Distributed fresh air system control method, controller, medium and product

Abstract

The invention discloses a distributed fresh air system control method, a controller, a medium and a product, and relates to the technical field of fresh air systems. The controller collects air detection data of each area and determines the theoretical wind speed of each area in combination with an air quality-wind speed curve so as to dynamically sense the fresh air requirements of all the areas. And the controller calculates the critical static pressure required by the corresponding area to reach the theoretical air speed under the maximum air valve opening degree of each branch air pipe, the maximum critical static pressure is determined as the total static pressure of the target main air pipe, and a basic pressure guarantee is provided for all the areas to meet the fresh air requirement. The controller is combined with a PID control algorithm to adjust the rotating speed of the main fresh air machine, it can be guaranteed that the total static pressure of the target main air pipe is stably achieved, and efficient and energy-saving operation of the main fresh air machine can be achieved. And meanwhile, the controller is matched with the corresponding target air valve opening degree through the target air valve resistance coefficient, independent and accurate regulation and control of all the branch air pipes are achieved, and different areas can obtain the adaptive fresh air volume according to the fresh air requirements of the areas.

Description

Technical Field

[0001] This application relates to the field of fresh air system technology, and in particular to a distributed fresh air system control method, controller, medium and product. Background Technology

[0002] With the improvement of people's living standards and the increasing demands for air quality, the application of fresh air systems is becoming more and more widespread. Fresh air systems introduce fresh outdoor air and expel stale indoor air, effectively improving air quality and creating a healthy and comfortable environment for people. In large buildings, due to differences in the functions and population density of different areas, the demand for fresh air varies from area to area, which necessitates independent adjustment and control of the fresh air supply to different areas.

[0003] Currently, the most common control method for fresh air systems is timed control, which means that the fresh air fan and the opening of the air valves are operated according to a preset time period and air volume parameters. In practical applications, some fresh air systems are also equipped with air quality detection devices. When the detected air quality is lower than a preset quality threshold, the fresh air fan is started at a preset speed and the air valves in the corresponding area are opened.

[0004] However, the above methods often lead to uneven distribution of fresh air. Due to the lack of continuous monitoring and dynamic response capabilities for real-time air quality in each area, some areas may experience excessive fresh air, resulting in energy waste, while other areas may suffer from insufficient fresh air, affecting indoor air quality. Summary of the Invention

[0005] This application provides a distributed fresh air system control method, controller, medium, and product, which enables independent and precise control of each branch duct, allowing different areas to obtain the appropriate fresh air volume according to their own fresh air needs.

[0006] In a first aspect, this application provides a distributed fresh air system control method, applied to a controller in the fresh air system. The fresh air system also includes a main fresh air unit, a main duct, and multiple branch ducts connected to different areas. Each branch duct is equipped with an adjustable electric damper. The method includes: collecting the current main fresh air unit speed, the current total static pressure of the main duct, and air detection data for the area corresponding to each branch duct; determining the theoretical wind speed for each area based on the air detection data and a preset air quality-wind speed curve; and calculating the maximum opening of each branch duct at the maximum damper position. Under the specified opening conditions, the critical static pressure required to achieve the theoretical wind speed in the corresponding area is determined as the target total static pressure of the main duct. Based on the current main fresh air unit speed and the deviation between the target total static pressure and the current total static pressure of the main duct, the main fresh air unit is driven to perform speed adjustment. Based on the target total static pressure of the main duct and the theoretical wind speed, the target damper resistance coefficient of each branch duct is calculated. Based on the preset damper opening-resistance curve, the target damper opening corresponding to the target damper resistance coefficient is queried to drive the electric damper on each branch duct to perform the target damper opening.

[0007] By employing the above technical solution, the controller collects air quality data from each area and, combined with a preset air quality-wind speed curve, determines the theoretical wind speed for each area. This enables dynamic sensing of the fresh air demand in all areas, ensuring precise matching of fresh air supply with regional air conditions and avoiding insufficient fresh air in polluted areas and excessive fresh air in clean areas. The controller calculates the critical static pressure required for each branch duct to achieve the theoretical wind speed under maximum valve opening conditions, and sets the maximum critical static pressure as the target main duct's total static pressure, providing a basic pressure guarantee for meeting the fresh air demand in all areas. The controller, combined with a PID control algorithm, adjusts the main fresh air unit's speed, ensuring both the stable achievement of the target main duct's total static pressure and efficient energy-saving operation of the main fresh air unit. Simultaneously, the controller matches the target valve resistance coefficient with the corresponding target valve opening, achieving independent and precise control of each branch duct. This allows different areas to obtain the appropriate fresh air volume according to their own fresh air needs, ultimately improving indoor air quality in all areas while reducing energy waste and balancing comfort and economy.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, the critical static pressure required for the corresponding area of ​​each branch duct to reach the theoretical wind speed under the condition of maximum valve opening is calculated. Specifically, this includes: obtaining the basic pipeline resistance coefficient of the branch duct; retrieving the filter clogging correction coefficient stored after the most recent update, whereby the filter clogging correction coefficient represents the resistance increment of the terminal filter, and a terminal filter is provided at the end of the branch duct; using the filter clogging correction coefficient to correct the basic pipeline resistance coefficient to obtain the current pipeline resistance coefficient; and based on a preset pressure-resistance-wind speed calculation model, substituting the current pipeline resistance coefficient and the theoretical wind speed into the calculation to obtain the critical static pressure required for the corresponding area of ​​the branch duct to reach the theoretical wind speed.

[0009] By adopting the above technical solution, the controller further optimizes the calculation accuracy of critical static pressure, effectively solving the problem of fresh air supply deviation caused by clogged terminal filters. As terminal filters gradually accumulate dust during actual use, the resistance of branch ducts increases. If this factor is ignored, the critical static pressure calculated based on the basic duct resistance coefficient of the branch ducts will deviate from the actual fresh air demand, resulting in insufficient fresh air supply in the area. The controller dynamically corrects the basic duct resistance coefficient by retrieving the filter clogging correction coefficient stored after the most recent update, ensuring that the current duct resistance coefficient accurately reflects the actual resistance state after the terminal filter becomes clogged. The controller then combines this with a preset pressure-resistance-wind speed calculation model to calculate the critical static pressure, which better matches actual operating conditions, ensuring that even with clogged terminal filters, each area can still accurately achieve the fresh air volume corresponding to the theoretical wind speed. This dynamic compensation mechanism for filter clogging not only improves the stability and reliability of the fresh air system control but also extends the effective service life of the terminal filters, reduces unnecessary filter replacement frequency, and lowers the maintenance cost of the fresh air system.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, before retrieving the filter clogging correction coefficient stored after the most recent update, the method further includes: at a preset calibration time, driving all electric air valves to their maximum opening; when the main fresh air unit speed remains constant within a preset time period, collecting the actual total static pressure of the main duct and the actual speed of the main fresh air unit; based on a preset standard characteristic curve of the fan, querying the standard total static pressure of the main duct corresponding to the actual speed of the main fresh air unit; calculating the ratio of the actual total static pressure of the main duct to the standard total static pressure of the main duct, generating the filter clogging correction coefficient, and storing it.

[0011] By adopting the above technical solution, the controller provides a scientific and automatic method for generating the filter clogging correction coefficient, solving the problems of time-consuming, labor-intensive, low-accuracy, and unupdable real-time updates associated with manual filter resistance calibration. At a preset calibration time, the controller drives all electric dampers to their maximum opening to eliminate the interference of damper opening on duct resistance. When the main fresh air unit's speed is stable, it collects the actual total static pressure of the main duct and the actual speed of the main fresh air unit. Based on the fan's standard characteristic curve, it queries the standard total static pressure of the main duct corresponding to the actual main fresh air unit's speed and generates the filter clogging correction coefficient using the ratio of the actual total static pressure to the standard total static pressure. This allows for an objective and accurate quantification of the resistance increase caused by filter clogging. This automatic calibration mechanism requires no manual intervention and can be triggered periodically or on demand, achieving dynamic updates to the filter clogging correction coefficient and ensuring the timeliness and accuracy of branch duct resistance coefficient correction. Furthermore, it eliminates the need for additional complex detection equipment; data acquisition and calculation can be completed using only the existing sensors in the fresh air system, reducing the hardware cost of the fresh air system.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, after calculating the ratio of the actual total static pressure of the main duct to the standard total static pressure of the main duct, generating and storing the filter clogging correction coefficient, the method further includes: determining whether the filter clogging correction coefficient is greater than a preset pollution warning threshold; if so, calling a preset filter filtration efficiency-face velocity curve, matching the highest face velocity corresponding to the filter clogging correction coefficient; and converting the highest face velocity into the wind speed protection upper limit value of a single branch duct.

[0013] By adopting the above technical solution, when the filter clogging correction coefficient exceeds the preset pollution warning threshold, it indicates that the terminal filter has accumulated a large amount of pollutants. If the air supply continues at the original theoretical wind speed, not only will the main fresh air unit's load surge and energy consumption increase due to excessive resistance, but the filtration effect of the terminal filter may also be reduced due to excessive airflow speed, or even damage the terminal filter. Therefore, the controller calls the filter efficiency-face velocity curve to accurately match the highest face velocity under the current degree of clogging and converts it into the wind speed protection upper limit value for a single branch duct, thereby limiting the impact of excessively high wind speeds on the terminal filter, ensuring that the terminal filter operates within the effective range, and extending its service life. At the same time, setting the wind speed protection upper limit value avoids the risk of failure caused by excessive load operation of the main fresh air unit, reduces the maintenance cost of the fresh air system, and ensures that the fresh air system can maintain a stable filtration effect and operating status even when the terminal filter is not replaced in time, further improving the reliability and safety of the fresh air system operation.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, based on the current main fresh air unit speed and the deviation between the target main duct total static pressure and the current main duct total static pressure, the main fresh air unit is driven to perform a speed adjustment operation. Specifically, this includes: calculating the static pressure difference between the target main duct total static pressure and the current main duct total static pressure; inputting the static pressure difference into a preset PID control algorithm model to obtain the speed adjustment amount; superimposing the speed adjustment amount with the current main fresh air unit speed to obtain the target main fresh air unit speed; determining whether the target main fresh air unit speed is within a preset safe operating speed range: if yes, then driving the main fresh air unit to accelerate or decelerate to the target main fresh air unit speed; if no, then driving the main fresh air unit to operate at the maximum boundary speed or minimum boundary speed of the preset safe operating speed range.

[0015] By adopting the above technical solution, the controller calculates the static pressure difference between the target main duct total static pressure and the current main duct total static pressure, and combines this with a PID control algorithm model to solve for the speed adjustment, thereby quickly responding to static pressure deviations, effectively suppressing overshoot and oscillation, and making the main fresh air unit speed adjustment more stable and precise. This ensures that the current main duct total static pressure stably approaches the target main duct total static pressure, providing a solid guarantee for the accurate distribution of fresh air volume in each area. Simultaneously, the controller determines whether the target main fresh air unit speed is within the preset safe operating speed range, avoiding problems such as increased mechanical wear and excessive noise caused by excessively high speeds, or insufficient fresh air supply caused by excessively low speeds. When the target main fresh air unit speed exceeds the preset safe operating speed range, the controller drives the main fresh air unit to operate at the boundary speed of the preset safe operating speed range, ensuring equipment operation safety while maximizing the fulfillment of the basic operating requirements of the fresh air system. This speed adjustment method, which balances accuracy and safety, improves the operational stability of the fresh air system, extends the service life of the main fresh air unit, and reduces energy consumption and operating noise.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, after determining the theoretical wind speed of each area based on air detection data and a preset air quality-wind speed curve, the method further includes: obtaining the current operating time, determining whether the current operating time is within a preset low-noise nighttime period; if so, calling a preset noise suppression coefficient, multiplying the noise suppression coefficient by the theoretical wind speed to obtain the corrected theoretical wind speed; and limiting the maximum boundary speed of the preset safe operating speed range to a preset silent speed threshold.

[0017] By adopting the above technical solution, when the controller determines that the current operating time falls within a preset low-noise nighttime period, it actively triggers a noise suppression mechanism. This mechanism multiplies the preset noise suppression coefficient by the theoretical wind speed to obtain a corrected theoretical wind speed, reducing airflow velocity while ensuring a basic fresh air volume, thus reducing duct noise at its source. Simultaneously, the controller limits the maximum speed limit of the preset safe operating speed range to a preset silent speed threshold, preventing mechanical noise from the main fresh air unit operating at high speeds. For noise-sensitive areas such as bedrooms and lounges, low-noise nighttime control enhances living comfort, allowing users to enjoy fresh air without being disturbed by noise. This time- and zone-based differentiated control strategy makes the fresh air system more aligned with users' actual usage scenarios, improving the system's human-centered design.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, the target valve resistance coefficient of each branch duct is calculated based on the total static pressure of the target main duct and the theoretical wind speed. Specifically, this includes: substituting the total static pressure of the target main duct and the theoretical wind speed into the flow resistance coefficient calculation formula to obtain the total flow resistance coefficient required for the corresponding area of ​​each branch duct to achieve the theoretical wind speed; obtaining the pipe resistance coefficient of each branch duct; and subtracting the pipe resistance coefficient from the total flow resistance coefficient to obtain the target valve resistance coefficient of each branch duct.

[0019] By adopting the above technical solution, the controller first calculates the total flow resistance coefficient to meet the area's fresh air demand using the flow resistance coefficient calculation formula, combined with the target main duct's total static pressure and theoretical wind speed. Then, it subtracts the branch duct's own pipe resistance coefficient to accurately separate the resistance that the electric damper needs to bear, i.e., the target damper resistance coefficient. This calculation method fully considers multiple factors such as the main duct's total static pressure, the area's wind speed demand, and the inherent pipe resistance, ensuring that the target damper resistance coefficient accurately reflects the actual demand to achieve the theoretical wind speed. This provides a reliable basis for adjusting the opening of the electric damper and solves the problem of fresh air volume distribution deviation caused by the reliance on experience values ​​and insufficient precision in traditional damper adjustment.

[0020] In a second aspect, embodiments of this application provide a controller comprising: one or more processors and a memory; the memory is coupled to the one or more processors and is used to store computer program code, the computer program code including computer instructions, wherein the one or more processors invoke the computer instructions to cause the controller to perform the methods described in the present aspect and any possible implementation thereof.

[0021] Thirdly, embodiments of this application provide a computer program product containing instructions that, when the computer program product is run on a controller, cause the controller to perform the method described in the present aspect and any possible implementation thereof.

[0022] Fourthly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a controller, cause the controller to perform the method described in the present aspect and any possible implementation thereof.

[0023] Understandably, the controller provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the methods provided in the embodiments of this application. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. By adopting the above technical solution, the controller collects air quality data for each area and, combined with a preset air quality-wind speed curve, determines the theoretical wind speed for each area. This enables dynamic sensing of the fresh air demand in all areas, ensuring precise matching of fresh air supply with regional air conditions and avoiding insufficient fresh air in polluted areas and excessive fresh air in clean areas. The controller calculates the critical static pressure required for each branch duct to achieve the theoretical wind speed under maximum valve opening conditions, and sets the maximum critical static pressure as the target main duct's total static pressure, providing a basic pressure guarantee for meeting the fresh air demand in all areas. The controller, combined with a PID control algorithm, adjusts the main fresh air fan speed, ensuring both the stable achievement of the target main duct's total static pressure and efficient energy-saving operation of the main fresh air fan. Simultaneously, the controller matches the target valve opening with the target valve resistance coefficient, achieving independent and precise control of each branch duct. This allows different areas to obtain the appropriate fresh air volume according to their own fresh air needs, ultimately improving indoor air quality in all areas while reducing energy waste and balancing comfort and economy.

[0025] 2. By adopting the above technical solution, the controller further optimizes the calculation accuracy of critical static pressure, effectively solving the problem of fresh air supply deviation caused by clogged terminal filters. As terminal filters gradually accumulate dust during actual use, the resistance of branch ducts increases. If this factor is ignored, the critical static pressure calculated based on the basic duct resistance coefficient of the branch ducts will deviate from the actual fresh air demand, resulting in insufficient fresh air supply in the area. The controller dynamically corrects the basic duct resistance coefficient by retrieving the filter clogging correction coefficient stored after the most recent update, ensuring that the current duct resistance coefficient accurately reflects the actual resistance state after the terminal filter becomes clogged. The controller then combines this with a preset pressure-resistance-wind speed calculation model to calculate the critical static pressure, which better matches actual operating conditions, ensuring that even with clogged terminal filters, each area can still accurately achieve the fresh air volume corresponding to the theoretical wind speed. This dynamic compensation mechanism for filter clogging not only improves the stability and reliability of the fresh air system control, but also extends the effective service life of the terminal filter, reduces unnecessary filter replacement frequency, and lowers the maintenance cost of the fresh air system.

[0026] 3. By adopting the above technical solution, the controller provides a scientific and automatic method for generating the filter clogging correction coefficient, solving the problems of time-consuming, labor-intensive, low-accuracy, and unupdable real-time updates associated with manual filter resistance calibration. At a preset calibration time, the controller drives all electric dampers to their maximum opening to eliminate the interference of damper opening on duct resistance. When the main fresh air unit's speed is stable, it collects the actual total static pressure of the main duct and the actual speed of the main fresh air unit. Based on the fan's standard characteristic curve, it queries the standard total static pressure of the main duct corresponding to the actual main fresh air unit's speed and generates the filter clogging correction coefficient using the ratio of the actual total static pressure to the standard total static pressure. This allows for an objective and accurate quantification of the resistance increase caused by filter clogging. This automatic calibration mechanism requires no manual intervention and can be triggered periodically or on demand, achieving dynamic updates to the filter clogging correction coefficient and ensuring the timeliness and accuracy of branch duct resistance coefficient correction. Furthermore, it eliminates the need for additional complex detection equipment; data acquisition and calculation can be completed using only the existing sensors in the fresh air system, reducing the hardware cost of the fresh air system. Attached Figure Description

[0027] Figure 1 This is a flowchart illustrating a distributed fresh air system control method in an embodiment of this application; Figure 2 This is a schematic diagram of the physical device structure of the controller in an embodiment of this application. Detailed Implementation

[0028] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification of this application, the singular expressions “a,” “an,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0029] Hereinafter, the terms "current" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "current" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0030] The fresh air system in the embodiments of this application will be described below.

[0031] A fresh air system is a set of intelligent ventilation equipment designed for the differentiated fresh air needs of multiple areas. Through the coordinated work of its components, it can introduce, purify and precisely distribute fresh outdoor air, while expelling stale indoor air, ultimately achieving the core goal of optimizing air quality in all scenarios. It is suitable for ventilation scenarios in multiple areas such as large buildings, residences and office buildings.

[0032] The core components of a fresh air system are described in detail below: The controller is the control center of the entire fresh air system. Its core functions include collecting operating data, performing logical operations and parameter calculations, and sending control commands to other components. It also has the ability to store data and perform calibration corrections. It can dynamically adjust the speed of the main fresh air unit and the opening of the electric air valve according to the changes in air quality and operating conditions in different areas, so as to ensure the accuracy and stability of the fresh air system operation.

[0033] The main fresh air unit is the power source of the fresh air system, responsible for drawing in fresh air from the outside, purifying it, and then delivering it into the main duct. Its speed can be flexibly adjusted according to control commands issued by the controller, thereby changing the air volume and pressure of the fresh air output. The operating status of the main fresh air unit directly affects the fresh air supply capacity of the entire fresh air system. Through closed-loop linkage with the controller, it can stably maintain the total static pressure of the target main duct, providing sufficient power support for the fresh air delivery to each branch duct. At the same time, it can operate within the preset safe operating speed range, balancing operating efficiency and equipment safety.

[0034] The main duct is the backbone of fresh air delivery. One end connects to the air outlet of the main fresh air unit, and the other end branches to multiple branch ducts. Its core function is to distribute the fresh air output from the main fresh air unit to each branch duct. The main duct needs to have a certain pressure-bearing capacity and sealing performance to prevent fresh air leakage or excessive pressure loss. At the same time, the main duct is usually equipped with a static pressure sensor to detect the total static pressure of the main duct in real time and feed it back to the controller to provide a basis for adjusting the speed of the main fresh air unit.

[0035] Branch ducts are branch channels connecting the main duct to various areas. Each branch duct corresponds to an independent ventilation area (such as a bedroom, office, or meeting room). Its structural parameters, such as duct diameter, length, and number of bends, are pre-designed based on the space size and fresh air requirements of the corresponding area. The ends of branch ducts are typically equipped with terminal filters for secondary purification of fresh air, ensuring the quality of the air delivered indoors. Additionally, each branch duct is fitted with an electric damper, which adjusts its opening to change duct resistance, thereby precisely controlling the fresh air supply to the corresponding area.

[0036] An electric damper is a flow control component installed on branch ducts. Its opening degree can be adjusted within the range of 0%-100% (0% represents fully closed, 100% represents fully open). Its core function is to change its own resistance according to control commands issued by the controller, thereby regulating the air velocity and volume of fresh air entering the branch duct. There is a fixed mapping relationship between the opening degree of the electric damper and the damper resistance coefficient (pre-stored as a damper opening degree-resistance curve). By calculating the target damper resistance coefficient, the controller can accurately match the corresponding target damper opening degree, realizing independent control of the fresh air volume in each area and meeting the differentiated needs of different areas.

[0037] The following describes the process of the method provided in this implementation. Please refer to [link / reference]. Figure 1 This is a flowchart illustrating a distributed fresh air system control method in an embodiment of this application.

[0038] S101. Collect the current main fresh air unit speed, the current main air duct total static pressure, and the air detection data of the area corresponding to each branch air duct. Among them, the current main fresh air unit speed refers to the actual operating speed of the main fresh air unit at the current data acquisition time, usually in revolutions per minute (rpm), for example, the main fresh air unit is running at a speed of 1500 rpm at the current time; the current main duct total static pressure refers to the actual static pressure generated by the air in the main duct at the current data acquisition time, in Pascals (Pa), for example, the current detected main duct total static pressure is 200 Pa; area refers to the independent spatial unit served by the fresh air system, which can be divided according to the function and spatial layout, such as bedrooms and living rooms in a residence, shops and public passages in a shopping mall; air detection data refers to the air-related parameters in the area collected by air quality sensors, used to reflect the air quality status, including PM2.5 concentration, carbon dioxide concentration, formaldehyde concentration, TVOC concentration, etc., which are not limited here, for example, the PM2.5 concentration in a certain area is 35 μg / m³ and the carbon dioxide concentration is 800 ppm.

[0039] Specifically, the controller acquires multiple types of data simultaneously through a preset acquisition frequency (e.g., once every 5 seconds): on the one hand, it reads the current speed of the main fresh air unit in real time through a speed sensor connected to the main fresh air unit; on the other hand, it collects the current total static pressure of the main air duct through static pressure sensors installed at key locations in the main air duct (e.g., near and far ends of the main air duct); at the same time, it collects air quality detection data for each area through air quality sensors deployed in the corresponding areas of each branch air duct.

[0040] S102. Based on air quality monitoring data and preset air quality-wind speed curves, determine the theoretical wind speed for each area; The preset air quality-wind speed curve refers to a function curve pre-stored in the controller, used to characterize the mapping relationship between air quality parameters and the required fresh air speed. This air quality-wind speed curve is pre-calibrated based on human comfort needs, air quality standards, and the purification capacity of the fresh air system. For example, the air quality-wind speed curve sets the required fresh air speed to 1.2 m / s when the PM2.5 concentration is 50 μg / m³, and the required fresh air speed to 1.8 m / s when the PM2.5 concentration is 100 μg / m³. The theoretical wind speed refers to the ideal fresh air speed that can meet the air quality improvement needs of the current area, obtained by matching the air quality-wind speed curve with the current area's air detection data. For example, if the current air detection data of area A shows that the pollution is serious, the theoretical wind speed obtained by matching is 2.0 m / s.

[0041] Specifically, the controller preprocesses the air quality monitoring data, removing outliers (such as data exceeding reasonable ranges due to air quality sensor malfunctions) to ensure the validity of the data. Then, the controller retrieves a pre-stored air quality-wind speed curve. This curve establishes corresponding mapping relationships for different types of air quality parameters (such as PM2.5 and carbon dioxide). If multiple pollutants exceed standards in a certain area, the controller prioritizes matching the parameter with the pollutant that has a greater impact on human health, or it matches a combination of pollutant exceedances. Next, the controller substitutes the preprocessed air quality monitoring data into the air quality-wind speed curve and accurately matches the theoretical wind speed for each area through interpolation and other methods. For example, if the carbon dioxide concentration in an office is 1000 ppm, after consulting the air quality-wind speed curve, the corresponding theoretical wind speed is determined to be 1.5 m / s. This theoretical wind speed can quickly reduce the indoor carbon dioxide concentration while ensuring human comfort. The accurate determination of the theoretical wind speed achieves precise alignment between the fresh air supply and the actual needs of the area, providing a clear target direction for subsequent static pressure calculations and equipment adjustments.

[0042] Optionally, after determining the theoretical wind speed for each area based on air quality monitoring data and a preset air quality-wind speed curve, the following steps can be performed, or not, and are not limited here: obtain the current operating time, determine whether the current operating time is within the preset low-noise nighttime period; if so, call the preset noise suppression coefficient, multiply the noise suppression coefficient by the theoretical wind speed to obtain the corrected theoretical wind speed; limit the maximum boundary speed of the preset safe operating speed range to the preset silent speed threshold.

[0043] Among them, the current operating time indicates the operating time of the fresh air system, such as 23:15 Beijing time; the preset low-noise nighttime period refers to the nighttime period that the controller has preset to prioritize ensuring a quiet environment, usually set according to the user's rest patterns, such as 22:00-07:00 the next day, suitable for residential, hotel and other scenarios sensitive to nighttime noise; the preset noise suppression coefficient is a coefficient less than 1 set to reduce nighttime operating noise, its value is calibrated according to the noise characteristics and quiet requirements of the fresh air system, such as 0.7 or 0.8. The smaller the preset noise suppression coefficient, the more obvious the noise suppression effect, but the basic fresh air volume must be guaranteed; the corrected theoretical wind speed refers to the wind speed after the preset noise suppression coefficient is compared with the original theoretical wind speed. The result obtained by multiplying the wind speed can meet the basic air quality requirements at night while reducing airflow and equipment operating noise. For example, if the original theoretical wind speed is 2.0 m / s and the preset noise suppression coefficient is 0.7, then the corrected theoretical wind speed is 1.4 m / s. The preset safe operating speed range refers to the speed range in which the main fresh air unit can operate safely and stably, such as 800-2000 rpm, which is determined by the equipment hardware parameters and operating safety standards. The preset silent speed threshold refers to the maximum operating speed of the main fresh air unit allowed during the preset low-noise period at night. This preset silent speed threshold is lower than the maximum boundary speed of the conventional safe operating speed range, such as 1200 rpm, to ensure that the main fresh air unit operates in a low-noise mode.

[0044] Specifically, the controller obtains the current operating time through its built-in clock module and then compares it with a preset low-noise nighttime period to determine if it has entered a period requiring silent operation. If the current operating time falls within the preset low-noise nighttime period, it indicates that the user is likely resting and highly sensitive to noise, requiring noise suppression while ensuring basic fresh air supply. The controller retrieves a preset noise suppression coefficient, which has been calibrated through multiple experiments to ensure that while reducing the fan speed, the fresh air volume still meets the basic needs of indoor air circulation and pollutant dilution, avoiding air quality deterioration due to excessive noise reduction. Subsequently, the controller multiplies this preset noise suppression coefficient by the previously determined theoretical fan speed for each area to obtain a corrected theoretical fan speed, reducing airflow noise in the branch ducts by lowering the fan speed. Simultaneously, to further control the mechanical noise of the main fresh air unit, the controller limits the maximum boundary speed of the preset safe operating speed range to a preset silent speed threshold. Even if the target main fresh air unit speed calculated based on static pressure deviation is higher than this preset silent speed threshold, the main fresh air unit is forced to operate at the preset silent speed threshold to avoid excessive noise caused by high fan speeds. If the current operating time is not within the preset low-noise period at night, the above correction operation will not be performed, and the fresh air system will continue to operate according to the original theoretical wind speed and normal safe speed range to ensure the efficiency of fresh air supply. This method realizes the "time-sharing control" of the fresh air system, taking into account both daytime air quality and nighttime quiet requirements, improving the comfort of the user experience and the user-friendly design of the product.

[0045] S103. Calculate the critical static pressure required for the corresponding area to reach the theoretical wind speed under the condition of maximum air valve opening for each branch duct, and determine the maximum critical static pressure as the total static pressure of the target main duct. Among them, the maximum valve opening refers to the fully open state of the electric valve (usually 100%). At this point, the resistance of the electric valve itself is minimal, and its influence on the pipeline resistance can be ignored. For example, if the opening range of the electric valve is 0-100%, the maximum valve opening is the state at 100%. Critical static pressure refers to the minimum static pressure value required to overcome pipeline resistance in a branch duct to increase the fresh air velocity to the theoretical velocity under the condition of maximum valve opening. The unit is Pascal (Pa). For example, a branch duct... To achieve the theoretical wind speed of 1.8 m / s, the required critical static pressure for the duct is 250 Pa. The target total static pressure of the main duct refers to the maximum value selected from the critical static pressures of all branch ducts. It is used to ensure that the main duct can provide sufficient pressure to meet the requirement of all branch ducts to achieve the theoretical wind speed at the maximum valve opening. It is the core target parameter for the speed regulation of the main fresh air unit. For example, if the critical static pressures of each branch duct are 220 Pa, 250 Pa, and 220 Pa respectively, then the target total static pressure of the main duct is determined to be 250 Pa.

[0046] Specifically, the controller first determines the theoretical wind speed, geometric dimensions (diameter / cross-sectional dimensions, length), material (corresponding roughness), local components (elbows, air outlets, etc.) and their drag coefficients, air density, and other basic parameters for each branch duct. Then, following the logic of total resistance = friction resistance + local resistance, it calculates the critical static pressure of a single branch duct (since the damper resistance is negligible at maximum damper opening, the critical static pressure is the total resistance loss of the branch duct at the theoretical wind speed; friction resistance is calculated using the friction resistance coefficient, the length and equivalent diameter of the branch duct, air density, and theoretical wind speed; local resistance is obtained by multiplying the sum of the drag coefficients of each component by the dynamic pressure). Finally, the controller iterates through the critical static pressures of all branch ducts, selects the maximum critical static pressure, and adds a 5%~10% engineering tolerance margin to ensure that the corresponding areas of all branch ducts reach the target total static pressure of the main duct at the theoretical wind speed.

[0047] Optionally, under normal circumstances, the critical static pressure required for the corresponding area to reach the theoretical wind speed under the condition of maximum valve opening for each branch duct can be calculated in the following ways, without limitation: obtain the basic pipe resistance coefficient of the branch duct; retrieve the filter clogging correction coefficient stored after the most recent update, which represents the resistance increment of the terminal filter, and a terminal filter is installed at the end of the branch duct; use the filter clogging correction coefficient to correct the basic pipe resistance coefficient to obtain the current pipe resistance coefficient; based on the preset pressure-resistance-wind speed calculation model, substitute the current pipe resistance coefficient and the theoretical wind speed into the calculation to obtain the critical static pressure required for the corresponding area of ​​the branch duct to reach the theoretical wind speed.

[0048] Specifically, the controller calculates the critical static pressure for each branch duct. Since valve opening affects duct resistance, to eliminate valve interference and ensure the critical static pressure reflects only the resistance requirements of the branch duct itself and its terminal filters, the controller first assumes all electric valves on the branch ducts are at their maximum opening. Then, combining the basic duct resistance coefficient and filter clogging correction coefficient for that branch duct, the controller calculates the current duct resistance coefficient and substitutes it into a preset pressure-resistance-velocity calculation model to determine the critical static pressure required for that branch duct to achieve the theoretical wind speed for the corresponding area. After calculating the critical static pressure for all branch ducts, the controller compares all critical static pressures and selects the highest critical static pressure as the target main duct's total static pressure. This is because the total static pressure of the main duct must meet the fresh air delivery requirements of the branch ducts with the greatest resistance. Only when the main duct provides this maximum critical static pressure can it be ensured that all branch ducts can achieve their respective theoretical wind speeds through valve opening adjustments during subsequent adjustments. This avoids the problem that some areas with high resistance cannot obtain sufficient fresh air due to insufficient pressure in the main duct, and provides a unified pressure guarantee for the precise control of the entire fresh air system.

[0049] Optionally, under normal circumstances, before retrieving the filter clogging correction coefficient stored after the most recent update, the following steps can be performed, or not, and are not limited here: At the preset calibration time, drive all electric air valves to the maximum valve opening. When the main fresh air fan speed remains unchanged within a preset time, collect the actual total static pressure of the main air duct and the actual speed of the main fresh air fan; based on the preset fan standard characteristic curve, query the standard total static pressure of the main air duct corresponding to the actual speed of the main fresh air fan; calculate the ratio of the actual total static pressure of the main air duct to the standard total static pressure of the main air duct, generate the filter clogging correction coefficient, and store it.

[0050] The preset calibration time refers to a specific time point or time interval used to calibrate the filter clogging correction coefficient, such as 3:00 AM daily (a time when there is little activity in the building and low demand for fresh air), or triggered once every 10 hours of cumulative operation. Its purpose is to obtain accurate calibration data with minimal interference to the fresh air system. Driving all electric dampers to their maximum opening degree means the controller sends control commands to all branch duct electric dampers, causing their blades to fully open (100% opening). At this time, the resistance of the electric dampers approaches zero, eliminating the interference of damper opening on duct resistance and ensuring that subsequent static pressure testing only reflects the inherent resistance of the terminal filter and ductwork. The preset duration is a time threshold set to stabilize the main fresh air unit's speed, such as 30 seconds, ensuring a smooth transition from adjustment to stable operation and avoiding data deviations caused by speed fluctuations. The actual total static pressure of the main duct refers to the actual static pressure detected in the main duct at the preset calibration time, measured in Pascals (Pa), such as 280 Pa, reflecting the pressure after filter clogging. Actual duct resistance status; actual main fresh air unit speed refers to the stable operating speed of the main fresh air unit at the preset calibration time, in revolutions per minute (rpm), for example, 1400 rpm; the preset fan standard characteristic curve is a function curve characterizing the mapping relationship between the main fresh air unit speed and the corresponding main duct total static pressure under ideal operating conditions (clean filter, no additional duct resistance), provided by the fan manufacturer and verified experimentally. For example, the standard main duct total static pressure corresponding to the actual main fresh air unit speed of 1400 rpm in the fan standard characteristic curve. Static pressure 200Pa; Standard main duct total static pressure refers to the static pressure value under ideal operating conditions corresponding to the actual main fresh air fan speed, obtained from the fan standard characteristic curve, for example, 200Pa; Filter clogging correction coefficient refers to the ratio of the actual main duct total static pressure to the standard main duct total static pressure, used to quantify the resistance increase caused by filter clogging, without units, for example, the ratio of 280Pa to 200Pa is 1.4, that is, the filter clogging correction coefficient is 1.4, the larger the filter clogging correction coefficient, the more serious the filter clogging.

[0051] Specifically, the controller initiates the calibration process according to a preset calibration time. To eliminate the influence of damper opening on duct resistance, it first drives all branch duct electric dampers to their maximum opening. Then, it waits for the main fresh air fan speed to stabilize, continuously monitoring the main fresh air fan speed. When the main fresh air fan speed fluctuates within a preset time period by less than a set threshold (e.g., ±5 rpm), it is determined that the main fresh air fan speed is stable. At this point, the actual total static pressure of the main duct and the actual main fresh air fan speed are collected to ensure that the data accurately reflects the operating conditions after the filter becomes clogged. Next, the controller calls the preset standard fan characteristic curve, using the actual main fresh air fan speed as the query condition, to accurately match the corresponding standard main duct total static pressure. This standard main duct total static pressure is the ideal static pressure reference when the terminal filter is clean. Subsequently, the controller generates a filter clogging correction coefficient by calculating the ratio of the actual total static pressure of the main duct to the standard total static pressure of the main duct. For example, if the actual total static pressure of the main duct is 280 Pa and the standard total static pressure is 200 Pa, the ratio of 1.4 is the most recently updated filter clogging correction coefficient. This coefficient directly reflects the increase in resistance caused by filter clogging. Finally, the controller stores the generated filter clogging correction coefficient and overwrites previous historical coefficients. This method requires no manual intervention, achieving automatic calibration and updating of the filter clogging correction coefficient. It solves the problems of time-consuming, labor-intensive, and low-accuracy manual detection of filter clogging status, ensuring that subsequent critical static pressure calculations accurately match the actual degree of clogging of the terminal filter. This provides reliable parameter support for the precise control of the fresh air system, while extending the effective service life of the terminal filter and reducing maintenance costs.

[0052] Optionally, after calculating the ratio of the actual total static pressure of the main duct to the standard total static pressure of the main duct, generating and storing the filter clogging correction coefficient, the following steps can be performed, or not, and are not limited here: determine whether the filter clogging correction coefficient is greater than the preset pollution warning threshold; if so, call the preset filter efficiency-face velocity curve, match the highest face velocity corresponding to the filter clogging correction coefficient; convert the highest face velocity into the wind speed protection upper limit value of a single branch duct.

[0053] The preset pollution warning threshold is a critical value used to determine whether the terminal filter needs to activate the protection mechanism. It is determined by the filter material, filtration efficiency requirements, and the safety standards for the operation of the fresh air system. For example, in 1.3, when the filter clogging correction coefficient is greater than the preset pollution warning threshold, it indicates that filter clogging has affected the normal operation of the fresh air system. The preset filter efficiency-face velocity curve is a pre-stored function curve that characterizes the mapping relationship between filter efficiency and the face velocity of air passing through the terminal filter. It is obtained from experimental tests. For example, the filter efficiency is 95% when the face velocity is 0.8 m / s, and drops to 80% when the face velocity is 1.2 m / s. The filter efficiency-face velocity curve reflects the core surface velocity of the airflow. Excessive wind speed will lead to a decrease in filtration efficiency. The maximum face velocity refers to the maximum face velocity that can guarantee the minimum filtration efficiency requirement, which is matched from the filter efficiency-face velocity curve and corresponds to the filter clogging correction coefficient. For example, when the filter clogging correction coefficient is 1.4 (exceeding the preset pollution warning threshold of 1.3), the matched maximum face velocity is 1.0 m / s. The wind speed protection upper limit of a single branch duct refers to the maximum value of the fresh air velocity in the branch duct, which is calculated based on the maximum face velocity according to parameters such as the cross-sectional area of ​​the branch duct. The unit is m / s. For example, if the cross-sectional area of ​​a branch duct is 0.02 m² and the maximum face velocity is 1.0 m / s, the converted wind speed protection upper limit is 1.0 m / s.

[0054] Specifically, the controller retrieves the filter clogging correction coefficient stored since the most recent update and compares it with the preset pollution warning threshold to determine the severity of filter clogging. If the filter clogging correction coefficient is less than or equal to the preset pollution warning threshold, it indicates that the filter clogging is minor and does not affect filtration efficiency or system operation; no further action is required, and the controller continues to operate according to the original control logic. If the filter clogging correction coefficient is greater than the preset pollution warning threshold, it indicates that the filter clogging is severe. In this case, if the controller continues to supply air at the original theoretical wind speed, the excessively high airflow velocity will pass through the clogged terminal filter, resulting in a significant decrease in filtration efficiency (pollutants cannot be fully intercepted). Furthermore, the airflow impact may damage the terminal filter and increase the operating load of the main fresh air unit. Therefore, the controller will call the preset filter filtration efficiency-face velocity curve and, based on the filter clogging correction coefficient, match the highest face velocity that guarantees a minimum filtration efficiency (e.g., 85%) to avoid damaging the filtration effect due to excessively high wind speed. Subsequently, the controller converts the highest surface velocity into the upper limit of the wind speed protection for a single branch duct based on parameters such as the cross-sectional area and duct resistance characteristics of the branch duct. During the conversion process, the non-uniformity of airflow within the branch duct must be considered, and adjustments are made using preset correction coefficients to ensure accurate conversion results. Finally, the controller applies this upper limit of wind speed protection to subsequent theoretical wind speed adjustments and static pressure calculations, limiting the fresh air velocity within the branch duct to this upper limit. This ensures both the filtration efficiency and lifespan of the terminal filter and prevents equipment overload, achieving system self-protection under conditions of excessive filter clogging, and further improving the reliability and stability of the fresh air system.

[0055] S104. Based on the current main fresh air fan speed and the deviation between the target main air duct total static pressure and the current main air duct total static pressure, drive the main fresh air fan to perform speed adjustment operation; Among them, deviation refers to the numerical difference between the target total static pressure of the main air duct and the current total static pressure of the main air duct. It is used to quantify the difference between the current total static pressure of the main air duct and the target total static pressure of the main air duct. If the target total static pressure of the main air duct is greater than the current total static pressure of the main air duct, it is a positive deviation, and vice versa. For example, the deviation between 280Pa and 240Pa is +40Pa. Speed ​​adjustment operation refers to the action of the controller sending control commands to the main fresh air unit to accelerate or decelerate it to change the operating speed. For example, driving the main fresh air unit from 1200rpm to 1500rpm, or from 1800rpm to 1400rpm.

[0056] Specifically, the controller calculates the target total static pressure of the main duct minus the current total static pressure of the main duct, obtaining the deviation (a positive deviation indicates insufficient current static pressure, and a negative deviation indicates excessive current static pressure). Then, based on the built-in adjustment algorithm (such as a PID algorithm) and the current main and fresh air unit speeds, it determines the direction and amount of speed adjustment. The controller sends control commands to the main and fresh air units, driving them to accelerate or decelerate (e.g., from 1200 rpm to 1500 rpm, or from 1800 rpm to 1400 rpm) until the current total static pressure of the main duct approaches the target total static pressure.

[0057] Optionally, under normal circumstances, based on the current main fresh air unit speed and the deviation between the target main duct total static pressure and the current main duct total static pressure, the main fresh air unit speed adjustment operation can be achieved in the following ways, without limitation: Calculate the static pressure difference between the target main duct total static pressure and the current main duct total static pressure; input the static pressure difference into a preset PID control algorithm model to obtain the speed adjustment amount; superimpose the speed adjustment amount with the current main fresh air unit speed to obtain the target main fresh air unit speed; determine whether the target main fresh air unit speed is within the preset safe operating speed range: if yes, drive the main fresh air unit to accelerate or decelerate to the target main fresh air unit speed; if no, drive the main fresh air unit to operate at the maximum or minimum boundary speed of the preset safe operating speed range.

[0058] Specifically, the controller calculates the static pressure deviation between the target total static pressure and the current total static pressure of the main duct, clarifying the magnitude and direction of the difference. Next, the controller inputs this static pressure deviation into a preset PID control algorithm model. The PID control algorithm model performs calculations based on the proportional, integral, and derivative characteristics of the static pressure deviation, dynamically adjusting control parameters to avoid overshoot or lag. For example, when the static pressure deviation is large, the PID control algorithm outputs a large speed adjustment to quickly reduce the deviation; when the static pressure deviation approaches zero, the speed adjustment gradually decreases to ensure smooth adjustment. Subsequently, the controller superimposes the calculated speed adjustment with the current main fresh air unit speed to obtain the target main fresh air unit speed. If the static pressure deviation is positive (current pressure insufficient), the speed adjustment is positive, and the target main fresh air unit speed is higher than the current main fresh air unit speed. If the static pressure deviation is negative (current pressure excessive), the speed adjustment is negative, and the target main fresh air unit speed is lower than the current main fresh air unit speed. Finally, the controller determines whether the target main fresh air fan speed is within the preset safe operating speed range (this preset safe operating speed range is preset according to the fan equipment parameters, energy consumption standards and operating safety requirements, such as 800-2000 rpm). If so, it directly drives the main fresh air fan to accelerate or decelerate to the target main fresh air fan speed. If not, it drives the main fresh air fan to operate at the maximum or minimum boundary speed of the preset safe operating speed range, ensuring that the main fresh air fan achieves pressure regulation within a safe range, providing a stable pressure foundation for precise air supply to each branch duct.

[0059] S105. Calculate the target damper resistance coefficient for each branch duct based on the target main duct's total static pressure and theoretical wind speed. The target damper resistance coefficient refers to the resistance coefficient that the electric damper needs to withstand in order to make the fresh air velocity in the corresponding branch duct reach the theoretical velocity. It has no unit. For example, the target damper resistance coefficient of a certain branch duct is 3.2.

[0060] Specifically, the controller, based on the theoretical wind speed of each branch duct and the determined total static pressure of the target main duct, combined with the friction resistance of the branch ducts and the resistance of local components (elbows, air outlets, etc.) (calculated using parameters such as the diameter, length, material, resistance coefficient of local components, and air density of the branch ducts), calculates the target valve resistance coefficient (unitless, e.g., 3.2) required for each branch duct to reach the theoretical wind speed using the formula: target main duct total static pressure = friction resistance of branch ducts + resistance of local components of branch ducts + resistance of valves in branch ducts. This is done using the formula: target valve resistance coefficient = (target main duct total static pressure - friction resistance of branch ducts - resistance of local components of branch ducts) / (0.5 × air density × theoretical wind speed²).

[0061] Optionally, under normal circumstances, the target valve resistance coefficient of each branch duct can be calculated based on the total static pressure and theoretical wind speed of the target main duct. This can be achieved in the following way, without limitation: Substitute the total static pressure and theoretical wind speed of the target main duct into the flow resistance coefficient calculation formula to obtain the total flow resistance coefficient required for the corresponding area of ​​each branch duct to achieve the theoretical wind speed; obtain the pipe resistance coefficient of each branch duct; subtract the pipe resistance coefficient from the total flow resistance coefficient to obtain the target valve resistance coefficient of each branch duct.

[0062] The flow resistance coefficient calculation formula is a pre-defined mathematical formula used to calculate the flow resistance coefficient based on the total static pressure and theoretical wind speed of the target main duct. The total flow resistance coefficient is the coefficient corresponding to all the resistance that a branch duct needs to overcome to reach the theoretical wind speed, including the inherent resistance of the duct and the resistance of the damper. It has no unit, for example, the total flow resistance coefficient of a branch duct is 5.8. The duct resistance coefficient is the inherent resistance coefficient caused by the structure of the branch duct itself (such as duct diameter, length, bends), excluding the resistance of the damper. It has no unit, for example, the duct resistance coefficient of a branch duct is 2.6. This duct resistance coefficient can be calculated or experimentally measured through duct structure parameters and pre-stored in the controller.

[0063] Specifically, for each branch duct, the controller substitutes the total static pressure of the target main duct and the theoretical wind speed of the corresponding area into the flow resistance coefficient calculation formula. Combined with standard air density parameters, it calculates the total flow resistance coefficient required for the branch duct to achieve the theoretical wind speed. This total flow resistance coefficient comprehensively reflects the total resistance that the duct and valve need to overcome together. Next, the controller retrieves the duct resistance coefficient of the branch duct (this duct resistance coefficient is an inherent property of the duct, pre-determined and stored through experiments or calculations, and remains unchanged if the duct structure is unchanged). Then, the controller subtracts the duct resistance coefficient from the total flow resistance coefficient to obtain the target valve resistance coefficient. By subtracting the inherent duct resistance from the total resistance, the controller accurately separates the valve resistance that the electric valve needs to handle, thus providing a clear target for valve opening adjustment.

[0064] S106. Based on the preset damper opening-resistance curve, query the target damper opening corresponding to the target damper resistance coefficient, so as to drive the electric damper on each branch duct to execute the target damper opening.

[0065] The preset damper opening-resistance curve is plotted by experimentally testing the damper resistance coefficient under different electric damper openings. For example, the damper resistance coefficient is 2.1 when the electric damper opening is 30% and 3.2 when the electric damper opening is 50%. Each electric damper opening in the damper opening-resistance curve corresponds to a unique damper resistance coefficient, and vice versa. The target damper opening refers to the degree of opening of the target damper corresponding to the target damper resistance coefficient, which is found in the damper opening-resistance curve and is usually expressed as a percentage (%).

[0066] Specifically, for each branch duct, the controller retrieves a preset valve opening-resistance curve. This curve is plotted based on actual test data of the specific electric valve model, ensuring the accuracy of the mapping relationship. Next, the controller uses the target valve resistance coefficient as a query condition and performs a precise match within the preset valve opening-resistance curve. If the target valve resistance coefficient matches an existing data point in the curve, the corresponding target valve opening is directly obtained. If it's an intermediate value, the corresponding target valve opening is calculated using algorithms such as linear interpolation. Subsequently, the controller sends a control command to the electric valve on that branch duct. Upon receiving the control command, the electric valve's internal motor drives the blades to rotate, adjusting to the target valve opening.

[0067] By employing the above technical solution, the controller collects air quality data from each area and, combined with a preset air quality-wind speed curve, determines the theoretical wind speed for each area. This enables dynamic sensing of the fresh air demand in all areas, ensuring precise matching of fresh air supply with regional air conditions and avoiding insufficient fresh air in polluted areas and excessive fresh air in clean areas. The controller calculates the critical static pressure required for each branch duct to achieve the theoretical wind speed under maximum valve opening conditions, and sets the maximum critical static pressure as the target main duct's total static pressure, providing a basic pressure guarantee for meeting the fresh air demand in all areas. The controller, combined with a PID control algorithm, adjusts the main fresh air unit's speed, ensuring both the stable achievement of the target main duct's total static pressure and efficient energy-saving operation of the main fresh air unit. Simultaneously, the controller matches the target valve resistance coefficient with the corresponding target valve opening, achieving independent and precise control of each branch duct. This allows different areas to obtain the appropriate fresh air volume according to their own fresh air needs, ultimately improving indoor air quality in all areas while reducing energy waste and balancing comfort and economy.

[0068] The controller in the embodiments of this invention is described below from the perspective of hardware processing. Please refer to [link / reference]. Figure 2 This is a schematic diagram of the physical device structure of the controller in an embodiment of this application.

[0069] It should be noted that, Figure 2The controller structure shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0070] like Figure 2 As shown, the controller includes a CPU 201, which can perform various appropriate actions and processes based on a program stored in the read-only memory ROM 202 or a program loaded from the storage section 208 into the random access memory RAM 203, such as performing the methods described in the above embodiments. The RAM 203 also stores various programs and data required for system operation. The CPU 201, ROM 202, and RAM 203 are interconnected via a bus 204. An I / O interface 205 is also connected to the bus 204.

[0071] The following components are connected to I / O interface 205: input section 206 including audio input devices, push-button switches, etc.; output section 207 including a liquid crystal display (LCD) and audio output devices, indicator lights, etc.; storage section 208 including a hard disk, etc.; and communication section 209 including a network interface card such as a LAN (Local Area Network) card, modem, etc. Communication section 209 performs communication processing via a network such as the Internet. Drive 210 is also connected to I / O interface 205 as needed. Removable media 211, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 210 as needed so that computer programs read from them can be installed into storage section 208 as needed.

[0072] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 209, and / or installed from removable medium 211. When the computer program is executed by CPU 201, it performs the various functions defined in the present invention.

[0073] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0074] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, program segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those shown in the drawings.

[0075] Specifically, the controller in this embodiment includes a processor and a memory. The memory stores a computer program, and when the computer program is executed by the processor, it implements the distributed fresh air system control method provided in the above embodiment.

[0076] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the controller described in the above embodiments; or it may exist independently and not assembled into the controller. The storage medium carries one or more computer programs that, when executed by a processor of the controller, cause the controller to implement the distributed fresh air system control method provided in the above embodiments.

[0077] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0078] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0079] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A distributed fresh air system control method, characterized in that, A controller for a fresh air system, the fresh air system further including a main fresh air unit, a main duct, and multiple branch ducts connected to different areas, each of the branch ducts being equipped with an adjustable-opening electric damper, the method comprising: Collect current main fresh air unit speed, current main air duct total static pressure, and air detection data for the area corresponding to each of the branch air ducts; Based on the air detection data and the preset air quality-wind speed curve, the theoretical wind speed for each area is determined. Calculate the critical static pressure required to reach the theoretical wind speed in the corresponding area of ​​each branch duct under the condition of maximum valve opening, and determine the maximum critical static pressure as the total static pressure of the target main duct. Based on the current main fresh air unit speed and the deviation between the target main air duct total static pressure and the current main air duct total static pressure, the main fresh air unit is driven to perform speed adjustment operation; Calculate the target valve resistance coefficient for each branch duct based on the target main duct total static pressure and the theoretical wind speed; Based on the preset valve opening-resistance curve, the target valve opening corresponding to the target valve resistance coefficient is queried, so as to drive the electric valve on each branch duct to execute the target valve opening.

2. The method according to claim 1, characterized in that, The calculation of the critical static pressure required to achieve the theoretical wind speed in the corresponding area of ​​each branch duct under the condition of maximum valve opening specifically includes: Obtain the basic pipeline resistance coefficient of the branch duct; Retrieve the filter clogging correction coefficient stored after the most recent update. The filter clogging correction coefficient represents the resistance increment of the terminal filter. The terminal filter is provided at the end of the branch duct. The filter clogging correction coefficient is used to correct the basic pipeline resistance coefficient to obtain the current pipeline resistance coefficient. Based on the preset pressure-resistance-wind speed calculation model, the current pipeline resistance coefficient and the theoretical wind speed are substituted into the calculation to obtain the critical static pressure required for the corresponding area of ​​the branch duct to reach the theoretical wind speed.

3. The method according to claim 2, characterized in that, Prior to the step of retrieving the filter clogging correction factor stored since the most recent update, the method further includes: At the preset calibration time, all the electric air valves are driven to the maximum valve opening. When the main fresh air fan speed remains unchanged within the preset time, the actual total static pressure of the main air duct and the actual speed of the main fresh air fan are collected. Based on the preset standard characteristic curve of the fan, query the standard main duct total static pressure corresponding to the actual main fresh air fan speed; Calculate the ratio of the actual total static pressure of the main duct to the total static pressure of the standard main duct, generate and store the filter clogging correction coefficient.

4. The method according to claim 3, characterized in that, After the steps of calculating the ratio of the actual total static pressure of the main duct to the standard total static pressure of the main duct, generating and storing the filter clogging correction coefficient, the method further includes: Determine whether the filter clogging correction coefficient is greater than the preset pollution warning threshold; If so, the preset filter efficiency-face velocity curve is invoked to match the highest face velocity corresponding to the filter clogging correction coefficient. The highest surface wind speed is converted into the wind speed protection limit value for a single branch duct.

5. The method according to claim 1, characterized in that, The step of driving the main fresh air unit to perform speed adjustment operation based on the current main fresh air unit speed and the deviation between the target main duct total static pressure and the current main duct total static pressure specifically includes: Calculate the static pressure difference between the target total static pressure of the main duct and the current total static pressure of the main duct; The static pressure difference is input into a preset PID control algorithm model to obtain the speed adjustment amount; The target main fresh air unit speed is obtained by superimposing the speed adjustment amount with the current main fresh air unit speed. Determine whether the target main fresh air unit's speed is within the preset safe operating speed range: If so, the main fresh air unit is driven to accelerate or decelerate to the target main fresh air unit speed; If not, then drive the main fresh air unit to operate at the maximum or minimum boundary speed within the preset safe operating speed range.

6. The method according to claim 5, characterized in that, After the step of determining the theoretical wind speed for each area based on the air quality detection data and the preset air quality-wind speed curve, the method further includes: Obtain the current running time and determine whether the current running time is within a preset low-noise nighttime period; If so, then the preset noise suppression coefficient is invoked, and the noise suppression coefficient is multiplied by the theoretical wind speed to obtain the corrected theoretical wind speed; The maximum boundary speed of the preset safe operating speed range is limited to a preset silent speed threshold.

7. The method according to claim 1, characterized in that, The calculation of the target damper resistance coefficient for each branch duct based on the target main duct total static pressure and the theoretical wind speed specifically includes: Substituting the total static pressure of the target main duct and the theoretical wind speed into the flow resistance coefficient calculation formula, the total flow resistance coefficient required to achieve the theoretical wind speed is obtained for the corresponding area of ​​each branch duct. Obtain the pipe resistance coefficient for each of the branch ducts; Subtracting the pipeline resistance coefficient from the total flow resistance coefficient yields the target valve resistance coefficient for each branch duct.

8. A controller, characterized in that, The controller includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, and the one or more processors invoking the computer instructions to cause the controller to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instructions are executed on the controller, the controller causes the controller to perform the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product is run on the controller, the controller performs the method as described in any one of claims 1-7.

Images