Adaptive temperature regulation method for a heating device

Abstract

The application discloses a heating equipment adaptive temperature regulation method, which comprises the following steps: firstly, collecting the temperatures of multiple different areas in a room to obtain indoor ambient temperature, and collecting the temperature of a preset position outdoors to obtain outdoor ambient temperature; then, determining an indoor-outdoor temperature difference value according to the indoor ambient temperature and the outdoor ambient temperature; next, determining a corresponding power output percentage according to the indoor-outdoor temperature difference value and a preset power output table; after determining the real-time output power of the heating equipment according to the rated power of the heating equipment and the power output percentage, generating and executing a temperature regulation strategy according to the real-time output power and the type of the heating equipment. The application realizes the purposes of precise temperature control and energy saving and consumption reduction of heating through multi-area temperature measurement, temperature difference-power quantization matching and adaptive adjustment combined with equipment characteristics.

Description

Technical Field

[0001] The embodiments of this application relate to, but are not limited to, the field of heating equipment control technology, and in particular to an adaptive temperature regulation method for heating equipment. Background Technology

[0002] Current heating systems suffer from significant shortcomings in temperature control. The comprehensiveness and accuracy of temperature sensing are lacking, often relying solely on localized temperature measurements to determine indoor temperature, failing to objectively reflect the temperature distribution differences across the entire indoor space. Furthermore, the system's control logic does not adequately integrate indoor and outdoor temperature changes, failing to accurately capture the crucial factor of indoor-outdoor temperature difference that influences heating demand, resulting in a mismatch between heating power output and actual heat load requirements. Existing systems mostly employ fixed power output or simple segmented power switching control methods, lacking flexible and precise power adaptation mechanisms. Moreover, after determining the control parameters, the lack of tailored adjustment schemes based on the characteristics of the heating equipment further exacerbates the problems of insufficient temperature control accuracy and lag in response, affecting not only heating comfort but also causing unnecessary energy waste. Summary of the Invention

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

[0004] This application provides an adaptive temperature regulation method for heating equipment. By measuring temperature in multiple zones and matching temperature difference with power quantization, and by adapting the method to the characteristics of the equipment, the method achieves the goals of precise temperature control and energy saving.

[0005] This application provides an adaptive temperature regulation method for heating equipment, comprising: collecting temperature data from multiple different areas indoors to obtain indoor ambient temperature; collecting temperature data from a preset outdoor location to obtain outdoor ambient temperature; determining an indoor-outdoor temperature difference based on the indoor and outdoor ambient temperatures; determining a corresponding power output percentage based on the indoor-outdoor temperature difference and a preset power output table; determining the real-time output power of the heating equipment based on its rated power and the power output percentage; and generating and executing a temperature regulation strategy based on the real-time output power and the type of heating equipment.

[0006] In one embodiment of this application, determining the corresponding power output percentage based on the indoor-outdoor temperature difference and a preset power output table includes: determining the power output percentage as 100% when the indoor-outdoor temperature difference is greater than or equal to a first temperature threshold defined by the power output table; determining the power output percentage as 0 when the indoor-outdoor temperature difference is less than or equal to a second temperature threshold defined by the power output table; and determining the power output percentage of the indoor-outdoor temperature difference based on the temperature-power coupling function of the power output table when the indoor-outdoor temperature difference does not exceed the temperature difference range defined by the power output table but the power output table does not record the power output percentage corresponding to the indoor-outdoor temperature difference.

[0007] In one embodiment of this application, the method further includes: when the cumulative change in the indoor-outdoor temperature difference exceeds a third temperature threshold or at each preset time interval, selecting multiple power feature points from a preset power output range; obtaining the indoor-outdoor temperature difference value corresponding to each power feature point; obtaining multiple temperature difference power data combinations based on the power feature points and their corresponding power feature points; calculating a first parameter and a second parameter of the temperature difference power coupling function curve based on the multiple temperature difference power data combinations; and correcting the temperature difference power coupling function curve based on the first parameter and the second parameter to obtain a corrected temperature difference power coupling function curve.

[0008] In one embodiment of this application, after collecting the indoor ambient temperature and the outdoor ambient temperature, the method further includes: performing a moving average filtering process on the indoor ambient temperature and the outdoor ambient temperature to obtain filtered indoor ambient temperature and outdoor ambient temperature; and performing temperature compensation processing on the filtered indoor ambient temperature and the outdoor ambient temperature to obtain corrected indoor ambient temperature and outdoor ambient temperature.

[0009] In one embodiment of this application, the indoor ambient temperature is acquired by a first temperature sensor, and the outdoor ambient temperature is acquired by a second temperature sensor. The step of performing temperature compensation processing on the filtered indoor and outdoor ambient temperatures to obtain corrected indoor and outdoor ambient temperatures includes: determining a corresponding first sensor compensation coefficient based on the installation location of the first temperature sensor; performing temperature compensation processing on the filtered indoor ambient temperature based on the first sensor compensation coefficient to obtain the corrected indoor ambient temperature; determining a corresponding second sensor compensation coefficient based on the installation location of the second temperature sensor; and performing temperature compensation processing on the filtered outdoor ambient temperature based on the second sensor compensation coefficient to obtain the corrected outdoor ambient temperature.

[0010] In one embodiment of this application, during the execution of the temperature regulation strategy, the method further includes: collecting the actual operating current and actual operating voltage of the heating equipment; obtaining the actual output power based on the actual operating current and the actual operating voltage; correcting the power output percentage based on the comparison result between the actual output power and the real-time output power; and adjusting the real-time output power of the heating equipment based on the corrected power output percentage.

[0011] In one embodiment of this application, generating and executing a temperature regulation strategy based on the real-time output power and the type of heating equipment includes: when the type of heating equipment is an electric heating equipment, generating a corresponding pulse width modulation signal based on the real-time output power, and controlling the conduction angle of the bidirectional thyristor through the pulse width modulation signal to adjust the output power of the electric heating equipment; when the type of heating equipment is a heat pump equipment, adjusting the compressor operating frequency and electronic expansion valve opening of the heat pump equipment based on the real-time output power to adjust the output power of the heat pump equipment.

[0012] In one embodiment of this application, the method further includes: when the outdoor ambient temperature is invalid, determining the power output percentage based on the rate of change of the indoor ambient temperature.

[0013] In one embodiment of this application, the installation location of the first temperature sensor meets at least one of the following conditions: 1.2 to 1.8 meters from the indoor ground; not less than 0.5 meters from the exterior wall; and avoiding areas exposed to direct sunlight and ventilation openings.

[0014] In one embodiment of this application, the second temperature sensor is a temperature and humidity detection module, which is equipped with a heating film and is installed outdoors in a location without direct sunlight.

[0015] This application provides an adaptive temperature regulation method for heating equipment. First, it collects temperature data from multiple different areas indoors to obtain the indoor ambient temperature, and then collects the temperature data from a preset outdoor location to obtain the outdoor ambient temperature. Next, it determines the indoor-outdoor temperature difference based on the indoor and outdoor ambient temperatures. Then, it determines the corresponding power output percentage based on the indoor-outdoor temperature difference and a preset power output table. After determining the real-time output power of the heating equipment based on its rated power and power output percentage, it generates and executes a temperature regulation strategy based on the real-time output power and the type of heating equipment. This application, by collecting temperature data from multiple indoor areas and the outdoor environment, achieves comprehensive and accurate temperature sensing across multiple indoor areas, overcoming the limitations of traditional systems that rely on localized temperature measurement. By matching the indoor-outdoor temperature difference with the power output percentage, it establishes a quantitative correlation between temperature difference and power, ensuring precise matching between heating power and temperature demand, and avoiding mismatches between power output and actual heat load. By developing adaptive adjustment strategies based on equipment type, the operating characteristics of the heating equipment can be fully adapted, optimizing the flexibility and accuracy of power adjustment. This effectively solves the problems of lag and poor control precision in traditional systems, thereby improving heating comfort and reducing energy consumption. Attached Figure Description

[0016] Figure 1 This is a flowchart of the adaptive temperature adjustment method for heating equipment provided in the embodiments of this application; Figure 2 This is a flowchart of the temperature difference power coupling function correction provided in the embodiments of this application; Figure 3 This is a flowchart of temperature data preprocessing provided in an embodiment of this application; Figure 4 This is provided by the embodiments of this application. Figure 3 The detailed flowchart of step 320; Figure 5 This is a flowchart of the output power correction provided in the embodiments of this application. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0018] It should be noted that although the flowchart shows a logical order, in some cases, the steps shown or described may be performed in a different order than that shown in the flowchart. The terms "first," "second," etc., used in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the structures, proportions, sizes, etc., depicted in the drawings are only used to complement the content disclosed in the specification for those skilled in the art to understand and read, and are not intended to limit the implementation conditions of this application. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in proportions, or adjustments to size, without affecting the effects and purposes achieved by this application, should still fall within the scope of the technical content disclosed in this application. Similarly, the terms such as "upper," "lower," "left," "right," "middle," and "one" used in this specification are only for clarity of description and are not used to limit the scope of implementation of this application. Changes or adjustments in their relative relationships, without substantially altering the technical content, should also be considered within the scope of implementation of this application.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0020] The power control mechanism of traditional heating systems suffers from a fundamental technical contradiction, the core of which lies in the essential disconnect between static power configuration and dynamic temperature difference. Existing technologies employ fixed power output or preset segmented power adjustment modes, failing to adaptively adjust to real-time changes in indoor and outdoor temperature differences. This results in a mismatch between heating power output and actual heat load demand. When the indoor and outdoor temperature difference exceeds the normal range, the fixed power output is insufficient to meet the actual heat load requirements, failing to guarantee heating effectiveness; conversely, in scenarios with smaller temperature differences, the system maintains high power operation, causing unnecessary energy waste.

[0021] Meanwhile, traditional systems lack a quantitative coupling relationship between temperature difference and power, and cannot match the correlation characteristics between the two through scientific models, further exacerbating the mismatch between power output and actual heat demand. The limitations of existing technology are also reflected in the lag in control logic. Segmented power adjustment typically relies on simple temperature threshold triggers, failing to achieve a continuous and smooth power transition. When the indoor and outdoor temperature difference fluctuates around the threshold, the system frequently switches power levels, causing temperature oscillations, affecting heating comfort, and resulting in equipment wear and tear. Furthermore, traditional systems lack comprehensive and accurate temperature sensing, often relying solely on local temperature measurement data to determine indoor temperature status, making it difficult to objectively reflect the temperature distribution differences throughout the entire indoor space. In addition, the control logic does not fully integrate the characteristics of the heating equipment to develop adaptive adjustment schemes, ultimately leading to insufficient temperature control accuracy and lag in response, reducing user experience and causing energy waste.

[0022] In view of this, this application provides an adaptive temperature regulation method for heating equipment. First, temperature data is collected from multiple different areas indoors to obtain the indoor ambient temperature, and the temperature at a preset outdoor location is also collected to obtain the outdoor ambient temperature. Then, the indoor and outdoor temperature difference is determined based on the indoor and outdoor ambient temperatures. Next, the corresponding power output percentage is determined based on the indoor and outdoor temperature difference and a preset power output table. After determining the real-time output power of the heating equipment based on its rated power and power output percentage, a temperature regulation strategy is generated and executed based on the real-time output power and the type of heating equipment. This application, by collecting temperature data from multiple indoor areas and the outdoor environment, can achieve comprehensive and accurate sensing of indoor temperatures across multiple areas, overcoming the limitations of traditional systems that rely on local temperature measurement. By matching the indoor and outdoor temperature difference with the power output percentage, a quantitative correlation between temperature difference and power is established, enabling precise matching of heating power with temperature difference requirements and avoiding mismatch between power output and actual heat load. By developing adaptive adjustment strategies based on equipment type, the operating characteristics of the heating equipment can be fully adapted, optimizing the flexibility and accuracy of power adjustment. This effectively solves the problems of lag and poor control precision in traditional systems, thereby improving heating comfort and reducing energy consumption.

[0023] The embodiments of this application will be further described below with reference to the accompanying drawings.

[0024] Reference Figure 1 , Figure 1 This is a flowchart of an adaptive temperature adjustment method for heating equipment provided in an embodiment of this application. The process may specifically include, but is not limited to, steps 110 to 160.

[0025] Step 110: Collect temperature data from multiple different areas indoors to obtain the indoor ambient temperature; Step 120: Collect the temperature at the preset outdoor location to obtain the outdoor ambient temperature; Step 130: Determine the indoor and outdoor temperature difference based on the indoor and outdoor ambient temperatures; Step 140: Determine the corresponding power output percentage based on the indoor and outdoor temperature difference and the preset power output table; Step 150: Determine the real-time output power of the heating equipment based on its rated power and power output percentage; Step 160: Generate and execute a temperature regulation strategy based on the real-time output power and the type of heating equipment.

[0026] Steps 110 to 160 will be described in detail below.

[0027] In a feasible embodiment, in step 110, temperature data can be collected from multiple different areas of the room by deploying first temperature sensors in different areas. Specifically, the sensors can be embedded in the heating equipment body and deployed in key areas of the room such as the center of the living room, near windows, and in corners, thereby achieving accurate multi-point sampling of the indoor temperature field (e.g., sampling frequency of 1Hz, measurement error ±0.2℃), ensuring that the collected indoor ambient temperature data can objectively reflect the overall indoor temperature distribution.

[0028] In one feasible embodiment, the mounting location of the first temperature sensor must meet at least one of the following conditions: The temperature sensor should be installed at a height between 1.2 meters and 1.8 meters above the indoor floor. The temperature sensor should be installed at a distance of no less than 0.5 meters from indoor or outdoor walls. The temperature sensor should be placed away from areas exposed to direct sunlight and ventilation openings to avoid environmental factors interfering with the accuracy of temperature acquisition.

[0029] In one feasible embodiment, at least two spatial points are used to collect indoor ambient temperature data: one integrated into the air outlet of the heating equipment to capture the real-time temperature at the equipment's output; and the other positioned at the center of the room's diagonal, 1.5m above the ground, to collect the average ambient temperature of the indoor space. The two sets of temperature data are processed using a weighted average algorithm to eliminate differences in the indoor temperature field distribution. The weighting coefficients are dynamically adjusted according to the room area; for example, rooms under 50 square meters use a 1:1 equal weighting, while rooms over 50 square meters use a weighting of 0.6 for the equipment and 0.4 for the space, ensuring that the temperature calculation results closely match the actual heat distribution characteristics of different apartment types.

[0030] In one feasible embodiment, in step 120, the outdoor ambient temperature can be acquired by a second temperature sensor. The second temperature sensor can be a temperature and humidity detection module, which can be equipped with a heating film to provide low-temperature anti-frost functionality, adapting to low-temperature outdoor environments and preventing frost from affecting the accuracy of temperature acquisition.

[0031] In one feasible embodiment, the second temperature sensor can be installed outdoors in a location without direct sunlight, thereby eliminating temperature measurement deviations caused by direct sunlight. The sampling frequency of this temperature and humidity detection module is no less than 1Hz, and the temperature measurement error is controlled within ±0.2℃, ensuring the real-time and accurate nature of outdoor ambient temperature data and providing reliable data support for subsequent calculations of indoor and outdoor temperature differences.

[0032] In one feasible embodiment, in step 130, the indoor ambient temperature can be considered. and outdoor ambient temperature The difference between indoor and outdoor temperatures is obtained. ,Right now = - .

[0033] In one feasible embodiment, the average value of temperature data collected from each indoor area can be calculated, and this average value can be determined as the representative value of the indoor ambient temperature. Then, the difference between this representative value and the outdoor ambient temperature can be calculated to obtain the indoor-outdoor temperature difference value that reflects the heat exchange demand between indoors and outdoors. Alternatively, temperature data from key indoor areas can be selected as the indoor ambient temperature, and the difference between this indoor and outdoor ambient temperatures can be calculated to obtain the indoor-outdoor temperature difference value for the corresponding scenario. .

[0034] In one feasible embodiment, in step 140, the power output table defines the percentage of power output corresponding to the current temperature difference within the temperature difference range of 0°C to 40°C. The continuous distribution relationship is shown in Table 1. The parameter settings in this table are obtained by fitting a large dataset of thermal response data from over 100,000 different apartment types. The apartment types covered span six climate zones, including frigid northern regions and temperate southern regions. This large-scale data fitting method optimizes the temperature difference-power mapping curve, making the curve more closely match the actual heat load requirements of different climate conditions and apartment types. Table 1 lists the power output percentage corresponding to typical temperature difference ranges. This table allows you to intuitively view the percentage of base power output under different temperature difference scenarios. This can provide a reliable reference for determining the subsequent real-time power output.

[0035] Table 1. Correspondence between temperature difference range and power output percentage

[0036] As can be seen from Table 1, at 0℃≤ It exhibits a linear increasing characteristic within the ≤40℃ range.

[0037] In one feasible embodiment, after obtaining the power output percentage corresponding to the current temperature difference through the power output meter, the rated power of the heating equipment can be used as a reference. and power output percentage The product of these two values ​​yields the real-time output power of the heating equipment. ,Right now The rated power of the equipment is pre-stored in the control unit integrated within the heating equipment according to the equipment model. It can be directly retrieved for calculation of real-time output power without the need for additional external equipment to obtain parameters.

[0038] In one feasible embodiment, during the process of determining the corresponding power output percentage based on the indoor-outdoor temperature difference and a preset power output table: When the indoor and outdoor temperature difference is greater than or equal to the first temperature threshold defined by the power output meter, the power output percentage is determined to be 100%. When the indoor and outdoor temperature difference is less than or equal to the second temperature threshold defined by the power output table, the power output percentage is determined to be 0. When the indoor and outdoor temperature difference does not exceed the temperature difference range defined by the power output meter, but the power output meter does not record the power output percentage corresponding to the indoor and outdoor temperature difference, the power output percentage of the indoor and outdoor temperature difference is determined according to the temperature difference power coupling function of the power output meter.

[0039] In one feasible embodiment, when the indoor-outdoor temperature difference is greater than or equal to 40°C, the power output percentage can be set to 100%, and the rated power can be adjusted to 100%, so that the real-time output power equals the rated power, allowing the device to operate at full power to withstand extreme low temperatures. When the indoor-outdoor temperature difference is less than or equal to 0°C, the power output percentage can be reduced to 0%, and the device can enter standby mode. This linear adjustment logic can overcome the limitations of the stepped response of traditional segmented control, achieving a smooth transition within the power range of 0% to 100%.

[0040] In one feasible embodiment, for cases where the indoor-outdoor temperature difference does not exceed the 0°C to 40°C range defined by the power output table, but the power output table does not directly record the power output percentage corresponding to that temperature difference, the power output percentage for that temperature difference can be determined based on the temperature difference-power coupling function of the power output table. This temperature difference-power coupling function can be calculated using linear interpolation. Specifically, two typical temperature difference values ​​adjacent to the current temperature difference value and their corresponding power output percentages in the power output table can be selected as reference points, and the power output percentage corresponding to the current temperature difference value can be obtained through linear interpolation. This method has a simple and efficient calculation logic, ensuring a continuous and smooth transition in power output. Furthermore, the temperature difference-power coupling function can also employ nonlinear interpolation or polynomial fitting algorithms according to actual needs to further improve the accuracy of power matching and adapt to the differences in heat load characteristics of different climate zones and different apartment types.

[0041] In one feasible embodiment, to address potential power output deviations during heating, temperature difference sampling and power calculation can be performed every 3 seconds to ensure real-time data acquisition and timely power adjustment. Simultaneously, a proportional-integral-derivative (PID) control algorithm can be introduced to correct for percentage deviations in power output. This algorithm's control cycle can be controlled within 100ms, enabling rapid response to subtle deviations in power output and ensuring the actual output power... The deviation from the theoretical calculation value is no more than ±2%, which effectively improves the accuracy and stability of the power regulation of the heating system and avoids temperature oscillation problems caused by power fluctuations.

[0042] In one feasible embodiment, to avoid deviations in the power mapping relationship, the temperature difference power coupling function can be periodically calibrated and maintained, such as... Figure 2 As shown, the correction process may include, but is not limited to, steps 210 to 240.

[0043] Step 210: When the cumulative change in the indoor and outdoor temperature difference exceeds the third temperature threshold or at each preset time interval, select multiple power characteristic points from the preset power output range. Step 220: Obtain the indoor and outdoor temperature difference values ​​corresponding to each power characteristic point, and obtain multiple temperature difference power data combinations based on the power characteristic points and their corresponding power characteristic points; Step 230: Calculate the first and second parameters of the temperature difference power coupling function curve based on the combination of multiple temperature difference power data; Step 240: Correct the temperature difference power coupling function curve according to the first parameter and the second parameter to obtain the corrected temperature difference power coupling function curve.

[0044] In a feasible embodiment, the third temperature threshold can be set according to the actual application scenario, for example, it can be set to 5℃, and the preset time period can be set to 72 hours. The preset power output range is the effective power range of the system operation, and representative power nodes such as 25%, 50%, and 75% can generally be selected as feature points. Selecting multiple feature points can ensure the comprehensiveness of calibration, avoid the deviation caused by calibration of a single feature point, and make the subsequent corrected coupling function curve more closely match the actual operating conditions.

[0045] In one feasible embodiment, when the device operates to each selected power characteristic point, the corresponding indoor and outdoor temperature difference value can be collected synchronously, and each group of indoor and outdoor temperature difference values ​​and power characteristic points can be matched one by one to form multiple sets of temperature difference power data combinations.

[0046] In a feasible embodiment, the temperature difference power coupling function curve can generally adopt a linear function model, whose expression can be set as y=ax+b, where y represents the power output percentage and x represents the indoor-outdoor temperature difference value. In this case, the first parameter is the slope 'a' of the linear function, and the second parameter is the intercept 'b'. By combining multiple sets of temperature difference power data obtained in step 220 and substituting them into the function model, the specific values ​​of the slope and intercept can be calculated using fitting algorithms such as the least squares method.

[0047] In a feasible embodiment, the first and second parameters calculated in step 230 are updated into the original temperature difference power coupling function to complete the correction of the function curve. The corrected coupling function curve can adapt to the current equipment operating status and environmental conditions.

[0048] In one feasible embodiment, after collecting indoor and outdoor ambient temperatures, the temperature data can be preprocessed before temperature difference calculation to make the subsequent temperature difference calculation results more accurate and eliminate the influence of environmental interference and inherent sensor bias on the data. Figure 3 As shown, the preprocessing process may include, but is not limited to, steps 310 to 320.

[0049] Step 310: Perform a moving average filter on the indoor and outdoor ambient temperatures to obtain the filtered indoor and outdoor ambient temperatures; Step 320: Perform temperature compensation processing on the filtered indoor and outdoor ambient temperatures to obtain the corrected indoor and outdoor ambient temperatures.

[0050] In a feasible embodiment, in step 310, when performing the moving average filtering process, 3 to 10 sampling periods can be selected as the sliding window size. This processing method can continuously capture temperature data within multiple adjacent sampling periods, calculate their average value, and use it as the effective temperature value for the current sampling period. Through this filtering process, temperature data spikes and glitches caused by factors such as instantaneous environmental fluctuations and sensor circuit noise can be effectively filtered out, avoiding the impact of random errors in a single sampling on the overall data accuracy, making the temperature data more stable and more closely reflecting the actual environmental temperature change trend.

[0051] In a feasible embodiment, in step 320, since sensors at different installation locations are affected by the thermal characteristics of the surrounding environment, even after filtering, the collected data may still have a certain deviation. Therefore, a corresponding compensation coefficient can be set according to the specific installation location of the sensor for correction.

[0052] In one feasible embodiment, such as Figure 4 As shown, the process of step 320 may include, but is not limited to, steps 410 to 440.

[0053] Step 410: Determine the corresponding compensation coefficient for the first temperature sensor based on its installation location; Step 420: Perform temperature compensation processing on the filtered indoor ambient temperature according to the first sensor compensation coefficient to obtain the corrected indoor ambient temperature; Step 430: Determine the corresponding compensation coefficient for the second temperature sensor based on its installation location; Step 440: Perform temperature compensation processing on the filtered outdoor ambient temperature according to the compensation coefficient of the second sensor to obtain the corrected outdoor ambient temperature.

[0054] Understandably, the first temperature sensor is used to collect indoor ambient temperature data, and its placement location affects it to varying degrees. For example, a sensor installed near a window is susceptible to radiation from outdoor heat sources, while a sensor installed in a corner is prone to interference from heat conduction through the wall. Sensors in different locations will exhibit varying degrees of data acquisition deviation. Therefore, corresponding compensation coefficient ranges can be pre-defined for different indoor placement areas. During the data processing stage, the compensation coefficient for each first temperature sensor can be matched according to its actual installation location, thereby ensuring the targeted and reasonable nature of the compensation operation.

[0055] In one feasible embodiment, the indoor ambient temperature, even after being processed by moving average filtering, may still exhibit systematic deviations due to the installation location. In this case, the filtered temperature collected by a single sensor can be calculated using the corresponding compensation coefficient of the first sensor to obtain the corrected temperature value for that sensor. Furthermore, the corrected temperature values ​​from multiple sensors can be combined to calculate a representative value that accurately reflects the overall indoor temperature state, avoiding the influence of single-location deviations on the overall judgment of the indoor temperature.

[0056] Understandably, the second temperature sensor, used to collect outdoor ambient temperature data, will have its installation location affecting the accuracy of the data collection. For example, a sensor installed in a shaded area will yield significantly different data compared to one installed near a vent. Therefore, it is possible to pre-set corresponding compensation coefficient ranges for the second sensor in different outdoor deployment scenarios, and then match the corresponding compensation coefficient based on the actual installation location of the second temperature sensor to ensure outdoor temperature compensation.

[0057] In one feasible embodiment, the filtered outdoor ambient temperature may still have systematic deviations due to the installation location. By calculating the filtered outdoor temperature data with the corresponding compensation coefficient of the second sensor, a corrected outdoor ambient temperature can be obtained. This temperature value can more accurately reflect the actual outdoor temperature state, and when the difference is calculated with the corrected indoor ambient temperature, the resulting temperature difference value will better match the actual heat exchange needs between indoors and outdoors.

[0058] In one feasible embodiment, for sensors installed near windows, whose temperature acquisition is easily affected by low outdoor temperatures or sunlight scattering, the compensation coefficient range can be set to +0.5℃ to +1.2℃; for sensors installed in wall corners, whose temperature acquisition is easily affected by the thermal conductivity of the wall, the compensation coefficient range can be set to -0.3℃ to +0.2℃. Through targeted compensation correction, systematic deviations caused by different installation locations can be further eliminated, ensuring that the final temperature data accurately reflects the actual indoor and outdoor ambient temperatures.

[0059] In one feasible embodiment, during the execution of the temperature regulation strategy, the actual output power of the device can be adjusted based on its actual operating data to avoid power output deviation; such as Figure 5 As shown, the process may include, but is not limited to, steps 510 to 530.

[0060] Step 510: Collect the actual operating current and actual operating voltage of the heating equipment; Step 520: Obtain the actual output power based on the actual operating current and actual operating voltage; Step 530: Based on the comparison between the actual output power and the real-time output power, correct the power output percentage, and adjust the real-time output power of the heating equipment according to the corrected power output percentage.

[0061] In a feasible embodiment, in step 510, the actual operating current and voltage of the device can be collected in real time by installing current and voltage detection elements in the device's power supply circuit. These two types of detection elements can be integrated into the device's control module, and the sampling frequency can be matched with the temperature difference sampling frequency mentioned above, thereby ensuring the real-time nature of the collected data.

[0062] In a feasible embodiment, in step 520, the actual operating current and the actual operating voltage are multiplied according to the basic formula for calculating electrical power to calculate the actual output power of the heating equipment. The calculation cycle of this process is no more than 100ms, which can quickly respond to changes in the operating status of the equipment and obtain the true power output of the equipment in a timely manner.

[0063] In a feasible embodiment, in step 530, the real-time output power is the theoretical power value calculated above. The actual output power can be compared with this theoretical power value. When the deviation exceeds ±3%, the power output percentage correction process is immediately initiated. Specifically, the real-time output power can be recalculated by fine-tuning the power output percentage and combining it with the device's rated power. This adjusts the device's power supply parameters, reducing the deviation between the actual output power and the theoretical power value. The entire adjustment cycle is no more than 100ms, enabling rapid power correction and ensuring that the device always outputs power accurately as needed, maintaining the stability and reliability of the heating system's temperature regulation.

[0064] In one feasible embodiment, when generating and executing a temperature regulation strategy based on the real-time output power and the type of heating equipment, if the heating equipment is an electric heating device, a corresponding pulse width modulation signal is generated based on the real-time output power. The conduction angle of the bidirectional thyristor is controlled by the pulse width modulation signal to adjust the output power of the electric heating device. If the heating equipment is a heat pump device, the compressor operating frequency and electronic expansion valve opening of the heat pump device are adjusted based on the real-time output power to regulate the output power of the heat pump device. Specifically, the strategy can be implemented according to the real-time output power... = × The system generates corresponding power regulation control commands, employing differentiated drive methods for different types of heating equipment. For electric heating devices, such as baseboard heaters, a bidirectional thyristor (SCR) of model BTB08-600SL can be used to perform power regulation. Based on real-time power demand, the power output percentage is converted into an equivalent duty cycle, and a 20kHz pulse-width modulation signal is output. This signal controls the conduction angle of the SCR, thereby achieving continuous and precise power regulation of the electric heating device. For heat pump devices, continuous adjustment of the actual output power can be achieved by adjusting the compressor operating frequency and the electronic expansion valve opening. The compressor operating frequency can be set from 30Hz to 120Hz, and the electronic expansion valve opening adjustment steps can be set from 0 to 500 steps, matching the corresponding operating parameters according to the real-time output power. Throughout the power regulation process, the actual operating current and voltage of the equipment can be collected in real time. The current acquisition accuracy can be controlled within ±0.5A, and the voltage acquisition accuracy within ±0.1V, while simultaneously correcting the power output percentage. Deviation is controlled to ensure that the error between the actual output power of the equipment and the theoretical calculation value is controlled within ±3%.

[0065] In one feasible embodiment, when the outdoor ambient temperature is invalid, the power output percentage is determined based on the rate of change of the indoor ambient temperature. Specifically, when the outdoor temperature sensor malfunctions, the system can switch to an indoor temperature change rate-assisted calculation mode. / Replacement for indoor and outdoor temperature difference Perform power output percentage Estimate. Among them... This represents the change in indoor temperature, calculated as the difference in indoor temperature between two consecutive samples. This refers to the time interval between two indoor temperature samplings.

[0066] It should be noted that the aforementioned methods for controlling heating power, including indoor and outdoor temperature difference acquisition and preprocessing, power output percentage matching correction, differentiated power adjustment execution, and fault condition switching, can all be implemented using a control unit integrated within the heating equipment. This control unit, through its built-in algorithm logic and functional components, transforms the aforementioned method steps into executable instruction sequences and data processing flows.

[0067] In one feasible embodiment, indoor temperature monitoring can employ a dual-configuration scheme: one is a DS18B20 digital chip with an accuracy of ±0.5℃, digital output, and single-bus communication for simplified connection, which can be embedded in the heating equipment itself; the other is a PT1000 platinum resistance sensor, paired with a ±1μA accuracy constant current source excitation circuit, which converts resistance changes into voltage signals, sampled by a 24-bit ADS1248 converter, with a measurement error of ±0.2℃ within the range of -40℃ to 85℃. The PT1000 sensor probe is metal-encapsulated and is positioned at the air outlet of the heating equipment and at a diagonal height of 1.5m inside the room, transmitting data to the control unit via shielded twisted-pair cable to eliminate electromagnetic interference. The outdoor temperature sensor can be an SHT30 integrated temperature and humidity module, installed in a north-facing area of ​​the building without direct sunlight, equipped with an anti-frost heating film to ensure stable data acquisition in low-temperature environments. It also uses a sensor module of equivalent accuracy, equipped with a PTFE protective shell and an automatic heating and defrosting system, and can operate stably at -40℃. All sensor nodes are connected to the built-in control unit of the heating equipment via the LoRa wireless communication protocol. This protocol has a transmission distance of ≥300m and an operating power consumption of ≤10μA. The sensor data refresh cycle is controlled within 3 seconds, and the data update cycle is synchronized with the indoor sensors, providing highly timely input for subsequent processes such as temperature difference calculation and power matching.

[0068] In one feasible embodiment, the operation of determining the corresponding power output percentage based on the indoor-outdoor temperature difference and a preset power output table is integrated into a control unit using an STM32H743 microprocessor. This microprocessor integrates a floating-point arithmetic unit, enabling rapid calculation of the temperature difference function. After acquiring the real-time indoor and outdoor temperatures, the control unit first executes a data preprocessing process, specifically including: eliminating instantaneous interference using a moving average filtering algorithm with a window size of 5; then performing targeted temperature compensation based on the sensor's installation location, for example, applying a compensation coefficient of +0.8℃ to the sensor near the window to correct systematic deviations caused by the installation location; finally, the effective temperature difference value is calculated. The control unit uses this effective temperature difference value as an index key to trigger a query operation in the power output table. The query operation is executed efficiently using a binary search algorithm with a time complexity of O(logn), completing the matching of the power output percentage within 10ms. For intermediate temperature difference values ​​not defined in the power output table, the control unit automatically uses linear interpolation to ensure continuous power output response within the 0-40℃ temperature difference range.

[0069] In one feasible embodiment, rated power Measurements can be performed using a high-precision power metering module, which integrates an ACS712 Hall current sensor and a voltage transformer. The Hall current sensor has a range of 0-30A and a linearity of ±0.5%, while the voltage transformer has an input of AC220V and an accuracy of 0.2%. The module's sampling frequency can reach 1kHz. This high-precision power metering module is bidirectionally interconnected with the control unit, transmitting the measured raw voltage and current data to the control unit in real time for data processing and subsequent calculations. The control unit automatically starts the rated power during the initial power-on phase. The calibration process involves progressively loading the rated load at 5%, 25%, 50%, 75%, and 100% in a gradient manner. Simultaneously, the power metering module receives the effective voltage and current values ​​at each load node. A least-squares method is used to fit and generate the actual power curve of the equipment, thereby correcting the deviation between the nominal value on the equipment nameplate and the actual output power. This deviation is typically controlled within ≤2%. During daily operation, the power metering module performs a rated power retest every 10 minutes. The retest data is also fed back to the control unit in real time. The control unit compares the deviations, and if the deviations from the calibration value exceed ±1% after three consecutive retests, the control unit will immediately trigger an alarm, prompting the user to inspect and maintain the equipment.

[0070] In one feasible embodiment, the calibration mechanism for the power output and temperature difference coupling curve can be set to two modes: timed calibration and dynamic calibration, to ensure the long-term accuracy of power regulation. The timed calibration cycle is set to 72 hours. The control unit automatically starts the calibration program at 2:00 AM, during off-peak electricity usage, gradually adjusting the power output percentage from 0% to 100% in 5% increments, while simultaneously recording the corresponding indoor and outdoor temperature difference values ​​at each power level. The steady-state response value is optimized using a PID self-tuning algorithm to improve the slope of the coupling curve, ensuring the matching accuracy between power output and temperature difference changes. Dynamic calibration is triggered when the cumulative temperature difference exceeds 5°C, such as in a scenario where a cold wave causes the temperature difference to rise from 20°C to 25°C within 2 hours. In this case, the control unit pauses the regular power control logic and performs rapid calibration at three characteristic power output percentages: 25%, 50%, and 75%. The entire calibration process takes ≤90 seconds, and the current power output of the device is maintained during calibration to avoid large fluctuations in indoor temperature. Calibration data is stored using a circular queue structure, retaining only the most recent 10 calibration results. A moving average algorithm is used to suppress random errors caused by single measurements, keeping the long-term drift of the coupling curve within ±2%.

[0071] In one feasible embodiment, to accommodate the differences in thermal characteristics of different buildings, users can independently set calibration-related parameters via a Bluetooth configuration tool. These parameters include: temperature sensor installation location compensation value (adjustable within ±2℃); power measurement deviation correction coefficient (range 0.95 to 1.05); and calibration trigger threshold (default 5℃, adjustable as needed within the range of 3℃ to 8℃). All calibration processes automatically generate complete log files, recording detailed information such as operation timestamps, real-time environmental parameters, and differences in coupling curves before and after calibration. The log files can be exported via USB for subsequent data analysis and troubleshooting. Before leaving the factory, the equipment can undergo full-range calibration in a high-low temperature test chamber ranging from -30℃ to 50℃ to establish an initial parameter baseline and ensure performance consistency across different batches. The calibration process strictly adheres to the standards of JJF1101-2003 "Environmental Testing Equipment Temperature and Humidity Calibration Specification" and GB / T5170.2-2008 "Environmental Testing Equipment for Electrical and Electronic Products - Test Methods - Temperature Test Equipment". The overall error after calibration is controlled within ±3℃.

[0072] In one feasible embodiment, the device's control unit completes parameter loading and component self-testing during the initialization phase. Non-volatile memory provides reference data storage support for the control unit, and the pre-stored power output table and rated power can be directly read by the control unit. The power execution module is driven by the control unit, receiving its self-test commands and subsequent power adjustment commands. After entering the operating state, indoor and outdoor temperature sensors synchronously acquire indoor and outdoor ambient temperatures at a frequency of 1Hz, and calculate the current temperature difference after moving average filtering. This value serves as the core trigger parameter for process initiation. After the temperature difference data passes the validity verification stage, the control unit uses a binary search algorithm to traverse the power output table and, based on the real-time temperature difference value... Match the corresponding power output percentage For extreme temperature differences exceeding the range defined in the table (such as indoor-outdoor temperature differences). (>40℃), automatically triggers the protection mechanism, reducing the power output percentage. Lock to 100% and log over-range events; when When <0℃, then Forced reset and disconnection of the main heating circuit. The decision-making process incorporates temperature difference rate monitoring (i.e., indoor temperature change rate auxiliary calculation mode). When the change exceeds 3℃ / min for two consecutive cycles, a predictive adjustment algorithm is activated to pre-adjust the power output percentage. To suppress temperature fluctuations. Received power output percentage. Upon receiving the command, the control unit combines the rated power calibrated in real time by the power metering module. implement The calculation outputs a power control signal, which is then converted from digital signal to analog signal and transmitted to the power execution module to drive it to perform power regulation. Different driving strategies are adopted for different types of heating equipment: electric heating equipment achieves stepless power regulation through thyristor phase-shift triggering, with the duty cycle of the output pulse width modulation signal corresponding to the power output percentage. Linear correspondence; the heat pump system translates the power command into compressor frequency parameters of 30-120Hz and electronic expansion valve opening parameters of 0-500 steps. During execution, the power metering module collects voltage and current data in real time, and the control unit calculates the deviation between the actual output power and the theoretical value. When the deviation exceeds ±5%, PID correction is initiated, and adjustments are made iteratively. Error correction. The process then enters the continuous monitoring phase, where the control unit completes three auxiliary tests within a 10-second adjustment cycle: first, a sensor communication status check to ensure the validity of indoor and outdoor ambient temperature data; second, an actuator response time test to verify the dynamic performance of power regulation; and third, an environmental interference assessment to identify the impact of sudden factors such as solar radiation and window opening on the indoor and outdoor temperature difference. The impact of temperature changes is considered. All monitoring data is integrated through state machine logic to form the basis for adjustment in the next cycle. The total response delay of this cycle can be controlled within 200ms, ensuring stable power output even when the temperature difference changes rapidly, and realizing full-link dynamic coupling from temperature sensing to power regulation.

[0073] In one feasible embodiment, a temperature change rate correction term can be introduced during the activation of the predictive regulation algorithm: when / When the heating rate is >2℃ / min (too fast), Increase the predicted amount by 5% to 10% based on the current calculated value; when / When the cooling rate is < -2℃ / min (too fast), Reduce the predicted value by 5% to 10%, and dynamically adjust the specific value of the predicted value according to the changing trend of three consecutive sampling cycles to suppress temperature fluctuation overshoot.

[0074] In one feasible embodiment, when the supply voltage is detected to exceed the rated value by ±10%, the control unit can automatically reduce the real-time output power to 90% of the rated power; when the equipment surface temperature exceeds 85°C, a stepped overheat protection mechanism is implemented, reducing the real-time output power by 2% for every 1°C exceeding the temperature; when the equipment operates continuously for more than 72 hours, a 10% power derating operation is automatically executed for one hour to reduce device losses. The trigger thresholds and recovery conditions for all limiting measures can be customized via the industrial bus interface.

[0075] In one feasible embodiment, the user can customize the calibration coefficient K to adjust the slope of the coupling curve. The adjustment range is 0.8 ≤ K ≤ 1.2. When K > 1, the power output under low-temperature conditions is enhanced. For example, when the indoor and outdoor temperature difference is 40°C, the actual power output percentage is 100% × K. When K < 1, the power output is reduced to achieve a deep energy-saving effect. This calibration coefficient is stored in non-volatile memory, and the data validity can be maintained for 10 years after power failure. It can be directly retrieved and used every time the device is powered on.

[0076] In one feasible embodiment, to verify the actual effectiveness of the temperature regulation method of this heating equipment, a 15-square-meter standard laboratory was selected in three typical climate zones: the first region (severe cold region), the second region (cold region), and the third region (hot summer and cold winter region) to construct an environmental simulation test system.

[0077] The experimental chamber uses 300mm thick PU insulation walls with a thermal conductivity λ=0.022W / (m·K). It is equipped with an independent temperature and humidity control system, capable of accurately simulating outdoor temperatures from -35℃ to 40℃ with a control accuracy of ±0.5℃. The indoor environment is maintained at the set baseline values ​​via a variable frequency air conditioner and a humidifier. A commercially available 2000W baseboard heater (traditional fixed power mode) was used for testing, and was simultaneously tested with the experimental prototype equipped with the aforementioned control unit. Both were connected to a power analyzer (accuracy class 0.5) and a distributed temperature acquisition system. This acquisition system sampled at 10-second intervals, with 6 monitoring points deployed within the experimental chamber.

[0078] Extreme cold condition testing (indoor-outdoor temperature difference ΔT = 40℃) was conducted in the first laboratory. The outdoor ambient temperature was set to -25℃, and the indoor target temperature was 22℃. After startup, the conventional equipment initially operated at full power (2000W). After 30 minutes, the indoor temperature rose to 19℃ and entered a plateau phase. Subsequently, due to the heat loss rate exceeding the power output capacity, the temperature slowly decreased to 18.5℃ and fluctuated (±1.2℃). The test prototype, however, triggered a percentage power output at ΔT = 40℃. =100%, Real-time Output Power Maintain 2000W for 25 minutes to bring the room temperature to the set value, then dynamically adjust the power output percentage. (Fluctuation range 92%~98%) Maintaining stable temperature, 72-hour continuous monitoring showed a maximum deviation of only ±0.4℃, which is 79% more accurate than the ±2.1℃ of traditional equipment. In the -35℃ extreme low temperature impact test, the prototype was still able to maintain an indoor temperature of no less than 20℃, while traditional equipment could not prevent the temperature from falling continuously, eventually dropping to 15.3℃.

[0079] The test was conducted in the second laboratory under normal temperature conditions (△T=20℃), with the outdoor temperature set at 2℃ and the indoor target at 22℃. Traditional equipment operated at 50% fixed power (1000W), but due to its inability to match the natural diurnal temperature fluctuations (the daytime indoor-outdoor temperature difference drops to 15℃, and the nighttime difference rises to 25℃), the indoor temperature overshooted to 24.3℃ during the day and dropped to 20.8℃ at night. The test prototype was monitored by power output percentage. Dynamic adjustment (percentage of power output during the day when ΔT=15℃) 37.5%, corresponding to real-time output power 750W, power output percentage at night when ΔT=25℃ 62.5%, corresponding to real-time output power With a power consumption of 1250W, the indoor temperature was ultimately controlled within the range of 21.8℃-22.3℃ (fluctuation ±0.25℃). Data from 72 hours of continuous operation showed that the prototype's total power consumption was 62.4kWh, compared to 75.6kWh for traditional equipment, resulting in an energy saving rate of 17.5%. The main energy-saving benefits were attributed to adaptive power increase during high ΔT periods at night and intelligent load reduction during low ΔT periods during the day.

[0080] The mild operating conditions (ΔT=5℃) were verified in the third laboratory, with an outdoor temperature of 18℃ and an indoor target temperature of 23℃. Traditional equipment, limited by its lowest power setting (500W), still exhibited a 300W redundant power consumption even at ΔT=5℃, resulting in a 72-hour power consumption of 36kWh. The test prototype was tested using power output percentage... =12.5% ​​to achieve real-time output power With a precise 250W output, the device maintains an indoor temperature fluctuation of ±0.3℃ while consuming only 29.8kWh of electricity, achieving an energy saving rate of 17.2%. In particular, during testing in rainy weather (outdoor humidity 90%), the prototype avoided the risk of condensation through a humidity compensation algorithm (△T correction coefficient +1.2℃), while traditional equipment, operating at a fixed power, experienced condensation at corner temperatures as low as 19℃.

[0081] Cross-climate zone comparative experiments further verified the universality of this application. In continental climate tests, the prototype achieved 18.7% energy savings compared to traditional equipment; in short-term use tests in subtropical climates, due to frequent temperature fluctuations in winter, the energy-saving effect increased to 20.3%. All experimental data were certified by a third-party testing agency, confirming that the constant temperature accuracy reached the design target of ±0.5℃ under extreme cold conditions of ΔT=40℃, the overall energy saving rate remained stable in the range of 15% to 20%, and the equipment operating noise decreased from 52dB of traditional equipment to 46dB, a reduction of 4-6dB, fully verifying the technological breakthroughs of this application in extreme climate adaptability and energy saving.

[0082] It should be noted that this application applies to household heating equipment, such as baseboard heaters, convection heaters, and oil-filled radiators; it can also be extended to commercial small-scale heating systems, including independent heating units in offices, constant temperature heating devices in shops, and zoned heating systems in hotel rooms. Its core algorithm framework has cross-domain adaptability and can provide underlying technical support for load prediction and optimization of HVAC systems, dynamic assessment of building energy consumption, and other fields. Specific application methods are as follows: In household baseboard electric heaters, this adjustment method collects indoor temperature through a temperature sensing module integrated into the device body and outdoor temperature through an external extended sensor. After calculating the temperature difference, it drives the power output of the internal heating element, so that the temperature fluctuation of a 10-30 square meter living space is controlled within ±0.5℃.

[0083] In commercial small-scale heating systems, including independent heating units in offices, constant temperature heating equipment in shops, zoned heating devices in hotel rooms, localized heating systems in catering establishments, and independent temperature control equipment in hospital wards, dynamic adjustment of heat load is achieved through communication between a centralized controller and terminal temperature control modules, enabling collaborative optimization of multi-zone temperature difference power coupling parameters. In the hotel room zoned heating scenario, this adjustment method is linked to the intelligent room control system. The room occupancy status is determined by the door sensor status. When long-term vacancy (>24 hours) is detected, the power response coefficient of the temperature difference is automatically reduced, maintaining the basic anti-freeze temperature (5℃) while reducing energy consumption by 30%–40%.

[0084] In the field of HVAC system optimization, this method provides power control algorithm support for air conditioning unit load prediction, fresh air system heat exchange efficiency assessment, air source heat pump heating units, and multi-split air conditioning systems. It optimizes the coordinated control logic of compressor operating frequency and fan speed through a temperature difference-power function model. Specifically, in air source heat pump heating units, this adjustment method is integrated with the defrosting logic of the heat pump system. When the temperature difference > 35℃ and frosting is detected, the output power percentage is automatically increased to 110% of the rated power (duration ≤ 5 minutes) for rapid defrosting. After defrosting, the system returns to the normal temperature difference-power coupling relationship.

[0085] In the field of mobile heating equipment, including vehicle-mounted independent heating devices, RV constant temperature systems, and outdoor mobile heaters, low-power battery-powered sensing modules collect temperature difference data and achieve dynamic adjustment of power range from 50W to 2000W in a 12V / 24V DC power supply system to adapt to drastic changes in outdoor temperature during vehicle operation.

[0086] In localized heating scenarios in industrial sites, including workshop workstation heating equipment, warehousing and logistics center temperature control systems, and greenhouse zone heating devices, differentiated power distribution to different workstations / areas is achieved through regional grid-based temperature difference monitoring, maintaining the temperature in the operating area at 20-25℃ while reducing energy consumption in non-operating areas.

[0087] In the field of heating for the protection of ancient buildings, indoor ambient temperature is collected by non-contact infrared temperature sensors, avoiding the damage to the building structure caused by the installation of traditional sensors. At the same time, a dynamic adjustment strategy with low power density (≤50W / ㎡) is adopted to prevent local high temperature from damaging cultural relics.

[0088] In the energy internet system, this regulation method supports smart heating terminals to access the smart energy management platform. By uploading real-time operating data of the temperature difference-power coupling curve, it provides terminal-side regulation resources for regional heating load forecasting, grid peak shaving and valley filling, and renewable energy consumption. When participating in demand response, it can complete a rapid adjustment of 5% to 20% of the power within 10 seconds.

[0089] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for adaptive temperature regulation of a heating device, characterized in that, include: Temperature data was collected from multiple different areas inside the room to obtain the indoor ambient temperature. The outdoor ambient temperature is obtained by collecting the temperature at a preset outdoor location. The indoor-outdoor temperature difference value is determined based on the indoor ambient temperature and the outdoor ambient temperature. The corresponding power output percentage is determined based on the indoor and outdoor temperature difference and the preset power output table; The real-time output power of the heating equipment is determined based on its rated power and the power output percentage. A temperature regulation strategy is generated and executed based on the real-time output power and the type of heating equipment.

2. The adaptive temperature regulation method for heating equipment according to claim 1, characterized in that, The step of determining the corresponding power output percentage based on the indoor-outdoor temperature difference and a preset power output table includes: When the indoor-outdoor temperature difference is greater than or equal to the first temperature threshold defined by the power output table, the power output percentage is determined to be 100%. When the indoor-outdoor temperature difference is less than or equal to the second temperature threshold defined by the power output table, the power output percentage is determined to be 0. When the indoor and outdoor temperature difference does not exceed the temperature difference range defined by the power output table, but the power output table does not record the power output percentage corresponding to the indoor and outdoor temperature difference, the power output percentage of the indoor and outdoor temperature difference is determined according to the temperature difference power coupling function of the power output table.

3. The adaptive temperature regulation method for heating equipment according to claim 2, characterized in that, The method further includes: When the cumulative change in the indoor and outdoor temperature difference exceeds the third temperature threshold or at each preset time interval, multiple power characteristic points are selected from the preset power output range. Obtain the indoor and outdoor temperature difference values ​​corresponding to each of the power feature points, and obtain multiple temperature difference power data combinations based on the power feature points and their corresponding power feature points; The first and second parameters of the temperature difference power coupling function curve are calculated based on the combination of the multiple temperature difference power data. The temperature difference power coupling function curve is corrected based on the first parameter and the second parameter to obtain the corrected temperature difference power coupling function curve.

4. The adaptive temperature regulation method for heating equipment according to claim 1, characterized in that, After collecting indoor and outdoor ambient temperatures, the method further includes: Perform a moving average filtering process on the indoor ambient temperature and the outdoor ambient temperature to obtain the filtered indoor ambient temperature and outdoor ambient temperature. Temperature compensation processing is performed on the filtered indoor and outdoor ambient temperatures to obtain corrected indoor and outdoor ambient temperatures.

5. The adaptive temperature regulation method for heating equipment according to claim 4, characterized in that, The indoor ambient temperature is acquired by a first temperature sensor, and the outdoor ambient temperature is acquired by a second temperature sensor. The step of performing temperature compensation processing on the filtered indoor and outdoor ambient temperatures to obtain corrected indoor and outdoor ambient temperatures includes: The corresponding compensation coefficient for the first temperature sensor is determined based on its installation location. The filtered indoor ambient temperature is compensated according to the first sensor compensation coefficient to obtain the corrected indoor ambient temperature. The corresponding compensation coefficient for the second temperature sensor is determined based on its installation location. The filtered outdoor ambient temperature is compensated based on the compensation coefficient of the second sensor to obtain the corrected outdoor ambient temperature.

6. The adaptive temperature regulation method for heating equipment according to claim 1, characterized in that, In the process of implementing the temperature regulation strategy, the method further includes: Collect the actual operating current and actual operating voltage of the heating equipment; The actual output power is obtained based on the actual operating current and the actual operating voltage. Based on the comparison between the actual output power and the real-time output power, the power output percentage is corrected, and the real-time output power of the heating equipment is adjusted according to the corrected power output percentage.

7. The adaptive temperature regulation method for heating equipment according to claim 1, characterized in that, The step of generating and executing a temperature regulation strategy based on the real-time output power and the type of heating equipment includes: When the heating equipment is an electric heating equipment, a corresponding pulse width modulation signal is generated based on the real-time output power, and the conduction angle of the bidirectional thyristor is controlled by the pulse width modulation signal to adjust the output power of the electric heating equipment. When the heating equipment is a heat pump, the operating frequency of the compressor and the opening of the electronic expansion valve of the heat pump are adjusted based on the real-time output power to regulate the output power of the heat pump.

8. The adaptive temperature regulation method for heating equipment according to claim 1, characterized in that, The method further includes: when the outdoor ambient temperature is invalid, determining the power output percentage based on the rate of change of the indoor ambient temperature.

9. The adaptive temperature regulation method for heating equipment according to claim 5, characterized in that, The installation location of the first temperature sensor satisfies at least one of the following conditions: 1.2 to 1.8 meters above the indoor floor; The distance from the outer wall shall not be less than 0.5 meters; Avoid areas with direct sunlight and ventilation openings.

10. The adaptive temperature regulation method for heating equipment according to claim 5, characterized in that, The second temperature sensor is a temperature and humidity detection module, which is equipped with a heating film and is installed outdoors in a place without direct sunlight.

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