Air conditioning system

Abstract

The application provides an air conditioning system, comprising indoor and outdoor units; further comprising a processing device provided with a generating part, an estimating part and an intervention part; wherein the generating part is configured to obtain at least one operating parameter of the air conditioning system, the estimating part is configured to construct a prediction model, estimate the relative relationship between the current demand load of the indoor unit and the output capacity of the outdoor unit according to the operating state parameter and the environmental parameter of the indoor unit, and generate the efficiency grade of each indoor unit based on the relative relationship, and the intervention part is configured to generate a corresponding intervention control strategy to intervene in the control of at least one operating parameter of the air conditioning system when the efficiency grade of one indoor unit is worse than the reference efficiency grade, according to the degree of deviation of the efficiency grade of the indoor unit from the reference intervention grade; the application enables the system to adaptively intervene in at least one operating parameter, so as to keep the performance within the expected range, thereby optimizing the performance while reducing the energy consumption.

Description

Technical Field

[0001] This invention relates to the field of air conditioning technology, and more particularly to an air conditioning system. Background Technology

[0002] Air conditioning systems consume energy to cool the air inside a building. The energy consumption of an air conditioning system depends on several factors, including the size of the building, the efficiency of the various components of the system, the set temperature, the climate in which the building is located, and user preferences. Generally, central air conditioning systems consume more energy than other types of air conditioning systems (such as window air conditioners or portable air conditioners) because they are designed to cool larger spaces and typically have more powerful compressors and fans to circulate cooled air throughout the building.

[0003] Existing technologies control the energy consumption of air conditioning systems, especially central air conditioning systems, through various methods. For example, when no one is in the building, the set temperature is temporarily set to a range with a large deviation, or a controller is used to automatically adjust the temperature according to the building's conditions. For instance, Chinese patent application (CN115437302A) discloses an AI intelligent control method for a large central air conditioning system, which includes: setting a data update frequency, controlling preset sensors to collect indoor and outdoor environmental data based on the data update frequency, and transmitting the collected indoor and outdoor environmental data to a control terminal; analyzing the indoor and outdoor environmental data based on the control terminal, and determining a target control strategy for the central air conditioning system based on the analysis results; generating control commands based on the target control strategy, distributing the control commands to corresponding controls for control, and feeding back the control results to a management terminal in real time for recording.

[0004] However, for central air conditioning systems, under the same refrigerant cycle, if some indoor units need to increase their output capacity while others need to decrease it, if the algorithm is not precise enough or cannot adapt to complex environmental changes, the generated control strategy may not be intelligent enough, ultimately leading to chaotic outdoor unit output capacity and higher energy consumption. Summary of the Invention

[0005] To avoid problems such as insufficiently accurate algorithms or inability to adapt to complex environmental changes, resulting in unintelligent control strategies and ultimately chaotic outdoor unit output capabilities and increased energy consumption, this application designs and provides an air conditioning system.

[0006] In one or more embodiments of this application, the air conditioning system includes at least one indoor unit and an outdoor unit fluidly connected to the indoor unit.

[0007] In one or more embodiments of this application, the air conditioning system further includes a processing device; the processing device includes a generation unit, an estimation unit, and an intervention unit; wherein the generation unit is configured to acquire at least one operating parameter of the air conditioning system, the estimation unit is configured to construct a prediction model, estimate the relative relationship between the current demand load of the indoor unit and the output capacity of the outdoor unit based on the operating status parameters of the indoor unit and environmental parameters, and generate an efficiency level for each indoor unit based on the relative relationship, and the intervention unit is configured to generate a corresponding intervention control strategy based on the degree to which the efficiency level of the indoor unit deviates from the benchmark intervention level when the efficiency level of an indoor unit is inferior to the benchmark efficiency level, so as to intervene and control at least one operating parameter of the air conditioning system.

[0008] In one or more embodiments of this application, the benchmark intervention level is a benchmark used to assess whether the indoor unit demand load is too low.

[0009] In one or more embodiments of this application, the operating parameters include at least one or more of the following: condensing temperature, evaporating temperature, throttling device opening degree, compressor frequency, compressor start / stop status, indoor fan start / stop status, indoor fan speed, outdoor fan start / stop status, and outdoor fan speed.

[0010] In one or more embodiments of this application, the indoor unit state parameters include at least one or more of the following: indoor ambient temperature, indoor ambient humidity, indoor location parameters, and indoor personnel parameters.

[0011] In one or more embodiments of this application, the environmental parameters include at least one or more of the following: outdoor ambient temperature, outdoor ambient humidity, weather type parameters, and geographical location parameters.

[0012] In one or more embodiments of this application, the processing apparatus includes a generation unit, an estimation unit, an optimization unit, and a compensation unit; wherein the generation unit is configured to acquire at least one operating parameter of the air conditioning system; the estimation unit is configured to estimate the relative relationship between the current demand load of the indoor unit and the output capacity of the air conditioning system based on the indoor unit status parameters and environmental parameters, and generate an efficiency level for each indoor unit based on the relative relationship; the optimization unit is configured to generate an optimized control strategy based on the indoor unit efficiency level, the optimized control strategy being able to reduce the marginal energy loss caused by a preset temperature compensation; and the compensation unit is configured to execute the optimized control strategy to optimize the control of at least one operating parameter of the air conditioning system.

[0013] In one or more embodiments of this application, the estimation unit is configured to construct a prediction model, using indoor unit state parameters and environmental parameters as inputs, to estimate the relative relationship between the current demand load of the indoor unit and the output capacity of the outdoor unit; and to pass the relative relationship between the current demand load of the indoor unit and the output capacity of the air conditioning system as input to a classifier, wherein the classifier is configured to generate the performance level of the indoor unit based on the relative relationship.

[0014] In one or more embodiments of this application, the optimization unit is further configured to construct an optimization model, taking the indoor unit performance level, indoor unit state parameters and environmental parameters as inputs, and outputting optimized temperature compensation parameters; the compensation unit is configured to optimize and control at least one operating parameter of the air conditioning system based on the optimized temperature compensation parameters.

[0015] In one or more embodiments of this application, the operating parameters include at least one or more of the following: condensing temperature, evaporating temperature, throttling device opening degree, compressor frequency, compressor start / stop status, indoor fan start / stop status, indoor fan speed, outdoor fan start / stop status, and outdoor fan speed.

[0016] In one or more embodiments of this application, the indoor unit state parameters include at least one or more of the following: indoor ambient temperature, indoor ambient humidity, indoor location parameters, and indoor personnel parameters.

[0017] In one or more embodiments of this application, the environmental parameters include at least one or more of the following: outdoor ambient temperature, outdoor ambient humidity, weather parameters, and geographical location parameters.

[0018] This invention generates an efficiency rating for each indoor unit, dynamically evaluates the performance of each indoor unit in real time, and further uses a predictive model to intelligently estimate the relative relationship between the current demand load of the indoor unit and the output capacity of the outdoor unit based on the indoor unit's operating status parameters and environmental parameters. This improves the system's adaptability to changes and enables the system to adaptively intervene in at least one operating parameter to keep performance within the expected range, thereby optimizing performance while reducing energy consumption.

[0019] Other features and advantages of the present invention will become clearer after reading the detailed embodiments of the invention in conjunction with the accompanying drawings. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 A schematic diagram of the structure of an air conditioning system provided for one or more embodiments of this application;

[0022] Figure 2 A schematic diagram of the structure of an air conditioning system provided for one or more embodiments of this application;

[0023] Figure 3 A schematic diagram of the structure of an air conditioning system provided for one or more embodiments of this application;

[0024] Figure 4 A schematic block diagram of the structure of a processing device in an air conditioning system provided for one or more embodiments of this application;

[0025] Figure 5 A schematic block diagram of the structure of a processing device in an air conditioning system provided for one or more embodiments of this application;

[0026] Figure 6 A flowchart of an air conditioning system provided for one or more embodiments of this application;

[0027] Figure 7 A flowchart of an air conditioning system provided for one or more embodiments of this application;

[0028] Figure 8 A flowchart of an air conditioning system provided for one or more embodiments of this application;

[0029] Figure 9 The compressor operating frequency curve of a traditional air conditioning system during operation;

[0030] Figure 10 The compressor operating frequency curve of the air conditioning system disclosed in this application;

[0031] Figure 11 This is the opening curve of an indoor electronic expansion valve during the operation of a traditional air conditioning system.

[0032] Figure 12 The opening curve of the same indoor electronic expansion valve during the operation of the air conditioning system disclosed in this application;

[0033] Figure 13 A schematic block diagram of the structure of a processing device in an air conditioning system provided for one or more embodiments of this application;

[0034] Figure 14 A flowchart of an air conditioning system provided for one or more embodiments of this application;

[0035] Figure 15A flowchart of an air conditioning system provided for one or more embodiments of this application;

[0036] Figure 16 A flowchart of an air conditioning system provided for one or more embodiments of this application;

[0037] In the diagram: 10. Outdoor unit; 101. Compressor; 102. Oil separator; 103. Gas-liquid separator; 104. Switching valve; 105. Outdoor heat exchanger; 106. Indoor heat exchanger; 106-1. Indoor heat exchanger; 106-2. Indoor heat exchanger; 107. Outdoor electronic expansion valve; 108. Indoor electronic expansion valve; 108-1. Indoor electronic expansion valve; 108-2. Indoor electronic expansion valve; 109. Liquid-side piping; 110. Gas-side piping; 111. Oil return capillary tube; 112. Liquid-side shut-off valve; 113. Gas-side shut-off valve; 114. Outdoor fan; 1 15. Liquid reservoir; 20. Indoor unit; 20-1. Indoor unit; 20-2. Indoor unit; 200. Processing device; 201. Generation unit; 202. Estimation unit; 203. Intervention unit; 301. Processor; 302. Non-volatile memory; 303. Volatile memory; 304. Display device; 305. Operating device; 306. Communication interface; 307. Drive device; 308. Bus; 309. Storage medium; 310. Storage medium; 201. Processing device; 211. Generation unit; 212. Estimation unit; 213. Optimization unit; 214. Compensation unit. Detailed Implementation

[0038] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0039] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application.

[0040] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "multiple" means two or more.

[0041] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0042] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" the second feature includes the first feature directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0043] The following disclosure provides many different embodiments or examples for implementing various structures of the invention. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the invention. Furthermore, reference numerals and letters may be repeated in different examples; this repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and arrangements discussed. In addition, examples of various specific processes and materials are provided in this invention, but those skilled in the art will recognize the application of other processes and the use of other materials.

[0044] Figure 1 This is a schematic diagram of the structure of an air conditioning system provided by one or more specific embodiments of the present invention.

[0045] Air conditioning systems are installed in buildings such as apartments, hotels, office buildings, and residences. In one or more embodiments of the present invention, the air conditioning system is a central air conditioning system, which provides a consistent comfort environment for the entire building, rather than just for a single room or area.

[0046] An air conditioning system integrates a refrigeration cycle. The refrigeration cycle uses a compressor, condenser, throttling device, and evaporator. The refrigeration cycle involves a series of processes—compression, condensation, expansion, and evaporation—to cool or heat an indoor space.

[0047] From a principle perspective, low-temperature, low-pressure refrigerant enters compressor 101, where it is compressed into a high-temperature, high-pressure refrigerant gas, which is then discharged. The discharged refrigerant gas flows into the condenser, where the compressed refrigerant is condensed into a liquid phase, and heat is released to the surrounding environment through the condensation process.

[0048] The throttling device expands the high-temperature, high-pressure liquid refrigerant that condenses in the condenser into a low-pressure liquid refrigerant. The evaporator evaporates the expanded refrigerant in the throttling device and returns the low-temperature, low-pressure refrigerant gas to the compressor 101. The evaporator achieves a cooling effect by utilizing the latent heat of refrigerant evaporation to exchange heat with the material being cooled. Throughout the cycle, the air conditioning system regulates the temperature of the indoor space.

[0049] In one or more embodiments of this application, the throttling device includes an indoor electronic expansion valve 108.

[0050] In one or more embodiments of this application, the air conditioning system includes an outdoor unit 10 and an indoor unit 20 connected to each other.

[0051] In one or more embodiments of this application, the air conditioning system includes an outdoor unit 10 and a plurality of indoor units 20 connected to each other. Figure 1 An indoor unit (such as) is shown in the figure. Figure 1 (As shown in Figure 20) Figure 2 Two indoor units 20 are shown in the figure (e.g. Figure 1 As shown in Figures 20-1 and 20-2, however, the number of indoor units 20 is not particularly limited in this application. More indoor units 20 can be arranged in an air conditioning system in the same manner as the indoor units 20 shown in the figures.

[0052] The indoor unit 20 and the outdoor unit 10 are connected by a liquid-side piping 109 and a gas-side piping 110. The liquid-side piping 109 and the gas-side piping 110 are used to supply refrigerant flow, so that the refrigerant can form a refrigerant loop and circulate in it.

[0053] In one or more embodiments of this application, a liquid-side shut-off valve 112 is provided on the liquid-side piping 109.

[0054] In one or more embodiments of this application, a gas-side shut-off valve 113 is provided on the gas-side piping 110.

[0055] The basic structure and function of the outdoor unit 10 are described below. When using the same system architecture, the number of outdoor units 10 in the air conditioning system can be expanded to multiple units, which can then operate in groups. The outdoor unit 10 is correspondingly configured with the outdoor electronic expansion valve 107.

[0056] In one or more embodiments of this application, the outdoor unit 10 refers to the portion of the refrigeration cycle that includes the compressor 101 and the outdoor heat exchanger 105. The outdoor unit 10 can perform heating or cooling operation on the outdoor side to provide energy to the indoor unit 20 for raising or lowering the indoor temperature. The outdoor unit 10 also includes a gas-liquid separator 103, an outdoor fan 114, and a reversing valve.

[0057] In one or more embodiments of this application, an outdoor unit 10 may also be provided with a liquid storage tank 115.

[0058] In one or more embodiments of this application, an oil separator 102 may also be provided in the outdoor unit 10. The function of the oil separator 102 in the air conditioning system is to separate the lubricating oil and the refrigerant. Since the compressor 101 requires lubricating oil to reduce friction and wear and ensure normal operation, and the lubricating oil mixes with the refrigerant when the compressor 101 is working, the oil separator 102 separates the lubricating oil from the refrigerant through the principle of physical separation (such as centrifugal force or gravity). The separated lubricating oil is recovered and recycled, while the refrigerant continues to flow.

[0059] In one or more embodiments of this application, an oil return capillary tube 111 may also be provided in the outdoor unit 10. The function of the oil return capillary tube 111 in the air conditioning system is to recover lubricating oil and guide it back to the compressor 101. Specifically, through the principle of adsorption and guidance, the deposited lubricating oil is recovered and guided to the lubrication system of the compressor 101, so as to realize the recycling of lubricating oil.

[0060] In heating operation, the outdoor unit 10 can form a refrigerant circuit for heating operation, which is sequentially connected from the liquid side piping 109 to the gas side piping 110 to the outdoor electronic expansion valve 107, the outdoor heat exchanger 105, the switching valve 104 (e.g., the passage between the E port and the S port of a four-way valve), the gas-liquid separator 103, the compressor 101, and the switching valve 104 (e.g., the passage between the D port and the C port of a four-way valve).

[0061] In cooling operation, the outdoor unit 10 can form a refrigerant circuit for cooling operation, which is sequentially connected from the gas side piping 110 to the liquid side piping 109 to a switching valve 104 (e.g., the passage between the C port and the S port of a four-way valve), a gas-liquid separator 103, a compressor 101, a switching valve 104 (e.g., the passage between the D port and the E port of a four-way valve), an outdoor heat exchanger 105, and an outdoor electronic expansion valve 107.

[0062] Compressor 101 is configured to draw in refrigerant and compress it to a high-temperature, high-pressure state. The suction side of compressor 101 is defined as the low-pressure side, and the discharge side as the high-pressure side. In heating mode, the outdoor electronic expansion valve 107 is located closer to the low-pressure side; in cooling mode, the outdoor electronic expansion valve 107 is located closer to the high-pressure side. The speed of compressor 101 is variablely controlled via a frequency converter.

[0063] The outdoor heat exchanger 105 is configured to function as a condenser in cooling operation and as an evaporator in heating operation. The outdoor heat exchanger 105 can exchange heat with the air guided by the outdoor fan 114, so that the refrigerant flowing in the outdoor heat exchanger 105 undergoes a phase change (condensation or evaporation).

[0064] In one or more embodiments of this application, the rotational speed of the outdoor fan 114 can be controlled to change the flow rate of air exchanging heat with the outdoor heat exchanger 105. The outdoor fan 114 can be an axial fan, a cross-flow fan, or other optional fan type. The outdoor fan 114 is located near the outdoor heat exchanger 105.

[0065] The gas-liquid separator 103 is located on the suction side of the compressor 101. It is a shell-shaped component used to separate and store the refrigerant into gas and liquid components. It can store excess refrigerant.

[0066] The structure and function of indoor unit 20 are described below, using two indoor units 20-1 and 20-2 as examples. The following description also applies to the other indoor units 20.

[0067] Indoor unit 20 utilizes the energy generated by outdoor unit 10 to either increase or decrease indoor temperature for cooling or heating operation. For example... Figure 2 As shown, indoor unit 20-1 includes a connected indoor heat exchanger 106-1 and an indoor electronic expansion valve 108-1, and indoor unit 20-2 includes a connected indoor heat exchanger 106-2 and an indoor electronic expansion valve 108-2.

[0068] Indoor heat exchangers 106-1 and 106-2 function as condensers during heating operation and as evaporators during cooling operation.

[0069] Indoor electronic expansion valve 108-1 and indoor electronic expansion valve 108-2 are configured to reduce the pressure of the refrigerant and cause it to expand.

[0070] The opening degrees of the outdoor electronic expansion valve 107, the indoor electronic expansion valve 108-1, and the indoor electronic expansion valve 108-2 are all adjustable to control the flow and pressure of the refrigerant. For example, the opening degree can be adjusted by the number of steps of the motor inside the electronic expansion valve. The number of steps refers to the fixed angle that the motor rotates each time it runs.

[0071] Indoor unit 20-1 is also equipped with an indoor fan 115-1, and indoor unit 20-2 is also equipped with an indoor fan 115-2. Indoor fans 115-1 and 115-2 can be axial fans, cross-flow fans, or other optional fan types.

[0072] In one or more embodiments of this application, such as Figure 3 As shown, the air conditioning system also includes a processing unit 200.

[0073] Figure 4 This is a schematic block diagram of the hardware configuration of the processing device 200. The processing device 200 includes components such as a processor 301, volatile memory 303, non-volatile memory 302, a display device 304, an operation device 305, a communication interface 306, and a drive device 307, which are interconnected via a bus. The processor 301 can be a dedicated processor 301, a central processing unit (CPU), etc. The processor 301 can access the memory unit to execute instructions or application programs stored in the memory unit to achieve related functions. The display device is used to display various information, the operation device is used to receive various operations, and the drive device is a hardware interrupt that interacts with the storage medium. In one or more embodiments of this application, the storage medium (such as...) Figure 4 As shown in 310, this includes media such as CD-ROMs, floppy disks, and optical-magnetic-optical disks that record information optically, electrically, or magnetically. Storage media (such as...) Figure 4 (As shown in 309) can also be a semiconductor memory that records information electrically, such as ROM or flash memory.

[0074] The processing device 200 can be an outdoor controller in the outdoor unit of an air conditioning system, such as an on-board system based on an MCU.

[0075] The functional configuration of the processing device 200 will be described below with reference to the accompanying drawings.

[0076] In one or more embodiments of this application, such as Figure 5 As shown, the processing device includes a generation unit 201, an estimation unit 02, and an intervention unit 203. Each of these components can be implemented by the processor 301 running a program.

[0077] In one or more embodiments of this application, the generation unit 201 is configured to acquire at least one operating parameter of the air conditioning system.

[0078] In one or more embodiments of this application, the generation unit 201 is configured to obtain a calculated compressor operating frequency. For example, the generation unit 201 may obtain the compressor operating frequency based on the total operating capacity of the indoor units and the corresponding correction coefficient (set constant), as disclosed in Chinese patent application (CN114198874A); or it may obtain the compressor operating frequency based on the ratio of the total operating capacity of the activated indoor units to the nominal capacity of the outdoor units; or it may obtain the compressor operating frequency based on the ratio of the number of activated indoor units to the total number of indoor units.

[0079] In one or more embodiments of this application, the generation unit 201 is configured to acquire the indoor electronic expansion valve opening degree calculated for fitting. For example, at the arrival of each sampling period, it acquires data from the sensor unit to calculate the target subcooling degree and the actual subcooling degree, uses the difference between the actual subcooling degree and the target subcooling degree as the subcooling degree difference value, and adjusts the electronic expansion valve opening degree signal according to the difference between the subcooling degree difference value of the current sampling period and the subcooling degree difference value of the previous sampling period to control the opening degree of the indoor electronic expansion valve, as disclosed in Chinese patent application (CN103486691A).

[0080] In one or more embodiments of this application, the generation unit 201 is configured to simultaneously acquire the calculated compressor operating frequency and the indoor electronic expansion valve opening, or may simultaneously acquire the calculated compressor operating frequency, the calculated indoor electronic expansion valve opening, the set indoor fan speed, etc.

[0081] In one or more embodiments of this application, the generation unit 201 may also obtain running parameters generated by other similar algorithms or methods.

[0082] The empirical formulas or algorithms for calculating and setting the operating parameters described above are well known to those skilled in the art and are not the focus of protection of this invention, so they will not be elaborated here.

[0083] The current load demand of the indoor unit is a dynamic parameter influenced by multiple factors, such as changes in the indoor set temperature, the indoor-outdoor temperature difference, indoor humidity, indoor-outdoor airflow, indoor activity levels, indoor-outdoor shading conditions, weather conditions, and the use of heating equipment. These factors all affect the load demand of the indoor unit. Traditional empirical formulas cannot reflect these dynamic changes. Although existing hardware computing capabilities can dynamically calculate operating parameters (compressor operating frequency), the response speed of the actuators (such as the compressor and electronic expansion valve) cannot adapt to the changes in dynamically calculated parameters. This leads to a mismatch between the current load demand and the output capacity of the outdoor unit in many cases, especially when the output capacity exceeds the load demand. This results in the system operating in a state of overheating or overcooling, wasting energy.

[0084] To address this issue, in one or more embodiments of this application, the estimation unit 02 is configured to construct a prediction model, estimate the relative relationship between the current demand load of the indoor unit and the output capacity of the outdoor unit based on the indoor unit's operating status parameters and environmental parameters, and generate the performance level of each indoor unit based on the relative relationship.

[0085] In one or more embodiments of this application, the processing apparatus further includes an intervention unit 203. The intervention unit 203 is configured to generate a corresponding intervention control strategy based on the degree to which the indoor unit's performance level deviates from the benchmark intervention level when an indoor unit's performance level is inferior to a benchmark performance level, so as to intervene and control at least one operating parameter of the air conditioning system; wherein the benchmark intervention level is a benchmark used to assess whether the indoor unit's demand load is too low.

[0086] For example, the baseline intervention level can be level 1. The higher the baseline intervention level, the greater the degree of degradation deviation and the more energy is wasted.

[0087] Figure 6 A flowchart of a processing device, specifically including, for example Figure 6 The steps are shown.

[0088] Step S101: Construct a prediction model.

[0089] Step S102: Based on the indoor unit's operating status parameters and environmental parameters, estimate the relative relationship between the current demand load of the indoor unit and the output capacity of the outdoor unit.

[0090] Step S103: Generate the efficiency level of each indoor unit based on the relative relationship.

[0091] Step S104: Determine whether there is an indoor unit whose performance level is inferior to the baseline performance level.

[0092] Step S105: If there is an indoor unit whose performance level is worse than the baseline performance level, then generate a corresponding intervention control strategy based on the degree to which the indoor unit's performance level deviates from the baseline intervention level.

[0093] Step S106: Intervene and control at least one operating parameter of the air conditioning system.

[0094] Step S107: If there is no indoor unit whose performance level is inferior to the baseline performance level, the current control strategy remains unchanged, for example, it can be controlled based on the operating parameters generated by the generation unit 201.

[0095] This invention generates an efficiency rating for each indoor unit, dynamically evaluates the performance of each indoor unit in real time, and further uses a predictive model to intelligently estimate the relative relationship between the current demand load of the indoor unit and the output capacity of the outdoor unit based on the indoor unit's operating status parameters and environmental parameters. This improves the system's adaptability to changes and enables the system to adaptively intervene in at least one operating parameter to keep performance within the expected range, thereby optimizing performance while reducing energy consumption.

[0096] Figure 7 A flowchart for building a predictive model.

[0097] For example, data collection for predictive models can be performed under experimental conditions (e.g. Figure 7 (as shown in step S201).

[0098] Each element of the collected dataset can include the ID of the indoor unit, the on / off status of the indoor unit, the number of enabled indoor units, the output capacity of the outdoor unit, the operating status parameters of the indoor unit, environmental parameters, and the relative relationship between the current demand load of the indoor unit and the output capacity of the outdoor unit; add time tags to generate a time series consisting of multiple elements.

[0099] The collected dataset is cleaned and preprocessed, for example, missing values ​​and outliers are handled (e.g.) Figure 7 (as shown in step S202).

[0100] In one or more embodiments of this application, a regression model (e.g., linear regression, support vector regression) or a neural network can be selected as the prediction model (e.g., ...). Figure 7 (See step S203). The processed dataset is divided into a training set, a test set, and a validation set.

[0101] The training set is used to train the prediction model, and the test set is used to evaluate the generalization performance of the prediction model. The training set is used to train the selected prediction model, adjusting its parameters to best fit the training data. The test set is used to evaluate the model's performance, and based on the evaluation results, the model is adjusted and optimized (e.g., ...). Figure 7 (as shown in step S204).

[0102] Validate the trained prediction model using a validation set (e.g.) Figure 7 (as shown in step S205).

[0103] Predictive models can use indoor unit operating status parameters and environmental parameters as inputs to estimate the relative relationship between the current demand load of indoor units and the output capacity of outdoor units (e.g., ...). Figure 7 (as shown in step S206); or the relative relationship between the current demand load of the indoor unit and the output capacity of the outdoor unit can be estimated by taking the output capacity of the outdoor unit, the operating status parameters of the indoor unit, and the environmental parameters as inputs.

[0104] Relative relationships can be represented by a statistical indicator, such as correlation coefficient, ratio, etc., without being limited to its specific mathematical representation here.

[0105] Using a trained prediction model, predictions are made based on indoor unit operating status parameters and environmental parameters to obtain inferred prediction results of the correlation.

[0106] In one or more embodiments of this application, the performance level of each indoor unit can be further generated by comparing it with a set threshold.

[0107] In one or more embodiments of this application, the performance level of each indoor unit can be generated by a classifier. Figure 8 This is an example of generating the performance rating for each indoor unit using a classifier. For example... Figure 8 As shown, the relative relationship between the current demand load of indoor units estimated by the prediction model and the output capacity of outdoor units is used as the input feature of the classifier (e.g., Figure 8 As shown in step S301, the indoor unit performance level is used as the target label (e.g., Figure 8 As shown in step S302, train a classifier (such as...). Figure 8 As shown in step S303, the output of the prediction model is mapped to different performance levels (e.g., ...). Figure 8 (See step S304). For example, based on historical data or expert knowledge, assign a corresponding performance level label to each indoor unit; this label can be discrete or continuous.

[0108] In one or more embodiments of this application, the operating parameters include at least one or more of the following: condensing temperature, evaporating temperature, throttling device opening degree, compressor frequency, compressor start / stop status, indoor fan start / stop status, indoor fan speed, outdoor fan start / stop status, and outdoor fan speed.

[0109] In one or more embodiments of this application, the operating parameter is the compressor frequency.

[0110] Taking five efficiency levels as an example, efficiency level 1 is the baseline efficiency level. If there is an indoor unit with an efficiency level lower than the baseline efficiency level (for example, any one of efficiency levels 2 to 5), the intervention unit 203 generates a corresponding intervention control strategy based on the degree to which the efficiency level deviates from the baseline intervention level, in order to intervene and control at least one operating parameter of the air conditioning system, such as correcting the calculation frequency of the startup phase when the compressor starts up next time.

[0111] The following table is an example:

[0112]

[0113] Where a and b are constants less than 1, and a is greater than b.

[0114] By intervening and controlling, the frequency of subsequent starts can be reduced to decrease the output capacity provided by the air conditioning system and avoid excessive waste.

[0115] If an already activated indoor unit is added to the air conditioning system, the intervention unit 203 generates a corresponding intervention control strategy based on the degree to which the efficiency level deviates from the baseline intervention level, in order to intervene and control at least one operating parameter of the air conditioning system, such as the compressor operating frequency after the addition of an already activated indoor unit.

[0116] The following table is an example:

[0117]

[0118] Where a and b are constants less than 1, and a is greater than b.

[0119] Figure 9 This is the compressor operating frequency curve of a traditional air conditioning system. Figure 10 This is the compressor operating frequency curve of the air conditioning system disclosed in this application. (Comparison) Figure 9 and Figure 10 It can be seen that in the air conditioning system provided by this application, the compressor frequency is relatively stable throughout the entire cycle, without frequent start-stop shocks, and the start frequency of the next cycle is effectively weakened, which reduces the overall system energy consumption and improves the compressor life.

[0120] In one or more embodiments of this application, the operating parameter is the opening degree of the indoor electronic expansion valve.

[0121] The following table is an example:

[0122]

[0123] Where a and b are constants less than 1, and a is greater than b.

[0124] Figure 11 This is the opening curve of an indoor electronic expansion valve during the operation of a traditional air conditioning system. Figure 12 This is the opening curve of the same indoor electronic expansion valve during the operation of the air conditioning system disclosed in this application. (Comparison) Figure 11 and Figure 12 It can be seen that in the air conditioning system provided in this application, the opening fluctuation of the indoor electronic expansion valve is small throughout the entire cycle, the performance of the indoor unit is regulated, and the energy consumption of the entire system is optimized.

[0125] In one or more embodiments of this application, the operating parameter is the indoor fan speed.

[0126] During startup, when the indoor ambient temperature deviates from the set temperature, existing technologies control the indoor fan to output at a higher speed to quickly reach the set temperature requirement. In this application, when one indoor unit's performance level is inferior to the benchmark performance level, a corresponding intervention control strategy is generated based on the degree to which the indoor unit's performance level deviates from the benchmark intervention level to intervene and control the indoor fan's speed, thereby reducing the speed.

[0127] Compared to existing technologies, this application achieves energy savings of approximately 9.7% and boasts excellent versatility. The combined use of the integrated frequency and the indoor electronic expansion valve effectively balances the capacity output in each room, better meeting the comfort requirements of the unit.

[0128] In one or more embodiments of this application, the indoor unit status parameters may include one or more of the following: indoor ambient temperature, indoor ambient humidity, indoor location parameters, and indoor personnel parameters.

[0129] In one or more embodiments of this application, the indoor ambient temperature includes a temperature difference based on the indoor ambient temperature.

[0130] In one or more embodiments of this application, indoor ambient humidity includes a humidity difference based on indoor ambient humidity.

[0131] In one or more embodiments of this application, indoor location parameters include: the type of air supply mechanism of the indoor unit (wall-mounted, floor-standing, or ceiling-mounted, etc.), the area of ​​the air-conditioned room, the distribution of doors and windows in the air-conditioned room, the opening and closing information of doors and windows in the air-conditioned room, the type of shading mechanism (curtain type) in the air-conditioned room, and the distribution of heating equipment (high-power computers) in the air-conditioned room.

[0132] In one or more embodiments of this application, indoor personnel parameters include: number of people, user ID, user comfort parameters, amount of clothing worn by users, and parameters of the area where the user is located.

[0133] In one or more embodiments of this application, such as Figure 13 As shown, the processing device 201 includes a generation unit 211, an estimation unit 212, an optimization unit 213, and a compensation unit 214. Each of these components can be implemented by a processor running a program.

[0134] In one or more embodiments of this application, the generation unit 211 is configured to acquire at least one operating parameter of the air conditioning system.

[0135] For a detailed description of the method for generating at least one operating parameter of the air conditioning system in the above embodiments, it will not be repeated here.

[0136] In one or more embodiments of this application, the estimation unit 212 is configured to estimate the relative relationship between the current demand load of the indoor unit and the output capacity of the air conditioning system based on the indoor unit status parameters and environmental parameters, and generate the efficiency level of each indoor unit based on the relative relationship.

[0137] In one or more embodiments of this application, the estimation unit 212 can estimate the relative relationship between the current demand load of the indoor unit and the output capacity of the air conditioning system based on the indoor unit state parameters and environmental parameters, according to empirical formulas or empirical methods, and generate the performance level of each indoor unit based on the relative relationship. The empirical formulas or empirical methods can employ techniques known to those skilled in the art.

[0138] In one or more embodiments of this application, the estimation unit 212 is configured to construct a prediction model, using indoor unit state parameters and environmental parameters as inputs, to estimate the relative relationship between the current demand load of the indoor unit and the output capacity of the outdoor unit; the relative relationship between the current demand load of the indoor unit and the output capacity of the air conditioning system is passed as input to the classifier, and the classifier is configured to generate the performance level of the indoor unit based on the relative relationship.

[0139] For details on how to construct the prediction model, please refer to the above embodiments for a detailed description, which will not be repeated here.

[0140] In one or more embodiments of this application, the optimization unit 213 is configured to generate an optimized control strategy based on the indoor unit performance level. The optimized control strategy can reduce the marginal energy loss caused by the preset temperature compensation.

[0141] Central air conditioning systems typically consider factors such as the location of different indoor units, environmental conditions, and airflow distribution. To improve the overall temperature control performance of the system, a temperature compensation program is designed. The main purpose of this program is to compensate for the return air temperature detected in different indoor units based on various factors in the actual operating environment, ensuring that the set temperature in each air-conditioned room is accurately achieved. For example, changes in the external environment, such as sunlight, can cause deviations in the return air temperature (i.e., the indoor ambient temperature), and the temperature compensation program can adjust accordingly. This program is embedded in the air conditioning system's control algorithm, dynamically compensating for temperature changes through sensor measurements and real-time feedback, enabling it to better adapt to complex operating environments.

[0142] However, the introduction of temperature compensation procedures also leads to marginal energy loss. In particular, temperature compensation procedures require real-time monitoring and adjustment of the indoor environment, and corresponding adjustment of the operating status of the indoor units, which may contradict the energy-priority control strategy. Existing technologies generally consider the disadvantages of temperature compensation procedures to outweigh the advantages, ignoring the additional energy consumption they bring. This embodiment aims to solve this problem, reducing the additional energy consumption caused by temperature compensation procedures while ensuring their advantages.

[0143] To address this issue, the present invention includes an optimization unit 213, which is configured to generate an optimized control strategy based on the indoor unit performance level, and reduce the marginal energy loss caused by the preset temperature compensation through the optimized control strategy.

[0144] In one or more embodiments of this application, the optimization unit 213 is specifically configured to construct an optimization model, taking the indoor unit performance level, indoor unit state parameters and environmental parameters as inputs, and outputting optimized temperature compensation parameters.

[0145] In one or more embodiments of this application, the compensation unit 214 is configured to execute an optimized control strategy to optimize the control of at least one operating parameter of the air conditioning system.

[0146] Figure 14 A flowchart of the processing device 201, specifically including as follows Figure 14 The steps are shown.

[0147] Step S401: Construct a prediction model.

[0148] Step S402: Based on the indoor unit's operating status parameters and environmental parameters, estimate the relative relationship between the current demand load of the indoor unit and the output capacity of the outdoor unit.

[0149] Step S403: Generate the efficiency level of each indoor unit based on the relative relationship.

[0150] Step S404: Construct an optimization model.

[0151] Step S405: Using the indoor unit performance level, indoor unit state parameters, and environmental parameters as inputs to the optimization model, output the optimization control strategy.

[0152] Step S406: Execute an optimized control strategy to optimize at least one operating parameter of the air conditioning system.

[0153] Figure 15 A flowchart for building an optimization model.

[0154] For example, data collection for optimizing the model can be performed under experimental conditions (e.g.) Figure 15 (as shown in step S501).

[0155] Each element of the collected dataset can include the ID of the indoor unit, the on / off status of the indoor unit, the number of enabled indoor units, the efficiency level of the indoor unit, the operating status parameters of the indoor unit, environmental parameters, temperature compensation values, and operating parameters of the air conditioning system; add time tags to generate a time series consisting of multiple elements.

[0156] The collected dataset is cleaned and preprocessed, for example, missing values ​​and outliers are handled (e.g.) Figure 15 (as shown in step S502).

[0157] In one or more embodiments of this application, a regression model (e.g., linear regression, support vector regression) or a neural network can be selected as the optimization model (e.g., ...). Figure 15 (See step S503). The processed dataset is divided into a training set, a test set, and a validation set.

[0158] The training set is used to train and optimize the model, while the test set is used to evaluate the generalization performance of the optimized model. The training set is used to train the selected optimized model, adjusting its parameters to best fit the training data. The test set is used to evaluate the model's performance, and based on the evaluation results, the model is adjusted and optimized (e.g., ...). Figure 15 (as shown in step S504).

[0159] Use a validation set to validate the trained optimized model (e.g.) Figure 15 (as shown in step S505).

[0160] The trained optimization model can use the indoor unit performance level as input to generate an optimized control strategy (such as...). Figure 15 (as shown in step S506).

[0161] In one or more embodiments of this application, a neural network can be selected as both a prediction model and an optimization model. That is, the prediction model is used to predict the energy efficiency level of the indoor unit, and then this predicted level is used as input to the optimization model. The optimization model is used to optimize temperature compensation to reduce marginal energy loss. The two models can cooperate with each other through joint optimization to improve the performance of the entire system.

[0162] The features used by the predictive and optimization models overlap in two dimensions: indoor unit state parameters and environmental parameters. The shared features enable the models to better understand the key characteristics of the data and promote consistency in decision-making between the predictive and optimization models.

[0163] like Figure 16 As shown in steps S601 to S609, in one or more embodiments of this application, the prediction model and the optimization model can be iteratively optimized using alternating or joint training methods. In each iteration, the prediction model is trained first, and then the output of the prediction model is used as the input of the optimization model to train the optimization model. Then the prediction model is trained again, and so on. This iterative optimization method helps the two models gradually work together to achieve better performance.

[0164] When evaluating the results, the predictive model can be evaluated using classification metrics such as accuracy or F1 score, while the optimization model can be evaluated using regression task metrics.

[0165] Using a trained optimization model, which takes the indoor unit efficiency level as input, the optimization model generates optimized temperature compensation values ​​as optimized temperature compensation parameters. The compensation unit 214 can then optimize and control at least one operating parameter of the air conditioning system, such as the compressor operating frequency, based on these optimized temperature compensation parameters.

[0166] The air conditioning system provided in this application can reduce the marginal energy loss caused by preset temperature compensation according to the efficiency level of the indoor unit, thereby improving the energy efficiency of the entire air conditioning system, reducing energy waste, and providing smarter and more economical indoor environmental control.

[0167] In one or more embodiments of this application, the indoor unit status parameters may include one or more of the following: indoor ambient temperature, indoor ambient humidity, indoor location parameters, and indoor personnel parameters.

[0168] In one or more embodiments of this application, the indoor ambient temperature includes a temperature difference based on the indoor ambient temperature.

[0169] In one or more embodiments of this application, indoor ambient humidity includes a humidity difference based on indoor ambient humidity.

[0170] In one or more embodiments of this application, indoor location parameters include: the type of air supply mechanism of the indoor unit (wall-mounted, floor-standing, or ceiling-mounted, etc.), the area of ​​the air-conditioned room, the distribution of doors and windows in the air-conditioned room, the opening and closing information of doors and windows in the air-conditioned room, the type of shading mechanism (curtain type) in the air-conditioned room, and the distribution of heating equipment (high-power computers) in the air-conditioned room.

[0171] In one or more embodiments of this application, indoor personnel parameters include: number of people, user ID, user comfort parameters, amount of clothing worn by users, and parameters of the area where the user is located.

[0172] In the description of the above embodiments, specific features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0173] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. Air conditioning system, including: At least one indoor unit; The outdoor unit is fluidly connected to the indoor unit; and Its characteristic is that it further includes: The processing device includes: A generation unit configured to acquire at least one operating parameter of the air conditioning system; The estimation unit is configured to estimate the relative relationship between the current demand load of the indoor unit and the output capacity of the air conditioning system based on the indoor unit's state parameters and environmental parameters, and to generate the performance level of each indoor unit based on the relative relationship. Specifically, it is configured to: construct a prediction model, using the indoor unit's state parameters and environmental parameters as input, to estimate the relative relationship between the current demand load of the indoor unit and the output capacity of the outdoor unit; and pass the relative relationship between the current demand load of the indoor unit and the output capacity of the air conditioning system as input to a classifier, which is configured to generate the performance level of the indoor unit based on the relative relationship. The optimization unit is configured to generate an optimized control strategy based on the indoor unit performance level, the optimized control strategy reducing marginal energy loss caused by preset temperature compensation; it is also configured to construct an optimization model, taking the indoor unit performance level, indoor unit state parameters, and environmental parameters as inputs, and outputting optimized temperature compensation parameters; and The compensation unit is configured to execute the optimized control strategy to optimize the control of at least one operating parameter of the air conditioning system; and to optimize the control of at least one operating parameter of the air conditioning system based on the optimized temperature compensation parameter.

2. The air conditioning system according to claim 1, characterized in that: The operating parameters include at least one or more of the following: condensing temperature, evaporating temperature, throttling device opening degree, compressor frequency, compressor start / stop status, indoor fan start / stop status, indoor fan speed, outdoor fan start / stop status, and outdoor fan speed.

3. The air conditioning system according to claim 1, characterized in that: The indoor unit status parameters include at least one or more of the following: indoor ambient temperature, indoor ambient humidity, indoor location parameters, and indoor personnel parameters.

4. The air conditioning system according to claim 1, characterized in that: The environmental parameters include at least one or more of the following: outdoor ambient temperature, outdoor ambient humidity, weather parameters, and geographical location parameters.

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