Intelligent heating and ventilation control method and device based on real-time positioning

Abstract

The embodiment of the invention provides an intelligent heating and ventilation control method and device based on real-time positioning, and the method comprises the steps: obtaining real-time positioning, calibrating the built-in time of a persistently operating system through the real-time positioning, and determining the control time; an initial environment control strategy is determined according to the real-time positioning, the initial environment control strategy is matched with the control time, and the initial environment control strategy represents a universal indoor environment state control strategy; acquiring climate information according to real-time positioning, determining a climate zone correction factor through the climate information, adjusting the initial environment control strategy by using the climate zone correction factor, and determining a target environment control strategy; the method provided by the embodiment of the invention is suitable for various climate zones and geographical environments, can meet the requirements of users in different regions, and has wide applicability and popularization value.

Description

Technical Field

[0001] This application relates to, but is not limited to, the field of HVAC control technology, and particularly relates to an intelligent HVAC control method and device based on real-time positioning. Background Art

[0002] In related technologies, traditional HVAC control systems usually rely on fixed preset schedules or simple temperature control logics to adjust the operation of heating equipment. However, this method has some limitations. For example, traditional HVAC control systems cannot dynamically adjust heating strategies according to geographical locations or climate conditions. In the face of cross-climate usage scenarios, it is difficult to optimize heating efficiency and comfort in different climate zones. Summary of the Invention

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

[0004] Embodiments of this application provide an intelligent HVAC control method and device based on real-time positioning, which are applicable to a variety of climate zones and geographical environments, can meet the needs of users in different regions, and have broad applicability and promotion value.

[0005] To achieve the above object, a first aspect of the embodiments of this application proposes an intelligent HVAC control method based on real-time positioning, including: obtaining real-time positioning, calibrating the system built-in time that runs persistently through the real-time positioning to determine the control time; determining an initial environmental control strategy according to the real-time positioning, and matching the initial environmental control strategy with the control time, where the initial environmental control strategy represents a general indoor environmental state control strategy; obtaining climate information according to the real-time positioning, determining a climate zone correction factor through the climate information, and adjusting the initial environmental control strategy using the climate zone correction factor to determine the target environmental control strategy.

[0006] In some embodiments, the obtaining real-time positioning, calibrating the system built-in time that runs persistently through the real-time positioning to determine the control time includes: obtaining real-time positioning, determining the local time zone, and obtaining the local standard time according to the local time zone; obtaining the local daylight saving offset rule, and adjusting the local standard time through the daylight saving offset rule to obtain the control time.

[0007] In some embodiments, obtaining climate information according to the real-time positioning, determining a climate zone correction factor through the climate information, and using the climate zone correction factor to adjust the initial environmental control strategy includes: determining climate information according to the latitude information in the real-time positioning, using the climate information to perform matching in the local climate database to obtain a climate zone correction factor, and determining a power change correction time according to the climate zone correction factor; determining the focus of air circulation according to the climate correction factor, where the focus of air circulation includes a temperature control strategy with temperature as the regulation focus and corresponding temperature regulation targets, and a humidity control strategy with humidity as the regulation focus and corresponding humidity regulation targets; obtaining multiple initial power change time points in the initial environmental control strategy, and adjusting each of the initial power change time points through the power change correction time to determine the target power change time points in the target environmental control strategy, where the formula for adjusting the initial power change time point through the power change correction time is: ; represents the target power change time point, represents the initial power change time point, represents the power change correction time.

[0008] In some embodiments, the method further includes: obtaining weather information according to the real-time positioning, and adjusting the target environmental control strategy according to the weather information.

[0009] In some embodiments, the method further includes: determining a start time point in the target environmental control strategy, and obtaining first electricity price information within a preset first time length before and after the start time point; if the electricity price at the start of the first time length is less than the electricity price at the start time point, setting the start of the first time length as the new start time point in the target environmental control strategy, and increasing the starting power at the new start time point to be greater than the power value originally set at the old start time point.

[0010] In some embodiments, the method further includes: determining an end time point in the target environmental control strategy, and obtaining second electricity price time information within a preset second time length before and after the end time point; if the electricity price at the start of the second time length is greater than the electricity price at the end of the second time length, setting the end of the second time length as the new end time point in the target environmental control strategy, and reducing the power value from the start of the second time length to the old end time point.

[0011] In some embodiments, the method further includes: if the electricity price at the start point of the second time length is less than the electricity price at the end time point, determining the start point of the second time length as the new end time point in the target environment control strategy, and increasing the starting power at the new end time point so that it is greater than the power value originally set at the old end time point.

[0012] To achieve the above object, a second aspect of the embodiments of the present application provides an intelligent HVAC control device, including: a positioning module, configured to obtain real-time positioning, calibrate the built-in time of the system running persistently through the real-time positioning, and determine the control time; a policy matching module, configured to determine an initial environment control strategy according to the real-time positioning, and match the initial environment control strategy with the control time, where the initial environment control strategy represents a general indoor environment state control strategy; a climate matching module, configured to obtain climate information according to the real-time positioning, determine a climate zone correction factor through the climate information, and adjust the initial environment control strategy by using the climate zone correction factor to determine a target environment control strategy.

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

[0014] To achieve the above object, a fourth aspect of the embodiments of the present application provides a storage medium, where the storage medium 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 HVAC control method described in the first aspect above is implemented.

[0015] The embodiments of the present application at least include the following beneficial effects: By using real-time positioning technology to calibrate the built-in time of the system, based on the geographical location information obtained from real-time positioning, the system can automatically set a general initial environmental control strategy, match the control time with the initial environmental control strategy, and ensure the accuracy of implementing the initial environmental control strategy. However, if the general initial environmental control strategy does not meet the local climate characteristics, the system will also obtain the local climate information based on real-time positioning, and dynamically adjust the initial environmental control strategy in combination with the climate zone correction factor, thereby significantly improving the adaptability and flexibility of the HVAC system, and ensuring the optimal environmental control effect in different climate zones. Moreover, by adjusting the initial environmental control strategy through the climate zone correction factor, it is also possible to minimize energy consumption while meeting the comfort requirements of users. For example, in terms of temperature control, extending the heating time in cold regions and shortening the heating time in warm regions can achieve the dual optimization of energy conservation and comfort. The intelligent HVAC control method proposed in the present application is applicable to a variety of climate zones and geographical environments, can meet the needs of users in different regions, and has broad applicability and promotion value.

[0016] Other features and advantages of the present application will be described in the following specification, and some of them will become obvious from the specification or can be understood by implementing the present application. The objectives and other advantages of the present application can be achieved and obtained through 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. Together with the embodiments of the present application, they are used to explain the technical solutions 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 HVAC control method based on real-time positioning provided by the embodiments of the present application; Figure 2 It is an optional flowchart of adjusting time by the order time provided by the embodiments of the present application; Figure 3 It is an optional specific flowchart of determining the target control strategy provided by the embodiments of the present application; Figure 4 It is an optional flowchart of adjusting the target control strategy according to the electricity price provided by the embodiments of the present application; Figure 5 It is an optional structural diagram of the HVAC system control mode provided by the embodiments of the present application; Figure 6 It is an optional diagram of the time point of power change adjusted by the electricity price provided by the embodiments of the present application; Figure 7 Another alternative schematic diagram of the power change time point for electricity price adjustment provided by this embodiment of the present application; Figure 8 Another alternative schematic diagram of the power change time point for electricity price adjustment provided by this embodiment of the present application; Figure 9 An alternative structural schematic diagram of the intelligent HVAC control device provided by this embodiment of the present application; Figure 10 An alternative hardware structural schematic diagram of the electronic device provided by the embodiment of the present application. Detailed implementation manners

[0019] In order to make the objectives, technical solutions and advantages of the present application clearer, 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 "several" is one or more, the meaning of "multiple" is more than two, understandings such as "greater than", "less than", "exceeding" do not include the present number, and understandings such as "above", "below", "within" include the present number.

[0021] It should be noted that although functional module division is performed 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 in the flowchart. Terms such as "first", "second", etc. in the description, claims or the above-mentioned drawings are used to distinguish similar objects and do not have to be used to describe a specific order or sequence.

[0022] In the related art, traditional HVAC control systems cannot dynamically adjust the heating strategy according to geographical location or climate conditions, resulting in difficulties in optimizing heating efficiency and comfort in different climate zones in the face of cross-climate usage scenarios.

[0023] Based on this, the embodiments of the present application provide an intelligent HVAC control method and device based on real-time positioning, which are applicable to a variety of climate zones and geographical environments, can meet the needs of users in different regions, and have wide applicability and promotion value.

[0024] The intelligent HVAC control method and device based on real-time positioning provided by the embodiments of the present application are specifically described through the following embodiments. First, the intelligent HVAC control method based on real-time positioning in the embodiments of the present application is described.

[0025] The following further elaborates on the embodiments of the present application with reference to the accompanying drawings.

[0026] As Figure 1 shown, Figure 1FIG. 0 is an alternative process schematic diagram of the intelligent HVAC control method based on real-time positioning provided by the embodiments of the present application. The intelligent HVAC control method based on real-time positioning can be executed by a remote server, or can also be executed by a terminal on the HVAC system, or can also be executed by the server in cooperation with the terminal. The intelligent HVAC control method based on real-time positioning includes, but is not limited to, the following steps S110 to S140: Step S110, obtain real-time positioning, calibrate the built-in time of the continuously running system through the real-time positioning, and determine the control time; Step S120, determine the initial environmental control strategy according to the real-time positioning, and match the initial environmental control strategy with the control time, where the initial environmental control strategy represents a general indoor environmental state control strategy; Step S130, obtain climate information according to the real-time positioning, determine the climate zone correction factor through the climate information, and use the climate zone correction factor to adjust the initial environmental control strategy to determine the target environmental control strategy.

[0027] It can be understood that by calibrating the built-in time of the system through the real-time positioning technology, according to the geographical location information obtained by the real-time positioning, the system can automatically set the general initial environmental control strategy, match the control time with the initial environmental control strategy, and ensure the accuracy of executing the initial environmental control strategy; however, if the general initial environmental control strategy does not meet the local climate characteristics, the local climate information obtained by the real-time positioning will also be combined with the climate zone correction factor to dynamically adjust the initial environmental control strategy, so as to significantly improve the adaptability and flexibility of the HVAC system and ensure the optimal environmental regulation effect under different climate zones; and, by adjusting the initial environmental control strategy through the climate zone correction factor, it is also possible to minimize energy consumption while meeting the comfort requirements of users. For example, in terms of temperature regulation, extending the heating time in cold regions and shortening the heating time in warm regions can achieve the dual optimization of energy conservation and comfort; the intelligent HVAC control method proposed in this application is applicable to a variety of climate zones and geographical environments, can meet the needs of users in different regions, and has wide applicability and promotion value.

[0028] The indoor environmental state control strategy includes, but is not limited to, specific control methods for indoor temperature, humidity, air circulation state, and ventilation conditions. The built-in time of the system represents the continuous timing starting from the factory by a continuously running clock. When the HVAC system is installed, the system calibrates the clock with the local time. Before the HVAC system is replaced and reinstalled, the built-in time of the system can represent the local time before the replacement location. After the replacement location and installation, the system calculates the time zone difference before the replacement location according to the real-time positioning, so as to obtain the local time after the replacement location, and obtain the control time based on this.

[0029] The intelligent HVAC control method proposed in the embodiments of this application serves global users, integrates global time zone data, daylight saving time policies, and climate zone adaptation algorithms, and realizes the automatic scheduling of cross-regional HVAC control modes through real-time clock timing and geolocation technology, providing convenient, efficient, and energy-saving HVAC solutions for different user groups such as multinational enterprises and immigrant families, and promoting the development of intelligent HVAC technology towards globalization and precision.

[0030] An always-on clock is built into the intelligent HVAC system. When the system is powered off, the clock can still operate normally. The time recorded by this clock can be counted from the factory. When the system is powered on and connected to the network, the time recorded by the clock can also be synchronized with the local time.

[0031] The time zone systems of multiple countries and regions are pre-integrated in the database of the intelligent HVAC system, covering key data such as the offsets of each region from Coordinated Universal Time (UTC). After the initial startup of the intelligent HVAC system, the system is in a standby state waiting for user operations. The user selects the location in the operation interface, or, after user authorization, the system can also obtain the geographical location information of the system through the built-in geolocation module (such as GNSS+IP positioning fusion technology) to accurately determine the longitude and latitude; according to the geographical location data input by the user or automatically located, the system finds the corresponding time zone information in the global time zone database, thereby automatically calibrating the local time.

[0032] After completing the local time calibration, the HVAC system will further adjust the environmental control mode in combination with the geographical location. For example, if the system is located in the temperate zone of the Northern Hemisphere, when the local time enters the winter period, the HVAC system will automatically determine and enable the AI control mode, and intelligently adjust its own operating power and duration according to various environmental factors such as indoor and outdoor temperature and humidity to provide a comfortable indoor environment. When the local time enters summer, the HVAC system will automatically switch to the standby mode to reduce unnecessary energy consumption, realizing the automatic intelligent adjustment of the heating mode with the change of time and season in different regions.

[0033] For most regions, a set of general initial environmental control strategies are set in the HVAC system. The environmental control strategies are used to control the working mode, operating power of the HVAC system within a specific time period, and the switching of the working mode at a specific time point. For example, at 18:00 local time, at dusk, the HVAC system needs to prepare to heat the indoor environment, and at 6:00 local time, at dawn, the HVAC system can stop heating.

[0034] Optionally, some regions implement the daylight saving time system, which is a system that artificially stipulates local time to save energy. The unified time adopted during the implementation of this system is called "daylight saving time". Generally, in the summer when it gets light early, the time is artificially adjusted forward by one hour, which can make people get up and go to bed earlier, reduce the lighting amount, make full use of the light resources, and thus save lighting electricity.

[0035] The HVAC system details key information such as the effective date, end date, and time offset of daylight saving time in each country. After the HVAC system completes geographical location positioning and time zone matching, it will automatically query the daylight saving time information of the corresponding region in the international daylight saving time rule library. When it detects that the current time is approaching the effective date of daylight saving time, the system prepares the time adjustment operation in advance. At the effective moment, the system automatically adjusts the time reference according to the offset in the daylight saving time rule library, for example, advancing the time by 1 hour. At the end of daylight saving time, the system can also automatically callback the time according to the rules to ensure the accuracy of the time.

[0036] When the daylight saving time system is used, compared with the standard time, the change time point of the outdoor environment changes. The HVAC system needs to change the time point of the execution strategy in the initial environment control strategy for the adjusted daylight saving time. Therefore, for regions implementing the daylight saving time system, the intelligent HVAC control method proposed in the embodiments of this application also proposes a method for calibrating the system execution time for the daylight saving time system, such as Figure 2 As shown, in some embodiments of this application, the specific method for calibrating time includes but is not limited to the following steps S210 to step S220: Step S210, obtain the real-time positioning, determine the local time zone, and obtain the local standard time according to the local time zone; Step S220, obtain the daylight saving time offset rule of the local area, and adjust the local standard time through the daylight saving time offset rule to obtain the control time.

[0037] The database of the HVAC system stores time zone information for various regions, including the offset from UTC and daylight saving time rules, etc. When approaching the effective date of daylight saving time, the HVAC system automatically adjusts the system time at the moment when daylight saving time takes effect. Exemplarily, assuming the real-time location information of the HVAC system is in New York, on the second Sunday of March every year, the HVAC system will automatically add 1 hour to the local standard time to obtain the control time; or, if the HVAC system is located in Tokyo (UTC+9), when the UTC time is 12:00, the HVAC system calculates that the local time is 21:00. At the same time, the HVAC system will also judge whether it is currently in the daylight saving time period according to the daylight saving time rules in the database. If it is in the daylight saving time, the local time will be adjusted accordingly. This automatic switching avoids the trouble of manual adjustment by users. The dynamic daylight saving time switching mechanism of this system ensures that the HVAC system can seamlessly connect and always maintain an accurate time reference when the daylight saving time changes in different regions, providing users with stable and efficient HVAC control services.

[0038] In some embodiments of the present application, the process of matching the climate zone parameter library based on the geographical location is also an important link for the intelligent HVAC system to achieve precise adjustment of the HVAC strategy. For regions located at different latitudes, the outdoor environmental states affected by solar illumination are different. Therefore, the indoor environmental control strategies also need to be changed according to the location information.

[0039] First, the process of determining the climate information through the location information and adjusting the general strategy through the climate information includes, but is not limited to, the following steps S310 to S320: Step S310, determine the climate information according to the latitude information in the real-time location, use the climate information to match in the local climate database to obtain the climate zone correction factor, and determine the power change correction time according to the climate zone correction factor; Step S320, determine the key points of air circulation according to the climate correction factor. The key points of air circulation include the temperature control strategy with temperature as the regulation focus and the corresponding temperature regulation target, and the humidity control strategy with humidity as the regulation focus and the corresponding humidity regulation target; Step S330, obtain multiple initial power change time points in the initial environmental control strategy, adjust each initial power change time point through the power change correction time, and determine the target power change time points in the target environmental control strategy. Among them, the formula for adjusting the initial power change time point through the power change correction time is: ; represents the target power change time point, represents the initial power change time point, represents the power change correction time.

[0040] The HVAC system comprehensively analyzes the current local time, the type of climate zone determined by the climate zone adaptation algorithm, and the personalized parameters preset by the user. The HVAC system dynamically adjusts the environmental control strategy according to the characteristics of different climate zones. Taking the frigid zone as an example, due to the long and extremely cold winter, to ensure a suitable indoor environment, the HVAC system defaults to start the anti-freezing mode. When the outdoor temperature is lower than a specific threshold, such as -10°C, the HVAC system operates in a constant temperature output mode to keep the indoor temperature at a certain level and prevent the pipes from freezing. In the temperate zone, the winter is relatively mild, and the starting temperature threshold of the AI control mode may be set at 18°C. The system will flexibly adjust the operation of the heating equipment according to the indoor and outdoor temperature changes to achieve a balance between comfort and energy conservation. For the tropical zone, the climate is hot and humid. The HVAC system will limit the high-temperature humidity adjustment. When the humidity is greater than 70%, the dehumidification heating function is started, with the focus on adjusting the indoor humidity to improve the living comfort. Through this dynamic strategy adjustment based on the climate zone, the system can better adapt to the climate differences in different regions and provide personalized and efficient heating services.

[0041] The embodiments of this application propose an adjustment formula for the power change time point ; For the adjustment process of one of the environmental variables, represents the initial power change time point corresponding to the power for executing the environmental variable, represents the power change correction time for adjusting the general change time point, which is a correction value set according to the characteristics of different climate zones, represents the modified target power change time point. In different regions, the basic environmental conditions of temperature and humidity changes are different, and the time for actively controlling the indoor temperature and indoor humidity is different. For example, in high-latitude regions, the external perceived temperature is generally cold, and the HVAC system needs to preheat before the sun sets. Therefore, the for controlling the start of the heating mode needs to be at least two hours in advance. The power change time point for night heating is corrected from the general 18:00 to 16:00. In addition, assuming the sun rises at 8:00, but the environmental temperature in high-latitude regions rises slowly. Therefore, the HVAC system needs to postpone the time additionally to continue heating. In the morning, the power change correction time can be set to four hours, that is, the one for controlling the closing of the heating mode is adjusted from the general = 6:00 to = 10:00; Or, in the tropical zone, its humidity is higher than the human comfort range all year round. First, the dehumidification mode of the HVAC system can be set to be continuously on. Second, according to the local climate characteristics, the power of the dehumidification mode can also be adjusted, and different dehumidification mode powers are set at different local times to make the indoor humidity reach the human body's perceived comfort range.

[0042] In addition, multiple temperature sensors and humidity sensors are integrated in the HVAC system to obtain the temperature and humidity outdoors and indoors respectively. The HVAC system will also dynamically correct the operating power and time according to the real-time temperature information and humidity information.

[0043] Specifically, the HVAC system determines the climate zone it belongs to based on real-time positioning, and then determines the climate information according to the climate zone. The HVAC system will comprehensively analyze the current local time, the type of climate zone determined by the climate zone adaptation algorithm, and the personalized parameters preset by the user. If it is winter and the device is located in a cold region, when the local time reaches the heating start time in the set control time and the outdoor temperature is lower than -10°C, the system will give priority to starting the anti-freezing mode to ensure the safe and stable operation of the heating system. In temperate regions, when the local time enters the heating season and the indoor temperature is lower than the lower limit of the comfortable temperature set by the user (such as 18°C), the system will automatically switch to the AI control mode, and the sensors will be used to monitor the indoor and outdoor environmental parameters in real time, and the power and operation time of the heating equipment will be intelligently adjusted to maintain the indoor comfortable temperature. In summer, regardless of the climate zone, as long as the local time meets the preset summer time period, the system will switch to the standby mode to reduce energy consumption.

[0044] The HVAC system can access the weather API interface to realize the linkage with the local real-time meteorological data, so as to correct the heating strategy. Through this interface, the system can obtain the local weather information in real time, such as key meteorological information such as air temperature, wind speed, and precipitation.

[0045] On the one hand, the weather information can make the control strategy more in line with the actual weather changes. For example, when the temperature drops suddenly, the system automatically increases the heating power to preheat the room in advance to ensure comfort; in windy weather, the indoor ventilation strategy is adjusted in combination with the outdoor environment. On the other hand, the energy utilization efficiency is improved. The operation of the heating equipment is accurately regulated according to the real-time meteorological data to avoid overheating or insufficient heating and reduce energy waste. This claim enables the intelligent heating system to keep up with the meteorological changes, provides a more comfortable and energy-saving heating experience for users, and enhances the intelligence and practicability of the system.

[0046] As Figure 5 shown, the dynamic correction method is a key link for the intelligent heating system to realize the continuous optimization of the scheduling strategy. The HVAC system arranges multiple sensors indoors and outdoors to monitor the changes in environmental temperature and humidity in real time. At the same time, intelligent devices and data analysis technologies are used to monitor and analyze user behavior, including the user's daily wake-up and sleep times, and the adjustment operations of the indoor temperature at different time periods.

[0047] Based on these real-time monitoring data, the HVAC system uses machine learning algorithms to optimize the scheduling strategy. For example, if the machine learning model analysis finds that users frequently adjust the indoor temperature within a certain period of time, it means that the current heating strategy may not meet user needs. The HVAC system will automatically adjust the heating parameters for that period, such as appropriately increasing or decreasing the heating power. Through continuous learning and adjustment, the system can gradually adapt to the usage habits and environmental changes of different users, making the switching of heating modes more accurate and the temperature control more stable, ultimately achieving the effect of improving user comfort and reducing energy consumption, providing users with a more intelligent and efficient heating experience.

[0048] Based on the above embodiments, this application also provides two specific implementation methods based on actual application scenarios.

[0049] Suppose a multinational company has branches in three representative international metropolises: New York, London, and Tokyo. There are significant time zone differences in different regions, and the climate conditions are also different. In the past, the heating systems of each branch were operated independently and managed separately, which not only led to high management costs, but also made it difficult to ensure the quality and efficiency of heating services. In order to improve overall operational efficiency and reduce energy consumption, the company urgently needs a smart heating system that can achieve unified management across time zones to meet the needs of employees in different regions for a comfortable office environment.

[0050] With the help of advanced GNSS modules, the node devices of each branch can automatically and accurately obtain the local longitude and latitude information. Based on these longitude and latitude data, the system quickly matches them in the global time zone database to determine the corresponding local time zone data. For example, after the node device in New York obtains the longitude and latitude, it matches to the Eastern Time in North America; the node device in London matches to Greenwich Mean Time; and the node device in Tokyo matches to Japan Standard Time.

[0051] After clarifying the time zone, the HVAC system further adjusts the heating strategy according to the local climate zone. New York has a temperate continental climate and is relatively cold in winter. The system sets the winter AI mode startup temperature threshold to 18°C. When the indoor temperature is lower than this threshold, the AI control mode is turned on and the heating equipment is intelligently adjusted to operate. The summer is relatively hot, and the standby temperature is set to 25°C. When the temperature is higher than this, the system enters standby mode. Tokyo has a subtropical monsoon climate. In addition to temperature control, humidity collaborative control is also enabled. When the humidity is >70%, dehumidification and heating are started to improve the comfort of the office environment.

[0052] In terms of daylight saving time switching, the equipment in New York follows the rules of the region where it is located. On the second Sunday of March every year, the equipment automatically increases the time by 1 hour, and the heating end time is postponed from the original 21:00 to 22:00. This adjustment is automatically completed by the system based on the built-in international daylight saving time rule library, without manual intervention.

[0053] In another specific embodiment, assume that a user immigrates from China (UTC+8) to Canada (UTC-5). When in China, the heating system used by the user was configured based on local time and climate conditions. However, Canada not only has a different time zone from China but also has significantly different climate conditions, especially colder in winter. The previous HVAC system configuration used in China is no longer applicable, and the user urgently needs to reconfigure the HVAC system to meet the heating requirements in the new environment and ensure the comfort of life.

[0054] When the user selects "Canada", the system responds quickly and automatically launches a series of operations. First, the system synchronizes with UTC-5 time through the NTP protocol to ensure that the device time is exactly the same as the local time, providing an accurate time basis for subsequent heating scheduling. Then, the system accurately matches the statutory holidays in Canada based on the built-in statutory holiday database. For example, on December 25th, Christmas, an important statutory holiday, the system will forcibly enable the anti-freeze mode to ensure the stable operation of the heating module of the HVAC system during special periods and avoid damage to facilities such as pipes due to low temperature.

[0055] At the same time, the system will automatically load the cold climate parameters according to the characteristics that most areas in Canada belong to the cold climate zone. When the outdoor temperature sensor detects that the outdoor temperature < -10°C, the HVAC system immediately starts the anti-freeze mode and outputs at a constant temperature of 4°C, effectively preventing the pipes from freezing and ensuring the safe and stable operation of the HVAC system in the cold Canadian winter, providing reliable heating protection for users.

[0056] Optionally, on the premise of obtaining the user's permission and authorization, the system can also use advanced machine learning technology to deeply analyze the user's daily routine. Data is collected through smart devices and sensors, such as recording information on the user's daily wake-up and bedtime, as well as operations to adjust the indoor temperature at different time periods. Based on this rich data, the system constructs a user behavior model and analyzes the user's preferences and needs for indoor temperature at different time periods.

[0057] In response to the analysis results, the system dynamically adjusts the preheating time of the heating equipment. For example, if it is found that the user usually wakes up at 7 am, the system will calculate and adjust the preheating time in advance to ensure that the indoor temperature reaches a comfortable state before the user wakes up. In this way, the user does not need to manually adjust the heating settings frequently. Finally, the user configuration time is significantly shortened from the original 2 hours to 5 minutes, greatly improving the efficiency of the user reconfiguring the heating system. At the same time, the temperature control error is accurately controlled within ±0.3°C, significantly enhancing the stability and comfort of the indoor temperature and bringing a more convenient and comfortable heating experience to users.

[0058] In addition, in some embodiments of the present application, the HVAC system can also obtain the local electricity price pattern according to real-time positioning, and adjust the control strategy of the HVAC system according to the electricity price pattern. For example, Figure 4 As shown, the intelligent HVAC control method proposed in the embodiments of the present application further includes, but is not limited to, the following steps S410 to S450: Step S410: Determine the start time point in the target environment control strategy, and obtain the first electricity price information within a preset first time length before and after the start time point; Step S420: If the electricity price at the start point of the first time length is less than the electricity price at the start time point, set the start point of the first time length as the new start time point in the target environment control strategy, and increase the starting power at the new start time point so that it is greater than the power value originally set at the old start time point; Step S430: Determine the end time point in the target environment control strategy, and obtain the second electricity price time information within a preset second time length before and after the end time; Step S440: If the electricity price at the start point of the second time length is greater than the electricity price at the end point of the second time length, set the end point of the second time length as the new end time point in the target environment control strategy, and reduce the power value from the start point of the second time length to the old end time point; Step S450: If the electricity price at the start point of the second time length is less than the electricity price at the end time point, determine the start point of the second time length as the new end time point in the target environment control strategy, and increase the starting power at the new end time point so that it is greater than the power value originally set at the old end time point.

[0059] Specifically, the HVAC system can also obtain the charging standard fluctuation data of the local electricity price at different time periods. The HVAC system obtains the electricity price change curves before and after each power change time point. The obtained time period interval can be 10 minutes before and after the time point or six hours before and after. The HVAC system analyzes the power change status and electricity price change status before and after the power change time point. The power change status includes changing from low power before the power change time point to high power after the power change time point (more accurately, at the power change time point), or changing from high power before the power change time point to low power after the power change time point. The electricity price change status includes changing from low electricity price before the power change time point to high electricity price after the power change time point (more accurately, at the power change time point), or changing from high electricity price before the power change time point to low electricity price after the power change time point. In the steps S410 to S450 of the embodiment, the start time point represents the power change time point when switching from the zero power state to startup, and the end time point represents the power change time point when switching from the operating state to shutdown.

[0060] It should be noted that the specific values of high power and low power in the embodiments of the present application can be determined according to the actual operation strategy of the HVAC system, and will not be limited here. The text representations of high power and low power are only used to represent the rising and falling characteristics of the operating power of the HVAC system before and after a specific time point. The difference between high power and low power is only that the power value in the high power state is greater than the power value in the low power state.

[0061] For one case, such as Figure 6 shown. For example, when before and after the power change time point, the originally set strategy is to switch from low power to high power operation, and the electricity charge rises from a low electricity price to a high electricity price, at this time, the HVAC system advances the power change time point. For example, assume that the system is planned to start heating at 18:00 sharp, that is, at the time point of 18:00, the power of the system increases, and at 18:00, the electricity charge will increase. Therefore, the system advances the power change time point for starting heating to 17:00 sharp. From 17:00 sharp to 18:00, the originally set power is increased so that it is greater than the heating start power originally set at 18:00, and the indoor temperature rises in advance. At 18:00, the actual indoor temperature is slightly higher than the originally set target temperature. When heating reaches 18:00, the system reduces the originally set power so that it is less than the heating start power originally set at 18:00, causing the indoor temperature to drop at a slow speed. After dropping to the pre-set target temperature, the operating power is fine-tuned according to the actual situation.

[0062] However, it should be clear that when before and after the power change time point, the originally set strategy is to switch from low power to high power operation, and the electricity price after the power change time point is lower than the electricity price at the power change time point, the power change time point for switching to high power will not be postponed, ensuring the heating, dehumidification, and air circulation requirements of users during a specific period.

[0063] In addition, as Figure 7 shown, assume that when before and after the power change time point, the originally set strategy is to switch from high power to low power operation, and the electricity charge rises from a high electricity price to a low electricity price. Continuing with the heating module as an example, originally at 5:00 sharp, the system is planned to increase the indoor temperature so that it is higher than the target temperature, so that the indoor temperature drops slowly after 6:00. Assume that the system was originally planned to stop heating at 6:00, and the electricity price at 5:00 is higher than the electricity prices at 6:00 and 7:00. Then the system will appropriately reduce the operating power from 5:00 to 6:00 so that it is less than the originally set operating power. In addition, the system will extend the heating time of the heating module, and the heating module operates until 7:00. From 6:00 to 7:00, the system will heat at the power originally set from 5:00 to 6:00.

[0064] As Figure 8As shown, assume that before and after the power change time point, the originally set strategy is to switch from high power to low power operation, and the electricity charge increases from a low electricity price to a high electricity price. Continuing with the heating module as an example, assume that the HVAC system plans to stop heating at exactly 6 o'clock, and the electricity price starts to increase at 5:30. At this time, the HVAC system will increase the operating power from 5 o'clock to 5:30, so that the indoor temperature at 5:30 is slightly higher than the preset target temperature. Then, the HVAC system can advance the end time point of stopping heating to 5:30, causing the indoor temperature to drop slowly. Or, the HVAC system can also continue heating without stopping, but at an operating power lower than the original power set from 5:30 to 6 o'clock, so as to complete more work during the low electricity price period and reduce energy consumption during the high electricity price period.

[0065] In some embodiments, the HVAC system is also provided with a photovoltaic module and a power storage module. The photovoltaic module is used to generate electricity using solar energy, and the power storage module is used to store the electric energy generated by the photovoltaic module and store electricity from the mains during low electricity price periods. Therefore, through the cooperation of the power storage module, the above embodiments can also have different implementation manners. The power storage module can store the mains electricity and photovoltaic electricity during low electricity price periods and supply power through the power storage module during high electricity price periods, so as to achieve peak shaving and valley filling and reduce the electricity cost. At the same time, the energy storage system can be used as a backup power supply to ensure the basic operation of the heating system in case of a power grid failure, improving the reliability and stability of the system.

[0066] In addition, referring to Figure 9 , this application also provides an intelligent HVAC control device 900, including: A positioning module 901, configured to obtain real-time positioning, calibrate the built-in time of the continuously operating system through the real-time positioning, and determine the control time; A policy matching module 902, configured to determine an initial environmental control policy according to the real-time positioning and match the initial environmental control policy with the control time, where the initial environmental control policy represents a general indoor environmental state control policy; A climate matching module 903, configured to obtain climate information according to the real-time positioning, determine a climate zone correction factor through the climate information, and use the climate zone correction factor to adjust the initial environmental control policy to determine the target environmental control policy.

[0067] The above intelligent HVAC control device and intelligent HVAC control method are based on the same inventive concept and will not be elaborated here.

[0068] In addition, referring to Figure 10 , Figure 10 illustrates the hardware structure of an electronic device in another embodiment. The electronic device includes: The processor 1001 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 1002 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 1002 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 1002 and are called by the processor 1001 to execute the intelligent HVAC control method based on real-time positioning in the embodiments of the present application. For example, execute the Figure 1 method steps S110 to step S100 in the above description, Figure 2 method steps S210 to step S220 in the above description, Figure 3 method steps S310 to step S330 in the above description, Figure 4 method steps S410 to step S450 in the above description; The input / output interface 1003 is used to implement information input and output; The communication interface 1004 is used to implement communication interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.); The bus 1005 transmits information between various components of the device (such as the processor 1001, the memory 1002, the input / output interface 1003, and the communication interface 1004); Among them, the processor 1001, the memory 1002, the input / output interface 1003, and the communication interface 1004 achieve communication connections with each other inside the device through the bus 1005.

[0069] 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 intelligent HVAC control method based on real-time positioning. For example, execute the Figure 1 method steps S110 to step S130 in the above description, Figure 2 method steps S210 to step S220 in the above description, Figure 3The method steps S310 to S330 in Figure 4 The method steps S410 to S450 in

[0070] 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 a memory remotely disposed relative to the processor, and these remote memories may 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.

[0071] 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.

[0072] Those skilled in the art can understand that Figures 1 to 4 The technical solutions shown in

[0073] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0074] 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 devices and equipment can be implemented as software, firmware, hardware, and appropriate combinations thereof.

[0075] In the description of the present 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 the present application described herein can be implemented in an order different from those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, 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.

[0076] It should be understood that in the present 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, indicating that there can be three relationships. 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 represents an "or" relationship between the associated objects before and after. "At least one (one) of the following" or its similar expression refers to any combination of these items, including any combination of single item (one) 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.

[0077] In several embodiments provided by the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the above-mentioned division of units is only a logical function division. In actual implementation, there can 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 between each other can be through some interfaces. The indirect coupling or communication connection of the apparatus or unit can be in electrical, mechanical or other forms.

[0078] The units described above as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place, or can be 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.

[0079] 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.

[0080] 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 this 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 that can store programs, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs.

[0081] The preferred embodiments of the embodiments of the present application have been described above with reference to the accompanying drawings. However, this does 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 fall within the scope of the rights of the embodiments of the present application.

Claims

1. An intelligent HVAC control method based on real-time positioning, characterized in that, Including: Obtain real-time positioning, calibrate the built-in time of the persistently running system through the real-time positioning, and determine the control time; Determine the initial environment control strategy according to the real-time positioning, and match the initial environment control strategy with the control time, wherein the initial environment control strategy represents a general indoor environment state control strategy; Obtain climate information according to the real-time positioning, determine the climate zone correction factor through the climate information, and use the climate zone correction factor to adjust the initial environment control strategy to determine the target environment control strategy.

2. The intelligent HVAC control method according to claim 1, wherein The obtaining of the real-time positioning, calibrating the built-in time of the persistently running system through the real-time positioning, and determining the control time includes: Obtain real-time positioning, determine the local time zone, and obtain the local standard time according to the local time zone; Obtain the local daylight saving offset rule, and adjust the local standard time through the daylight saving offset rule to obtain the control time.

3. The intelligent HVAC control method according to claim 1, characterized in that, The obtaining of the climate information according to the real-time positioning, determining the climate zone correction factor through the climate information, and using the climate zone correction factor to adjust the initial environment control strategy includes: Determine the climate information according to the latitude information in the real-time positioning, match the climate information in the local climate database to obtain the climate zone correction factor, and determine the power change correction time according to the climate zone correction factor; Determine the key points of air circulation according to the climate correction factor, where the key points of air circulation include a temperature control strategy with temperature as the regulation focus and the corresponding temperature regulation target, and a humidity control strategy with humidity as the regulation focus and the corresponding humidity regulation target; Obtain multiple initial power change time points in the initial environment control strategy, and adjust each of the initial power change time points through the power change correction time to determine the target power change time points in the target environment control strategy, where the formula for adjusting the initial power change time point through the power change correction time is: ； indicates the target power change time point, indicates the initial power change time point, indicates the power change correction time.

4. The intelligent HVAC control method according to claim 1, characterized in that, The method further includes: Obtain weather information according to the real-time positioning, and adjust the target environment control strategy according to the weather information.

5. The intelligent HVAC control method according to claim 1, wherein The method further includes: Determine the start time point in the target environment control strategy, and obtain the first electricity price information within a preset first time length before and after the start time point; If the electricity price at the start of the first time length is less than the electricity price at the start time point, set the start of the first time length as the new start time point in the target environment control strategy, and increase the starting power at the new start time point to be greater than the power value originally set at the old start time point.

6. The intelligent HVAC control method according to claim 1, characterized in that, The method further includes: Determine the end time point in the target environment control strategy, and obtain the second electricity price time information within a preset second time length before and after the end time; If the electricity price at the start point of the second time length is greater than the electricity price at the end point of the second time length, set the end point of the second time length as the new end time point in the target environmental control strategy, and reduce the power value from the start point of the second time length to the old end time point.

7. The intelligent HVAC control method according to claim 6, characterized in that, The method further includes: If the electricity price at the start point of the second time length is less than the electricity price at the end time point, determine the start point of the second time length as the new end time point in the target environmental control strategy, and increase the starting power at the new end time point so that it is greater than the power value originally set at the old end time point.

8. An intelligent HVAC control device, characterized in that, It includes: A positioning module, configured to obtain real-time positioning, calibrate the built-in time of the continuously operating system through the real-time positioning, and determine the control time; A strategy matching module, configured to determine an initial environmental control strategy according to the real-time positioning, and match the initial environmental control strategy with the control time, where the initial environmental control strategy represents a general indoor environmental state control strategy; A climate matching module, configured to obtain climate information according to the real-time positioning, determine a climate zone correction factor through the climate information, and use the climate zone correction factor to adjust the initial environmental control strategy to determine the target environmental control strategy.

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 HVAC control 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 HVAC control method according to any one of claims 1 to 7.

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