A distributed collaborative makeup air system for commercial food service buildings

Abstract

This application provides a distributed collaborative air supply system for commercial and catering buildings, relating to the field of intelligent building technology. It includes: multiple air supply units distributed throughout the building interior, each unit comprising an energy storage module for processing fresh air; an energy supply unit for providing energy to the energy storage module; and a central controller connected to each air supply unit and the energy supply unit. The central controller is configured to control the energy supply unit to store energy in the energy storage module during a first time period; and during a second time period different from the first, to control the operation of each air supply unit, utilizing the energy stored in the energy storage module to process fresh air and supply it into the building, thereby coordinating with the building's exhaust system to maintain indoor environmental balance. This application achieves on-demand energy release based on real-time demand, ensuring the system's economic efficiency in utilizing off-peak electricity storage, and further improving operational energy efficiency and precisely maintaining the indoor environment through dynamic response.

Description

Technical Field

[0001] This invention belongs to the field of intelligent building technology, specifically relating to a distributed collaborative air supply system for commercial catering buildings. Background Technology

[0002] In the ventilation energy consumption management of commercial and catering buildings, one approach to reduce operating costs during peak electricity price periods is to pre-generate and store cooling or heating energy for processing fresh air during off-peak hours at night, and then use it during peak daytime business hours. However, existing make-up air systems that implement this approach suffer from inflexible coupling between the energy storage module and the air supply terminal in terms of control logic, often only achieving simple timed charging and discharging. After the system charges the energy storage module during off-peak hours, it often releases energy in a fixed pattern during business hours, unable to make fine-tuned adjustments based on the actual indoor heat and humidity load, changes in occupancy, or the real-time dynamics of the exhaust system. This leads to two consequences: first, the stored energy may be released too early or too quickly, failing to effectively maintain the environment in the later stages of business; second, the energy release rate and temperature cannot be optimized according to actual needs, resulting in energy waste or decreased comfort. Summary of the Invention

[0003] In view of the above-mentioned defects or deficiencies in the prior art, a distributed collaborative air supply system for commercial catering buildings is provided, comprising:

[0004] Multiple make-up air units are distributed throughout the building interior, each of which includes an energy storage module for processing fresh air;

[0005] An energy supply unit is used to provide energy to the energy storage module;

[0006] The main controller is connected to each of the aforementioned air supply units and the energy supply unit; the main controller is configured to:

[0007] The energy supply unit is controlled to store energy into the energy storage module during the first time period;

[0008] In a second time period, which is different from the first time period, the operation of each of the air supply units is controlled to process fresh air and send it into the room using the energy stored in the energy storage module, so as to maintain the indoor environmental balance in coordination with the building's exhaust system.

[0009] According to the technical solution provided in this application, the first time period includes the off-peak electricity period of the power grid and / or the period of sufficient solar energy; the second time period includes the peak electricity period of the power grid and / or the business hours of the building.

[0010] During the first time period, the main controller controls the energy supply unit to prioritize the use of solar energy and switches to off-peak electricity from the grid when solar energy is insufficient, so as to store energy for the energy storage module.

[0011] During the second time period, the main controller controls the operation of each of the air supply units, using the energy stored in the energy storage module to process fresh air and supply it to the room, while stopping or reducing the energy obtained from the energy supply unit.

[0012] According to the technical solution provided in this application, the energy storage module is made of phase change material; each of the air supply units also includes a local control module that is communicatively connected to the main controller;

[0013] The system also includes a sensor network connected to the main controller for collecting environmental parameters and personnel data from multiple independent areas inside the building.

[0014] The main controller is further configured to:

[0015] Based on the environmental parameters and personnel data, predict the environmental load of multiple independent areas;

[0016] Based on the environmental load of each independent area, a corresponding air supply parameter control instruction is generated for each independent area, and the air supply parameter control instruction includes a target air supply volume or a target air supply temperature.

[0017] The local control module is configured to: receive air supply parameter control commands issued by the main controller corresponding to its independent area, and control the fan speed and heating / cooling device of the make-up air unit to achieve the target air supply volume or target air supply temperature.

[0018] According to the technical solution provided in this application, the environmental parameters include the indoor static pressure of each independent area; the make-up air system further includes:

[0019] An exhaust volume monitoring module is used to obtain the real-time exhaust volume of the exhaust system;

[0020] The main controller is further configured to:

[0021] Based on the indoor static pressure and the real-time exhaust volume, calculate the compensation air volume required to maintain the target pressure of each of the independent zones;

[0022] When generating the air supply parameter control command, the compensation air volume is integrated with the air supply demand based on the environmental load prediction to determine the target air supply volume, so that the make-up air volume, exhaust air volume and pressure status of each independent area are dynamically matched to suppress the disorderly infiltration of air or the diffusion of pollutants caused by negative pressure.

[0023] According to the technical solution provided in this application, the main controller is specifically configured for:

[0024] Receive real-time environmental data, the real-time exhaust volume, and environmental load predicted based on historical data;

[0025] Based on the relationship between the rate of change of the real-time exhaust volume and the exhaust sudden change threshold, the dominant control objective in the current control cycle is determined.

[0026] If the rate of change of the real-time exhaust volume exceeds the exhaust sudden change threshold, the dominant control target is set to pressure balance, and when the main controller generates the air supply parameter control command, the compensation air volume is used as the main determining factor of the target air supply volume.

[0027] If the rate of change of the real-time exhaust volume is lower than the exhaust sudden change threshold, the dominant control objective is set to environmental comfort and energy saving. When the main controller generates the air supply parameter control command, it takes the air supply demand based on the environmental load prediction as the main determining factor of the target air supply volume, and makes fine adjustments in conjunction with the compensation air volume.

[0028] According to the technical solution provided in this application, the main controller is further configured to:

[0029] The multi-objective fusion weighting coefficient is dynamically calculated based on the rate of change of the real-time exhaust volume, the remaining energy status of the energy storage module, the current electricity price period, and the deviation of the real-time environmental parameters of each independent area from their target values.

[0030] The multi-objective fusion weighting coefficient is used to dynamically adjust the ratio of the compensation air volume and the air supply demand based on environmental load prediction in the target air volume when generating the air supply parameter control command.

[0031] The master controller determines the synthesis ratio according to the following logic:

[0032] When the rate of change of the real-time exhaust volume is higher, the remaining energy of the energy storage module is lower, and the current period is the peak electricity price period, the weight of the compensation air volume in the target air supply volume is increased to prioritize ensuring rapid balance of indoor pressure and prevent disorderly infiltration from causing a surge in air conditioning load.

[0033] When the rate of change of the real-time exhaust volume is stable, the remaining energy of the energy storage module is sufficient, and the environmental parameters of each area are close to the target value, the weight of the air supply demand based on the environmental load prediction in the target air supply volume is increased to optimize comfort and reduce fan energy consumption.

[0034] According to the technical solution provided in this application, the building interior includes multiple independent areas that are functionally sequentially related, and the air supply system further includes:

[0035] A regional differential pressure sensor network is installed at the connecting parts between critical adjacent areas where there is a risk of pollutant diffusion, for real-time monitoring of the pressure difference between the critical adjacent areas;

[0036] The main controller is further configured to:

[0037] Based on the cleanliness requirements and pollution source distribution within the building, a directional positive pressure gradient target from the pollution risk zone to the clean zone is preset for multiple independent areas;

[0038] Based on the real-time monitoring data of the regional differential pressure sensor network and the real-time exhaust volume of the exhaust system, the gradient compensation air volume required for each independent region to maintain the directional positive pressure gradient target is dynamically calculated.

[0039] The gradient compensation air volume required for each independent area is integrated into the corresponding air supply parameter control command to control the air supply volume of the make-up air unit in each independent area, so as to guide the air from the clean area to the pollution risk area.

[0040] According to the technical solution provided in this application, the main controller is further configured to:

[0041] Real-time monitoring of the rate of change of the exhaust volume of the exhaust system;

[0042] If the rate of change of the exhaust volume is detected to exceed the sudden change response threshold within a unit time, it is determined to be a sudden exhaust condition.

[0043] Under the aforementioned sudden exhaust ventilation condition, the main controller activates a gradient enhancement mode, which is as follows:

[0044] Within the preset emergency response time, the make-up air units located in the pollution risk area and its immediate downstream area are preferentially adjusted to increase their target air supply volume by a rate not less than the preset increase ratio, so as to consolidate and increase the actual pressure gradient maintained according to the directional positive pressure gradient target.

[0045] According to the technical solution provided in this application, the main controller is also communicatively connected to the building's indoor air conditioning system; the main controller is further configured to:

[0046] The compressor load rate of the air conditioning system is acquired in real time; at the same time, the deviation between the actual temperature of each independent area after adjustment by the make-up air system and the set temperature of the air conditioner is monitored.

[0047] The cooperative operation mode is triggered when both of the following conditions are met:

[0048] The compressor load rate of the air conditioning system continuously exceeds the high load threshold for a first duration.

[0049] There exists at least one independent area where the actual temperature deviates from the air conditioner's set temperature beyond the allowable threshold, and the direction of this deviation is contrary to the operating mode of the air conditioning system.

[0050] In the cooperative operation mode, the main controller issues a cooperative adjustment command to the air supply unit in the affected area. This command adjusts the air supply temperature setpoint to be close to the air conditioning setpoint without changing the target air supply volume.

[0051] According to the technical solution provided in this application, the main controller is further configured to:

[0052] In the cooperative operation mode, based on the expected energy consumption caused by adjusting the supply air temperature setpoint, as well as the current energy cost and the available energy status of the energy storage module, a decision is made on whether to execute, partially execute, or modify the cooperative adjustment command.

[0053] Compared with existing technologies, the beneficial effects of this application are as follows: It achieves on-demand energy release based on real-time demand: By coordinating and controlling the operation of each air supply unit during the second time period (e.g., business hours) through the central controller, the system can utilize the energy stored in the energy storage module to process fresh air. The timing, intensity (supply air temperature), and range (supply air volume) of energy release are no longer fixed, but are dynamically linked to the building's exhaust system and the indoor environmental balance requirements. This allows the stored energy to be released at the most needed time and place with the most appropriate intensity, avoiding energy waste or environmental control failure caused by rigid control. Simultaneously, it lays the foundation for intelligent energy saving and dynamic balance control: The time-sharing control framework of energy storage in the first time period and energy consumption in the second time period, combined with the central controller's proactive coordination of the air supply unit operation, provides core architectural support for the system to achieve a higher level of intelligent optimization. It ensures that the system, while utilizing off-peak electricity for energy storage, further improves operational energy efficiency and precisely maintains the indoor environment through dynamic response. Attached Figure Description

[0054] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0055] Figure 1 A schematic diagram of a distributed collaborative air supply system for commercial catering buildings provided in an embodiment of this application;

[0056] The text labels in the image represent:

[0057] 1. Main controller; 2. Energy supply unit; 3. Energy storage module; 4. Make-up air unit; 5. Exhaust system. Detailed Implementation

[0058] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0059] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0060] As mentioned in the background section regarding technical issues, this application proposes a distributed collaborative air supply system for commercial catering buildings, such as... Figure 1 As shown, it includes:

[0061] Multiple make-up air units 4 are distributed in the interior of the building, each of the make-up air units 4 including an energy storage module 3 for processing fresh air;

[0062] Energy supply unit 2 is used to provide energy to the energy storage module 3;

[0063] The main controller 1 is connected to each of the aforementioned air supply units 4 and the energy supply unit 2; the main controller 1 is configured to:

[0064] The energy supply unit 2 is controlled to store energy into the energy storage module 3 during the first time period;

[0065] In a second time period, which is different from the first time period, the operation of each of the air supply units 4 is controlled to process fresh air and send it into the room using the energy stored in the energy storage module 3, so as to maintain the indoor environmental balance in conjunction with the building's exhaust system 5.

[0066] Specifically, the distributed collaborative air supply system refers to a system that is not a traditional centralized system where a single large unit supplies air to the entire building through a duct network. Its core characteristics lie in its distributed and collaborative nature. Distributed nature is reflected in the system's physical structure, with multiple air supply units 4 dispersed throughout the building. Collaboration is reflected in the system's control logic, where these dispersed units do not operate independently but are coordinated by a central controller 1, cooperating with the building's existing exhaust system 5 to jointly achieve environmental control goals. Air supply unit 4: This is the basic module for the system's air supply function. Its quantity and installation location can be planned according to the building's space size and functional zoning (such as kitchen stove area, food preparation area, private rooms, and dining area). Each unit is a relatively independent enclosure. Its core component is the energy storage module 3, which, when implemented, is a container or component encapsulated with specific materials. Its function is to absorb and store energy (such as thermal or cold energy) during a certain period and release that energy during another period to change the temperature of the air flowing through it (i.e., fresh air). For example, in winter, it can store heat to preheat cold outdoor fresh air; in summer, it can store cold air to precool hot outdoor fresh air. The make-up air unit 4 also includes necessary fans, air filters, air inlets and outlets, and control interfaces. Energy supply unit 2: This is a collection of devices or interfaces that provide an energy source for the energy storage modules 3. In implementation, it can take many specific forms. A common form is a power interface connected to the building's power grid. More preferred implementations also include renewable energy utilization devices, such as solar photovoltaic panels integrated with the building's roof or facade and a matching power conversion system, or solar collectors and circulation pipelines. The function of the energy supply unit 2 is to deliver electrical or thermal energy to the energy storage modules 3 of each make-up air unit 4 according to instructions. Main controller 1: This is typically a hardware device (such as an industrial PLC, dedicated industrial computer, or high-performance embedded system) containing a processor, memory, and communication interfaces, and runs dedicated control software. In its implementation, the main controller 1 establishes a bidirectional data connection with each make-up air unit 4 and energy supply unit 2 via wired (such as RS485 bus, Ethernet) or wireless (such as LoRa, Zigbee, Wi-Fi) communication protocols. Its configured control logic is time-segmented.

[0067] First period: During this period (e.g., the off-peak electricity hours from midnight to 6 a.m., or when there is sufficient sunlight during the day), the main controller 1 sends a command to the energy supply unit 2 to start the energy supply. The energy supply unit 2 then begins to work, delivering the generated energy (electricity or heat) to the energy storage modules 3 of each air supply unit 4 to complete the energy storage. This process can be figuratively understood as charging the system's battery (energy storage module 3).

[0068] The second time period: This is a time period different from the first time period (e.g., peak restaurant hours at noon and in the evening, or peak electricity usage during the day). During this time, the main controller 1 controls each make-up air unit 4 to start operating. The fans of the make-up air unit 4 start, introducing fresh air from the outside. As the fresh air flows through the energy storage module 3, it exchanges heat with the module, thus being heated or cooled (i.e., treated). The treated fresh air is then delivered into the room. Simultaneously, the main controller 1 ensures that this air delivery process coordinates with the building's exhaust system 5 (i.e., existing equipment such as kitchen fume purification units and bathroom exhaust fans). Specifically, the main controller 1 can dynamically adjust the total air volume of the make-up air units 4 or the air volume of specific areas based on the start / stop status or exhaust volume of the exhaust system 5, with the aim of jointly maintaining indoor environmental balance, mainly referring to air pressure balance and temperature balance.

[0069] The technical principle of this implementation is as follows: energy storage is decentralized to each air supply terminal (makeup air unit 4), forming numerous distributed micro-energy storage stations. This follows the principle of "energy stored and used locally," greatly reducing energy losses (including heat / cold loss and transmission power loss) along the transmission path from the central storage tank to the end user, and improving the terminal efficiency of energy utilization. The central controller 1, as the central decision-making unit, performs unified scheduling of distributed resources based on time strategies (first / second time periods) and system interaction (sensing exhaust status). In terms of time, it follows the principle of economic optimization in scheduling energy charging and discharging. In terms of space and intensity, based on the negative pressure distribution caused by the exhaust system 5, it commands the corresponding makeup air unit 4 to start and adjust its output, matching the makeup air behavior with the exhaust behavior in time and space, thereby accurately offsetting the negative pressure and maintaining the indoor and outdoor pressure difference within a reasonable range. This active and coordinated makeup air method is more advanced and energy-efficient in principle than traditional passive infiltration or timed and fixed-speed makeup air.

[0070] This implementation achieves energy time-shifting, reducing operating costs: the system stores energy in the first period (low-cost or free energy period) and releases and operates in the second period (high-cost or high-demand energy period), achieving optimized energy allocation in the time dimension. This can directly utilize the peak-valley electricity price difference of the power grid, or store energy for nighttime use when solar energy is abundant, significantly reducing direct electricity costs during peak electricity consumption periods. It also improves responsiveness and energy efficiency to dynamic loads: the distributed air supply unit 4 can quickly deliver air locally, avoiding energy loss and response delays caused by long-distance ductwork in centralized systems. The coordinated control logic of the main controller 1 ensures that the air supply volume closely follows changes in the exhaust volume, promptly balancing indoor negative pressure and reducing untreated air infiltrating from the outside, thereby indirectly reducing the air conditioning energy consumption required to treat this infiltrated air. Furthermore, the modular distributed architecture makes the system layout highly flexible, easily adaptable to commercial and catering buildings with different spatial layouts, especially easy to install in renovation projects, eliminating the need for complex central ductwork systems. Simultaneously, the failure of a single unit does not affect the operation of other units, improving overall reliability.

[0071] In a preferred embodiment, the first time period includes off-peak electricity hours and / or periods with abundant solar energy; the second time period includes peak electricity hours and / or the building's operating hours;

[0072] During the first time period, the main controller 1 controls the energy supply unit 2 to prioritize the use of solar energy, and switches to off-peak electricity from the grid when solar energy is insufficient, so as to store energy for the energy storage module 3.

[0073] During the second time period, the main controller 1 controls the operation of each of the air supply units 4, uses the energy stored in the energy storage module 3 to process fresh air and send it into the room, and at the same time stops or reduces the energy obtained from the energy supply unit 2.

[0074] Specifically, off-peak electricity hours refer to the billing periods with relatively low electricity prices set by the power company based on grid load conditions. Specific time periods vary depending on region and seasonal policies, but are commonly nighttime hours (e.g., 10:00 PM to 8:00 AM the following day). In implementation, the main controller 1 needs to store or be able to obtain the local peak-valley electricity price schedule via the network. The controller can accurately determine whether it is currently in an off-peak electricity hour by synchronizing with its built-in real-time clock or receiving network time protocols. Sufficient solar energy hours refer to the time periods when outdoor sunlight intensity is sufficient for solar energy utilization devices to effectively generate electricity. In implementation, an irradiance sensor needs to be installed near the solar energy device (e.g., photovoltaic panels or collectors). The main controller 1 continuously reads the sensor data. An irradiance threshold can be set (e.g., greater than 300 W / m²), and when the measured value consistently exceeds this threshold, it is determined to be a "sufficient solar energy hour." This usually corresponds to sunny or cloudless days. Building operating hours refer to the main periods during which a restaurant or catering building is open to the public and provides services. For example, for a restaurant, the business hours might be lunch (11:00-14:00) and dinner (17:00-21:00). In implementation, the daily business hours can be pre-set on the human-machine interface of the main controller 1, or automatically generated by the control system based on historical customer flow data. Prioritizing solar energy and switching to off-peak grid electricity when solar energy is insufficient: this strategy clarifies the priority and switching logic for various energy sources. The specific implementation steps are as follows:

[0075] The main controller 1 first determines whether the current period is a time of abundant solar energy. If so, it sends a command to the energy supply unit 2 to start the solar energy utilization device (such as starting the photovoltaic inverter to generate electricity in the grid, or starting the solar thermal circulation pump) to use the electrical or thermal energy generated by solar energy to charge the energy storage module 3.

[0076] If the current period is not a time of abundant solar energy (such as at night or on a cloudy or rainy day), the main controller 1 further determines whether the current period is a time of off-peak electricity from the power grid. If so, it issues a command to switch to the grid power supply mode, using off-peak electricity to charge the energy storage module 3. This switching action can be implemented through the intelligent distribution cabinet or power switching module within the energy supply unit 2. The main controller 1 controls relays or contactors via digital output signals or communication commands to select the power supply circuit. Stopping or reducing energy intake from the energy supply unit 2: During the second period (such as peak hours or business hours), the main controller 1 will instruct the energy supply unit 2 to reduce its output or completely shut down external energy input. For example, shutting down the grid power supply circuit or putting the solar energy device into standby mode. At this time, the energy required for the operation of the supplementary wind unit 4 comes entirely from the energy stored in the energy storage module 3 during the first period. This means that when energy costs are highest or demand is greatest, the system mainly relies on pre-stored cheap energy to operate, achieving decoupling of operating costs from energy demand.

[0077] This implementation maximizes economic efficiency and energy saving: by prioritizing the use of zero-cost solar energy, followed by low-cost off-peak electricity from the grid, this strategy minimizes energy acquisition costs at the source. Stopping the use of expensive grid electricity during peak business hours further avoids high electricity bills, significantly reducing the system's total lifecycle operating costs. It also increases the proportion of renewable energy utilization: by prioritizing solar energy, it proactively converts unstable and intermittent solar energy into stable and usable heat or cold energy for storage, improving the building's own utilization of renewable energy and helping to reduce dependence on fossil fuels, thus providing environmental benefits. Furthermore, it enhances the strategic and robust nature of system operation: by concretizing the concept of time-of-use control into an operable energy dispatch strategy based on multiple conditions, it frees the system from reliance on a single energy source, forming a stable energy supply system with solar energy as the primary source, off-peak electricity as a supplement, and peak electricity not being used, thus enhancing the system's ability to cope with energy supply fluctuations.

[0078] In a preferred embodiment, the energy storage module 3 is made of a phase change material; each of the air supply units 4 also includes a local control module that is communicatively connected to the main controller 1;

[0079] The system also includes a sensor network connected to the main controller 1, used to collect environmental parameters and personnel data from multiple independent areas inside the building;

[0080] The main controller 1 is further configured to:

[0081] Based on the environmental parameters and personnel data, predict the environmental load of multiple independent areas;

[0082] Based on the environmental load of each independent area, a corresponding air supply parameter control instruction is generated for each independent area, and the air supply parameter control instruction includes a target air supply volume or a target air supply temperature.

[0083] The local control module is configured to: receive the air supply parameter control command issued by the main controller 1 corresponding to its independent area, and control the fan speed and heating / cooling device of the make-up air unit 4 to achieve the target air supply volume or target air supply temperature.

[0084] Specifically, the energy storage module 3 is made of phase change material (PCM): PCM is a substance that undergoes a phase change (e.g., from solid to liquid, or from liquid to solid) at a specific temperature (phase change temperature), absorbing or releasing a large amount of latent heat in the process. In implementation, the selected PCM (e.g., inorganic hydrated salts for low-temperature cold storage, or organic paraffin and fatty acid mixtures for medium-temperature heat storage) is encapsulated in a metal or plastic container, typically with fins on the outside to increase the heat exchange area. This module is installed in the air duct of the make-up air unit 4. When energy storage is needed, the energy-carrying medium flowing through the module (e.g., cold water, hot water, or an electric heater) melts or solidifies the PCM, completing heat or cold storage. When fresh air needs to be processed, outdoor air flows through the module, exchanging heat with the PCM; the air is heated or cooled, while the PCM releases energy and gradually undergoes a phase change. Local control module: This is a sub-controller deployed inside each make-up air unit 4. It typically consists of a microcontroller (MCU), motor drive circuitry, communication module, and signal acquisition circuitry. Its functions are as follows: on the one hand, it receives instructions from the main controller 1 (such as the target wind speed and target temperature); on the other hand, it controls the speed of the fan in this unit (by adjusting the motor drive voltage or frequency), and controls the start / stop and power of heating / cooling devices (such as the on / off state of electric heaters or the frequency of heat pump compressors). Simultaneously, it may also upload sensor data from this unit (such as outlet air temperature and fan status) to the main controller 1. Sensor network: This consists of a large number of sensor nodes distributed throughout various independent areas of the building (such as different private rooms, different sections of the lobby, and different functional corners of the kitchen). Each node typically integrates multiple sensors, such as: environmental parameter sensors: temperature and humidity sensors, carbon dioxide concentration sensors, PM2.5 sensors, etc. Personnel data sensors: These can use passive infrared sensors to count the presence of people, or use camera-based visual analysis technology to estimate the number of people in an area, or indirectly determine the number by analyzing mobile phone signal density using Wi-Fi probes. These sensor nodes periodically report the collected data to the main controller 1 via wired or wireless means. Predicting the environmental load of multiple independent areas: In implementation, the main controller 1 uses historical and real-time data (temperature, humidity, CO2 concentration, number of people) uploaded from the sensor network as input. It uses a pre-set mathematical model or machine learning algorithm (such as time series analysis, regression model, neural network) for analysis and calculation (the training sample set is constructed based on historical time series data accumulated from the long-term operation of the building; its core inputs include time information, indoor and outdoor environmental parameters, real-time personnel data of each area, and equipment operating status; the output is the actual environmental load value at the corresponding moment or in the future, used to train the model to learn the mapping relationship between environmental parameters, personnel activities, and load demand). For example, the algorithm can learn a pattern such as "during lunchtime, when the number of people in area A reaches 30, an additional X kW of cooling is usually required to maintain the set temperature of 26°C."Based on current personnel data and environmental trends, the algorithm predicts the cooling or heating load required to maintain the set environment in each area over a future period (the next 15 minutes), as well as the amount of fresh air (ventilation load) required to maintain air quality. It then generates and executes air supply parameter control instructions: Based on the predicted environmental load, the main controller 1 calculates a "customized" air supply plan for each independent area. This plan is encapsulated as an "air supply parameter control instruction," which mainly includes: Target air supply volume: The volumetric flow rate (m³ / h) of fresh air needed to be supplied to the area to meet the predicted ventilation and heat / humidity loads. Target air supply temperature: The temperature value (°C) of the fresh air needed to be supplied to offset the predicted heat load in the area. This instruction is sent via the communication network to the local control module of the make-up air unit 4 serving that area. The local control module then acts accordingly: adjusting the fan speed to the corresponding air volume and simultaneously controlling the heating / cooling device to ensure the outflowing fresh air temperature reaches the target value. The energy source for the heating / cooling device is the energy stored in the phase change material energy storage module 3 of this unit.

[0085] It should be noted that the user data involved in the embodiments of this application are all authorized, and the acquisition, processing, and transmission comply with legal and regulatory requirements, and necessary confidentiality measures have been taken.

[0086] In a preferred embodiment, the environmental parameters include the indoor static pressure of each independent zone; the make-up air system further includes:

[0087] An exhaust volume monitoring module is used to obtain the real-time exhaust volume of the exhaust system 5;

[0088] The main controller 1 is further configured to:

[0089] Based on the indoor static pressure and the real-time exhaust volume, calculate the compensation air volume required to maintain the target pressure of each of the independent zones;

[0090] When generating the air supply parameter control command, the compensation air volume is integrated with the air supply demand based on the environmental load prediction to determine the target air supply volume, so that the make-up air volume, exhaust air volume and pressure status of each independent area are dynamically matched to suppress the disorderly infiltration of air or the diffusion of pollutants caused by negative pressure.

[0091] Specifically, indoor static pressure refers to the difference between the absolute air pressure at a point inside a building and the outdoor atmospheric pressure at the same elevation. In ventilation engineering, relative static pressure is usually the focus. During implementation, micro-differential pressure sensors need to be installed in each independent area. One end of the sensor senses the indoor pressure through a pressure tap, and the other end is connected to a common reference point (such as outdoors, or a pressure-stable area within the building), thereby continuously measuring the static pressure value of that area relative to the reference point. This data is uploaded to the main controller 1 via a sensor network. Exhaust volume monitoring module: This device is used to acquire the total exhaust volume of the building exhaust system 5 in real time. There are several implementation methods: a wind speed sensor (such as a Pitot tube or thermal anemometer) can be installed on the main duct of the exhaust system 5 to calculate the volumetric flow rate by measuring the wind speed and duct cross-sectional area; a power sensor can also be installed on the exhaust fan power supply line to indirectly estimate the air volume by monitoring the fan power and combining it with the fan performance curve; a more direct method is to communicate with the intelligent controller of the exhaust system 5 to directly read its set or feedback operating air volume data. This module sends the real-time exhaust volume data to the main controller 1. Calculate the compensation air volume: The main controller 1 dynamically calculates the required compensation air volume for each area based on the following logic:

[0092] Target Pressure: A target static pressure value is set for each individual area, relative to the outdoor atmospheric pressure at the same elevation. For commercial and restaurant buildings, it is generally desirable to maintain a slightly negative pressure (e.g., -5 Pa to -10 Pa) relative to the outside to prevent cooking fumes from escaping; while the dining area should maintain a slightly positive pressure (e.g., +5 Pa to +10 Pa) relative to the outside to prevent kitchen odors from penetrating. Public areas can be maintained at near-zero pressure relative to the outside (i.e., essentially equal to the outdoor pressure).

[0093] Calculation Process: The main controller 1 continuously reads the measured indoor static pressure value of a certain area and compares it with the target pressure value to obtain the static pressure deviation. Simultaneously, it considers the real-time exhaust air volume, as exhaust air is the main source of disturbance causing indoor pressure changes. The controller uses a pressure control algorithm (such as PID control) with the static pressure deviation and exhaust air volume as the main inputs to calculate the amount of air needed to supplement or reduce the area to eliminate the deviation and offset the impact of exhaust air—this is the compensation air volume. This air volume is specifically used for pressure regulation. The compensation air volume is then fused with the supply air demand based on environmental load prediction: At this point, the main controller 1 has two air volume reference values ​​calculated for the same area: one is the supply air demand predicted based on comfort and air quality environmental load, and the other is the compensation air volume based on pressure balance. The goal of fusion is to generate a final target supply air volume for execution. Fusion Strategy: Simple fusion may involve taking the larger of the two values ​​to ensure that both comfort and pressure requirements are met simultaneously. More intelligent fusion can use weighted summation, with the weights dynamically adjusted according to operating conditions. For example, during peak cooking times in the kitchen and when exhaust volume surges, the weight of the compensation airflow is increased to prioritize maintaining negative pressure and prevent the spread of cooking fumes. Determining the target supply airflow: Through the above-mentioned integrated calculations, a final airflow command value that combines comfort and pressure balance requirements is obtained. Suppressing disorderly air infiltration or pollutant diffusion: Through the above-mentioned dynamic matching control, the system achieves linkage between the supply airflow, exhaust airflow, and pressure status. When the exhaust airflow is large, the system automatically increases the supply airflow to balance the negative pressure, thus preventing outdoor air from being forcefully drawn in through door and window gaps (disorderly infiltration). By precisely controlling the pressure difference between different areas, a directional airflow from the clean area to the contaminated area can be formed, thereby effectively suppressing the diffusion of kitchen fumes and other pollutants into the dining area.

[0094] In a preferred embodiment, the main controller 1 is specifically configured to:

[0095] Receive real-time environmental data, the real-time exhaust volume, and environmental load predicted based on historical data;

[0096] Based on the relationship between the rate of change of the real-time exhaust volume and the exhaust sudden change threshold, the dominant control objective in the current control cycle is determined.

[0097] If the rate of change of the real-time exhaust volume exceeds the exhaust sudden change threshold, the dominant control target is set to pressure balance, and when the main controller 1 generates the air supply parameter control command, the compensation air volume is used as the main determining factor of the target air supply volume.

[0098] If the rate of change of the real-time exhaust volume is lower than the exhaust sudden change threshold, the dominant control objective is set as environmental comfort and energy saving. When the main controller 1 generates the air supply parameter control command, it takes the air supply demand based on the environmental load prediction as the main determining factor of the target air supply volume, and makes fine adjustments in conjunction with the compensation air volume.

[0099] This implementation method establishes a bimodal decision-making logic, enabling the system to intelligently switch between "pressure balance priority" and "comfort and energy saving priority" modes. Its specific implementation relies on the construction and execution of the following key components:

[0100] First, a threshold for sudden changes in exhaust air volume needs to be preset or calculated online in the main controller 1. This threshold is a physically meaningful critical value for the rate of change of air volume (the unit can be m³ / (h·s) or % / s), used to distinguish between normal fluctuations and drastic changes in the exhaust system 5. In practice, this threshold can be obtained by analyzing historical exhaust air data (such as taking the upper limit of the normal fluctuation range), or set according to the step change in exhaust air volume caused by the maximum possible start-stop combination of kitchen equipment. The main controller 1 calculates the rate of change of real-time exhaust air volume in real time, that is, the derivative or difference of the current exhaust air volume relative to the previous moment or the short-term historical average.

[0101] When a new control cycle begins (e.g., every 10-30 seconds), the main controller 1 executes the following decision-making process: it compares the calculated real-time exhaust ventilation change rate with a preset exhaust ventilation sudden change threshold. The decision logic is binary: if the change rate exceeds the threshold, it is determined that the exhaust ventilation system 5 is in a state of drastic change (e.g., multiple stoves igniting simultaneously). At this time, the system sets the primary control objective to pressure balance. Under this objective, when generating air supply parameter control commands, the calculated compensation air volume is used as the main determining factor for determining the target air supply volume. This means that the system will mobilize resources to prioritize and quickly supplement air volume to offset exhaust ventilation sudden changes and prevent excessive negative pressure in the room. The air supply demand based on environmental load prediction is only used as a secondary reference or is ignored at this time. If the change rate is below the threshold, it is determined that the exhaust ventilation system 5 is operating relatively smoothly. At this time, the system sets the primary control objective to environmental comfort and energy saving. Under this objective, when generating commands, the predicted air supply demand is used as the main determining factor for the target air supply volume, aiming to meet the needs of personnel thermal comfort and air quality. At the same time, the system will still make fine adjustments based on the compensated air volume, that is, introduce a small correction value to ensure that the pressure does not deviate too far from the safe range during the comfort control process.

[0102] The effectiveness of this implementation lies in giving the system the ability to prioritize responses to sudden disturbances. It ensures that during critical moments when kitchen operations cause drastic fluctuations in exhaust ventilation, the system can temporarily set aside refined energy-saving goals and prioritize maintaining stable building pressure—a fundamental safety and hygiene requirement—effectively preventing the instantaneous deterioration caused by backflow or disorderly infiltration of cooking fumes. During most periods of stable exhaust ventilation, the system reverts to refined comfort and energy-saving controls, avoiding energy waste caused by prolonged excessive supplemental airflow. This achieves adaptive optimization of the system's control strategy under both extreme and normal operating conditions, balancing multiple objectives such as safety, hygiene, comfort, and energy conservation.

[0103] In a preferred embodiment, the main controller 1 is further configured to:

[0104] The multi-objective fusion weighting coefficient is dynamically calculated based on the rate of change of the real-time exhaust volume, the remaining energy status of the energy storage module 3, the current electricity price period, and the deviation of the real-time environmental parameters of each independent area from their target values.

[0105] The multi-objective fusion weighting coefficient is used to dynamically adjust the ratio of the compensation air volume and the air supply demand based on environmental load prediction in the target air volume when generating the air supply parameter control command.

[0106] The master controller 1 determines the synthesis ratio according to the following logic:

[0107] When the rate of change of the real-time exhaust volume is higher, the remaining energy of the energy storage module 3 is lower, and the current period is the peak electricity price period, the weight of the compensation air volume in the target air supply volume is increased to prioritize ensuring rapid balance of indoor pressure and prevent disorderly infiltration from causing a surge in air conditioning load.

[0108] When the rate of change of the real-time exhaust volume is stable, the remaining energy of the energy storage module 3 is sufficient, and the environmental parameters of each area are close to the target value, the weight of the air supply demand based on the environmental load prediction in the target air supply volume is increased to optimize comfort and reduce fan energy consumption.

[0109] Specifically, to achieve the aforementioned dynamic fusion control, a dynamic weight calculation logic runs within the main controller 1. This logic comprehensively considers four aspects of real-time information: first, the degree of real-time change in the air volume of the exhaust system 5; second, the remaining releaseable energy of the energy storage modules 3 in each make-up air unit 4; third, the current electricity billing period; and fourth, the difference between the actual environmental parameters (such as temperature and carbon dioxide concentration) of each independent area within the building and their set target values.

[0110] The main controller 1 first standardizes these information with different dimensions, transforming them into dimensionless indicators between 0 and 1 that can be compared uniformly. Each indicator reflects the urgency of prioritizing the control objective of pressure balance under the current state.

[0111] For example, regarding changes in exhaust ventilation, the system compares the measured rate of change with a preset upper limit. If the rate of change reaches or exceeds this upper limit, the corresponding urgency index is set to its maximum value of 1.0; if there is no change, it is set to 0; in intermediate states, the value is proportionally applied. Regarding the remaining energy of energy storage module 3, when energy is extremely abundant, the corresponding factor is 0, indicating that there is no need to prioritize pressure maintenance due to energy shortage; when energy is about to be depleted, the factor is 1.0, indicating an urgent need to maintain pressure to prevent additional load; in intermediate states, the value is also proportionally applied. Regarding electricity price factors, the system assigns cost pressure factors of 1.0, 0.5, and 0 respectively based on peak, flat, and valley periods. Regarding environmental deviations, if the temperature and carbon dioxide concentration in all areas are within the comfort range, the factor is set to 0; if any area deviates beyond the standard, the factor will be negative or used to reduce the overall weight of pressure maintenance, to indicate that the system needs to consider comfort.

[0112] Based on the four standardized indicators mentioned above, the controller determines the dynamic weight of the pressure compensation target in the final airflow command through preset rules or algorithms. One approach is to use preset rule logic for judgment. For example:

[0113] When exhaust gas changes drastically and it is currently during peak electricity pricing periods, this indicates that the system is facing significant disturbances and high energy costs. In this case, pressure balance should be the overriding objective, and the weight of pressure compensation should be set to a high value, such as 0.8.

[0114] When the remaining energy of the energy storage module 3 is low and the exhaust changes are also significant, it indicates that a disturbance has occurred under the condition of energy shortage. It is still necessary to prioritize ensuring pressure stability. At this time, the weight can be set to a medium-high value, such as 0.7.

[0115] When the exhaust changes are gradual, the environmental comfort in each area is good, and the energy storage module 3 has sufficient energy, it indicates that the system is in a stable and ideal state. At this time, more consideration can be given to optimizing comfort and saving fan energy consumption. Therefore, the weight of pressure compensation can be reduced, for example, set to 0.4.

[0116] Under other normal operating conditions, an intermediate weight value, such as 0.6, is used to achieve balanced control of multiple objectives.

[0117] Another approach is to use a continuously calculated weighted summation formula. This formula multiplies real-time values ​​of indicators such as exhaust gas changes, energy status, and electricity price factors by their respective preset sensitivity coefficients, sums them, and then adjusts the result with a bias term. Finally, it continuously calculates a dynamic weight value between a set minimum (e.g., 0.3) and a maximum (e.g., 0.9). This setup ensures that, under any extreme conditions, the system will not completely ignore either the pressure balance or comfort / energy saving control objectives.

[0118] After determining the weight of pressure compensation (denoted as W), the weights of comfort and energy-saving targets are naturally 1-W. The final target air volume issued to each make-up air unit 4 is obtained by weighted summation of the pressure compensation air volume and the air supply demand based on environmental load forecasts using these two weights.

[0119] The effectiveness of this control method lies in enabling the air supply system's output to move beyond simple mode switching. Instead, it allows for smooth and intelligent adjustments based on the intensity of exhaust disturbances, the amount of its own energy reserves, external electricity prices, and the current level of comfort. For example, at the beginning of the dinner rush, exhaust volume surges and electricity costs are high, but energy reserves are still sufficient. The system will assign a higher weight to pressure balance (e.g., 0.7) to quickly stabilize pressure. During the middle of the rush, exhaust volume is relatively stable, but the restaurant is crowded and temperatures are rising. The system will appropriately reduce the pressure weight (e.g., 0.5) to balance comfort and energy conservation. Near the end of the business day, exhaust volume decreases, and the energy reserves in energy storage module 3 are low. The system may again moderately increase the pressure balance weight to reserve the last of its energy. In this way, the system can find the most economical and suitable multi-objective balance point in all operating phases, and its overall energy efficiency and environmental adaptability are significantly better than traditional fixed-mode or simple-switching control strategies.

[0120] In a preferred embodiment, the building interior includes multiple functionally sequentially related independent areas, and the air supply system further includes:

[0121] A regional differential pressure sensor network is installed at the connecting parts between critical adjacent areas where there is a risk of pollutant diffusion, for real-time monitoring of the pressure difference between the critical adjacent areas;

[0122] The main controller 1 is further configured to:

[0123] Based on the cleanliness requirements and pollution source distribution within the building, a directional positive pressure gradient target from the pollution risk zone to the clean zone is preset for multiple independent areas;

[0124] Based on the real-time monitoring data of the regional differential pressure sensor network and the real-time exhaust volume of the exhaust system 5, the gradient compensation air volume required for each independent region to maintain the directional positive pressure gradient target is dynamically calculated.

[0125] The gradient compensation air volume required for each independent area is integrated into the corresponding air supply parameter control command to control the air supply volume of the make-up air unit 4 in each independent area, so as to guide the air from the clean area to the pollution risk area.

[0126] Specifically, to accurately guide airflow between different functional areas within a building, a spatial relationship model of these areas must first be established within the system. Taking a typical restaurant as an example, its kitchen (open-flame cooking area), preparation area (food delivery aisle), and dining area are functionally interconnected. The central controller, based on this actual functional layout of the building, establishes a topology model in its internal configuration software, clearly defining each independent area and their physical connections, and specifying the attributes of each area. For example, the kitchen is marked as a contamination risk area, the dining area as a clean area, and the preparation area serves as a buffer zone between the two.

[0127] Once the model is established, sensors need to be deployed at key points connecting different areas to monitor pressure changes. For example, a high-precision differential pressure transmitter should be installed at the doorway from the kitchen to the preparation area, and at the entrance / exit from the preparation area to the main hall. Each sensor's two pressure taps are led to the interiors of the two adjacent areas, enabling continuous, real-time measurement of the pressure difference between them, such as the real-time pressure difference between the kitchen and the preparation area.

[0128] Regarding control objectives, the main controller 1 presets a set of directional pressure gradient targets. These target values ​​are typically set according to hygiene and epidemic prevention regulations, aiming to create a directional airflow from the clean area to the contamination risk area. A typical pressure gradient setting is as follows: the clean area (hall) maintains a slightly positive pressure relative to the outside; the buffer zone (preparation room) maintains a slightly negative pressure or close to zero pressure relative to the clean area; and the contamination risk area (kitchen) maintains a more significant negative pressure relative to the buffer zone. In this way, the entire space forms a distribution pattern of pressure decreasing in a stepwise manner. In the system, these objectives are specified as a series of target pressure difference values ​​between adjacent areas.

[0129] During dynamic control, the system performs a pressure gradient adjustment calculation at a fixed time period (e.g., every 10 seconds). Within each period, the main controller 1 collects two types of data: the real-time pressure difference between adjacent areas measured by various differential pressure sensors, and the total real-time exhaust volume obtained from the exhaust system 5. The core objective of the control calculation is to calculate a suitable gradient compensation airflow for each independent area, ensuring that under the influence of these airflows, the measured pressure difference of all adjacent areas approximates its preset target pressure difference, and that the total make-up airflow and total exhaust airflow of the entire building remain essentially balanced.

[0130] The specific calculation method to achieve this goal can employ the principle of iterative feedback regulation. First, the system calculates the difference between the measured pressure difference and the target pressure difference at each monitoring interface, i.e., the pressure difference error. Then, based on the fundamental relationship in fluid mechanics that pressure difference is proportional to the square of airflow, the controller will initially estimate the direction and magnitude of airflow adjustment required to eliminate this error in each relevant area. For example, if the negative pressure in the kitchen is insufficient relative to the preparation area, the air supply volume in the kitchen needs to be increased to bring it closer to the exhaust volume and thus increase the negative pressure. This step can use a proportional control algorithm, multiplying the pressure difference error by a preset proportional coefficient to obtain the initial airflow correction.

[0131] However, since the pressure in each zone is interconnected, adjusting the airflow in one zone will simultaneously affect the pressure difference between it and all adjacent zones. Therefore, it is necessary to combine the error equations of all the monitoring interfaces mentioned above, along with the constraint equations that require the total airflow to be balanced, into a simultaneous system of equations. The system solves this system of equations in real time by running a preset numerical algorithm (such as the Jacobi iteration method) within the controller, thereby calculating in one go the gradient compensation airflow that should be executed in all zones to achieve the optimal global pressure distribution.

[0132] The calculated gradient compensation airflow is the basic guarantee airflow used to maintain the predetermined pressure gradient. In actual operation, it is integrated with the supply airflow previously calculated based on environmental load prediction to meet comfort and energy-saving requirements. The integration method can be to take the larger value of the two, or to use it as an input for weighted synthesis under the aforementioned dynamic weighting framework. The final target supply airflow command is then sent to the make-up air units 4 in each corresponding area for execution. Through this cyclical closed-loop control, the system can dynamically and accurately adjust the supply air distribution, physically guiding air from the high-pressure clean area to the low-pressure pollution risk area, thereby constructing an invisible protective barrier formed by airflow between the kitchen and dining area.

[0133] The implementation of this solution elevates the traditional, rudimentary management of overall building pressure through ventilation systems to a new level of refined control over the distribution of pressure within internal spaces. The direct result is the fundamental prevention of the uncontrolled spread of kitchen fumes, steam, and odors to the dining area, significantly improving the hygiene of the indoor environment and the dining experience for customers. Simultaneously, by effectively isolating the hot and humid air from the kitchen, the cooling load on the lobby's air conditioning system is reduced, achieving energy conservation and emission reduction. Furthermore, this control mechanism provides a controllable and reliable baseline state for the system to respond quickly and stably to sudden ventilation surges.

[0134] In a preferred embodiment, the main controller 1 is further configured to:

[0135] Real-time monitoring of the rate of change in exhaust volume of the exhaust system 5;

[0136] If the rate of change of the exhaust volume is detected to exceed the sudden change response threshold within a unit time, it is determined to be a sudden exhaust condition.

[0137] Under the aforementioned sudden exhaust condition, the main controller 1 activates the gradient enhancement mode, which is as follows:

[0138] Within the preset emergency response time, the make-up air unit 4 located in the pollution risk area and its adjacent downstream area is preferentially adjusted to increase its target air supply volume by a rate not less than the preset increase ratio, so as to consolidate and increase the actual pressure gradient maintained according to the directional positive pressure gradient target.

[0139] Specifically, to achieve rapid response to sudden ventilation conditions, the system continuously monitors the operating status of the ventilation system 5. The main controller 1 calculates the instantaneous rate of change of the exhaust volume in real time at a high frequency (e.g., once per second) to assess the severity of exhaust fluctuations. Simultaneously, the system presets a high threshold for sudden change response. This threshold is typically determined based on the exhaust rise rate corresponding to extreme events recorded in historical operating data, such as the simultaneous activation of all stoves in the kitchen. Its value is significantly higher than the threshold used for switching between normal modes.

[0140] In terms of decision-making logic, when the system detects that the instantaneous rate of change of exhaust volume exceeds the aforementioned sudden change response threshold for two consecutive sampling periods, it determines that a sudden exhaust condition has occurred. At this time, the system will record the stable pressure gradient state between each region before the sudden change occurs, as a benchmark for subsequent control.

[0141] Once a sudden ventilation emergency is confirmed, the main controller 1 will immediately interrupt the ongoing regular control cycle, activate the preset gradient enhancement mode, and simultaneously start a timer corresponding to the preset emergency response time. In this mode, the system's control objective will be temporarily adjusted to: prioritizing the consolidation and increase of the pressure gradient at key locations to prevent the spread of pollutants, without considering short-term energy consumption.

[0142] The specific control strategy is implemented as follows:

[0143] First, regarding target adjustment, the system will temporarily adjust the target pressure difference between the contaminated risk area (such as the kitchen) and its adjacent downstream area (such as the food preparation room) to several times the original set value during the emergency response time, such as 1.5 times, thereby forming a larger negative pressure gradient than usual.

[0144] Secondly, regarding instruction generation, to achieve this temporary enhancement target, the system employs a control method combining feedforward and feedback. The feedforward part directly calculates the basic incremental air volume required by the kitchen and food preparation area makeup air unit 4 based on the step increase in exhaust air volume and empirical coefficients. The feedback part calculates the corrected air volume based on the deviation between the current measured pressure difference and the temporary enhancement target, using a higher control gain. The sum of the two parts yields the required total incremental air volume.

[0145] Subsequently, the system will convert the calculated total incremental air volume into direct air volume setting instructions for the kitchen and food preparation area makeup air unit 4, according to a rate no less than the preset increase ratio (for example, requiring the target air supply volume to increase to at least 160% of the original plan). These instructions have the highest priority in the system and will be issued and executed immediately.

[0146] During the execution and monitoring phase, upon receiving the instruction, the wind turbine of the make-up air unit 4 in the relevant area will accelerate to the target speed within seconds. Throughout the emergency response period, the system will continuously monitor the pressure difference changes at key locations to ensure that they converge towards the temporary reinforcement target.

[0147] Finally, regarding mode exit and recovery, the gradient enhancement mode will exit when the preset emergency response time ends, or when the system detects that the rate of change in exhaust volume has fallen below the safe threshold and the pressure difference at key locations has stabilized. The system will then gradually restore the temporarily adjusted target pressure difference to the original set value, and the control strategy will smoothly switch back to the regular gradient control mode, re-integrating comfort and energy-saving optimization goals to resume normal operation.

[0148] In a preferred embodiment, the main controller 1 is also communicatively connected to the building's indoor air conditioning system; the main controller 1 is further configured to:

[0149] The compressor load rate of the air conditioning system is acquired in real time; at the same time, the deviation between the actual temperature of each independent area after adjustment by the make-up air system and the set temperature of the air conditioner is monitored.

[0150] The cooperative operation mode is triggered when both of the following conditions are met:

[0151] The compressor load rate of the air conditioning system continuously exceeds the high load threshold for a first duration.

[0152] There exists at least one independent area where the actual temperature deviates from the air conditioner's set temperature beyond the allowable threshold, and the direction of this deviation is contrary to the operating mode of the air conditioning system.

[0153] In the cooperative operation mode, the main controller 1 issues a cooperative adjustment command to the air supply unit 4 in the affected area. This command adjusts the air supply temperature setpoint to be close to the air conditioning setpoint without changing the target air supply volume.

[0154] Specifically, to achieve coordinated operation with the air conditioning system, a communication connection must first be established between the two. The main controller 1 needs to expand its communication interface to establish a standard communication connection with the main controller of the building automation system or air conditioning unit, such as using communication protocols commonly used in building automation, like BACnet or Modbus TCP / IP. Through this connection, the main controller 1 can obtain the compressor load rate of the air conditioning system in real time. This load rate is usually expressed as a percentage and can be read directly from the air conditioning controller or calculated by monitoring the ratio of the compressor's operating current to its rated current.

[0155] At the same time, the main controller 1 continuously monitors the actual temperature of each independent zone after adjustment by the make-up air system from its own sensor network, and obtains the corresponding zone's air conditioning set temperature from the air conditioning system. These two pieces of data are the basis for determining whether to start coordinated operation.

[0156] Regarding the triggering condition judgment for the collaborative operation mode, the main controller 1 will continuously run a judgment logic that requires the following two conditions to be met simultaneously before the collaborative mode will be triggered:

[0157] The first condition is the determination of high air conditioning load. This means the compressor load rate continuously exceeds a preset high load threshold for a certain duration (i.e., the first duration). The purpose of setting this duration is to confirm that the air conditioning system is indeed operating under a continuous high load, rather than experiencing momentary fluctuations. The first duration is a preset time length used to confirm that the air conditioning system is in a continuous, rather than momentary, high load state. Its specific value can be set according to the building's thermal inertia, the air conditioning system's response speed, and the required control precision; typically, it ranges from 5 to 15 minutes. In a specific embodiment, for example, the high load threshold is set to 85%, and the first duration is 10 minutes. This means that only when the compressor load rate is continuously above 85% for 10 minutes is the condition considered met, indicating that the air conditioning system is facing insufficient cooling capacity or excessive energy consumption.

[0158] The second condition is the determination of environmental regulation conflict. This means there exists at least one independent area where the deviation between the actual temperature and the air conditioner's set temperature exceeds an allowable threshold, and the direction of this deviation contradicts the current operating mode of the air conditioning system. For example, suppose the allowable deviation threshold is set at 1.5℃. In summer cooling mode, the air conditioning system is working to cool the room, but if the actual temperature in a certain area is more than 1.5℃ higher than the set temperature (i.e., the room is too hot), then this deviation direction contradicts the air conditioner's cooling target, indicating that the air conditioning effect in that area is poor. In winter heating mode, the criterion for determining a deviation conflict is whether the actual temperature is more than 1.5℃ lower than the set temperature (i.e., the room is too cold).

[0159] Only when both of the above conditions are met will the system determine that there is a working condition where the air conditioning system needs assistance and the makeup air system may be able to provide assistance, thus officially triggering the collaborative operation mode.

[0160] In the generation and execution of coordinated adjustment commands, once the coordinated operation mode is entered, the main controller 1 will first identify the affected areas, namely the areas where the actual temperature deviates from the set temperature by more than the standard and in opposite directions.

[0161] Subsequently, a coordinated adjustment command will be issued to the make-up air unit 4 in these affected areas. The core requirement of this command is to adjust the set value of its air supply temperature so that it approaches the direction of the air conditioning set temperature, without changing the originally determined target air supply volume.

[0162] In practice, assuming the current supply air temperature setpoint of the make-up air unit 4 in a certain affected area is determined by comfort control logic, while the air conditioning setpoint is a different value, in summer cooling mode, if the area becomes overheated, the coordination command will appropriately lower the supply air temperature setpoint of the make-up air unit 4. For example, it can be set to prioritize the smaller of the current supply air temperature setpoint and a value 2°C lower than the air conditioning setpoint, with the aim of supplying cooler fresh air into the room, directly helping to lower the temperature in that area and thus reducing the burden on the air conditioning system. In winter heating mode, the opposite adjustment will be taken. The key here is that this temperature adjustment always takes into account the premise of not changing the target air volume of the make-up air unit 4, thus ensuring that the original pressure control and ventilation needs are not disturbed, only the processing temperature of the supplied fresh air is changed.

[0163] In a preferred embodiment, the main controller 1 is further configured to:

[0164] In the cooperative operation mode, based on the expected energy consumption caused by adjusting the air supply temperature setpoint, as well as the current energy cost and the available energy status of the energy storage module 3, a decision is made on whether to execute, partially execute, or modify the cooperative adjustment command.

[0165] Specifically, in the collaborative operation mode, the system does not mechanically execute all collaborative adjustment instructions, but instead conducts an intelligent cost-benefit assessment to determine whether and how to execute them.

[0166] After the collaborative mode is triggered and the initial supply air temperature adjustment value is calculated, the main controller 1 will not immediately issue a command. Instead, it will first assess the expected increase in energy consumption caused by this adjustment. The system has a pre-set energy consumption calculation model for the supplementary air unit 4. This model calculates the additional cooling or heating required to process the fresh air to the new set temperature based on the difference between the adjusted supply air temperature setpoint, the current temperature of the energy storage module 3, and the temperature of the outdoor fresh air. Then, based on the current energy form used to process the fresh air—whether it's directly releasing the energy stored in the phase change material or requiring the activation of auxiliary electric heating or cooling devices—this additional cooling or heating requirement is converted into an expected increase in energy consumption, quantified in kilowatt-hours. For example, if an additional electric heater is required, the expected increase in energy consumption equals the required heat divided by the electric heating efficiency; if only the cooling stored in the phase change cold storage module is consumed, the expected increase in energy consumption can be converted into the consumed cold storage capacity.

[0167] Simultaneously, the system calculates a dynamic allowable threshold. This threshold represents the maximum energy cost or resource consumption the system is willing to incur to assist the air conditioner under current conditions. The calculation of this threshold considers two factors: first, the current energy cost, i.e., the electricity price period; and second, the current available energy state of the energy storage module 3. Specifically, the system sets different benchmark energy cost coefficients based on peak, valley, and flat electricity price periods. For example, the coefficient is most stringent during peak electricity periods, resulting in a lower allowable threshold; while the coefficient is most lenient during valley electricity periods, resulting in a higher allowable threshold. Furthermore, the system determines an energy state factor based on the percentage of remaining available energy in the energy storage module 3. When available energy is sufficient, this factor is larger, and the allowable threshold is correspondingly higher; when available energy is critically low, this factor decreases significantly, and the allowable threshold is correspondingly tightened to ensure the system can operate autonomously during subsequent critical periods. Finally, multiplying the electricity price factor and the energy state factor, and then multiplying by a preset benchmark threshold constant, yields a dynamically changing allowable threshold.

[0168] After completing the above two calculations, the main controller 1 will compare the expected increase in energy consumption with the allowable threshold and make a final decision based on the comparison result:

[0169] If the expected increase in energy consumption is less than or equal to the allowable threshold, it indicates that the current energy cost is acceptable and energy storage resources are sufficient. In this case, the system will make an execution decision, that is, issue the coordinated adjustment command in full according to the initially calculated adjustment plan.

[0170] If the expected increase in energy consumption exceeds the allowable threshold, it indicates that the current cost is too high or energy storage resources are already strained. In this case, the system will make a decision to restrict or cancel the adjustment. Specifically, there are two possible approaches: one is partial execution, which involves proportionally reducing the originally set adjustment range for the supply air temperature and recalculating the expected increase in energy consumption until it meets the allowable threshold. For example, if the original plan was to lower the supply air temperature by 3 degrees Celsius, after evaluation, it might only be lowered by 1 degree Celsius. The other approach, in cases of extreme resource scarcity or extremely high costs, is to directly cancel the coordinated adjustment, maintaining the original supply air temperature setting. This means that the supplementary air unit 4 continues to operate according to its original comfort control logic without providing additional assistance.

[0171] Ultimately, the system generates and issues the final adjustment instructions based on the above decision results, or maintains the original state if the execution is cancelled.

[0172] This implementation effectively prevents situations where mechanical execution of coordinated commands could lead to undesirable consequences. For example, it avoids excessive consumption of energy storage module 3 to assist the air conditioner during peak electricity price periods, which would result in insufficient energy for the system during subsequent periods when supplemental airflow is needed more, requiring the purchase of electricity at higher prices to maintain operation. It upgrades the entire system's operating strategy from a simple technical response to a comprehensive optimization integrating technology and economics. While pursuing indoor environmental comfort, it firmly adheres to the bottom line of operational economy and system sustainability, achieving a higher level of intelligent control and energy-saving effects.

[0173] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A distributed collaborative makeup air system for a commercial food service building, characterized in that, include: Multiple make-up air units (4) are distributed in the interior of the building, each of the make-up air units (4) includes an energy storage module (3) for processing fresh air. Energy supply unit (2) is used to provide energy to the energy storage module (3); The main controller (1) is connected to each of the aforementioned air supply units (4) and the energy supply unit (2); the main controller (1) is configured to: The energy supply unit (2) is controlled to store energy in the energy storage module (3) during the first time period; In the second period, which is different from the first period, the operation of each of the air supply units (4) is controlled to process fresh air and send it into the room using the energy stored in the energy storage module (3) in order to maintain the balance of the indoor environment in coordination with the building's exhaust system (5). The energy storage module (3) is made of phase change material; each of the air supply units (4) also includes a local control module that is communicatively connected to the main controller (1); The system also includes a sensor network connected to the main controller (1) for collecting environmental parameters and personnel data from multiple independent areas inside the building; The main controller (1) is further configured as follows: Based on the environmental parameters and personnel data, predict the environmental load of multiple independent areas; Based on the environmental load of each independent area, a corresponding air supply parameter control instruction is generated for each independent area, and the air supply parameter control instruction includes a target air supply volume or a target air supply temperature. The local control module is configured to: receive the air supply parameter control command issued by the main controller (1) corresponding to its independent area, and control the fan speed and heating / cooling device of the make-up air unit (4) to achieve the target air supply volume or target air supply temperature. The environmental parameters include the indoor static pressure of each independent zone; the make-up air system also includes: The exhaust volume monitoring module is used to obtain the real-time exhaust volume of the exhaust system (5); The main controller (1) is further configured to: Based on the indoor static pressure and the real-time exhaust volume, calculate the compensation air volume required to maintain the target pressure of each of the independent zones; When generating the air supply parameter control command, the compensation air volume is integrated with the air supply demand based on the environmental load prediction to determine the target air supply volume, so that the make-up air volume, exhaust air volume and pressure status of each independent area are dynamically matched to suppress the disorderly infiltration of air or the diffusion of pollutants caused by negative pressure.

2. The distributed collaborative transair system for commercial food service buildings of claim 1, wherein, The first time period includes off-peak electricity hours and / or periods with abundant solar power; the second time period includes peak electricity hours and / or the building's operating hours. During the first time period, the main controller (1) controls the energy supply unit (2) to prioritize the use of solar energy and switch to off-peak electricity from the power grid when solar energy is insufficient, so as to store energy for the energy storage module (3). During the second time period, the main controller (1) controls the operation of each of the air supply units (4), uses the energy stored in the energy storage module (3) to process fresh air and send it into the room, and at the same time stops or reduces the energy obtained from the energy supply unit (2).

3. The distributed collaborative transair system for commercial food service buildings of claim 1, wherein, The main controller (1) is specifically configured for: Receive real-time environmental data, the real-time exhaust volume, and environmental load predicted based on historical data; Based on the relationship between the rate of change of the real-time exhaust volume and the exhaust sudden change threshold, the dominant control objective in the current control cycle is determined. If the rate of change of the real-time exhaust volume exceeds the exhaust sudden change threshold, the dominant control target is set to pressure balance, and when the main controller (1) generates the air supply parameter control command, the compensation air volume is used as the main determining factor of the target air supply volume. If the rate of change of the real-time exhaust volume is lower than the exhaust sudden change threshold, the dominant control objective is set as environmental comfort and energy saving. When the main controller (1) generates the air supply parameter control instruction, it takes the air supply demand based on the environmental load prediction as the main determining factor of the target air supply volume, and makes fine adjustments in conjunction with the compensation air volume.

4. The distributed collaborative transair system for commercial food service buildings of claim 3, wherein, The main controller (1) is further configured to: Based on the rate of change of the real-time exhaust volume, the remaining energy status of the energy storage module (3), the current electricity price period, and the deviation of the real-time environmental parameters of each independent area from their target values, the multi-objective fusion weight coefficient is dynamically calculated. The multi-objective fusion weighting coefficient is used to dynamically adjust the ratio of the compensation air volume and the air supply demand based on environmental load prediction in the target air volume when generating the air supply parameter control command. The master controller (1) determines the synthesis ratio according to the following logic: When the rate of change of the real-time exhaust volume is higher, the remaining energy of the energy storage module (3) is lower, and the current period is the peak electricity price period, the weight of the compensation air volume in the target air supply volume is increased to prioritize ensuring rapid balance of indoor pressure and prevent disorderly infiltration from causing a surge in air conditioning load. When the rate of change of the real-time exhaust volume is stable, the remaining energy of the energy storage module (3) is sufficient, and the environmental parameters of each area are close to the target value, the weight of the air supply demand based on the environmental load prediction in the target air supply volume is increased to optimize comfort and reduce fan energy consumption.

5. The distributed collaborative transair system for commercial food service buildings of claim 1, wherein, The building interior comprises multiple functionally sequential independent areas, and the air supply system further includes: A regional differential pressure sensor network is installed at the connecting parts between critical adjacent areas where there is a risk of pollutant diffusion, for real-time monitoring of the pressure difference between the critical adjacent areas; The main controller (1) is further configured to: Based on the cleanliness requirements and pollution source distribution within the building, a directional positive pressure gradient target from the pollution risk zone to the clean zone is preset for multiple independent areas; Based on the real-time monitoring data of the regional differential pressure sensor network and the real-time exhaust volume of the exhaust system (5), the gradient compensation air volume required for each independent region to maintain the directional positive pressure gradient target is dynamically calculated. The gradient compensation air volume required for each independent area is integrated into the corresponding air supply parameter control command to control the air supply volume of the make-up air unit (4) in each independent area, so as to guide the air from the clean area to the pollution risk area.

6. The distributed collaborative transair system for commercial food service buildings of claim 5, wherein, The main controller (1) is also configured to: Real-time monitoring of the rate of change of exhaust volume of the exhaust system (5); If the rate of change of the exhaust volume is detected to exceed the sudden change response threshold within a unit time, it is determined to be a sudden exhaust condition. Under the aforementioned sudden exhaust condition, the main controller (1) activates the gradient enhancement mode, which is as follows: Within the preset emergency response time, the make-up air units (4) located in the pollution risk area and its adjacent downstream area are preferentially adjusted to increase their target air supply volume by a ratio not less than the preset increase, so as to consolidate and increase the actual pressure gradient maintained according to the directional positive pressure gradient target.

7. The distributed collaborative transair system for commercial food service buildings of claim 1, wherein, The main controller (1) is also communicatively connected to the building's indoor air conditioning system; the main controller (1) is further configured to: The compressor load rate of the air conditioning system is acquired in real time; at the same time, the deviation between the actual temperature of each independent area after adjustment by the make-up air system and the set temperature of the air conditioner is monitored. The cooperative operation mode is triggered when both of the following conditions are met: The compressor load rate of the air conditioning system continuously exceeds the high load threshold for a first duration. There exists at least one independent area where the actual temperature deviates from the air conditioner's set temperature beyond the allowable threshold, and the direction of this deviation is contrary to the operating mode of the air conditioning system. In the cooperative operation mode, the main controller (1) issues a cooperative adjustment command to the air supply unit (4) in the affected area. The command adjusts the air supply temperature setpoint to be close to the air conditioning setpoint without changing the target air supply volume.

8. The distributed collaborative air supply system for commercial catering buildings according to claim 7, characterized in that, The main controller (1) is also configured to: In the cooperative operation mode, based on the expected energy consumption caused by adjusting the air supply temperature setpoint, as well as the current energy cost and the available energy status of the energy storage module (3), a decision is made on whether to execute, partially execute, or modify the cooperative adjustment command.

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