CN116007152A - Air conditioner control method, device, air conditioner equipment and storage medium - Google Patents
Air conditioner control method, device, air conditioner equipment and storage medium Download PDFInfo
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Abstract
The application relates to an air conditioner control method, an air conditioner control device, air conditioning equipment and a storage medium. The method comprises the following steps: and determining corresponding temperature comparison conditions according to the obtained current environment temperature in the non-use time period, wherein the temperature comparison conditions comprise an over-high temperature condition and an over-low temperature condition, determining an energy-saving temperature threshold corresponding to the current environment temperature by using an energy-saving neural network model, and under the condition that the comparison result between the current environment temperature and the energy-saving temperature threshold accords with the temperature comparison conditions, indicating that the environment temperature is over-high or over-low in the inner chamber in the non-use time period, wherein the preset operation mode is used for controlling the operation frequency of the compressor of the air conditioner to be kept below the preset operation frequency, namely, the air conditioner is enabled to perform low-load operation so as to perform small-amplitude temperature adjustment on the indoor environment, and the temperature difference between the indoor temperature and the life suitable temperature of a user is reduced as much as possible, so that the excessive consumption of electric quantity due to the over-high temperature difference between the indoor temperature and the life suitable temperature of the user is avoided.
Description
Technical Field
The present disclosure relates to the field of air conditioning technologies, and in particular, to an air conditioning control method, an air conditioning device, an air conditioning apparatus, and a storage medium.
Background
At present, an air conditioner unit is one of household appliances which are installed by a household, and the energy consumption of the air conditioner causes that the consumption of the air conditioner is relatively high in the total power consumption of the household.
When using an air conditioner, it is generally selected to turn off the air conditioner once the indoor temperature reaches a desired temperature or a person leaves the room, and it is considered that the air conditioner is turned off for several hours to save several hours of electricity. However, after the air conditioner is turned off, the indoor temperature can be greatly influenced due to the fact that the temperature is higher after the wall is exposed to the sun or the temperature is lower after the wall is frozen, when the indoor temperature deviates from the ideal temperature, a user can turn on the air conditioner unit again, and the air conditioner unit can continuously run for a period of time after being turned on, so that the indoor temperature can reach the ideal temperature, and the frequent turning off and the starting of the air conditioner unit can generate larger power consumption.
For users, the electricity charge is counted in the month or the quarter, the electricity charge cannot reflect the daily electricity consumption, and the users can not accurately grasp whether to turn off the air conditioner or continuously run for more energy saving under the condition of higher or lower environmental temperature, so that the operation of the air conditioner cannot be accurately controlled selectively.
Disclosure of Invention
In order to solve the technical problem that the power consumption is excessive due to the fact that the air conditioning unit is suddenly started in an environment with a high temperature or a low temperature, the application provides an air conditioning control method, an air conditioning device, air conditioning equipment and a storage medium.
In a first aspect, the present application provides an air conditioner control method, including:
determining corresponding temperature comparison conditions according to the acquired current environmental temperature in a non-use time period, wherein the temperature comparison conditions comprise a temperature too high condition and a temperature too low condition;
determining an energy-saving temperature threshold corresponding to the current environmental temperature based on an energy-saving neural network model;
determining whether a comparison result between the current ambient temperature and the energy-saving temperature threshold meets the temperature comparison condition;
and if the comparison result meets the temperature comparison condition, operating according to a preset operation mode, wherein the preset operation mode is used for controlling the operation frequency of the compressor of the air conditioner not to exceed the preset operation frequency.
In a second aspect, the present application provides an air conditioner control device, including:
the acquisition module is used for determining corresponding temperature comparison conditions according to the acquired current environment temperature in the non-use time period, wherein the temperature comparison conditions comprise a temperature too high condition and a temperature too low condition;
The processing module is used for determining an energy-saving temperature threshold corresponding to the current environment temperature based on an energy-saving neural network model;
the determining module is used for determining whether the comparison result between the current environment temperature and the energy-saving temperature threshold meets the temperature comparison condition or not;
and the operation module is used for operating according to a preset operation mode if the comparison result meets the temperature comparison condition, wherein the preset operation mode is used for controlling the operation frequency of the compressor of the air conditioner not to exceed the preset operation frequency.
In a third aspect, the present application provides an air conditioning apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
determining corresponding temperature comparison conditions according to the acquired current environmental temperature in a non-use time period, wherein the temperature comparison conditions comprise a temperature too high condition and a temperature too low condition;
determining an energy-saving temperature threshold corresponding to the current environmental temperature based on an energy-saving neural network model;
determining whether a comparison result between the current ambient temperature and the energy-saving temperature threshold meets the temperature comparison condition;
And if the comparison result meets the temperature comparison condition, operating according to a preset operation mode, wherein the preset operation mode is used for controlling the operation frequency of the compressor of the air conditioner not to exceed the preset operation frequency.
In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
determining corresponding temperature comparison conditions according to the acquired current environmental temperature in a non-use time period, wherein the temperature comparison conditions comprise a temperature too high condition and a temperature too low condition;
determining an energy-saving temperature threshold corresponding to the current environmental temperature based on an energy-saving neural network model;
determining whether a comparison result between the current ambient temperature and the energy-saving temperature threshold meets the temperature comparison condition;
and if the comparison result meets the temperature comparison condition, operating according to a preset operation mode, wherein the preset operation mode is used for controlling the operation frequency of the compressor of the air conditioner not to exceed the preset operation frequency.
Based on the air conditioner control method, corresponding temperature comparison conditions are determined according to the obtained current environment temperature in a non-use time period, the temperature comparison conditions comprise a temperature too high condition and a temperature too low condition, an energy-saving neural network model is utilized to determine an energy-saving temperature threshold corresponding to the current environment temperature, and when the comparison result between the current environment temperature and the energy-saving temperature threshold meets the temperature comparison conditions, the condition that the environment temperature is too high or too low in the inner chamber in the non-use time period is indicated, and a user suddenly starts an air conditioner set to reach a set temperature in the environment so as to easily generate more power consumption.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to a person skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a schematic flow chart of a method for controlling hollow-core control according to one embodiment;
FIG. 2 is a schematic diagram of electricity consumption of an air conditioner before use of an embodiment of a hollow air conditioning control method;
FIG. 3 is a schematic diagram of electricity consumption of an air conditioner after use of the air conditioner control method according to one embodiment;
FIG. 4 is a schematic diagram of a configuration of a predetermined neural network model in one embodiment;
FIG. 5 is a block diagram of a hollow-core control device according to one embodiment;
fig. 6 is an internal structural diagram of an air conditioner device according to one embodiment.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present application based on the embodiments herein.
In one embodiment, fig. 1 is a schematic flow chart of an air conditioner control method in one embodiment, and referring to fig. 1, an air conditioner control method is provided. The embodiment is mainly exemplified by the application of the method to an air conditioner, and the air conditioner control method specifically comprises the following steps:
and step S210, determining corresponding temperature comparison conditions according to the acquired current environment temperature in the non-use time period, wherein the temperature comparison conditions comprise an over-high temperature condition and an under-low temperature condition.
Specifically, the non-use period refers to a period when the air conditioner enters a sleep state or does not execute any control instruction, corresponding temperature comparison conditions are determined according to the obtained current environment temperature in the non-use period, the temperature comparison conditions comprise a temperature too high condition and a temperature too low condition, the current season can be determined according to the current environment temperature, different temperature comparison conditions are adopted in different seasons, for example, whether the current environment temperature is too high in summer or not needs to be judged, whether the current environment temperature is too low in winter or not needs to be judged, because the temperature difference between the current environment temperature and the life suitable temperature of a user is too large due to the fact that the current environment temperature is too high or too low, the phenomenon that the air conditioner is suddenly started to consume electricity is caused, and the life suitable temperature of the user is 18 ℃ to 25 ℃ generally, so that the set temperature of the user for the air conditioner is always in the temperature range.
Step S220, determining an energy-saving temperature threshold corresponding to the current environment temperature based on the energy-saving neural network model.
Specifically, the energy-saving neural network model is a neural network model trained through deep learning, the current environmental temperature is used as an input parameter to be input into the energy-saving neural network model, the output parameter of the energy-saving neural network model is an energy-saving temperature threshold, namely, different current environmental temperatures are provided with energy-saving temperature thresholds corresponding to the current environmental temperatures, and the energy-saving temperature thresholds are used as reference values of the current environmental temperatures which are too high or too low.
Step S230, determining whether the comparison result between the current ambient temperature and the energy-saving temperature threshold meets the temperature comparison condition.
Specifically, the current environmental temperature is compared with the corresponding energy-saving temperature threshold value, and whether the operation according to the preset operation mode is needed or not is determined by utilizing the comparison result between the current environmental temperature and the corresponding energy-saving temperature threshold value and the matching result of the temperature comparison condition.
Step S240, if the comparison result meets the temperature comparison condition, operating according to a preset operation mode, where the preset operation mode is used to control the operation frequency of the compressor of the air conditioner not to exceed the preset operation frequency.
Specifically, the comparison result between the current environmental temperature and the energy-saving temperature threshold meets the temperature comparison condition, which means that the current environmental temperature is too high or too low, so that the temperature difference between the current environmental temperature and the life suitable temperature of the user is too large, if the temperature difference is placed, the electricity consumption is consumed in a transitional manner under the condition that the user suddenly starts the air conditioner, in order to avoid the phenomenon, the air conditioner is controlled to operate according to a preset operation mode, namely, the low-load operation mode, so that the operation frequency of the compressor of the air conditioner is maintained below the preset operation frequency, the preset operation frequency can be specifically 45Hz or 40Hz, the user-defined operation frequency can be specifically used for controlling the compressor to be in the low operation frequency according to the application scene requirement, and the smaller the operation frequency of the compressor is, the smaller the electricity consumption is less. Therefore, the air conditioner is controlled to run under low load in the non-use time period so as to reduce the temperature difference between the current environment temperature and the life suitable temperature of the user as much as possible, and the air conditioner is used for keeping the indoor environment temperature under the condition that the outdoor environment temperature is too high or too low, so that the electricity consumption is not excessively consumed due to the fact that the temperature difference between the indoor environment temperature and the set temperature is too large when the user suddenly starts the air conditioner.
As shown in fig. 2, when the air conditioner is not controlled to operate in the low-load operation mode in the non-use time period, a user suddenly starts the air conditioner to generate larger electricity consumption under the condition that the ambient temperature is too high or too low, and as shown in fig. 3, when the air conditioner is controlled to operate in the low-load operation mode in the non-use time period, the user suddenly starts the air conditioner to avoid the transitional electricity consumption under the condition that the ambient temperature is too high or too low.
In one embodiment, the current environmental temperature includes a current outdoor temperature and/or a current indoor temperature, the energy-saving temperature threshold includes a preset outdoor temperature and/or a preset indoor temperature, and if the comparison result meets the temperature comparison condition, the energy-saving temperature threshold operates according to a preset operation mode, including:
if the comparison result between the current outdoor temperature and the preset outdoor temperature meets the temperature comparison condition, operating according to a preset operation mode; and/or the number of the groups of groups,
and if the comparison result between the current indoor temperature and the preset indoor temperature meets the temperature comparison condition, operating according to a preset operation mode.
Specifically, whether the current environmental temperature is too high or too low is judged by utilizing a comparison result between the current outdoor temperature and the preset outdoor temperature and/or by utilizing a comparison result between the current indoor temperature and the preset indoor temperature, and at least one comparison result accords with a temperature comparison condition in the comparison result between the current outdoor temperature and the preset outdoor temperature and the comparison result between the current indoor temperature and the preset indoor temperature, so that the phenomenon that the current environmental temperature is too high or too low is judged, the air conditioner needs to be controlled to operate under low load to maintain the indoor temperature, and the situation that the temperature difference between the indoor temperature and the life suitable temperature of a user is too large is avoided, so that the user can consume electric quantity in a transitional mode when the air conditioner is started suddenly.
In one embodiment, the preset operation mode includes a preset cooling mode, and the operation according to the preset operation mode includes:
under the condition that the temperature comparison condition is an over-high temperature condition, determining that the preset operation mode is a preset refrigeration mode;
and operating according to the preset refrigeration mode.
Specifically, in the case that the temperature comparison condition is a condition that the temperature is too high, the current environmental temperature indicates summer, whether the indoor temperature and the outdoor temperature are too high needs to be judged, if the current environmental temperature is too high and the user suddenly starts the air conditioner, the air conditioner needs to refrigerate from the higher temperature to the set temperature, namely, the refrigerating temperature difference is larger, so that the energy consumption required for refrigeration is more, therefore, in the case that the current outdoor temperature is larger than the preset outdoor temperature, the comparison result between the current outdoor temperature and the preset outdoor temperature accords with the condition that the temperature is too high, in the case that the current indoor temperature is larger than the preset indoor temperature, the comparison result between the current indoor temperature and the preset indoor temperature accords with the condition that the temperature is too high, in the case that at least one of the two conditions occurs, the air conditioner needs to be controlled to perform low-load operation to perform refrigeration processing in a small range, so as to maintain the indoor temperature at the optimal energy-saving temperature, thereby shortening the temperature difference between the indoor temperature and the user life proper temperature, and avoiding the sudden starting of the air conditioner under the condition that the temperature difference between the indoor temperature and the set temperature is too high.
Under the condition that the temperature comparison condition is the over-high temperature condition, if the current outdoor temperature is smaller than the preset outdoor temperature, the current environment temperature does not accord with the over-high temperature condition, namely the current outdoor temperature is not over-high at the moment, and the air conditioner does not need to be controlled to operate according to the low-load refrigeration mode.
Under the condition that the temperature comparison condition is the temperature too low condition, if the current outdoor temperature is larger than the preset outdoor temperature, the current environment temperature does not accord with the temperature too low condition, namely the current outdoor temperature is not too low at the moment, and the air conditioner does not need to be controlled to operate according to the low-load heating mode.
In one embodiment, the preset operation mode further includes a preset heating mode, and the operation according to the preset operation mode includes:
under the condition that the temperature comparison condition is a temperature too low condition, determining that the preset operation mode is a preset heating mode;
and operating according to the preset heating mode.
Specifically, when the temperature comparison condition is a condition that the temperature is too low, the current environmental temperature indicates that whether the indoor and outdoor temperatures are too low or not needs to be judged, if the current environmental temperature is too low and the air conditioner is suddenly started by a user, the air conditioner needs to be heated from the lower temperature to the set temperature, namely, the heating temperature difference is large, so that the energy consumption required by heating is large, and the electricity consumption is large.
In one embodiment, if the comparison result meets the temperature comparison condition, before the operation according to the preset operation mode, the method further includes:
determining the starting state of an energy-saving mode;
and if the comparison result meets the temperature comparison condition, operating according to a preset operation mode, wherein the operation comprises the following steps:
if the starting state is starting, and the comparison result between the current outdoor temperature and the preset outdoor temperature accords with the temperature comparison condition, the vehicle is operated according to a preset operation mode; or alternatively, the first and second heat exchangers may be,
and if the starting state is not started, and the comparison result between the current indoor temperature and the preset indoor temperature accords with the temperature comparison condition, the vehicle is operated according to a preset operation mode.
Specifically, the starting state of the energy-saving mode is used for determining whether the outdoor temperature is used as a detection standard of low-load operation or the indoor temperature is used as a detection standard of low-load operation, if the starting state of the energy-saving mode is the starting state, whether the comparison result between the current outdoor temperature and the corresponding preset outdoor temperature meets the temperature comparison condition is judged, if the comparison result between the current outdoor temperature and the preset outdoor temperature meets the temperature comparison condition, the current outdoor temperature is excessively high or excessively low, the air conditioner is controlled to operate according to the preset operation mode, the indoor is always kept at the optimal energy-saving temperature, the temperature difference between the indoor temperature and the life suitable temperature of a user is reduced as much as possible, and the power consumption is not consumed in a transitional way when the user suddenly starts the air conditioner to heat or cool from the optimal energy-saving temperature.
And under the condition that the starting state of the energy-saving mode is not started, judging whether the comparison result between the current indoor temperature and the corresponding preset indoor temperature meets the temperature comparison condition, if the comparison result between the current indoor temperature and the preset indoor temperature meets the temperature comparison condition, indicating that the current indoor temperature is too high or too low, and controlling the air conditioner to operate according to the preset operation mode.
In one embodiment, if the comparison result meets the temperature comparison condition, after the operation according to the preset operation mode, the method further includes:
determining the operation duration of the preset operation mode;
and controlling the air conditioner to enter a shutdown state under the condition that the running time length reaches the preset time length.
Specifically, when the air conditioner starts to operate according to the preset operation mode, starting to count time, obtaining the operation duration of the preset operation mode, and under the condition that the operation duration reaches the preset duration, indicating that the air conditioner has operated for a longer time according to low load, still not receiving an opening instruction of a user, indicating that the user may not use the air conditioner in a short period of time, and enabling the air conditioner to enter a shutdown state in order to save electric energy.
The method specifically may be that when the starting state of the energy-saving mode is not started, and the comparison result between the current indoor temperature and the preset indoor temperature meets a temperature too low condition or a temperature too high condition, the air conditioner is controlled to perform low-load operation according to the preset operation mode, and when the energy-saving mode is not started, the air conditioner is controlled to enter the shutdown state only when the operation duration of the air conditioner according to the preset operation mode reaches the preset duration, that is, whether the energy-saving mode of the air conditioner is in the starting state or not is controlled to enter the shutdown state when the operation duration of the air conditioner according to the preset operation mode reaches the preset duration is described herein, and when the energy-saving mode of the air conditioner is not started, the air conditioner in the starting state is controlled not to enter the shutdown state even when the operation duration of the air conditioner according to the preset operation mode reaches the preset duration. The two conditions are combined, and the condition that the air conditioner enters the shutdown state in which scene can be specifically set according to the actual application.
In one embodiment, after the determining the operation duration of the preset operation mode, the method further includes:
and under the condition that a control instruction is received before the operation time reaches the preset time, exiting the preset operation mode and adjusting the operation parameters of the air conditioner according to the control instruction.
Specifically, the control instruction refers to a parameter modification instruction initiated by a user, the control instruction is used for changing an operation parameter of the air conditioner, the initiation mode of the control instruction can be specifically voice, gesture, terminal remote control, remote controller remote control and the like, and when the control instruction is received before the operation duration reaches the preset duration, the air conditioner needs to exit the preset operation mode and modify the operation parameter in time according to the control instruction, and at this time, the operation duration of the preset operation mode needs to be cleared so as to restart timing when the preset operation mode is entered next time.
In one embodiment, the determining the corresponding temperature comparison condition according to the obtained current environmental temperature in the non-use time period includes:
under the condition that the current outdoor temperature in the current environment temperature acquired in the non-use time period is in a first preset temperature range, taking the temperature-over condition as the temperature comparison condition, wherein the temperature-over condition is used for indicating that the temperature in the current environment temperature is greater than the corresponding temperature in the energy-saving temperature threshold; or alternatively, the first and second heat exchangers may be,
And under the condition that the current outdoor temperature in the current environment temperature acquired in the non-use time period is in a second preset temperature range, taking the temperature too-low condition as the temperature comparison condition, wherein the temperature too-low condition is used for indicating that the temperature in the current environment temperature is smaller than the corresponding temperature in the energy-saving temperature threshold.
Specifically, the current ambient temperature includes a current outdoor temperature, the first preset temperature range refers to a high temperature range, specifically, the temperature range can be 30 ℃ to 40 ℃ or 28 ℃ to 43 ℃, and specifically, the summer temperature ranges of different areas are referred to, when the current outdoor temperature is within the first preset temperature range, the current season of the air conditioner is summer, whether the current ambient temperature is too high needs to be judged, and therefore, the temperature too high condition is taken as a temperature comparison condition.
The second preset temperature range is a low temperature range, specifically, the temperature range can be-14 ℃ to 13 ℃ or-20 ℃ to 18 ℃, specifically, the winter temperature ranges of different areas are referenced, when the current outdoor temperature range is in the second preset temperature range, which means that the current season of the air conditioner is winter, whether the current environment temperature is too low is needed to be judged, and therefore the temperature too low condition is taken as the temperature comparison condition.
Because the temperature difference between the ambient temperature in spring or autumn and the life suitable temperature of the user is smaller, the probability of starting the air conditioner to perform refrigeration or heating is smaller, and therefore, whether the air conditioner needs to perform low-load operation is judged only under the conditions of over-high temperature and under-low temperature.
In one embodiment, the current environmental temperature further includes a current indoor temperature, and the determining, based on the energy-saving neural network model, an energy-saving temperature threshold corresponding to the current environmental temperature includes:
inputting the current outdoor temperature, the current indoor temperature and unit parameters of the air conditioner into the energy-saving neural network model, and outputting the energy-saving temperature threshold, wherein the energy-saving temperature threshold comprises a preset indoor temperature corresponding to the current indoor temperature and a preset outdoor temperature corresponding to the current outdoor temperature, and the unit parameters comprise the unit match number and the power consumption in unit time.
Specifically, the unit parameters of the air conditioner include the unit match number and the power consumption in a unit time, and the unit time may be specifically one hour, one day, one week or one month, in this embodiment, the unit time refers to one day, the current indoor and outdoor temperature difference is determined according to the current outdoor temperature and the current indoor temperature, the current outdoor temperature A1, the current indoor and outdoor temperature B1, the current indoor and outdoor temperature difference C1, the unit match number P1 and the power consumption H1 in the unit time are taken as input parameters together to be input into the energy-saving neural network model, and the energy-saving neural network model learns the characteristic relationship between the indoor temperature, the outdoor temperature, the indoor and outdoor temperature difference, the unit match number, the power consumption in the unit time and the temperature threshold, so when the energy-saving neural network model receives different indoor temperatures, the outdoor temperatures, the indoor and outdoor temperature differences, the unit match number and the power consumption in the unit time, preset temperatures corresponding to the energy-saving neural network model are output, and the preset temperatures include the preset indoor temperature M1 and the preset outdoor temperature M2.
In one embodiment, before the corresponding temperature comparison condition is determined according to the acquired current environmental temperature in the non-use time period, the method further includes:
acquiring a historical data set, wherein the historical data set comprises a plurality of data sets, and each data set comprises a plurality of sampling parameters, wherein the sampling parameters comprise indoor temperature, outdoor temperature, unit parameters and power consumption in unit time;
inputting all the sampling parameters in each data set as input parameters into a preset neural network model to obtain output parameters;
and adjusting network parameters of the preset neural network model according to the comparison result between the output parameters and the expected parameters to obtain the energy-saving neural network model.
Specifically, the sampling parameters in the data sets include outdoor temperature, indoor-outdoor temperature difference, unit match number, power consumption in unit time, preset outdoor temperature and preset indoor temperature, the preset indoor temperature is a set temperature of a user in a scene, the preset outdoor temperature is used for indicating a reference temperature of which the outdoor temperature is too high or too low, the preset neural network model is utilized to perform iterative learning on the plurality of data sets so as to learn characteristic relations between different outdoor temperatures, indoor-outdoor temperature difference, unit match number, power consumption in unit time and outdoor temperature labels and indoor temperature labels, namely, the outdoor temperature, the indoor-outdoor temperature difference, the unit match number and the power consumption in unit time are taken as input parameters to a preset neural network model to obtain output parameters, the output parameters include candidate indoor temperature and candidate outdoor temperature, the output parameters are compared with expected parameters, the expected parameters include the preset indoor temperature in the data sets, namely, the candidate indoor temperature and the preset indoor temperature are compared, the candidate outdoor temperature are compared with the preset outdoor temperature, the candidate outdoor temperature are compared with the expected indoor temperature, the output parameters are compared with the expected outdoor temperature, and the output parameters are compared with the expected indoor temperature, and the output parameters are adjusted to obtain the neural network energy-saving model.
And adjusting network parameters of the preset neural network model according to the comparison result between the output parameters and the expected parameters to obtain an energy-saving neural network model, wherein the energy-saving neural network model specifically comprises:
updating a network weight and a network threshold of the preset neural network model according to the calculated difference value when the calculated difference value between the output parameter and the expected parameter is larger than the preset difference value, and executing the step of inputting all the sampling parameters in the untrained data set into the preset neural network model by using the updated preset neural network model as input parameters to obtain the output parameter; or alternatively, the first and second heat exchangers may be,
and taking the preset neural network model corresponding to the output parameter as the energy-saving neural network model under the condition that the calculated difference value between the output parameter and the expected parameter is equal to or smaller than a preset difference value.
Specifically, the calculated difference is obtained by substituting the output parameter and the expected parameter into the inverse error function, and if the calculated difference is greater than the preset difference, the network weight and the network threshold of the preset neural network model are required to be reversely adjusted according to the calculated difference, further deep learning is continuously performed on the data set by using the adjusted preset neural network model until the calculated difference smaller than the preset difference is obtained, at the moment, the minimum error value is obtained by the inverse error function, at the moment, training is stopped, and the neural network model corresponding to the calculated difference is used as a final energy-saving neural network model.
As shown in the figure, in order to obtain the mass unit operation data from the air conditioner manufacturer, to obtain the values of the preset indoor temperature M1 and the preset outdoor temperature M2, the artificial neural network in the artificial intelligence is required to continuously learn and train the specified operation parameters in the mass data, so that the characteristic values are required to be extracted as the input values of training, the characteristic values comprise the outdoor temperature A1, the indoor temperature B1, the unit match number P1, the outdoor and indoor and outdoor temperature difference delta C1 and the power consumption H1 in unit time, the artificial neural network is one of popular deep learning models, the characteristic values are designed through the rolling and pooling operation of three layers of deep stacking, the characteristic values are used as input signals, a plurality of M values are manually marked according to the power consumption analysis in unit time, and the output tolerance value M can be obtained after training by continuously operating and training the convolution layer and the pooling layer of the artificial neural network structure. After training, any characteristic parameter can be input to accurately obtain the tolerance value M.
The method comprises the following steps:
a. the specific parameter index of the following table is obtained through big data (the parameter is an analog non-actual parameter, only used for reference):
b. and normalizing the data by using a matlab-carried premnmx () function, inputting the normalized data as input parameters into a preset neural network model, and comparing the output parameters with corresponding M1 and M2 to determine a calculated difference value.
c. Model building, namely continuously correcting the network weight and the network threshold value of a preset neural network model through training of sample data to enable an error function to descend along the negative gradient direction and approach to expected output. The network model comprises input layer, hidden layer and output layer, wherein the hidden layer can have one or more layers, as shown in figure 4, is a three-layer network model of n×k×m, i.e. n is the number of neurons in the input layer, m is the number of neurons in the output layer, k is the number of neurons in the hidden layer, and the network adopts S-type transfer function
By means of a counter error function->
(ti is the desired output and Oi is the calculated output of the network), thereby continuously adjusting the network weight and threshold value to minimize the error function E.
d. Performing hidden layer design
The related research shows that the neural network with the hidden layer can approach a nonlinear function with arbitrary precision as long as hidden nodes are enough. Thus, a predictive model is built using a three-layer multiple-input single-output network with a hidden layer. Currently, there is no explicit formula for determining the number of neurons in the hidden layer, and only some empirical formulas are used, and the final determination of the number of neurons still needs to be determined empirically and through multiple experiments. The empirical formula is referred to herein in terms of the number of hidden neurons: 
Wherein n is the number of neurons of an input layer, m is the number of neurons of an output layer, and a is [1,10]Constant of the same.
Implementation of the model: the prediction adopts a neural network tool box in MATLAB for training the network, and the specific implementation steps of the prediction model are as follows: the training sample data is normalized and then is input into a network, the excitation functions of a hidden layer and an output layer of the network are respectively tan sig and log sig functions, the training function of the network is traingdx, the performance function of the network is mse, and the number of neurons of the hidden layer is initially set to be 4. Setting network parameters. The number of network iterations epochs is 8000, the expected error gold is 0.00000001, and the learning rate lr is 0.01. After the parameters are set, the training network is started, and learning is completed after the expected error is reached through repeated learning. After the network training is finished, the corresponding preset indoor temperature M1 and the preset outdoor temperature M2 can be predicted by inputting the current indoor temperature, the current outdoor temperature, the number of air conditioner units and the power consumption in unit time into the network.
Summarizing: in the model training stage, multiple inputs and outputs are imported, and the characteristic relation between the inputs and the outputs (M1 and M2) is extracted through linear and nonlinear changes in the model through a network. And in the using stage of the model test, inputting corresponding (A1, B1, P1, C1 and H1), and summing the characteristics of the model according to the characteristic relation and the characteristics obtained in the training stage so as to obtain a corresponding output result.
FIG. 1 is a flow chart of a method for controlling hollow fiber in one embodiment. It should be understood that, although the steps in the flowchart of fig. 1 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 1 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of other steps or sub-steps of other steps.
In one embodiment, as shown in fig. 5, there is provided an air conditioner control device including:
an obtaining module 310, configured to determine a corresponding temperature comparison condition according to the obtained current ambient temperature in a non-use period, where the temperature comparison condition includes an over-temperature condition and an under-temperature condition;
A processing module 320, configured to determine an energy-saving temperature threshold corresponding to the current environmental temperature based on an energy-saving neural network model;
a determining module 330, configured to determine whether a comparison result between the current ambient temperature and the energy-saving temperature threshold meets the temperature comparison condition;
and an operation module 340, configured to operate according to a preset operation mode if the comparison result meets the temperature comparison condition, where the preset operation mode is used to control the operation frequency of the compressor of the air conditioner not to exceed a preset operation frequency.
In one embodiment, the operation module 340 is specifically configured to:
if the comparison result between the current outdoor temperature and the preset outdoor temperature meets the temperature comparison condition, operating according to a preset operation mode; and/or the number of the groups of groups,
and if the comparison result between the current indoor temperature and the preset indoor temperature meets the temperature comparison condition, operating according to a preset operation mode.
In one embodiment, the operation module 340 is further configured to:
under the condition that the temperature comparison condition is an over-high temperature condition, determining that the preset operation mode is a preset refrigeration mode;
and operating according to the preset refrigeration mode.
In one embodiment, the operation module 340 is further configured to:
under the condition that the temperature comparison condition is a temperature too low condition, determining that the preset operation mode is a preset heating mode;
and operating according to the preset heating mode.
In one embodiment, the operation module 340 is further configured to:
determining the starting state of an energy-saving mode;
if the starting state is starting, and the comparison result between the current outdoor temperature and the preset outdoor temperature accords with the temperature comparison condition, the vehicle is operated according to a preset operation mode; or if the starting state is not started, and the comparison result between the current indoor temperature and the preset indoor temperature accords with the temperature comparison condition, and the vehicle is operated according to a preset operation mode.
In one embodiment, the operation module 340 is further configured to:
determining the operation duration of the preset operation mode;
and controlling the air conditioner to enter a shutdown state under the condition that the running time length reaches the preset time length.
In one embodiment, the operation module 340 is further configured to:
and under the condition that a control instruction is received before the operation time reaches the preset time, exiting the preset operation mode and adjusting the operation parameters of the air conditioner according to the control instruction.
In one embodiment, the obtaining module 310 is further configured to:
under the condition that the current outdoor temperature in the current environment temperature acquired in the non-use time period is in a first preset temperature range, taking the temperature-over condition as the temperature comparison condition, wherein the temperature-over condition is used for indicating that the temperature in the current environment temperature is greater than the corresponding temperature in the energy-saving temperature threshold; or alternatively, the first and second heat exchangers may be,
and under the condition that the current outdoor temperature in the current environment temperature acquired in the non-use time period is in a second preset temperature range, taking the temperature too low condition as the temperature comparison condition, wherein the temperature too low condition is used for indicating that the temperature in the current environment temperature is smaller than the corresponding temperature in the energy-saving temperature threshold, and the minimum value of the first preset temperature range is larger than the maximum value of the second preset temperature range.
In one embodiment, the processing module 320 is further configured to:
inputting the current outdoor temperature, the current indoor temperature and unit parameters of the air conditioner into the energy-saving neural network model, and outputting the energy-saving temperature threshold, wherein the energy-saving temperature threshold comprises a preset indoor temperature corresponding to the current indoor temperature and a preset outdoor temperature corresponding to the current outdoor temperature, and the unit parameters comprise the unit match number and the power consumption in unit time.
In one embodiment, the apparatus further comprises a training module for:
acquiring a historical data set, wherein the historical data set comprises a plurality of data sets, and each data set comprises a plurality of sampling parameters, wherein the sampling parameters comprise indoor temperature, outdoor temperature, unit parameters and power consumption in unit time;
inputting all the sampling parameters in each data set as input parameters into a preset neural network model to obtain output parameters;
and adjusting network parameters of the preset neural network model according to the comparison result between the output parameters and the expected parameters to obtain the energy-saving neural network model.
Fig. 6 shows an internal structural diagram of the air conditioner device of one embodiment. As shown in fig. 6, the air conditioning apparatus includes a processor, a memory, a network interface, an input device, and a display screen connected through a system bus. The memory includes a nonvolatile storage medium and an internal memory. The non-volatile storage medium of the air conditioning apparatus stores an operating system, and may also store a computer program which, when executed by a processor, causes the processor to implement an air conditioning control method. The internal memory may also store a computer program that, when executed by the processor, causes the processor to perform the air conditioning control method. The display screen of the air conditioning equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the air conditioning equipment can be a touch layer covered on the display screen, and can also be keys or a remote controller and the like arranged on the shell of the air conditioning equipment.
It will be appreciated by those skilled in the art that the structure shown in fig. 6 is merely a block diagram of a portion of the structure associated with the present application and is not limiting of the air conditioning apparatus to which the present application is applied, and that a particular air conditioning apparatus may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, the air conditioning control apparatus provided herein may be implemented in the form of a computer program that is operable on an air conditioning device as shown in fig. 6. The memory of the air conditioning apparatus may store various program modules constituting the air conditioning control device, such as the acquisition module 310, the processing module 320, the acquisition module 330, and the operation module 340 shown in fig. 5. The computer program constituted by the respective program modules causes the processor to execute the steps in the air conditioner control method of the respective embodiments of the present application described in the present specification.
The air conditioner shown in fig. 6 may determine corresponding temperature comparison conditions including an over-temperature condition and an under-temperature condition according to the acquired current ambient temperature during the non-use period by the acquisition module 310 in the air conditioner control device shown in fig. 5. The air conditioning apparatus may perform determining, by the processing module 320, an energy saving temperature threshold corresponding to the current ambient temperature based on an energy saving neural network model. The air conditioning apparatus may perform determining, by the obtaining module 330, an energy saving temperature threshold corresponding to the current ambient temperature based on the energy saving neural network model. The air conditioning equipment can operate according to a preset operation mode when the comparison result between the current environment temperature and the energy-saving temperature threshold meets the temperature comparison condition through the operation module 340, wherein the preset operation mode is used for controlling the operation frequency of the compressor of the air conditioner not to exceed a preset operation frequency.
In one embodiment, an air conditioning apparatus is provided that includes a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the method of any of the above embodiments when executing the computer program.
In one embodiment, a computer readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements a method as described in any of the above embodiments.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program, which may be stored on a non-transitory computer readable storage medium, and which, when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing is only a specific embodiment of the invention to enable those skilled in the art to understand or practice the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (13)
1. An air conditioner control method, characterized in that the method comprises:
determining corresponding temperature comparison conditions according to the acquired current environmental temperature in a non-use time period, wherein the temperature comparison conditions comprise a temperature too high condition and a temperature too low condition;
determining an energy-saving temperature threshold corresponding to the current environmental temperature based on an energy-saving neural network model;
determining whether a comparison result between the current ambient temperature and the energy-saving temperature threshold meets the temperature comparison condition;
and if the comparison result meets the temperature comparison condition, operating according to a preset operation mode, wherein the preset operation mode is used for controlling the operation frequency of the compressor of the air conditioner not to exceed the preset operation frequency.
2. The method according to claim 1, wherein the current ambient temperature comprises a current outdoor temperature and/or a current indoor temperature, the energy saving temperature threshold comprises a preset outdoor temperature and/or a preset indoor temperature, and the operating according to a preset operation mode if the comparison result meets the temperature comparison condition comprises:
if the comparison result between the current outdoor temperature and the preset outdoor temperature meets the temperature comparison condition, operating according to a preset operation mode; and/or the number of the groups of groups,
And if the comparison result between the current indoor temperature and the preset indoor temperature meets the temperature comparison condition, operating according to a preset operation mode.
3. The method of claim 2, wherein the predetermined mode of operation comprises a predetermined cooling mode, the operating in the predetermined mode of operation comprising:
under the condition that the temperature comparison condition is an over-high temperature condition, determining that the preset operation mode is a preset refrigeration mode;
and operating according to the preset refrigeration mode.
4. The method of claim 2, wherein the predetermined mode of operation further comprises a predetermined heating mode, the operating in the predetermined mode of operation comprising:
under the condition that the temperature comparison condition is a temperature too low condition, determining that the preset operation mode is a preset heating mode;
and operating according to the preset heating mode.
5. The method of claim 2, wherein if the comparison result meets the temperature comparison condition, the method further comprises, prior to operating in a predetermined operating mode:
determining the starting state of an energy-saving mode;
and if the comparison result meets the temperature comparison condition, operating according to a preset operation mode, wherein the operation comprises the following steps:
If the starting state is starting, and the comparison result between the current outdoor temperature and the preset outdoor temperature accords with the temperature comparison condition, the vehicle is operated according to a preset operation mode; or alternatively, the first and second heat exchangers may be,
and if the starting state is not started, and the comparison result between the current indoor temperature and the preset indoor temperature accords with the temperature comparison condition, the vehicle is operated according to a preset operation mode.
6. The method of claim 1, wherein if the comparison result meets the temperature comparison condition, after operating in a preset operation mode, the method further comprises:
determining the operation duration of the preset operation mode;
and controlling the air conditioner to enter a shutdown state under the condition that the running time length reaches the preset time length.
7. The method of claim 6, wherein after the determining the operation duration of the preset operation mode, the method further comprises:
and under the condition that a control instruction is received before the operation time reaches the preset time, exiting the preset operation mode and adjusting the operation parameters of the air conditioner according to the control instruction.
8. The method of claim 1, wherein determining the corresponding temperature alignment condition from the acquired current ambient temperature during the non-use period comprises:
Under the condition that the current outdoor temperature in the current environment temperature acquired in the non-use time period is in a first preset temperature range, taking the temperature-over condition as the temperature comparison condition, wherein the temperature-over condition is used for indicating that the temperature in the current environment temperature is greater than the corresponding temperature in the energy-saving temperature threshold; or alternatively, the first and second heat exchangers may be,
and under the condition that the current outdoor temperature in the current environment temperature acquired in the non-use time period is in a second preset temperature range, taking the temperature too low condition as the temperature comparison condition, wherein the temperature too low condition is used for indicating that the temperature in the current environment temperature is smaller than the corresponding temperature in the energy-saving temperature threshold, and the minimum value of the first preset temperature range is larger than the maximum value of the second preset temperature range.
9. The method of claim 1, wherein the current ambient temperature comprises a current indoor temperature and a current outdoor temperature, wherein the determining an energy-saving temperature threshold corresponding to the current ambient temperature based on an energy-saving neural network model comprises:
inputting the current outdoor temperature, the current indoor temperature and unit parameters of the air conditioner into the energy-saving neural network model, and outputting the energy-saving temperature threshold, wherein the energy-saving temperature threshold comprises a preset indoor temperature corresponding to the current indoor temperature and a preset outdoor temperature corresponding to the current outdoor temperature, and the unit parameters comprise the unit match number and the power consumption in unit time.
10. The method of claim 1, wherein prior to determining the corresponding temperature alignment condition based on the obtained current ambient temperature during the non-use period, the method further comprises:
acquiring a historical data set, wherein the historical data set comprises a plurality of data sets, and each data set comprises a plurality of sampling parameters, wherein the sampling parameters comprise indoor temperature, outdoor temperature, unit parameters and power consumption in unit time;
inputting all the sampling parameters in each data set as input parameters into a preset neural network model to obtain output parameters;
and adjusting network parameters of the preset neural network model according to the comparison result between the output parameters and the expected parameters to obtain the energy-saving neural network model.
11. An air conditioner control device, characterized in that the device comprises:
the acquisition module is used for determining corresponding temperature comparison conditions according to the acquired current environment temperature in the non-use time period, wherein the temperature comparison conditions comprise a temperature too high condition and a temperature too low condition;
the processing module is used for determining an energy-saving temperature threshold corresponding to the current environment temperature based on an energy-saving neural network model;
The determining module is used for determining whether the comparison result between the current environment temperature and the energy-saving temperature threshold meets the temperature comparison condition or not;
and the operation module is used for operating according to a preset operation mode if the comparison result meets the temperature comparison condition, wherein the preset operation mode is used for controlling the operation frequency of the compressor of the air conditioner not to exceed the preset operation frequency.
12. An air conditioning apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method of any one of claims 1 to 10 when the computer program is executed by the processor.
13. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 10.
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