Energy-saving intelligent control method for air conditioning and ventilation of high-space spiral air supply

Abstract

The present application relates to air conditioning technology field, disclose high space spiral air supply air conditioning ventilation energy-saving intelligent control method. The method comprises: real-time acquisition of multi-point temperature and humidity and carbon dioxide concentration parameters; build wet condition state space model; determine the target air supply state point and the equipment dew point; based on energy optimal processing straight line reverse analysis optimal mixed air ratio; combined with the minimum fresh air ratio constraint to generate collaborative control instruction, synchronous adjustment of fresh air valve, return air valve and cold water valve, and shut off the reheating coil. The system comprises a state parameter acquisition module, a modeling module, an optimal mixed air ratio calculation module and a collaborative control instruction generation module. The present application optimizes the mixed air ratio dynamically, eliminates the reheating process, realizes the collaborative optimization of energy saving, precise humidity control and air quality guarantee.

Description

Technical Field

[0001] This invention belongs to the field of air conditioning technology, specifically relating to an intelligent control method for energy-saving ventilation in large spaces with spiral air supply. Background Technology

[0002] Tall buildings (such as stadiums, exhibition centers, and industrial plants) present unique challenges to the airflow organization and energy efficiency control of air conditioning and ventilation systems due to their large internal volume, significant thermal stratification, and the concentration of personnel activity areas in the lower part. Traditional air conditioning systems often use top-down or side-down air supply methods, which are difficult to effectively deliver treated air to personnel activity areas. This can easily lead to over-cooling or overheating of the upper space, while the temperature and humidity in the lower area do not meet the standards, resulting in energy waste and reduced comfort.

[0003] To improve airflow distribution, spiral ventilation technology has been introduced into high-ceilinged spaces. By inducing rotating airflow, it enhances momentum transfer in the vertical direction, thereby improving air delivery efficiency and temperature uniformity. However, existing spiral ventilation systems still follow conventional air conditioning logic in their operation and control, lacking deep coupling with the dynamic load characteristics of high-ceilinged spaces.

[0004] Ventilation energy conservation and control become a significant bottleneck during the transitional seasons (spring and autumn). During this period, outdoor fresh air has favorable temperature and humidity conditions, and theoretically, increasing the fresh air ratio could achieve free cooling and meet indoor air quality requirements. However, existing systems generally use a fixed fresh air to return air mixing ratio, which cannot be dynamically adjusted based on real-time meteorological parameters and indoor load.

[0005] When fresh air and return air are mixed in a fixed ratio, the mixing point often deviates from the ideal path of the air handling process, especially showing significant defects in humidity control: the dew point temperature of the mixed air does not match the settings of the subsequent cooling coils or reheat devices, causing the system to still need to start reheating after dehumidification to meet the supply air temperature requirements, resulting in a "cold first, then hot" cancellation phenomenon. This not only significantly increases energy consumption but also makes it difficult to stably control relative humidity within the design range, affecting indoor environmental quality.

[0006] In existing technologies, some systems attempt to introduce temperature control or CO2 concentration feedback to adjust the fresh air volume, but they do not consider the enthalpy-humidity diagram geometry and dew point constraints in the air heat and humidity treatment process. Fixed air mixing strategies ignore wet-bulb temperature as a key indicator of air cooling potential, failing to maximize the utilization of the natural cooling capacity of fresh air while ensuring dehumidification. Especially during transitional seasons with large diurnal temperature differences and frequent humidity fluctuations, static air mixing ratios can easily cause the air treatment process to repeatedly cross the saturation line, leading to unnecessary reheating and humidification / dehumidification conflicts. Summary of the Invention

[0007] To address the problem in existing large-space air conditioning systems where a fixed fresh air-return air mixing ratio during transitional seasons leads to a deviation of the mixed air state point from the ideal processing path, necessitating cooling, dehumidification, and reheating to offset the heat, resulting in significant energy waste and reduced humidity control accuracy, this invention provides an intelligent energy-saving control method for spiral air conditioning systems in large spaces. This method senses and models the humidity conditions of multiple points in the air conditioning system in real time, dynamically calculating the optimal fresh air-return air mixing ratio with the goal of minimizing energy consumption. This ensures that the mixed air state point precisely falls on the energy-optimal processing path determined by the target supply air state point and the dew point of the coil unit. Thus, while meeting indoor air quality requirements, it eliminates the reheating process during transitional seasons, fundamentally improving system energy efficiency.

[0008] This invention provides a method for intelligent control of energy-saving ventilation in large spaces using spiral air supply air conditioning, the method comprising:

[0009] The system acquires multi-dimensional operating status parameters of the air conditioning system in real time. These parameters include the dry-bulb temperature and relative humidity of the outdoor fresh air, the dry-bulb temperature, relative humidity and carbon dioxide concentration of the indoor return air main, the dry-bulb temperature and relative humidity of the mixed air box, and the dry-bulb temperature and relative humidity of the air supplied after the surface cooler.

[0010] Based on the acquired multi-dimensional operating state parameters, a wet operating condition state space model of the air handling process of the air conditioning system is dynamically constructed. The wet operating condition state space model represents the real-time state points of outdoor fresh air, indoor return air, mixed air and supply air on the standard enthalpy-humidity chart.

[0011] Based on the preset indoor environment control target and the wet working condition state space model, the target air supply state point is calculated and determined, and the equipment dew point state is determined in combination with the performance characteristics of the air conditioning system surface cooler.

[0012] Based on the target air supply state point and the equipment dew point state, an energy-optimal processing straight line connecting the two is determined in the wet operating condition state space model, and the optimal mixing air ratio is obtained by reverse analysis based on geometric constraints. This optimal mixing air ratio ensures that the new mixed air state point formed by the weighted mixing of the outdoor fresh air state point and the indoor return air state point falls precisely on the energy-optimal processing straight line.

[0013] Based on the optimal air-mixing ratio obtained from the analysis, and combined with the minimum fresh air ratio constraint calculated based on the carbon dioxide concentration in the indoor return air duct, a set of coordinated control commands is generated and output to the actuator of the air conditioning system. The coordinated control commands synchronously regulate the opening of the fresh air valve, the return air valve, and the chilled water valve of the surface cooler, while ensuring that the reheat coil valve is in a fully closed state.

[0014] As one embodiment of the present invention, the real-time acquisition of multi-dimensional operating status parameters of the air conditioning system specifically includes:

[0015] A first sensing unit group is installed at the outdoor fresh air inlet to measure the dry bulb temperature and relative humidity of the outdoor fresh air. The first sensing unit group includes a platinum resistance temperature sensor with an accuracy class of A and a capacitive polymer humidity sensor with a measurement range covering 0 to 100% relative humidity. Both are encapsulated in a housing with an IP65 protection level and a radiation shield.

[0016] A second sensing unit group is installed before the return air main of the air conditioning unit enters the mixing section. It is used to measure the dry bulb temperature, relative humidity and carbon dioxide concentration of the indoor return air. In addition to the temperature and humidity sensors of the same specifications as the first sensing unit group, the second sensing unit group also integrates a carbon dioxide sensor that adopts the non-dispersive infrared principle, which has a measurement range of 0 to 5000 parts per million concentration.

[0017] A third sensing unit group is installed in the mixed air box after the fresh air and return air are mixed to measure the dry bulb temperature and relative humidity of the mixed air. The sensor specifications are consistent with the temperature and humidity sensor specifications of the first sensing unit group.

[0018] A fourth sensing unit group is installed in the main air supply duct after the surface cooler coil and fan of the air conditioning unit to measure the dry bulb temperature and relative humidity of the final air supply. Its sensor specifications are consistent with the temperature and humidity sensor specifications of the first sensing unit group.

[0019] All sensor units are connected to the central controller via an RS-485 serial bus using the Remote Terminal Unit protocol, and data is acquired and reported at a frequency of 1 Hz.

[0020] As one embodiment of the present invention, the dynamic construction of the wet operating condition state space model of the air handling process of the air conditioning system specifically includes:

[0021] The central controller receives raw data on dry-bulb temperature and relative humidity from all sensor unit groups;

[0022] Using the built-in function library for calculating the thermophysical properties of moist air under standard atmospheric pressure, the dry-bulb temperature and relative humidity data of each measuring point are converted in real time into complete thermodynamic state parameters including enthalpy, moisture content, specific volume, and wet-bulb temperature;

[0023] The calculated outdoor fresh air state parameters, indoor return air state parameters, mixed air state parameters, and supply air state parameters are plotted and updated in real time on a digital enthalpy-humidity map in the form of a two-dimensional coordinate system, with moisture content as the vertical axis and dry-bulb temperature as the horizontal axis, forming a visualized and dynamic state space model.

[0024] As one embodiment of the present invention, the calculation to determine the target air supply state point and the determination of the equipment dew point state in combination with the performance characteristics of the air conditioning system's surface cooler specifically include:

[0025] The central controller has a built-in building heat load prediction model based on the resistance-capacitance network method. This model predicts the total indoor cooling load and humidity load in the future control cycle based on historical indoor and outdoor temperature and humidity data, solar radiation illuminance data and preset building envelope thermal parameters.

[0026] Based on the predicted total indoor cooling load and combined with the airflow organization characteristics of the spiral air supply in the high space, the target supply air temperature required to offset the load is calculated.

[0027] Based on the indoor humidity control target and the predicted indoor moisture load, the target supply air moisture content required to maintain indoor humidity balance is calculated.

[0028] The target air supply temperature and the target air supply humidity together constitute the target air supply state point;

[0029] The dew point state of the equipment is the theoretical minimum air handling temperature and saturated moisture content that the surface cooler can reach under specific operating conditions. Its value is obtained by looking up tables or calculating functions based on the chilled water supply temperature and flow rate entering the surface cooler, as well as the heat transfer coefficient and heat transfer area of ​​the surface cooler itself, and other pre-calibrated performance parameters.

[0030] As one embodiment of the present invention, the step of obtaining the optimal mixing wind ratio based on geometric constraints through reverse analysis specifically includes:

[0031] In the digitized enthalpy-humidity diagram of humid air, the coordinates of the outdoor fresh air state point are ( , The coordinates of the indoor return air status point are ( , The target air supply state point coordinates are as follows: The device dew point status coordinates are as follows: ;

[0032] The energy-optimal processing straight line is the connection point. With point A straight line;

[0033] The proportion of fresh air in the total air volume, i.e., the mixing ratio, is denoted as: The new mixed air state point formed after mixing ( , The coordinates of ) satisfy a linear superposition relationship:

[0034] ;

[0035] The geometric constraints are the requirements for the new mixed air state point. , The point () must be located on the energy-optimal processing line, i.e., point ( , ),point With point Three points are collinear;

[0036] By solving the system of linear equations relating the three collinear points, the unique optimal mixing ratio can be analytically determined. The calculation expression;

[0037] Based on this expression, the central controller substitutes the measured coordinates of each state point and calculates the optimal mixing wind ratio under the current operating conditions in real time. .

[0038] As one embodiment of the present invention, the step of generating and outputting a set of coordinated control commands based on the optimal mixing air ratio obtained by analysis and combined with the minimum fresh air ratio constraint calculated based on the carbon dioxide concentration in the indoor return air duct specifically includes:

[0039] The minimum fresh air ratio constraint is the minimum proportion of fresh air that must be introduced to ensure indoor air quality; its value... Calculations are performed based on the steady-state mass balance equation:

[0040] ;

[0041] in This represents the measured carbon dioxide concentration in the return air. This represents the measured outdoor fresh air carbon dioxide concentration. The preset target value for the carbon dioxide concentration in the supply air;

[0042] The central controller will calculate the optimal mixing ratio. Compared to minimum fresh air ratio Compare;

[0043] like Greater than or equal to The final control of the mixing ratio is then adopted. Set as ;

[0044] like Less than This indicates that indoor air quality requirements cannot be met under optimal energy conditions. In this case, the system prioritizes indoor air quality and will ultimately control the mixing ratio. Forced to be set as ;

[0045] The central controller will ultimately determine the control mixing ratio. This is converted to a target opening command for the fresh air valve, specifically: target opening = Simultaneously, a target opening command for the return air valve is generated, the value of which is... ;

[0046] At the same time, the central controller starts the proportional-integral-derivative controller. The process variable of the controller is the dry bulb temperature of the air supply measured by the fourth sensor unit group. The set value is the temperature component T_s of the target air supply state point. Its output signal is used to adjust the opening of the cooling water valve of the surface cooler to accurately control the air supply temperature.

[0047] Throughout the process, the control signal sent to the hot water valve of the reheat coil is forcibly set to 0 to ensure that it is in a fully shut-off state.

[0048] According to another aspect of the present invention, a high-ceilinged spiral air supply air conditioning ventilation energy-saving intelligent control system is provided, the system comprising:

[0049] The status parameter acquisition module includes a first, second, third and fourth sensing unit groups respectively installed in the outdoor fresh air inlet, indoor return air main duct, mixing air box and supply air main duct, for real-time acquisition of multi-dimensional operating status parameters of the air conditioning system.

[0050] A wet operating condition state space modeling module, which is electrically connected to the state parameter acquisition module, is used to receive the multi-dimensional operating state parameters and dynamically construct a wet operating condition state space model of the air handling process of the air conditioning system.

[0051] The optimal mixing air ratio calculation module is connected to the wet condition state space modeling module. It is used to determine the energy optimal processing line in the wet condition state space model according to the preset indoor environment control target, and obtain the optimal mixing air ratio through reverse analysis based on geometric constraints.

[0052] The collaborative control command generation module, which is connected to the optimal mixing air ratio calculation module, is used to generate and output a set of collaborative control commands to the actuators of the fresh air valve, return air valve and surface cooler chilled water valve of the air conditioning system based on the optimal mixing air ratio obtained by analysis and combined with the minimum fresh air ratio constraint, and to forcibly shut off the reheat coil valve.

[0053] In one embodiment of the present invention, the state parameter acquisition module, the wet condition state space modeling module, the optimal mixing wind ratio calculation module, and the collaborative control command generation module are all integrated into a central controller with an embedded architecture. The central controller includes a 30-bit microprocessor with a main frequency of not less than 800 MHz, a random access memory of not less than 256 megabytes, and non-volatile flash memory for storing algorithm programs and building model parameters. The central controller is equipped with multiple analog output channels and digital input / output channels for outputting 0 to 10 volt analog control voltage to the valve actuator and receiving digital signals from sensors.

[0054] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0055] 1. By dynamically optimizing the mixing ratio of fresh air and return air, the state point of the mixed air is precisely located on the energy-optimal processing path formed by the target air supply point and the equipment dew point. This fundamentally eliminates the cooling and reheating process commonly seen in air conditioning systems during transitional seasons, directly avoids the huge energy waste caused by the offsetting of cooling and heating, and significantly reduces the operating cost of the system.

[0056] 2. This invention decouples humidity control from temperature control. By precisely setting the initial state of the mixed air, the cooling process of a single surface cooler can simultaneously achieve precise control of the supply air temperature and humidity, improving the comfort and stability of the indoor environment and solving the problem of humidity being easily out of control under traditional control methods.

[0057] 3. This invention uses indoor air quality requirements based on carbon dioxide concentration as a rigid constraint for optimizing the air-fuel ratio, ensuring that while achieving extreme energy saving, the indoor fresh air volume always meets hygiene standards, thus achieving the dual goals of energy saving and health.

[0058] This method is highly adaptive and can respond in real time to dynamic changes in outdoor climate conditions, indoor load, and human activity levels. It continuously seeks out and operates at the system's highest energy efficiency point. Compared with traditional control strategies that use fixed mixing ratios or simple logic judgments, its energy saving and control accuracy are significantly improved. Attached Figure Description

[0059] Figure 1 This is a schematic diagram of the overall technical solution architecture of the intelligent control method for energy saving in high-ceilinged spiral air supply air conditioning proposed in this invention;

[0060] Figure 2 This is a schematic diagram of the core principle framework of the dynamic analysis of the optimal mixing wind ratio based on the wet working condition state space model and the optimal energy processing path in this invention.

[0061] Figure 3 This is a logical flowchart of the real-time perception of multi-dimensional operating state parameters and wet condition state space modeling in this invention.

[0062] Figure 4 This is a flowchart illustrating the logical process of determining the target air supply state point and equipment dew point in collaboration with the linear generation of optimal energy processing in this invention.

[0063] Figure 5 This is a diagram of the collaborative control command generation and execution mechanism linkage control logic framework that integrates the minimum fresh air ratio constraint in this invention.

[0064] Figure 6 This is a schematic diagram of the multi-level interaction relationship and data flow between the central controller of this invention and each sensing unit group and actuator. Detailed Implementation

[0065] Please refer to Figures 1 to 6 This invention provides an intelligent control method for energy-saving ventilation in large-space spiral air conditioning systems. It aims to address the technical shortcomings of existing technologies, such as the use of a fixed fresh air to return air mixing ratio during transitional seasons, which causes the mixed air state point to deviate from the ideal processing path. This necessitates cooling, dehumidification, and reheating to offset the cold and heat, resulting in significant energy waste and humidity control failure. This method constructs a dynamic humidity state space model by real-time sensing of the humidity conditions of multiple points in the air conditioning system. With the goal of minimizing energy consumption, it reverse-analyzes the optimal mixing air ratio, ensuring that the mixed air state point precisely falls on the energy-optimal processing line determined by the target supply air state point and the equipment dew point. This eliminates the reheating process and fundamentally improves system energy efficiency while ensuring indoor air quality.

[0066] The method includes the following steps: S1, acquiring multi-dimensional operating status parameters of the air conditioning system in real time; S2, dynamically constructing a wet operating condition state space model of the air handling process of the air conditioning system based on the acquired multi-dimensional operating status parameters; S3, calculating and determining the target air supply state point according to the preset indoor environment control target and the wet operating condition state space model, and determining the equipment dew point state in combination with the performance characteristics of the air conditioning system's surface cooler; S4, determining an energy-optimal processing straight line connecting the target air supply state point and the equipment dew point state in the wet operating condition state space model, and obtaining the optimal mixing air ratio through reverse analysis based on geometric constraints; S5, generating and outputting a set of coordinated control commands to the actuators of the air conditioning system based on the optimal mixing air ratio obtained through analysis, and in combination with the minimum fresh air ratio constraint calculated based on the carbon dioxide concentration in the indoor return air duct.

[0067] In step S1, multi-dimensional operating status parameters of the air conditioning system are acquired in real time. This step is achieved by deploying four sets of sensor units at key nodes of the air conditioning system. The first set of sensor units is located at the outdoor fresh air inlet and is used to measure the dry-bulb temperature and relative humidity of the outdoor fresh air. This set of sensor units includes a platinum resistance temperature sensor with an accuracy class A and a capacitive polymer humidity sensor with a measurement range covering 0 to 100% relative humidity. Both are encapsulated in a housing with a radiation shield and an IP65 protection rating to ensure stable and reliable measurement data under severe weather conditions such as strong sunlight, rain, and snow.

[0068] The second sensing unit is located before the mixing section of the air conditioning unit's return air main duct. It measures the dry-bulb temperature, relative humidity, and carbon dioxide concentration of the indoor return air. In addition to integrating temperature and humidity sensors of the same specifications as the first sensing unit, this unit is also equipped with a carbon dioxide sensor using the non-dispersive infrared principle. Its measurement range is 0 to 5000 parts per million (ppm) concentration, with a response time of no more than 30 seconds and a long-term drift of less than 2% per year.

[0069] The third sensing unit is located in the mixed air chamber after the fresh air and return air have been mixed. It measures the dry-bulb temperature and relative humidity of the mixed air. Its sensor model, accuracy, and packaging are completely identical to those of the first sensing unit to ensure data consistency and comparability. The fourth sensing unit is located in the main supply air duct after the air conditioning unit's cooling coil and fan. It measures the dry-bulb temperature and relative humidity of the final supplied air. Its sensor specifications are also consistent with those of the first sensing unit.

[0070] All four sensor units are connected to the central controller via an RS-485 serial bus using the Remote Terminal Unit Protocol. The data acquisition frequency is set to 1 Hz, meaning that complete temperature, humidity, and carbon dioxide concentration data are reported once per second. The central controller verifies the raw data. If a sensor's data exceeds its physical reasonable range or its rate of change is abnormal for three consecutive times, a fault diagnosis program is triggered, a fault code is recorded, and the system is switched to a backup data source or a historical data interpolation algorithm is activated to maintain system operation.

[0071] In step S2, a wet-condition state-space model of the air handling process of the air conditioning system is dynamically constructed based on the acquired multi-dimensional operating state parameters. After receiving the raw dry-bulb temperature and relative humidity data reported by each sensor unit group, the central controller calls the built-in function library for calculating the thermophysical properties of moist air under standard atmospheric pressure to convert the dry-bulb temperature and relative humidity of each measuring point into a complete set of thermodynamic state parameters, including enthalpy, moisture content, specific volume, and wet-bulb temperature. The conversion process strictly follows the international standard ISO15099 and the moist air property calculation formulas in the ASHRAE Fundamentals Handbook to ensure the authority and accuracy of the calculation results. For example, the calculation of moisture content W is based on the relationship between saturated water vapor partial pressure and actual water vapor partial pressure, while the enthalpy h is obtained by superimposing the sensible heat of dry air and the latent heat of water vapor.

[0072] After parameter conversion, the central controller plots the moisture content and dry-bulb temperature of four state points—outdoor fresh air, indoor return air, mixed air, and supply air—in real time on a digital enthalpy-humidity chart. This chart is presented in a two-dimensional Cartesian coordinate system, with the horizontal axis representing dry-bulb temperature ranging from 0 to 50 degrees Celsius, and the vertical axis representing moisture content ranging from 0 to 25 grams per kilogram of dry air. Each state point is displayed with dynamic markers and real-time numerical labels. The state-space model is updated every second, forming a continuously evolving air handling process trajectory, providing a dual foundation of visualization and numerical representation for subsequent geometric analysis and optimization calculations.

[0073] In step S3, based on the preset indoor environmental control target and the wet operating condition state space model, the target air supply state point is calculated and determined, and the equipment dew point state is determined in conjunction with the performance characteristics of the air conditioning system's surface cooler. The target air supply state point is defined by both the target air supply temperature and the target air supply moisture content. The determination of the target air supply temperature relies on the built-in building heat load prediction model.

[0074] This model employs the resistance-capacitance network method, simplifying the building envelope into an equivalent circuit network composed of thermal resistance and thermal capacity. Model inputs include historical data on indoor and outdoor temperature and humidity over the past 24 hours, forecasted solar radiation irradiance for the next two hours, and pre-set heat transfer coefficients and thermal inertia indices for building walls, roofs, and windows. By solving the heat balance differential equation, the model predicts the total indoor cooling load within a future control period (typically 15 minutes). With wet load .

[0075] Taking advantage of the unique airflow organization characteristics of spiral air supply in large spaces—that is, the supply airflow descends along a spiral trajectory and mixes thoroughly with the indoor air—the supply air temperature must meet certain requirements. ,in For indoor design temperature, The corrected temperature difference, to account for mixing efficiency, is obtained from a table based on the room height, air supply velocity, and spiral angle. The target supply air moisture content is determined by both the indoor humidity control target and the predicted moisture load, and is calculated using the following formula:

[0076] ;

[0077] in For indoor design humidity levels, air density, This represents the total air volume of the system. The latent heat of vaporization. The target supply air state point obtained from this. Marked in the wet condition state-space model. Equipment dew point status. This represents the theoretical minimum air handling condition that the surface cooler can achieve under current operating conditions, corresponding to the saturated air state at the surface temperature of the cooler. This state point is determined based on the cooler's performance characteristic database, which stores equipment dew point data under different combinations of chilled water supply temperature, flow rate, and oncoming wind speed. The central controller, based on the measured chilled water supply temperature and flow rate, queries the database or calculates the current state using empirical formulas based on the measured temperature and flow rate. and And mark it in the state-space model.

[0078] In step S4, based on the target air supply state point and the equipment dew point state, an energy-optimal processing line connecting the two is determined in the wet operating condition state space model, and the optimal mixing air ratio is obtained through reverse analysis based on geometric constraints. The energy-optimal processing line is defined as the line connecting the equipment dew point... With the target air supply status point The straight line segment represents the only feasible path to achieve the transition from the mixed air state to the target supply air state solely through cooling and dehumidification via a surface cooler, requiring no reheating throughout the process, thus minimizing energy consumption. Let the coordinates of the outdoor fresh air state point be ( , The coordinates of the indoor return air status point are ( , ), Mixing ratio Defined as the proportion of fresh air volume to total air volume, the mixed air state point formed after mixing ( , It satisfies a linear superposition relationship:

[0079] ;

[0080] Geometric constraints require points ( , The line must lie on the energy-optimal treatment line. The parametric equation of this line can be expressed as:

[0081] ;

[0082] Will( , Substituting into the above formula, we get the following about The linear equation is given. After simplification, the optimal mixing ratio can be obtained. The parsing expression:

[0083] ;

[0084] The central controller will be tested. Substituting into this expression, the current operating condition can be calculated in real time. This calculation process is performed once per control cycle to ensure that the mixing ratio is always dynamically adjusted according to the operating conditions.

[0085] In step S5, based on the obtained optimal mixing air ratio and combined with the minimum fresh air ratio constraint calculated based on the carbon dioxide concentration in the indoor return air duct, a set of coordinated control commands is generated and output to the actuators of the air conditioning system. Minimum fresh air ratio This is the minimum proportion of fresh air that must be introduced to meet indoor air hygiene standards, and its calculation is based on the steady-state mass balance equation. Let... The measured return air carbon dioxide concentration is from the second sensing unit group. The outdoor fresh air carbon dioxide concentration (usually taken as 400 parts per million). For the preset target value of carbon dioxide concentration in the supply air (usually 800 to 1000 parts per million), then The central controller will calculate the results. and Compare. If ≥ This indicates that the optimal energy solution simultaneously meets air quality requirements and ultimately controls the mixing ratio. Set as .like < This indicates that simply pursuing energy efficiency will lead to insufficient fresh air volume. In this case, the system prioritizes indoor air quality and forcibly reduces the fresh air volume. Set as .Sure Then, the central controller converts it into valve control commands: the target opening command for the fresh air valve is... The target opening degree command for the return air valve is (1- ) These two commands are sent to the corresponding electric damper actuator via the analog output channel as a DC voltage signal of 0 to 10 volts.

[0086] Simultaneously, the central controller activates the proportional-integral-derivative (PID) controller, whose process variable is the supply air dry-bulb temperature measured by the fourth sensor unit, and whose setpoint is... The controller output signal is used to adjust the opening of the chilled water valve of the surface cooler to precisely maintain the supply air temperature. Throughout the control process, the control signal sent to the hot water valve of the reheat coil is forced to 0 volts to ensure that the reheat coil is in a fully shut-off state and to prevent the occurrence of heat and cold cancellation. All control command outputs undergo dead-time filtering and rate limiting to prevent frequent actuator operation and extend equipment life.

[0087] The complete implementation of the above method relies on a highly integrated hardware and software platform. The core of this platform is an embedded central controller, which integrates a state parameter acquisition module, a wet condition state-space modeling module, an optimal mixing wind ratio calculation module, and a collaborative control command generation module. The central controller employs a 30-bit microprocessor with a clock frequency of no less than 800 MHz and is equipped with no less than 256 megabytes of random access memory for caching sensor data, running real-time calculation tasks, and storing intermediate variables. Non-volatile flash memory with a capacity of no less than 4 gigabytes is used to store the operating system, control algorithm programs, building thermal model parameters, surface cooler performance database, and historical operation logs.

[0088] The controller is equipped with eight analog output channels, each outputting 0 to 10 volts DC voltage to drive the actuators of the fresh air valve, return air valve, chilled water valve, and reheat valve. It also features 16 digital input / output channels to receive on / off alarm signals from sensors and control the start / stop of the fan. Communication interfaces include one RS-485 bus for connecting to the sensor unit group and one Ethernet interface for communicating with the host computer monitoring system. Upon power-up, the entire system automatically executes a self-test program to verify the online status of each sensor and actuator and the integrity of the communication link, ensuring the safe and reliable execution of the control logic.

[0089] This embodiment achieves refined and intelligent control of the air conditioning system in large spaces during transitional seasons through the close coordination of the above five steps. This method not only eliminates the root cause of energy waste from the offsetting of cooling and heating in principle, but also incorporates humidity control into a unified optimization framework, while using carbon dioxide concentration as a hard constraint to ensure indoor air quality, forming a comprehensive solution that integrates energy saving, comfort, and health.

Claims

1. A high and large space spiral air supply air conditioning ventilation energy saving intelligent control method, characterized in that, The application relates to a method for dynamically constructing a state space model of an air conditioning system, comprising the following steps: Real-time acquisition of multi-dimensional operating state parameters of the air conditioning system; the multi-dimensional operating state parameters include the dry-bulb temperature and the relative humidity of outdoor fresh air, the dry-bulb temperature, the relative humidity and the carbon dioxide concentration of indoor return air, the dry-bulb temperature and the relative humidity in a mixed air box, and the dry-bulb temperature and the relative humidity of supply air after a cooling coil; Based on the acquired multi-dimensional operating state parameters, a wet working condition state space model of the air conditioning system air treatment process is dynamically constructed, comprising the following steps: A central controller receives dry-bulb temperature and relative humidity original data from all sensor unit groups; The dry-bulb temperature and the relative humidity data of each measuring point are converted into complete thermodynamic state parameters including enthalpy, humidity content, specific volume and wet-bulb temperature by using a built-in standard atmospheric pressure wet air thermophysical property calculation function library; The calculated outdoor fresh air state parameters, indoor return air state parameters, mixed air state parameters and supply air state parameters are real-time drawn and updated on a digital wet air psychrometric chart in the form of two-dimensional coordinates, i.e. humidity content as the ordinate and dry-bulb temperature as the abscissa, to form a visual and dynamic state space model; The wet working condition state space model represents real-time state points of outdoor fresh air, indoor return air, mixed air and supply air on a standard wet air psychrometric chart; According to a preset indoor environment control target and the wet working condition state space model, a target supply air state point is calculated and determined, and a device dew point state is determined in combination with the performance characteristics of a cooling coil of the air conditioning system; Based on the target supply air state point and the device dew point state, an energy-optimal treatment straight line connecting the two points is determined in the wet working condition state space model, and an optimal mixed air ratio is obtained by reverse analysis based on geometric constraints, so that a new mixed air state point formed by weighting mixing of the outdoor fresh air state point and the indoor return air state point accurately falls on the energy-optimal treatment straight line; According to the obtained optimal mixed air ratio and in combination with a minimum fresh air ratio constraint calculated based on the carbon dioxide concentration of the indoor return air main pipe, a group of coordinated control instructions is generated and output to an execution mechanism of the air conditioning system, the coordinated control instructions synchronously control the opening degrees of a fresh air valve, a return air valve and a cooling water valve of the cooling coil, and simultaneously ensure that a reheating coil valve is in a full-off state.

2. The energy-saving intelligent control method for high and large space spiral air supply air conditioning and ventilation according to claim 1, characterized in that, Real-time acquisition of multi-dimensional operating state parameters of the air conditioning system, comprising: A first sensor unit group is arranged at an outdoor fresh air inlet, and is used for measuring the dry-bulb temperature and the relative humidity of outdoor fresh air; the first sensor unit group comprises a platinum resistance temperature sensor with an A-grade precision level and a capacitive polymer humidity sensor with a 0-100% relative humidity measurement range, and the two sensors are jointly packaged in an IP65-grade shell with a radiation-proof cover; A second sensor group is arranged at a position before the return air main pipe of the air handling unit enters the mixing section, for measuring the dry bulb temperature, relative humidity and carbon dioxide concentration of the indoor return air; in addition to the temperature and humidity sensors with the same specifications as the first sensor group, the second sensor group also integrates a carbon dioxide sensor based on the non-dispersive infrared principle, with a measurement range of 0 to 5000 parts per million concentration; A third sensor group is arranged in the mixed air box after the mixing of fresh air and return air is completed, for measuring the dry bulb temperature and relative humidity of the mixed air, with the sensor specifications consistent with those of the temperature and humidity sensors of the first sensor group; A fourth sensor group is arranged in the main supply air duct after the refrigerant coil and fan of the air handling unit, for measuring the dry bulb temperature and relative humidity of the final supply air, with the sensor specifications consistent with those of the temperature and humidity sensors of the first sensor group; All sensor groups are connected to the central controller through an RS-485 serial bus using the remote terminal unit protocol, and data acquisition and reporting are performed at a frequency of 1 Hz.

3. The energy-saving intelligent control method for high and large space spiral air supply air conditioning and ventilation according to claim 2, characterized in that, The target supply air state point is determined by calculation, and the equipment dew point state is determined in combination with the performance characteristics of the air conditioning system cooling coil, including: The central controller is built-in with a building heat load prediction model based on the resistance-capacitance network method, which predicts the indoor total cooling load and humidity load in the future control period based on historical indoor and outdoor temperature and humidity data, solar radiation intensity data, and pre-set building envelope thermal parameters; According to the predicted indoor total cooling load, and in combination with the air distribution characteristics of high and large space spiral supply air, the target supply air temperature required to offset the load is calculated; According to the indoor humidity control target and the predicted indoor humidity load, the target supply air moisture content required to maintain the indoor humidity balance is calculated; The target supply air state point is composed of the target supply air temperature and the target supply air moisture content; The equipment dew point state is the theoretical minimum air handling temperature and saturated moisture content that the cooling coil can reach under certain working conditions, and its value is obtained by table lookup or function calculation based on the chilled water supply temperature and flow entering the cooling coil, and the heat transfer coefficient and heat transfer area of the cooling coil itself.

4. The energy-saving intelligent control method for high and large space spiral air supply air conditioning and ventilation according to claim 3, characterized in that, The optimal mixed air ratio is obtained by reverse analysis based on geometric constraints, including: In the digitized wet air enthalpy psychrometric chart, the outdoor fresh air state point is marked as (x1, y1), the indoor return air state point is marked as (x2, y2), the target supply air state point is marked as (x3, y3), and the device dew point state is marked as (xd, yd). , , , , , ; The energy optimal processing straight line is a straight line connecting the points and the point . The proportion of fresh air in the total air, i.e. the mixed air ratio, is denoted as The coordinates of the state point of the new mixed air formed after mixing (x, y) satisfy the linear superposition relationship: , ​ ； The geometric constraint is that the new mixture air state point , ) must be on the energy optimal processing straight line, i.e. the three points of point , ), point and point are collinear. By solving the linear equations of the three collinear points, the unique optimal mixing wind ratio is analytically obtained The calculation expression; The central controller substitutes the measured coordinates of the state points into the expression to calculate the optimal mixed air ratio in real time under the current working condition .

5. The energy-saving intelligent control method for high and large space spiral air supply air conditioning and ventilation according to claim 4, characterized in that, the optimal mixed wind ratio The calculation expression is: 。 6. The energy-saving intelligent control method for high and large space spiral air supply air conditioning and ventilation according to claim 5, characterized in that, According to the optimal mixed air ratio obtained by analysis, and in combination with the minimum fresh air ratio constraint calculated based on the carbon dioxide concentration of the indoor return air main pipe, a set of collaborative control instructions is generated and output, including: The minimum fresh air ratio constraint is the minimum proportion of fresh air that must be introduced to ensure indoor air quality , The calculation is made according to the steady-state mass balance equation: ； wherein is a measured return air carbon dioxide concentration, is a measured outdoor fresh air carbon dioxide concentration, is a preset supply air carbon dioxide concentration target value; The central controller compares the calculated optimal mixing air ratio with the minimum fresh air ratio ; If greater than or equal to , the control mixed air ratio is set to ; If less than , it indicates that the indoor air quality requirements cannot be met under the energy optimal conditions, at which time the system prioritizes indoor air quality, and the control mixed air ratio will eventually be adopted ; The central controller will finally determine the control mixed air ratio Convert to the target opening degree instruction of the fresh air valve, specifically the target opening degree At the same time, the target opening degree instruction of the return air valve is generated, and the value is .

7. The energy-saving intelligent control method for high and large space spiral air supply air conditioning and ventilation according to claim 6, characterized in that, Generating and outputting a set of collaborative control instructions also includes: The central controller starts a proportional-integral-derivative controller, whose process variable is the supply air dry-bulb temperature measured by the fourth sensor unit, and whose set value is the temperature component of the target supply air state point The output signal of which is used to adjust the opening of the surface air cooler cold water valve to accurately control the supply air temperature; During the entire process, the control signal to the hot water valve of the reheat coil is forced to be 0, ensuring that it is in the full-off state.

8. The energy-saving intelligent control method for high and large space spiral air supply air conditioning and ventilation according to claim 7, characterized in that, The output of all control instructions is subjected to dead zone filtering and rate limiting processing to prevent frequent action of the actuator. 9.The high and large space spiral air supply air conditioning ventilation energy saving intelligent control method according to claim 8, characterized in that, The central controller checks the original data, and if a sensor data is detected to be outside its physically reasonable range or have an abnormal change rate for 24 consecutive hours, a fault diagnosis program is triggered, a fault code is recorded, and the system is maintained running by switching to a backup data source or enabling a historical data interpolation algorithm.

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