Control method and device of multi-split equipment, multi-split equipment and storage medium

Abstract

The invention discloses a multi-split equipment control method and device, multi-split equipment and a storage medium, and relates to the technical field of multi-split equipment, the multi-split equipment comprises an outdoor unit and at least two indoor units, the outdoor unit comprises at least one compressor, and the method comprises the steps that indoor unit feature information of the multi-split equipment in operation is obtained; and frequency prediction is conducted according to the indoor unit characteristic information and a frequency prediction model corresponding to the multi-split equipment, the target operation frequency is determined, and the compressor is controlled to operate according to the target operation frequency. Through the mode, more accurate, timely and stable compressor frequency control can be realized, so that a comfortable temperature environment is created, and the user experience is improved.

Description

Technical Field

[0001] This application relates to the field of multi-split air conditioning technology, and in particular to control methods, devices, multi-split air conditioning equipment, and storage media for multi-split air conditioning equipment. Background Technology

[0002] Traditional multi-split air conditioning systems obtain the target frequency through experience / rule tables and control the compressor operation. However, due to limitations in the number of features, control granularity, and post-error feedback, this can easily lead to phenomena such as over-temperature, under-temperature, and temperature oscillation. Summary of the Invention

[0003] The main objective of this application is to provide a control method, device, multi-split air conditioning unit, and storage medium for multi-split air conditioning equipment, aiming to solve the technical problem that multi-split air conditioning equipment in the prior art cannot achieve accurate and stable compressor frequency control.

[0004] To achieve the above objectives, this application proposes a control method for a multi-split air conditioning system, the multi-split air conditioning system including an outdoor unit and at least two indoor units, wherein the outdoor unit includes at least one compressor, and the method includes:

[0005] Obtain the characteristic information of the indoor unit of the multi-split air conditioning system during operation;

[0006] Frequency prediction is performed based on the indoor unit's characteristic information and the frequency prediction model corresponding to the multi-split air conditioning unit to determine the target operating frequency, and the compressor is controlled to operate at the target operating frequency.

[0007] In one embodiment, before the step of determining the target operating frequency by performing frequency prediction based on the unit characteristic information and the frequency prediction model corresponding to the multi-unit equipment, the method further includes:

[0008] Obtain the unit's historical operating information for the multi-unit system;

[0009] A frequency prediction model for the multi-unit equipment is obtained by constructing a model based on the unit's historical operating information.

[0010] In one embodiment, the historical operating information includes the operating information of all indoor units and the historical operating frequency of the compressor;

[0011] The step of constructing a model based on the historical operating information to obtain the frequency prediction model of the multi-unit equipment includes:

[0012] A frequency prediction model for the multi-split air conditioning system is obtained by constructing a model based on the operating information of all indoor units and the historical operating frequency of the compressor.

[0013] In one embodiment, the step of constructing a model based on the operating information of all indoor units and the historical operating frequency of the compressor to obtain the frequency prediction model of the multi-split air conditioning system includes:

[0014] The model output variables are determined based on the historical operating frequency.

[0015] The model input variables are determined based on the operating information of the internal machine;

[0016] The model is constructed based on the model output variables and model input variables to obtain the frequency prediction model corresponding to the multi-unit equipment.

[0017] In one embodiment, the step of constructing a model based on the model output variables and model input variables to obtain the frequency prediction model of the multi-unit air conditioning system includes:

[0018] Machine learning is performed based on the model output variables and model input variables, and the frequency prediction model corresponding to the multi-unit equipment is obtained through the machine learning results.

[0019] In one embodiment, the step of constructing a model based on the model output variables and model input variables to obtain the frequency prediction model corresponding to the multi-unit air conditioning system includes:

[0020] Deep learning is performed based on the model output variables and model input variables, and the frequency prediction model of the multi-unit equipment is obtained through the deep learning results.

[0021] In one embodiment, the operating information of the indoor unit includes at least one of environmental status information, historical status information, and historical control information. The environmental status information includes at least one of historical indoor temperature and historical outdoor temperature, and the historical control information includes at least one of user-controlled temperature and user-controlled fan speed.

[0022] Furthermore, to achieve the above objectives, this application also proposes a control device for a multi-split air conditioning system, the control device comprising:

[0023] The acquisition module is used to acquire the characteristic information of the indoor unit of the multi-split air conditioning system during operation;

[0024] The prediction module is used to predict the frequency based on the characteristic information of the indoor unit and the frequency prediction model corresponding to the multi-split air conditioning unit, determine the target operating frequency, and control the compressor to operate at the target operating frequency.

[0025] In addition, to achieve the above objectives, this application also proposes a multi-unit device, which includes: a memory, a processor, and a control program for the multi-unit device stored in the memory and executable on the processor. The control program for the multi-unit device is configured to implement the control method for the multi-unit device as described above.

[0026] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the control method for multi-unit equipment as described above.

[0027] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the control method for multi-unit equipment as described above.

[0028] This application proposes one or more technical solutions, wherein the control method for multi-split air conditioning units is applied to multi-split air conditioning units, the multi-split air conditioning units including an outdoor unit and at least two indoor units, the outdoor unit including at least one compressor, and the method comprising: acquiring characteristic information of the indoor unit units during operation of the multi-split air conditioning unit; performing frequency prediction based on the characteristic information of the indoor unit units and a frequency prediction model corresponding to the multi-split air conditioning unit to determine a target operating frequency, and controlling the compressor to operate at the target operating frequency. Through the above method, more accurate, timely, and stable compressor frequency control can be achieved, thereby creating a comfortable temperature environment and improving the user experience. Attached Figure Description

[0029] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0030] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 A flowchart illustrating an embodiment of the control method for multi-unit air conditioning equipment in this application;

[0032] Figure 2 This is a structural schematic diagram of the multi-unit air conditioning system of this application;

[0033] Figure 3 A flowchart illustrating the second embodiment of the control method for multi-unit air conditioning systems in this application;

[0034] Figure 4 A simplified flowchart illustrating the control method for a multi-unit air conditioning system provided in Embodiment 2 of this application;

[0035] Figure 5 A schematic diagram of a multi-split air conditioning unit for the control method of the multi-split air conditioning unit provided in Embodiment 2 of this application;

[0036] Figure 6 This is a schematic diagram of the module structure of the control device for a multi-unit air conditioning system according to an embodiment of this application;

[0037] Figure 7 This is a schematic diagram of the hardware operating environment involved in the control method of the multi-unit equipment in the embodiments of this application.

[0038] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0039] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0040] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0041] The main solution of this application embodiment is: to obtain the characteristic information of the indoor unit of the multi-split air conditioning unit during operation; to perform frequency prediction based on the characteristic information of the indoor unit and the frequency prediction model corresponding to the multi-split air conditioning unit, to determine the target operating frequency, and to control the compressor to operate according to the target operating frequency.

[0042] Traditional multi-split air conditioning systems obtain the target frequency through experience / rule tables and control the compressor operation. However, due to limitations in the number of features, control granularity, and post-error feedback, this can easily lead to phenomena such as over-temperature, under-temperature, and temperature oscillation.

[0043] This application provides a solution that predicts the target operating frequency based on the characteristic information of the indoor unit of the multi-split air conditioning system and the frequency prediction model corresponding to the multi-split air conditioning system, and controls the compressor to operate at the target operating frequency. This can achieve more accurate, timely and stable compressor frequency control, thereby creating a comfortable temperature environment and improving the user experience.

[0044] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as an air conditioner, a multi-split air conditioning unit, and a fresh air system, or an electronic device or multi-split air conditioning unit capable of performing the above functions. The following description uses a multi-split air conditioning unit as an example to illustrate this embodiment and the subsequent embodiments.

[0045] Based on this, the embodiments of this application provide a control method for multi-unit air conditioning equipment, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the control method for multi-unit air conditioning systems according to this application.

[0046] In this embodiment, the control method for the multi-unit air conditioning system includes steps S10 to S20:

[0047] In this embodiment, the control method for multi-split air conditioning units is applied to multi-split air conditioning units, such as... Figure 2 As shown, the multi-split air conditioning system includes an outdoor unit A and at least two indoor units B1 and B2. Each outdoor unit includes at least one compressor 1, which provides the high-temperature refrigerant during operation, thereby achieving heat exchange between the indoor and outdoor units. Through the collaborative operation of the indoor and outdoor units, a complete cooling and heating system is formed, ensuring that the multi-split air conditioning system can effectively regulate indoor temperature and humidity, providing a comfortable living or working environment.

[0048] Step S10: Obtain the characteristic information of the indoor unit of the multi-split air conditioning system during operation.

[0049] It should be noted that the indoor unit characteristic information refers to the operating characteristic information of all operating indoor units in a multi-split air conditioning system. This operating characteristic information includes, but is not limited to, the current indoor and outdoor temperatures of the environment in which the indoor unit is located, the current set temperature and fan speed corresponding to the indoor unit, and other operating parameter information. In this embodiment, the current set temperature and fan speed corresponding to the indoor unit can be set by the user, or they can be determined by the indoor unit by looking up the set temperature and fan speed corresponding to the current indoor and outdoor temperatures in historical operating parameters. This embodiment does not limit the method of obtaining the current set temperature and fan speed corresponding to the indoor unit. In this embodiment, each indoor unit corresponds to one set of indoor unit characteristic information.

[0050] Step S20: Based on the indoor unit's characteristic information and the frequency prediction model corresponding to the multi-split unit, perform frequency prediction to determine the target operating frequency, and control the compressor to operate according to the target operating frequency.

[0051] It should be noted that each multi-split air conditioning unit corresponds to a frequency prediction model, which is constructed based on the historical operating information of the multi-split air conditioning unit. This historical operating information includes the operating information of all indoor units in the multi-split air conditioning unit and the historical operating frequency of the compressor. In this embodiment, the historical operating frequency of the compressor under each historical operating condition is used as the dependent variable y for that historical operating condition, and the features corresponding to the operating information of all operating indoor units under that historical operating condition are used as the independent variable x for that historical operating condition, resulting in multiple dependent variables y and independent variables x under various historical operating conditions. A frequency prediction model y = f(x1,x2,...,xn) is constructed based on the dependent variables y and independent variables x under multiple historical operating conditions. In this embodiment, model construction can be performed using machine learning, deep learning, or other methods; this embodiment does not limit the method of model construction.

[0052] It is understandable that the constructed frequency prediction model can output the frequency at which the compressor needs to operate under the current indoor unit characteristics by taking into account the operating characteristic information of all currently running indoor units. In this embodiment, the target operating frequency refers to the frequency at which the compressor needs to operate under the current indoor unit characteristics output by the frequency prediction model.

[0053] This embodiment provides a multi-split air conditioning system, including an outdoor unit and at least two indoor units. Each outdoor unit includes at least one compressor. The method includes: acquiring characteristic information of the indoor unit units during operation; performing frequency prediction based on the indoor unit unit characteristic information and a frequency prediction model corresponding to the multi-split air conditioning system to determine a target operating frequency; and controlling the compressors to operate at the target operating frequency. Through this method, more accurate, timely, and stable compressor frequency control can be achieved, thereby creating a comfortable temperature environment and improving the user experience.

[0054] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in Embodiment 1 above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 3 Before step S20, steps S01 to S02 are also included:

[0055] Step S01: Obtain the historical operating information of the multi-unit equipment.

[0056] Step S02: Based on the historical operating information of the unit, a model is constructed to obtain the frequency prediction model of the multi-unit equipment.

[0057] It should be noted that the historical operating information of a multi-split air conditioning unit consists of the operating information of all indoor units in the multi-split air conditioning unit and the operating frequency of the compressor. The historical operating information of the unit does not distinguish the operating information of individual indoor units. Instead, it summarizes the operating information of all indoor units to obtain the historical operating frequency of the compressor and the operating information of all indoor units under historical operating conditions.

[0058] It is understandable that the historical operating frequency of the compressor under each historical operating condition is used as the dependent variable y corresponding to each historical operating condition, and the operating information of all operating indoor units under each historical operating condition is used as the independent variable x corresponding to each historical operating condition, to construct a frequency prediction model of y = f(x1,x2,...,xn).

[0059] In one feasible implementation, the historical operating information includes the operating information of all indoor units and the historical operating frequency of the compressor, and step S02 may include step A20:

[0060] Step A20: Based on the operating information of all indoor units and the historical operating frequency of the compressor, a model is constructed to obtain the frequency prediction model of the multi-split air conditioning unit.

[0061] In one feasible implementation, the operating information of the indoor unit includes at least one of environmental status information, historical status information, and historical control information. The environmental status information includes at least one of historical indoor temperature and historical outdoor temperature, and the historical control information includes at least one of user-controlled temperature and user-controlled fan speed.

[0062] It should be noted that the operating information of all indoor units includes at least one of the following under various historical operating conditions: environmental status information, historical status information, and historical control information of all operating indoor units. Environmental status information includes, but is not limited to, historical indoor and outdoor temperatures during operation; historical status information includes, but is not limited to, the required cooling / heating capacity and expansion valve opening of each indoor unit during operation; and historical control information includes, but is not limited to, the set temperature and fan speed of each indoor unit during operation.

[0063] In one feasible implementation, step A20 may include steps B21 to B23:

[0064] Step B21: Determine the model output variables based on the historical operating frequency.

[0065] Step B22: Determine the model input variables based on the operating information of the internal machine.

[0066] Step B23: Construct a model based on the model output variables and model input variables to obtain the frequency prediction model corresponding to the multi-unit equipment.

[0067] It should be noted that the historical operating frequency of the compressor under each historical operating condition is used as the model output variable y. In this embodiment, the model output variable is also called the dependent variable. The features corresponding to the operating information of all running indoor units under each historical operating condition are used as the model input variable x. In this embodiment, the model input variable is also called the independent variable.

[0068] Understandably, based on the model output and input variables under various historical operating conditions, a model can be constructed to obtain a frequency prediction model of y = f(x1,x2,...,xn). After inputting the characteristics of multiple indoor units, the target operating frequency for the entire set of indoor units can be obtained through the frequency prediction model corresponding to the multi-unit system.

[0069] In one possible implementation, step B23 may include step C21:

[0070] Step C21: Perform machine learning based on the model output variables and model input variables, and obtain the frequency prediction model corresponding to the multi-unit equipment through the machine learning results.

[0071] It should be noted that machine learning is performed based on the model output variables and model input variables under various historical operating conditions. The machine learning methods include, but are not limited to, linear regression, decision trees and random forests, support vector machines, and other machine learning methods. After the machine learning is completed, the frequency prediction model corresponding to the multi-unit equipment is obtained.

[0072] In one possible implementation, step B23 may include step D21:

[0073] Step D21: Perform deep learning based on the model output variables and model input variables, and obtain the frequency prediction model of the multi-unit equipment through the deep learning results.

[0074] It should be noted that, in addition to the machine learning method mentioned above, neural networks and deep learning can also be used to train the model by combining the model output variables and model input variables under various historical operating conditions, thus obtaining the frequency prediction model corresponding to the multi-unit equipment. Other methods can also be used to construct the frequency prediction model; this embodiment does not impose any limitations on this approach.

[0075] This embodiment acquires the historical operating information of the multi-split air conditioning unit; based on the historical operating information, a model is constructed to obtain the frequency prediction model of the multi-split air conditioning unit. Through this method, a frequency prediction model based on the overall needs of multiple indoor units can be accurately constructed, while ensuring the model's performance.

[0076] For example, to help understand the implementation flow of the control method for multi-unit air conditioning equipment obtained by combining Embodiment 1 and Embodiment 2 above, please refer to... Figure 4 , Figure 4 A simplified flowchart of a control method for multi-unit air conditioning systems is provided, specifically:

[0077] The control method for multi-split air conditioning units in this embodiment may include the following steps: 1. Obtaining multi-split air conditioning unit information, such as... Figure 5 The indoor units A1, A2, and A3 shown constitute a multi-split air conditioning unit. 2. Based on the historical data of this unit, train a frequency prediction model for the entire unit. a) Collect historical data from multiple indoor units, including three types of features: environmental conditions (indoor temperature, outdoor temperature, etc.), operating conditions (operating frequency, expansion valve opening, etc.), and user settings (set temperature Tset, set fan speed Wset, etc.). b) Using the operating frequency as the dependent variable y and other features as independent variables x, construct a frequency prediction model y = f(x1,x2,...,xn). Note: If multiple indoor unit features are input, the model can obtain the target frequency for the multiple indoor units. 3. Obtain the features of the multiple indoor units of this unit, call the frequency prediction model, and obtain the target frequency of the unit. 4. Control the compressor operation according to the target frequency. Through the above methods, more accurate, timely, and stable compressor frequency control can be achieved, thereby creating a comfortable temperature environment.

[0078] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the control method of the multi-unit equipment of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0079] This application also provides a control device for multi-unit air conditioning systems; please refer to [reference needed]. Figure 6 The control device for the multi-unit air conditioning system includes:

[0080] The acquisition module 10 is used to acquire the characteristic information of the indoor unit of the multi-split air conditioning system during operation.

[0081] The prediction module 20 is used to predict the frequency based on the indoor unit's characteristic information and the frequency prediction model corresponding to the multi-split unit, determine the target operating frequency, and control the compressor to operate at the target operating frequency.

[0082] In one embodiment, the prediction module 20 is further configured to acquire the historical operating information of the multi-unit equipment; and to construct a model based on the historical operating information to obtain the frequency prediction model of the multi-unit equipment.

[0083] In one embodiment, the prediction module 20 is further configured to construct a model based on the operating information of all indoor units and the historical operating frequency of the compressor, thereby obtaining a frequency prediction model for the multi-split air conditioning unit.

[0084] In one embodiment, the prediction module 20 is further configured to determine the model output variable based on the historical operating frequency and to determine the model input variable based on the operating information of the internal unit;

[0085] The model is constructed based on the model output variables and model input variables to obtain the frequency prediction model corresponding to the multi-unit equipment.

[0086] In one embodiment, the prediction module 20 is further configured to perform machine learning based on the model output variables and model input variables, and obtain the frequency prediction model corresponding to the multi-unit equipment through the machine learning results.

[0087] In one embodiment, the prediction module 20 is further configured to perform deep learning based on the model output variables and model input variables, and obtain the frequency prediction model of the multi-unit equipment through the deep learning results.

[0088] This embodiment acquires the characteristic information of the indoor unit of the multi-split air conditioning system during operation; based on the characteristic information of the indoor unit and the frequency prediction model corresponding to the multi-split air conditioning system, it performs frequency prediction to determine the target operating frequency, and controls the compressor to operate at the target operating frequency. Through this method, more accurate, timely, and stable compressor frequency control can be achieved, thereby creating a comfortable temperature environment and improving the user experience.

[0089] The control device for multi-split air conditioning units provided in this application, employing the control method for multi-split air conditioning units described in the above embodiments, can solve the technical problem in the prior art where multi-split air conditioning units cannot achieve accurate and stable compressor frequency control. Compared with the prior art, the beneficial effects of the control device for multi-split air conditioning units provided in this application are the same as those of the control method for multi-split air conditioning units provided in the above embodiments, and other technical features in the control device for multi-split air conditioning units are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0090] This application provides a multi-unit air conditioning device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the control method of the multi-unit air conditioning device in the first embodiment described above.

[0091] The following is for reference. Figure 7This document illustrates a structural diagram of a multi-connector device suitable for implementing embodiments of this application. The multi-connector device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 7 The multi-unit air conditioning system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0092] like Figure 7 As shown, the multi-unit device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the multi-unit device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows the multi-unit equipment to communicate wirelessly or wiredly with other devices to exchange data. Although the figures show multi-unit equipment with various systems, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0093] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0094] The multi-split air conditioning system provided in this application, employing the control method for multi-split air conditioning systems described in the above embodiments, can solve the technical problem in the prior art where multi-split air conditioning systems cannot achieve accurate and stable compressor frequency control. Compared with the prior art, the beneficial effects of the multi-split air conditioning system provided in this application are the same as the beneficial effects of the control method for multi-split air conditioning systems provided in the above embodiments, and other technical features of this multi-split air conditioning system are the same as those disclosed in the method of the previous embodiment, and will not be repeated here.

[0095] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0096] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0097] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the control method of the multi-unit device described in the above embodiments.

[0098] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0099] The aforementioned computer-readable storage medium may be included in the multi-unit equipment; or it may exist independently and not assembled into the multi-unit equipment.

[0100] The aforementioned computer-readable storage medium carries one or more programs that, when executed by the multi-split air conditioning unit, cause the multi-split air conditioning unit to: acquire characteristic information of the indoor unit units during operation; perform frequency prediction based on the indoor unit unit characteristic information and the frequency prediction model corresponding to the multi-split air conditioning unit to determine the target operating frequency; and control the compressor to operate at the target operating frequency.

[0101] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0102] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0103] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0104] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the control method of the multi-split air conditioning unit described above. This solves the technical problem in the prior art that multi-split air conditioning units cannot achieve accurate and stable compressor frequency control. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the control method of the multi-split air conditioning unit provided in the above embodiments, and will not be repeated here.

[0105] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the control method for multi-unit devices as described above.

[0106] The computer program product provided in this application can solve the technical problem that multi-split air conditioning equipment cannot achieve accurate and stable compressor frequency control in the prior art. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the control method for multi-split air conditioning equipment provided in the above embodiments, and will not be repeated here.

[0107] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A control method for a multi-unit air conditioning system, characterized in that, Multi-split air conditioning units include an outdoor unit and at least two indoor units, the outdoor unit including at least one compressor, the method comprising: Obtain the characteristic information of the indoor unit of the multi-split air conditioning system during operation; Frequency prediction is performed based on the indoor unit's characteristic information and the frequency prediction model corresponding to the multi-split air conditioning unit to determine the target operating frequency, and the compressor is controlled to operate at the target operating frequency.

2. The method as described in claim 1, characterized in that, Before the step of determining the target operating frequency by performing frequency prediction based on the unit characteristic information and the frequency prediction model corresponding to the multi-unit equipment, the method further includes: Obtain the unit's historical operating information for the multi-unit system; A frequency prediction model for the multi-unit equipment is obtained by constructing a model based on the unit's historical operating information.

3. The method as described in claim 2, characterized in that, The historical operating information includes the operating information of all indoor units and the historical operating frequency of the compressor; The step of constructing a model based on the historical operating information to obtain the frequency prediction model of the multi-unit equipment includes: A frequency prediction model for the multi-split air conditioning system is obtained by constructing a model based on the operating information of all indoor units and the historical operating frequency of the compressor.

4. The method as described in claim 3, characterized in that, The step of constructing a model based on the operating information of all indoor units and the historical operating frequency of the compressor to obtain the frequency prediction model of the multi-split air conditioning system includes: The model output variables are determined based on the historical operating frequency. The model input variables are determined based on the operating information of the internal machine; The model is constructed based on the model output variables and model input variables to obtain the frequency prediction model corresponding to the multi-unit equipment.

5. The method as described in claim 4, characterized in that, The step of constructing the model based on the model output variables and model input variables to obtain the frequency prediction model of the multi-unit air conditioning system includes: Machine learning is performed based on the model output variables and model input variables, and the frequency prediction model corresponding to the multi-unit equipment is obtained through the machine learning results.

6. The method as described in claim 4, characterized in that, The step of constructing a model based on the model output variables and model input variables to obtain the frequency prediction model corresponding to the multi-unit air conditioning system includes: Deep learning is performed based on the model output variables and model input variables, and the frequency prediction model of the multi-unit equipment is obtained through the deep learning results.

7. The method as described in claim 3, characterized in that, The operating information of the indoor unit includes at least one of environmental status information, historical status information, and historical control information. The environmental status information includes at least one of historical indoor temperature and historical outdoor temperature. The historical control information includes at least one of user-controlled temperature and user-controlled fan speed.

8. A control device for a multi-unit air conditioning system, characterized in that, The control device for the multi-unit air conditioning system includes: The acquisition module is used to acquire the characteristic information of the indoor unit of the multi-split air conditioning system during operation; The prediction module is used to predict the frequency based on the characteristic information of the indoor unit and the frequency prediction model corresponding to the multi-split air conditioning unit, determine the target operating frequency, and control the compressor to operate at the target operating frequency.

9. A multi-unit air conditioning system, characterized in that, The multi-split air conditioning unit includes: a memory, a processor, and a control program for the multi-split air conditioning unit stored in the memory and executable on the processor. The control program for the multi-split air conditioning unit is configured to implement the control method for the multi-split air conditioning unit as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium stores a control program for a multi-split air conditioning unit, which, when executed by a processor, implements the control method for the multi-split air conditioning unit as described in any one of claims 1 to 7.

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