A self-learning control gateway and method for an air conditioning system

Abstract

The application relates to the technical field of air conditioner control, in particular to a self-learning control gateway and method for an air conditioner system, the gateway comprising two communication interfaces, wherein the air conditioner interface is used for establishing a connection with a communication bus between an air conditioner device and an original control system, realizing data monitoring, and can also be used for establishing a communication connection with the air conditioner device, realizing data interaction; the centralized control interface is used for establishing a communication connection with the original control system, realizing data forwarding and reply; the uplink communication interface communicates with a cloud platform, realizing unified regulation and control of the air conditioner device; the processor obtains the parameter address and corresponding data of the monitored parameters through the air conditioner interface and carries out average value processing; the processor completes the interaction of control data through the air conditioner interface and the uplink communication interface; the processor forwards and replies data to the original control system through the centralized control interface; the storage module is used for storing the average value data obtained through calculation and collected in the self-learning stage; the application can solve the double-host conflict problem and completely avoid communication error.

Description

Technical Field

[0001] This invention relates to the field of air conditioning control technology, and in particular to a self-learning control gateway and method for air conditioning systems. Background Technology

[0002] In existing air conditioning systems consisting of multiple air conditioners, a control system from the air conditioner manufacturer is typically deployed to centrally monitor all air conditioners, read parameters, and issue commands, ensuring the stable operation of the system. With increasing demands for intelligent air conditioning management and energy conservation, it is often necessary to add an air conditioning control gateway to expand control functions. However, two core issues in existing technology make it difficult for new gateways to be compatible with network access:

[0003] 1. Dual-host conflict issue. The original control system already serves as the communication host for the air conditioning system. If a new gateway is added and directly connected in parallel or series on the communication bus, it will create two communication hosts, leading to bus occupancy conflicts, disordered command interaction, severely affecting the normal communication of the air conditioning system, and even causing the entire air conditioning system to malfunction.

[0004] 2. Communication Detection Error Issue. The original control system generally has a communication detection function, periodically reading the operating parameters of each air conditioner to confirm the communication link is normal. When a new gateway is added and the communication link is adjusted, if the original control system does not receive valid data responses from the air conditioners for an extended period, it will trigger an error mechanism. A normal air conditioner typically contains over 100 operating parameters, but the definitions, addresses, and meanings of these parameters vary significantly between different brands and models. When the new air conditioner control gateway communicates with the air conditioner, it does not need to adapt all parameters; it will only add a dozen or so parameters strongly related to the core control functions (such as temperature adjustment and operating mode switching). The daily monitoring and control of the air conditioner revolves around these core parameters; the remaining parameters are meaningless for the extended functions of the new gateway. However, the original control system will randomly read some irrelevant parameters. Although these parameters are not important, they must be responded to; otherwise, the original control system's error mechanism will still be triggered. Existing solutions often involve sending false data back to the original control system to avoid errors. However, air conditioners have numerous operating parameters, and it is impossible to predict which specific parameters the original control system will read under different operating conditions. Furthermore, the range of false data is difficult to control precisely. If the false data sent back exceeds the normal operating parameter range of the air conditioner, it will still be identified by the original control system and trigger an error, thus failing to fundamentally solve the problem. Summary of the Invention

[0005] The purpose of this invention is to provide a self-learning control gateway and method for air conditioning systems, thereby solving the problems existing in the prior art. To achieve the above objective, this invention provides the following technical solution:

[0006] In a first aspect, the present invention provides a self-learning control gateway for an air conditioning system, comprising:

[0007] The system has two communication interfaces, defined as an air conditioning interface and a central control interface. The air conditioning interface is used to establish a connection with the communication bus between the air conditioning equipment and the original control system to achieve data monitoring, and can also be used to establish a communication connection with the air conditioning equipment to achieve data interaction. The central control interface is used to establish a communication connection with the original control system to achieve data forwarding and reply.

[0008] The uplink communication interface communicates with the cloud platform to achieve unified control of the air conditioning equipment.

[0009] The processor obtains the monitored parameter address and its corresponding data through the air conditioning interface and performs average value processing; it completes the interaction of control data through the air conditioning interface and the uplink communication interface; it forwards and replies to the original control system through the centralized control interface.

[0010] The storage module is used to store the arithmetic mean data collected and calculated during the self-learning phase.

[0011] As a further technical solution, the uplink communication interface communicates with the cloud platform via 4G communication.

[0012] As a further technical solution, both of the aforementioned communication interfaces are 485 communication interfaces.

[0013] Secondly, the present invention provides a self-learning method for a control gateway, comprising the following steps:

[0014] S101. Connect the air conditioning interface of the self-learning control gateway as described in the first aspect to the communication bus between the original air conditioning control system and each air conditioning device. At this time, the self-learning control gateway and the original control system maintain parallel communication with the air conditioning devices. The original control system works normally, ensuring the uninterrupted operation of the air conditioning system.

[0015] S102. The self-learning control gateway listens to all communication data between the original control system and each air conditioning device in real time through the air conditioning interface, including the addresses corresponding to all air conditioning parameters read by the original control system and the actual air conditioning response data corresponding to each parameter address.

[0016] S103. The self-learning control gateway preprocesses all the collected data corresponding to each parameter address, calculates the arithmetic mean of each data, and stores the arithmetic mean data corresponding to each parameter address in the storage module along with the parameter address. The self-learning ends here.

[0017] As a further technical solution, the data preprocessing in step S103 includes the following steps: First, sort the data according to the numerical value, exclude the 10% largest value and the 10% smallest value, eliminate the influence of extreme abnormal data, and then calculate the arithmetic mean of the remaining 80% of valid data.

[0018] As a further technical solution, a self-learning preset duration is set, and the collected data is preprocessed after the duration ends.

[0019] As a further technical solution, the self-learning preset time is set to at least 10 minutes.

[0020] Thirdly, the present invention provides a control method for an air conditioning system, comprising the following steps:

[0021] S201. As described in the first aspect, the self-learning control gateway has completed self-learning according to the self-learning method described in the second aspect. The communication link between the original control system and the air conditioning equipment is disconnected. The air conditioning interface of the self-learning control gateway is connected to the communication line on the side of the air conditioning equipment, and the centralized control interface is connected to the communication line on the side of the original control system. At this time, the control gateway is connected in series between the original control system and the air conditioning equipment.

[0022] S202. The self-learning control gateway starts working and communicates with each air conditioning device according to the address corresponding to the preset monitoring parameters. It reads and processes the actual operating parameter data of the air conditioner in real time. For other irrelevant parameters, the self-learning control gateway does not need to read them in real time, but only responds as needed when requested by the original control system.

[0023] As a further technical solution, in step S202, when the original control system sends a parameter reading request to the air conditioning equipment, the self-learning control gateway intercepts the request and makes a judgment. If the parameter address requested by the original control system is not included in the address corresponding to the preset monitoring parameter, the self-learning control gateway retrieves the average value of the parameter corresponding to the parameter address from the storage module and replies to the original control system through the centralized control interface.

[0024] As a further technical solution, if the parameter address requested by the original control system is included in the address corresponding to the preset monitoring parameter of the self-learning control gateway, the self-learning control gateway directly extracts the actual data of the parameter it reads in real time and replies it to the original control system through the centralized control interface.

[0025] The beneficial effects of the present invention are as follows:

[0026] (1) This invention uses a link switching design of “parallel self-learning first, then serial operation” to make the self-learning control gateway the only communication relay node between the original control system and the air conditioning equipment after being connected in series. The original control system only communicates with the self-learning control gateway, and the air conditioning equipment only interacts with the original control system through the self-learning control gateway, thus completely eliminating the conflict of dual hosts occupying the bus and ensuring stable communication.

[0027] (2) In view of the characteristics of air conditioners having a large number of parameters and different brands and models, with only a dozen core parameters related to control, this invention collects all normal operating data of parameters read by the original control system through a self-learning mechanism and calculates the arithmetic average. When responding to irrelevant parameter requests, the arithmetic average is used, and when responding to core parameters, real-time data is used. Both are based on the actual operating state of the air conditioner and are bound to be within the normal parameter range. This solves the pain point of false data easily exceeding the limit and reporting errors, and there is no need to manually preset the parameter range, making it more adaptable.

[0028] (3) The control gateway self-learning method of the present invention adopts a parallel access method. The original control system works normally, the link switching process takes a short time, and it will not cause the air conditioning system to stop, thus ensuring the continuity of operation.

[0029] (4) The self-learning control gateway and method of the present invention can simplify the access process, without requiring major modifications to the original control system, thus reducing upgrade costs. Attached Figure Description

[0030] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute a limitation thereof. It should also be understood that these drawings are for simplicity and clarity and are not necessarily drawn to scale. The invention will now be described and explained with additional features and details using the drawings, wherein:

[0031] Figure 1 A schematic diagram of the self-learning control gateway structure in Embodiment 1 of the present invention is shown;

[0032] Figure 2 The diagram shows the communication link connection of the self-learning method in Embodiment 2 of the present invention;

[0033] Figure 3 The diagram shows the communication link connection of the control method in Embodiment 3 of the present invention. Detailed Implementation

[0034] The technical solutions in typical embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0035] Example 1

[0036] like Figure 1 As shown, this embodiment provides a self-learning control gateway for an air conditioning system, including a processor, two independent communication interfaces (defined as the air conditioning interface and the central control interface, respectively), an uplink communication interface, and a storage module.

[0037] In this embodiment, both communication interfaces are 485 communication interfaces, defined as the air conditioning interface and the central control interface, respectively. The air conditioning interface is used to establish a connection with the communication bus between the air conditioning equipment and the original control system to realize data monitoring, and can also be used to establish a communication connection with the air conditioning equipment to realize data interaction; the central control interface is used to establish a communication connection with the original control system to realize data forwarding and reply.

[0038] The uplink communication interface communicates with the cloud platform via 4G to achieve unified control of the air conditioning equipment. Specifically, the uplink communication interface adopts a 4G LTE Cat.1 wireless communication module, supporting all mobile, China Unicom, and China Telecom networks. It has TCP / IP protocol stack and MQTT IoT protocol support capabilities, and establishes a secure connection with the cloud platform through an SSL / TLS encrypted channel, enabling remote unified control of distributed air conditioning equipment, online firmware upgrades, and cloud storage and analysis of operating data.

[0039] The processor (MCU) obtains the monitored parameter address and its corresponding data through the air conditioning interface and performs average value processing; it completes the interaction of control data through the air conditioning interface and the uplink communication interface; and it forwards and replies to the original control system through the centralized control interface.

[0040] When the air conditioning interface of the self-learning control gateway is connected to the communication bus between the original air conditioning control system and each air conditioning device, the processor can monitor all communication data between the original control system and each air conditioning device in real time, including the addresses corresponding to all air conditioning parameters read by the original control system and the actual air conditioning response data corresponding to each parameter address. Then the processor performs average processing on the data.

[0041] The storage module is used to store the arithmetic mean data collected and calculated during the self-learning phase.

[0042] When the self-learning control gateway is connected in series between the original control system and the air conditioning equipment, forming a communication link of "original control system - self-learning control gateway - air conditioning equipment", on the one hand, the processor completes the interaction of control data through the air conditioning interface and the uplink communication interface to control the air conditioning equipment; and communicates with each air conditioning unit according to the address corresponding to the preset monitoring parameters, reading and processing the actual operating parameter data of the air conditioner in real time; on the other hand, when the original control system sends a parameter reading request to the air conditioning equipment, the processor performs logical judgment: 1. If the parameter address requested by the original control system is not included in the address corresponding to the preset monitoring parameters, the self-learning control gateway retrieves the average value of the parameter corresponding to that parameter address from the storage module and replies to the original control system through the centralized control interface; 2. If the parameter address requested by the original control system is included in the address corresponding to the preset monitoring parameters of the self-learning control gateway, the self-learning control gateway directly extracts the actual data of that parameter read in real time and replies to the original control system through the centralized control interface.

[0043] Example 2

[0044] This embodiment provides a self-learning method for a control gateway, including the following steps:

[0045] S101. Connect the air conditioning interface of the self-learning control gateway as described in Example 1 to the communication bus between the original air conditioning control system and each air conditioning device (e.g., Figure 2 As shown in the figure, at this time, the self-learning control gateway and the original control system are connected in parallel with the air conditioning equipment. The original control system works normally, ensuring the uninterrupted operation of the air conditioning system. This embodiment adopts the parallel access method, the original control system can work normally, the link switching process takes a short time, and will not cause the air conditioning system to stop, thus ensuring continuous operation.

[0046] S102. The self-learning preset duration is at least 10 minutes. The self-learning control gateway monitors all communication data between the original control system and each air conditioning unit in real time through the air conditioning interface, including the addresses corresponding to all air conditioning parameters read by the original control system and the actual response data of the air conditioning unit corresponding to each parameter address.

[0047] S103. After the self-learning preset time expires, the self-learning control gateway preprocesses all the collected data corresponding to each parameter address. First, the data is sorted by numerical value, and the 10% of the largest and 10% of the smallest values ​​are excluded to eliminate the influence of extreme abnormal data. Then, the arithmetic mean is calculated for the remaining 80% of the valid data. After calculating the arithmetic mean, the arithmetic mean data corresponding to each parameter address is associated with the parameter address and stored in the storage module. At this point, the self-learning ends.

[0048] This embodiment's self-learning method addresses the challenges of numerous air conditioner parameters, significant brand and model differences, and the fact that only a dozen or so core parameters are control-related. It uses a self-learning mechanism to collect normal operating data from all parameters read by the original control system and calculate the arithmetic mean. Since the self-learning control gateway in this embodiment can be connected in series between the original control system and the air conditioning unit, when queried by the original control system, the self-learning control gateway consistently replies with data within the normal range (the arithmetic mean, based on the actual operating state of the air conditioner, is necessarily within the normal parameter range, solving the problem of false data easily exceeding limits and causing errors), completely avoiding error problems caused by data exceeding limits.

[0049] Example 3

[0050] This embodiment provides a control method for an air conditioning system, including the following steps:

[0051] S201. As described in Example 1, the self-learning control gateway has completed self-learning according to the self-learning method described in Example 2. The communication link between the original control system and the air conditioning equipment is disconnected. The air conditioning interface of the self-learning control gateway is connected to the communication line on the side of the air conditioning equipment, and the central control interface is connected to the communication line on the side of the original control system. At this time, the control gateway is connected in series between the original control system and the air conditioning equipment, forming a communication link of "original control system - self-learning control gateway - air conditioning equipment" (e.g., Figure 3 (As shown), completely avoid dual-host conflicts;

[0052] The self-learning method in Example 2 is a prerequisite for the control method in this example. The self-learning method in Example 2 adopts "parallel self-learning", while this example adopts "serial operation". Through the link switching design of "parallel self-learning first, then serial operation", the self-learning control gateway becomes the only communication relay node between the original control system and the air conditioning equipment after being connected in series. The original control system only communicates with the self-learning control gateway, and the air conditioning equipment only interacts with the original control system through the self-learning control gateway, completely eliminating the conflict of dual hosts occupying the bus and ensuring stable communication.

[0053] S202. The self-learning control gateway starts working and communicates with each air conditioning device according to the preset monitoring parameter corresponding address (which can be understood as the preset monitoring point, i.e., the address corresponding to a dozen or so parameters that are strongly related to the core control function). It reads the actual operating parameter data of the air conditioner in real time (parameter data under the address corresponding to the monitoring parameter) and processes it. For other irrelevant parameters, the self-learning control gateway does not need to read them in real time, but only responds as needed when the original control system requests them.

[0054] When the original control system sends a parameter read request to the air conditioning equipment, the self-learning control gateway intercepts the request and makes a judgment:

[0055] If the parameter address requested by the original control system is not included in the address corresponding to the preset monitoring parameter, the self-learning control gateway retrieves the average value of the parameter corresponding to that parameter address from the storage module and replies it to the original control system through the centralized control interface.

[0056] If the parameter address requested by the original control system is included in the address corresponding to the preset monitoring parameter of the self-learning control gateway, the self-learning control gateway directly extracts the actual data of the parameter it reads in real time and replies it to the original control system through the centralized control interface.

[0057] In this embodiment, during the control process, the self-learning control gateway uses the arithmetic mean when responding to irrelevant parameter requests and real-time data when responding to core parameters. Both are based on the actual operating status of the air conditioner and are bound to be within the normal parameter range. This ensures that the core parameters and irrelevant parameters responded to by the original control system are within a reasonable range, solving the pain point of false data easily exceeding limits and causing errors, and eliminating the need for manual preset of parameter ranges.

[0058] Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make possible changes and modifications to the technical solutions of the present invention by utilizing the methods and techniques disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solutions of the present invention shall fall within the protection scope of the technical solutions of the present invention.

Claims

1. A self-learning control gateway for an air conditioning system, characterized in that, include: The system has two communication interfaces, defined as an air conditioning interface and a central control interface. The air conditioning interface is used to establish a connection with the communication bus between the air conditioning equipment and the original control system to achieve data monitoring, and can also be used to establish a communication connection with the air conditioning equipment to achieve data interaction. The central control interface is used to establish a communication connection with the original control system to achieve data forwarding and reply. The uplink communication interface communicates with the cloud platform to achieve unified control of the air conditioning equipment. The processor obtains the monitored parameter address and its corresponding data through the air conditioner interface and performs average processing. It completes the interaction of control data through the air conditioning interface and the uplink communication interface; It forwards and replies to the original control system through the centralized control interface; The storage module is used to store the arithmetic mean data collected and calculated during the self-learning phase.

2. The self-learning control gateway for an air conditioning system as described in claim 1, characterized in that, The uplink communication interface communicates with the cloud platform via 4G communication.

3. The self-learning control gateway for an air conditioning system as described in claim 1, characterized in that, Both of the aforementioned communication interfaces are 485 communication interfaces.

4. A self-learning method for controlling a gateway, characterized in that, Includes the following steps: S101. Connect the air conditioning interface of the self-learning control gateway as described in any one of claims 1-3 to the communication bus between the original air conditioning control system and each air conditioning device. At this time, the self-learning control gateway and the original control system maintain parallel communication with the air conditioning device. The original control system works normally, ensuring the uninterrupted operation of the air conditioning system. S102. The self-learning control gateway listens to all communication data between the original control system and each air conditioning device in real time through the air conditioning interface, including the addresses corresponding to all air conditioning parameters read by the original control system and the actual air conditioning response data corresponding to each parameter address. S103. The self-learning control gateway preprocesses all the collected data corresponding to each parameter address, calculates the arithmetic mean of each data, and stores the arithmetic mean data corresponding to each parameter address in the storage module along with the parameter address. The self-learning ends here.

5. The self-learning method for a control gateway as described in claim 4, characterized in that, Step S103 involves preprocessing the collected data. The process includes the following steps: First, sort the data by numerical value, exclude the 10% largest and 10% smallest values ​​to eliminate the influence of extreme outliers, and then calculate the arithmetic mean of the remaining 80% of valid data.

6. The self-learning method for a control gateway as described in claim 5, characterized in that, The self-learning process is preset for a certain duration, and the collected data is preprocessed after the duration ends.

7. The self-learning method for a control gateway as described in claim 6, characterized in that, The self-learning preset time is at least 10 minutes.

8. A control method for an air conditioning system, characterized in that, Includes the following steps: S201. The self-learning control gateway as described in any one of claims 1-3 has completed self-learning according to the self-learning method as described in any one of claims 4-7. The communication link between the original control system and the air conditioning equipment is disconnected. The air conditioning interface of the self-learning control gateway is connected to the communication line on the side of the air conditioning equipment, and the central control interface is connected to the communication line on the side of the original control system. At this time, the control gateway is connected in series between the original control system and the air conditioning equipment. S202. The self-learning control gateway starts working and communicates with each air conditioning device according to the address corresponding to the preset monitoring parameters. It reads and processes the actual operating parameter data of the air conditioner in real time. For other irrelevant parameters, the self-learning control gateway does not need to read them in real time, but only responds as needed when requested by the original control system.

9. The control method for an air conditioning system as described in claim 8, characterized in that, In step S202, when the original control system sends a parameter reading request to the air conditioning equipment, the self-learning control gateway intercepts the request and makes a judgment. If the parameter address requested by the original control system is not included in the address corresponding to the preset monitoring parameter, the self-learning control gateway retrieves the arithmetic average value of the parameter corresponding to the parameter address from the storage module and replies it to the original control system through the centralized control interface.

10. The control method for an air conditioning system as described in claim 9, characterized in that, If the parameter address requested by the original control system is included in the address corresponding to the preset monitoring parameter of the self-learning control gateway, the self-learning control gateway directly extracts the actual data of the parameter it reads in real time and replies it to the original control system through the centralized control interface.

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