CN107014037B - Intelligent air conditioner control system and air conditioner - Google Patents
Intelligent air conditioner control system and air conditioner Download PDFInfo
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- CN107014037B CN107014037B CN201710207022.9A CN201710207022A CN107014037B CN 107014037 B CN107014037 B CN 107014037B CN 201710207022 A CN201710207022 A CN 201710207022A CN 107014037 B CN107014037 B CN 107014037B
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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
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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
- F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
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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
- F24F2110/00—Control inputs relating to air properties
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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
- F24F11/65—Electronic processing for selecting an operating mode
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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
- F24F2120/00—Control inputs relating to users or occupants
- F24F2120/20—Feedback from users
Abstract
Intelligent air conditioner control system includes: the input module is used for inputting static data, wherein the static data comprises the area S of an air-conditioning room, the number N of reasonably using people in the air-conditioning room, the rated power P of the air conditioner and the standard air-conditioning power P1 corresponding to the area S of the air-conditioning room; the detection module is used for inputting dynamic data, and the dynamic data comprises the number of people actually used in the air-conditioning room N1; the identification module is used for identifying the relationship between the static data and the relationship between the dynamic data and the static data; the storage module comprises a plurality of control units, each control unit stores a control algorithm corresponding to one air conditioner running mode, and the processing module is used for calling one control unit in the storage module according to the output of the identification module and executing the control algorithm in the control unit; and the response module is used for analyzing the control algorithm and controlling the action of the air conditioner. An air conditioner is also disclosed. The invention has the advantage of high automation degree.
Description
Technical Field
The invention relates to the technical field of air conditioning equipment, in particular to an intelligent air conditioner control system and an air conditioner.
Background
The air conditioner is mainly used for manually adjusting indoor air to an optimum state. The content of the regulation mainly comprises temperature regulation, defrosting control, humidity regulation, air flow speed regulation, air cleanliness regulation and the like.
The air conditioner has certain refrigerating capacity and heating capacity, and the refrigerating capacity and the heating capacity meet the air conditioning requirements of air-conditioning rooms with certain areas. However, when purchasing an air conditioner, a user does not necessarily purchase a product of a corresponding specification strictly according to a corresponding area and power, and meanwhile, the refrigeration capacity and the heating capacity of the product of the same specification are different, so that the phenomenon of energy consumption or insufficient power occurs in actual use. Moreover, even if the user purchases the air conditioner according to the corresponding relationship, the heat preservation performance of the room, the number of the users of the air-conditioned room and the time period of each day are different, different air-conditioning requirements can be provided.
Therefore, the prior art air conditioning equipment has the problem that the capacity of the prior art air conditioning equipment is not matched with the air conditioning requirement.
Disclosure of Invention
The invention discloses an intelligent air conditioner control system, aiming at solving the problem that the capacity of an air conditioner in the prior art is not matched with the requirement of the air conditioner.
An intelligent air conditioner control system comprising:
the system comprises an input module, a data processing module and a data processing module, wherein the input module is used for inputting static data, and the static data comprises the area S of an air-conditioning room, the number N of reasonably-used people in the air-conditioning room, the rated power P of an air conditioner and the standard air-conditioning power P1 corresponding to the area S of the air-conditioning room; the detection module is used for inputting dynamic data, and the dynamic data comprises the number of people actually used in the air-conditioning room N1; an identification module to identify relationships between the static data and relationships between the dynamic data and the static data; the storage module comprises a plurality of control units, each control unit stores a control algorithm corresponding to one air conditioner running mode, and the control algorithm takes the relation between static data as a control condition or takes the relation between dynamic data and static data as a control condition; the processing module is used for calling one control unit in the storage module according to the output of the identification module and executing a control algorithm in the control unit; and the response module is used for analyzing the control algorithm and controlling the action of the air conditioner.
Further, the identification module identifies the relationship between the rated power P and the standard air conditioner power P1, if the rated power P is less than the standard air conditioner power P1, the processing module calls a corresponding control unit in the storage unit, and the response module analyzes a control algorithm in the control unit to control the air conditioner to act according to the rated maximum power; if the rated power P is larger than the standard air conditioner power P1, the processing module calls a control unit in the storage unit, and the response module analyzes a control algorithm in the control unit and controls the air conditioner to act according to a set operation mode.
Further, the identification module identifies the relationship between the number N of the reasonable users of the air-conditioning room and the number N1 of the actual users of the air-conditioning room, if the number N of the reasonable users of the air-conditioning room is greater than the number N1 of the actual users of the air-conditioning room, the processing module calls a corresponding control unit in the storage unit, and the response module analyzes a control algorithm in the control unit and controls the air conditioner to act according to a set operation mode; if the number N of the reasonable users of the air-conditioning room is less than the number N1 of the actual users of the air-conditioning room, the processing module calls a corresponding control unit in the storage unit, the response module analyzes a control algorithm in the control unit, the temperature and cold sensor is started, the air conditioner is controlled to supply air according to the detection value of the temperature and cold sensor, and the air conditioner is controlled to act according to the rated maximum power.
The energy-saving control system further comprises a timing module, wherein the timing module generates a timing interrupt signal and outputs the timing interrupt signal to the processing module, and the storage module further comprises a control unit which stores an energy-saving control algorithm; the processing module receives the timing interrupt signal, calls the control unit, and the response module analyzes the energy-saving control algorithm to control the air conditioner to operate according to an energy-saving mode.
Further, the dynamic data further comprises a real-time ambient temperature;
the system also comprises an inference module which is used for adjusting a control algorithm in the control unit according to the dynamic data to form a control strategy.
Further, the static data further comprises a standard human activity amount M, the dynamic data further comprises a real-time human activity amount detection parameter M1 of the air-conditioned room, and the identification module is used for determining the relationship between the number N1 of actually used people in the air-conditioned room and the set temperature difference and the relationship between the real-time human activity amount M1 of the air-conditioned room and the set temperature difference under the condition of the static data;
the control unit of the storage module is respectively stored with a first control algorithm established by taking the number N of reasonably using people in the air-conditioning room as a control condition and a second control algorithm established by taking the standard human activity M as a control condition;
and the reasoning module adjusts a control algorithm to form a control strategy according to the relation between the actual number of people in the air-conditioning room N1 and the set temperature difference and according to the relation between the real-time human activity detection parameter M1 and the set temperature difference.
Further, after the identification module determines the relationship between the static data and the dynamic data, each group of rooms is respectively assigned with the actual number of people using N1 and the set temperature difference, and each group of rooms has the real-time human activity detection parameter M1 and the set temperature difference, and a deterministic indicator belongs to (0, 1), wherein the deterministic indicator respectively represents the probability of executing the first control algorithm or the second control algorithm.
The system further comprises a learning module, wherein the learning module is used for storing the control strategy formed by the reasoning module.
Preferably, the real-time human activity M1 of the air-conditioned room is detected by a temperature and cold sensor; the area S of the air-conditioned room is detected by a TOF sensor, and the number of people actually used in the air-conditioned room N1 is detected by an infrared sensor.
The air conditioner control system disclosed by the invention adds a learning and judging process in the kernel of the control algorithm, continuously learns according to the actual environment in the control process, and iterates to form an optimal control scheme, so that the air conditioner capacity is optimally applied when the actual number of people in an air-conditioning room changes and the activity changes.
The invention also discloses an air conditioner, which comprises an intelligent air conditioner control system, wherein the intelligent air conditioner control system comprises: the system comprises an input module, a data processing module and a data processing module, wherein the input module is used for inputting static data, and the static data comprises the area S of an air-conditioning room, the number N of reasonably-used people in the air-conditioning room, the rated power P of an air conditioner and the standard air-conditioning power P1 corresponding to the area S of the air-conditioning room; the detection module is used for inputting dynamic data, and the dynamic data comprises the number of people actually used in the air-conditioning room N1; an identification module to identify relationships between the static data and relationships between the dynamic data and the static data; the storage module comprises a plurality of control units, each control unit stores a control algorithm corresponding to one air conditioner running mode, and the control algorithm takes the relation between static data as a control condition or takes the relation between dynamic data and static data as a control condition; the processing module is used for calling one control unit in the storage module according to the output of the identification module and executing a control algorithm in the control unit; and the response module is used for analyzing the control algorithm and controlling the action of the air conditioner.
The air conditioner disclosed by the invention has the advantage of high intelligent degree.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a block diagram schematically illustrating a first embodiment of an intelligent air conditioning control system according to the present disclosure;
FIG. 2 is a flow chart of the air conditioner operating in a heating energy-saving mode;
FIG. 3 is a flow chart of the air conditioner operating in a cooling, dehumidifying and energy-saving mode;
fig. 4 is a block diagram schematically illustrating a second embodiment of an intelligent air conditioner control system according to the present disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a block diagram of an embodiment of an intelligent air conditioner control system disclosed in the present invention is shown. Similar to the prior art, if the user selects the traditional air-conditioning mode through the remote controller, the intelligent air-conditioning control system disclosed by the invention can work in the traditional automatic control mode, namely, the rotating speed of the compressor and the flow of the refrigerant are adjusted according to the temperature difference between the ambient temperature and the set temperature, the temperature difference between the ambient temperature and the set temperature is eliminated, and the temperature of the air-conditioning room and the temperature and the humidity of the air-conditioning room are adjusted. In the invention, the mode is defined as a set operation mode, and the set operation mode is stored in a control unit of a storage module of the intelligent air-conditioning control system and can be called by a processing module at any time. In order to deal with the deviation among the parameters such as the air-conditioning room area, the air-conditioning power, the number of people using the air-conditioning room and the like, the invention makes the following improvements:
as shown in fig. 1, the intelligent air conditioner control system disclosed by the invention comprises an input module, a detection module, an identification module, a storage module, a processing module and a response module. The input module is used for inputting the air-conditioning room and basic static data which can affect the air-conditioning effect to the next-level control architecture. In the embodiment, the static data comprises the area S of the air-conditioning room, the number N of reasonably-used people in the air-conditioning room, the rated power P of the air conditioner and the standard air-conditioning power P1 corresponding to the area of the air-conditioning room. The standard air conditioner power P1 corresponding to the air conditioner room area is written into the intelligent air conditioner control system in advance according to the following numerical relationship. Preferably, the refrigerating capacity of 180W per square meter and the heating capacity of 220W per square meter correspond to each other, and the standard air-conditioning power P1 of 5-100 square meters of air-conditioning room area is written in the system in advance and forms a one-to-one correspondence relationship. The number of people reasonably using the air-conditioning rooms is N, according to the convention in the technical measures 2009 for civil architectural engineering design across the country, the number of people reasonably using the ordinary office areas and the residential areas is 0.25 per square meter (4 square meters per person), which is an ideal parameter, and the parameter is kept unchanged for the ordinary use environment. The static data also includes the area S of the air conditioned room, which is detected by the TOF sensor. Since the air conditioner is moved a little, the installation position is usually fixed, and thus the area S of the air-conditioned room is also input as a static data into the control system through the input module. And calculating the upper limit reasonable number of people N corresponding to the air-conditioning room area S according to the corresponding air-conditioning room area S, namely N =0.25 person/square meter air-conditioning room area S.
The response module is used for analyzing a control instruction output by the control system, configuring actions of a compressor and a throttling device in an air conditioner refrigeration cycle and adjusting the indoor temperature and humidity. The response module is also communicated with the terminal, and feeds back a control process to the user in real time through a user interface on the terminal. The response module and the terminal can select common WIFI communication in a wireless communication mode. The user interface is a common APP. The process of forming real-time feedback on the user interface is similar to the wireless control of prior art air conditioners. The terminal is a mobile phone, a tablet computer or other terminals with human-computer interaction interfaces. The technical scheme for establishing wireless communication between the response module and the terminal is not the protection key point of the invention and is not described herein again.
Since the air-conditioning equipment purchased by the user and the air-conditioning environment actually used may not be matched, the control system is expected to maintain the optimal temperature and humidity control scheme under the existing hardware conditions according to the actual use environment, which is also the target of the intelligent air-conditioning control system. In order to achieve the aim, the detection module of the intelligent air-conditioning control system inputs dynamic data into the system, wherein the dynamic data comprises the number of people actually used in an air-conditioning room N1. The identification module of the intelligent air conditioner control system identifies the relationship between the static data, wherein the relationship between the static data is mainly the relationship between the rated power P of the air conditioner and the standard air conditioner power P1. The identification module also identifies the relationship between the static data and the dynamic data, and the relationship between the static data and the dynamic data is mainly the relationship between the actual number of people in the air-conditioning room N1 and the reasonable number of people in the air-conditioning room N. In addition to the control units for setting the operation modes in correspondence with the storage, in the present embodiment, each control unit stores a control algorithm having a relationship between static data as a control condition, or a relationship between dynamic data and static data as a control condition. These control units are provided in the memory module. After the identification module identifies the relationship between the static data or the relationship between the static data and the dynamic data, the processing module calls a corresponding control algorithm to control.
More specifically, the identification module identifies the relationship between the rated power P and the standard air conditioner power P1, if the rated power P is less than the standard air conditioner power P1, it indicates that the air conditioner capacity has a margin, the processing module calls a corresponding control unit in the storage unit, and the response module analyzes a control algorithm in the control unit and controls the air conditioner to operate according to the rated maximum power according to the control algorithm; if the rated power P is larger than the standard air conditioner power P1, the processing module calls a control unit in the storage unit, and the response module analyzes a control algorithm in the control unit and controls the air conditioner to act according to a set operation mode according to the control algorithm.
In addition to the relationship between the rated power P and the standard air conditioner power P1, the identification module identifies the relationship between the number N of the reasonable users of the air conditioner room and the number N1 of the actual users of the air conditioner room, if the number N of the reasonable users of the air conditioner room is larger than the number N1 of the actual users of the air conditioner room, the processing module calls the corresponding control unit in the storage unit, and the response module analyzes the control algorithm in the control unit and controls the air conditioner to act according to the set operation mode. If the number N of the reasonable users of the air-conditioning room is less than the number N1 of the actual users of the air-conditioning room, the processing module calls a corresponding control unit in the storage unit, the response module analyzes a control algorithm in the control unit, the temperature and cold sensor is started, the air conditioner is controlled to supply air according to the detection value of the temperature and cold sensor, and the air conditioner is controlled to act according to the rated maximum power. The technical scheme of detecting human body feeling and supplying air by the temperature and cold sensor is disclosed in the prior art, is not the protection key point of the invention and is not described in detail herein.
By the mode, on the premise of not increasing or adjusting hardware equipment of the air conditioner, the optimal control mode of the air conditioner can be automatically obtained according to the static data and the dynamic data of the air conditioner room, manual intervention is not needed, and more ideal user experience can be obtained.
It is easy to understand that the requirement for indoor temperature adjustment is different at different time intervals of a day, and the traditional control method does not distinguish the time intervals and only carries out closed-loop control to adjust the indoor temperature according to the temperature difference between the ambient temperature and the set temperature. However, in actual use, the temperature variation law corresponding to a specific period of time is substantially maintained, for example, for lunch and dinner time, i.e. 12 o 'clock to 1 o' clock at noon, and 6 o 'clock to 7 o' clock at afternoon, the temperature generally rises significantly for a household restaurant area. Under such conditions, there may be some hysteresis in the conditioning effect if the operation is in the set operating mode. In order to solve the problem of lag in adjusting effect, the intelligent air conditioner control system provided by the invention further comprises a timing module. And generating a timing interrupt signal through a timing module. The processing module receives the timing interrupt signal, calls an energy-saving control algorithm stored in a control unit, and the response module analyzes the energy-saving control algorithm to control the air conditioner to operate according to an energy-saving mode. In the following, the above control process is described in detail, when the air conditioner operates in the heating mode, the timing module is kept in the timing state by default after being started, and the starting time of the special time period is stored in the control system. And when the display time of the clock signal is 20 minutes before the starting time of the special time period, the timing module generates a timing interrupt signal and outputs the timing interrupt signal to the processing module, and the detection module inputs the actual number of people in the air-conditioning room N1 in 20 continuous minutes. If N1 is not 0 within 2O minutes, the operation state of the air conditioner is maintained. If N1 is 0 in 20 minutes, judging whether the environment temperature is greater than or equal to 22 ℃, if the environment temperature is less than 22 ℃, maintaining the running state of the air conditioner, if the environment temperature is greater than or equal to 22 ℃, judging whether the difference between the environment temperature and the set temperature is less than or equal to 1 ℃, and if the difference is greater than 1 ℃, actively regulating and reducing the set temperature by 0.5 ℃ to maintain the running of the air conditioner. If the temperature is less than or equal to 1 ℃, the running state of the air conditioner is maintained. After running for a certain period, judging whether the ambient temperature is more than or equal to 22 ℃ again. Similarly, when operating in the cooling or dehumidifying mode, if N1 is 0 within 20 minutes, it is determined whether the ambient temperature is 27 ℃ or less, if it is greater than 27 ℃, the operating state of the air conditioner is maintained, if the ambient temperature is 27 ℃ or less, it is determined whether the difference between the ambient temperature and the set temperature is 1 ℃ or less, and if it is 1 ℃ or less, the operating state of the air conditioner is maintained. If the temperature is higher than 1 ℃, actively adjusting to raise the set temperature by 0.5 ℃ to maintain the operation of the air conditioner. After running for a certain period, judging whether the ambient temperature is less than or equal to 27 ℃ again. And exiting the energy-saving mode until the timing is finished or N1 is detected to be not 0. The energy-saving mode can ensure that the temperature of the air-conditioning room is adjusted before people move in a special time period, thereby solving the problem of hysteresis of the traditional closed-loop control.
Referring to fig. 4, a block diagram of a second embodiment of the intelligent air conditioner control system disclosed in the present invention is shown. As shown in the figure, when the rated power P of the air conditioner is greater than the standard air conditioner power P1, the capacity of the air conditioner is in a margin and can be used normally, but the uncertain number of people and the human activity in the air-conditioned room have non-quantitative and certain trend influence on the indoor temperature. For example, if the number of people in a room is large and the activity of the human body is high, the indoor ambient temperature rises. However, the ambient temperature is not in a proportional relationship with all dynamic data, and even if the ambient temperature is maintained in a proportional relationship, the magnitude of the rise of the indoor ambient temperature caused by each index is not exactly the same, and the opposite trend may occur. For example, when the number of people in a room is small, but the activity of human body is high, the influence of the number of people in the room and the activity of human body on the indoor temperature tend to be opposite. These complex situations require that the air conditioner be able to parse and calculate the sensed data, quickly and accurately make identification, control and monitoring responses, and determine the priority of control.
To achieve the above object, specifically, the static data further includes a standard human activity amount M in the conditioned room, and the actual human activity amount M1 in the conditioned room is detected by the thermal sensor. The human body activity amount M1 is obtained by estimating the surface temperature of the human body from a thermal image obtained by a thermal sensor. The control unit of the storage module stores at least two groups of control algorithms established according to static data, and the first group of control algorithms makes control conditions by taking the number N of reasonably using people in the air-conditioning room as reference. And if the number N of the reasonable users of the air-conditioning room is greater than the number N1 of the actual users of the air-conditioning room, the air conditioner operates according to a set operation mode. If the number N of the reasonable users of the air-conditioning room is less than the number N1 of the actual users of the air-conditioning room, the air conditioner supplies air according to the detection value of the temperature and cold sensor and controls the air conditioner to act according to the rated maximum power. The second group of control algorithms makes control conditions with reference to the standard human activity M in the air-conditioned room, and if the standard human activity M is greater than the actual human activity M1 in the air-conditioned room, the air conditioner operates according to the set operation mode. If the standard human body activity M is less than the actual human body activity M1 in the air-conditioning room, the air conditioner supplies air according to the detection value of the temperature and cold sensor.
The identification module is used for extracting characteristic information from the dynamic data according to the static data and determining the relationship between the static data and the dynamic data. The identification module provides a filtering algorithm for the control system of the air conditioner and extracts characteristic information from the detected signal flow of the dynamic data. When the air conditioner is actually used, the air conditioner starts to operate, the indoor temperature, the number of people and the human activity amount can continuously change, the identification module identifies the change of the human activity amount M1 in the air-conditioned room or the change of the number N1 of people actually used in the air-conditioned room, so that an ideal control algorithm is hopefully selected, and the control of the control system achieves an ideal control effect. Thus, the identification module assigns a deterministic identification t to each set of static and dynamic data identified. For example, when the area of the air-conditioned room is S and the number of people actually used in the air-conditioned room N1 is less than the upper limit reasonable number of people N, the first set of control algorithms preset in the storage module operates according to the set operation mode in order to achieve the desired temperature control effect for the room with the area S. In this state, the recognition module may consider that, when the above condition of the number of people actually used in the air-conditioned room is satisfied, that is, when the number of people is less than the reasonable number N, the probability of performing control according to the first group of control algorithms stored in the storage module is very high, and is close to 1. Because the probability is very high, the identification module gives a deterministic identifier t, t epsilon (0.9, 1) to the relationship between the area of the air-conditioning room and the number of people using the air-conditioning room N1, and the identification module can randomly allocate identifiers in the interval. IF the value is 0.95, i.e. the formula IF (N1< N) THEN (1st group, 0.95) is satisfied, the probability of executing the first set of control algorithms is 95%. Meanwhile, the dynamic data continuously feeds back the actual human activity M1 of the air-conditioned room, if the human activity M1 is greater than the standard activity M, under such a condition, the recognition module can think that the probability of air supply according to the temperature and cold sensor detection value is very high and is close to 1 when the conditions of the air-conditioned room area S and the human activity are met, and at this time, the recognition module gives a deterministic identifier t1 to the relationship between the air-conditioned room area S and the air-conditioned room human activity M1, and t1 belongs to (0.9, 1). Any given value in this range may be 0.96, i.e., satisfy the formula IF (M1> M) THEN (2nd Group, 0.96), with a probability of 96% for the second set of control algorithms to be executed, i.e., the control system begins controlling the operation of the air conditioner with the second algorithm.
After the deterministic identification is obtained, the influence of the number of people and the activity of human bodies in the air-conditioning room on the room temperature can be displayed, and meanwhile, a single group of control algorithm cannot meet the requirement of accurate control. In order to enable the control system to automatically find a group of optimal control modes, dynamic data continuously feed back the ambient temperature of the air-conditioning room at the same time, the identification module extracts the detection value and compares the detection value with the set temperature, if the ambient temperature reaches the set temperature within the set time, the inference module in the air-conditioner control system generates a control strategy, ignores the first group of control algorithms and controls according to the second group of control algorithms. And if the ambient temperature does not reach the set temperature within the set time, an inference module in the air conditioner control system generates a control strategy, operates according to the first group of control algorithms, and sets the control effect within the time. And selecting a group of control algorithms with smaller control temperature difference for control.
Meanwhile, the control system assumes that the control strategy generated at the moment is the optimal control algorithm corresponding to the dynamic data, including the actual number of people in the air-conditioning room, the actual human activity amount in the air-conditioning room and the running time, and stores the static data, the dynamic data and the control strategy corresponding to the optimal control algorithm in the learning module in a one-to-one correspondence relationship. If the input module and the detection module input the same static data and dynamic data again, the optimal control algorithm in the learning module is directly called for control.
In order to accelerate the speed of calling the optimal control algorithm from the learning module, in the process of adjusting and generating the control strategy by the inference module, uncertain identifications allocated to a first group of control algorithms and a second group of control algorithms are assigned, for example, in the adjustment period, if the inference module determines that the second group of control algorithms is better than the first group of control algorithms, the uncertain identifications allocated to the first group of control algorithms X1 (e.g., 0.9, 1) and the uncertain identifications allocated to the second group of control algorithms X1 (e.g., 0.1, 0.2) are correspondingly stored in the learning module. When the algorithm is called from the learning module, the optimal control algorithm can be directly used for control according to the uncertain identification and the adjusting period.
In the above example, the intervals in which the deterministic indications given to each set of control algorithms by the identification module are the same, i.e. the probabilities of using the two sets of control algorithms are similar. And the control effect of one set of control algorithms may be significantly better than the control effect of another set of control algorithms if available in the laboratory. Under the condition, the inference module firstly determines the probability represented by the identifier according to the prestored control effect, directly adopts a control algorithm with higher probability, and then verifies the control effect through the continuously fed back actual parameters of the air-conditioning room. If the control effect of the air-conditioned room does not reach the ideal effect within the set time, the priority of the control algorithm is changed, another set of control algorithm is called, and the control effect is verified within the same set time. The reasoning module judges the two groups of control effects simultaneously, selects a group of control algorithms with better control effects according to the control results, and records the control algorithms in the learning module by using the optimal control algorithms. If the input module and the detection module input the same static data again, the control is directly carried out by an optimal algorithm in the learning module.
According to the intelligent air conditioner control system disclosed by the embodiment, a learning and judging process is added in the kernel of the control algorithm, learning is continuously carried out according to the actual environment in the control process, an optimal control scheme is formed in an iteration mode, and the indoor environment can be kept in the optimal temperature state when the environment of an air-conditioning room changes.
The invention also discloses an air conditioner adopting the air conditioner control system, and the air conditioner provided with the air conditioner control system has the same technical effect. The air conditioner control system is described in detail with reference to the above embodiments and the drawings in the specification, and is not described herein again.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (7)
1. An intelligent air conditioner control system, comprising:
the system comprises an input module, a data processing module and a data processing module, wherein the input module is used for inputting static data, and the static data comprises the area S of an air-conditioning room, the number N of reasonably-used people in the air-conditioning room, the rated power P of an air conditioner, the standard air-conditioning power P1 corresponding to the area S of the air-conditioning room and the standard human activity M in the air-conditioning room;
the detection module is used for inputting dynamic data, and the dynamic data comprises the number of people actually using the air-conditioning room N1, the actual activity of human body M1 and the real-time environment temperature;
a storage module, the storage module comprising a plurality of control units, at least two sets of control algorithms established according to the static data being stored in the control units, wherein a first set of control algorithms comprises: if the number N of the reasonable users of the air-conditioning room is greater than the number N1 of the actual users of the air-conditioning room, the air conditioner acts according to a set operation mode; if the number N of the reasonable users of the air-conditioning room is less than the number N1 of the actual users of the air-conditioning room, the air conditioner supplies air according to the detection value of the temperature and cold sensor and controls the air conditioner to act according to the rated maximum power; the second set of control algorithms includes: if the standard human body activity M is larger than the actual human body activity M1 of the air-conditioning room, the air conditioner acts according to a set operation mode, and if the standard human body activity M is smaller than the actual human body activity M1 of the air-conditioning room, the air conditioner supplies air according to the detection value of the temperature and cold sensor;
the identification module is used for determining the relation between the number N1 of actually used people in the air-conditioning room and the set temperature difference and the relation between the real-time human activity M1 of the air-conditioning room and the set temperature difference under the condition of the static data when the rated power P of the air conditioner is larger than the standard air-conditioning power P1; respectively endowing each group of rooms with an actual number of people N1 and a set temperature difference, and each group of rooms with a certainty mark of a real-time human activity detection parameter M1 and the set temperature difference, wherein the certainty mark belongs to (0, 1), and the certainty mark represents the probability of executing a first group of control algorithms or a second group of control algorithms;
the processing module is used for calling and executing a group of control algorithms with higher probability in the first group of control algorithms or the second group of control algorithms according to the output of the identification module; and
and the response module is used for analyzing the control algorithm and controlling the action of the air conditioner.
2. The intelligent air conditioner control system of claim 1, wherein:
if the rated power P is smaller than the standard air conditioner power P1, the processing module calls a corresponding control unit in the storage unit, and the response module analyzes a control algorithm in the control unit to control the air conditioner to act according to the rated maximum power.
3. The intelligent air conditioner control system of claim 2, wherein:
the timing module generates a timing interrupt signal and outputs the timing interrupt signal to the processing module, and the storage module further comprises a control unit which stores an energy-saving control algorithm; the processing module receives the timing interrupt signal, calls the control unit, and the response module analyzes the energy-saving control algorithm to control the air conditioner to operate according to an energy-saving mode.
4. The intelligent air conditioner control system of claim 3, wherein:
the system also comprises an inference module which is used for adjusting a control algorithm in the control unit according to the dynamic data to form a control strategy.
5. The intelligent climate control system of claim 4,
the system also comprises a learning module which is used for storing the control strategy formed by the reasoning module.
6. The intelligent air-conditioning control system according to any one of claims 1 to 5,
detecting a real-time human activity detection parameter M1 of the air-conditioned room through a temperature and cold sensor; the area S of the air-conditioned room is detected by a TOF sensor, and the number of people actually used in the air-conditioned room N1 is detected by an infrared sensor.
7. An air conditioner characterized by comprising the intelligent air conditioning control system according to any one of claims 1 to 6.
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| CN112283897B (en) * | 2020-09-18 | 2022-09-16 | 海信空调有限公司 | Air conditioner and control method |
| CN112415964A (en) * | 2020-11-13 | 2021-02-26 | 佛山市顺德区美的电子科技有限公司 | Control method, control device, household appliance and storage medium |
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