An air conditioner energy-saving control system and method based on multi-sensor fusion

Abstract

The present application relates to the technical field of intelligent control, in particular to an air conditioner energy-saving control system and method based on multi-sensor fusion, which determines the real-time strong condensation necessity degree of the condenser according to the outdoor temperature and condenser condensation temperature to analyze the heat dissipation resistance performance of the air conditioner outdoor unit, and according to the wind speed of the condenser windward surface to analyze the condenser blockage working condition performance, and according to the continuous operation time length to analyze the heat influence performance of the non-condensing components under long-term operation of the air conditioner; determines the real-time strong rotation speed tendency degree of the condenser according to the compressor rotation speed to analyze the compressor working condition performance, and according to the indoor temperature to analyze the user historical air conditioner use habit, and according to the expansion valve superheat to analyze the parameter operation performance of the expansion valve; determines the real-time condensing rotation speed demand degree of the condenser by coordinating the strong condensation necessity degree and the strong rotation speed tendency degree, adaptively adjusts the prediction time domain window step length, and finally obtains the condenser rotation speed regulation and control result with higher adaptation degree, so as to improve the air conditioner energy-saving control efficiency.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology, specifically to an air conditioning energy-saving control system and method based on multi-sensor fusion. Background Technology

[0002] When an air conditioner is operating, the large fan installed inside the outdoor unit, close to the condenser, is the condenser fan. The high-speed rotation of the condenser fan drives outdoor air to laterally wash against the condenser fins, significantly improving air-side heat exchange efficiency and allowing the high-temperature refrigerant to release its latent heat, thus enhancing the air conditioner's heat exchange performance. The condenser's rotational speed is essentially the same as the condenser fan's rotational speed. The condenser's rotational speed and the air conditioner's energy-saving performance are inversely related. When the condenser's rotational speed is high, energy efficiency is poor, resulting in redundant energy consumption; conversely, when the condenser's rotational speed is too low, it is difficult to meet the air conditioner's heat exchange requirements.

[0003] Existing technologies often use MPC (Model Predictive Control) predictive models to regulate the condenser speed during the air conditioning cooling process. The inputs are multi-dimensional information such as real-time condensing temperature, superheat, and compressor frequency. After analytical calculation, the output is the target speed command of the condenser. The prediction time domain window step size is the internal control parameter of the MPC predictive model, which is essentially the sampling period of the controller, that is, the time interval between system state update and control quantity calculation.

[0004] In the process of calculating and controlling condenser speed commands using the MPC predictive model, the prediction time-domain window step size of the MPC predictive model during air conditioning control is traditionally preset to a fixed empirical value. However, in actual scenarios, the operating conditions of the air conditioner vary at different times, and the prediction time-domain window step size parameter needs to match the urgency of the speed demand corresponding to the current operating condition. For example, if the real-time outdoor unit ambient temperature is higher and the condenser gap is more severely clogged, the real-time heat exchange efficiency is lower, and the necessity for increasing the condenser speed is higher. In this case, a smaller prediction time-domain window step size needs to be applied. At the same time, the condenser speed control needs to be matched with the operation of multiple components such as the compressor and expansion valve, as well as the user's historical usage habits. For example, when the compressor has a stronger short-term speed increase trend, the expansion valve has a higher superheat, and the real-time urgency of heat exchange is higher than the user's historical usage habits, there is a more urgent demand for condenser speed, and a smaller prediction time-domain window step size needs to be applied. Therefore, the air conditioning operation adaptability obtained by traditionally using a preset fixed speed is low, further reducing the energy-saving control efficiency of the air conditioner. Summary of the Invention

[0005] To address the above technical problems, this invention provides an air conditioning energy-saving control system and method based on multi-sensor fusion.

[0006] This invention provides an air conditioning energy-saving control method based on multi-sensor fusion, comprising: Real-time data collection includes outdoor temperature, indoor temperature, as well as the condenser condensing temperature, condenser wind speed, continuous operating time, compressor speed, and expansion valve superheat of the air conditioner. The heat dissipation resistance of the outdoor unit of the air conditioner is analyzed based on the outdoor temperature and the condenser condensing temperature. The condenser blockage condition is analyzed based on the wind speed on the condenser's windward side. The thermal impact of non-condensing components under long-term operation of the air conditioner is analyzed based on the continuous operating time to determine the necessity of real-time strong condensation of the condenser. The compressor's operating performance is analyzed based on the compressor speed, the user's historical air conditioning usage habits are analyzed based on the indoor temperature, and the expansion valve's parameter operation performance is analyzed based on the expansion valve's superheat, thus determining the condenser's real-time high speed tendency. By combining the necessary degree of strong condensation and the tendency of strong rotation speed, the real-time condensation speed requirement of the condenser is determined; Based on the required condensing speed, the prediction time-domain window step size is adaptively adjusted to control the real-time speed of the condenser.

[0007] In some embodiments of the present invention, the analysis of the heat dissipation resistance performance of the outdoor unit of the air conditioner based on the outdoor temperature and the condenser condensation temperature includes: The difference between the outdoor temperature and the condenser condensing temperature is calculated to quantify the heat dissipation resistance of the outdoor unit of the air conditioner and obtain the real-time heat dissipation resistance factor of the condenser.

[0008] In some embodiments of the present invention, the analysis of condenser blockage performance based on the wind speed on the windward side of the condenser includes: Real-time acquisition of condenser speed; Based on the historical condenser speed and corresponding historical condenser wind speed in the historical air conditioning refrigeration process, calculate the average value of the historical condenser wind speed at the same historical condenser speed as the current condenser speed. The difference between the historical average wind speed on the condenser's windward side and the current wind speed on the condenser's windward side is calculated to quantify the condenser's blockage performance and obtain the real-time blockage factor of the condenser.

[0009] In some embodiments of the present invention, the thermal impact performance of non-condensing components under long-term operation of the air conditioner is analyzed based on the continuous operating duration, including: Extract the historical maximum duration of continuous operation in the air conditioning refrigeration process; Calculate the ratio of the current continuous operation duration to the maximum historical continuous operation duration to quantify the thermal impact performance of non-condensing components under long-term air conditioning operation and obtain the real-time thermal impact factor of the condenser.

[0010] In some embodiments of the present invention, analyzing the compressor operating performance based on the compressor speed includes: Extract the historical maximum speed of the compressor in the historical air conditioning refrigeration process; Calculate the ratio of the current compressor speed to the compressor's historical maximum speed to obtain the real-time compressor speed factor of the air conditioner; A two-dimensional coordinate system is constructed with time as the horizontal axis and the compressor speed at each sampling time in the short historical period as the vertical axis, starting from the current moment. The least squares linear fitting method is used to fit a straight line to each sample point in the two-dimensional coordinate system to obtain the slope of the current short-term fitted straight line corresponding to the current compressor speed. Extract the maximum slope of the short-term fitted straight line in the historical air conditioning refrigeration process; Calculate the ratio of the current short-term fitted line slope to the maximum slope of the short-term fitted line to obtain the real-time short-term compressor operating condition factor of the air conditioner. By weighted fusion of the compressor speed factor and the short-term compressor operating condition factor, the compressor operating condition performance is quantified to obtain the real-time compressor frequency increase performance of the air conditioner.

[0011] In some embodiments of the present invention, analyzing users' historical air conditioning usage habits based on the indoor temperature includes: Real-time collection of perceived temperature for each person in the room, and calculation of the average perceived temperature for all people; Based on the historical indoor temperature and the corresponding historical average temperature during the historical air conditioning cooling process, calculate the average of the historical indoor temperature corresponding to the same historical average temperature as the current average temperature. Calculate the difference between the current indoor temperature and the historical average indoor temperature to quantify the user's historical air conditioning usage habits and obtain the real-time user habit influencing factors for air conditioning.

[0012] In some embodiments of the present invention, the parameter operation performance of the expansion valve is analyzed based on the superheat of the expansion valve, including: Obtain the historical average superheat value of the expansion valve in the historical air conditioning refrigeration process; Calculate the ratio between the current expansion valve superheat and the historical average expansion valve superheat to quantify the parameter operation performance of the expansion valve and obtain the real-time expansion valve operating condition influence factor of the air conditioner.

[0013] In some embodiments of the present invention, adaptively adjusting the prediction time-domain window step size according to the condensation speed demand includes: Obtain the historical average condensing speed requirement in the historical air conditioning refrigeration process; The difference between the historical average condensing speed demand and the condensing speed demand is calculated, and a hyperbolic tangent function is introduced to adaptively adjust the prediction time-domain window step size to obtain an optimized prediction time-domain window step size.

[0014] This invention provides an air conditioning energy-saving control system based on multi-sensor fusion, comprising: a memory and a processor, wherein: The memory is used to store program code; The processor is configured to read program code stored in the memory and execute the method described in the first aspect of the present invention.

[0015] In some embodiments of the present invention, the processor includes: The data acquisition module is used to collect outdoor temperature, indoor temperature, as well as the condenser condensing temperature, condenser wind speed, continuous operation time, compressor speed, and expansion valve superheat of the air conditioner in real time. The strong condensation necessity analysis module is used to analyze the heat dissipation resistance of the outdoor unit of the air conditioner based on the outdoor temperature and the condenser condensation temperature, analyze the condenser blockage condition based on the wind speed on the condenser's windward side, and analyze the thermal impact of non-condensing components under long-term operation of the air conditioner based on the continuous operation duration, so as to determine the real-time strong condensation necessity of the condenser. The strong speed tendency analysis module is used to analyze the compressor operating performance based on the compressor speed, analyze the user's historical air conditioning usage habits based on the indoor temperature, and analyze the parameter operation performance of the expansion valve based on the expansion valve superheat to determine the real-time strong speed tendency of the condenser. The condensing speed demand acquisition module is used to coordinate the degree of necessity for strong condensation and the tendency of strong speed to determine the real-time condensing speed demand of the condenser. The speed control module is used to adaptively adjust the prediction time-domain window step size according to the condenser speed requirement, thereby controlling the real-time speed of the condenser.

[0016] The present invention provides an air conditioning energy-saving control system and method based on multi-sensor fusion, which has the following beneficial effects: The present invention analyzes the heat dissipation resistance of the outdoor unit of the air conditioner based on outdoor temperature and condenser condensing temperature, analyzes the condenser blockage condition based on the wind speed on the condenser's windward side, and analyzes the thermal impact of non-condensing components under long-term operation based on continuous operation time to determine the real-time strong condensation necessity of the condenser; The present invention analyzes the compressor's operating condition based on compressor speed, analyzes the user's historical air conditioning usage habits based on indoor temperature, and analyzes the expansion valve's parameter operation based on the expansion valve's superheat to determine the real-time strong speed trend of the condenser; Then, by coordinating the strong condensation necessity and the strong speed trend, the real-time condensing speed demand of the condenser is determined; Finally, based on the condensing speed demand, the prediction time domain window step size is adaptively adjusted to control the real-time speed of the condenser. This invention can combine and analyze the complex operating conditions (ambient temperature, condenser blockage, thermal impact of non-condensing components) and multi-component coordination (compressor operating conditions, expansion valve parameter operation) in air conditioning refrigeration scenarios, as well as the user's air conditioning usage habits, to obtain a more adaptable air conditioning condenser speed control result, thereby improving the energy-saving control efficiency of air conditioning based on multi-sensor fusion. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating an air conditioning energy-saving control method based on multi-sensor fusion provided by the present invention. Detailed Implementation

[0018] The scenario addressed in this invention is as follows: an air conditioner mainly consists of an indoor unit and an outdoor unit. The indoor unit primarily includes an evaporator and an expansion valve, while the outdoor unit includes a compressor and a condenser. The condenser's function is to improve the air conditioner's heat exchange performance. During the air conditioning cooling process, the condenser speed command is often calculated and analyzed using an MPC prediction model. The prediction time domain window step size is an internal control parameter of the MPC prediction model, traditionally preset to a fixed value. However, the condenser speed command obtained through a fixed prediction time domain window step size has low adaptability.

[0019] Therefore, the purpose of this invention is to combine and analyze the complex operating conditions and multi-component collaborative operation requirements in air conditioning refrigeration scenarios to obtain a prediction time-domain window step size with higher adaptability under the MPC prediction model, thereby obtaining a more efficient condenser speed control result.

[0020] The following description, in conjunction with the accompanying drawings, details a specific solution for an air conditioning energy-saving control system and method based on multi-sensor fusion provided by the present invention. For example... Figure 1 As shown, an embodiment of the present invention provides an air conditioning energy-saving control method based on multi-sensor fusion, which specifically includes: S100: Real-time collection of outdoor temperature, indoor temperature, as well as the condenser condensing temperature, condenser wind speed, continuous operation time, compressor speed, and expansion valve superheat of the air conditioner.

[0021] In embodiments of the present invention, outdoor temperature, indoor temperature, as well as the condenser condensing temperature, condenser wind speed, continuous operating time, compressor speed, and expansion valve superheat of the air conditioner are collected in real time. The specific implementation method is as follows: The system reads real-time outdoor temperature at the location of the outdoor unit, indoor temperature in the room where the indoor unit is located, and real-time condenser temperature at the condenser via a temperature sensing module. It also reads the perceived temperature (body surface temperature) of individuals in the room via a thermal infrared sensing module. A vane-type fan speed sensor reads the wind speed at the condenser's airflow direction. A time-series recording module records the continuous operating time of the air conditioner during the current cooling cycle. An operating parameter storage module reads the compressor speed, expansion valve superheat, and condenser speed. Furthermore, the outdoor temperature, indoor temperature, condenser temperature, condenser airflow direction, continuous operating time, compressor speed, and expansion valve superheat are all collected at the same frequency.

[0022] The data obtained above is cleaned and preprocessed to obtain processed data for subsequent analysis.

[0023] S200: Analyze the heat dissipation resistance of the outdoor unit of the air conditioner based on the outdoor temperature and the condenser condensing temperature, analyze the condenser blockage condition based on the wind speed on the condenser's front side, and analyze the thermal impact of non-condensing components under long-term operation of the air conditioner based on the continuous operation time to determine the necessity of strong condensation of the condenser in real time.

[0024] The condenser is responsible for forcing outdoor air to flow through it and carrying away heat. Therefore, the outdoor ambient temperature directly determines the difficulty of heat dissipation. The higher the outdoor temperature, the closer the outdoor air temperature is to the condenser tube wall temperature, and the less the air can absorb and remove heat. In this case, a stronger airflow is needed to enhance heat exchange. At the same time, when the condenser gaps become clogged, the condenser should be accelerated to compensate. Also, because the air conditioner operates in cooling mode for a long time, non-condensing components such as the outer casing and liquid-filled chassis will be continuously heated, resulting in the microenvironment close to the fin inlet having a more significant high temperature tendency compared to the outdoor temperature. In this case, the condenser also needs to be accelerated appropriately.

[0025] Based on the above analysis, in the embodiments of the present invention, the heat dissipation resistance of the outdoor unit of the air conditioner is analyzed according to the outdoor temperature and the condenser condensing temperature, the condenser blockage condition is analyzed according to the wind speed on the condenser front side, and the thermal impact of non-condensing components under long-term operation of the air conditioner is analyzed according to the continuous operation time, so as to determine the necessity of strong condensation of the condenser in real time.

[0026] In air conditioning cooling mode, the condenser acts as the outdoor heat exchanger, dispersing the heat from the high-temperature refrigerant in the air conditioning system into the outdoor air. The condenser forces outdoor air to flow through it, carrying away heat. Therefore, the outdoor ambient temperature directly determines the difficulty of heat dissipation. The higher the outdoor temperature, the closer the outdoor air temperature is to the condenser tube wall temperature, and the less the air can absorb and remove heat. This results in poorer heat dissipation from the condenser, requiring a stronger airflow to enhance heat exchange and bring the condensation effect back to normal. Conversely, when the outdoor temperature is low, the air temperature is low, naturally resulting in strong heat exchange, and a small airflow is sufficient to meet the heat dissipation needs. Therefore, to perform a more accurate analysis of the condenser's rotational speed requirements, real-time outdoor temperature can be used as an auxiliary analysis.

[0027] Therefore, the heat dissipation resistance performance of the outdoor unit of the air conditioner is analyzed based on the outdoor temperature and the condenser condensing temperature. Further analysis includes: The difference between the outdoor temperature and the condenser condensing temperature is calculated to quantify the heat dissipation resistance performance of the outdoor unit of the air conditioner, obtaining the real-time heat dissipation resistance factor of the condenser. Specifically, at the current moment... The heat dissipation resistance factor of the condenser is: In the formula, Indicates the current time The heat dissipation resistance factor of the condenser; Indicates the current time The outdoor temperature; Indicates the current time The condenser condensing temperature; This represents a linear normalization function, such as a max-min normalization function, used to normalize the thermal resistance value to a certain value. Within the range, the maximum and minimum values ​​in the maximum-minimum normalization function are taken from the values ​​calculated by the current air conditioner at all times during all refrigeration processes up to the present. The extreme values. It should be noted that for the maximum and minimum normalization functions in this embodiment, if the maximum and minimum values ​​are the same in extreme cases, it means that the corresponding data of the current air conditioner is completely stable so far. In this case, the normalization operation cannot be performed on the normalization object. The technical solution provided in this embodiment is not applicable to this situation. Therefore, the technical solution provided in this embodiment will not be executed, and a data error indication signal will be directly output.

[0028] In actual condenser operation scenarios, dust, lint, and debris can clog the gaps between condenser fins and the air inlet and outlet. Even if the outdoor condenser is rotating normally, the airflow through the condenser will be significantly reduced. Previously, a large amount of low-temperature outdoor air could continuously carry away heat, but with insufficient airflow, less air can participate in heat exchange, and the amount of heat that can be carried away per unit time will decrease significantly, resulting in a decrease in the condenser's heat exchange capacity. In order to maintain condensing pressure, the condenser should increase its speed to compensate. Therefore, in order to obtain a more suitable speed requirement assessment result, it is necessary to combine the analysis of the real-time blockage condition of the condenser.

[0029] Therefore, the condenser's performance under blockage conditions is analyzed based on the wind speed on the condenser's windward side. Further details include: First, the condenser speed is collected in real time. Specifically, the condenser speed is read in real time through the operating parameter storage module.

[0030] Then, based on the historical condenser speed and the corresponding historical condenser wind speed in the historical air conditioning refrigeration process, the average historical condenser wind speed at the same historical condenser speed as the current condenser speed is calculated.

[0031] Finally, the difference between the historical average wind speed on the condenser's windward side and the current wind speed on the condenser's windward side is calculated to quantify the condenser's blockage performance and obtain the real-time blockage factor. Specifically, at the current moment... The blockage factor of the condenser is: In the formula, Indicates the current time The condenser's blockage factor; This represents the average wind speed on the windward side of the condenser at the same historical condenser speed as the current condenser speed. Indicates the current time Wind speed on the condenser's windward side; This represents a linear normalization function, such as a max-min normalization function, used to normalize congestion condition values ​​to a normal value. Within the range, the maximum and minimum values ​​in the maximum-minimum normalization function are taken from the values ​​calculated by the current air conditioner at all times during all refrigeration processes up to the present. The extreme value.

[0032] If the current wind speed on the condenser's front side is lower than the historical average wind speed at the same condenser speed, that is, the difference between the two is... The larger the value, the greater the likelihood of condenser clogging, and the higher the corresponding clogging factor.

[0033] If the condenser's real-time heat dissipation resistance factor The larger the value, the greater the blocking factor. The larger the value, the more urgent the need for real-time speed increase of the condenser; therefore, it can be combined with the heat dissipation resistance factor. and blocking factors Analyze the real-time acceleration urgency coefficient of the condenser, and thus, determine the current moment. The urgency coefficient for accelerating the condenser is defined as: In the formula, Indicates the current time The urgency coefficient for accelerating the condenser; Indicates the current time The heat dissipation resistance factor of the condenser; Indicates the current time The condenser's blockage factor.

[0034] Similarly, calculate and record the real-time acceleration urgency coefficient of the condenser.

[0035] The above assessment of condenser speed requirements is based solely on the ambient temperature and blockage of the condenser. However, in real-world scenarios, the condenser coil itself relies on air cooling for heat dissipation. But non-condensing components such as the compressor exhaust pipe, casing, and liquid accumulation chassis are continuously heated under long-term operating conditions. The casing heats up the surrounding air, thereby raising the actual temperature of the intake air. This results in a more significant trend towards higher temperatures in the microenvironment close to the fin inlet compared to the monitored outdoor temperature, leading to an increase in the condensation saturation temperature. In this case, the condenser should be appropriately accelerated. Therefore, to accurately assess the required condenser speed, a combined analysis of the thermal effects of non-condensing components under long-term operation can be performed.

[0036] Therefore, the thermal impact of non-condensing components on air conditioners under long-term operation is analyzed based on the duration of continuous operation. Further analysis includes: First, the maximum duration of continuous historical operation in the air conditioning refrigeration process is extracted. Specifically, this is done through the time sequence recording module.

[0037] Then, the ratio of the current continuous operating time to the historical maximum continuous operating time is calculated to quantify the thermal impact performance of non-condensing components under long-term air conditioning operation, thus obtaining the real-time thermal impact factor of the condenser. Specifically, at the current moment... The heat influence factor of the condenser is: In the formula, Indicates the current time The thermal influence factor of the condenser; Indicates the current continuous operation duration; This indicates the longest continuous operation time in the air conditioning refrigeration process. This represents the difference correction parameter, which has the same dimensions as the denominator and takes the smallest value greater than 0. This is to prevent the denominator from being 0; for example, it can be set... This can prevent the difference from being 0 without significantly interfering with the calculation of normal values.

[0038] The ratio of current continuous operation duration to the historical maximum continuous operation duration The larger the value, the longer the non-condensing components are continuously heated, resulting in a more significant tendency for the microenvironment immediately adjacent to the fin inlet to reach a higher temperature compared to the monitored outdoor temperature, thus increasing the condenser's thermal impact factor. The larger.

[0039] After obtaining the urgent coefficient for accelerating the condenser and thermal influence factors After that, in terms of the urgency of accelerating... Thermal impact factor of non-condensing components connected on the basis This determines the necessary level of strong condensation from the condenser in real time. Specifically, at the current moment... The degree of condensation required by the condenser is: In the formula, Indicates the current time The degree of necessity for strong condensation in the condenser; Indicates the current time The thermal influence factor of the condenser; Indicates the current time The urgency coefficient for accelerating the condenser.

[0040] S300: Analyzes compressor operating performance based on compressor speed, analyzes user's historical air conditioning usage habits based on indoor temperature, and analyzes expansion valve parameter operation performance based on expansion valve superheat to determine the real-time strong speed trend of the condenser.

[0041] The condenser speed needs to be matched with the operating conditions of the air conditioner's compressor and expansion valve, as well as the user's historical usage habits. For example, when the compressor has a stronger short-term acceleration trend, the expansion valve has a higher superheat, and the current heat exchange urgency is higher than the user's historical usage habits, there is a more urgent need to increase the condenser speed. Therefore, the real-time strong speed trend of the condenser is obtained by analyzing the performance of multiple component operating conditions.

[0042] Based on the above analysis, in the embodiments of the present invention, the compressor operating performance is analyzed based on the compressor speed, the user's historical air conditioning usage habits are analyzed based on the indoor temperature, and the parameter operation performance of the expansion valve is analyzed based on the expansion valve superheat, so as to determine the real-time strong speed tendency of the condenser.

[0043] The compressor operating conditions vary at different times of air conditioning operation. For example, when the real-time speed frequency of the compressor at the front end of the condenser is high and the frequency increase is significant in the short term, the exhaust mass flow rate and total heat dissipation increase. The condenser needs to remove more heat instantaneously, and the condensing pressure tends to rise. This reflects a greater demand for strong load on the indoor side, making it more necessary to increase the condenser speed. Moreover, as soon as the compressor speed increases, the system high pressure rises simultaneously. If the condenser speed remains unchanged, the heat dissipation capacity cannot keep up with the increased heat generation of the compressor, which will lead to compressor overload and a sharp drop in cooling efficiency. Therefore, in order to obtain more accurate results on the condenser speed demand, it is necessary to perform a matching analysis on the short-term compressor operating conditions.

[0044] Therefore, compressor performance is analyzed based on compressor speed. Further analysis includes: First, extract the historical maximum compressor speed from the historical air conditioning refrigeration process. Specifically, extract the historical maximum compressor speed from the air conditioning refrigeration process using the time sequence recording module.

[0045] Then, the ratio of the current compressor speed to the compressor's historical maximum speed is calculated to obtain the real-time compressor speed factor of the air conditioner. Specifically, at the current moment... The compressor speed factor of the air conditioner is: In the formula, Indicates the current time Air conditioner compressor speed factor; Indicates the current time Air conditioner compressor speed (current compressor speed); This indicates the historical maximum speed of the compressor during the air conditioning refrigeration process.

[0046] Next, a two-dimensional coordinate system is constructed with time as the x-axis and the compressor speed at each sampling time within the historical short period as the y-axis, starting from the current moment. The least squares linear fitting method is then used to fit a straight line to each sample point in the two-dimensional coordinate system, obtaining the slope of the current short-term fitted straight line corresponding to the current compressor speed, denoted as . (Current moment) The slope of the current short-term fitted line corresponding to the compressor speed. It should be noted that if the slope of the short-term fitted line is less than zero, the slope of the short-term fitted line will be set to zero.

[0047] Furthermore, the maximum slope of the short-term fitted straight line corresponding to all sampling moments in the historical air conditioning refrigeration process is extracted and denoted as... .

[0048] Furthermore, the ratio of the current short-term fitted line slope to the maximum slope of the short-term fitted line is calculated to obtain the real-time short-term compressor operating condition factor of the air conditioner. Specifically, at the current moment... The short-term compressor operating condition factor of the air conditioner is: In the formula, Indicates the current time Short-term compressor operating condition factor of air conditioner; Indicates the current time The slope of the current short-term fitted line corresponding to the compressor speed (current compressor speed); This represents the maximum slope of the short-term fitted straight line corresponding to all sampling moments in the historical air conditioning refrigeration process. This represents the difference correction parameter, which has the same dimensions as the denominator and takes the smallest value greater than 0. This is to prevent the denominator from being 0; for example, it can be set... This can prevent the difference from being 0 without significantly interfering with the calculation of normal values.

[0049] Finally, by weighted fusion of compressor speed factor and short-term compressor operating condition factor, the compressor operating condition performance is quantified to obtain the real-time compressor frequency increase performance of the air conditioner. Specifically, at the current moment... The frequency increase of the air conditioner compressor is as follows: In the formula, Indicates the current time The frequency increase of the air conditioner compressor; Indicates the current time Air conditioner compressor speed factor; Indicates the current time Short-term compressor operating condition factor of air conditioner; Indicates the compressor speed weight. Indicates the compressor operating condition weight. , which can be set to , The specific value can be adjusted according to the actual scenario, such as when the compressor speed is relatively low ( The change rate of compressor speed is relatively small in the short term, but it is relatively large in the short term. (If it is relatively large), then increase Set value, decrease Setting value.

[0050] Intelligent air conditioners can analyze human body temperature and users' historical air conditioning usage habits during cooling operations. If the current indoor temperature is higher than the average indoor temperature based on the user's current perceived temperature, the need for cooling is higher, the urgency for heat exchange is higher, and the demand for condenser speed is higher.

[0051] Therefore, based on indoor temperature analysis, users' historical air conditioning usage habits are observed. Further details include: First, the perceived temperature of each person in the room is collected in real time, and the average perceived temperature of all people is calculated. Specifically, the perceived temperature of each person in the room is acquired in real time using thermal infrared technology, and the average perceived temperature of all people is calculated.

[0052] Then, based on the historical indoor temperature and the corresponding historical average temperature during the historical air conditioning cooling process, the average historical indoor temperature corresponding to the same historical average temperature as the current average temperature is calculated. This historical average indoor temperature better reflects the historical air conditioning usage habits of people at that temperature.

[0053] Finally, the difference between the current indoor temperature and the historical average indoor temperature is calculated to quantify the user's historical air conditioning usage habits and obtain the real-time user habit influencing factors. Specifically, at the current moment... The factors influencing air conditioner user habits are: In the formula, Indicates the current time Factors influencing air conditioner user habits; Indicates the current time The indoor temperature; This represents the average of historical indoor temperatures corresponding to the same historical average perceived temperature as the current average perceived temperature. This represents a linear normalization function, such as a max-min normalization function, used to normalize temperature differences to a certain value. Within the range, the maximum and minimum values ​​in the maximum-minimum normalization function are taken from the values ​​calculated by the current air conditioner at all times during all refrigeration processes up to the present. The extreme value.

[0054] If the air conditioner's compressor frequency increases in real time... The larger the value, the greater the influence of user habits. The larger the value, the more urgent the heat exchange demand at that moment; therefore, it can be combined with the compressor frequency increase. And factors influencing user habits Analyze the real-time heat exchange urgency of the air conditioner, and thus, determine the current moment. The heat exchange urgency of an air conditioner is defined as: In the formula, Indicates the current time The urgency of heat exchange in air conditioning; Indicates the current time Factors influencing condenser user habits; Indicates the current time The frequency of the air conditioner compressor is increased.

[0055] There is a strong correlation between the condenser speed control and the expansion valve performance. Superheat is a key parameter for expansion valve operation. Superheat is the temperature at which the refrigerant liquid continues to absorb heat after being completely evaporated into saturated vapor in the evaporator. When the superheat is too high, the amount of liquid entering the evaporator decreases, the evaporation pressure drops, and the cooling capacity decreases. However, the compressor is still operating at this time, and the exhaust heat does not decrease proportionally. Therefore, the condenser speed needs to be increased. Thus, the operating parameters of the expansion valve need to be matched and analyzed.

[0056] Therefore, the operating performance of the expansion valve is analyzed based on its superheat. Further details include: First, obtain the average superheat value of the historical expansion valve in the historical air conditioning refrigeration process. Specifically, extract the historical expansion valve superheat value in the historical air conditioning refrigeration process through the operating parameter storage module, and calculate the average superheat value of the historical expansion valve in the historical air conditioning refrigeration process.

[0057] Then, the ratio between the current expansion valve superheat and the historical average expansion valve superheat is calculated to quantify the expansion valve's parameter operation performance and obtain the real-time expansion valve operating condition influencing factors of the air conditioner. Specifically, at the current moment... The operating condition influencing factors of the air conditioner's expansion valve are: In the formula, Indicates the current time Factors affecting the real-time operating condition of the expansion valve in air conditioning systems; Indicates the current time The expansion valve superheat of the air conditioner (current expansion valve superheat). This represents the historical average superheat of the air conditioner's expansion valve at all sampling times during the historical air conditioning refrigeration process. This represents the difference correction parameter, which has the same dimensions as the denominator and takes the smallest value greater than 0. This is to prevent the denominator from being 0; for example, it can be set... This can prevent the difference from being 0 without significantly interfering with the calculation of normal values.

[0058] If the air conditioner's real-time heat exchange urgency The larger the value, the greater the influence factor on the operating conditions of the expansion valve. The larger the value, the more urgent the current demand for high condenser speed; therefore, it can be considered in conjunction with the urgency of heat exchange. Factors affecting the operating conditions of expansion valves Analyze the real-time strong speed trend of the condenser, and thus, determine the current moment. The high speed tendency of the condenser is defined as: In the formula, Indicates the current time The tendency of the condenser to operate at high speed; Indicates the current time Factors affecting the real-time operating condition of the expansion valve in air conditioning systems; Indicates the current time The urgency of heat exchange in air conditioning.

[0059] S400: Combines the necessity of strong condensation with the tendency of strong speed to determine the real-time condensing speed requirement of the condenser.

[0060] If the condenser requires strong condensation in real time The larger the value, the stronger the tendency of the rotational speed. The larger the value, the higher the required condenser speed.

[0061] Therefore, in embodiments of the present invention, the real-time condensing speed requirement of the condenser is determined by coordinating the necessity of strong condensation and the tendency for strong rotational speed. Specifically, at the current moment... The required condenser speed is: In the formula, Indicates the current time The required condenser rotation speed; Indicates the current time The degree of necessity for strong condensation in the condenser; Indicates the current time The tendency of the condenser to operate at high speed; This represents a linear normalization function, such as a max-min normalization function, used to normalize to... Within the range, the maximum and minimum values ​​in the maximum-minimum normalization function are taken from the values ​​calculated by the current air conditioner at all times during all refrigeration processes up to the present. The extreme value.

[0062] Similarly, the real-time condensing speed requirement of the condenser is calculated and stored in the operating parameter storage module.

[0063] S500: Based on the required condenser speed, it adaptively adjusts the prediction time window step size, thereby controlling the real-time speed of the condenser.

[0064] The predictive time-domain window step size is essentially the controller's sampling period, which is the time interval between system state updates and control quantity calculations. The more urgent the demand for condenser speed, the smaller the time interval between system state updates and control quantity calculations should be to meet the increasing real-time speed demand. Therefore, the corresponding predictive time-domain window step size should be smaller. Conversely, the lower the demand for condenser speed, the more inclined towards low noise and energy saving, and the larger the predictive time-domain window step size should be.

[0065] Based on the above analysis, in the embodiments of the present invention, the prediction time-domain window step size is adaptively adjusted according to the condenser speed demand, thereby controlling the real-time speed of the condenser. Further aspects include: First, the average historical condensing speed demand is obtained for each historical air conditioning refrigeration process. Specifically, the operating parameter storage module obtains the historical condensing speed demand corresponding to all sampling moments in the historical air conditioning refrigeration process and calculates the average historical condensing speed demand.

[0066] Then, the difference between the historical average condensing speed demand and the condensing speed demand is calculated, and a hyperbolic tangent function is introduced to adaptively adjust the prediction time-domain window step size, thus obtaining the optimized prediction time-domain window step size. Specifically, at the current moment... The optimal prediction time-domain window step size for the MPC prediction model is: In the formula, Indicates the current time Optimize the prediction time-domain window step size of the MPC prediction model; This represents the historical average condenser speed requirement in the air conditioning refrigeration process. Indicates the current time The required condenser rotation speed; Indicates the current time The original prediction time-domain window of the MPC prediction model; This represents the hyperbolic tangent function.

[0067] Furthermore, the real-time rotational speed of the condenser is controlled based on the optimized prediction time-domain window. The specific implementation method is as follows: The MPC prediction model uses an adaptive, real-time optimized prediction time window. The target speed command for the condenser is calculated and transmitted to the execution module to complete the condenser speed regulation. The specific MPC prediction model is optimized by the prediction time-domain window. The processing flow for the condenser target speed command is as follows (this part is existing; the flow is simply listed below for ease of understanding): First, establish a multi-input single-output linear time-varying model (LTV) and sample all input measurements at the current time. Second, based on the adaptively updated prediction model, the prediction time-domain window is optimized. Future trends in condenser condensing temperature, expansion valve superheat, and exhaust temperature within the system; Third, construct a weighted cost function to balance control accuracy and energy saving; Fourth, solve the quadratic programming (QP) problem with hard constraints to obtain the real-time condenser speed command.

[0068] To achieve more efficient air conditioning energy-saving control, the complete air conditioning energy-saving control process based on multi-sensor fusion will be further improved. The specific implementation method is as follows: First, the auxiliary calculation data is updated based on the latest collected multi-dimensional sensor data, and then the optimized prediction time-domain window of the adaptive MPC prediction model is calculated and updated in real time. and the ideal speed of the condenser (by the optimized prediction time domain window) The target rotational speed of the condenser is obtained.

[0069] Then, in the low-frequency range where the target speed of the condenser is below 800 rpm, a voltage compensation coefficient is superimposed. The voltage compensation coefficient can be set to a preset empirical constant greater than zero (e.g., 0.5V) to solve the problem of insufficient torque and step loss jitter of the condenser at low speed, and to complete dead zone compensation and low-frequency torque correction. Additionally, a high-pressure warning is triggered when the condenser condensing temperature exceeds 60 degrees Celsius, forcing the condenser to operate at its maximum speed; if the condenser condensing temperature falls below 22 degrees Celsius for 30 seconds, the minimum condenser speed is restricted and cannot be reduced further. Furthermore, it has a built-in AI self-learning function that remembers user habits, such as sleep temperature, away mode, and turning on the device in advance when returning home, and automatically generates personalized operating plans; it is compatible with extreme environments from -15℃ to 50℃, with energy efficiency attenuation of ≤15%, and can still operate stably in high temperature and cold weather to meet the needs of different regions. In addition, the air conditioner supports remote control via a mobile app, allowing users to turn it on and off in advance, adjust the temperature and mode, and view energy consumption data. It also supports voice control, is compatible with mainstream smart speakers, and eliminates the need for manual operation, enabling "voice-controlled temperature and mode switching." Furthermore, it integrates into the whole-house smart home ecosystem, allowing it to work with devices such as TVs and smart locks, automatically turning on the air conditioner when the door is opened and automatically turning it off when the user leaves home, thus enhancing convenience.

[0070] This embodiment also provides an air conditioning energy-saving control system based on multi-sensor fusion, including a memory and a processor. The memory stores program code. The processor reads the program code stored in the memory and executes real-time acquisition of outdoor temperature, indoor temperature, and the air conditioner's condenser condensing temperature, condenser wind speed, continuous operating time, compressor speed, and expansion valve superheat. Based on the outdoor temperature and condenser condensing temperature, it analyzes the heat dissipation resistance of the outdoor unit, analyzes the condenser blockage based on the condenser wind speed, and analyzes the thermal impact of non-condensing components during long-term operation to determine the real-time necessity of strong condensation. Based on the compressor speed, it analyzes the compressor's operating performance, analyzes the user's historical air conditioning usage habits based on the indoor temperature, and analyzes the expansion valve's parameter operation based on the expansion valve superheat to determine the real-time strong speed trend of the condenser. It coordinates the strong condensation necessity and the strong speed trend to determine the real-time condensing speed demand of the condenser. Based on the condensing speed demand, it adaptively adjusts the prediction time-domain window step size to control the real-time speed of the condenser.

[0071] Furthermore, the processor includes a data acquisition module, a strong condensation necessity analysis module, a strong speed trend analysis module, a condensation speed demand acquisition module, and a speed control module, wherein: The data acquisition module is used to collect outdoor temperature, indoor temperature, as well as the condenser condensing temperature, condenser wind speed, continuous operation time, compressor speed, and expansion valve superheat of the air conditioner in real time. The strong condensation necessity analysis module is used to analyze the heat dissipation resistance of the outdoor unit of the air conditioner based on the outdoor temperature and the condenser condensing temperature, analyze the condenser blockage condition based on the wind speed on the condenser's windward side, and analyze the thermal impact of non-condensing components under long-term operation of the air conditioner based on the continuous operation time, so as to determine the real-time strong condensation necessity of the condenser. The strong speed trend analysis module is used to analyze the compressor's operating performance based on the compressor speed, analyze the user's historical air conditioning usage habits based on the indoor temperature, and analyze the expansion valve's parameter operation performance based on the expansion valve's superheat, thereby determining the condenser's real-time strong speed trend. The condensing speed demand acquisition module is used to determine the real-time condensing speed demand of the condenser by coordinating the necessity of strong condensation and the tendency of strong speed. The speed control module is used to adaptively adjust the prediction time-domain window step size according to the condenser speed requirement, thereby controlling the real-time speed of the condenser.

Claims

1. An air conditioning energy-saving control method based on multi-sensor fusion, characterized in that, include: Real-time data collection includes outdoor temperature, indoor temperature, as well as the condenser condensing temperature, condenser wind speed, continuous operating time, compressor speed, and expansion valve superheat of the air conditioner. The heat dissipation resistance of the outdoor unit of the air conditioner is analyzed based on the outdoor temperature and the condenser condensing temperature. The condenser blockage condition is analyzed based on the wind speed on the condenser's windward side. The thermal impact of non-condensing components under long-term operation of the air conditioner is analyzed based on the continuous operating time to determine the necessity of real-time strong condensation of the condenser. The compressor's operating performance is analyzed based on the compressor speed, the user's historical air conditioning usage habits are analyzed based on the indoor temperature, and the expansion valve's parameter operation performance is analyzed based on the expansion valve's superheat, thus determining the condenser's real-time high speed tendency. By combining the necessary degree of strong condensation and the tendency of strong rotation speed, the real-time condensation speed requirement of the condenser is determined; Based on the required condensing speed, the prediction time-domain window step size is adaptively adjusted to control the real-time speed of the condenser.

2. The air conditioning energy-saving control method based on multi-sensor fusion according to claim 1, characterized in that, The analysis of the air conditioner outdoor unit's heat dissipation resistance based on the outdoor temperature and the condenser condensation temperature includes: The difference between the outdoor temperature and the condenser condensing temperature is calculated to quantify the heat dissipation resistance of the outdoor unit of the air conditioner and obtain the real-time heat dissipation resistance factor of the condenser.

3. The air conditioning energy-saving control method based on multi-sensor fusion according to claim 1, characterized in that, The condenser blockage condition is analyzed based on the wind speed on the condenser's windward side, including: Real-time acquisition of condenser speed; Based on the historical condenser speed and corresponding historical condenser wind speed in the historical air conditioning refrigeration process, calculate the average value of the historical condenser wind speed at the same historical condenser speed as the current condenser speed. The difference between the historical average wind speed on the condenser's windward side and the current wind speed on the condenser's windward side is calculated to quantify the condenser's blockage performance and obtain the real-time blockage factor of the condenser.

4. The air conditioning energy-saving control method based on multi-sensor fusion according to claim 1, characterized in that, The thermal impact of non-condensing components on air conditioners under long-term operation was analyzed based on the aforementioned continuous operating duration, including: Extract the historical maximum duration of continuous operation in the air conditioning refrigeration process; Calculate the ratio of the current continuous operation duration to the maximum historical continuous operation duration to quantify the thermal impact performance of non-condensing components under long-term air conditioning operation and obtain the real-time thermal impact factor of the condenser.

5. The air conditioning energy-saving control method based on multi-sensor fusion according to claim 1, characterized in that, The compressor's operating performance is analyzed based on the compressor speed, including: Extract the historical maximum speed of the compressor in the historical air conditioning refrigeration process; Calculate the ratio of the current compressor speed to the compressor's historical maximum speed to obtain the real-time compressor speed factor of the air conditioner; A two-dimensional coordinate system is constructed with time as the horizontal axis and the compressor speed at each sampling time in the short historical period as the vertical axis, starting from the current moment. The least squares linear fitting method is used to fit a straight line to each sample point in the two-dimensional coordinate system to obtain the slope of the current short-term fitted straight line corresponding to the current compressor speed. Extract the maximum slope of the short-term fitted straight line in the historical air conditioning refrigeration process; Calculate the ratio of the current short-term fitted line slope to the maximum slope of the short-term fitted line to obtain the real-time short-term compressor operating condition factor of the air conditioner. By weighted fusion of the compressor speed factor and the short-term compressor operating condition factor, the compressor operating condition performance is quantified to obtain the real-time compressor frequency increase performance of the air conditioner.

6. The air conditioning energy-saving control method based on multi-sensor fusion according to claim 1, characterized in that, Based on the indoor temperature analysis, the user's historical air conditioning usage habits were observed, including: Real-time collection of perceived temperature for each person in the room, and calculation of the average perceived temperature for all people; Based on the historical indoor temperature and the corresponding historical average temperature during the historical air conditioning cooling process, calculate the average of the historical indoor temperature corresponding to the same historical average temperature as the current average temperature. Calculate the difference between the current indoor temperature and the historical average indoor temperature to quantify the user's historical air conditioning usage habits and obtain the real-time user habit influencing factors for air conditioning.

7. The air conditioning energy-saving control method based on multi-sensor fusion according to claim 1, characterized in that, The operating performance of the expansion valve is analyzed based on the superheat of the expansion valve, including: Obtain the historical average superheat value of the expansion valve in the historical air conditioning refrigeration process; Calculate the ratio between the current expansion valve superheat and the historical average expansion valve superheat to quantify the parameter operation performance of the expansion valve and obtain the real-time expansion valve operating condition influence factor of the air conditioner.

8. The air conditioning energy-saving control method based on multi-sensor fusion according to claim 1, characterized in that, Based on the required condensation speed, the prediction time-domain window step size is adaptively adjusted, including: Obtain the historical average condensing speed requirement in the historical air conditioning refrigeration process; The difference between the historical average condensing speed demand and the condensing speed demand is calculated, and a hyperbolic tangent function is introduced to adaptively adjust the prediction time-domain window step size to obtain an optimized prediction time-domain window step size.

9. An air conditioning energy-saving control system based on multi-sensor fusion, characterized in that, The system includes: a memory and a processor, wherein: The memory is used to store program code; The processor is configured to read program code stored in the memory and execute the method as described in any one of claims 1 to 8.

10. The air conditioning energy-saving control system based on multi-sensor fusion according to claim 9, characterized in that, The processor includes: The data acquisition module is used to collect outdoor temperature, indoor temperature, as well as the condenser condensing temperature, condenser wind speed, continuous operation time, compressor speed, and expansion valve superheat of the air conditioner in real time. The strong condensation necessity analysis module is used to analyze the heat dissipation resistance of the outdoor unit of the air conditioner based on the outdoor temperature and the condenser condensation temperature, analyze the condenser blockage condition based on the wind speed on the condenser's windward side, and analyze the thermal impact of non-condensing components under long-term operation of the air conditioner based on the continuous operation duration, so as to determine the real-time strong condensation necessity of the condenser. The strong speed tendency analysis module is used to analyze the compressor operating performance based on the compressor speed, analyze the user's historical air conditioning usage habits based on the indoor temperature, and analyze the parameter operation performance of the expansion valve based on the expansion valve superheat to determine the real-time strong speed tendency of the condenser. The condensing speed demand acquisition module is used to coordinate the degree of necessity for strong condensation and the tendency of strong speed to determine the real-time condensing speed demand of the condenser. The speed control module is used to adaptively adjust the prediction time-domain window step size according to the condenser speed requirement, thereby controlling the real-time speed of the condenser.

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