CN113375311B - FCU tail end control method, device, medium and electronic equipment - Google Patents

FCU tail end control method, device, medium and electronic equipment Download PDF

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CN113375311B
CN113375311B CN202110667781.XA CN202110667781A CN113375311B CN 113375311 B CN113375311 B CN 113375311B CN 202110667781 A CN202110667781 A CN 202110667781A CN 113375311 B CN113375311 B CN 113375311B
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temperature
change rate
target
determining
temperature change
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CN113375311A (en
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陈海阳
孙一凫
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Beijing Shanggeyun Intelligent Technology Co ltd
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Beijing Shanggeyun Intelligent Technology Co ltd
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
    • F24F11/63—Electronic processing
    • F24F11/64—Electronic processing using pre-stored data
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/50—Control or safety arrangements characterised by user interfaces or communication
    • F24F11/52—Indication arrangements, e.g. displays
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/50—Control or safety arrangements characterised by user interfaces or communication
    • F24F11/54—Control or safety arrangements characterised by user interfaces or communication using one central controller connected to several sub-controllers
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/50—Control or safety arrangements characterised by user interfaces or communication
    • F24F11/56—Remote control
    • F24F11/58—Remote control using Internet communication
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/50—Control or safety arrangements characterised by user interfaces or communication
    • F24F11/61—Control or safety arrangements characterised by user interfaces or communication using timers
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/70—Control systems characterised by their outputs; Constructional details thereof
    • F24F11/72—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure
    • F24F11/74—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure for controlling air flow rate or air velocity
    • F24F11/77—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure for controlling air flow rate or air velocity by controlling the speed of ventilators
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F2110/00—Control inputs relating to air properties
    • F24F2110/10—Temperature
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F2130/00—Control inputs relating to environmental factors not covered by group F24F2110/00
    • F24F2130/10—Weather information or forecasts
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B30/00—Energy efficient heating, ventilation or air conditioning [HVAC]
    • Y02B30/70—Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating

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  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • Signal Processing (AREA)
  • Fluid Mechanics (AREA)
  • Fuzzy Systems (AREA)
  • Mathematical Physics (AREA)
  • Air Conditioning Control Device (AREA)

Abstract

The embodiment of the application discloses a method, a device, a medium and an electronic device for controlling the tail end of an FCU. The method comprises the following steps: judging whether the collection quantity of the environmental parameters and the operation parameters meets a preset condition or not by collecting the environmental parameters and the operation parameters in the operation process of the air-conditioning system, and if so, training a temperature change rate regression model according to the environmental parameters and the operation parameters; acquiring a target temperature, and determining a target change rate according to the target temperature, the indoor temperature acquired in real time and preset control delay meeting duration; and determining a control parameter at the tail end of the FCU according to the target change rate and the temperature change rate corresponding to at least one fan gear output by the temperature change rate regression model, and finishing the control of the indoor temperature. According to the technical scheme, the control on the indoor temperature can be completed according to the requirements of the user, the problems of single consideration factor, inaccurate temperature control and temperature change rate discomfort in the prior art are solved, and the indoor comfort level of the user is improved.

Description

FCU tail end control method, device, medium and electronic equipment
Technical Field
The embodiment of the application relates to the technical field of air conditioners, in particular to a method, a device, a medium and electronic equipment for controlling the tail end of an FCU.
Background
The air conditioner is a household appliance commonly used in the home at present. With the development of air conditioning technology and the higher and higher requirements of people on the comfort level of indoor temperature, the intelligent air conditioner gradually replaces the traditional air conditioner to become the first choice of people.
Currently, temperature control of most FCU air conditioning systems is accomplished through a local fan coil temperature controller. The temperature controller judges the control action to be taken according to the set target value and the collected environmental temperature value.
Because the thermal inertia of different spaces at different moments is different, the temperature cannot be accurately controlled by simply judging the adjusting direction by the indoor temperature, the indoor temperature fluctuation is large, and the indoor comfort is influenced.
Disclosure of Invention
The embodiment of the application provides a method, a device, a medium and electronic equipment for controlling the tail end of an FCU (fiber channel Unit), which can realize convenient control of an air conditioning system to adjust indoor temperature at an accurate and controllable change rate and improve indoor comfort.
In a first aspect, an embodiment of the present application provides a method for controlling an end of an FCU, where the method is performed by a controller of an FCU air conditioning system, and the method includes:
collecting environmental parameters and operating parameters in the operating process of an air conditioning system; wherein the environmental parameters include indoor temperature and outdoor temperature; the operation parameters comprise air supply temperature and fan gears;
if the collection quantity of the environmental parameters and the operation parameters meets a preset condition, training a temperature change rate regression model according to the environmental parameters and the operation parameters; the output result of the temperature change rate regression model is the temperature change rate corresponding to at least one fan gear;
acquiring a target temperature, and determining a target change rate according to the target temperature, the indoor temperature acquired in real time and a preset control delay satisfaction time;
and determining a control parameter at the tail end of the FCU according to the target change rate and the temperature change rate corresponding to at least one fan gear output by the temperature change rate regression model.
Further, determining a target change rate according to the target temperature, the indoor temperature collected in real time and the preset control delay satisfaction duration, includes:
determining target temperature variation according to the target temperature and the indoor temperature collected in real time;
and determining a target change rate according to the target temperature change and a preset control delay meeting duration.
Further, determining a control parameter of the end of the FCU according to the target change rate and the temperature change rate of at least one fan gear output by the temperature change rate regression model, including:
determining whether a temperature change rate larger than the target change rate exists in the output result of the temperature change rate regression model;
if so, determining the minimum temperature change rate as a control execution change rate from the temperature change rates larger than the target change rate;
and determining the fan gear corresponding to the control execution change rate as a control parameter of the tail end of the FCU.
Further, training a regression model of temperature change rate according to the environmental parameters and the operational parameters includes:
collecting environmental parameters and operating parameters according to a collection period, and determining the temperature variation of the sample according to a preset control period;
determining the sample temperature change rate according to the sample temperature change quantity and a preset control period;
and training a basic model based on the sample temperature change rate and the sample operation parameters to obtain a temperature change rate regression model.
Further, the operating parameters further include: the water inlet temperature, the water outlet temperature and the air return temperature;
the preset control period is 10 minutes;
the acquisition period of the environmental parameter and the operating parameter is 1 minute.
Further, the environmental parameters further include weather data;
the collection period of the weather data is 1 hour.
Further, the method further comprises:
and if the collection quantity of the environmental parameters and the operation parameters does not meet the preset condition, determining the gear of the fan according to the difference value of the target temperature and the return air temperature.
In a second aspect, an embodiment of the present application provides a control device for an FCU end, including:
a parameter acquisition module: the system is used for collecting environmental parameters and operating parameters in the operating process of the air-conditioning system; wherein the environmental parameters include indoor temperature and outdoor temperature; the operation parameters comprise air supply temperature and fan gears;
a model training module: the system comprises a temperature change rate regression model, a parameter acquisition unit, a parameter storage unit and a parameter comparison unit, wherein the temperature change rate regression model is used for training a temperature change rate regression model according to the environmental parameters and the operating parameters if the acquisition quantity of the environmental parameters and the operating parameters meets preset conditions; the output result of the temperature change rate regression model is the temperature change rate corresponding to at least one fan gear;
a rate of change determination module: the system comprises a controller, a target temperature acquisition unit, a target control delay unit and a target change rate acquisition unit, wherein the controller is used for acquiring a target temperature and determining a target change rate according to the target temperature, a real-time acquired indoor temperature and a preset control delay satisfying duration;
a control parameter determination module: and the control parameter used for determining the control parameter at the tail end of the FCU according to the target change rate and the temperature change rate corresponding to at least one fan gear output by the temperature change rate regression model.
In a third aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a control method for an end of an FCU according to an embodiment of the present application.
In a fourth aspect, an embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and executable by the processor, where the processor executes the computer program to implement the control method of the FCU according to the embodiment of the present application.
According to the technical scheme provided by the embodiment of the application, whether the collection quantity of the environmental parameters and the collection quantity of the operation parameters meet preset conditions or not is judged by collecting the environmental parameters and the operation parameters in the operation process of the air conditioning system, and if the collection quantity of the environmental parameters and the collection quantity of the operation parameters meet the preset conditions, a temperature change rate regression model is trained according to the environmental parameters and the operation parameters; acquiring a target temperature, and determining a target change rate according to the target temperature, the indoor temperature acquired in real time and a preset control delay satisfaction time; and determining a control parameter at the tail end of the FCU according to the target change rate and the temperature change rate corresponding to at least one fan gear output by the temperature change rate regression model, and finishing the control of the indoor temperature. The scheme can achieve the beneficial effects of accurate temperature control and moderate temperature change rate by the means.
Drawings
Fig. 1 is a flowchart of a control method of an FCU end according to an embodiment of the present application;
fig. 2 is a flowchart of a control method of an FCU end according to a second embodiment of the present application;
fig. 3 is a flowchart of a control method of an FCU end according to a third embodiment of the present application;
fig. 4 is a block diagram of a control device at an end of an FCU according to a fourth embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to a sixth embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some of the structures related to the present application are shown in the drawings, not all of the structures.
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the steps as a sequential process, many of the steps can be performed in parallel, concurrently or simultaneously. In addition, the order of the steps may be rearranged. The process may be terminated when its operations are completed, but could have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, subprograms, and the like.
Example one
Fig. 1 is a flowchart of a method for controlling an end of an FCU according to an embodiment of the present application, where this embodiment is applicable to a scenario where a user wishes to change an indoor temperature at a controllable change rate, and the method may be executed by a control apparatus of the end of the FCU according to an embodiment of the present application, where the apparatus may be implemented by software and/or hardware, and may be integrated into an electronic device.
As shown in fig. 1, the method for controlling the FCU end includes:
s110, collecting environmental parameters and operating parameters in the operating process of the air conditioning system; wherein the environmental parameters include indoor temperature and outdoor temperature; the operation parameters comprise air supply temperature and fan gears.
Where FCU is an abbreviation for Fan Coil Fan Coil Unit of an air conditioner. The general air-conditioning system is an air-water air-conditioning system, and the fan-coil unit mainly comprises a fan, a coil, an air filter, a regulating device and a box body. The control method of the FCU terminal may be remote control, for example, cloud remote control, where the environment data acquired by the sensor and the operation data of the device are transmitted back to the cloud, and the cloud sends a control instruction to the FCU terminal after calculation. The control method may also be a local control, for example, a button on a remote controller is used to issue an instruction to the end of the FCU, which is not limited in this embodiment.
In this embodiment, the air conditioning system generally includes a refrigeration host, a water pump, a blower, a piping system, a terminal device, and other auxiliary devices. The FCU terminal device is responsible for processing the air state by using the cold and heat from the distribution, so that the temperature, the humidity and the like of the target ambient air can meet the requirements.
The operation process of the air conditioning system is a refrigerating process or a heating process after the air conditioning system is started. The environmental parameter may be a parameter of an indoor environment or a parameter of an outdoor environment. The operation parameters are parameters of the air conditioning system in the cooling or heating process. In this embodiment, the operation parameter may be any one of the air supply temperature, the fan gear, the water inlet temperature, the water outlet temperature, and the air return temperature, or a combination of different parameters. The air supply temperature refers to the temperature of air at an air outlet of the air conditioner, and the air return temperature refers to the temperature of air pumped back into the room by the air conditioner; the gear of the fan can be divided into a high gear, a middle gear and a low gear; the water inlet temperature and the water outlet temperature are respectively the water temperature at the inlet and the outlet of a water loop in the air conditioning system. The embodiment can control the air conditioning system more accurately according to the change of the environment by acquiring various parameters, so that the indoor temperature is more comfortable.
The mode of acquiring the parameters can be that sensors with different functions, such as a temperature sensor, a humidity sensor and the like, are installed in the air conditioning system and are used for acquiring parameters such as temperature, humidity and the like in the environment.
S120, if the collection quantity of the environment parameters and the operation parameters meets preset conditions, training a temperature change rate regression model according to the environment parameters and the operation parameters; and the output result of the temperature change rate regression model is the temperature change rate corresponding to at least one fan gear.
The condition that the collection quantity meets the preset condition means that environmental parameters and operation parameters accumulated by a data collection device in the air conditioning system meet certain preset conditions. The preset condition may be a period of time. For example, if the time period is set to 24 hours in advance, the air conditioning system satisfies the preset condition after collecting data for 24 hours. The preset condition may also be a specific numerical value. For example, the number of data is set to 1 ten thousand in advance, and the air conditioning system meets the preset condition after collecting ten thousand data. In this embodiment, the preset time period or the preset data amount may be set in different environments according to user requirements, or may be a fixed value that has been set when the air conditioning system is shipped from a factory, which is not limited in this embodiment.
The temperature change rate is a rate of change of temperature, and for example, when the temperature changes from x to y within time t, the temperature change rate is (x-y)/t.
The regression model is a mathematical model for quantitatively describing the statistical relationship. It is a predictive modeling technique that studies the relationship between independent and dependent variables by establishing a relationship equation between the independent and dependent variables, the relationship equation being a so-called regression equation. The regression model needs to be trained by a large amount of data, and the collected independent variables and dependent variables are firstly input into the model, and the model learns the relationship between the independent variables and the dependent variables. The trained model can be used for prediction, and the independent variable is input into the model to obtain the predicted dependent variable. In this embodiment, the independent variable is an environmental parameter and an operating parameter, and the dependent variable is a temperature change rate corresponding to at least one fan gear, which can be understood that different fan gears have different temperature change rates. The regression techniques commonly used at present include linear regression, nonlinear regression, and logistic regression, which is not limited in this embodiment.
And S130, acquiring a target temperature, and determining a target change rate according to the target temperature, the real-time acquired indoor temperature and a preset control delay satisfying duration.
The target temperature refers to a temperature which is expected to be achieved indoors, and the target temperature can be set according to the requirements of users. The mode of obtaining the target temperature can be that a user inputs the temperature on a remote controller, the temperature data is uploaded to a cloud terminal through a communication technology, and a cloud terminal server obtains the target temperature input by the user. The preset control delay satisfaction time is how long the indoor temperature reaches the target temperature after the elapse of time, and may be 30 minutes, for example. The preset control delay satisfying time length can be set according to the requirements of users, and can also be set when the air conditioning system leaves a factory. The target rate of change is how fast the temperature change is expected to be in practice.
The real-time acquisition refers to instant acquisition, and the data acquired by the equipment has almost no time difference.
Illustratively, when a target temperature a is input by a user on a remote controller, a current indoor temperature b is obtained by a sensor in the air conditioning system, and the user wants that the indoor temperature can reach a from b within a time T, the target change rate is (a-b)/T.
And S140, determining a control parameter at the tail end of the FCU according to the target change rate and the temperature change rate corresponding to at least one fan gear output by the temperature change rate regression model.
In this embodiment, optionally, the control parameter at the end of the FCU is a fan gear. Illustratively, the target change rate is x, and the regression model outputs a high-gear pre-temperature measurement change rate of x 1 The pre-temperature measurement degree change rate of the middle gear is x 2 The pre-temperature measurement degree change rate of the low gear is x 3 . X and x are 1 、x 2 、x 3 And comparing, and selecting a proper fan gear to adjust the indoor temperature.
According to the technical scheme provided by the embodiment of the application, whether the collection quantity of the environmental parameters and the collection quantity of the operation parameters meet the preset conditions or not is judged by collecting the environmental parameters and the operation parameters in the operation process of the air-conditioning system, and if the collection quantity of the environmental parameters and the collection quantity of the operation parameters meet the preset conditions, a temperature change rate regression model is trained according to the environmental parameters and the operation parameters; acquiring a target temperature, and determining a target change rate according to the target temperature, the indoor temperature acquired in real time and a preset control delay satisfaction time; and determining a control parameter at the tail end of the FCU according to the target change rate and the temperature change rate corresponding to at least one fan gear output by the temperature change rate regression model, finishing the adjustment of the indoor temperature, overcoming the limitation of single consideration factor in the prior art, and achieving the advantages of accurate temperature control and improvement of indoor comfort.
Example two
Fig. 2 is a flowchart of a control method for an FCU end according to a second embodiment of the present application, where the present embodiment is optimized based on the foregoing embodiments. The concrete optimization is as follows: training a temperature change rate regression model according to the environmental parameters and the operating parameters, comprising: collecting environmental parameters and operating parameters according to a collection period, and determining the temperature variation of the sample according to a preset control period; determining the sample temperature change rate according to the sample temperature change quantity and a preset control period; and training a basic model based on the sample temperature change rate and the sample operation parameters to obtain a temperature change rate regression model.
As shown in fig. 2, the method of this embodiment specifically includes the following steps:
s210, collecting environmental parameters and operating parameters in the operating process of the air-conditioning system; wherein the environmental parameters include indoor temperature and outdoor temperature; the operating parameters include air supply temperature and fan gear.
And S220, collecting the environmental parameters and the operation parameters according to the collection period, and determining the temperature variation of the sample according to a preset control period.
In this embodiment, optionally, the environment parameters further include weather parameters, and the collection period of the weather parameters is 1 hour.
In this embodiment, optionally, the collection period of the environmental parameter and the operation parameter is 1 minute. In the implementation, the weather parameters are taken into sample data of the training model, the influence of weather factors on the indoor environment is considered, and the temperature change rates of different fan gears can be more accurately predicted, so that the proper gear is selected to adjust the indoor temperature.
Before enough sample data is collected, the air conditioning system determines the gear of the fan according to the target value and the return air temperature every other period, wherein the period is a preset control period. The preset control period may be different from the acquisition period, and in this embodiment, optionally, the preset control period is 10 minutes. This embodiment can be timely through setting up reasonable control cycle of predetermineeing the indoor temperature adjustment.
Illustratively, taking the indoor temperature of the environmental parameter as an example, in the present embodiment, optionally, the acquisition period is set to 1 minute, and the preset control period is set to 10 minutes. Air conditioning system at t 1 The indoor temperature collected at any moment is a 1 And the indoor temperature collected at one minute intervals is a 2 By analogy, the room temperature collected at the 10 th minute was a 10 . The amount of change in the indoor temperature during the preset control period is | a 10 -a 1 |。
And S230, determining the sample temperature change rate according to the sample temperature change amount and a preset control period.
Illustratively, the preset control period is 5 minutes, taking the indoor temperature as an example of the environmental parameter. The change amount of the indoor temperature within 5 minutes is | a 5 -a 1 If the indoor temperature changes at a rate of | a |, the indoor temperature changes at a rate of | a 5 -a 1 |/5min。
S240, training a basic model based on the sample temperature change rate and the sample operation parameters to obtain a temperature change rate regression model.
Wherein, the basic model refers to a model which is not trained by using sample data.
Specifically, the sample operation parameters are used as independent variables, the sample temperature change rate is used as a dependent variable and is input into the basic model, the model learns the relation between the dependent variable and the independent variable, the parameters of the model are obtained, and then a temperature change rate regression model is obtained. After the model is trained, the model outputs the corresponding temperature change rate after the environmental parameters or the operating parameters are input again. In this embodiment, as time increases, accumulated sample data is more and more, and the model of the pre-temperature measurement degree change rate is more and more accurate, so that the temperature control is more and more accurate.
And S250, acquiring a target temperature, and determining a target change rate according to the target temperature, the real-time acquired indoor temperature and a preset control delay meeting duration.
And S260, determining a control parameter at the tail end of the FCU according to the target change rate and the temperature change rate corresponding to at least one fan gear output by the temperature change rate regression model.
According to the technical scheme provided by the embodiment of the application, the environmental parameters and the operation parameters are collected according to the collection period, and the temperature variation of the sample is determined according to the preset control period; determining the temperature change rate of the sample according to the temperature change quantity of the sample and a preset control period; and training a basic model based on the sample temperature change rate and the sample operation parameters to finally obtain a temperature change rate regression model. According to the embodiment of the application, the temperature change rate regression model is built and trained through the means. The trained model can predict the temperature change rate of the corresponding gear according to different fan gears, the prediction result is accurate, and a user can select a fan gear corresponding to the appropriate temperature change rate to adjust the indoor temperature according to the requirement of the user on the temperature change speed.
EXAMPLE III
Fig. 3 is a flowchart of a control method for an FCU end according to a third embodiment of the present application, and the present embodiment is optimized based on the foregoing embodiments. The concrete optimization is as follows: determining a target change rate according to the target temperature, the indoor temperature acquired in real time and the preset control delay satisfaction time, wherein the target change rate comprises the following steps: determining target temperature variation according to the target temperature and the indoor temperature collected in real time; and determining a target change rate according to the target temperature change and a preset control delay meeting duration. Determining a control parameter of the tail end of the FCU according to the target change rate and the temperature change rate of at least one fan gear output by the temperature change rate regression model, wherein the control parameter comprises the following steps: determining whether a temperature change rate larger than the target change rate exists in the output result of the temperature change rate regression model; if so, determining the minimum temperature change rate as the control execution change rate from the temperature change rates larger than the target change rate; and determining the fan gear corresponding to the control execution change rate as a control parameter at the tail end of the FCU.
As shown in fig. 3, the method of this embodiment specifically includes the following steps:
s310, collecting environmental parameters and operating parameters in the operating process of the air conditioning system; wherein the environmental parameters include indoor temperature and outdoor temperature; the operating parameters include air supply temperature and fan gear.
S320, judging whether the collection quantity of the environmental parameters and the operation parameters meets preset conditions, and if so, executing S330; if not, go to S390.
And S330, collecting the environmental parameters and the operating parameters according to the collection period, and determining the temperature variation of the sample according to a preset control period.
In this embodiment, optionally, the environment parameters further include weather parameters, and the collection period of the weather parameters is 1 hour.
In this embodiment, optionally, the collection period of the environmental parameter and the operation parameter is 1 minute. In the implementation, the weather parameters are taken into sample data of the training model, the influence of weather factors on the indoor environment is considered, and the temperature change rates of different fan gears can be more accurately predicted, so that the proper gear is selected to adjust the indoor temperature.
Before enough sample data is collected, the air conditioning system determines the gear of the fan according to the target value and the return air temperature every other period, wherein the period is a preset control period. The preset control period may be different from the acquisition period, and in this embodiment, optionally, the preset control period is 10 minutes. This embodiment can be timely through setting up reasonable control cycle of predetermineeing the indoor temperature adjustment.
Illustratively, taking the indoor temperature of the environmental parameter as an example, in the present embodiment, optionally, the acquisition period is set to 1 minute, and the preset control period is set to 10 minutes. Air conditioning system at t 1 The indoor temperature collected at any moment is a 1 And the indoor temperature collected at one minute intervals is a 2 By analogy, the room temperature collected at the 10 th minute is a 10 . The amount of change in the indoor temperature during the preset control period is | a 10 -a 1 |。
And S340, determining the sample temperature change rate according to the sample temperature change amount and a preset control period.
Illustratively, the preset control period is 5 minutes, taking the indoor temperature as an example of the environmental parameter. The change amount of the indoor temperature within 5 minutes is | a 5 -a 1 If the indoor temperature changes at a rate of | a | 5 -a 1 |/5min。
And S350, training a basic model based on the sample temperature change rate and the sample operation parameters to obtain a temperature change rate regression model.
Wherein, the basic model refers to a model which is not trained by using sample data.
Specifically, the sample operation parameters are used as independent variables, the sample temperature change rate is used as a dependent variable and is input into the basic model, the model learns the relation between the dependent variable and the independent variable, the parameters of the model are obtained, and then a temperature change rate regression model is obtained. After the model is trained, the model outputs the corresponding temperature change rate after the environmental parameters or the operating parameters are input again. In this embodiment, as time increases, accumulated sample data is more and more, and the model of the pre-temperature measurement degree change rate is more and more accurate, so that the temperature control is more and more accurate.
And S360, determining the target temperature variation according to the target temperature and the indoor temperature acquired in real time.
Wherein the target temperature amount is a degree of change in the desired temperature in practice.
Illustratively, if the temperature that the user wants to reach indoors is x, and the indoor temperature collected by the device in real time is y, the target temperature variation is | y-x |.
And S370, determining a target change rate according to the target temperature change amount and the preset control delay meeting duration.
Illustratively, if it is desired in practice to vary the temperature within the chamber by Δ T over time T, the target rate of change is T/Δ T. The embodiment can control the speed of temperature change according to the requirement of the user, thereby improving the indoor comfort level of the user.
And S380, determining the minimum temperature change rate which is greater than the target change rate in the output result of the temperature change rate regression model as a control execution change rate, and determining the fan gear corresponding to the control execution change rate as a control parameter at the tail end of the FCU.
Specifically, the regression model has different output results for different gears. E.g. predicted temperature change rate at for a high gear model 1 The predicted temperature change rate of the middle gear is delta t 2 The temperature change rate is Deltat 3 . If the target change rate is Δ t, Δ t is compared with Δ t 1 、Δt 2 And Δ t 3 A comparison is made. If Δ t 2 And Δ t 3 Are both greater than Δ t, and Δ t 2 Less than Δ t 3 Then select Δ t 2 And the corresponding middle gear serves as a control parameter of the tail end of the FCU, namely the gear of the fan of the air conditioning system is set as the middle gear. The embodiment can adjust the indoor temperature according to the change rate desired by the user, and can select the appropriate change rate to prevent the indoor temperature fluctuation from being too large.
And S390, determining a fan gear according to the difference value of the target temperature and the return air temperature.
Wherein the fan gear cannot be determined by the model to adjust the indoor temperature when the air conditioning system has not collected enough sample data to train the model. The gear of the fan can be determined according to the difference value between the target temperature and the return air temperature, wherein the return air temperature represents the current indoor temperature. The gear determination code is as follows:
Figure BDA0003118001200000141
specifically, a parameter mode is set. The air conditioner has two modes of refrigeration and heating, and if the air conditioner is in the refrigeration mode, mode = -1 is carried out; if the mode is the heating mode, then mode =1. Let diff = (space target temperature-return air temperature) × mode. If diff is more than or equal to 1.5, the gear of the fan is the highest gear; if diff is more than or equal to 1.0, the gear of the fan is set to be a middle gear; if diff is more than or equal to 0.2, the gear of the air blower is in a low gear, and if diff is less than 0.2, the equipment is closed. This embodiment may be able to change the room temperature at a suitable rate of change before enough sample data has not been collected to train the model.
According to the technical scheme provided by the embodiment of the application, the target temperature variation is determined according to the target temperature and the indoor temperature acquired in real time; and determining a target change rate according to the target temperature change amount and the preset control delay meeting duration, determining the minimum temperature change rate which is greater than the target change rate in the output result of the temperature change rate regression model as a control execution change rate, and determining the fan gear corresponding to the control execution change rate as a control parameter at the tail end of the FCU. This embodiment realizes changing indoor temperature with controllable rate of change through above means, has overcome among the prior art rate of change of indoor temperature uncontrollable, the great limitation of temperature fluctuation, has reached the beneficial effect that temperature control is accurate, improve indoor comfort.
In addition, according to the technical scheme provided by the embodiment of the application, under the condition that the collection quantity of the environmental parameters and the operation parameters does not meet the preset condition, the gear of the fan is determined according to the difference value between the target temperature and the return air temperature, and the beneficial effect that the indoor temperature can be changed at a proper change rate under the condition that enough sample data are not collected to train the model is achieved.
Example four
Fig. 4 is a block diagram of a control device of an FCU end according to a fourth embodiment of the present application, where the control device can execute a control method of the FCU end according to any embodiment of the present application, and has corresponding functional modules and beneficial effects of the execution method. As shown in fig. 4, the apparatus may include:
a parameter collecting module 410, configured to collect an environmental parameter and an operating parameter during an operating process of the air conditioning system; wherein the environmental parameters include indoor temperature and outdoor temperature; the operation parameters comprise air supply temperature and fan gears;
a model training module 420, configured to train a temperature change rate regression model according to the environment parameters and the operation parameters if the collection number of the environment parameters and the operation parameters meets a preset condition; the output result of the temperature change rate regression model is the temperature change rate corresponding to at least one fan gear;
the change rate determining module 430 is configured to obtain a target temperature, and determine a target change rate according to the target temperature, a real-time acquired indoor temperature, and a preset control delay satisfaction duration;
and a control parameter determining module 440, configured to determine a control parameter at the end of the FCU according to the target change rate and a temperature change rate corresponding to the at least one fan gear output by the temperature change rate regression model.
Further, the model training module 420 includes:
and the first variable quantity determining unit is used for acquiring the environmental parameters and the operating parameters according to the acquisition period and determining the temperature variable quantity of the sample according to the preset control period.
The first change rate determining unit determines the sample temperature change rate according to the sample temperature change amount and a preset control period;
and the model obtaining unit is used for training a basic model based on the sample temperature change rate and the sample operation parameters to obtain a temperature change rate regression model.
Further, the change rate determining module 430 includes:
the second variable quantity determining unit is used for determining target temperature variable quantity according to the target temperature and the indoor temperature collected in real time;
and the second change rate determining unit is used for determining a target change rate according to the target temperature change amount and the preset control delay meeting duration.
Further, the control parameter determining module 440 is specifically configured to:
determining whether a temperature change rate larger than the target change rate exists in the output result of the temperature change rate regression model;
if so, determining the minimum temperature change rate as a control execution change rate from the temperature change rates larger than the target change rate;
and determining the fan gear corresponding to the control execution change rate as a control parameter of the tail end of the FCU.
If the collection quantity of the environmental parameters and the operation parameters does not meet the preset conditions, the device further comprises:
and a fan gear determining module 450, configured to determine a fan gear according to a difference between the target temperature and the return air temperature.
The product can execute the control method of the FCU tail end provided by the embodiment of the application, and has corresponding functional modules and beneficial effects of the execution method.
EXAMPLE five
An embodiment five of the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the computer program implements the method for controlling the FCU end according to all embodiments of the present application:
collecting environmental parameters and operating parameters in the operating process of an air-conditioning system; wherein the environmental parameters include indoor temperature and outdoor temperature; the operation parameters comprise air supply temperature and fan gears;
if the collection quantity of the environmental parameters and the operation parameters meets a preset condition, training a temperature change rate regression model according to the environmental parameters and the operation parameters; the output result of the temperature change rate regression model is the temperature change rate corresponding to at least one fan gear;
acquiring a target temperature, and determining a target change rate according to the target temperature, the indoor temperature acquired in real time and preset control delay meeting duration;
and determining a control parameter at the tail end of the FCU according to the target change rate and the temperature change rate corresponding to at least one fan gear output by the temperature change rate regression model.
Any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
EXAMPLE six
Fig. 5 is a schematic structural diagram of an electronic device according to a sixth embodiment of the present application. FIG. 5 illustrates a block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present application. The electronic device 12 shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 5, electronic device 12 is in the form of a general purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, industry Standard Architecture (ISA) bus, micro-channel architecture (MAC) bus, enhanced ISA bus, video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Electronic device 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by electronic device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and/or cache memory 32. The electronic device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, and commonly referred to as a "hard drive"). Although not shown in FIG. 5, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
Electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), with one or more devices that enable a user to interact with electronic device 12, and/or with any devices (e.g., network card, modem, etc.) that enable electronic device 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. In the electronic device 12 of the present embodiment, the display 24 is not provided as a separate body but is embedded in the mirror surface, and when the display surface of the display 24 is not displayed, the display surface of the display 24 and the mirror surface are visually integrated. Also, the electronic device 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 20. As shown, the network adapter 20 communicates with the other modules of the electronic device 12 over the bus 18. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 16 executes various functional applications and data processing by running a program stored in the system memory 28, for example, to implement a control method for an FCU end provided by an embodiment of the present invention, including: collecting environmental parameters and operating parameters in the operating process of an air conditioning system; wherein the environmental parameters include indoor temperature and outdoor temperature; the operation parameters comprise air supply temperature and fan gears; if the collection quantity of the environmental parameters and the operation parameters meets a preset condition, training a temperature change rate regression model according to the environmental parameters and the operation parameters; the output result of the temperature change rate regression model is the temperature change rate corresponding to at least one fan gear; acquiring a target temperature, and determining a target change rate according to the target temperature, the indoor temperature acquired in real time and preset control delay meeting duration; and determining control parameters at the tail end of the FCU according to the target change rate and the temperature change rate corresponding to at least one fan gear output by the temperature change rate regression model.
It is to be noted that the foregoing is only illustrative of the presently preferred embodiments and application of the principles of the present invention. It will be understood by those skilled in the art that the present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the application. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims (8)

1. A method of controlling an end of an FCU, the method performed by a controller of an FCU air conditioning system, the method comprising:
collecting environmental parameters and operating parameters in the operating process of an air-conditioning system; wherein the environmental parameters include indoor temperature and outdoor temperature; the operation parameters comprise air supply temperature and fan gears;
if the collection number of the environmental parameters and the collection number of the operation parameters meet preset conditions, collecting the environmental parameters and the operation parameters according to a collection period, and determining the temperature variation of the sample according to a preset control period;
determining the sample temperature change rate according to the sample temperature change quantity and a preset control period;
training a basic model based on the sample temperature change rate and the sample operation parameters to obtain a temperature change rate regression model; the output result of the temperature change rate regression model is the temperature change rate corresponding to at least one fan gear;
acquiring a target temperature, and determining a target change rate according to the target temperature, the indoor temperature acquired in real time and preset control delay meeting duration; the preset control delay satisfaction time period comprises the time taken for the indoor temperature to reach the target temperature; the target change rate is the degree of speed of the temperature change expected in practice;
determining whether a temperature change rate larger than the target change rate exists in the output result of the temperature change rate regression model;
if so, determining the minimum temperature change rate as the control execution change rate from the temperature change rates larger than the target change rate;
and determining the fan gear corresponding to the control execution change rate as a control parameter of the tail end of the FCU.
2. The method of claim 1, wherein determining the target rate of change based on the target temperature, the real-time collected indoor temperature, and a preset control delay satisfaction duration comprises:
determining target temperature variation according to the target temperature and the indoor temperature acquired in real time;
and determining a target change rate according to the target temperature change amount and a preset control delay meeting duration.
3. The method of claim 1, wherein the operating parameters further comprise: the water inlet temperature, the water outlet temperature and the air return temperature;
the preset control period is 10 minutes;
the collection period of the environmental parameters and the operating parameters is 1 minute.
4. The method of claim 1, wherein the environmental parameters further include weather data;
the collection period of the weather data is 1 hour.
5. The method of claim 1, further comprising:
and if the collection quantity of the environmental parameters and the operation parameters does not meet the preset condition, determining the gear of the fan according to the difference value of the target temperature and the return air temperature.
6. A control device for an end of an FCU, comprising:
the parameter acquisition module is used for acquiring environmental parameters and operating parameters in the operating process of the air conditioning system; wherein the environmental parameters include indoor temperature and outdoor temperature; the operation parameters comprise air supply temperature and fan gears;
the model training module is used for training a temperature change rate regression model according to the environmental parameters and the operation parameters if the collection quantity of the environmental parameters and the operation parameters meets preset conditions; the output result of the temperature change rate regression model is the temperature change rate corresponding to at least one fan gear;
the change rate determining module is used for acquiring a target temperature and determining a target change rate according to the target temperature, the indoor temperature acquired in real time and a preset control delay meeting duration; the preset control delay satisfaction time period comprises time taken for the indoor temperature to reach the target temperature; the target change rate is the degree of the desired temperature change in practice;
the control parameter determining module is used for determining a control parameter at the tail end of the FCU according to the target change rate and the temperature change rate corresponding to at least one fan gear output by the temperature change rate regression model;
wherein the model training module comprises: the first variable quantity determining unit is used for acquiring the environmental parameters and the operating parameters according to the acquisition period and determining the temperature variable quantity of the sample according to the preset control period;
the first change rate determining unit is used for determining the change rate of the sample temperature according to the sample temperature change amount and a preset control period;
the model obtaining unit is used for training a basic model based on the sample temperature change rate and the sample operation parameters to obtain a temperature change rate regression model;
the control parameter determination module is specifically configured to:
determining whether the temperature change rate larger than the target change rate exists in the output result of the temperature change rate regression model;
if so, determining the minimum temperature change rate as the control execution change rate from the temperature change rates larger than the target change rate;
and determining the fan gear corresponding to the control execution change rate as a control parameter at the tail end of the FCU.
7. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, is adapted to carry out the method of controlling an end of an FCU according to any one of claims 1-5.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of controlling an end of an FCU according to any of claims 1-5 when executing the computer program.
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