Air conditioner condensate water recovery type fresh air pre-cooling method and system in high-humidity area

Abstract

The invention provides an air conditioner condensate water recovery type fresh air pre-cooling method and system in a high-humidity area. According to the method, air conditioner condensate water temperature data in a high-humidity area are collected, and periodic gradient fluctuation characteristics of the air conditioner condensate water temperature data are analyzed to obtain a cooling capacity generation rule; condensate water is guided into a phase change cold storage module, cold storage state parameters are generated based on material volume deformation, and a fresh air pre-cooling demand sequence is generated by synchronizing indoor personnel density changes; and when the refrigerating capacity is attenuated, a condensate water film driven by fresh air flow is triggered to evaporate and strengthen heat exchange, the cold capacity distribution proportion is calculated, an energy release threshold value is corrected based on a fresh air outlet deviation value, cold capacity is released in batches through a multi-stage control system, finally, a reference value is reversely calibrated, phase change balance is maintained, and closed-loop control is achieved. Energy-saving closed-loop control over condensate water recovery and dynamic cold distribution is achieved, the energy efficiency of an air conditioning system in a high-humidity area and the indoor environment comfort degree are remarkably improved, and the fresh air pre-cooling effect is synchronously optimized.

Description

Technical Field

[0001] The present application relates to the technical field of heating, ventilation and air conditioning (HVAC) energy conservation and sustainable water resource utilization, and in particular to a fresh air pre-cooling method and system for air conditioning condensate recovery in high humidity areas. Background Art

[0002] In tropical, subtropical coastal or rainforest areas with high temperatures and high humidity year-round (such as southern China and Southeast Asia), building air-conditioning systems need to process outdoor fresh air with high sensible heat and a large amount of latent heat (wet load). The energy consumed in processing fresh air (pre-cooling and dehumidification) usually accounts for 20%-40% of the total energy consumption of the air-conditioning system. At the same time, when the air conditioner is in cooling operation, it will produce condensed water with a relatively low temperature (usually 10-18°C). The cooling capacity contained in this cold water is directly discharged and wasted in traditional systems. Therefore, there is an urgent need to develop an automated device that can efficiently recycle the cooling energy of air-conditioning condensed water to pre-cool the fresh air, thereby significantly reducing the energy consumption of fresh air processing and saving water resources.

[0003] An advanced solution currently addressing this need is a composite condensate recovery and pre-cooling device based on a combination of a plate heat exchanger and a spray system. The core process of this solution is as follows: first, the low-temperature condensate generated by the air conditioner is collected; the outdoor fresh air first flows through the air side channel of a plate heat exchanger; the stored condensate is circulated through the other side channel of the plate heat exchanger by a water pump, and indirect sensible heat exchange is carried out with the incoming air through the metal plate wall inside the heat exchanger, thereby initially cooling the fresh air; then, the fresh air that has undergone preliminary cooling enters a spray humidification section, where another portion of the condensate is atomized and sprayed into the fresh air flow through a high-pressure nozzle; in an environment with high relative humidity, the atomized condensate partially evaporates, absorbing heat using the latent heat of evaporation, further reducing the fresh air temperature (close to the wet-bulb temperature); the system is equipped with a temperature and humidity sensor and a control unit to adjust the condensate flow and spray volume according to real-time operating conditions.

[0004] Although this composite condensate recovery and pre-cooling solution utilizes the cooling capacity of condensate, it has significant defects: in a high temperature and high humidity environment, when the outdoor air is close to saturation, the evaporation efficiency of the condensate in the spray section drops sharply, resulting in minimal secondary cooling effect, and may even form entrained water droplets due to incomplete evaporation, interfering with the normal operation of subsequent air-conditioning equipment; at the same time, the condensate itself may contain dust, microorganisms or pipe corrosion impurities, and directly atomizing and spraying it poses the risk of polluting the quality of fresh air, breeding biological pollutants and clogging subsequent equipment; in addition, the solution integrates multiple components such as condensate collection and storage, plate heat exchangers, water pumps, spray systems and precision control systems. The system structure is complex, which not only increases the cost and difficulty of installation and maintenance, but its complex control strategy also faces challenges in precise implementation under actual changeable hot and humid climate conditions. Summary of the Invention

[0005] The present application provides a method and system for pre-cooling fresh air with air conditioning condensate recovery in high humidity areas, which is used to solve the problems in the prior art of low spray evaporation efficiency in high humidity environments, resulting in poor pre-cooling effect or even failure, the risk of water pollution and easy clogging of subsequent equipment by direct atomization of condensate, and the complex structure, difficult control, and high installation and maintenance costs of the composite pre-cooling system.

[0006] In a first aspect, the present application provides a fresh air pre-cooling method for air conditioning condensate recovery in high humidity areas, comprising:

[0007] Collecting temperature data of air conditioning condensate in high-humidity areas, analyzing the periodic gradient fluctuation characteristics in the temperature data to obtain the cooling capacity generation pattern caused by intermittent operation of the air conditioner;

[0008] The air conditioning condensate is introduced into a phase change cold storage module, a cold storage state parameter is generated based on the volume deformation of the phase change material in the phase change cold storage module, and a fresh air pre-cooling demand sequence synchronized with the change in indoor occupant density is generated in combination with the cold energy generation law;

[0009] When the gradient fluctuation characteristic shows a trend of attenuation of the air conditioning cooling capacity, a condensed water film evaporation enhancement heat exchange process driven by the residual pressure of the fresh air flow is triggered, and the cooling capacity allocation ratio of the fresh air path is calculated based on the correlation between the cold storage state parameter and the demand sequence;

[0010] Obtaining a deviation value of the actual pre-cooling effect at the fresh air outlet, and correcting the critical energy release activation threshold of the phase change cold storage module based on the deviation value when a preset time point is reached, while simultaneously releasing cold energy to the fresh air path in batches through a multi-stage control system in combination with the cold energy distribution ratio;

[0011] The detection reference value of the cold storage state parameter is reversely calibrated according to the action parameters of the multi-stage control system, and the phase change equilibrium state of the phase change cold storage module is synchronously maintained to complete the closed-loop control process of the fresh air pre-cooling method of air conditioning condensate recovery in high humidity areas.

[0012] Optionally, when the gradient fluctuation characteristic shows a trend of attenuation of the air conditioner cooling capacity, a condensed water film evaporation enhanced heat exchange process driven by the residual pressure of the fresh air flow is triggered, and the cooling capacity distribution ratio of the fresh air path is calculated based on the correlation between the cold storage state parameter and the demand sequence, including:

[0013] Monitoring the temperature drop data of the cooling start-up section in the gradient fluctuation feature, and generating a cooling attenuation signal when the temperature drops of three consecutive cooling start-up sections are lower than a preset proportional value of the historical average value for the same period;

[0014] In response to the cooling attenuation signal, the fiber carrier layer unfolded by the roller shutter mechanism on the inner wall of the fresh air duct of the air conditioner is activated, and the condensed water of the air conditioner is transported to the surface of the fiber carrier layer through the guide groove, and the gas pressure generated by the fresh air flow is used to increase the rate at which water molecules are separated from the surface of the fiber carrier layer;

[0015] Reading the numerical cold storage state parameter output by the phase change cold storage module in real time, and simultaneously reading the value of the fresh air pre-cooling demand at the current moment in the demand sequence in real time, performing an arithmetic operation on the cold storage state parameter and the value to obtain a basic ratio;

[0016] The pre-stored evaporation compensation coefficient is retrieved, and the proportional coefficient of the instantaneous cooling demand borne by the fresh air system is written into the control actuator as the cooling distribution ratio of the fresh air path.

[0017] Optionally, when a preset time point is reached, the critical energy release activation threshold of the phase change cold storage module is corrected based on the deviation value, and the cold energy is released to the fresh air path in batches through a multi-stage control system in combination with the cold energy distribution ratio, including:

[0018] Calculate the deviation between the total amount of cooling capacity actually released and the total amount of cooling capacity required at the preset fixed time point each day;

[0019] Analyze the positive or negative value of the deviation value to adjust the critical energy release activation threshold of the phase change cold storage module: increase or decrease;

[0020] The cooling capacity distribution ratio is input into the shunt regulator in the multi-stage control system and the parallel cooling capacity delivery valve opening is controlled by the shunt regulator. The valves are opened in batches according to the order of the cooling capacity delivery valve numbers to release the cooling capacity to the fresh air path, and the release time of each batch is fixed.

[0021] Optionally, the detection reference value of the cold storage state parameter is reversely calibrated according to the action parameter of the multi-stage control system, and the phase change equilibrium state of the phase change cold storage module is synchronously maintained to complete the closed-loop control process of the fresh air pre-cooling method with condensate recovery for air conditioning in high humidity areas, including:

[0022] Recording the opening duration and opening parameters of each branch regulating valve in the multi-stage control system, and calculating the actual total output of cooling capacity based on the opening duration and the opening parameters;

[0023] Reversely comparing the actual total output with a volume deformation detection value of the phase change material in the phase change cold storage module: when the total output of cold energy is higher than a preset detection value, increasing a detection reference value of a cold storage state parameter; and when the total output of cold energy is lower than the preset detection value, decreasing the detection reference value of the cold storage state parameter;

[0024] By changing the interval time of the cooling release batches, the temperature difference between the inside and outside of the phase change material is stabilized within the phase change equilibrium range. When the correction of the detection reference value is completed and the temperature difference meets the standard, it is determined that the closed-loop control process of the fresh air pre-cooling method with condensate recovery of air conditioning in high humidity areas is completed.

[0025] Optionally, analyzing the periodic gradient fluctuation characteristics in the temperature data to obtain a cooling capacity generation rule caused by intermittent operation of the air conditioner includes:

[0026] Continuously record the temperature data of condensed water at the air conditioner drain outlet, and divide the temperature data into continuous data intervals of equal length;

[0027] The temperature drop starting point located in each equal-length data interval is used as the air conditioner start time, and the temperature rise ending point located is used as the air conditioner shutdown time;

[0028] Calculating the temperature difference between adjacent starting and ending points, and using the temperature difference as the theoretical cooling capacity value of the air conditioner per unit operating cycle;

[0029] Calculating a proportional coefficient of theoretical cooling capacity values ​​in adjacent intervals, and determining that the air conditioner has entered a cooling capacity attenuation stage when the value of the proportional coefficient is less than a preset proportional value of the historical average coefficient for three consecutive times;

[0030] The number of times the air conditioner is started and the duration thereof in a unit time window are counted to generate a time distribution curve of cooling capacity generation, and the time distribution curve is analyzed to ultimately obtain a cooling capacity generation pattern caused by the intermittent operation of the air conditioner.

[0031] Optionally, generating a cold storage state parameter based on the volume deformation of the phase change material in the phase change cold storage module includes:

[0032] The volume deformation signal is collected in real time through the contact deformation sensor array on the outer wall of the phase change cold storage module;

[0033] Convert the deformation signal amplitude into deformation reference value;

[0034] A corresponding relationship table between the rate of change of the deformation reference amount and the rate of change of temperature is established, and a deviation between the two is calculated based on the relationship table. When the deviation exceeds a threshold, a sensor calibration mode is activated, and the deviation is reversely calibrated.

[0035] When the phase change material in the phase change cold storage module is in a solid-liquid mixed state, the current deformation reference amount is mapped to a cold storage state parameter according to the calibrated deviation.

[0036] Optionally, combining the cooling capacity generation rule to synchronously generate a fresh air pre-cooling demand sequence synchronized with the change in indoor occupant density includes:

[0037] The infrared sensing device collects the density data of people in the room every minute, and generates a corresponding time curve based on the density data;

[0038] By analyzing the time curve, a corresponding density value interval is obtained, and the density value interval is mapped to a standard fresh air pre-cooling demand level, wherein the demand level includes three levels: high, medium and low;

[0039] Reading the peak period in the cooling generation law, and locating the peak period in the time curve where the cooling output intensity exceeds a certain percentage of the peak value;

[0040] During the peak period, converting the minute-by-minute density data into a demand tag sequence with a time stamp;

[0041] When it is detected that the demand level is high for three consecutive periods, a cooling preload identification symbol is added before the corresponding period of the demand marking sequence to obtain a marked fresh air precooling demand sequence synchronized with the change of indoor occupant density.

[0042] In a second aspect, the present application provides a fresh air pre-cooling system for air conditioning condensate recovery in high humidity areas, comprising:

[0043] An acquisition module is used to collect temperature data of air conditioning condensate in high-humidity areas, analyze the periodic gradient fluctuation characteristics in the temperature data, and obtain the cooling capacity generation pattern caused by the intermittent operation of the air conditioner;

[0044] a generation module for introducing the air conditioning condensate into a phase change cold storage module, generating a cold storage state parameter based on the volume deformation of the phase change material in the phase change cold storage module, and generating a fresh air pre-cooling demand sequence synchronized with changes in indoor occupant density in combination with the cold energy generation law;

[0045] an enhancement module, configured to trigger, when the gradient fluctuation characteristic indicates a trend of attenuation of the air conditioner's cooling capacity, an enhanced heat exchange process by evaporating a condensed water film driven by the residual pressure of the fresh air flow, and calculate a cooling capacity allocation ratio for the fresh air path based on a correlation between the cold storage state parameter and the demand sequence;

[0046] a release module, configured to obtain a deviation value of the actual pre-cooling effect at the fresh air outlet, and to modify the critical energy release activation threshold of the phase change cold storage module based on the deviation value when a preset time point is reached, while simultaneously releasing the cold energy to the fresh air path in batches through a multi-stage control system in combination with the cold energy distribution ratio;

[0047] The calibration module is used to reversely calibrate the detection reference value of the cold storage state parameter according to the action parameters of the multi-stage control system, synchronously maintain the phase change equilibrium state of the phase change cold storage module, and complete the closed-loop control process of the air conditioning condensate recovery fresh air pre-cooling method in high humidity areas.

[0048] In a third aspect, the present application provides a computing device comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a fresh air pre-cooling method for air conditioning condensate recovery in high-humidity areas as described in the first aspect above.

[0049] In a fourth aspect, the present application provides a computer storage medium storing a computer program. When the computer program is executed by a computer, it implements a fresh air pre-cooling method for air conditioning condensate recovery in high humidity areas as described in the first aspect.

[0050] This application accurately captures the intermittent operation rules of air conditioners and the dynamics of cooling generation by real-time analysis of the periodic gradient fluctuation characteristics of condensate water temperature data; by introducing condensate into the phase change cold storage module and generating cold storage state parameters based on the material volume deformation, the fresh air pre-cooling demand sequence is synchronously constructed in combination with the changes in personnel density to achieve dynamic matching of cooling reserve and cooling demand; by triggering airflow to drive thin film evaporation to enhance heat exchange when the cooling capacity is detected to be attenuated, and by associating the cold storage state with the demand sequence to calculate the cooling distribution ratio, the bottleneck of evaporation efficiency in high humidity environment is broken through and the coordinated distribution of cold sources is optimized; by regularly correcting the energy release threshold based on the fresh air outlet pre-cooling deviation, the cooling is released in batches in combination with the distribution ratio, and the cooling fluctuation is adaptively suppressed; by reversely calibrating the cold storage state detection benchmark and maintaining phase change balance, the measurement error is eliminated and the long-term stable operation of the system is guaranteed, ultimately forming a closed-loop control.

[0051] Furthermore, the core subordinate step predicts the attenuation trend by monitoring the temperature drop in the refrigeration startup section, triggering the expansion of the fiber carrier layer and the enhancement of the evaporation of the condensed water film, and using the fresh air flow pressure to improve the evaporation efficiency in a high-humidity environment; the basic ratio is obtained by real-time calculation of the cold storage state and the pre-cooling demand value, and the cooling capacity distribution ratio is dynamically generated in combination with the evaporation compensation coefficient, realizing the precise coordinated control of phase change cold storage and evaporative cooling, and significantly reducing the dependence on complex sensors.

[0052] These and other aspects of the present application will become more readily apparent from the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0054] Figure 1A flow chart of a fresh air pre-cooling method for air conditioning condensate recovery in high humidity areas provided by the present application is shown;

[0055] Figure 2 A schematic diagram of a scenario of a fresh air pre-cooling method for air conditioning condensate recovery in high humidity areas provided by the present application is shown;

[0056] Figure 3 The present invention shows a schematic structural diagram of a fresh air pre-cooling system for air conditioning condensate recovery in high humidity areas;

[0057] Figure 4 A schematic structural diagram of a computing device provided by the present application is shown. DETAILED DESCRIPTION

[0058] In order to enable people skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0059] In some of the processes described in the specification and claims of this application and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this document or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any order of execution. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit "first" and "second" to being different types.

[0060] In coastal areas or rainforests, where temperatures are high and humidity year-round, air conditioners consume significant amounts of electricity to cool and dehumidify incoming air. One energy-saving approach is to recycle the cold condensate produced by air conditioners to pre-cool the incoming air. The current mainstream approach is to first cool the incoming air through a metal water-cooled radiator, then spray the condensate mist directly on it for secondary cooling. However, this solution has three significant drawbacks: First, in hot and humid weather, the sprayed condensate mist is difficult to evaporate, significantly reducing the pre-cooling effect. Water droplets may even be blown into the air conditioner, affecting operation. Second, while the condensate may appear clean, it can actually contain dust, bacteria, or pipe contaminants. Spraying it onto incoming air can contaminate the air and clog air conditioner components. Third, the entire system is complex, requiring a water tank, pump, radiator, spray device, and complex controller, resulting in high installation and maintenance costs and cumbersome operation.

[0061] The present invention proposes a new method for recycling condensed water, which is smarter and cleaner. The core lies in two key improvements: first, by analyzing the natural changes in the temperature of the condensed water to understand the state of the air conditioning refrigeration, and then the condensed water is introduced into an intelligent cold storage box (phase change cold storage module), which can sense its own cold reserve in real time and predict the future demand for fresh air pre-cooling based on the changing trend of the number of people in the room; second, when the system detects that the air conditioning refrigeration capacity begins to weaken, it will automatically start a high-efficiency water film cooling mechanism - spreading a special water-absorbing fiber layer in the fresh air duct, evenly spreading the condensed water into a thin layer of water film, and cleverly using the natural airflow force of the air conditioning supply itself to greatly accelerate the evaporation rate of the water film and quickly absorb the heat of the fresh air. Most importantly, the system will dynamically calculate how much cold is stored in the intelligent cold storage box and how much cold the fresh air currently needs, and intelligently allocate the most appropriate combination ratio. The entire process can also automatically learn and adjust to keep the system running stably. In this way, we have effectively solved the old problem: thin film evaporation is less affected by humidity and can effectively cool down even on hot and humid days; no longer spraying water mist naturally eliminates air pollution and equipment blockage; the system structure is also greatly simplified, making it easier to manufacture, install and maintain.

[0062] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0063] Figure 1 The present invention provides a flowchart of a method for pre-cooling fresh air with condensed water recovery in high humidity areas. Figure 1 As shown, the method includes:

[0064] 101. Collect temperature data of air conditioning condensate in high humidity areas, analyze periodic gradient fluctuation characteristics in the temperature data, and obtain cooling energy generation patterns caused by intermittent operation of the air conditioner;

[0065] Optionally, step 101 may specifically include the following steps:

[0066] 1011. Continuously record temperature data of condensed water at the air conditioner drain outlet, and divide the temperature data into continuous data intervals of equal length;

[0067] 1012. The temperature drop starting point located in each equal-length data interval is used as the air conditioner start time, and the temperature rise ending point located is used as the air conditioner stop time;

[0068] 1013. Calculate the temperature change difference between adjacent start and end points, and use the temperature change difference as the theoretical cooling capacity value of the air conditioner per unit operation cycle;

[0069] 1014. Calculate a proportional coefficient of theoretical cooling capacity values ​​in adjacent intervals, and determine that the air conditioner has entered a cooling capacity attenuation stage when the proportional coefficient is less than a preset proportional value of a historical average coefficient for three consecutive times;

[0070] 1015. Count the number of times the air conditioner is started and the duration thereof within a unit time window to generate a time distribution curve of cooling capacity, and analyze the time distribution curve to ultimately obtain a cooling capacity generation pattern caused by intermittent operation of the air conditioner.

[0071] In the above scheme, condenser water temperature data is first continuously collected by a temperature sensor and divided into consecutive equal-length intervals of 30 minutes. For example, the full-day data for system C is divided into 48 intervals. Next, the temperature series is smoothed within each interval, and turning points are identified by the change in the difference between adjacent temperatures. When the difference changes from non-negative to negative, it is marked as the start-up time, for example, at 11:35, the temperature is 24.0 degrees Celsius. When the difference changes from negative to non-negative, it is marked as the shutdown time, for example, at 11:48, the temperature is 23.9 degrees Celsius. The absolute value of the temperature difference between the start-up and shutdown times is then calculated as the theoretical cooling capacity. For example, the absolute value of 24.0 minus 23.9 is 0.1 degrees Celsius. The proportional coefficient of adjacent cooling capacity values ​​is then calculated. For example, the 16th cooling capacity value of 2.1 degrees Celsius divided by the 15th value of 2.3 degrees Celsius is 0.91. Cooling capacity degradation is determined when the proportional coefficient is less than a threshold of 0.736 (the product of the historical average coefficient and a preset proportional value of 80%) for three consecutive times. Finally, the number of starts and the average single cooling value within the unit time window are counted. For example, from 14:00 to 15:00, there are 3 starts and the average cooling value is 1.93 degrees Celsius. The cooling intensity is calculated as 3 times 1.93, which is 5.79 degrees Celsius per hour. The time distribution curve is drawn to analyze the rules.

[0072] In this embodiment of the present application, in step 1011, a temperature sensor continuously collects condensate temperature data from the air conditioner drain outlet and divides the data into continuous equal-length data intervals of a fixed duration of 30 minutes to form standardized analysis units. In step 1012, the temperature series of each interval is smoothed, and turning points are located by the change in the adjacent temperature difference. When the difference changes from non-negative to negative, it is marked as the start time, such as 11:35, when the temperature is 24.0 degrees Celsius. When the difference changes from negative to non-negative, it is marked as the shutdown time, such as 11:48, when the temperature is 23.9 degrees Celsius. In step 1013, the absolute value of the temperature difference between the start and shutdown times is calculated as the theoretical cooling capacity value, cooling capacity = |start time temperature value - shutdown time temperature value|, for example, cooling capacity = |23.8-23.9| = 0.1°C (Note: the actual typical value is approximately 2-3°C). In step 1014, the adjacent cooling capacity value proportional coefficient Ri = QiQi-1 is calculated, where Qi is the cooling capacity value of the i-th operation. For example, the proportional coefficient of adjacent cooling values ​​on the same day: R 16 =Q 16 / Q 15 =2.1 / 2.3≈0.91, R 17 =Q 17 / Q 16 =1.8 / 2.1≈0.86, R 18 =Q 18 / Q 17 =1.5 / 1.8≈0.83. Taking the historical average coefficient R_avg = 0.92 (the average of the past 100 times) and the preset ratio value 80%, the threshold value = 0.92 × 0.8 = 0.736. Because 0.91 > 0.736, 0.86 > 0.736, and 0.83 > 0.736, the attenuation determination is not triggered. In step 1015, the number of starts and the average single cooling capacity within the unit time window are counted. Cooling intensity = number of starts × average single cooling capacity. For example, there were three starts between 2:00 PM and 3:00 PM (14:05, 14:22, and 14:40), with cooling capacities of 2.1°C, 1.9°C, and 1.8°C, respectively. The average single cooling capacity = (2.1 + 1.9 + 1.8) / 3 = 1.93°C, and the cooling intensity = 3 × 1.93 = 5.79°C / hour. Plotting a full-day curve shows that cooling intensity from 2:00 PM to 4:00 PM is consistently higher than in the morning, indicating that cooling demand is concentrated in the afternoon. Plotting hourly time distribution curves analyzes the cooling capacity generation patterns during intermittent air conditioning operation.

[0073] In actual application, when system C is running all day, the temperature data is divided into 48 30-minute intervals; in a certain interval, after smoothing processing, the temperature is detected to be 24.0 degrees Celsius at the startup time of 11:35 and the temperature is 23.9 degrees Celsius at the shutdown time of 11:48; the absolute value of the single cooling value 24.0 minus 23.9 is calculated to be 0.1 degrees Celsius; the proportional coefficients of adjacent cooling values ​​on that day are 0.91, 0.86, and 0.83, which are all higher than the 80% threshold of 0.736 of the historical average of 0.92, and no attenuation judgment is triggered; statistics show that the system was started three times from 14:00 to 15:00 with an average cooling value of 1.93 degrees Celsius and a cooling intensity of 5.79 degrees Celsius per hour. The curve shows that the cooling demand in the afternoon is significantly higher than that in the morning.

[0074] The closed-loop process of this solution achieves standardized segmentation of temperature data, accurate identification of air conditioning start and stop nodes, quantitative calculation of single cooling effects, early warning of cooling capacity degradation based on dynamic proportional thresholds, and visual analysis of the regularity of cooling generation periods, providing a complete technical path for air conditioning system performance evaluation and operation optimization.

[0075] 102. Introducing the air conditioning condensate into a phase change cold storage module, generating a cold storage state parameter based on the volume deformation of the phase change material in the phase change cold storage module, and combining the cold energy generation rule to synchronously generate a fresh air pre-cooling demand sequence synchronized with the change in indoor occupant density;

[0076] Optionally, step 102 may specifically include the following steps:

[0077] 1021. Collecting volume deformation signals in real time through a contact-type deformation sensor array on the outer wall of the phase change cold storage module;

[0078] 1022. Convert the deformation signal amplitude into a deformation reference value;

[0079] 1023. Establish a corresponding relationship table between the rate of change of the deformation reference value and the rate of change of the temperature, and calculate the deviation between the two based on the relationship table. When the deviation exceeds a threshold, activate the sensor calibration mode and reversely calibrate the deviation.

[0080] 1024. When the phase change material in the phase change cold storage module is in a solid-liquid mixed state, the current deformation reference value is mapped to a cold storage state parameter according to the calibrated deviation.

[0081] 1025. Collect density data of people in the room every minute through an infrared sensing device, and generate a corresponding time curve based on the density data;

[0082] 1026. Obtain a corresponding density value interval by analyzing the time curve, and map the density value interval to a standard fresh air pre-cooling demand level, wherein the demand level includes three levels: high, medium, and low;

[0083] 1027. Read the peak period in the cooling generation rule, and locate the peak period in the time curve where the cooling output intensity exceeds a certain percentage of the peak value;

[0084] 1028. During the peak period, convert the minute-by-minute density data into a demand tag sequence with a timestamp;

[0085] 1029. When it is detected that the demand level is high for three consecutive periods, a cooling capacity pre-loading identification symbol is added before the corresponding period of the demand marking sequence to obtain a marked fresh air pre-cooling demand sequence synchronized with the change of indoor occupant density.

[0086] In the above solution, the phase change thermal storage module uses a special material to store cold energy. This material absorbs or releases cold energy when transitioning between solid and liquid states. The contact deformation sensor array is a set of sensors mounted on the module's outer wall, detecting volume changes. The deformation signal is the physical change data collected by the sensors. The deformation baseline is a normalized value of the deformation signal, with 0 representing a completely liquid state and 100 representing a completely solid state. The change rate correspondence table records the theoretical correspondence between the phase change material's deformation rate and the temperature change rate. Deviation refers to the difference between the measured deformation rate and the theoretical rate. The sensor calibration mode triggers an automatic correction process when the deviation is excessive. The cold storage status parameter is a quantitative value representing the module's current cold storage level, ranging from 0 to 100. The infrared sensor uses infrared scanning to collect occupancy density data. Density data represents the number of people per unit area counted per minute. The time curve shows the change in occupancy density over time. The demand level is the level of fresh air pre-cooling demand, classified by occupancy density, and includes high, medium, and low. Peak hours are when the air conditioning output is at its highest. The demand mark sequence is a time-stamped minute-level demand record. The cooling preload mark is a mark for pre-storing cooling during consecutive high-demand periods.

[0087] In an embodiment of the present application, first, in step 1021, a piezoresistive sensor array attached to the outer wall of the phase change cold storage module is used to collect deformation electrical signals at a frequency of 10 times per second, for example, a voltage value of 0.38 volts is detected; secondly, in step 1022, the original voltage signal is converted into a deformation reference value calculation formula as follows: reference value = (voltage value / maximum range) × 100, where the maximum range 1V corresponds to a completely solid state (100), and 0V corresponds to a completely liquid state (0), for example, a voltage of 0.38V is converted into a reference value of 38; then, in step 1023, a pre-stored change rate correspondence table is called to calculate in real time the deviation rate between the deformation rate ΔS / Δt and the temperature change rate ΔT / Δt, using the formula: deviation rate = ΔSΔt-k×ΔTΔt, where k is the theoretical conversion coefficient. For example, when the measured ΔS / Δt=1.2 / min, ΔT / Δt=-0.3℃ / min, and k=4, the deviation rate=|(1.2-4×(-0.3)) / (4×(-0.3))|=200%; if the deviation rate is greater than 15%, the calibration mode is activated, and 1.2 / min is corrected to 0.9 / min; then, in step 1024, when the temperature detection shows that the phase change material in the phase change cold storage module is in a solid-liquid mixed state, the calibrated reference amount is multiplied by the correction coefficient 0.95 to obtain the cold storage state parameter, for example, 38 multiplied by 0.95 is 36.1; then, in step 1025, the ceiling infrared thermal imager is used to scan the room every minute, and the density of people is counted through image recognition, and a corresponding time curve is generated based on the density data; for example, 0.72 people are detected at 14:00 Square meters; then, in step 1026, density is mapped to a demand level based on a preset threshold, where the demand levels include high, medium, and low. For example, a density below 0.3 people per square meter is low, 0.3 to 0.6 is medium, and above 0.6 is high, with 0.72 people per square meter corresponding to high demand. Then, in step 1027, peak periods, such as 2:00 PM to 4:00 PM, where cooling intensity exceeds 80% of the peak value are extracted from the cooling generation pattern. Then, in step 1028, a timestamp is added to each minute of density data during the peak period to generate a demand tag sequence, such as 2:00 PM high demand. Finally, in step 1029, if the demand level for three consecutive time periods is high, an asterisk is added to the corresponding timestamp to obtain a marked fresh air pre-cooling demand sequence synchronized with changes in indoor occupant density. For example, 2:00 PM high demand is changed to asterisk 14:00 PM high demand.

[0088] In actual application, when the air conditioning system of shopping mall A was running at 14:00, it detected a voltage signal of 0.38 volts from the deformation sensor on the outer wall of the phase change cold storage module. The voltage value was proportionally converted to a deformation reference value of 38 by dividing 0.38 volts by the maximum range of 1 volt and then multiplying by 100. According to the pre-stored relationship table, the deviation rate between the deformation rate of 1.2 units per minute and the temperature drop rate of 0.3 degrees Celsius per minute was calculated to be 200%, triggering the calibration mode and correcting the deformation rate to 0.9 units per minute. When the module was in a solid-liquid mixed state, the calibrated reference value was converted to 38. The standard value 38 is multiplied by the correction coefficient 0.95 to obtain the cold storage state parameter 36.1; at the same time, the population density is measured as 0.72 people per square meter through infrared thermal imaging scanning; according to the density threshold of 0.6 people per square meter, it is determined to be a high-level fresh air pre-cooling demand; based on the cold energy generation law, 14:00 to 16:00 is locked as the cold energy peak period; a demand mark with a timestamp of 14:00 high-level is generated; because a high-level demand is detected for three consecutive minutes from 14:00 to 14:02, an asterisk mark is automatically added in front of the corresponding mark, and finally an asterisk high-level pre-cooling scheduling instruction is formed.

[0089] This solution enables precise monitoring and automatic calibration of the phase-change thermal storage module status, establishes a dynamic hierarchical mapping of occupant density to fresh air demand, intelligently identifies consecutive high-demand periods during peak air conditioning cooling periods and adds pre-cooling markers, providing data support for on-demand pre-cooling of the fresh air system.

[0090] 103. When the gradient fluctuation characteristic indicates a trend of attenuation of the air conditioning cooling capacity, triggering a heat exchange enhancement process using condensed water film evaporation driven by residual pressure of the fresh air flow, and calculating a cooling capacity allocation ratio of the fresh air path based on a correlation between the cold storage state parameter and the demand sequence;

[0091] Optionally, step 103 may specifically include the following steps:

[0092] 1031. Monitor the temperature drop data of the cooling start-up segment in the gradient fluctuation feature, and generate a cooling attenuation signal when the temperature drops of three consecutive cooling start-up segments are lower than a preset proportional value of the historical average value for the same period;

[0093] 1032. In response to the cooling attenuation signal, activate the fiber carrier layer unfolded by the roller shutter mechanism on the inner wall of the fresh air duct of the air conditioner, and transport the condensed water from the air conditioner to the surface of the fiber carrier layer through the guide groove, thereby utilizing the gas pressure generated by the fresh air flow to increase the rate at which water molecules are separated from the surface of the fiber carrier layer;

[0094] 1033. Read the numerical cold storage state parameter output by the phase change cold storage module in real time, and simultaneously read the value of the fresh air pre-cooling demand at the current moment in the demand sequence in real time, and perform an arithmetic operation on the cold storage state parameter and the value to obtain a basic ratio;

[0095] 1034. Retrieve the pre-stored evaporation compensation coefficient, and write the proportional coefficient of the instantaneous cooling demand borne by the fresh air system into the control actuator as the cooling distribution ratio of the fresh air path.

[0096] In the above scheme, the gradient fluctuation feature refers to the periodic downward trend in the air conditioner condensate water temperature data. The cooling startup phase is the period of time during which the temperature continues to drop after the air conditioner is started. The temperature drop amplitude data is the amplitude of the temperature drop during the cooling startup phase. The cooling attenuation signal is the result of determining whether the air conditioner's cooling capacity has decreased. The fresh air duct is the channel for transporting outdoor air. The roller shutter mechanism is a mechanical device that controls the deployment of the fiber carrier layer. The fiber carrier layer is a porous material layer attached to the inner wall of the duct. The gas pressure is the pressure generated by the air flow. The cold storage state parameter is a quantitative value (0-100) of the current cold storage level of the phase change cold storage module. The demand sequence is a time-stamped record of fresh air pre-cooling demand. The base ratio is the result of calculating the cold storage state parameter and the demand value. The evaporation compensation coefficient is a cooling capacity compensation coefficient preset based on historical data. The cooling capacity allocation ratio is the proportion of the cooling capacity demand borne by the fresh air system to the total cooling capacity demand.

[0097] In an embodiment of the present application, first, the temperature drop data of the air conditioning refrigeration startup segment in the gradient fluctuation feature is monitored through step 1031, and a refrigeration attenuation signal is generated when the temperature drop of three consecutive refrigeration startup segments is lower than a preset proportion value of the historical average value for the same period, for example, the detection drop of 1.8 degrees Celsius, 1.7 degrees Celsius, and 1.6 degrees Celsius are all lower than the eighty percent threshold of 2.0 degrees Celsius of the historical average of 2.5 degrees Celsius; secondly, in response to the refrigeration attenuation signal, a roller shutter mechanism on the inner wall of the fresh air duct is activated through step 1032, the fiber carrier layer is unfolded, and the condensed water is transported to the surface of the fiber carrier layer by using the guide groove, and the gas pressure generated by the 3 meters per second fresh air flow is used to accelerate the evaporation of water molecules; then, in step 1033, the numerical cold storage state parameter of the phase change cold storage module, such as 60, is read in real time, the demand level at the current moment in the demand sequence is analyzed, such as high demand is mapped to the value 3, and the basic ratio is calculated, and the basic ratio = cold storage state parameter ÷ demand number. For example, the basic ratio = 60 ÷ 3 = 20; finally, step 1034 is used to retrieve the pre-stored evaporation compensation coefficient 0.4, and the cooling capacity distribution ratio = basic ratio × compensation coefficient, for example, 20 × 0.4 = 8%, and write it into the fresh air system controller.

[0098] In actual application, the air-conditioning system of Shopping Mall A detected three consecutive temperature drops of 1.8 degrees Celsius, 1.7 degrees Celsius and 1.6 degrees Celsius during the cooling startup period, which were lower than the 80% threshold of 2.0 degrees Celsius of the historical average of 2.5 degrees Celsius, triggering a cooling attenuation signal; the fiber carrier layer in the fresh air duct automatically unfolded, and the condensed water formed a thin film through the guide groove, and the airflow of 3 meters per second accelerated evaporation; the cold storage state parameter 60 and the high demand mapping value 3 were read to calculate the basic ratio of 20; combined with the evaporation compensation coefficient of 0.4, a cooling distribution ratio of 8% was generated to control the fresh air system.

[0099] This solution automatically identifies the attenuation of air conditioning cooling capacity and enhances condensed water evaporation. It dynamically calculates the cooling capacity allocation ratio based on the cold storage status and real-time demand, thereby optimizing system energy efficiency.

[0100] 104. Obtain a deviation value of the actual pre-cooling effect at the fresh air outlet, and when a preset time point is reached, modify the critical energy release activation threshold of the phase change cold storage module based on the deviation value. Simultaneously, release the cold energy to the fresh air path in batches through a multi-stage control system in combination with the cold energy distribution ratio;

[0101] Optionally, step 104 may specifically include the following steps:

[0102] 1041. Calculate the deviation between the total amount of cooling capacity actually released and the total amount of cooling capacity required at the preset fixed time point each day.

[0103] 1042. Analyze the positive or negative value of the deviation value to adjust the critical energy release activation threshold of the phase change cold storage module to increase or decrease;

[0104] 1043. Input the cooling capacity distribution ratio into the shunt regulator in the multi-stage control system and control the opening of the parallel cooling capacity delivery valves through the shunt regulator. Open the valves in batches according to the order of the cooling capacity delivery valve numbers to release the cooling capacity to the fresh air path, wherein the release duration of each batch is fixed.

[0105] In the above scheme, the actual pre-cooling effect deviation value refers to the difference between the total amount of cooling capacity released at the fresh air outlet and the total amount of the demand sequence. The preset time point is a fixed daily verification time. The critical energy release activation threshold is the critical parameter value that triggers the phase change thermal storage module to release cooling capacity. The multi-stage control system includes a shunt regulator and a batch control unit for parallel cooling valves. The cooling capacity distribution ratio is the proportion of cooling capacity demand borne by the fresh air path. The shunt regulator is a processor that proportionally controls the valve opening. The cooling capacity delivery valve is an actuator that regulates the cooling capacity flow. Batch release refers to the activation of cooling capacity delivery in time periods according to the valve number sequence.

[0106] In the embodiment of the present application, first, step 1041 is used to calculate the deviation between the actual total amount of cooling capacity released at the fresh air outlet and the total amount of the demand sequence at a preset time point every day, and the formula is: deviation value = (actual value - demand value) ÷ demand value. For example, when the actual cooling capacity is 1000 kcal and the demand is 1200 kcal, the deviation value = (1000-1200) ÷ 1200 = -0.167; secondly, step 1042 is used to adjust the critical energy release activation threshold according to the positive or negative value of the deviation value. When the deviation is negative, the threshold value is lowered, for example, from 50 to 45 to release the cooling capacity in advance, and when the deviation is positive, the threshold value is raised to delay the release; finally, step 1043 is used to input the cooling capacity distribution ratio into the shunt regulator of the multi-stage control system, and the number of valves to be opened is calculated according to the ratio. The valves are opened in batches according to the order of the numbers. For example, if there are 100 valves in total and the distribution ratio is 7%, 7 valves need to be opened, and they are opened in 3 batches: 3 valves are opened in the first batch (No. 1-3), 2 valves are opened in the second batch (No. 4-5), and 2 valves are opened in the third batch (No. 6-7).

[0107] In actual applications, at a preset verification time, such as the end of the daily operating cycle of facility B, air-conditioning system A detects that the actual cooling capacity released is 980 kcal, which is lower than the total demand of 1150 kcal. After calculating the deviation value of negative 0.148, the triggering action is: the critical energy release activation threshold of the cold storage module C is reduced from the baseline value of 50 to 45; the cooling capacity distribution ratio is 7% and the input is input to the shunt regulator D to control the parallel valve group E, of which 7 out of the total 100 are released in three batches. The first batch of valves E1-E3 are opened for 2 minutes, the second batch E4-E5 are opened for 2 minutes, and the last batch E6-E7 are opened for 2 minutes.

[0108] This solution dynamically corrects the threshold of the cold storage module through deviation feedback, combines it with multi-level batch control to achieve precise distribution of cooling capacity and improve fresh air pre-cooling efficiency.

[0109] 105. Reversely calibrate the detection reference value of the cold storage state parameter according to the action parameters of the multi-stage control system, synchronously maintain the phase change equilibrium state of the phase change cold storage module, and complete the closed-loop control process of the air conditioning condensate recovery fresh air pre-cooling method in high humidity areas.

[0110] Optionally, step 105 may specifically include the following steps:

[0111] 1051. Record the opening duration and opening parameters of each branch regulating valve in the multi-stage control system, and calculate the actual total output of cooling capacity based on the opening duration and the opening parameters;

[0112] 1052. Reversely compare the actual total output with the volume deformation detection value of the phase change material in the phase change cold storage module: when the total cooling output is higher than a preset detection value, increase the detection reference value of the cold storage state parameter; when the total cooling output is lower than the preset detection value, decrease the detection reference value of the cold storage state parameter;

[0113] 1053. By changing the interval time of the cooling release batches, the temperature difference between the inside and outside of the phase change material is stabilized within the phase change equilibrium range. When the correction of the detection reference value is completed and the temperature difference meets the standard, it is determined that the closed-loop control process of the air conditioning condensate recovery fresh air pre-cooling method in high humidity areas is completed.

[0114] In the above scheme, the action parameters refer to the operational data of the valve opening time and opening degree (opening and closing degree) in the multi-level control system; the actual output total is the sum of the cold release calculated by the valve parameters; the volume deformation detection value is the volume contraction of the phase change cold storage module due to the cold release; the detection reference value is the reference standard used to judge the cold storage state; the preset detection value is the cold output reference value set according to historical data; the phase change equilibrium state is the state in which the internal temperature distribution of the phase change material is uniform and the energy release is continuous and stable; the batch interval time is the pause time between cold release batches; the phase change equilibrium range is the temperature difference range for maintaining the thermal balance of the material.

[0115] In this embodiment, step 1051 first records the opening duration of each branch control valve in the multi-stage control system, such as valve D1 being open for 2 minutes, and the opening parameter, such as 50% opening. According to the formula: Actual output total = ∑(valve opening × opening duration × unit flow coefficient), where the unit flow coefficient is a valve design parameter. For example, if valve D1 is open for 2 minutes at 50% and the coefficient is 2 kcal / min, the cooling output = 0.5 × 2 × 2 = 2 kcal. Next, step 1052 compares the actual output total, such as 18 kcal, with the volume deformation detection value, such as 15 units. If the output exceeds the preset detection value of 16 kcal, the detection reference value is increased, such as from 60 to 62; if it is below the preset value, the reference value is lowered. Finally, step 1053 adjusts the cooling batch interval, such as from 2 minutes to 3 minutes, to stabilize the temperature difference between the inside and outside of the phase change material within the equilibrium range, such as ±1°C. When the reference value correction is complete and the temperature difference meets the standard, closed-loop control is completed.

[0116] In actual application, the multi-stage control unit of the air-conditioning system A records the action parameters of the valve group D: valve D1 is opened at 50% for 2 minutes, of which the flow coefficient 2 and D2 are opened at 60% for 2 minutes; the total cooling output is calculated by the formula = 0.5×2×2+0.6×2×2=4.4 kcal; the total amount of 4.4 kcal is compared with the volume deformation detection value of 3.8 units of the phase change cold storage module B. Since 4.4 kcal is higher than the preset detection value of 3.5 kcal, the cold storage state parameter detection reference value is raised from 60 to 62; simultaneously, the cooling release batch interval is extended from 2 minutes to 3 minutes, so that the temperature difference between the inside and outside of module B is stabilized at 0.7 degrees Celsius, with the target balance range of ±1 degree Celsius. When the reference value correction is completed and the temperature difference meets the standard, the closed-loop control is completed.

[0117] This solution reversely calibrates the cold storage state detection benchmark value through valve action parameters and dynamically corrects the monitoring accuracy. Combined with the release interval optimization to maintain the thermal balance of the phase change material, this solution achieves closed-loop control of the entire process of condensed water cooling recovery, storage, and release, thereby improving the energy efficiency stability and response accuracy of air-conditioning systems in high-humidity areas.

[0118] Figure 2 The present application provides a scenario diagram of a fresh air pre-cooling method for air conditioning condensate recovery in high humidity areas, such as Figure 2 As shown, a complete embodiment of steps 101 to 105 includes:

[0119] In the application of the condensate recovery fresh air pre-cooling method for the air conditioning system of shopping mall A, first, step 101 is executed to continuously collect condensate temperature data and divide it into 30-minute intervals. In a certain interval, the temperature of 24.0 degrees Celsius at the start time of 11:35 and the temperature of 23.9 degrees Celsius at the shutdown time of 11:48 are identified, and a single cooling capacity value of 0.1 degrees Celsius is calculated. The proportional coefficients of 0.75, 0.72, and 0.70 are monitored for three consecutive times and are lower than the historical average threshold of 0.736 to determine the cooling capacity attenuation. The cooling capacity law curve is generated to show that 14:00 to 16:00 is the peak period; then step 102 is executed to introduce condensate into the phase change cold storage module, and the deformation voltage of 0.38 volts is detected and converted into a reference value of 38. After calibration with a 200% deviation rate, the cold storage state parameter of 36.1 is obtained. At the same time, the infrared scanning personnel density of 0.72 people per square meter is mapped as a high-level demand, and the asterisk-marked 14:00 is generated in combination with the peak period. Advanced demand sequence; then execute step 103 to monitor three consecutive temperature drops of 1.8 degrees Celsius, 1.7 degrees Celsius, and 1.6 degrees Celsius, which are lower than the historical threshold of 2.0 degrees Celsius, triggering a decay signal, starting the fiber layer of the fresh air duct to accelerate evaporation, reading the cold storage parameter 36.1 and the high demand value 3 to calculate the basic ratio 12.03, and applying the compensation coefficient 0.4 to obtain a cooling capacity distribution ratio of 4.81%; then execute step 104 to calculate the actual cooling capacity of 980 kcal and the demand of 1150 kcal at 18:00, with a deviation of -0.148, lowering the critical energy release threshold from 50 to 45, and opening the valve in three batches at a ratio of 4.81% to release cooling capacity; finally, execute step 105 to record the valve opening time of 50% for 2 minutes, calculate the actual output total of 4.4 kcal, which is 3.5 kcal higher than the preset value, raise the detection baseline value to 62, and extend the batch interval to 3 minutes to maintain the temperature difference of 0.7 degrees Celsius within the equilibrium range, completing closed-loop control.

[0120] A complete closed loop is achieved for air conditioning condensate data collection, phase change cold storage status monitoring, personnel demand mapping, refrigeration attenuation response, evaporative enhanced heat exchange, dynamic cold distribution, deviation threshold correction, valve batch control, and parameter reverse calibration. While maintaining the thermal balance of the phase change material, the cold recovery efficiency and energy utilization rate of the air conditioning system in high humidity areas are improved.

[0121] This program Figure 3 The present invention provides a schematic diagram of a fresh air pre-cooling system for air conditioning condensate recovery in high humidity areas. Figure 3 As shown, the system includes:

[0122] The acquisition module 31 is used to collect the temperature data of the air-conditioning condensed water in high humidity areas, analyze the periodic gradient fluctuation characteristics in the temperature data, and obtain the cooling capacity generation law caused by the intermittent operation of the air-conditioning;

[0123] a generation module 32 for introducing the air conditioning condensate into a phase change cold storage module, generating a cold storage state parameter based on the volume deformation of the phase change material in the phase change cold storage module, and generating a fresh air pre-cooling demand sequence synchronized with changes in indoor occupant density in combination with the cold energy generation law;

[0124] an enhancement module 33 for triggering, when the gradient fluctuation characteristic indicates a trend of attenuation of the air conditioning cooling capacity, an enhanced heat exchange process of condensed water film evaporation driven by the residual pressure of the fresh air flow, and calculating a cooling capacity allocation ratio of the fresh air path based on a correlation between the cold storage state parameter and the demand sequence;

[0125] a release module 34 configured to obtain a deviation value of the actual pre-cooling effect at the fresh air outlet, and to modify the critical energy release activation threshold of the phase change cold storage module based on the deviation value when a preset time point is reached, while simultaneously releasing the cold energy to the fresh air path in batches through a multi-stage control system in combination with the cold energy distribution ratio;

[0126] The calibration module 35 is used to reversely calibrate the detection reference value of the cold storage state parameter according to the action parameters of the multi-stage control system, synchronously maintain the phase change equilibrium state of the phase change cold storage module, and complete the closed-loop control process of the air conditioning condensate recovery fresh air pre-cooling method in high humidity areas.

[0127] Figure 3 The high humidity area air conditioning condensate water recovery type fresh air pre-cooling system can be implemented Figure 1 The implementation principles and technical effects of the high-humidity air conditioning condensate recovery fresh air pre-cooling method described in the illustrated embodiment are not further elaborated. The specific manner in which each module and unit performs the operation of the high-humidity air conditioning condensate recovery fresh air pre-cooling system in the above embodiment has been described in detail in the relevant embodiments of the method and will not be further elaborated here.

[0128] In one possible design, Figure 3 The embodiment shown is a high humidity area air conditioning condensate recovery type fresh air pre-cooling system can be implemented as a computing device, such as Figure 4 As shown, the computing device may include a storage component 41 and a processing component 42;

[0129] The storage component 41 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 42 .

[0130] The processing component 42 is used for the above Figure 1 The embodiment provides a fresh air pre-cooling method for air conditioning condensate recovery in high humidity areas.

[0131] The processing component 42 may include one or more processors to execute computer instructions to perform all or part of the steps in the above method. Of course, the processing component may also be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above method.

[0132] The storage component 41 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0133] Of course, a computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0134] The input / output interface provides an interface between the processing component and the peripheral interface module, which can be an output device, an input device, etc.

[0135] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0136] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0137] The present application also provides a computer storage medium storing a computer program, wherein the computer program can achieve the above-mentioned Figure 1 The embodiment shown is a fresh air pre-cooling method for air conditioning condensate recovery in high humidity areas.

[0138] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0139] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0140] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by means of hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A fresh air pre-cooling method for air conditioning condensate recovery in high humidity areas, characterized in that: include: Collecting temperature data of air conditioning condensate in high-humidity areas, analyzing the periodic gradient fluctuation characteristics in the temperature data to obtain the cooling capacity generation pattern caused by intermittent operation of the air conditioner; The air conditioning condensate is introduced into a phase change cold storage module, a cold storage state parameter is generated based on the volume deformation of the phase change material in the phase change cold storage module, and a fresh air pre-cooling demand sequence synchronized with the change in indoor occupant density is generated in combination with the cold energy generation law; When the gradient fluctuation characteristic shows a trend of attenuation of the air conditioning cooling capacity, a condensed water film evaporation enhancement heat exchange process driven by the residual pressure of the fresh air flow is triggered, and the cooling capacity allocation ratio of the fresh air path is calculated based on the correlation between the cold storage state parameter and the demand sequence; Obtaining a deviation value of the actual pre-cooling effect at the fresh air outlet, and correcting the critical energy release activation threshold of the phase change cold storage module based on the deviation value when a preset time point is reached, while simultaneously releasing cold energy to the fresh air path in batches through a multi-stage control system in combination with the cold energy distribution ratio; The detection reference value of the cold storage state parameter is reversely calibrated according to the action parameters of the multi-stage control system, and the phase change equilibrium state of the phase change cold storage module is synchronously maintained to complete the closed-loop control process of the fresh air pre-cooling method of air conditioning condensate recovery in high humidity areas.

2. The method according to claim 1, characterized in that When the gradient fluctuation characteristics show a trend of attenuation of the air conditioning cooling capacity, a heat exchange enhancement process of condensed water film evaporation driven by the residual pressure of the fresh air flow is triggered, and the cooling capacity distribution ratio of the fresh air path is calculated based on the correlation between the cold storage state parameter and the demand sequence, including: Monitoring the temperature drop data of the cooling start-up section in the gradient fluctuation feature, and generating a cooling attenuation signal when the temperature drops of three consecutive cooling start-up sections are lower than a preset proportional value of the historical average value for the same period; In response to the cooling attenuation signal, the fiber carrier layer unfolded by the roller shutter mechanism on the inner wall of the fresh air duct of the air conditioner is activated, and the condensed water of the air conditioner is transported to the surface of the fiber carrier layer through the guide groove, and the gas pressure generated by the fresh air flow is used to increase the rate at which water molecules are separated from the surface of the fiber carrier layer; Reading the numerical cold storage state parameter output by the phase change cold storage module in real time, and simultaneously reading the value of the fresh air pre-cooling demand at the current moment in the demand sequence in real time, performing an arithmetic operation on the cold storage state parameter and the value to obtain a basic ratio; The pre-stored evaporation compensation coefficient is retrieved, and the proportional coefficient of the instantaneous cooling demand borne by the fresh air system is written into the control actuator as the cooling distribution ratio of the fresh air path.

3. The method according to claim 1, characterized in that When a preset time point is reached, the critical energy release activation threshold of the phase change cold storage module is corrected based on the deviation value, and the cold energy is released to the fresh air path in batches through a multi-level control system in combination with the cold energy distribution ratio, including: Calculate the deviation between the total amount of cooling capacity actually released and the total amount of cooling capacity required at the preset fixed time point each day; Analyze the positive or negative value of the deviation value to adjust the critical energy release activation threshold of the phase change cold storage module: increase or decrease; The cooling capacity distribution ratio is input into the shunt regulator in the multi-stage control system and the parallel cooling capacity delivery valve opening is controlled by the shunt regulator. The valves are opened in batches according to the order of the cooling capacity delivery valve numbers to release the cooling capacity to the fresh air path, and the release time of each batch is fixed.

4. The method according to claim 1, wherein The detection reference value of the cold storage state parameter is reversely calibrated according to the action parameters of the multi-stage control system, and the phase change equilibrium state of the phase change cold storage module is synchronously maintained to complete the closed-loop control process of the fresh air pre-cooling method with condensate recovery for air conditioning in high humidity areas, including: Recording the opening duration and opening parameters of each branch regulating valve in the multi-stage control system, and calculating the actual total output of cooling capacity based on the opening duration and the opening parameters; Reversely comparing the actual total output with a volume deformation detection value of the phase change material in the phase change cold storage module: when the total output of cold energy is higher than a preset detection value, increasing a detection reference value of a cold storage state parameter; and when the total output of cold energy is lower than the preset detection value, decreasing the detection reference value of the cold storage state parameter; By changing the interval time of the cooling release batches, the temperature difference between the inside and outside of the phase change material is stabilized within the phase change equilibrium range. When the correction of the detection reference value is completed and the temperature difference meets the standard, it is determined that the closed-loop control process of the fresh air pre-cooling method with condensate recovery of air conditioning in high humidity areas is completed.

5. The method according to claim 1, wherein The periodic gradient fluctuation characteristics in the temperature data are analyzed to obtain the cooling capacity generation pattern caused by the intermittent operation of the air conditioner, including: Continuously record the temperature data of condensed water at the air conditioner drain outlet, and divide the temperature data into continuous data intervals of equal length; The temperature drop starting point located in each equal-length data interval is used as the air conditioner start time, and the temperature rise ending point located is used as the air conditioner shutdown time; Calculating the temperature difference between adjacent starting and ending points, and using the temperature difference as the theoretical cooling capacity value of the air conditioner per unit operating cycle; Calculating a proportional coefficient of theoretical cooling capacity values ​​in adjacent intervals, and determining that the air conditioner has entered a cooling capacity attenuation stage when the value of the proportional coefficient is less than a preset proportional value of the historical average coefficient for three consecutive times; The number of times the air conditioner is started and the duration thereof in a unit time window are counted to generate a time distribution curve of cooling capacity generation, and the time distribution curve is analyzed to ultimately obtain a cooling capacity generation pattern caused by the intermittent operation of the air conditioner.

6. The method according to claim 1, wherein Generating a cold storage state parameter based on the volume deformation of the phase change material in the phase change cold storage module includes: The volume deformation signal is collected in real time through the contact deformation sensor array on the outer wall of the phase change cold storage module; Convert the deformation signal amplitude into deformation reference value; A corresponding relationship table between the rate of change of the deformation reference amount and the rate of change of temperature is established, and a deviation between the two is calculated based on the relationship table. When the deviation exceeds a threshold, a sensor calibration mode is activated, and the deviation is reversely calibrated. When the phase change material in the phase change cold storage module is in a solid-liquid mixed state, the current deformation reference amount is mapped to a cold storage state parameter according to the calibrated deviation.

7. The method according to claim 1, characterized in that In combination with the cooling capacity generation rule, a fresh air pre-cooling demand sequence synchronized with the change in indoor occupant density is generated, including: The infrared sensing device collects the density data of people in the room every minute, and generates a corresponding time curve based on the density data; By analyzing the time curve, a corresponding density value interval is obtained, and the density value interval is mapped to a standard fresh air pre-cooling demand level, wherein the demand level includes three levels: high, medium and low; Reading the peak period in the cooling generation law, and locating the peak period in the time curve where the cooling output intensity exceeds a certain percentage of the peak value; During the peak period, converting the minute-by-minute density data into a demand tag sequence with a time stamp; When it is detected that the demand level is high for three consecutive periods, a cooling preload identification symbol is added before the corresponding period of the demand marking sequence to obtain a marked fresh air precooling demand sequence synchronized with the change of indoor occupant density.

8. A fresh air pre-cooling system with condensed water recovery for air conditioning in high humidity areas, characterized in that: include: Collecting temperature data of air conditioning condensate in high-humidity areas, analyzing the periodic gradient fluctuation characteristics in the temperature data to obtain the cooling capacity generation pattern caused by intermittent operation of the air conditioner; The air conditioning condensate is introduced into a phase change cold storage module, a cold storage state parameter is generated based on the volume deformation of the phase change material in the phase change cold storage module, and a fresh air pre-cooling demand sequence synchronized with the change in indoor occupant density is generated in combination with the cold energy generation law; When the gradient fluctuation characteristic shows a trend of attenuation of the air conditioning cooling capacity, a condensed water film evaporation enhancement heat exchange process driven by the residual pressure of the fresh air flow is triggered, and the cooling capacity allocation ratio of the fresh air path is calculated based on the correlation between the cold storage state parameter and the demand sequence; Obtaining a deviation value of the actual pre-cooling effect at the fresh air outlet, and correcting the critical energy release activation threshold of the phase change cold storage module based on the deviation value when a preset time point is reached, while simultaneously releasing cold energy to the fresh air path in batches through a multi-stage control system in combination with the cold energy distribution ratio; The detection reference value of the cold storage state parameter is reversely calibrated according to the action parameters of the multi-stage control system, and the phase change equilibrium state of the phase change cold storage module is synchronously maintained to complete the closed-loop control process of the fresh air pre-cooling method of air conditioning condensate recovery in high humidity areas.

9. A computing device, characterized in that It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a fresh air pre-cooling method for air conditioning condensate recovery in high humidity areas as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that A computer program is stored, and when the computer program is executed by a computer, the method for pre-cooling fresh air with air conditioning condensate recovery in high humidity areas as described in any one of claims 1 to 7 is implemented.

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