normalize the correction amplitude. Secondly, for the moisture hysteresis calculation smoothing coefficient, the initial smoothing coefficient is multiplied by the exponential function value of the deviation value of the corresponding grid in the negative comfort deviation map divided by the global average deviation value of the comfort deviation map, where the initial smoothing coefficient is a preset empirical value to control the filtering strength of the moisture hysteresis calculation, and the global average deviation value of the comfort deviation map is the arithmetic mean of all grid deviations to adjust the exponential decay sensitivity. Then, the corrected smoothing coefficient is applied to the parameter calculation.

[0090] The optimized calculation smoothing coefficient is generated by calculation, so that the heat surge and the moisture hysteresis are more suitable for the on-site feedback, and thus the refreshing of the grid initial value can directly refer to the calculation smoothing coefficient to improve the dynamic accuracy of the heat pulse index map and enhance the tracking ability to the disturbance changes.

[0091] 5-2. Refreshing of the grid initial value.

[0092] To bridge the current period feedback and the next period prediction, the grid initial value of the next period is refreshed, so that the space-time grid is initialized to reflect the corrected dynamics and avoid the cumulative error caused by the propagation of historical deviation.

[0093] To refresh the grid initial value of the next period, for each space-time grid unit, the initial value is calculated by adding the current period fusion heat and moisture contribution value to the deviation value of the corresponding grid in the comfort deviation map multiplied by the cosine value of the angle between the grid unit and the air volume transfer path, wherein the current period fusion heat and moisture contribution value is the result of superposition of multiple sources as the baseline, the deviation value of the corresponding grid in the comfort deviation map is the surface fitting result of the heat and moisture offset to quantify the feedback correction, and the cosine value of the angle between the grid unit and the air volume transfer path is a quantitative indicator of the direction influence; then all the initial values are taken as the starting data of the space-time grid of the next period, and input into the fusion process.

[0094] Through the calculation and refreshing, the refreshed grid initial value is generated, the continuous adaptation to the heat and moisture profile is realized, so that the subsequent heat pulse index map can capture the on-site heat and moisture dynamic changes based on the optimized initial value to improve the overall control efficiency and promote the adaptability of the system to the passenger flow and meteorological fluctuations.

[0095] After the step S5 is processed, the corrected calculation smoothing coefficient and the refreshed grid initial value are formed as the input basis for the subsequent cycle, so that the generation of the heat pulse index map can directly respond to the comfort deviation feedback, and the continuous and accurate tracking of the heat and moisture disturbance in the terminal building is realized.

[0096] The above formulas are all dimensionless values, and the formulas are obtained by software simulation of a large amount of data to obtain a formula of the nearest real situation, and the preset parameters in the formula are set by the person skilled in the art according to the actual situation.

[0097] It should be noted that the system of the present application can be deployed in the device itself to realize embedded application, or can be run on PC or other terminal with user interface, so as to meet various hardware environments and use requirements.

[0098] It is apparent that many modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that the application can be practiced otherwise than specifically described, without departing from the spirit and scope of the application. Accordingly, the disclosure of the above embodiments of the application is intended for purposes of illustration only and is not intended to limit the scope of the application.

[0099] It is to be understood that the phraseology or terminology herein is for the purpose of description and not of limitation, such that the terminology or phraseology used herein is not intended to serve as limiting. Instead, it is intended that the scope of the application be governed only by the following claims and equivalents thereof.

[0100] The above description is only specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. An air conditioning control method for airport zoning control, characterized by, The method comprises the following steps: S1: passenger flow lines, air flow and outdoor meteorological field are fused into the same space-time grid, and a terminal building heat and moisture contour is drawn in real time; S2: the heat and moisture gradient curvature is calculated between the continuous grids, and a heat pulse index map is generated, and the heat impulse and the moisture lag amplitude of each grid are calculated, and if the cosine coefficient is higher than the threshold, the priority adjustment weight is marked in the heat pulse index map; S3: the partition enthalpy-wind adjustment instruction is automatically generated according to the marked heat pulse index map, the air supply enthalpy offset, the air volume transfer path and the fresh air mixing ratio are given at one time, and the execution end is kept after the balance of the air supply and return air pressure difference; S4: the actual heat and moisture offset is collected through the breathing area sentinel sensing layer after the execution end completes the adjustment, the comfort deviation map is summarized and sent back to the analysis module; S5: the analysis module corrects the heat impulse and the moisture lag amplitude calculation smoothing coefficient according to the comfort deviation map, and refreshes the next period grid initial value, so that the subsequent heat pulse index map is closer to the heat and moisture dynamic change.

2. The air conditioning control method for airport zoning control according to claim 1, characterized by, Step S1 comprises the following processing logic: Passenger flow line data, air flow data and outdoor meteorological field data are collected, the number and stay time of passengers in the space-time grid unit are recorded by an infrared sensor array, the wind speed vector and direction are recorded by a partition wind speed sensor and an air conditioning air outlet monitor, and the temperature, humidity and wind direction are recorded by an external meteorological station sensor; the passenger flow line data, air flow data and outdoor meteorological field data are fused into the space-time grid unit divided at a fixed interval in a three-dimensional coordinate system, and the fused heat and moisture contribution value is calculated as a unified quantitative representation of multi-source data.

3. The air conditioning control method for airport zoning control according to claim 2, characterized by, Step S1 further comprises the following processing logic: The heat and moisture gradient is calculated on the fused space-time grid unit, the heat and moisture contour is generated by using a spline function interpolation based on the heat and moisture gradient value, and the heat and moisture contour represents the continuous space view of the heat and moisture distribution in the terminal building in the form of an isogram.

4. The air conditioning control method for airport zoning control according to claim 3, characterized by, Step S2 comprises the following processing logic: The heat and moisture gradient curvature is calculated between the continuous grids on the heat and moisture contour, the heat pulse index map is generated by using a grid aggregation method to represent the pulse intensity distribution of the heat and moisture change in the form of a color scale; the heat impulse and the moisture lag amplitude of each grid are calculated as quantitative indexes of the heat advance rate and the humidity decay lag; the heat impulse and the moisture lag amplitude are constructed into a vector in a polar coordinate, the cosine coefficient is calculated as a judgment coefficient, and if the cosine coefficient is higher than the threshold, the priority adjustment weight is marked in the heat pulse index map in the form of a numerical label superimposed on the corresponding grid.

5. The air conditioning control method for airport zoning control according to claim 4, characterized by, Step S2 further comprises the following processing logic: The heat impulse acquisition logic first calculates the total heat increase per unit area by difference between two infrared thermal images to quantify the heat change amplitude, then calculates the instantaneous heat work by dividing the corresponding passenger flow stay time to reflect the heat dissipation rate, and finally forms a single numerical index by accumulating the instantaneous heat work along the main direction of the air conditioning air flow to reflect the dynamic characteristics of the heat advance.

6. The air conditioning control method for airport zoning control according to claim 4, characterized by, Step S2 further comprises the following processing logic: The moisture lag amplitude acquisition logic first determines the local humidity sudden rise degree by extracting the difference between the maximum value and the average value from two absolute humidity fields, then estimates the lag persistence by back calculating the remaining humidity decay time based on the ventilation and air exchange prediction curve, and finally generates a single numerical index by multiplying the local humidity sudden rise value to characterize the lag amplitude of the humidity fluctuation.

7. The air conditioning control method for airport zoning control according to claim 4, characterized by, Step S3 comprises the following processing logic: According to the labeled heat pulse index map, a supply enthalpy offset is generated to match the heat disturbance dominated by heat impulse, a air volume transfer path is calculated to realize the dynamic transfer of air volume from low priority areas to high priority areas and balance the partition air volume distribution, a fresh air mixing ratio is determined to coordinate the humidity disturbance dominated by humidity hysteresis and synchronize ventilation and supply air, and a differential pressure correction factor is integrated with the supply enthalpy offset, the air volume transfer path and the fresh air mixing ratio calculation to keep the supply and return air pressure difference balanced, and then the partition enthalpy-air regulation instructions are issued to the execution end after the balance.

8. The air conditioning control method for airport zoning control according to claim 7, characterized by, Step S4 includes the following processing logic: After the execution end completes the adjustment, the actual heat and humidity offset is collected through the breathing zone sentinel sensing layer to quantify the difference from the expected comfort level and verify the execution effect, the actual heat and humidity offset is summarized into a comfort deviation map to visualize the partition deviation distribution and map the adjusted pattern, and the comfort deviation map is sent back to the analysis module to transmit feedback information and support dynamic adjustment of heat impulse and humidity hysteresis calculation.

9. The air conditioning control method for airport zoning control according to claim 8, characterized by, Step S5 includes the following processing logic: The analysis module corrects the calculation smoothing coefficient of heat impulse and humidity hysteresis with the comfort deviation map to integrate adjustment feedback and adjust parameter calculation sensitivity, refreshes the next time period grid initial value to bridge the current feedback and the next prediction and initializes the space-time grid, ensures that the subsequent heat pulse index map is close to the field heat and humidity dynamic change and improves the response accuracy to sudden disturbance.

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