CN115200171A - Air conditioner control method and system based on time series prediction - Google Patents
Air conditioner control method and system based on time series prediction Download PDFInfo
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- CN115200171A CN115200171A CN202210831193.XA CN202210831193A CN115200171A CN 115200171 A CN115200171 A CN 115200171A CN 202210831193 A CN202210831193 A CN 202210831193A CN 115200171 A CN115200171 A CN 115200171A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/54—Control or safety arrangements characterised by user interfaces or communication using one central controller connected to several sub-controllers
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/52—Indication arrangements, e.g. displays
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/61—Control or safety arrangements characterised by user interfaces or communication using timers
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/70—Control systems characterised by their outputs; Constructional details thereof
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/10—Temperature
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B30/00—Energy efficient heating, ventilation or air conditioning [HVAC]
- Y02B30/70—Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating
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Abstract
The invention relates to the technical field of machine room air conditioner control, discloses an air conditioner control method and system based on time sequence prediction, and aims to solve the problems of poor operation effect and frequent start and stop of the existing air conditioner control method of a base station machine room, and the scheme mainly comprises the following steps: creating a time series prediction model for predicting an indoor temperature; acquiring the current indoor temperature and the on-off state of an air conditioner of a base station machine room in real time; when the air conditioner is in a closed state, judging whether temperature prediction is carried out or not according to the size relation between the current indoor temperature and a first preset value, and judging whether the air conditioner is turned on or not according to the size relation between predicted temperature data and a second preset value; and when the air conditioner is in an opening state, judging whether to predict the temperature according to the magnitude relation between the current indoor temperature and the third preset value, and judging whether to close the air conditioner according to the magnitude relation between predicted temperature data and the second preset value. The invention improves the operation effect and the service life of the air conditioner, and is particularly suitable for the base station room.
Description
Technical Field
The invention relates to the technical field of air conditioner control of a machine room, in particular to an air conditioner control method and system based on time series prediction.
Background
At present, in the energy consumption of a base station, the consumption proportion of an air conditioner side is high. Because the structure and the theory of the air-conditioning system are complex, most operation and maintenance personnel set corresponding temperature control upper and lower limit threshold values for starting and stopping the air conditioner for a long time or seasonally at present. For example, the air conditioner is started when the temperature rises to the upper threshold (e.g., 32 ℃) and is turned off when the temperature falls to the lower threshold (e.g., 30 ℃), simply and roughly. However, the traditional control mode of the air conditioning system, which is a typical complex multivariable system with high nonlinearity, coupling, time-varying property and uncertainty, is difficult to achieve an ideal operation effect through simple threshold value setting control, and in the practical application process, the air conditioning condition, the service bearing and the environmental change of each machine room are greatly different, the traditional control model cannot be rapidly adapted to all the machine room conditions, and meanwhile, frequent start and stop of the air conditioner can be caused due to improper setting of the upper and lower limits, so that the operation effect is influenced, and the service life of the air conditioner is also influenced.
Disclosure of Invention
The invention aims to solve the problems of poor operation effect and frequent start and stop of the existing air conditioner control method of a base station room, and provides an air conditioner control method and system based on time sequence prediction.
The technical scheme adopted by the invention for solving the technical problems is as follows:
on one hand, the air conditioner control method based on time series prediction is provided and applied to a base station room, and comprises the following steps:
step 1, creating a time series prediction model for predicting indoor temperature;
step 2, acquiring the current indoor temperature and the on-off state of an air conditioner of a base station machine room in real time, if the air conditioner is in the off state, entering step 3, and if the air conditioner is in the on state, entering step 4;
step 3, judging whether the current indoor temperature is greater than or equal to a first preset value, if not, keeping the air conditioner closed, if so, predicting a first temperature sequence of a next time window through the time sequence prediction model, and judging whether the highest temperature in the first temperature sequence is greater than or equal to a second preset value, if so, starting the air conditioner, otherwise, keeping the air conditioner closed, and the first preset value is smaller than the second preset value;
and 4, judging whether the current indoor temperature is less than or equal to a third preset value, if not, keeping the air conditioner on, if so, predicting a second temperature sequence of a next time window after the air conditioner is off through the time sequence prediction model, judging whether the highest temperature in the second temperature sequence is greater than or equal to the second preset value, if so, keeping the air conditioner on, otherwise, closing the air conditioner, and enabling the third preset value to be less than the second preset value.
Further, the creating of the time series prediction model for predicting the indoor temperature specifically includes:
historical data based on a time sequence are obtained, a time sequence prediction model used for predicting indoor temperature is trained according to the historical data, and the historical data at least comprise the indoor temperature, the outdoor temperature and equipment load of a base station machine room.
Further, the predicting the first temperature sequence or the second temperature sequence of the next time window by the time sequence prediction model specifically includes:
the method comprises the steps of obtaining current time information, current outdoor temperature and current equipment load of a base station machine room, inputting the current indoor temperature, the current time information, the current outdoor temperature, the current equipment load and time information corresponding to a next time window into a time sequence prediction model, and obtaining a first temperature sequence or a second temperature sequence of the next time window.
Further, the step 3 further comprises:
and if the highest temperature in the first temperature sequence is less than a second preset value, updating the first preset value to the highest temperature in the first temperature sequence.
Further, the second preset value is determined according to the warning temperature of the base station machine room, and the warning temperature is determined according to the base station efficiency.
Further, the method further comprises:
and if the air conditioner is in a closed state and the current indoor temperature is greater than or equal to the warning temperature of the base station machine room, starting the air conditioner, generating an alarm signal and recording alarm information.
In another aspect, an air conditioner control system based on time series prediction is provided, which is applied to a base station room, and includes:
a creation module for creating a time series prediction model for predicting an indoor temperature;
the acquisition module is used for acquiring the current indoor temperature and the on-off state of an air conditioner of a base station machine room in real time;
the control module is used for judging whether the current indoor temperature is greater than or equal to a first preset value or not when the air conditioner is in a closed state, if not, keeping the air conditioner closed, if so, predicting a first temperature sequence of a next time window through the time sequence prediction model, judging whether the highest temperature in the first temperature sequence is greater than or equal to a second preset value or not, if so, starting the air conditioner, otherwise, keeping the air conditioner closed, and enabling the first preset value to be smaller than the second preset value; and
when the air conditioner is in an open state, judging whether the current indoor temperature is less than or equal to a third preset value, if not, keeping the air conditioner open, if so, predicting a second temperature sequence of a next time window after the air conditioner is closed through the time sequence prediction model, judging whether the highest temperature in the second temperature sequence is greater than or equal to a second preset value, if so, keeping the air conditioner open, otherwise, closing the air conditioner, and enabling the third preset value to be less than the second preset value.
Further, the creating of the time series prediction model for predicting the indoor temperature specifically includes:
historical data based on a time sequence are obtained, a time sequence prediction model used for predicting indoor temperature is trained according to the historical data, and the historical data at least comprise the indoor temperature, the outdoor temperature and equipment load of a base station machine room.
Further, the predicting the first temperature sequence or the second temperature sequence of the next time window by the time sequence prediction model specifically includes:
and acquiring current time information, current outdoor temperature and current equipment load of a base station room, and inputting the current indoor temperature, the current time information, the current outdoor temperature, the current equipment load and time information corresponding to a next time window into the time sequence prediction model to obtain a first temperature sequence or a second temperature sequence of the next time window.
Further, the control module is further configured to:
and if the highest temperature in the first temperature sequence is smaller than a second preset value, updating the first preset value to the highest temperature in the first temperature sequence.
The beneficial effects of the invention are: according to the air conditioner control method and system based on time series prediction, the time series prediction model is established through historical data, the start and stop of the air conditioner are controlled according to the current indoor temperature and the temperature data of the next time window obtained through prediction, and the operation effect of the air conditioner is improved. In addition, the invention also dynamically sets the upper and lower temperature control limits, so that the air conditioner cannot be started and stopped at high frequency while energy conservation is ensured, and the service life of the air conditioner is prolonged.
Drawings
Fig. 1 is a schematic flowchart of an air conditioner control method based on time series prediction according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an air conditioning control system based on time series prediction according to an embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
The invention provides an air conditioner control method and system based on time series prediction, which are applied to a base station room and mainly comprise the following technical scheme: the creation module creates a time series prediction model for predicting the indoor temperature; the acquisition module acquires the current indoor temperature and the on-off state of an air conditioner of a base station machine room in real time; when the air conditioner is in a closed state, the control module judges whether the current indoor temperature is greater than or equal to a first preset value or not, if not, the air conditioner is kept closed, if yes, the first temperature sequence of the next time window is predicted through the time sequence prediction model, whether the highest temperature in the first temperature sequence is greater than or equal to a second preset value or not is judged, if yes, the air conditioner is started, otherwise, the air conditioner is kept closed, and the first preset value is smaller than the second preset value; and when the air conditioner is in an opening state, judging whether the current indoor temperature is less than or equal to a third preset value, if not, keeping the air conditioner on, if so, predicting a second temperature sequence of a next time window after the air conditioner is closed through the time sequence prediction model, judging whether the highest temperature in the second temperature sequence is greater than or equal to the second preset value, if so, keeping the air conditioner on, otherwise, closing the air conditioner, and the third preset value is less than the second preset value.
Specifically, the present invention requires setting three preset temperature values in advance, which are a first preset value, a second preset value and a third preset value, respectively, where the second preset value is greater than the first preset value, and the first preset value is greater than the third preset value. The first preset value is a threshold value for judging whether to predict the temperature when the air conditioner is in a closed state, namely when the current indoor temperature is greater than or equal to the first preset value, the temperature is predicted, and whether to start the air conditioner is judged according to the size relation between the predicted temperature and the second preset value. And the third preset value is a threshold value for judging whether to perform temperature prediction when the air conditioner is in an on state, namely when the current indoor temperature is less than or equal to the third preset value, the air conditioner is supposed to be turned off and the temperature prediction is performed, and whether to turn off the air conditioner is judged according to the size relation between the predicted temperature and the second preset value. According to the invention, the first preset value and the third preset value for judging whether temperature prediction is carried out are respectively set, and whether the running state of the air conditioner is changed or not is determined according to the predicted temperature value, so that the problems of poor running effect of the air conditioner and frequent start and stop of the air conditioner caused by the existing fixed temperature control threshold value are avoided, and meanwhile, the energy-saving effect and the service life of the air conditioner are improved.
Examples
The air conditioner control method based on time series prediction, which is provided by the embodiment of the invention, is applied to a base station room, and comprises the following steps as shown in figure 1:
step 1, establishing a time series prediction model for predicting indoor temperature;
in this embodiment, historical data based on a time sequence may be obtained, and a time sequence prediction model for predicting indoor temperature may be trained according to the historical data, where the historical data at least includes indoor temperature, outdoor temperature, and device load of a base station room.
Step 2, acquiring the current indoor temperature T and the on-off state of an air conditioner of a base station machine room in real time, if the air conditioner is in the off state, entering step 3, and if the air conditioner is in the on state, entering step 4;
in the embodiment, the current indoor temperature T can be acquired in real time through the indoor temperature sensor; meanwhile, the control module of the air conditioner can send the current on-off state of the air conditioner in a communication mode in real time, wherein the communication mode can be wired or wireless, such as Bluetooth, wiFi and the like.
In this embodiment, the control of the air conditioner state is realized by setting the start-stop tag r, r =0, the air conditioner is turned off, r =1, and the air conditioner is turned on.
Step 3, judging whether the current indoor temperature T is greater than or equal to a first preset value T 1 If not, the air conditioner is kept closed, and if yes, the next time window t is predicted through the time series prediction model u And determining the highest temperature T in the first temperature sequence h1 Whether it is greater than or equal to a second preset value T 2 If yes, the air conditioner is started, otherwise, the air conditioner is kept closed, and the first preset value T is set 1 Less than a second predetermined value T 2 ；
The embodiment is based on the warning temperature T of the base station room a Determining a second preset value T 2 I.e. T 2 ＝T a -u, wherein uIs risk tolerant.
The embodiment determines the warning temperature T according to the efficiency of the base station a When the indoor temperature reaches the warning temperature T a Time, base station efficiency may be affected. When the air conditioner is in a closed state, judging the current indoor temperature T and the warning temperature T of the base station machine room a If T is greater than or equal to T a And if so, starting the air conditioner, and simultaneously generating an alarm signal and recording alarm information.
When the air conditioner is in a closed state, if the current indoor temperature T does not reach a first preset value T 1 I.e. when T < T 1 When the air conditioner is kept off, r =0; if the current indoor temperature T rises to reach the first preset value T 1 I.e. when T.gtoreq.T 1 Predicting the next time window t by a time series prediction model u And according to the maximum temperature T in the first temperature sequence h1 And a second preset value T 2 Whether the air conditioner is started or not is judged according to the magnitude relation of the air conditioner. In particular, if T h1 ≥T 2 ＝T a U, turn on air conditioner, r =1, if T h1 ＜T 2 ＝T a U, then keep the air conditioner off, r =0. Wherein, t u The time window for turning on the air conditioner is related to the lag of the cooling effect of the air conditioner.
In addition, this embodiment is at T h1 ＜T 2 ＝T a U, the first preset value T is also set 1 Is updated to T h1 The dynamic modification of the upper limit and the lower limit of the temperature control is realized, the energy conservation is ensured, the high-frequency starting and stopping of the air conditioner are avoided, and the operation effect and the service life of the air conditioner are improved.
In this embodiment, the next time window t is predicted by the time series prediction model u The first temperature sequence of (1) specifically includes:
obtaining current time information, current outdoor temperature and current equipment load of a base station machine room, and enabling the current indoor temperature, the current time information, the current outdoor temperature, the current equipment load and a next time window t u Inputting the corresponding time information into the time sequence prediction model to obtain the next time window t u First temperature ofA sequence of degrees.
Step 4, judging whether the current indoor temperature T is less than or equal to a third preset value T 3 If not, the air conditioner is kept on, and if yes, the next time window t after the air conditioner is closed is predicted through the time series prediction model d And determining the highest temperature T in the second temperature sequence h2 Whether it is greater than or equal to a second preset value T 2 If yes, keeping the air conditioner on, otherwise, turning off the air conditioner, and obtaining a third preset value T 3 Less than a second predetermined value T 2 。
Specifically, when the air conditioner is in an on state, if the current indoor temperature T does not decrease to the third preset value T 3 I.e. when T > T 3 When the air conditioner is started, the air conditioner is kept started, and r =1; if the current indoor temperature T is reduced to a third preset value T 3 I.e. when T is less than T 3 Then, the next time window t after the air conditioner is closed is predicted through the time series prediction model d And according to the maximum temperature T in the second temperature sequence h2 And a second preset value T 2 Whether the air conditioner is turned off is judged according to the magnitude relation of the air conditioner. In particular, if T h2 ≥T 2 ＝T a U, keep the air conditioner on, r =1, if T h2 ＜T 2 ＝T a U, then turn off air conditioner, r =0. Wherein, t d And the time window for saving energy of the air conditioner is related to the number of the air conditioners starting and stopping.
In summary, in the embodiment, the time series prediction model is created through the historical data, and the start and stop of the air conditioner are controlled according to the current indoor temperature and the predicted temperature data of the next time window, so that the operation effect of the air conditioner is improved. And this embodiment still sets for the control by temperature change bound through the developments, when guaranteeing energy-conservation, can not do the high frequency to air conditioning equipment and open and stop, has improved the life of air conditioner.
Based on the above technical solution, this embodiment further provides an air conditioner control system based on time series prediction, which is applied to a base station room, as shown in fig. 2, and includes:
a creation module for creating a time series prediction model for predicting an indoor temperature;
the acquisition module is used for acquiring the current indoor temperature T and the on-off state of an air conditioner of the base station machine room in real time;
a control module for judging whether the current indoor temperature T is greater than or equal to a first preset value T when the air conditioner is in a closed state 1 If not, the air conditioner is kept closed, and if yes, the next time window t is predicted through the time sequence prediction model u And determining the highest temperature T in the first temperature sequence h1 Whether it is greater than or equal to a second preset value T 2 If yes, the air conditioner is started, otherwise, the air conditioner is kept closed, and the first preset value T is set 1 Less than a second predetermined value T 2 (ii) a And
when the air conditioner is in an opening state, judging whether the current indoor temperature T is less than or equal to a third preset value T 3 If not, the air conditioner is kept on, and if yes, the next time window t after the air conditioner is closed is predicted through the time series prediction model d And determining the highest temperature T in the second temperature sequence h2 Whether it is greater than or equal to a second preset value T 2 If yes, keeping the air conditioner on, otherwise, closing the air conditioner, and obtaining a third preset value T 3 Less than a second predetermined value T 2 。
It can be understood that, because the air-conditioning control system based on time series prediction according to the embodiment of the present invention is a system for implementing the air-conditioning control method based on time series prediction according to the embodiment, the system disclosed in the embodiment is relatively simple in description because it corresponds to the method disclosed in the embodiment, and the relevant points can be referred to the partial description of the method.
Claims (10)
1. The air conditioner control method based on time series prediction is applied to a base station room and is characterized by comprising the following steps of:
step 1, creating a time series prediction model for predicting indoor temperature;
step 2, acquiring the current indoor temperature and the on-off state of an air conditioner of a base station machine room in real time, if the air conditioner is in the off state, entering step 3, and if the air conditioner is in the on state, entering step 4;
step 3, judging whether the current indoor temperature is greater than or equal to a first preset value, if not, keeping the air conditioner closed, if so, predicting a first temperature sequence of a next time window through the time sequence prediction model, and judging whether the highest temperature in the first temperature sequence is greater than or equal to a second preset value, if so, starting the air conditioner, otherwise, keeping the air conditioner closed, and the first preset value is smaller than the second preset value;
and 4, judging whether the current indoor temperature is less than or equal to a third preset value, if not, keeping the air conditioner on, if so, predicting a second temperature sequence of a next time window after the air conditioner is off through the time sequence prediction model, judging whether the highest temperature in the second temperature sequence is greater than or equal to the second preset value, if so, keeping the air conditioner on, otherwise, closing the air conditioner, and enabling the third preset value to be less than the second preset value.
2. The air-conditioning control method based on time-series prediction according to claim 1, wherein the creating of the time-series prediction model for predicting the indoor temperature specifically includes:
historical data based on a time sequence are obtained, a time sequence prediction model used for predicting indoor temperature is trained according to the historical data, and the historical data at least comprise the indoor temperature, the outdoor temperature and equipment load of a base station machine room.
3. The air conditioner control method based on time series prediction according to claim 2, wherein the predicting the first temperature series or the second temperature series of the next time window by the time series prediction model specifically comprises:
and acquiring current time information, current outdoor temperature and current equipment load of a base station room, and inputting the current indoor temperature, the current time information, the current outdoor temperature, the current equipment load and time information corresponding to a next time window into the time sequence prediction model to obtain a first temperature sequence or a second temperature sequence of the next time window.
4. The air conditioner control method based on time-series prediction as set forth in claim 1, wherein the step 3 further includes:
and if the highest temperature in the first temperature sequence is smaller than a second preset value, updating the first preset value to the highest temperature in the first temperature sequence.
5. The air conditioner control method based on time series prediction as claimed in claim 1, wherein the second preset value is determined according to an alarm temperature of a base station room, and the alarm temperature is determined according to base station efficiency.
6. The air conditioner controlling method based on time-series prediction as set forth in claim 5, wherein the method further comprises:
and if the air conditioner is in a closed state and the current indoor temperature is greater than or equal to the warning temperature of the base station machine room, starting the air conditioner, generating an alarm signal and recording alarm information.
7. Air conditioner control system based on time series prediction is applied to base station computer lab, its characterized in that includes:
a creation module for creating a time series prediction model for predicting an indoor temperature;
the acquisition module is used for acquiring the current indoor temperature and the on-off state of an air conditioner of a base station machine room in real time;
the control module is used for judging whether the current indoor temperature is greater than or equal to a first preset value or not when the air conditioner is in a closed state, if not, keeping the air conditioner closed, if so, predicting a first temperature sequence of a next time window through the time sequence prediction model, judging whether the highest temperature in the first temperature sequence is greater than or equal to a second preset value or not, if so, starting the air conditioner, otherwise, keeping the air conditioner closed, and enabling the first preset value to be smaller than the second preset value; and
when the air conditioner is in an open state, judging whether the current indoor temperature is less than or equal to a third preset value, if not, keeping the air conditioner open, if so, predicting a second temperature sequence of a next time window after the air conditioner is closed through the time sequence prediction model, judging whether the highest temperature in the second temperature sequence is greater than or equal to the second preset value, if so, keeping the air conditioner open, otherwise, closing the air conditioner, and the third preset value is less than the second preset value.
8. The air conditioning control system based on time series prediction as set forth in claim 7, wherein the creating of the time series prediction model for predicting the indoor temperature specifically includes:
obtaining historical data based on a time sequence, and training a time sequence prediction model for predicting indoor temperature according to the historical data, wherein the historical data at least comprises the indoor temperature, the outdoor temperature and the equipment load of a base station room.
9. The air conditioning control system based on time series prediction as claimed in claim 8, wherein the predicting the first temperature series or the second temperature series of the next time window by the time series prediction model specifically comprises:
and acquiring current time information, current outdoor temperature and current equipment load of a base station room, and inputting the current indoor temperature, the current time information, the current outdoor temperature, the current equipment load and time information corresponding to a next time window into the time sequence prediction model to obtain a first temperature sequence or a second temperature sequence of the next time window.
10. The air conditioning control system based on time series prediction of claim 7, wherein the control module is further configured to:
and if the highest temperature in the first temperature sequence is smaller than a second preset value, updating the first preset value to the highest temperature in the first temperature sequence.
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