Intelligent heating method and device based on machine learning and electronic equipment

Abstract

The embodiment of the invention provides an intelligent heating method and device based on machine learning and electronic equipment, and the method comprises the steps that preset temperature adjustment operation on indoor temperature is controlled, the temperature change condition of the indoor temperature is obtained, and the temperature response performance of a room is determined; acquiring a preset target temperature, determining a regulation and control temperature and a time pre-threshold thereof according to the target temperature and the temperature response performance, and determining a target control strategy according to the temperature response performance and the regulation and control temperature; acquiring an environment state in real time, identifying the environment state through a pre-trained environment identification model, updating the temperature response performance, and adjusting the target control strategy through the updated temperature response performance; according to the method provided by the embodiment of the invention, through accurate thermal energy compensation, the indoor temperature can be always kept within a set numerical value or range, and discomfort caused by large-range fluctuation of the temperature is reduced.

Description

Technical Field

[0001] This application relates to, but is not limited to, the technical field of heating and ventilation equipment, and particularly relates to an intelligent heating method, device, and electronic device based on machine learning. Background Art

[0002] In traditional heating and ventilation systems, temperature regulation is usually based on fixed control strategies, such as PID control. Although these methods can maintain the indoor temperature to a certain extent, in the face of complex environmental changes, the heating and ventilation system dominated by traditional PID control is greatly affected by the real-time indoor temperature. In order to keep the indoor temperature constant or within a suitable range, the heating and ventilation system needs to frequently perform heating and cooling operations according to the fluctuations of the indoor temperature, thus affecting the actual experience of users. Summary of the Invention

[0003] The following is an overview of the subject matter described in detail in this article. This overview is not intended to limit the scope of protection of the claims.

[0004] Embodiments of this application provide an intelligent heating method, device, and electronic device based on machine learning. Through precise thermal energy compensation, the indoor temperature can always be maintained at a set value or within a range, reducing the discomfort caused by temperature fluctuations.

[0005] To achieve the above object, a first aspect of the embodiments of this application proposes an intelligent heating method based on machine learning, including: controlling a preset temperature adjustment operation on the indoor temperature, obtaining the temperature change situation of the indoor temperature, and determining the temperature response performance of the room; obtaining a preset target temperature, determining a regulated temperature and its time lead threshold according to the target temperature and the temperature response performance, and determining a target control strategy according to the temperature response performance and the regulated temperature; obtaining the environmental state in real time, identifying the environmental state through a pre-trained environmental recognition model, updating the temperature response performance, and adjusting the target control strategy through the updated temperature response performance.

[0006] In some embodiments, the controlling a preset temperature adjustment operation on the indoor temperature, obtaining the temperature change situation of the indoor temperature, and determining the temperature response performance of the room includes: controlling the indoor temperature to rise by a preset first temperature difference under the rated power output condition, obtaining the first time length of the heating process, and determining the active heating efficiency according to the first temperature difference and the first time length; controlling the indoor temperature to naturally decrease by a preset second temperature difference, obtaining the second time length of the natural cooling process, and determining the natural cooling efficiency according to the second temperature difference and the second time length; determining the temperature response performance of the room according to the active heating efficiency and the natural cooling efficiency.

[0007] In some embodiments, the control performs a preset temperature adjustment operation on the indoor temperature, obtains the temperature change of the indoor temperature, and determines the temperature response performance of the room, further including: obtaining the target temperature and a preset temperature regulation duration, determining the second temperature difference according to the temperature regulation duration, and determining the first temperature difference according to a preset heating-up duration coefficient and the temperature regulation duration; performing the temperature adjustment operation through the first temperature difference and the second temperature difference to determine the temperature response performance.

[0008] In some embodiments, obtaining a preset target temperature, determining a regulated temperature and its time lead threshold according to the target temperature and the temperature response performance, and determining a target control strategy according to the temperature response performance and the regulated temperature, includes: obtaining an initial control strategy, where the initial control strategy includes the target temperature, a regulation start time point and a regulation end time point calculated based on the real-time indoor temperature, the regulation start time point represents the time point when the temperature adjustment starts, and the regulation end time point represents the time point when the temperature adjustment stops; determining a temperature reaching time point between the regulation start time point and the regulation end time point based on the time lead threshold, where the temperature reaching time point represents the time point when the indoor temperature is adjusted to the regulated temperature; obtaining electricity price information, determining a temperature adjustment power according to the electricity price information and the temperature reaching time point, determining a temperature adjustment duration according to the temperature adjustment power, the indoor temperature and the regulated temperature, determining a new regulation start time point according to the temperature adjustment duration and the temperature reaching time point, and obtaining the target control strategy.

[0009] In some embodiments, the environmental state is obtained in real time, the environmental state is identified through a pre-trained environment recognition model, the temperature response performance is updated, and the target control strategy is adjusted through the updated temperature response performance, including: obtaining the indoor temperature in real time, determining a qualified time threshold based on the indoor temperature and the target temperature, where the qualified time threshold represents the time required to adjust the indoor temperature to the target temperature based on the temperature adjustment power; obtaining a real-time time point, if the difference between the real-time time point and the temperature reaching time point is greater than the qualified time threshold, no corresponding temperature adjustment output is started; if the difference between the real-time time point and the temperature reaching time point is equal to the qualified time threshold, output is performed based on the temperature adjustment power in the latest target control strategy; during the output process with the temperature adjustment power, the temperature change of the performed temperature adjustment process is inspected based on a preset inspection frequency, and the temperature adjustment power is adjusted in real time according to the difference between the real-time time point and the temperature reaching time point.

[0010] In some embodiments, obtaining a preset target temperature, determining a regulated temperature according to the target temperature and the temperature response performance, and determining a target control strategy according to the temperature response performance and the regulated temperature further includes: controlling to operate at the temperature adjustment power so that the indoor temperature is adjusted to the regulated temperature; determining a constant temperature power according to the temperature response performance, and controlling to continuously operate at the constant temperature power.

[0011] In some embodiments, the method of obtaining the environmental state in real time, identifying the environmental state through a pre-trained environmental recognition model, updating the temperature response performance, and adjusting the target control strategy through the updated temperature response performance includes: during the operation at the constant temperature power, obtaining the indoor temperature in real time, and inputting the temperature response performance for determining the constant temperature power and the real-time indoor temperature into the environmental recognition model; calling the environmental recognition model, and when the change amplitude of the indoor temperature is greater than a preset temperature fluctuation threshold, updating the temperature response performance based on the change rate of the indoor temperature; obtaining a preset regulation duration, determining a dynamic adjustment power according to the real-time indoor temperature and the regulation duration, and controlling to operate at the dynamic adjustment power so that the indoor temperature is adjusted to the regulated temperature again after the regulation duration; the environmental recognition model determines a new constant temperature power based on the updated temperature response performance and the target temperature, and controls to operate at the new constant temperature power.

[0012] In some embodiments, the intelligent heating method further includes: obtaining the indoor temperature in real time, and determining the actual temperature adjustment efficiency through the indoor temperature and the initial temperature of the room; determining a temperature adjustment verification function according to the actual temperature adjustment efficiency and the temperature response efficiency, and judging the effectiveness of the target control strategy through the temperature adjustment verification function.

[0013] To achieve the above object, a second aspect of the embodiments of the present application provides an electronic device, which includes a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, the intelligent heating method described in the first aspect above is implemented.

[0014] To achieve the above object, a third aspect of the embodiments of the present application provides a storage medium, which is a computer-readable storage medium, the storage medium stores a computer program, and when the computer program is executed by a processor, the intelligent heating method described in the first aspect above is implemented.

[0015] The embodiments of the present application at least include the following beneficial effects: Before substantially regulating the indoor temperature of a room, through a preset temperature regulation operation on the indoor temperature, the change of the indoor temperature is obtained in real time to determine the temperature response performance of the room; after determining the temperature response performance of the room, combined with the preset target temperature, a target control strategy is determined, and the indoor temperature of the room is adjusted in real time through the target control strategy, that is, according to the characteristics of different rooms and the heating and heat dissipation conditions, the device power output is dynamically adjusted to maintain the indoor thermal balance. By dynamically adjusting the target control strategy, the overheating or overcooling caused by environmental changes in the traditional PID control method is avoided, thereby reducing the energy consumption of the system. During the process of adjusting the indoor temperature, the user may change the state of the room, and the environment of the room changes, thus affecting the temperature response performance of the room. By obtaining the environmental state in real time and updating the temperature response performance, it is possible to adapt to different environmental conditions and ensure the best temperature control in various situations.

[0016] Other features and advantages of the present application will be described in the following specification, and in part, will be obvious from the specification, or will be understood by implementing the present application. The objectives and other advantages of the present application can be achieved and obtained by the structures specifically pointed out in the specification, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings are used to provide a further understanding of the technical solutions of the present application, and constitute a part of the specification. They are used to explain the technical solutions of the present application together with the embodiments of the present application, and do not constitute a limitation to the technical solutions of the present application.

[0018] Figure 1 It is an optional flowchart of the intelligent heating method based on machine learning provided by the embodiments of the present application; Figure 2 It is an optional flowchart of calculating the temperature response performance provided by the embodiments of the present application; Figure 3 It is an optional flowchart of determining the target control strategy provided by the embodiments of the present application; Figure 4 It is an optional flowchart of the regulation process provided by the embodiments of the present application; Figure 5 It is an optional flowchart of determining the effectiveness of temperature control provided by the embodiments of the present application; Figure 6 It is an optional structural diagram of the heating control device provided by the embodiments of the present application; Figure 7 It is an optional hardware structural diagram of the electronic device provided by the embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] In order to make the objectives, technical solutions and advantages of the present application more clear and understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0020] In the description of the present application, the meaning of "a number of" is one or more, the meaning of "a plurality of" is two or more, "greater than", "less than", "exceeding", etc. are understood as not including the present number, and "above", "below", "within", etc. are understood as including the present number.

[0021] It should be noted that although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order from the module division in the device or the flowchart. Terms such as "first", "second", etc. in the specification, claims or the above-mentioned drawings are used to distinguish similar objects and do not necessarily need to be used to describe a specific order or sequence.

[0022] In the related art, the heating and ventilation system dominated by traditional PID control is greatly affected by the real-time indoor temperature. In order to keep the indoor temperature constant or within a suitable range, the heating and ventilation system needs to frequently perform heating and cooling operations according to the fluctuations of the indoor temperature.

[0023] Based on this, the embodiments of the present application provide an intelligent heating method, device and electronic device based on machine learning. Through precise thermal energy compensation, the indoor temperature can always be maintained at a set value or within a range, reducing the discomfort caused by temperature fluctuations.

[0024] The intelligent heating method, device and electronic device based on machine learning provided by the embodiments of the present application will be specifically described through the following embodiments. First, the intelligent heating method based on machine learning in the embodiments of the present application will be described.

[0025] This application can be used in numerous general-purpose or special-purpose computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and so on. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This application can also be practiced in a distributed computing environment where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0026] The following further elaborates on the embodiments of this application in conjunction with the accompanying drawings.

[0027] As Figure 1 shown, Figure 1 FIG. is an alternative flowchart of the intelligent heating method based on machine learning provided by the embodiment of this application. The intelligent heating method based on machine learning can be executed by a heating and ventilation system terminal, or can also be executed by a server in cooperation with the heating and ventilation system terminal. The intelligent heating method based on machine learning includes but is not limited to the following steps S110 to S130: Step S110, control a preset temperature adjustment operation for the indoor temperature, obtain the temperature change of the indoor temperature, and determine the temperature response performance of the room; Step S120, obtain a preset target temperature, determine the regulated temperature and its time lead threshold according to the target temperature and the temperature response performance, and determine the target control strategy according to the temperature response performance and the regulated temperature; Step S130, obtain the environmental state in real time, identify the environmental state through a pre-trained environmental recognition model, update the temperature response performance, and adjust the target control strategy through the updated temperature response performance.

[0028] Based on this, the temperature response performance refers to the ability of a room or system to respond to temperature changes, that is, the speed and degree of temperature change when heat is input or output. It reflects the thermophysical properties of the room or system and its adaptability to temperature changes. Before substantially regulating the indoor temperature of the room, by performing a preset temperature adjustment operation on the indoor temperature, the indoor temperature change situation is obtained in real time to determine the temperature response performance of the room; after determining the temperature response performance of the room, combined with the preset target temperature, a target control strategy is determined, and the indoor temperature of the room is adjusted in real time through the target control strategy, that is, according to the characteristics of different rooms and the heating and heat dissipation situations, the device power output is dynamically adjusted to maintain the indoor thermal balance. By dynamically adjusting the target control strategy, the overheating or cooling caused by environmental changes in the traditional PID control method is avoided, thereby reducing the energy consumption of the system. During the process of adjusting the indoor temperature, the user may change the state of the room, and the environment of the room changes, thereby affecting the temperature response performance of the room. By obtaining the environmental state in real time and updating the temperature response performance, it is possible to adapt to different environmental conditions and ensure the best temperature control in various situations. The method proposed in the embodiments of the present application can always keep the indoor temperature within the set value or range through precise heat energy compensation, reducing the discomfort caused by temperature fluctuations.

[0029] In the field of intelligent heating, the traditional PID control method often has difficulty in accurately grasping the unique heat dissipation characteristics of each room. The embodiments of the present application propose a full-power heating and natural cooling process without user presence and a heating and cooling process within the room temperature range with user participation. The system can automatically obtain the physical heat dissipation characteristics of the room.

[0030] In some embodiments of the present application, during the full-power heating stage, the HVAC system operates at the rated power to rapidly increase the indoor temperature. During this process, heat fully diffuses in the room and exchanges heat with various parts of the room. Subsequently, it enters the natural cooling stage. After the device is turned off, heat begins to dissipate from the room to the outside, and the temperature gradually drops. In this process, physical characteristics such as the insulation performance and space volume of the room will directly affect the speed of temperature drop. By real-time monitoring the speed of temperature drop, the temperature response performance of the room can be obtained.

[0031] When there is a user in the room, full-power heating may cause the indoor temperature to exceed the range that the user can bear, resulting in discomfort for the user and affecting the user experience. When a user is present indoors, the HVAC system should take the user experience as the primary goal and should not affect the user experience in order to adjust its own parameters. On the premise that the user-set parameters have the highest response priority, if the user actively adjusts the operating power of the HVAC system due to discomfort, the calculation process of the current temperature response performance will be interrupted. Therefore, in some embodiments of the present application, the HVAC system designs an effective temperature rise and fall measurement range for the preset target temperature that does not affect the user experience, and calculates the temperature response performance within this temperature rise and fall measurement range.

[0032] It should be noted that the HVAC system does not need to test the temperature response performance before each start-up for heating. The HVAC system can update the temperature response performance at a preset update frequency during the time when the user does not use the HVAC system. The preset update frequency can be once a week or when the actual temperature control value after the temperature control process exceeds the system control preset temperature fluctuation threshold for re-learning and updating. The HVAC system stores the value of the temperature response performance. When the preset start time is reached or the user actively turns on the HVAC system, the HVAC system can automatically obtain the latest temperature response performance to execute other steps of the method proposed in the embodiments of the present application.

[0033] First, as shown in Figure 2 shown, Figure 2 the specific operation steps of the heating and cooling processes are shown. Figure 1 Step S110 in includes, but is not limited to, the following steps S210 to S230: Step S210, control the indoor temperature to rise by a preset first temperature difference under the rated power output condition, obtain the first time length of the heating process, and determine the active heating efficiency according to the first temperature difference and the first time length; Step S220, control the indoor temperature to naturally drop by a preset second temperature difference, obtain the second time length of the natural cooling process, and determine the natural cooling efficiency according to the second temperature difference and the second time length;

[0034] The temperature response performance of a room represents the ability of a heating and ventilation system to adjust the indoor temperature of the room at a specific power. The temperature response performance is related to the heating capacity, cooling capacity, humidity, volume, ventilation performance of the room, as well as the time and frequency of users entering and leaving the room. In the calculation process of the influence ability of the heating module of the heating and ventilation system on the indoor temperature, it is first necessary to quickly raise the indoor temperature to the target value. In this embodiment, it is set that the heating and ventilation system operates at the rated heating power, and the indoor temperature change of the room is monitored and recorded in real time. When the indoor temperature rises by a preset first temperature difference, the time length required for this heating process is obtained, and the ratio of the first temperature difference to this time length is calculated to obtain the active heating efficiency. Subsequently, the heating and ventilation system is turned off, and the indoor temperature naturally drops. The indoor temperature change of the room is monitored and recorded in real time. When the indoor temperature drops by a preset second temperature difference, the time length required for the natural temperature drop process is read, and the ratio of the second temperature difference to this time length is calculated to obtain the natural cooling efficiency.

[0035] It should be noted that the active heating efficiency reflects the rate of change of the indoor temperature when the heating and ventilation system operates at the rated power, while the natural cooling efficiency characterizes the rate at which the room releases heat to the outside as a high-temperature source. By calculating the active heating efficiency, the influence ability of the heating and ventilation system on the indoor temperature at a specific power can be determined. When the user starts the heating and ventilation system and sets the target temperature, the system can calculate the specific time required to raise the indoor temperature to the target temperature at a specific power according to the active heating efficiency, and control different heating rates by adjusting this power to meet the personalized needs of users.

[0036] At the same time, by calculating the natural cooling efficiency, the heating and ventilation system can determine the heat loss rate in the room. After adjusting the temperature to the target temperature, the system can further adjust the operating power so that the rate at which the heating and ventilation system releases heat to the room at this power matches the heat loss rate of the room, thereby achieving the effect of maintaining the indoor temperature at an appropriate level with a constant power.

[0037] When the user is not in the room, the heating and ventilation system can operate at the rated power for heating. When the indoor temperature rises to the peak when the heating and ventilation system operates at the rated power, the equipment is turned off. At this time, the indoor heat begins to dissipate to the outside, and the temperature gradually drops. By recording the time required for the temperature to drop from the peak, the heat dissipation speed of the room in the natural state can be intuitively reflected, enabling the indoor temperature of the room to actively rise and naturally drop under a larger temperature difference, and the calculated temperature response performance is also more persuasive. Since the physical properties such as the heat insulation performance, space volume, and building materials of different rooms are different, their heat dissipation speeds will also be significantly different. By recording this specific temperature drop time, the system can comprehensively quantify these complex physical properties and provide an accurate basis for subsequent heating control.

[0038] When the user is in the room, the HVAC system obviously cannot raise the indoor temperature to an excessively high level. Through the target temperature set by the user or preset in advance, a temperature control range is designed. Generally speaking, the temperature control range can be set to increase by 5°C or decrease by 4°C. The HVAC system controls the indoor temperature to rise by 4°C with the rated heating power and calculates the active heating efficiency. Subsequently, the HVAC system stops running, allowing the indoor temperature to drop naturally by 4°C, and calculates the natural cooling efficiency.

[0039] In this embodiment, by raising the indoor temperature by 5°C, when calculating the active heating efficiency, the increased temperature will not significantly affect the user experience. During the process of the indoor temperature dropping by 4°C, the range of the second temperature difference is large enough to make the calculation of the natural cooling efficiency valid. At the same time, when the indoor temperature drops naturally to 4°C, it will only start when the device is started for the first time or when the temperature adjustment threshold exceeds the temperature fluctuation threshold of the system reset predicted by the system and the system operation model needs to be updated, which will not significantly affect the user experience.

[0040] It should be noted that detecting whether the user is present can be achieved through an infrared sensor, or, on the premise of obtaining the user's authorization, the time when the user enters and leaves the room in the historical usage situation is statistically analyzed, stored, and analyzed, so as to predict the time when the user is in the room, and different temperature response performance calculation methods are adopted for the periods when the user is in the room or not in the room to adapt to the user experience.

[0041] Similarly, in the hot season, the HVAC system needs to cool the room. At this time, the room will act as a cold source to absorb heat from the hot outdoor, and the refrigeration module of the HVAC system needs to absorb heat from the room. Specifically, in the calculation process of the influence ability of the refrigeration module of the HVAC system on the indoor temperature, the indoor temperature needs to be quickly reduced to the target value first. Set the HVAC system to operate at the rated refrigeration power, and monitor and record the change of the indoor temperature of the room in real time. When the indoor temperature drops to the preset third temperature difference, obtain the third time length required for this cooling process, and calculate the ratio of the third temperature difference to the third time length to obtain the active refrigeration efficiency. Subsequently, turn off the HVAC system, allow the indoor temperature to rise naturally, and monitor and record the change of the indoor temperature of the room in real time. When the indoor temperature rises to the preset fourth temperature difference, read the fourth time length required for the natural temperature rise process, and calculate the ratio of the fourth temperature difference to the fourth time length to obtain the natural heating efficiency.

[0042] The active cooling efficiency can characterize the rate at which the indoor temperature decreases under the cooling power operation of the HVAC system, while the natural heating-up efficiency characterizes the rate at which the room absorbs heat from the outside as a cold source. By calculating the active cooling efficiency, the cooling capacity of the HVAC system at a specific power can be determined. When the user activates the cooling function of the HVAC system and sets the target temperature, the system can calculate the specific time required to reduce the indoor temperature to the target temperature at a specific power according to the active cooling efficiency, and control different cooling rates by adjusting this power, which can also meet the user's personalized needs for cooling.

[0043] Meanwhile, by calculating the natural heating-up efficiency, the HVAC system can determine the rate at which the room temperature rises after the cooling stops. This parameter is crucial for understanding the thermal dynamic characteristics of the room, as it reveals the natural inflow rate of heat into the room without active cooling. In practical applications, the natural heating-up efficiency can assist the HVAC system in optimizing the cooling strategy, achieving efficient use of energy by reasonably adjusting the operating power and cycle of the system, and ensuring that the indoor temperature can be stably maintained within the set comfortable range under different environmental conditions.

[0044] After determining the temperature response performance of the room, the indoor temperature of the room can be adjusted according to the user's preferences and settings. In some embodiments of the present application, referring to Figure 3 as shown Figure 1 step S120 in includes but is not limited to the following steps S310 to S330: Step S310, obtain the initial control strategy. The initial control strategy includes the target temperature, the start time point and the end time point of regulation calculated based on the real-time indoor temperature. The start time point of regulation represents the time point when the temperature adjustment starts, and the end time point of regulation represents the time point when the temperature adjustment stops; Step S320, determine the temperature-reaching time point between the start time point and the end time point of regulation based on the time pre-threshold. Herein, the temperature-reaching time point represents the time point when the indoor temperature is adjusted to the regulated temperature;

[0045] Specifically, in the initial stage of starting the heating module of the HVAC system, if the indoor temperature is lower than the target temperature set by the user, the system will determine the regulated temperature based on the temperature response performance and the target temperature set by the user. In this embodiment, and under the heating condition, when the real-time temperature is less than or equal to the target temperature, the device outputs at the rated power to raise the ambient temperature by 5°C, and accurately calculates the required first heating power through the heating duration. Subsequently, the device stops outputting, and the environment cools down naturally by 4°C, and the second heating power is accurately calculated through the cooling duration.

[0046] Based on the detailed calculation of the room temperature response performance in the above implementation, the HVAC system can accurately infer the time point when the indoor temperature drops to the low temperature threshold. When the indoor temperature is about to reach the low temperature threshold, the system will automatically switch to the first heating power for heating to ensure that the indoor temperature is accurately adjusted to the regulated temperature again at the next temperature reaching time point. This process enables the HVAC system to deeply learn and accurately control the thermal characteristics of the room. By dynamically adjusting the heating power, it realizes the unity of stable maintenance of the indoor temperature and energy-saving operation, creating a comfortable and efficient indoor thermal environment for users.

[0047] In the process of dynamically adjusting the indoor temperature through the above implementation, when there is a large change between the temperature reaching time point and the preset value, the HVAC system will recalculate the temperature response performance according to the new temperature reaching time point and update the subsequent temperature reaching time points according to the current indoor temperature.

[0048] Different from the ordinary heating system that presets a fixed pre-heating time, the HVAC system determines the temperature adjustment duration required to raise the current indoor temperature to the regulated temperature according to the temperature response performance, sets the temperature reaching time point, and sets the goal that the indoor temperature is equal to the regulated temperature at the temperature reaching time point. The regulation start time point is determined according to the temperature adjustment duration, that is, at the regulation start time point, the HVAC system starts to heat.

[0049] In addition, the HVAC system will also obtain the electricity price information within a period of time before the temperature reaching time point, and adjust the heating power of the HVAC system between the regulation start time point and the temperature reaching time point according to the fluctuation of the electricity price information. If the electricity price fluctuates from high to low, the HVAC system will first preheat at a low power, and when the electricity price becomes low, it will update the temperature adjustment power according to the remaining time. If the electricity price fluctuates from low to high, it will first heat at a high power during the low electricity price period, calculate the time difference between the time point when the electricity price becomes high and the temperature reaching time point, predict the temperature drop value of the indoor temperature within this time difference through the temperature response performance, determine the required value of the indoor temperature at the time point when the electricity price becomes high according to the regulated temperature and the above temperature drop value, the HVAC system heats at a high power during the low electricity price time so that the indoor temperature at the time point when the electricity price becomes high is equal to the sum of the regulated temperature and the temperature drop value, and then during the high electricity price period, the HVAC system operates at a low power. After adjusting to the temperature reaching time point, the indoor temperature is exactly equal to the regulated temperature.

[0050] Before the temperature adjustment of the HVAC system starts, obtain the indoor temperature in real time, and determine the qualified time threshold based on the indoor temperature and the target temperature. Here, the qualified time threshold represents the time required to adjust the indoor temperature to the target temperature based on the temperature adjustment power. Obtain the real-time time point. If the difference between the real-time time point and the temperature reaching time point is greater than the qualified time threshold, do not start the corresponding temperature adjustment output. If the difference between the real-time time point and the temperature reaching time point is equal to the qualified time threshold, output based on the temperature adjustment power in the latest target control strategy. During the output process with the temperature adjustment power, check the temperature change situation of the temperature adjustment process that has been carried out based on the preset inspection frequency, and adjust the temperature adjustment power in real time according to the difference between the real-time time point and the temperature reaching time point. With the dynamic changes of the indoor environment, such as events like users entering and leaving the room, opening and closing windows, etc., the room temperature and temperature response performance will be affected. During the heating process of the HVAC system with the temperature adjustment power, the actual indoor temperature change may deviate from the expected trajectory. Therefore, after the control start time point, the HVAC system obtains the indoor temperature data in real time and inputs these data into a pre-trained environment recognition model to monitor the change situation of the indoor temperature. By calculating the first time difference between the current time and the control start time point, combined with the environment recognition model, evaluate the heating capacity of the HVAC system. The environment recognition model updates the temperature response performance accordingly. Based on the updated temperature response performance and the real-time indoor temperature data, predict the time point when the indoor temperature is adjusted to the target temperature at the current temperature adjustment power. Compare this predicted time point with the preset temperature reaching time point: If the time difference between the two is less than or equal to the qualified time threshold, it indicates that the current temperature adjustment power and the temperature response performance match well, and there is no need to adjust the temperature adjustment power. If the second time difference exceeds the qualified time threshold, it may be that the indoor temperature will be adjusted to the control temperature in advance, resulting in energy waste, or it cannot be adjusted to the target temperature for a long time, affecting the user experience. At this time, adjust the temperature adjustment power according to the second time difference between the current time and the temperature reaching time point, and the updated temperature response performance, so as to optimize the energy utilization efficiency and improve the user comfort level.

[0051] Alternatively, after the HVAC system receives the heating instruction, the HVAC system first operates at the temperature adjustment power calculated based on the time difference between the current real-time temperature and the preset end time, quickly raises the indoor temperature to the control temperature, and then operates at the constant temperature power to keep the indoor temperature within a suitable range, such as Figure 4 As shown, the above embodiments specifically include but are not limited to the following steps S410 to step S420: Step S410, control to operate at the temperature adjustment power to adjust the indoor temperature to the control temperature; Step S420, determine the constant temperature power according to the temperature response performance, and control to continuously operate at the constant temperature power.

[0052] In this embodiment, when the regulated temperature is equal to the target temperature, the system first operates at a temperature regulation power calculated based on the time difference between the current real-time temperature and the preset end time, ensuring that the indoor temperature is adjusted to the regulated temperature within the shortest time. Subsequently, the HVAC system calculates and determines the constant temperature power based on the temperature response performance of the room. Under the operation of this constant temperature power, the rate at which the HVAC system releases heat to the room is adjusted to a dynamic balance with the rate at which the room loses heat to the outside as a heat source, thereby achieving stable maintenance of the indoor temperature. Through precise calculation of the temperature response performance, the HVAC system can dynamically adjust the operation power to ensure that the indoor temperature always remains within the target temperature range under the constant temperature power. This process avoids the energy waste and temperature fluctuations caused by frequent adjustment of the operation power in traditional systems, significantly improving the energy efficiency of the system and the comfort of users. In addition, the system can also dynamically optimize the constant temperature power according to real-time environmental data to adapt to different operating conditions, further enhancing the adaptability and energy-saving effect of the system. By combining the precise calculation of the temperature response performance and the dynamic adjustment of the constant temperature power, the HVAC system can achieve efficient and energy-saving operation while ensuring the stability of the indoor temperature, providing a comfortable and economical indoor heating environment for users.

[0053] Similarly, due to the dynamic changes in the indoor environment, during the process of continuous operation at the set constant temperature power, as the temperature response performance of the room undergoes persistent changes, the indoor temperature may deviate significantly from the regulated temperature. Therefore, during the operation at the constant temperature power, the HVAC system also needs to continuously obtain the indoor temperature. When the change amplitude of the indoor temperature is greater than the preset temperature fluctuation threshold, the HVAC system operates at the maximum power again to re-adjust the indoor temperature to the regulated temperature. Subsequently, the environment recognition model is called to update the temperature response performance based on the change rate of the indoor temperature. By calculating the new constant temperature power based on the updated temperature response performance, under the operation of the new constant temperature power, the heating efficiency of the HVAC system for the room is equal to the natural cooling efficiency of the room. Therefore, the indoor temperature of the room can be maintained at the regulated temperature.

[0054] Due to the dynamic characteristics of the indoor environment, the response performance of the indoor temperature may continuously change due to various factors. During the continuous operation of the HVAC system at a set constant temperature power, these changes may cause a significant deviation between the indoor temperature and the target regulated temperature. The HVAC system continuously monitors the indoor temperature during operation. When it detects that the change amplitude of the indoor temperature exceeds the preset temperature fluctuation threshold, the HVAC system will automatically perform power compensation calculation based on the current temperature overshoot value to adjust the operation mode, quickly callback the indoor temperature to the regulated temperature, and then the HVAC system calls the environment recognition model to update the temperature response performance parameters according to the change rate of the indoor temperature. Based on the updated temperature response performance, the system recalculates and determines a new constant temperature power. At this new constant temperature power, the heating rate of the HVAC system and the natural heat dissipation rate of the room achieve dynamic balance, thus ensuring that the indoor temperature is stably maintained at the regulated temperature.

[0055] During the process of the HVAC system dynamically adjusting the indoor temperature, the environmental state of the room will continuously change, and these changes will directly affect the temperature response performance of the room. Therefore, during the process of dynamically adjusting the indoor temperature, it is necessary to continuously monitor the changes in the environmental state and dynamically calibrate the temperature response performance used as the adjustment benchmark according to these changes.

[0056] The embodiment of the present application proposes a dynamic calibration method based on an environment recognition model. The HVAC system integrates a variety of sensors (including but not limited to temperature sensors, humidity sensors, light sensors, gas flow sensors, etc.) for continuously perceiving the changes in the environmental state in the room. The system collects environmental state data through these sensors and inputs this data into a pre-trained environment recognition model. The environment recognition model is based on machine learning algorithms and can analyze the impact of environmental state changes on the temperature response performance and update the temperature response performance in real time.

[0057] With the temperature response performance updated in real time, the HVAC system can dynamically adjust the temperature control strategy to ensure the stability and comfort of the indoor temperature. The HVAC system optimizes the heating or cooling power according to the updated temperature response performance, so that the indoor temperature always remains within the target range, which not only improves the adaptability of the system but also significantly reduces the temperature fluctuations and increased energy consumption caused by environmental changes.

[0058] In addition, the introduction of the environment recognition model enables the HVAC system to better cope with complex environmental conditions, such as extreme weather, high humidity or low light, etc. Through continuous learning and optimization, the system can gradually improve its performance in different environments and provide users with a more efficient, energy-saving and comfortable indoor environment.

[0059] First, the environmental humidity in the room can affect the heat absorption efficiency and release efficiency, and can also affect the user's actual temperature perception. Humidity has a significant impact on the heat capacity of air. Air with high humidity has a higher heat capacity, which means that in an environment with higher humidity, the air has a stronger ability to absorb or release heat. Therefore, the HVAC system needs to operate at a higher power to change the indoor temperature in an environment with high humidity; air with high humidity has better heat conduction performance. This means that heat is more easily transferred in an environment with high humidity. In the cold season, the air with high humidity will transfer heat to the outside faster, resulting in a faster drop in indoor temperature; in the hot season, the air with high humidity will transfer heat to the inside faster, resulting in a faster rise in indoor temperature. Therefore, the HVAC system needs to operate more frequently in an environment with high humidity to maintain the stability of the indoor temperature; at the same time, humidity is one of the important factors affecting thermal comfort. High humidity will make users feel stuffy, and even if the temperature is appropriate, people will still feel uncomfortable. Therefore, when the HVAC system adjusts the temperature, it needs to consider the influence of humidity at the same time to ensure the comfort of the indoor environment.

[0060] In addition, the air circulation state in the room can also affect the heat absorption efficiency and release efficiency of the indoor heat. When users enter or leave the room or open or close the window, the air circulation rate between the indoor and outdoor changes, and the heat exchange efficiency between the indoor and outdoor also changes accordingly. The air circulation direction represents the flow direction of the high-temperature air or low-temperature air in the room. By synthesizing the air circulation direction and the air circulation rate, the indoor air renewal rate is obtained. After obtaining the air circulation state, the air circulation state is quantified through the environmental recognition model, and the temperature response performance is updated accordingly.

[0061] When users enter or leave the room or open or close the window, the air circulation between the indoor and outdoor changes. An increase in the indoor and outdoor air renewal rate will cause a significant increase in the heat exchange rate between the indoor and outdoor air, resulting in the indoor temperature quickly approaching the outdoor temperature. In the heating scenario, when users enter or leave the room or open the window, the heat in the room will quickly dissipate to the outside, causing the indoor temperature to drop rapidly, changing the temperature response performance of the room and reducing the heating efficiency of the HVAC module.

[0062] A higher indoor air renewal rate can enhance the convective heat transfer efficiency between the indoor air and the object surface. According to the convective heat transfer formula Q = hAΔT, where h is the convective heat transfer coefficient, A is the heat transfer area, and ΔT is the temperature difference. An increase in the air velocity will increase the value of h, thereby accelerating heat transfer and enabling the indoor temperature to be adjusted to the set value faster; good air circulation can prevent excessive local temperature differences. For example, when the air conditioner is heating, the hot air will rise and accumulate at the upper part of the room, while the lower part has a lower temperature. By promoting air circulation, the heat can be more evenly distributed throughout the room, reducing the vertical temperature difference and improving the overall thermal comfort.

[0063] In addition, during the temperature regulation process of the HVAC system, the HVAC system itself can also directly compare the rate of change of the indoor temperature with the desired temperature response efficiency by obtaining the indoor temperature in real time, so as to judge the effectiveness of the temperature regulation process. Specifically, as Figure 5 shown, judging the effectiveness of the temperature regulation process includes but is not limited to the following steps S510 to S520: Step S510: Obtain the indoor temperature in real time, and determine the actual temperature regulation efficiency based on the indoor temperature and the initial temperature of the room; Step S520: Determine the temperature regulation verification function based on the actual temperature regulation efficiency and the temperature response efficiency, and judge the effectiveness of the target control strategy through the temperature regulation verification function.

[0064] Specifically, during the implementation of the target control strategy of the HVAC system, both the operating state of the system and the response characteristics of the indoor thermal environment will have a significant impact on the precise temperature regulation effect of the indoor temperature, resulting in the actual temperature change trajectory deviating from the expected set path, and causing a deviation between the temperature regulation process of the indoor temperature and the expectation. During the temperature regulation process of the room, obtain the indoor temperature in real time. An actual temperature regulation process function can be fitted from the indoor temperature and the corresponding time. The temperature regulation process of the room can be intuitively observed from the actual temperature regulation process function. The starting point of the actual temperature regulation process function is the initial temperature of the room, and the initial temperature is also the temperature before the temperature regulation process of the room. During the temperature regulation process, obtain the indoor temperature in real time, and determine the actual temperature regulation efficiency based on the indoor temperature and the initial temperature. The calculation formula for the actual temperature regulation efficiency is: K_inspection = (K_actual - K_initial_actual) / (T - T_R1), where K_inspection represents the actual temperature regulation efficiency, K_actual represents the real-time indoor temperature, K_initial_actual represents the initial temperature, T represents the real-time time, and T_R1 represents the start time of the HVAC system. Summarize and plot the actual temperature regulation efficiency during the temperature regulation process of the HVAC system to obtain the temperature regulation verification function.

[0065] It can be understood that the temperature response performance theoretically quantifies the expected ability of the HVAC system to regulate the indoor temperature under the condition of operating at the set power, and is a key indicator to measure the system design and theoretical performance. The temperature regulation verification function truly records the temperature regulation effect of the HVAC system under the actual operating conditions, and is a dynamic curve for evaluating the actual operating performance of the system. Therefore, comparing and analyzing the temperature regulation verification function with the temperature response performance can effectively reveal the difference degree between the actual temperature regulation ability of the HVAC system and the expected goal, and further provide a comparison basis for judging the effectiveness of the target control strategy.

[0066] In an optional embodiment, an effective means of comparing the temperature regulation verification function with the temperature response performance is to calculate the ratio between the actual temperature regulation efficiency and the temperature response performance at each moment. Set a reasonable preset range. When the ratio stably falls within this interval, it can be determined that the actual temperature regulation process of the HVAC system conforms to the expectation and the system is operating normally; otherwise, if the ratio exceeds this range, it indicates that there is a deviation in the target control strategy of the HVAC system and timely optimization and adjustment are required. In an actual application scenario, if the operating power of the HVAC system remains constant, the temperature response performance can be taken as a constant value, representing the average change rate of the indoor temperature in the constant power operation mode. This constant value can be determined through theoretical calculation combined with system parameter calibration; when the operating power of the HVAC system fluctuates, the temperature response performance becomes a function that changes in real time, dynamically reflecting the instantaneous change rate of the indoor temperature under real-time power fluctuations. Its calculation needs to be dynamically fitted and corrected based on real-time power monitoring data and temperature change feedback.

[0067] During the temperature regulation process of the HVAC system, when the user sets a new target temperature, the HVAC system needs to make a jump in the target temperature based on the newly set control strategy; the HVAC system obtains the previously set target temperature and the newly set updated temperature of the user. First, a temperature conversion heating and cooling function is constructed through the target temperature and the updated temperature. Specifically, the calculation formula of the temperature conversion heating and cooling function is: KZ=(KM1 - KM2) / (TM2 - TM1), where KZ represents the temperature conversion heating and cooling function, KM1 represents the originally set target temperature, KM2 represents the newly set updated temperature, TM2 represents the time when the indoor temperature is adjusted to the updated temperature, and TM1 represents the time when the user sets the updated temperature. Generally speaking, starting from when the user sets the updated temperature, the HVAC system calculates a new control strategy through an algorithm and executes it quickly. The difference between TM2 and TM1 can be the pre-set regulation time difference of the HVAC system, and its value can be 10 minutes, that is, TM2 = TM1 + 10.

[0068] Then, the HVAC system needs to calculate the mode conversion output compensation percentage function PZ and the constant temperature output percentage function PH. Specifically, the value of the mode conversion output compensation percentage function PZ is equal to the quotient obtained by dividing the active heating efficiency of the HVAC system by the temperature conversion heating and cooling function, and the constant temperature output percentage function PH is equal to the quotient obtained by dividing the active heating efficiency by the natural cooling efficiency. The absolute value of the difference between the originally set target temperature and the newly set updated temperature is the variable temperature adjustment interval value; the difference between the start time of the variable temperature operation and the time to adjust to the updated temperature is the mode adjustment duration. To achieve variable temperature, only a compensation value needs to be added to the constant temperature output percentage. When the updated temperature is higher than the target temperature (KM2 > KM1), the compensation value is positive; when the preset temperature of the next mode is lower than the cut-off temperature of the previous mode, the compensation value is negative. Based on this, the system has preset a mode conversion compensation percentage function. When KM2 > KM1, the value of the variable temperature real-time output power of the HVAC system is WZ = W * (|PH + PZ|); when KM2 < KM1, the value of the variable temperature real-time output power is WZ = W * (|PH - PZ|), where W represents the current real-time power.

[0069] In addition, referring to Figure 6 , this application also provides a heating control device 600, including: A test module 601, configured to control a preset temperature adjustment operation for the indoor temperature, obtain the temperature change of the indoor temperature, and determine the temperature response performance of the room; A strategy module 602, configured to obtain a preset target temperature, determine a regulated temperature and its time pre-threshold according to the target temperature and the temperature response performance, and determine a target control strategy according to the temperature response performance and the regulated temperature; An update module 603, configured to obtain the environmental state in real time, identify the environmental state through a pre-trained environmental recognition model, update the temperature response performance, and adjust the target control strategy through the updated temperature response performance.

[0070] The above heating control device 600 and the intelligent heating method based on machine learning are based on the same inventive concept, and will not be elaborated here.

[0071] In addition, referring to Figure 7 , Figure 7 schematically shows the hardware structure of an electronic device in another embodiment. The electronic device includes: The processor 701 can be implemented in ways such as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application; The memory 702 can be implemented in forms such as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 702 can store an operating system and other application programs. When implementing the technical solutions provided in the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 702 and are called by the processor 701 to execute the machine learning-based intelligent heating method in the embodiments of the present application. For example, to execute the Figure 1 method steps S110 to S130 in Figure 2 the method steps S210 to S230 in Figure 3 the steps S310 to S320 in Figure 4 the steps S410 to S420 in Figure 5 the steps S510 to S520 in The input / output interface 703 is used to implement information input and output; The communication interface 704 is used to implement communication and interaction between this device and other devices, and can implement communication through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.); The bus 705 transmits information between various components of the device (such as the processor 701, the memory 702, the input / output interface 703, and the communication interface 704); Among them, the processor 701, the memory 702, the input / output interface 703, and the communication interface 704 are communicatively connected to each other inside the device through the bus 705.

[0072] The embodiments of the present application also provide a storage medium. The storage medium is a computer-readable storage medium for computer-readable storage. The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the above-mentioned machine learning-based intelligent heating method. For example, to execute the Figure 1 method steps S110 to S130 in Figure 2 the method steps S210 to S230 in Figure 3Steps S310 to S320 in Figure 4 Steps S410 to S420 in Figure 5 Steps S510 to S520 in

[0073] As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory may optionally include memories remotely disposed relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above networks include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0074] The embodiments described in the embodiments of the present application are for more clearly illustrating the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art will know that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.

[0075] Those skilled in the art can understand that Figures 1 to 5 the technical solutions shown in

[0076] do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than those shown in the figures, or combine certain steps, or different steps.

[0077] Those of ordinary skill in the art can understand that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, and appropriate combinations thereof.

[0078] In the description of this application and the above-mentioned accompanying drawings, terms such as "first", "second", "third", "fourth", etc. (if any) are used to distinguish similar objects and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances so that the embodiments of this application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that comprises a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0079] It should be understood that in this application, "at least one (item)" means one or more, and "a plurality" means two or more. "And / or" is used to describe the association relationship of associated objects and indicates that three relationships can exist. For example, "A and / or B" can mean: only A exists, only B exists, and both A and B exist at the same time. Among them, A and B can be singular or plural. The character " / " generally means that the associated objects before and after are in an "or" relationship. "At least one (one) of the following" or similar expressions refer to any combination of these items, including any combination of single items (ones) or plural items (ones). For example, at least one (one) of a, b, or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0080] In several embodiments provided by this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the above-mentioned division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of devices or units can be in an electrical, mechanical, or other form.

[0081] The units described above as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0082] In addition, in each embodiment of the present application, the functional units may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of a software functional unit.

[0083] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it may be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, may be embodied in the form of a software product. The computer software product is stored in a storage medium and includes multiple instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store programs.

[0084] The preferred embodiments of the embodiments of the present application have been described above with reference to the accompanying drawings, and thus do not limit the scope of the rights of the embodiments of the present application. Any modifications, equivalent replacements, and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of the present application shall be within the scope of the rights of the embodiments of the present application.

Claims

1. An intelligent heating method based on machine learning, characterized in that, Including: Controlling a preset temperature adjustment operation for the indoor temperature, obtaining the temperature change of the indoor temperature, and determining the temperature response performance of the room; Obtaining a preset target temperature, determining a regulated temperature and its time lead threshold according to the target temperature and the temperature response performance, and determining a target control strategy according to the temperature response performance and the regulated temperature; Obtaining the environmental state in real time, identifying the environmental state through a pre-trained environmental recognition model, updating the temperature response performance, and adjusting the target control strategy through the updated temperature response performance.

2. The intelligent heating method according to claim 1, wherein The controlling a preset temperature adjustment operation for the indoor temperature, obtaining the temperature change of the indoor temperature, and determining the temperature response performance of the room includes: Controlling the indoor temperature to rise by a preset first temperature difference under the rated power output condition, obtaining the first time length of the heating process, and determining the active heating efficiency according to the first temperature difference and the first time length; Controlling the indoor temperature to naturally decrease by a preset second temperature difference, obtaining the second time length of the natural cooling process, and determining the natural cooling efficiency according to the second temperature difference and the second time length; Determining the temperature response performance of the room according to the active heating efficiency and the natural cooling efficiency.

3. The intelligent heating method according to claim 2, wherein The controlling a preset temperature adjustment operation for the indoor temperature, obtaining the temperature change of the indoor temperature, and determining the temperature response performance of the room further includes: Obtaining the target temperature and a preset temperature regulation length, determining the second temperature difference according to the temperature regulation length, and determining the first temperature difference according to a preset heating duration coefficient and the temperature regulation length; Performing the temperature adjustment operation through the first temperature difference and the second temperature difference, and determining the temperature response performance.

4. The intelligent heating method according to claim 1, characterized in that The obtaining a preset target temperature, determining a regulated temperature and its time lead threshold according to the target temperature and the temperature response performance, and determining a target control strategy according to the temperature response performance and the regulated temperature includes: Obtaining an initial control strategy, where the initial control strategy includes the target temperature, a regulated start time point and a regulated end time point calculated based on the real-time indoor temperature, the regulated start time point represents the time point when the temperature adjustment starts, and the regulated end time point represents the time point when the temperature adjustment stops; Determining a temperature reaching time point between the regulated start time point and the regulated end time point based on the time lead threshold, where the temperature reaching time point represents the time point when the indoor temperature is adjusted to the regulated temperature; Obtaining electricity price information, determining the temperature adjustment power according to the electricity price information and the temperature reaching time point, determining the temperature adjustment duration according to the temperature adjustment power, the indoor temperature and the regulated temperature, and determining a new regulated start time point according to the temperature adjustment duration and the temperature reaching time point, to obtain the target control strategy.

5. The intelligent heating method according to claim 4, characterized in that The obtaining the environmental state in real time, identifying the environmental state through a pre-trained environmental recognition model, updating the temperature response performance, and adjusting the target control strategy through the updated temperature response performance includes: Obtain the indoor temperature in real time, and determine a qualified time threshold based on the indoor temperature and the target temperature, where the qualified time threshold represents the time required to adjust the indoor temperature to the target temperature based on the temperature adjustment power; Obtain the real-time time point. If the difference between the real-time time point and the temperature reaching time point is greater than the qualified time threshold, do not start the corresponding temperature adjustment output; If the difference between the real-time time point and the temperature reaching time point is equal to the qualified time threshold, output based on the temperature adjustment power in the latest target control strategy; During the process of outputting with the temperature adjustment power, check the temperature change situation of the performed temperature adjustment process based on a preset inspection frequency, and adjust the temperature adjustment power in real time according to the difference between the real-time time point and the temperature reaching time point.

6. The intelligent heating method according to claim 4, wherein The step of obtaining a preset target temperature, determining a regulated temperature according to the target temperature and the temperature response performance, and determining a target control strategy according to the temperature response performance and the regulated temperature further includes: Control to operate with the temperature adjustment power to adjust the indoor temperature to the regulated temperature; Determine a constant temperature power according to the temperature response performance, and control to continuously operate with the constant temperature power.

7. The intelligent heating method according to claim 6, wherein The step of obtaining the environmental state in real time, identifying the environmental state through a pre-trained environmental recognition model, updating the temperature response performance, and adjusting the target control strategy through the updated temperature response performance includes: During the process of operating with the constant temperature power, obtain the indoor temperature in real time, and input the temperature response performance for determining the constant temperature power and the real-time indoor temperature into the environmental recognition model; Call the environmental recognition model. When the change amplitude of the indoor temperature is greater than a preset temperature fluctuation threshold, update the temperature response performance based on the change rate of the indoor temperature; Obtain a preset regulation duration, determine a dynamic adjustment power according to the real-time indoor temperature and the regulation duration, and control to operate with the dynamic adjustment power to adjust the indoor temperature to the regulated temperature again after the regulation duration; The environmental recognition model determines a new constant temperature power based on the updated temperature response performance and the target temperature, and controls to operate with the new constant temperature power.

8. The intelligent heating method according to claim 1, characterized in that, It further includes: Obtain the indoor temperature in real time, and determine the actual temperature adjustment efficiency through the indoor temperature and the initial temperature of the room; Determine a temperature adjustment verification function according to the actual temperature adjustment efficiency and the temperature response efficiency, and judge the effectiveness of the target control strategy through the temperature adjustment verification function.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the intelligent heating method according to any one of claims 1 to 7.

10. A storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the intelligent heating method according to any one of claims 1 to 7.

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