CN113865038B

CN113865038B - Air conditioner control method and device, air conditioner and storage medium

Info

Publication number: CN113865038B
Application number: CN202110951070.5A
Authority: CN
Inventors: 岳宝; 梁新刚; 陈群; 王顺江; 郑春元; 李斌
Original assignee: State Grid Fuxin Electric Power Supply Co; Tsinghua University; State Grid Corp of China SGCC; GD Midea Heating and Ventilating Equipment Co Ltd; State Grid Liaoning Electric Power Co Ltd
Current assignee: State Grid Fuxin Electric Power Supply Co; Tsinghua University; State Grid Corp of China SGCC; GD Midea Heating and Ventilating Equipment Co Ltd; State Grid Liaoning Electric Power Co Ltd
Priority date: 2021-08-18
Filing date: 2021-08-18
Publication date: 2023-06-30
Anticipated expiration: 2041-08-18
Also published as: CN113865038A

Abstract

The application provides an air conditioner control method, an air conditioner control device, an air conditioner and a storage medium, wherein the method comprises the following steps: acquiring current indoor parameters, outdoor parameters and human body parameters; correcting human body parameters through correction functions; the correction function is obtained by feeding back the adjustment behavior of the air conditioner by the user; calculating the current indoor comfort level according to the indoor parameters, the outdoor parameters and the corrected human body parameters; and adjusting control parameters of the air conditioner according to the current indoor comfort level and the preset comfort level corresponding to the current air conditioner mode. According to the method and the device, the human body related parameters are corrected based on the correction function adjusted by the user, so that the calculation precision of the comfort level is improved, and the comfort level preference of the user is more accurately represented. And the indoor state point can be firstly adjusted to the fastest response point, so that the comfort level requirement of a user can be rapidly met. And then the state point is adjusted to the optimal energy-saving point, so that the optimal comfort level meeting the user requirement is achieved with the lowest energy consumption.

Description

Air conditioner control method and device, air conditioner and storage medium

Technical Field

The application belongs to the technical field of electrical equipment, and particularly relates to an air conditioner control method, an air conditioner control device, an air conditioner and a storage medium.

Background

With the continuous development of society, the living standard of people is increasingly improved, and the comfort of people to indoor environment is increasingly important. Control of the indoor environment based on human comfort is an important direction of current air conditioning system development. And the requirements of different users on comfort level are different, so that the identification of the personalized comfort level of the users is a key technology for improving the control level of the air conditioning system.

At present, a PMV (Predicted Mean Vote, predicted average number of votes) model is generally used in the related art to control an air conditioning system, an environment and a human body parameter are collected mainly through a sensor, a corresponding PMV value is calculated according to the collected parameter, the calculated PMV value is compared with a preset threshold, and the running states of air supply speed, refrigeration/heating and humidification/dehumidification of the air conditioning system are adjusted according to the comparison result, so that the indoor environment achieves a comfortable state satisfactory to a user.

However, in the related art, if all parameters required by the PMV model are acquired, more sensors are required, and the equipment cost is high. And the PMV model is a general model which is obtained according to statistics and is suitable for most crowds, and cannot accurately evaluate personalized comfort of users, so that the indoor environment is difficult to achieve a comfortable state which is satisfied by users really by controlling an air conditioner.

Disclosure of Invention

According to the air conditioner control method, the air conditioner control device, the air conditioner and the storage medium, through correcting human body parameters based on the correction function adjusted by the user, the calculation accuracy of comfort is improved, the comfort preference of the user is represented more accurately, and therefore the indoor environment can be controlled to really achieve the comfortable state of user satisfaction. No new detection equipment is added in the air conditioner, the equipment cost is low, the user does not need to be inquired about human parameters, and the trouble is not caused to the user.

An embodiment of a first aspect of the present application provides an air conditioner control method, including:

acquiring current indoor parameters, outdoor parameters and human body parameters;

correcting the human body parameters through a correction function; the correction function is obtained by feeding back the adjustment behavior of the air conditioner by a user;

calculating the current indoor comfort level according to the indoor parameter, the outdoor parameter and the corrected human body parameter;

and adjusting control parameters of the air conditioner according to the current indoor comfort level and the preset comfort level corresponding to the current air conditioning mode so as to enable the indoor environment to reach the preset comfort level.

In some embodiments of the present application, the acquiring the current indoor parameter, the outdoor parameter, and the human parameter includes:

Acquiring current indoor parameters and outdoor parameters; the indoor parameters at least comprise one or more of indoor temperature, indoor humidity and indoor wind speed; the outdoor parameters at least comprise one or more of building function information, outdoor temperature, outdoor wind speed and outdoor radiation illuminance;

and calculating human body parameters of a user according to the indoor parameters and the outdoor parameters, wherein the human body parameters comprise average radiation temperature, clothes-holding quantity and metabolic rate.

In some embodiments of the present application, the calculating the human body parameter of the user according to the indoor parameter and the outdoor parameter includes:

calculating the average radiation temperature according to the indoor temperature included by the indoor parameter and the outdoor temperature included by the outdoor parameter;

calculating the clothes-putting quantity according to the outdoor temperature;

and determining the metabolic rate according to the building function information included in the outdoor parameters.

In some embodiments of the present application, the correction function is obtained by feedback of the user's conditioning behavior of the air conditioner, including:

acquiring indoor parameters, outdoor parameters, human body parameters and user regulation data of an air conditioner under a plurality of past working conditions;

and calculating to obtain a correction function according to the indoor parameter, the outdoor parameter, the human body parameter and the regulation data under each working condition.

In some embodiments of the present application, the calculating to obtain the correction function according to the indoor parameter, the outdoor parameter, the human parameter and the adjustment data under each working condition includes:

according to the indoor parameters, the outdoor parameters and the human body parameters under each working condition, respectively calculating the indoor comfort level under each working condition;

according to the adjustment data of the user on the air conditioner under each working condition, respectively calculating the correction parameters of indoor comfort level under each working condition;

the indoor comfort level under each working condition is corrected according to the correction parameters corresponding to each working condition;

according to the indoor parameters, the outdoor parameters, the human body parameters and the corrected indoor comfort level under each working condition, respectively calculating a correction function relation under each working condition;

and according to the correction function relation under each working condition, adopting a least square method to solve simultaneously to obtain a correction function.

In some embodiments of the present application, according to the adjustment data of the user on the air conditioner under each working condition, a correction parameter of indoor comfort level under each working condition is calculated, including:

according to the adjustment amplitude of each indoor parameter included in the adjustment data of the air conditioner by a user under the first working condition, respectively determining the correction coefficient corresponding to each indoor parameter through a pre-trained machine learning model; the first working condition is any working condition in each working condition; the indoor parameters comprise one or more of indoor temperature, indoor humidity and indoor wind speed;

And calculating the correction parameters of the indoor comfort degree under the first working condition according to the adjustment amplitude and the correction coefficient corresponding to each indoor parameter under the first working condition.

In some embodiments of the present application, adjusting the control parameter of the air conditioner according to the current indoor comfort level and the preset comfort level corresponding to the current air conditioner mode includes:

determining that the current indoor comfort level is not equal to the preset comfort level corresponding to the current air conditioning mode;

determining a state point set corresponding to the preset comfort level, wherein the state point set comprises at least one indoor state point, and the indoor state point comprises corresponding indoor parameters;

and selecting one indoor state point from the state point set, and adjusting the value of the current control parameter of the air conditioner to the value of the indoor parameter corresponding to the selected indoor state point.

In some embodiments of the present application, the selecting an indoor status point from the set of status points includes:

randomly selecting an indoor state point from the state point set; or,

determining the energy consumption corresponding to each indoor state point in the state point set, and selecting the indoor state point with the lowest energy consumption from the state point set as the optimal energy-saving point; or,

And determining the current indoor state point corresponding to the current indoor comfort level, respectively calculating the state difference value between each indoor state point in the state point set and the current indoor state point, and selecting the indoor state point corresponding to the minimum state difference value from the state point set as the fastest response point.

In some embodiments of the present application, the method further comprises:

and after the value of the current control parameter of the air conditioner is adjusted to the value of the indoor parameter corresponding to the fastest response point, adjusting the value of the indoor parameter corresponding to the fastest response point of the control parameter of the air conditioner to the value of the indoor parameter corresponding to the optimal energy-saving point.

In some embodiments of the present application, the method further comprises:

and if the current indoor comfort level is equal to the preset comfort level corresponding to the current air conditioning mode, and the current indoor state point corresponding to the current indoor comfort level is not equal to the optimal energy-saving point, adjusting the value of the indoor parameter corresponding to the current indoor state point to the value of the indoor parameter corresponding to the optimal energy-saving point.

In some embodiments of the present application, the adjusting the control parameter of the air conditioner according to the current indoor comfort level and the preset comfort level corresponding to the current air conditioning mode includes:

determining the fastest response point corresponding to the current indoor state point from an equal comfort level line where the preset comfort level is located according to the current indoor state point corresponding to the current indoor comfort level;

and modifying the control parameters of the air conditioner into the control parameters corresponding to the fastest response points.

In some embodiments of the present application, after modifying the control parameter of the air conditioner to the control parameter corresponding to the fastest response point, the method further includes:

determining an optimal energy-saving point from the equal comfort level line;

and adjusting control parameters of the air conditioner according to the equal comfort level line so as to adjust an indoor state point from the fastest response point to the optimal energy-saving point along the equal comfort level line.

determining an optimal energy-saving point from an equal comfort level line where the preset comfort level is located;

And modifying the control parameters of the air conditioner into the control parameters corresponding to the optimal energy-saving points.

determining that the current indoor comfort level is equal to a preset comfort level corresponding to a current air conditioning mode, and determining that a current indoor state point corresponding to the current indoor comfort level is not the optimal energy-saving point on an equal comfort level line where the preset comfort level is located;

and adjusting control parameters of the air conditioner according to the equal comfort level line so as to adjust indoor state points to the optimal energy-saving point along the equal comfort level line.

An embodiment of a second aspect of the present application provides an air conditioner control device, including:

the acquisition module is used for acquiring current indoor parameters, outdoor parameters and human body parameters;

the correction module is used for correcting the human body parameters through a correction function; the correction function is obtained by feeding back the adjustment behavior of the air conditioner by a user;

the comfort level calculating module is used for calculating the current indoor comfort level according to the indoor parameter, the outdoor parameter and the corrected human body parameter;

And the control parameter adjusting module is used for adjusting the control parameters of the air conditioner according to the current indoor comfort level and the preset comfort level corresponding to the current air conditioning mode so as to enable the indoor environment to reach the preset comfort level.

An embodiment of a third aspect of the present application provides an air conditioner, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the method described in the first aspect.

An embodiment of the fourth aspect of the present application provides a computer readable storage medium having stored thereon a computer program for execution by a processor to implement the method of the first aspect.

The technical scheme provided in the embodiment of the application has at least the following technical effects or advantages:

according to the embodiment of the application, the human body parameters are corrected through the correction function, and the user is introduced to feed back the adjustment data of the air conditioner in the calculation process of the correction function. The current indoor comfort level is calculated according to the corrected human body parameters, so that the comfort level calculation precision is improved, the calculated current indoor comfort level is closer to the actual state of the current indoor environment, and the comfort level preference of the user can be represented more accurately. Because the human body parameters are corrected through the correction function, no new detection equipment is added in the air conditioner, the equipment cost is low, the human body parameters are not required to be inquired to the user, and the trouble to the user is avoided.

Further, the control parameters of the air conditioner are adjusted according to the current indoor comfort level, and the indoor state point can be adjusted to the fastest response point so as to quickly meet the comfort level requirement of a user. The control parameters of the air conditioner can be regulated to regulate the state point to the optimal energy-saving point, so that the optimal comfort level meeting the demands of users can be achieved with the lowest energy consumption.

Additional aspects and advantages of the application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the application.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the application. Also, like reference numerals are used to designate like parts throughout the figures.

In the drawings:

FIG. 1 illustrates a computational logic diagram of a correction function based on user adjustment provided in an embodiment of the present application;

fig. 2 shows a flowchart of an air conditioner control method according to an embodiment of the present application;

FIG. 3 is a schematic diagram showing the fastest response point and the best energy saving point according to an embodiment of the present application;

FIG. 4 is another flow chart of an air conditioner control method according to an embodiment of the present application;

fig. 5 is a schematic structural diagram of an air conditioner control device according to an embodiment of the present disclosure;

fig. 6 is a schematic structural diagram of an air conditioner according to an embodiment of the present application;

fig. 7 shows a schematic diagram of a storage medium according to an embodiment of the present application.

Detailed Description

Exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

It is noted that unless otherwise indicated, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this application belongs.

An air conditioner control method, an air conditioner control device, an air conditioner and a storage medium according to embodiments of the present application are described below with reference to the accompanying drawings.

The embodiment of the application provides an air conditioner control method, which is used for acquiring indoor parameters and outdoor parameters based on existing sensors in an air conditioner system, and calculating human parameters such as average radiation temperature, clothes-wearing amount, metabolic rate and the like based on the indoor parameters and the outdoor parameters. And further, according to the above parameters, the indoor comfort level is calculated through a comfort level model, which may be a PMV model. And the comfort level model is adaptively corrected according to the adjustment behavior of the user on the air conditioning system, so that the personalized comfort level of the user can be accurately evaluated on the premise of keeping the cost of the air conditioning system unchanged, and the indoor environment can truly reach the comfortable state satisfied by the user by controlling the air conditioner.

The comfort level is corrected by the user adjusting feedback, so that the comfort level model can more accurately represent the comfort level preference of the user. Specifically, the correction function for correcting the human body parameter is calculated by the operations of steps S1 to S2, and the comfort level is calculated using the corrected human body parameter, so that the calculation accuracy of the comfort level can be improved.

S1: and acquiring indoor parameters, outdoor parameters, human body parameters and user regulation data of the air conditioner under a plurality of past working conditions.

Since the cooling/heating mode of the air conditioner is mainly determined by the outdoor temperature, the working conditions in the embodiment of the application may mainly include the outdoor temperature.

The indoor parameters comprise one or more of indoor temperature, indoor humidity, indoor wind speed, building function information and the like. The indoor temperature, the indoor humidity and the like can be detected by a sensor arranged on the indoor unit of the air conditioner, and the indoor wind speed can be converted through a windshield. The outdoor parameters include one or more of outdoor temperature, outdoor wind speed, outdoor illuminance, and the like. Parameters such as outdoor temperature, outdoor wind speed, outdoor illuminance and the like can be detected and acquired by a sensor arranged on the outdoor unit of the air conditioner. The building function information is used to indicate a function of a building in which the air conditioner is installed, for example, the building function information may indicate that the function of the building in which the air conditioner is installed is an office building, a residence, a school, a mall, a laboratory, or the like. The building function information can be preset in the air conditioner or obtained through the internet of things function of the air conditioner, for example, building function information corresponding to a building for installing the air conditioner is set in a debugging mode of the air conditioner.

In the embodiment of the application, the external work information and the motion quantity information of the user under each working condition can be obtained, and the external work information and the motion quantity information can be preset in the air conditioner. The external acting information and the motion quantity information of the user can be detected by moving wearing equipment such as a bracelet and the like, and then the detected external acting information and motion quantity information are sent to the air conditioner through the wearing equipment.

The user adjustment data includes the user's adjustment frequency, adjustment amplitude, adjustment value, etc. for temperature, wind speed, and humidity. The user adjusts the temperature, wind speed or humidity and other control parameters of the air conditioner through a remote controller, a control panel on the air conditioner, an application program installed on a mobile phone or a computer and other equipment, and the air conditioner can record the adjusting data of the user on the adjusting frequency, the adjusting amplitude, the specific adjusting value and the like of the control parameters.

In the past, in the process of using the air conditioner by a user, indoor parameters and outdoor parameters under a plurality of working conditions and adjustment data of the user on the air conditioner are acquired. For example, the indoor temperature, the outdoor temperature, and the user adjustment data when the outdoor temperature is 37 ℃, the indoor temperature, the outdoor temperature, and the user adjustment data when the outdoor temperature is-5 ℃, and the like are recorded.

After the indoor parameters and the outdoor parameters under each working condition are obtained, the human body parameters of the user under each working condition are calculated according to the indoor parameters and the outdoor parameters under each working condition, wherein the human body parameters comprise average radiation temperature, clothes-wearing quantity and metabolic rate. For each working condition, the process of calculating the human body parameters is the same. The following specifically describes a first working condition as an example, where the first working condition is any working condition of the plurality of working conditions recorded in step S1.

Specifically, according to the indoor temperature included in the indoor parameter and the outdoor temperature included in the outdoor parameter under the first working condition, the average radiation temperature under the first working condition is calculated through the formula (1).

Tr＝αT ₁ +(1-α)T ₄ …(1)

At the publicIn formula (1), tr is the average radiation temperature, T ₁ Is the indoor temperature, T ₄ Is the outdoor temperature, α is a coefficient related to the structural parameters of the wall and the thermal properties.

And calculating the clothes amount of the user according to the outdoor temperature. Specifically, the calculation is performed by using the formula (2).

In the formula (2), clo is the clothes amount, T ₄ | _@6am Is the outdoor temperature of 6 a.m.

The metabolic rate of the user is determined according to the building function information included in the outdoor parameters. Specifically, if the building function information indicates that the function of the building in which the air conditioner is installed is an office building, a house, or a school, it is determined that the metabolic rate of the user is a first preset value, which may be 1.2met or 1.3met, or the like. If the building function information indicates a mall or laboratory, the metabolic rate of the user is determined to be a second preset value, which may be 1.6met or 1.7met, etc. The metabolism rate of the user can also be determined by detecting the quantity information of the user motion through a wearable device such as a mobile bracelet, then sending the detected quantity information of the motion to an air conditioner through the wearable device, and determining the metabolism rate of the user according to the quantity information of the user motion.

To ensure the accuracy of the correction function calculated in step S2, a large amount of data may be recorded in this step, and if the data corresponding to any working condition is referred to as a record, 400, 1000 or more pieces of data may be recorded to provide more samples for calculating the correction function.

S2: and calculating to obtain a correction function according to the indoor parameters, the outdoor parameters, the human body parameters and the adjustment data of the user on the air conditioner under each working condition.

The process of determining the correction function is the same for each operating condition. Any one of the plurality of working conditions recorded in step S1 is taken as an example for explanation, and for convenience of description, any one of the plurality of working conditions recorded in step S1 is referred to as a first working condition.

After the human body parameters of the user under the first working condition are calculated in the mode in the step S1, the indoor comfort level under the first working condition is calculated according to the indoor parameters, the outdoor parameters and the human body parameters under the first working condition. In addition to the above-mentioned parameters, the user' S external work information may be added when calculating the indoor comfort, and the external work information may be set to 0 or acquired in the manner described in step S1.

The embodiment of the application can calculate the comfort level through a PMV model, and particularly calculate the indoor comfort level under the first working condition through a formula (3).

PMV＝(0.303e ^-0.036M +0.028){M-W-3.05×10 ^-3 ×[5733-6.99×M-W-Pa-0.42×M-W-58.15-1.72×10-5M5867-Pa-0.0014M×34-ta-3.96×10 ^-8 f _cl [(t _cl +273.15) ⁴ -(t _r +273.15) ⁴ ]-f _cl h _cl (t _cl -t _a )…(3)

Wherein t is _cl ＝35.7-0.028(M-W)-I _cl {3.96×10 ^-8 f _cl h _cl [(t _cl +273.15) ⁴ -tr+273.154+fclhcl(tcl-ta)；

h _cl ＝max(2.38×(t _cl -t _a ) ^0.25 ，12.1×v _a ^0.5 )；

In the above formula (3), M is a metabolic rate; w is external work doing information; p (P) _a The partial pressure of water vapor is calculated according to indoor humidity; t is t _a Is the indoor temperature; i _cl The clothes amount is the clothes amount; f (f) _cl Is the thermal resistance of the clothing according to the clothing quantity I _cl Calculating to obtain; t is t _cl Human body surface temperature; t is t _r Is the average radiation temperature; h is a _cl Is the convective heat transfer coefficient; v _a Is the indoor wind speed.

And (3) calculating the indoor comfort degree under the first working condition through the formula (3), wherein the indoor comfort degree is the theoretical comfort degree under the first working condition. Because the human body parameters are calculated according to the indoor parameters and the outdoor parameters, certain errors exist, and then errors are introduced in the calculation of indoor comfort level. Therefore, the embodiment of the application corrects the human body parameters, and particularly corrects the indoor comfort level based on the user adjustment feedback. The corrected indoor comfort is then used to determine a correction function for the human body parameter.

Firstly, according to the adjustment data of a user on an air conditioner under a first working condition, calculating a correction parameter of indoor comfort under the first working condition. Specifically, when the user adjusts the temperature, humidity up or wind speed down, the comfort theoretical value is corrected up. When the user adjusts the temperature, humidity or wind speed downwards, the comfort theoretical value is corrected downwards. According to the method, according to the adjusting amplitude of each indoor parameter included in the adjusting data of the air conditioner by the user under the first working condition, correction coefficients corresponding to each indoor parameter are respectively determined through a pre-trained machine learning model; each indoor parameter comprises one or more of indoor temperature, indoor humidity and indoor wind speed; and calculating the correction parameters of indoor comfort level under the first working condition according to the adjustment amplitude and the correction coefficient corresponding to each indoor parameter under the first working condition.

Specifically, the mapping relation between different regulation data and correction coefficients corresponding to the indoor temperature, the indoor humidity and the indoor wind speed respectively is calculated through a pre-trained machine learning model. According to the regulation data of the user on the air conditioner under the first working condition, the correction coefficients corresponding to the indoor temperature, the indoor humidity and the indoor wind speed are respectively determined through a machine learning model, and then the correction parameters of the indoor comfort degree under the first working condition are calculated through a formula (4).

ΔPMV＝β ₁ ×ΔT+β ₂ ×ΔH+β ₃ ×ΔV…(4)

In formula (4), Δpmv is a correction parameter of comfort; beta ₁ The correction coefficient corresponding to the indoor temperature is the partial derivative of the PMV to the indoor temperature; delta T is the regulating amplitude of indoor temperature, namely the difference between the temperature values before and after regulation; beta ₂ The correction coefficient corresponding to the indoor humidity is the partial derivative of the PMV to the indoor humidity; ΔH is the indoor humidity regulating widthA degree; beta ₃ The correction coefficient of the indoor wind speed is the partial derivative of the PMV to the indoor wind speed; deltaV is the adjustment amplitude of the indoor wind speed. It is noted that one or more of the parameters Δt, Δh, and Δv may be 0.

In equation (3), the calculation of PMV is complex, and it is difficult to explicitly solve the partial derivatives of PMV on each adjustment parameter, namely beta ₁ 、β ₂ And beta ₃ . The calculations are thus performed here using a machine learning method, in particular: calculating the change condition of PMV after micro-adjustment of temperature, humidity or wind speed under a plurality of working conditions by a central difference method; and taking the indoor parameters, the outdoor parameters and the human body parameters under each working condition as input, taking the adjusted PMV change as output, and training a machine learning model, thereby obtaining the mapping relation between different adjustment data and correction coefficients corresponding to the temperature, the humidity and the wind speed respectively. The preset machine learning algorithm can be an artificial neural network, a support vector machine, a random forest and other algorithms. Taking a preset machine learning algorithm as an example of a support vector machine for explanation, RBF (Radial Basis Function ) can be selected as a kernel function in the support vector machine, average absolute error and average absolute percentage error are taken as evaluation indexes, and insensitive coefficients, punishment coefficients and width coefficients in the support vector machine are subjected to parameter adjustment so as to ensure fitting precision and fitting speed of machine learning. The phenomenon of over fitting in the training process is avoided through cross validation. The insensitive coefficient, the punishment coefficient and the width coefficient are three control parameters in the machine learning, and the fitting precision and the fitting speed of the machine learning can be adjusted by controlling the three parameters.

After the correction parameters are calculated in the above manner, the indoor comfort level under the first working condition is corrected according to the correction parameters, and the correction parameters can be added on the basis of the indoor comfort level under the first working condition. After the indoor comfort level is corrected, a correction function relation under the first working condition is calculated according to the indoor parameter, the outdoor parameter, the human body parameter and the corrected indoor comfort level under the first working condition. By the method, a correction function relation under each working condition is calculated, and a least square method is adopted for simultaneous solving to obtain a correction function.

Taking the average radiation temperature, the clothes-coating amount and the metabolic rate as examples, the model form for correcting the parameters is as follows:

wherein, gamma ₁₁ 、γ ₂ And gamma ₃ The partial derivatives of PMV to Clo, tr and M are calculated by the same method as beta ₁ 、β ₂ And beta ₃ ；a ₁ 、b ₁ The correction function coefficient of the clothes quantity; a, a ₂ 、b ₂ A correction function coefficient for the average radiation temperature; a, a ₃ 、b ₃ Is a modified function coefficient of metabolic rate.

Six unknown quantities are in the formula (5), and when the working condition is equal to six, the correction function coefficients can be calculated immediately by combining the six correction function relation formulas; when the working conditions are more than six, the equation set becomes an overdetermined equation, and at the moment, the least square method is adopted to calculate the approximate solution of the correction function coefficients.

The indoor comfort level model after correction is obtained through the method, and the indoor comfort level is calculated by using the model before the next correction. When the current indoor comfort level is determined to be unequal to the preset comfort level corresponding to the current air conditioning mode, the control parameters of the air conditioner are modified to the control parameters corresponding to the preset comfort level, and when a plurality of combinations of the control parameters exist, the most energy-saving combination is preferred.

The logic diagram is calculated based on a correction function adjusted by a user as shown in fig. 1, wherein the indoor temperature, the indoor humidity and the indoor wind speed belong to indoor parameters, the outdoor temperature belongs to outdoor parameters, and the average radiation temperature, the dressing amount and the metabolic rate belong to human body parameters. The comfort level calculation unit is used for calculating the comfort level through the above formula (3). The user adjustment feedback means correcting the comfort theoretical value calculated by the comfort calculating unit according to the adjustment data of the user, and obtaining a comfort correction value. And then calculating an average radiation temperature correction function, a dressing volume correction function and a metabolic rate correction function according to the comfort level correction value.

After the correction function is obtained, the operation of the air conditioner can be controlled by the method shown in fig. 2, so that the indoor environment reaches the comfortable state satisfied by the user. As shown in fig. 2, the method specifically includes the following steps:

Step 101: and acquiring current indoor parameters, outdoor parameters and human body parameters.

And acquiring current indoor parameters such as indoor temperature, indoor humidity, indoor wind speed and the like through a sensor arranged on the indoor unit. And acquiring preset building function information corresponding to a building on which the air conditioner is installed, wherein the indoor parameters further comprise the building function information. And acquiring the current outdoor parameters such as the outdoor temperature, the outdoor wind speed and the like through a sensor arranged on the outdoor unit.

And calculating human body parameters of the user according to the current indoor parameters and the outdoor parameters. Specifically, the average radiation temperature is calculated by the above formula (1) according to the indoor temperature included in the indoor parameter and the outdoor temperature included in the outdoor parameter. According to the current outdoor temperature, the clothes amount is calculated through the formula (2). And determining the metabolic rate according to the building function information included in the indoor parameters. If the building function information indicates that the function of the building in which the air conditioner is installed is an office building, a house, or a school, it is determined that the metabolic rate of the user is a first preset value, which may be 1.2met or 1.3met, or the like. If the building function information indicates a mall or laboratory, determining that the metabolic rate of the user is a second preset value, wherein the second preset value is greater than the first preset value, and the second preset value can be 1.6met or 1.7 met.

Step 102: correcting human body parameters through correction functions; the correction function is obtained by feedback of the user on the adjusting behavior of the air conditioner.

The above steps S1-S2 calculate correction functions including an average radiation temperature correction function, a clothes-holding quantity correction function, and a metabolic rate correction function. And then modifying the related parameters of the human body according to the obtained correction function. Specifically, the average radiation temperature included in the human body parameter is corrected according to the average radiation temperature correction function, that is, the average radiation temperature calculated in step 101 is substituted into the average radiation temperature correction function, and the corrected average radiation temperature is calculated. Correcting the dressing amount included in the human body parameters according to the dressing amount correction function, namely substituting the dressing amount calculated in the step 101 into the dressing amount correction function, and calculating to obtain the corrected dressing amount. Correcting the metabolic rate included in the human body parameters according to the metabolic rate correction function, namely substituting the metabolic rate calculated in the step 101 into the metabolic rate correction function, and calculating to obtain the corrected metabolic rate.

The corrected human body parameters are more in line with the current actual conditions of the user, and the personalized parameters of the user in the current state are obtained after correction.

Step 103: and calculating the current indoor comfort level according to the indoor parameters, the outdoor parameters and the corrected human body parameters.

After the human body parameters are corrected, the current indoor comfort level is calculated according to the current indoor parameters, the outdoor parameters and the corrected human body parameters through the formula (3). Because the human body parameters are corrected through the correction function, and the user adjustment feedback is introduced into the correction function, the calculation error of the indoor comfort level can be reduced, the accuracy of comfort level calculation is improved, and the calculated current indoor comfort level represents the actual state of the current indoor environment more closely.

Step 104: and adjusting control parameters of the air conditioner according to the current indoor comfort level and the preset comfort level corresponding to the current air conditioning mode so as to enable the indoor environment to reach the preset comfort level.

The current air conditioning mode may be a cooling mode or a heating mode, the preset comfort level corresponding to the cooling mode may be-0.5 or-0.8, and the preset comfort level corresponding to the heating mode may be 0.5 or 0.8. The control parameters of the air conditioner comprise one or more of wind speed, temperature, humidity and the like.

Comparing the current indoor comfort level with the preset comfort level corresponding to the current air conditioning mode, and when the current indoor comfort level is determined to be unequal to the preset comfort level corresponding to the current air conditioning mode, modifying the control parameters of the air conditioner into the control parameters corresponding to the preset comfort level. The control parameters of the air conditioner comprise one or more of wind speed, temperature, humidity and the like. When there are a plurality of combinations of these control parameters, the most energy-efficient combination is called an optimal energy-saving point, and the control target is preferably the optimal energy-saving point.

Comparing the current indoor comfort level with the preset comfort level corresponding to the current air conditioning mode, judging whether the control parameter of the air conditioner is the optimal energy-saving point or not when the current indoor comfort level is equal to the preset comfort level corresponding to the current air conditioning mode, and if so, operating according to the current mode; if not, adjusting the control parameters of the air conditioner to the optimal energy saving point.

Specifically, when the current indoor comfort level is determined to be unequal to the preset comfort level corresponding to the current air conditioning mode, a state point set corresponding to the preset comfort level is determined, wherein the state point set comprises at least one indoor state point, the indoor state point comprises corresponding indoor parameters, and the indoor parameters comprise one or more of indoor temperature, indoor wind speed and indoor humidity. The air conditioner operates according to the indoor parameters corresponding to any indoor state point in the state point set, so that the indoor environment can reach the preset comfort level. And selecting one indoor state point from the state point set, and adjusting the value of the current control parameter of the air conditioner to the value of the indoor parameter corresponding to the selected indoor state point.

As an implementation manner, an indoor status point may be randomly selected from the status point set, and the value of the current control parameter of the air conditioner may be adjusted to the value of the indoor parameter corresponding to the randomly selected indoor status point.

In another implementation, the energy consumption for each indoor state point in the set of state points may be determined separately. The energy consumption corresponding to the indoor state point is the energy consumption required by the air conditioner to operate according to the indoor parameter corresponding to the indoor state point. And selecting an indoor state point with the lowest energy consumption from the state point set as an optimal energy-saving point, and adjusting the value of the current control parameter of the air conditioner to the value of the indoor parameter corresponding to the optimal energy-saving point to achieve the effect of achieving the optimal comfort level meeting the user requirement with the lowest energy consumption.

In some implementations, a current indoor state point corresponding to the current indoor comfort level can be determined, and the value of the indoor parameter corresponding to the current indoor state point is the value of the current control parameter of the air conditioner. And respectively calculating a state difference value between each indoor state point and the current indoor state point in the state point set. When the air conditioner changes the state of the indoor environment by controlling the change of the wind speed, the temperature and the humidity, compared with the temperature and the humidity, the air conditioner has the advantages that the feeling of the user on the wind speed is the most direct and rapid, the temperature is the second most direct and the humidity is the last. Controlling wind speed variation is the fastest way to change indoor comfort. Therefore, a difference value between the indoor wind speed corresponding to each indoor state point in the state point set and the indoor wind speed corresponding to the current indoor state point can be calculated, and the difference value is determined as the state difference value. Or, calculating a temperature difference between the indoor temperature corresponding to each indoor state point in the state point set and the indoor temperature corresponding to the current indoor state point, and determining the temperature difference as the state difference. Or, calculating a humidity difference between the indoor humidity corresponding to each indoor state point in the state point set and the indoor humidity corresponding to the current indoor state point, and determining the humidity difference as the state difference.

After the state difference value is calculated through any mode, the indoor state point corresponding to the smallest state difference value is selected from the state point set to be used as the fastest response point. And adjusting the value of the current control parameter of the air conditioner to the value of the indoor parameter corresponding to the fastest response point so as to rapidly meet the comfort level requirement of a user.

After the value of the current control parameter of the air conditioner is adjusted to the value of the indoor parameter corresponding to the fastest response point, the value of the indoor parameter corresponding to the fastest response point of the control parameter of the air conditioner can be adjusted to the value of the indoor parameter corresponding to the optimal energy-saving point. The method and the device can meet the comfort level requirement of the user at the fastest speed, then the user can adjust the comfort level requirement to be the best energy-saving point, and the best comfort level requirement of the user can be met at the lowest energy consumption.

In other embodiments of the present application, it is determined that the current indoor comfort level is equal to the preset comfort level corresponding to the current air conditioning mode, and when the current indoor state point corresponding to the current indoor comfort level is not ideal with the optimal energy-saving point, the value of the indoor parameter corresponding to the current indoor state point is adjusted to the value of the indoor parameter corresponding to the optimal energy-saving point, so that the effect of achieving the optimal comfort level meeting the user requirement with the lowest energy consumption is achieved.

Besides the control parameters of the air conditioner are adjusted by the mode of the state point set, the control parameters can also be adjusted by the mode of an equal comfort curve. If it is determined that the current indoor comfort level is not equal to the preset comfort level corresponding to the current air conditioning mode, it is indicated that the current indoor state point corresponding to the current indoor comfort level is not on the equal comfort level line where the preset comfort level is located, as shown in fig. 3. The current indoor state point corresponding to the current indoor comfort level represents the value of the control parameters such as the wind speed, the temperature, the humidity and the like of the current air conditioner, and the current indoor state point in the coordinate system with the wind speed is the coordinate point represented by the temperature and the wind speed set by the current air conditioner, wherein the horizontal axis is the temperature and the vertical axis is the wind speed shown in fig. 3.

And under the condition that the current indoor comfort level is not equal to the preset comfort level, determining the fastest response point corresponding to the current indoor state point from an equal comfort level line where the preset comfort level is located according to the current indoor state point corresponding to the current indoor comfort level. The fastest response point is used to represent a coordinate point of the control parameter that takes the shortest time to adjust the indoor comfort to the above-mentioned preset comfort. When the air conditioner changes the state of the indoor environment by controlling the change of the wind speed, the temperature and the humidity, compared with the temperature and the humidity, the air conditioner has the advantages that the feeling of the user on the wind speed is the most direct and rapid, the temperature is the second most direct and the humidity is the last. Controlling wind speed variation is the fastest way to change indoor comfort. Therefore, when the fastest response point is determined, the wind speed is preferentially changed to enable the indoor comfort level to reach the preset comfort level, as in fig. 3, a perpendicular line is drawn from the indoor state point to the transverse axis, and an intersection point of the perpendicular line and an equal comfort level line where the preset comfort level is located is the fastest response point. The temperature of the fastest response point is the same as that of the indoor state point, and the wind speeds are different.

After the fastest response point is determined in the above manner, the control parameter of the air conditioner is modified to the control parameter corresponding to the fastest response point, namely, the value of the wind speed set in the air conditioner is modified to the wind speed corresponding to the fastest response point. After the control parameters are modified, the air conditioner blows air according to the modified air speed, so that the indoor environment can reach the preset comfort level in the shortest time, namely, the indoor environment can be quickly adjusted to the comfortable state satisfied by the user.

In other embodiments of the present application, for energy saving, after the wind speed of the air conditioner is modified to the wind speed corresponding to the fastest response point, the optimal energy saving point with the lowest energy consumption is determined from the equal comfort level line by comparing the energy consumption corresponding to each state point on the equal comfort level line. And adjusting control parameters of the air conditioner according to the equal comfort level line so as to adjust the indoor state point from the fastest response point to the optimal energy-saving point along the equal comfort level line. Specifically, for a plurality of state points between the fastest response point and the optimal energy-saving point on the equal comfort level line, from the order of far from the optimal energy-saving point, the values of the control parameters such as wind speed, temperature, humidity and the like of the air conditioner are sequentially modified to the values of the parameters such as wind speed, temperature, humidity and the like corresponding to each state point, so that the energy consumption of the air conditioner is gradually reduced until the state that the energy consumption of the air conditioner is the lowest is regulated on the premise that the comfort level of the indoor environment is always equal to the preset comfort level, and the effect that the optimal comfort level meeting the user demands is achieved by the lowest energy consumption is achieved.

In other embodiments of the present application, the control state of the air conditioner may not be adjusted to the fastest response point, but when it is determined that the current indoor comfort level is not equal to the preset comfort level corresponding to the current air conditioning mode, the optimal energy-saving point is directly determined from the equal comfort level line where the preset comfort level is located, and then the control parameter of the air conditioner is modified to the control parameter corresponding to the optimal energy-saving point. Thus, the effects of lowest energy consumption and optimal comfort can be achieved in one step.

In the embodiment of the application, if it is determined that the current indoor comfort level is equal to the preset comfort level corresponding to the current air conditioning mode, the indoor state point corresponding to the current comfort level is indicated to be on an equal comfort level line where the preset comfort level is located, and it is indicated that the current indoor environment has reached the optimal comfort level satisfied by the user. Further, comparing the energy consumption corresponding to each state point on the comfort level line, determining whether the indoor state point corresponding to the current comfort level is the best energy-saving point with the lowest energy consumption, and if the indoor state point is the best energy-saving point, adjusting the current control parameters of the air conditioner is not needed, and the air conditioner is in the state of lowest energy consumption and realizing the best comfort level. If the indoor state point corresponding to the current indoor comfort level is not the optimal energy-saving point on the equal comfort level line where the preset comfort level is located, adjusting the control parameters of the air conditioner according to the equal comfort level line, so that the indoor state point is adjusted to the optimal energy-saving point along the equal comfort level line.

Namely, for a plurality of state points between the indoor state points and the optimal energy-saving points on the equal comfort level line, the values of the control parameters such as wind speed, temperature, humidity and the like of the air conditioner are sequentially modified into the values of the parameters such as wind speed, temperature, humidity and the like corresponding to the state points from the order from far to near to the optimal energy-saving point, so that the energy consumption of the air conditioner is gradually reduced until the state that the energy consumption of the air conditioner is the lowest is regulated on the premise that the comfort level of the indoor environment is always equal to the preset comfort level, and the effect that the optimal comfort level meeting the user demands is achieved by the lowest energy consumption is realized.

In the embodiment of the application, after the indoor state point is adjusted to the optimal energy-saving point in the above manner, if the indoor state is deviated, the indoor state point is adjusted to the optimal energy-saving point again in the above manner, so as to keep the air conditioner continuously to realize the optimal indoor comfort level with the lowest energy consumption.

In order to facilitate understanding of the methods provided by the embodiments of the present application, the following description is made with reference to the accompanying drawings. As shown in fig. 4, the indoor parameters and the outdoor parameters are input into a pre-trained correction model to obtain a dressing amount correction function, a metabolic rate correction function and an average radiation temperature correction function, the dressing amount is corrected by the dressing amount correction function, the metabolic rate is corrected by the metabolic rate correction function, and the average radiation temperature is corrected by the average radiation temperature correction function. And calculating the current indoor comfort level according to the indoor parameters, the outdoor parameters, the corrected dressing volume, the metabolic rate and the average radiation temperature. Judging whether the current indoor comfort level is equal to the preset comfort level, if so, judging whether the current indoor state point is the optimal energy-saving point, and if so, keeping the current control parameters of the air conditioner unchanged. If not, the running state of the air conditioner is adjusted to the optimal energy saving point. And if the current indoor comfort level is not equal to the preset comfort level, adjusting the control parameters of the air conditioner so as to adjust the indoor state point to the optimal energy-saving point.

The embodiment of the application corrects the comfort level through user adjustment feedback. So that the comfort model more accurately characterizes the comfort preferences of the user. The current indoor comfort level is calculated according to the corrected human body parameters, so that the comfort level calculation accuracy is improved, and the calculated current indoor comfort level is closer to the actual state of the current indoor environment. Because the human body parameters are corrected through the correction function, no new detection equipment is added in the air conditioner, the equipment cost is low, the human body parameters are not required to be inquired to the user, and the trouble to the user is avoided. Further, the control parameters of the air conditioner are adjusted according to the current indoor comfort level, and the indoor state point can be adjusted to the fastest response point first, so that the comfort level requirement of a user can be met rapidly. The control parameters of the air conditioner can be regulated to regulate the state point to the optimal energy-saving point, so that the optimal comfort level meeting the demands of users can be achieved with the lowest energy consumption.

An embodiment of the present application provides an air conditioner control device, which is configured to execute the air conditioner control method provided in any one of the foregoing embodiments, as shown in fig. 5, where the device includes:

an acquisition module 601, configured to acquire current indoor parameters, outdoor parameters, and human parameters;

The correction module 602 is configured to correct the human parameter through a correction function; the correction function is obtained by feeding back the adjustment behavior of the air conditioner by the user;

a comfort level calculating module 603, configured to calculate a current indoor comfort level according to the indoor parameter, the outdoor parameter and the corrected human body parameter;

the control parameter adjustment module 604 is configured to adjust control parameters of the air conditioner according to the current indoor comfort level and a preset comfort level corresponding to the current air conditioning mode, so that the indoor environment reaches the preset comfort level.

An obtaining module 601, configured to obtain current indoor parameters and outdoor parameters; the indoor parameters at least comprise one or more of indoor temperature, indoor humidity, indoor wind speed and building function information; the outdoor parameter comprises at least one or more of outdoor temperature, outdoor wind speed, outdoor illuminance; according to the indoor parameters and the outdoor parameters, the human body parameters of the user are calculated, wherein the human body parameters comprise average radiation temperature, clothes-wearing quantity and metabolic rate.

An obtaining module 601, configured to calculate an average radiation temperature according to an indoor temperature included in the indoor parameter and an outdoor temperature included in the outdoor parameter; calculating the clothes-putting quantity according to the outdoor temperature; and determining the metabolic rate according to the building function information included in the indoor parameters.

The correction module 602 is configured to obtain indoor parameters, outdoor parameters, human parameters and user adjustment data of the air conditioner under a plurality of past working conditions; and calculating to obtain a correction function according to the indoor parameters, the outdoor parameters, the human body parameters and the regulation data under each working condition.

The correction module 602 is configured to calculate indoor comfort level under each working condition according to the indoor parameter, the outdoor parameter and the human body parameter under each working condition; according to the adjustment data of the user on the air conditioner under each working condition, respectively calculating the correction parameters of indoor comfort level under each working condition; the indoor comfort level under each working condition is corrected according to the correction parameters corresponding to each working condition; according to the indoor parameters, the outdoor parameters, the human body parameters and the corrected indoor comfort level under each working condition, respectively calculating a correction function relation under each working condition; and according to the correction function relation under each working condition, adopting a least square method to solve simultaneously to obtain a correction function.

The correction module 602 is configured to determine, according to an adjustment amplitude of each indoor parameter included in the adjustment data of the air conditioner by the user under the first working condition, correction coefficients corresponding to each indoor parameter through a machine learning model trained in advance; the first working condition is any working condition in each working condition; each indoor parameter comprises one or more of indoor temperature, indoor humidity and indoor wind speed; and calculating the correction parameters of indoor comfort level under the first working condition according to the adjustment amplitude and the correction coefficient corresponding to each indoor parameter under the first working condition.

A control parameter adjustment module 604, configured to determine that the current indoor comfort level is not equal to the preset comfort level corresponding to the current air conditioning mode; determining a state point set corresponding to the preset comfort level, wherein the state point set comprises at least one indoor state point, and the indoor state point comprises corresponding indoor parameters; and selecting one indoor state point from the state point set, and adjusting the value of the current control parameter of the air conditioner to the value of the indoor parameter corresponding to the selected indoor state point.

A control parameter adjustment module 604, configured to randomly select an indoor status point from the status point set; or determining the energy consumption corresponding to each indoor state point in the state point set, and selecting the indoor state point with the lowest energy consumption from the state point set as the optimal energy-saving point; or determining the current indoor state point corresponding to the current indoor comfort level, respectively calculating the state difference value between each indoor state point in the state point set and the current indoor state point, and selecting the indoor state point corresponding to the minimum state difference value from the state point set as the fastest response point.

The control parameter adjustment module 604 is configured to adjust the value of the current control parameter of the air conditioner to the value of the indoor parameter corresponding to the fastest response point, and then adjust the value of the control parameter of the air conditioner from the value of the indoor parameter corresponding to the fastest response point to the value of the indoor parameter corresponding to the optimal energy saving point.

And the control parameter adjustment module 604 is configured to determine that the current indoor comfort level is equal to the preset comfort level corresponding to the current air conditioning mode, and that the current indoor state point corresponding to the current indoor comfort level is not equal to the optimal energy-saving point, and adjust the value of the control parameter of the air conditioner from the value of the indoor parameter corresponding to the current indoor state point to the value of the indoor parameter corresponding to the optimal energy-saving point.

A control parameter adjustment module 604, configured to determine that the current indoor comfort level is not equal to the preset comfort level corresponding to the current air conditioning mode; determining the fastest response point corresponding to the current indoor state point from an equal comfort level line where the preset comfort level is located according to the current indoor state point corresponding to the current indoor comfort level; and modifying the control parameters of the air conditioner into control parameters corresponding to the fastest response points.

A control parameter adjustment module 604, configured to determine an optimal energy saving point from the equal comfort level line; and adjusting control parameters of the air conditioner according to the equal comfort level line so as to adjust the indoor state point from the fastest response point to the optimal energy-saving point along the equal comfort level line.

A control parameter adjustment module 604, configured to determine that the current indoor comfort level is not equal to the preset comfort level corresponding to the current air conditioning mode; determining an optimal energy-saving point from an equal comfort level line where a preset comfort level is located; and modifying the control parameters of the air conditioner into the control parameters corresponding to the optimal energy-saving points.

A control parameter adjustment module 604, configured to determine that the current indoor comfort level is equal to a preset comfort level corresponding to the current air conditioning mode, and determine that a current indoor state point corresponding to the current indoor comfort level is not an optimal energy-saving point on an equal comfort level line where the preset comfort level is located; and adjusting control parameters of the air conditioner according to the equal comfort level line so as to adjust the indoor state point to the optimal energy-saving point along the equal comfort level line.

The air conditioner control device provided by the above embodiment of the present application and the air conditioner control method provided by the embodiment of the present application are the same inventive concept, and have the same advantages as the method adopted, operated or implemented by the application program stored therein.

The embodiment of the application also provides an air conditioner for executing the air conditioner control method. Referring to fig. 6, a schematic diagram of an air conditioner according to some embodiments of the present application is shown. As shown in fig. 6, the air conditioner 7 includes: a processor 700, a memory 701, a bus 702 and a communication interface 703, the processor 700, the communication interface 703 and the memory 701 being connected by the bus 702; the memory 701 stores a computer program that can be executed on the processor 700, and when the processor 700 executes the computer program, the air conditioner control method provided in any of the foregoing embodiments of the present application is executed.

The memory 701 may include a high-speed random access memory (RAM: random Access Memory), and may further include a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. The communication connection between the system network element and at least one other network element is implemented via at least one communication interface 703 (which may be wired or wireless), the internet, a wide area network, a local network, a metropolitan area network, etc. may be used.

Bus 702 may be an ISA bus, a PCI bus, an EISA bus, or the like. The buses may be classified as address buses, data buses, control buses, etc. The memory 701 is configured to store a program, and the processor 700 executes the program after receiving an execution instruction, and the air conditioner control method disclosed in any of the foregoing embodiments of the present application may be applied to the processor 700 or implemented by the processor 700.

The processor 700 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the methods described above may be performed by integrated logic circuitry in hardware or instructions in software in processor 700. The processor 700 may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU for short), a network processor (Network Processor, NP for short), etc.; but may also be a Digital Signal Processor (DSP), application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the embodiments of the present application may be embodied directly in hardware, in a decoded processor, or in a combination of hardware and software modules in a decoded processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in the memory 701, and the processor 700 reads information in the memory 701, and in combination with its hardware, performs the steps of the above method.

The air conditioner provided by the embodiment of the application and the air conditioner control method provided by the embodiment of the application are the same in invention conception, and have the same beneficial effects as the method adopted, operated or realized by the air conditioner.

The present embodiment also provides a computer readable storage medium corresponding to the air conditioner control method provided in the foregoing embodiment, referring to fig. 7, the computer readable storage medium is shown as an optical disc 30, and a computer program (i.e. a program product) is stored thereon, where the computer program, when executed by a processor, performs the air conditioner control method provided in any of the foregoing embodiments.

It should be noted that examples of the computer readable storage medium may also include, but are not limited to, a phase change memory (PRAM), a Static Random Access Memory (SRAM), a Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a flash memory, or other optical or magnetic storage medium, which will not be described in detail herein.

The computer readable storage medium provided by the above embodiments of the present application has the same advantageous effects as the method adopted, operated or implemented by the application program stored therein, for the same inventive concept as the air conditioner control method provided by the embodiments of the present application.

It should be noted that:

in the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the present application may be practiced without these specific details. In some instances, well-known structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the application, various features of the application are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the application and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be construed as reflecting the following schematic diagram: i.e., the claimed application requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this application.

Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the present application and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.

The foregoing is merely a preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the technical scope of the present application should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. An air conditioner control method, comprising:

acquiring indoor parameters, outdoor parameters, human body parameters and user regulation data of an air conditioner under a plurality of past working conditions; wherein, according to the indoor parameter and the outdoor parameter, calculating the human body parameter of the user;

calculating to obtain a correction function according to the indoor parameter, the outdoor parameter, the human body parameter and the regulation data under each working condition, wherein the correction function comprises an average radiation temperature correction function;

correcting the human body parameters through a correction function; calculating the current indoor comfort level according to the current indoor parameter, the outdoor parameter and the corrected human body parameter,

wherein the human parameter comprises an average radiation temperature;

adjusting control parameters of an air conditioner according to the current indoor comfort level and the preset comfort level corresponding to the current air conditioning mode so as to enable the indoor environment to reach the preset comfort level;

wherein, according to the indoor parameter, the outdoor parameter, the human parameter and the adjustment data under each working condition, a correction function is obtained by calculation, which comprises:

calculating a correction function relation under each working condition according to the indoor parameter, the outdoor parameter, the human body parameter and the corrected indoor comfort level under each working condition, wherein the corrected indoor comfort level is obtained by correcting the indoor comfort level under each working condition according to the adjustment data of a user on the air conditioner under each working condition;

and obtaining a correction function by adopting a preset method according to the correction function relation under each working condition.

2. The method of claim 1, wherein the obtaining current indoor parameters, outdoor parameters, and human parameters comprises:

Acquiring current indoor parameters and outdoor parameters; the indoor parameters at least comprise one or more of indoor temperature, indoor humidity, indoor wind speed and building function information; the outdoor parameters at least comprise one or more of outdoor temperature, outdoor wind speed and outdoor radiation illuminance;

the parameters of the human body also comprise clothing amount and metabolic rate.

3. The method of claim 2, wherein said calculating the user's body parameters from said indoor parameters and said outdoor parameters comprises:

calculating the clothes-putting quantity according to the outdoor temperature;

and determining the metabolic rate according to the building function information included in the indoor parameters.

4. The method of claim 1, wherein said calculating a correction function based on said indoor parameter, said outdoor parameter, said body parameter, and said adjustment data for each operating condition comprises:

5. The method of claim 4, wherein the calculating the correction parameter of indoor comfort level under each working condition according to the adjustment data of the user to the air conditioner under each working condition includes:

6. The method of claim 1, wherein adjusting the control parameters of the air conditioner according to the current indoor comfort level and the preset comfort level corresponding to the current air conditioning mode comprises:

7. The method of claim 6, wherein said selecting an indoor status point from said set of status points comprises:

randomly selecting an indoor state point from the state point set; or,

8. The method of claim 7, wherein the method further comprises:

9. The method of claim 7, wherein the method further comprises:

10. The method according to claim 1, wherein adjusting the control parameters of the air conditioner according to the current indoor comfort level and the preset comfort level corresponding to the current air conditioning mode comprises:

11. The method of claim 10, wherein after modifying the control parameter of the air conditioner to the control parameter corresponding to the fastest response point, further comprising:

determining an optimal energy-saving point from the equal comfort level line;

12. The method according to claim 1, wherein adjusting the control parameters of the air conditioner according to the current indoor comfort level and the preset comfort level corresponding to the current air conditioning mode comprises:

13. The method according to any one of claims 10-12, wherein adjusting the control parameters of the air conditioner according to the current indoor comfort level and the preset comfort level corresponding to the current air conditioning mode comprises:

14. An air conditioner control device, comprising:

The correction module is used for correcting the human body parameters through a correction function;

a comfort level calculating module for calculating the current indoor comfort level according to the current indoor parameter, the outdoor parameter and the corrected human body parameter,

wherein the human parameter comprises an average radiation temperature;

the control parameter adjusting module is used for adjusting control parameters of the air conditioner according to the current indoor comfort level and the preset comfort level corresponding to the current air conditioning mode so as to enable the indoor environment to reach the preset comfort level;

15. An air conditioner comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor runs the computer program to implement the method of any one of claims 1-13.

16. A computer readable storage medium having stored thereon a computer program, wherein the program is executed by a processor to implement the method of any of claims 1-13.