CN117146369A - Heat exchange adjusting system of multi-split air conditioner - Google Patents
Heat exchange adjusting system of multi-split air conditioner Download PDFInfo
- Publication number
- CN117146369A CN117146369A CN202311343755.7A CN202311343755A CN117146369A CN 117146369 A CN117146369 A CN 117146369A CN 202311343755 A CN202311343755 A CN 202311343755A CN 117146369 A CN117146369 A CN 117146369A
- Authority
- CN
- China
- Prior art keywords
- indoor
- temperature
- control
- heat
- air
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 claims abstract description 33
- 230000001105 regulatory effect Effects 0.000 claims abstract description 16
- 238000012544 monitoring process Methods 0.000 claims abstract description 8
- 238000012546 transfer Methods 0.000 claims description 34
- 239000003507 refrigerant Substances 0.000 claims description 28
- 230000007613 environmental effect Effects 0.000 claims description 18
- 230000008569 process Effects 0.000 claims description 15
- 238000013461 design Methods 0.000 claims description 10
- 238000010438 heat treatment Methods 0.000 claims description 9
- 238000005457 optimization Methods 0.000 claims description 9
- 230000004044 response Effects 0.000 claims description 9
- 238000001816 cooling Methods 0.000 claims description 7
- 238000001704 evaporation Methods 0.000 claims description 6
- 230000008713 feedback mechanism Effects 0.000 claims description 6
- 238000009792 diffusion process Methods 0.000 claims description 5
- 238000005086 pumping Methods 0.000 claims description 5
- 238000012360 testing method Methods 0.000 claims description 5
- 230000001276 controlling effect Effects 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000008859 change Effects 0.000 claims description 3
- 230000006835 compression Effects 0.000 claims description 3
- 238000007906 compression Methods 0.000 claims description 3
- 238000009833 condensation Methods 0.000 claims description 3
- 230000005494 condensation Effects 0.000 claims description 3
- 238000004134 energy conservation Methods 0.000 claims description 3
- 230000008020 evaporation Effects 0.000 claims description 3
- 239000012530 fluid Substances 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 238000007142 ring opening reaction Methods 0.000 claims description 3
- 230000010355 oscillation Effects 0.000 claims 1
- 239000002699 waste material Substances 0.000 abstract description 6
- 230000004069 differentiation Effects 0.000 abstract 1
- 230000010354 integration Effects 0.000 abstract 1
- 230000009286 beneficial effect Effects 0.000 description 4
- 206010063385 Intellectualisation Diseases 0.000 description 2
- 238000005299 abrasion Methods 0.000 description 2
- 238000004378 air conditioning Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 238000005057 refrigeration Methods 0.000 description 2
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
Landscapes
- Air Conditioning Control Device (AREA)
Abstract
The application discloses a heat exchange regulating system of a multi-split air conditioner, which relates to the technical field of air conditioners, wherein a PID (proportion integration differentiation) algorithm and an MPC (MPC) algorithm are adopted, temperature control is realized by a model-based method, more accurate and stable temperature control is provided, temperature fluctuation and overshoot are reduced, a sensor unit in a control module monitors temperature, humidity and pressure parameters in real time, the data are used for feedback control, the real-time monitoring and the feedback control enable the system to respond to changes in time, higher performance and stability are provided, in addition, the multi-split air conditioner system adopts a Ziegler-Nichols method to optimize parameters of a PID controller, and the MPC algorithm is used for optimizing control input, so that the system can reach a steady state more quickly, and energy waste is reduced.
Description
Technical Field
The application relates to the technical field of air conditioners, in particular to a heat exchange adjusting system of a multi-split air conditioner.
Background
Multiple on-line air conditioners, also called multiple extension air conditioning systems, are commonly used in commercial buildings and large-scale houses, and unlike traditional single indoor units and outdoor units, multiple on-line systems allow to connect a plurality of indoor units to one single outdoor unit, the indoor units can be distributed in different rooms or areas, each indoor unit can be independently controlled to meet different temperature requirements of each room, and the main advantages of the system include energy saving, high flexibility, convenient installation and the like.
The heat exchange regulating system of the multi-split air conditioner is used as a key component in the system and is responsible for managing and regulating the heat exchange process in the system so as to keep the indoor temperature in a required range, and the heat exchange regulating system of the multi-split air conditioner realizes efficient air conditioning and temperature regulation by controlling the flow of the refrigerant and the operation of the indoor unit.
However, the conventional heat exchange system generally adopts a switch control or a basic temperature control algorithm, so that temperature fluctuation is high, accurate indoor temperature control is difficult to realize, the temperature fluctuation is high, the system is frequently started and stopped, additional mechanical abrasion and resource waste are caused, meanwhile, intelligent adaptability cannot be adaptively adjusted according to environmental conditions and load requirements, and a constant operation or a system which cannot adapt to load changes can cause excessive equipment abrasion, so that a heat exchange adjusting system of a multi-split air conditioner capable of reducing temperature fluctuation and overshoot is needed to solve the problems.
Disclosure of Invention
(one) solving the technical problems
Aiming at the defects of the prior art, the application provides a heat exchange adjusting system of a multi-split air conditioner, which solves the problems that the accurate indoor temperature control is difficult to realize by a switch control or basic temperature control algorithm in the prior art, and the self-adaptive adjustment can not be carried out according to the environmental conditions and the load demands.
(II) technical scheme
In order to achieve the above object, the present application provides a heat exchange adjusting system of a multi-split air conditioner, comprising:
the indoor unit module comprises an indoor heat exchanger, a fan unit and a control unit, wherein the indoor heat exchanger is used for processing and adjusting indoor air, the indoor unit absorbs or releases heat from the indoor air through the indoor heat exchanger, and the fan unit is used for sending the air subjected to heat exchange into a room;
the outdoor unit module comprises an outdoor heat exchanger, a refrigerant releases and absorbs heat in an outdoor environment, maintains the working temperature of the system, and also comprises a compressor for compressing and pumping the refrigerant;
the working medium circulation module is used for managing the circulation flow of the refrigerant in the system, evaporating and condensing the refrigerant at different environment temperatures, realizing the cooling and heating of indoor air, including compression, expansion, evaporation and condensation, and being responsible for converting and regulating the state of the refrigerant, so as to realize the control of the air temperature;
the control module comprises a sensor unit and a controller unit, is used for monitoring indoor and outdoor environment parameters, temperature and humidity, accurately adjusting the work of the indoor and outdoor units according to user settings, collecting data in real time by using the sensor, and then coordinating the components by the controller.
The application is further arranged to: the indoor unit comprises an indoor heat exchanger, and the refrigerant absorbs heat and releases heat in indoor air through the indoor heat exchanger;
the fan unit is used for sending air into the room, and improving the air flow and uniformity by controlling the speed and direction of the fan;
the sensor unit is arranged at a key position, monitors temperature, humidity and pressure, and monitors environmental conditions in real time;
the controller unit uses the sensor data to adjust the work of the indoor unit and the outdoor unit and maintain the set temperature and humidity;
the application is further arranged to: in the control module, the implementation of the temperature control step specifically includes:
step 1, modeling temperature:
describing a heat transfer process between indoor air and an external environment based on a heat transfer equation and a convection heat transfer equation;
modeling indoor air flow, and determining air mixing and temperature distribution conditions;
introducing a controller into the model to describe a target of temperature control and a feedback mechanism;
step 2, designing a control algorithm:
based on a PID control algorithm, an MPC algorithm is adopted, and control input is adjusted according to prediction of a model;
step 3, parameter optimization:
optimizing parameters of the PID controller by using a Ziegler-Nichols method;
in MPC, according to performance index, including overshoot and steady state error design objective function, find the best input;
step 4, real-time control:
collecting real-time environmental data including indoor and outdoor temperature and humidity through a sensor;
calculating a control input based on a control algorithm based on the current state and the target;
transmitting the calculated control signals to indoor and outdoor units for temperature adjustment;
step 5, feedback control:
comparing the actual temperature with the set temperature, and calculating an error;
dynamically adjusting the control input to reduce the error based on the error and feedback from the control algorithm;
the application is further arranged to: in the temperature modeling step, based on a heat conduction equation and a convection heat transfer equation, the heat transfer process between indoor air and an external environment is described specifically as follows:
describing the heat conduction process of indoor structures of walls, ceilings and floors by adopting a diffusion equation, wherein the specific heat conduction equation is as follows:
,
wherein,is the temperature distribution->Is thermal conductivity, +.>Is the Laplacian, the ∈>Is a heat source;
the heat transfer between the indoor and outdoor air is described using the convective heat transfer equation, which is expressed as:
,
wherein,is the convection heat transfer coefficient>For heat exchange surface area>And->Indoor and outdoor temperatures, respectively;
the application is further arranged to: the temperature modeling step further comprises the steps of modeling indoor air flow and determining air mixing and temperature distribution, wherein the air mixing and temperature distribution conditions are specifically as follows:
modeling the flow of indoor air by using Navier-Stokes equations, wherein the flow comprises mass, momentum and energy conservation equations;
grid division is carried out on the indoor space, the air flow area is discretized, and then a Navier-Stokes equation in a discrete form is used for solving;
simulating a temperature field and air flow by combining a temperature equation and a fluid equation to obtain indoor temperature distribution;
the application is further arranged to: the temperature modeling step further comprises the steps of introducing a controller into the model, describing a target and a feedback mechanism of temperature control, and specifically comprises the following steps:
a PID controller is introduced, and the PID controller controls outputThe calculation formula is as follows:
,
wherein,is the error between the set temperature and the actual temperature, < >>、/>And->Proportional, integral and differential gains;
the controller adjusts the work of the indoor unit and the outdoor unit in real time according to the temperature error, and realizes the steady-state and dynamic control of the set temperature;
the application is further arranged to: in the control algorithm design step, proportional gain is determined based on a PID control algorithmIntegration time->And differential time->Output of PID controller +.>The method comprises the following steps:
,
in real-time control, according to the current temperature errorAnd the output of the controller, calculate the control input after adjusting, including changing the fan speed and work of the compressor of the indoor unit;
the application is further arranged to: the said
In the control algorithm design step, an MPC algorithm is adopted to carry out model prediction control, future system response is predicted, control input is adjusted according to the predicted system response, and a cost function is as follows:
,
wherein,is a reference trace, i.e. a desired temperature profile, < >>Is a response of the system, +.>And->Is a weight matrix, < >>Is the number of steps of control prediction;
obtaining control input by solving an optimization problemThe first control input is then applied to the system, and the process is repeated for each control cycle;
the application is further arranged to: in the control algorithm design step, the optimization of the PID control parameters based on Ziegler-Nichols specifically comprises the following steps:
using a change controllerIn the manner of (2) performing a ring-opening test, increasing +.>Until the system continuously oscillates, at this timeReach critical gain->;
According to the critical gainThe method specifically comprises the following steps:
;
。
(III) beneficial effects
The application provides a heat exchange adjusting system of a multi-split air conditioner. The beneficial effects are as follows:
the heat exchange regulating system of the multi-split air conditioner provided by the application can absorb or release heat from a refrigerant in indoor air through the indoor heat exchanger to realize cooling and heating of the indoor air, meanwhile, the heat exchanged air is uniformly fed into the room through the fan unit, the speed and the direction of the fan are controlled to improve the air flow and uniformity, the outdoor unit module comprises the outdoor heat exchanger, the refrigerant releases or absorbs heat in the outdoor environment to keep the normal operation of refrigeration/heating circulation, the compressor is responsible for compressing and pumping the refrigerant to ensure the refrigerating effect of the system, and the working medium circulation module is responsible for managing the circulation flow of the refrigerant in the system to realize cooling and heating of the indoor air.
The control module is used for monitoring environmental parameters and realizing the intellectualization and the accuracy of temperature control at the same time:
firstly, describing a heat transfer process between indoor air and an external environment based on a heat conduction equation and a convection heat transfer equation in the aspect of temperature modeling, describing heat conduction of indoor structures of walls, ceilings and floors by using a diffusion equation, describing heat transfer between indoor air and outdoor air by using the convection heat transfer equation, secondly, designing a control algorithm, namely adopting a PID control algorithm and a model predictive control MPC algorithm, wherein the PID controller ensures that the indoor temperature is close to a set value by dynamically adjusting a control input according to a temperature error, and simultaneously, the MPC algorithm adjusts the control input by means of model prediction according to the prediction of the model so as to better adapt to different environmental conditions and user requirements.
In the aspect of parameter optimization, a Ziegler-Nichols method is used for optimizing parameters of a PID controller, so that a critical gain is achieved in an open loop test of the system to improve steady state performance, in an MPC algorithm, according to performance indexes including overshoot and steady state errors, an objective function is designed to find an optimal control input, energy waste is reduced, environmental data including indoor and outdoor temperatures and humidity are collected in real time through a sensor unit in a real-time control stage, based on a control algorithm, the control input is calculated according to the current state and the target and is transmitted to an indoor unit and an outdoor unit to realize temperature adjustment, the system is guaranteed to respond to environmental changes in time, stable temperature control is provided, finally, the control input is dynamically adjusted according to feedback of the error and the control algorithm through comparing actual temperature with set temperature, so that the error is reduced, and intelligent and accurate temperature control is provided.
In summary, the heat exchange regulating system of the multi-split air conditioner provided by the application adopts PID and MPC algorithms, realizes temperature control by a model-based method, provides more accurate and stable temperature control, reduces temperature fluctuation and overshoot, monitors temperature, humidity and pressure parameters in real time by a sensor unit in a control module, uses the data for feedback control, enables the system to respond to changes in time by real-time monitoring and feedback control, provides higher performance and stability, and in addition, the multi-split air conditioner system adopts Ziegler-Nichols method to optimize parameters of a PID controller and uses MPC algorithm to optimize control input, thereby being beneficial to the system to reach steady state more quickly and reducing energy waste.
The method solves the problems that in the prior art, accurate indoor temperature control is difficult to realize by a switch control or basic temperature control algorithm, and self-adaptive adjustment cannot be carried out according to environmental conditions and load requirements.
Drawings
FIG. 1 is a diagram of a heat exchange adjusting system of a multi-split air conditioner according to the present application;
fig. 2 is a flow chart of temperature control of a heat exchange adjusting system of the multi-split air conditioner.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Examples
Referring to fig. 1-2, the present application provides a heat exchange adjusting system of a multi-split air conditioner, comprising:
the indoor unit module comprises an indoor heat exchanger, a fan unit and a control unit, wherein the indoor heat exchanger is used for processing and adjusting indoor air, the indoor unit absorbs or releases heat from the indoor air through the indoor heat exchanger, and the fan unit is used for sending the air subjected to heat exchange into a room;
the indoor unit comprises an indoor heat exchanger, and the refrigerant absorbs heat and releases heat in indoor air through the indoor heat exchanger;
a fan unit for feeding air into the room, improving air flow and uniformity by controlling the speed and direction of the fan;
the outdoor unit module comprises an outdoor heat exchanger, a refrigerant releases and absorbs heat in an outdoor environment, maintains the working temperature of the system, and also comprises a compressor for compressing and pumping the refrigerant;
an outdoor heat exchanger, wherein the refrigerant releases and absorbs heat in an outdoor environment;
the working medium circulation module is used for managing the circulation flow of the refrigerant in the system, evaporating and condensing the refrigerant at different environment temperatures, realizing the cooling and heating of indoor air, including compression, expansion, evaporation and condensation, and being responsible for converting and regulating the state of the refrigerant, so as to realize the control of the air temperature;
the control module comprises a sensor unit and a controller unit, is used for monitoring indoor and outdoor environment parameters, temperature and humidity, accurately adjusting the work of the indoor and outdoor units according to user settings, collecting data in real time by using the sensor, and then coordinating the components by the controller;
the sensor unit is arranged at a key position, monitors temperature, humidity and pressure, and monitors environmental conditions in real time;
a controller unit for adjusting the operation of the indoor and outdoor units using the sensor data and maintaining the set temperature and humidity;
in the control module, the implementation of the temperature control step specifically includes:
step 1, modeling temperature:
describing a heat transfer process between indoor air and an external environment based on a heat transfer equation and a convection heat transfer equation;
modeling indoor air flow, and determining air mixing and temperature distribution conditions;
introducing a controller into the model to describe a target of temperature control and a feedback mechanism;
step 2, designing a control algorithm:
based on a PID control algorithm, an MPC algorithm is adopted, and control input is adjusted according to prediction of a model;
step 3, parameter optimization:
optimizing parameters of the PID controller by using a Ziegler-Nichols method;
in MPC, according to performance index, including overshoot and steady state error design objective function, find the best input;
step 4, real-time control:
collecting real-time environmental data including indoor and outdoor temperature and humidity through a sensor;
calculating a control input based on a control algorithm based on the current state and the target;
transmitting the calculated control signals to indoor and outdoor units for temperature adjustment;
step 5, feedback control:
comparing the actual temperature with the set temperature, and calculating an error;
dynamically adjusting the control input to reduce the error based on the error and feedback from the control algorithm;
through temperature control, intelligent and accurate temperature control is realized, self-adaptive adjustment is carried out according to different environmental conditions and user requirements, and the best performance of the system is ensured;
in the temperature modeling step, based on a heat conduction equation and a convection heat transfer equation, describing a heat transfer process between indoor air and an external environment specifically includes:
describing the heat conduction process of indoor structures of walls, ceilings and floors by adopting a diffusion equation, wherein the specific heat conduction equation is as follows:
,
wherein,is the temperature distribution->Is thermal conductivity, +.>Is the Laplacian, the ∈>Is a heat source;
the heat transfer between the indoor and outdoor air is described using the convective heat transfer equation, which is expressed as:
,
wherein,is the convection heat transfer coefficient>For heat exchange surface area>And->Indoor and outdoor temperatures, respectively;
the temperature modeling step further comprises the step of modeling indoor air flow, and determining air mixing and temperature distribution, specifically:
modeling the flow of indoor air by using Navier-Stokes equations, wherein the flow comprises mass, momentum and energy conservation equations;
grid division is carried out on the indoor space, the air flow area is discretized, and then a Navier-Stokes equation in a discrete form is used for solving;
simulating a temperature field and air flow by combining a temperature equation and a fluid equation to obtain indoor temperature distribution;
the temperature modeling step further comprises the step of introducing a controller into the model to describe a target and a feedback mechanism of temperature control, and specifically comprises the following steps:
a PID controller is introduced, and the PID controller controls outputThe calculation formula is as follows:
,
wherein,is the error between the set temperature and the actual temperature, < >>、/>And->Proportional, integral and differential gains;
the controller adjusts the work of the indoor unit and the outdoor unit in real time according to the temperature error, and realizes the steady-state and dynamic control of the set temperature;
in the control algorithm design step, proportional gain is determined based on a PID control algorithmIntegration time->And differential time->Output of PID controller +.>The method comprises the following steps:
,
in real-time control, according to the current temperature errorAnd the output of the controller, calculate the control input after adjusting, including changing the fan speed and work of the compressor of the indoor unit;
in the control algorithm design step, an MPC algorithm is adopted to carry out model prediction control, future system response is predicted, control input is adjusted according to the predicted system response, and a cost function is as follows:
,
wherein,is a reference trace, i.e. a desired temperature profile, < >>Is a response of the system, +.>And->Is a weight matrix, < >>Is the number of steps of control prediction;
obtaining control input by solving an optimization problemThe first control input is then applied to the system, and the process is repeated for each control cycle;
in the control algorithm design step, optimizing the parameters of the PID control based on Ziegler-Nichols specifically comprises the following steps:
using a change controllerIn the manner of (2) performing a ring-opening test, increasing +.>Until the system continuously oscillates, at this timeReach critical gain->;
According to the critical gainThe method specifically comprises the following steps:
;
。
in the present application, the above is combined with the above matters:
the heat exchange regulating system of the multi-split air conditioner provided by the application can absorb or release heat from a refrigerant in indoor air through the indoor heat exchanger to realize cooling and heating of the indoor air, meanwhile, the heat exchanged air is uniformly fed into the room through the fan unit, the speed and the direction of the fan are controlled to improve the air flow and uniformity, the outdoor unit module comprises the outdoor heat exchanger, the refrigerant releases or absorbs heat in the outdoor environment to keep the normal operation of refrigeration/heating circulation, the compressor is responsible for compressing and pumping the refrigerant to ensure the refrigerating effect of the system, and the working medium circulation module is responsible for managing the circulation flow of the refrigerant in the system to realize cooling and heating of the indoor air.
The control module is used for monitoring environmental parameters and realizing the intellectualization and the accuracy of temperature control at the same time:
firstly, describing a heat transfer process between indoor air and an external environment based on a heat conduction equation and a convection heat transfer equation in the aspect of temperature modeling, describing heat conduction of indoor structures of walls, ceilings and floors by using a diffusion equation, describing heat transfer between indoor air and outdoor air by using the convection heat transfer equation, secondly, designing a control algorithm, namely adopting a PID control algorithm and a model predictive control MPC algorithm, wherein the PID controller ensures that the indoor temperature is close to a set value by dynamically adjusting a control input according to a temperature error, and simultaneously, the MPC algorithm adjusts the control input by means of model prediction according to the prediction of the model so as to better adapt to different environmental conditions and user requirements.
In the aspect of parameter optimization, a Ziegler-Nichols method is used for optimizing parameters of a PID controller, so that a critical gain is achieved in an open loop test of the system to improve steady state performance, in an MPC algorithm, according to performance indexes including overshoot and steady state errors, an objective function is designed to find an optimal control input, energy waste is reduced, environmental data including indoor and outdoor temperatures and humidity are collected in real time through a sensor unit in a real-time control stage, based on a control algorithm, the control input is calculated according to the current state and the target and is transmitted to an indoor unit and an outdoor unit to realize temperature adjustment, the system is guaranteed to respond to environmental changes in time, stable temperature control is provided, finally, the control input is dynamically adjusted according to feedback of the error and the control algorithm through comparing actual temperature with set temperature, so that the error is reduced, and intelligent and accurate temperature control is provided.
In summary, the heat exchange regulating system of the multi-split air conditioner provided by the application adopts PID and MPC algorithms, realizes temperature control by a model-based method, provides more accurate and stable temperature control, reduces temperature fluctuation and overshoot, monitors temperature, humidity and pressure parameters in real time by a sensor unit in a control module, uses the data for feedback control, enables the system to respond to changes in time by real-time monitoring and feedback control, provides higher performance and stability, and in addition, the multi-split air conditioner system adopts Ziegler-Nichols method to optimize parameters of a PID controller and uses MPC algorithm to optimize control input, thereby being beneficial to the system to reach steady state more quickly and reducing energy waste.
It is to be understood that the above examples of the present application are provided by way of illustration only and not by way of limitation of the embodiments of the present application. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are desired to be protected by the following claims.
Claims (9)
1. The utility model provides a many online air conditioner's heat transfer governing system which characterized in that includes:
the indoor unit module comprises an indoor heat exchanger, a fan unit and a control unit, wherein the indoor heat exchanger is used for processing and adjusting indoor air, the indoor unit absorbs or releases heat from the indoor air through the indoor heat exchanger, and the fan unit is used for sending the air subjected to heat exchange into a room;
the outdoor unit module comprises an outdoor heat exchanger, a refrigerant releases and absorbs heat in an outdoor environment, maintains the working temperature of the system, and also comprises a compressor for compressing and pumping the refrigerant;
the working medium circulation module is used for managing the circulation flow of the refrigerant in the system, evaporating and condensing the refrigerant at different environment temperatures, realizing the cooling and heating of indoor air, including compression, expansion, evaporation and condensation, and being responsible for converting and regulating the state of the refrigerant, so as to realize the control of the air temperature;
the control module comprises a sensor unit and a controller unit, is used for monitoring indoor and outdoor environment parameters, temperature and humidity, accurately adjusting the work of the indoor and outdoor units according to user settings, collecting data in real time by using the sensor, and then coordinating the components by the controller.
2. The heat exchange adjusting system of the multi-split air conditioner according to claim 1, wherein,
the indoor unit comprises an indoor heat exchanger, and the refrigerant absorbs heat and releases heat in indoor air through the indoor heat exchanger;
the fan unit is used for sending air into the room, and improving the air flow and uniformity by controlling the speed and direction of the fan;
the sensor unit is arranged at a key position, monitors temperature, humidity and pressure, and monitors environmental conditions in real time;
the controller unit adjusts the operation of the indoor and outdoor units using the sensor data, maintaining the set temperature and humidity.
3. The heat exchange adjusting system of a multi-split air conditioner according to claim 1, wherein the control module realizes the temperature control step comprising:
step 1, modeling temperature:
describing a heat transfer process between indoor air and an external environment based on a heat transfer equation and a convection heat transfer equation;
modeling indoor air flow, and determining air mixing and temperature distribution conditions;
introducing a controller into the model to describe a target of temperature control and a feedback mechanism;
step 2, designing a control algorithm:
based on a PID control algorithm, an MPC algorithm is adopted, and control input is adjusted according to prediction of a model;
step 3, parameter optimization:
optimizing parameters of the PID controller by using a Ziegler-Nichols method;
in MPC, according to performance index, including overshoot and steady state error design objective function, find the best input;
step 4, real-time control:
collecting real-time environmental data including indoor and outdoor temperature and humidity through a sensor;
calculating a control input based on a control algorithm based on the current state and the target;
transmitting the calculated control signals to indoor and outdoor units for temperature adjustment;
step 5, feedback control:
comparing the actual temperature with the set temperature, and calculating an error;
the control input is dynamically adjusted to reduce the error based on the error and feedback from the control algorithm.
4. The heat exchange regulating system of a multi-split air conditioner according to claim 3, wherein in the temperature modeling step, a heat transfer process between indoor air and an external environment is described based on a heat transfer equation and a convection heat transfer equation, specifically:
describing the heat conduction process of indoor structures of walls, ceilings and floors by adopting a diffusion equation, wherein the specific heat conduction equation is as follows:
,
wherein,is the temperature distribution->Is thermal conductivity, +.>Is the Laplacian, the ∈>Is a heat source;
the heat transfer between the indoor and outdoor air is described using the convective heat transfer equation, which is expressed as:
,
wherein,is the convection heat transfer coefficient>For heat exchange surface area>And->Indoor and outdoor temperatures, respectively.
5. The heat exchange regulating system of a multi-split air conditioner according to claim 3, wherein the temperature modeling step further comprises modeling the indoor air flow, and determining the air mixing and temperature distribution, specifically:
modeling the flow of indoor air by using Navier-Stokes equations, wherein the flow comprises mass, momentum and energy conservation equations;
grid division is carried out on the indoor space, the air flow area is discretized, and then a Navier-Stokes equation in a discrete form is used for solving;
and combining a temperature equation and a fluid equation, simulating a temperature field and air flow, and acquiring indoor temperature distribution.
6. The heat exchange regulating system of a multi-split air conditioner according to claim 3, wherein the temperature modeling step further comprises introducing a controller into a model to describe a target and a feedback mechanism of temperature control, and specifically comprises:
a PID controller is introduced, and the PID controller controls outputThe calculation formula is as follows:
,
wherein,is the error between the set temperature and the actual temperature, < >>、/>And->Proportional, integral and differential gains;
the controller adjusts the work of the indoor unit and the outdoor unit in real time according to the temperature error, and realizes the steady-state and dynamic control of the set temperature.
7. The heat exchange adjusting system of a multi-split air conditioner according to claim 3, wherein in the control algorithm designing step, a proportional gain is determined based on a PID control algorithmIntegration time->And differential time->Output of PID controller +.>The method comprises the following steps:
,
in real-time control, according to the current temperature errorAnd an output of the controller, calculating adjusted control inputs including varying fan speeds of the indoor unit and operation of the compressor.
8. A heat exchange regulating system of a multi-split air conditioner according to claim 3, wherein the heat exchange regulating system comprises
In the control algorithm design step, an MPC algorithm is adopted to carry out model prediction control, future system response is predicted, control input is adjusted according to the predicted system response, and a cost function is as follows:
,
wherein,is a reference trace, i.e. a desired temperature profile, < >>Is a response of the system, +.>And->Is a weight matrix, < >>Is the number of steps of control prediction;
obtaining control input by solving an optimization problemThe first control input is then applied to the system and the process is repeated for each control cycle.
9. The heat exchange adjusting system of a multi-split air conditioner according to claim 3, wherein in the control algorithm designing step, optimizing parameters of the PID control based on Ziegler-Nichols specifically comprises:
using a change controllerIn the manner of (2) performing a ring-opening test, increasing +.>Until a continuous oscillation of the system occurs, at which time +.>Reach critical gain->;
According to the critical gainThe method specifically comprises the following steps:
;
。
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202311343755.7A CN117146369B (en) | 2023-10-17 | 2023-10-17 | Heat exchange adjusting system of multi-split air conditioner |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202311343755.7A CN117146369B (en) | 2023-10-17 | 2023-10-17 | Heat exchange adjusting system of multi-split air conditioner |
Publications (2)
Publication Number | Publication Date |
---|---|
CN117146369A true CN117146369A (en) | 2023-12-01 |
CN117146369B CN117146369B (en) | 2024-07-16 |
Family
ID=88902835
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202311343755.7A Active CN117146369B (en) | 2023-10-17 | 2023-10-17 | Heat exchange adjusting system of multi-split air conditioner |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN117146369B (en) |
Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104154635A (en) * | 2014-08-14 | 2014-11-19 | 河海大学常州校区 | Variable air volume room temperature control method based on fuzzy PID and prediction control algorithm |
CN107120782A (en) * | 2017-02-28 | 2017-09-01 | 上海交通大学 | A kind of HVAC system control method based on multi-user's hot comfort data |
US20180004173A1 (en) * | 2016-06-30 | 2018-01-04 | Johnson Controls Technology Company | Variable refrigerant flow system with multi-level model predictive control |
CN109451750A (en) * | 2016-06-30 | 2019-03-08 | 江森自控科技公司 | Model Predictive Control is optimized into the HVAC system being used together with distributed rudimentary air side |
US20190353384A1 (en) * | 2018-05-16 | 2019-11-21 | Mitsubishi Electric Research Laboratories, Inc. | System and Method for Thermal Comfort Control |
CN110501900A (en) * | 2019-10-08 | 2019-11-26 | 安阳师范学院 | A method of train fresh air system temperature is adjusted based on fuzzy controller |
CN110715466A (en) * | 2019-09-27 | 2020-01-21 | 同济大学 | Multi-connected air conditioning system and control method thereof |
US20220113688A1 (en) * | 2019-01-11 | 2022-04-14 | Nanyang Technological University | Method and control system for controlling building service systems |
CN114580254A (en) * | 2020-12-01 | 2022-06-03 | 天津大学 | Building indoor temperature regulation and control method and system based on model predictive control |
-
2023
- 2023-10-17 CN CN202311343755.7A patent/CN117146369B/en active Active
Patent Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104154635A (en) * | 2014-08-14 | 2014-11-19 | 河海大学常州校区 | Variable air volume room temperature control method based on fuzzy PID and prediction control algorithm |
US20180004173A1 (en) * | 2016-06-30 | 2018-01-04 | Johnson Controls Technology Company | Variable refrigerant flow system with multi-level model predictive control |
CN109451750A (en) * | 2016-06-30 | 2019-03-08 | 江森自控科技公司 | Model Predictive Control is optimized into the HVAC system being used together with distributed rudimentary air side |
CN107120782A (en) * | 2017-02-28 | 2017-09-01 | 上海交通大学 | A kind of HVAC system control method based on multi-user's hot comfort data |
US20190353384A1 (en) * | 2018-05-16 | 2019-11-21 | Mitsubishi Electric Research Laboratories, Inc. | System and Method for Thermal Comfort Control |
US20220113688A1 (en) * | 2019-01-11 | 2022-04-14 | Nanyang Technological University | Method and control system for controlling building service systems |
CN110715466A (en) * | 2019-09-27 | 2020-01-21 | 同济大学 | Multi-connected air conditioning system and control method thereof |
CN110501900A (en) * | 2019-10-08 | 2019-11-26 | 安阳师范学院 | A method of train fresh air system temperature is adjusted based on fuzzy controller |
CN114580254A (en) * | 2020-12-01 | 2022-06-03 | 天津大学 | Building indoor temperature regulation and control method and system based on model predictive control |
Non-Patent Citations (1)
Title |
---|
王长涛;郭高超;赵剑明;韩忠华;朱毅;: "粒子群优化PID在变风量空调系统中的应用", 自动化仪表, no. 02, 20 February 2018 (2018-02-20) * |
Also Published As
Publication number | Publication date |
---|---|
CN117146369B (en) | 2024-07-16 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Qi et al. | Multivariable control of indoor air temperature and humidity in a direct expansion (DX) air conditioning (A/C) system | |
EP3593056B1 (en) | Air conditioner controller | |
Lin et al. | Modeling, identification and control of air-conditioning systems | |
US10054324B2 (en) | Close humidity and temperature control method | |
EP2806223B1 (en) | Air-conditioning system that adjusts temperature and humidity | |
Qi et al. | Multivariable control-oriented modeling of a direct expansion (DX) air conditioning (A/C) system | |
CN112503746B (en) | Control method of cold source system of power station house based on machine learning and particle swarm algorithm | |
JP6324628B2 (en) | Heat pump utilization system control device and heat pump utilization system including the same | |
JP2021515177A (en) | Temperature control system and method | |
Sane et al. | Building HVAC control systems-role of controls and optimization | |
CN108168031B (en) | Fine-tuning response ventilation air conditioner control method based on air valve position resetting static pressure value | |
CN105352109A (en) | Variable-air-volume air-conditioning terminal temperature control system and method based on climate compensation | |
US20080277488A1 (en) | Method for Controlling HVAC Systems | |
JP4166051B2 (en) | Air conditioning system | |
WO2020016959A1 (en) | Air conditioning device and air conditioning method | |
Petrie et al. | Energy efficient control methods of HVAC systems for smart campus | |
CN114580254A (en) | Building indoor temperature regulation and control method and system based on model predictive control | |
CN105605748A (en) | Wind-water joint adjusting control method and system for air conditioning system | |
CN106839257A (en) | A kind of method for controlling air-conditioner | |
CN117146369B (en) | Heat exchange adjusting system of multi-split air conditioner | |
CN112628958B (en) | Air conditioner control method and air conditioner | |
US20220373206A1 (en) | Chiller controller for optimized efficiency | |
JP5318446B2 (en) | Outside air intake system | |
Liu et al. | Fuzzy pid controller design of air handling unit for constant temperature and humidity air-conditioning | |
He et al. | A Novel VAV Air Conditioning Control System Based on Swarm Intelligence |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |