Intelligent liquid storage system for energy-saving air conditioner

Abstract

The present application relates to the field of liquid storage adjustment, and particularly relates to an intelligent liquid storage system for an energy-saving air conditioner, which collects operation data of an air conditioning system during a continuous operation period, extracts operation deviation characteristics of an outlet of a liquid accumulator, combines a refrigerant dryness fluctuation amplitude of an inlet of the liquid accumulator, evaluates liquid storage working condition stability of the air conditioning system, calls working condition fluctuation characteristics of the liquid accumulator, evaluates whether the liquid accumulator meets a liquid storage stability benchmark, adaptively matches and analyzes liquid storage adjustment of the air conditioning system, identifies a liquid storage stable period, updates a template database based on an energy efficiency deviation amount corresponding to the liquid storage stable period, and improves energy efficiency, stability and control adaptability of the air conditioning system under variable working conditions. The present application improves energy-saving effect of the air conditioning system and enhances system stability under variable working conditions.

Description

Technical Field

[0001] This invention relates to the field of liquid storage regulation, and more particularly to an intelligent liquid storage system for energy-saving air conditioners. Background Technology

[0002] During operation, the load of an air conditioning system changes in real time due to various factors such as outdoor ambient temperature and solar radiation. As a key component in the refrigerant circuit of the air conditioning system, the receiver's main function is to regulate the refrigerant circulation under different operating conditions, ensuring a stable refrigerant state entering the evaporator, thereby maintaining the system's efficient and reliable operation.

[0003] In variable operating conditions, especially under partial load or rapid load changes, extremely high demands are placed on the dynamic adjustment capabilities of the liquid receiver. Therefore, there is an urgent need to provide an intelligent liquid receiver system that can comprehensively assess the liquid receiver status, intelligently match the optimal adjustment strategy, and possess self-learning and self-optimization capabilities, so as to effectively improve the energy efficiency, stability, and control adaptability of the air conditioning system under variable operating conditions.

[0004] Chinese Patent Application Publication No. CN118896375A discloses a control method, device, electronic equipment, and medium for an air conditioning energy-saving strategy. The method involves inputting first air conditioning control parameters into a preset air conditioning energy-saving strategy prediction model to obtain the energy-saving strategy; then inputting second air conditioning control parameters into a preset cooling capacity prediction model to obtain the cooling capacity of the air conditioner; and finally inputting third air conditioning control parameters into a preset room load prediction model to obtain the predicted room load. The process then returns to the step of obtaining the first air conditioning control parameters at the next moment. By combining the cooling capacities of different air conditioners with accurate load estimation, the accuracy of the control strategy can be further improved, thereby achieving an optimal balance between parameters such as overshoot, comfort, and economy.

[0005] However, the following problems still exist in the existing technology. The assessment of the liquid storage status is based on a single dimension, resulting in delayed judgment. The adjustment strategies are rigid and lack adaptability to different operating conditions. There is a lack of effective self-learning and strategy optimization mechanisms. Summary of the Invention

[0006] Therefore, the present invention provides an intelligent liquid storage system for energy-saving air conditioners to overcome the problems of incomplete liquid storage status assessment, poor adaptive capability of adjustment strategies, and lack of self-optimization mechanism in the prior art.

[0007] To achieve the above objectives, the present invention provides an intelligent liquid storage system for energy-saving air conditioners, comprising: A template storage module, which includes a template database that stores several liquid conditioning templates; The data acquisition module is used to collect the operating data of the air conditioning system during continuous operation and extract the operating deviation characteristics of the liquid receiver outlet. The storage and demand analysis module is used to evaluate the stability of the air conditioning system's liquid storage condition by combining the operating deviation characteristics and the refrigerant dryness fluctuation range at the liquid receiver inlet. The adaptation evaluation module is used to call the operating condition fluctuation characteristics of the liquid reservoir and evaluate whether the liquid reservoir meets the liquid storage stability benchmark. The template adjustment module is used to perform a matching analysis on the liquid storage adjustment of the air conditioning system based on the evaluation results of the adaptation evaluation module, which conforms to the liquid storage stability benchmark. This includes: Based on the template matching degree, the corresponding matching adjustment template is extracted, and the corresponding adjustment command is executed. Based on the execution condition characteristics corresponding to the adjustment command, the liquid storage recovery trend is analyzed. The evaluation and update module is used to identify the stable period of the liquid storage and update the template database based on the energy efficiency deviation corresponding to the stable period of the liquid storage.

[0008] Furthermore, the storage and demand analysis module is used to evaluate the stability of the liquid storage condition of the air conditioning system, including: If the subcooling difference at the liquid reservoir outlet is less than the preset subcooling difference, it is determined that the subcooling stability requirement is met. If the differential pressure fluctuation at the reservoir outlet is less than the preset differential pressure fluctuation range, it is determined that the pressure stability requirement is met. If the refrigerant dryness fluctuation range at the liquid receiver inlet is less than the preset dryness fluctuation range, it is determined that the dryness stability requirement is met. When the requirements for subcooling stability, pressure stability, and dryness stability are met simultaneously, the air conditioning system is determined to have liquid storage stability. Among them, the operational deviation characteristics include the difference in subcooling and the amplitude of pressure difference fluctuation.

[0009] Furthermore, if the air conditioning system does not have stable liquid storage conditions, the operating condition fluctuation characteristics of the liquid storage device are used to assess whether the liquid storage device meets the liquid storage stability benchmark.

[0010] Furthermore, the adaptation evaluation module is used to evaluate whether the liquid reservoir meets the liquid storage stability benchmark, including: If the frequency of liquid level changes in the receiver exceeds the preset frequency, and the fluctuation range of superheat at the receiver outlet exceeds the preset superheat fluctuation range, then the air conditioning system is determined to meet the liquid storage stability benchmark. Among them, the operating condition fluctuation characteristics include the frequency of liquid level changes in the reservoir and the fluctuation range of suction superheat at the reservoir outlet.

[0011] Furthermore, the template adjustment module is used to determine the template matching degree, including: This is used to obtain data sequences corresponding to the operating deviation characteristics and the refrigerant dryness fluctuation amplitude at the inlet of the receiver within a predetermined time window. This is used to divide the predetermined time window into several consecutive sub-windows, and to calculate the coefficient of variation of each feature in each sub-window respectively; The feature vectors of the corresponding data sequence are constructed based on the coefficient of variation, and together they form a feature vector group; This is used to read several template vector groups stored in the template database, calculate the overall similarity between the feature vector group and each template vector group, and use the overall similarity as the template matching degree. The overall similarity is the sum of the similarities between each feature vector in the feature vector group and the corresponding feature vector in the template vector group.

[0012] Furthermore, the template adjustment module is used to extract the corresponding matching adjustment template, including: This is used to sort the template matching degree in descending order, and the template vector group corresponding to the first template matching degree is used as the matching adjustment template.

[0013] Furthermore, the template adjustment module is used to analyze the recovery trend of the reservoir fluid, including: Used to obtain the change in the operating condition characteristics of the execution over a predetermined time period, and to calculate the corresponding statistical variance as the degree of operating condition instability; If the instability of the operating condition is less than the preset instability of the operating condition, it is determined to be a steady-state recovery trend; The operating conditions characteristics include liquid level recovery time, superheat fluctuation, and compressor power change rate.

[0014] Furthermore, the evaluation update module is used to identify periods of stable storage liquid, including: If the liquid storage recovery trend is a steady-state recovery trend, and the duration of the steady-state recovery trend is within a preset duration, then the corresponding time period is identified as the stable liquid storage period.

[0015] Furthermore, the evaluation update module is used to determine the energy efficiency deviation, including: Used to obtain the actual energy efficiency of the air conditioning system in the current operating mode; Used to calculate the difference between the actual energy efficiency and the target energy efficiency corresponding to the operating mode; The absolute value of the ratio of the difference to the target energy efficiency is used to determine the energy efficiency deviation. The operating modes include cooling mode and heating mode.

[0016] Furthermore, the evaluation and update module is used to determine whether to update the template database, including: If the energy efficiency deviation is greater than or equal to the preset energy efficiency deviation, an avoidance tag will be set for the corresponding matching adjustment template. When the matching adjustment template is set with the avoidance tag a predetermined number of times, the matching adjustment template will be removed. If the energy efficiency deviation is less than the preset energy efficiency deviation, then the template matching degree corresponding to the matching adjustment template is increased.

[0017] Compared with existing technologies, this invention includes a template storage module, comprising a template database storing several liquid storage adjustment templates; a data acquisition module for collecting operating data of the air conditioning system during continuous operation and extracting operating deviation characteristics at the liquid receiver outlet; a storage-demand analysis module for evaluating the stability of the air conditioning system's liquid storage conditions by combining operating deviation characteristics with the refrigerant dryness fluctuation amplitude at the liquid receiver inlet; an adaptation evaluation module for calling the liquid receiver's operating condition fluctuation characteristics to evaluate whether the liquid receiver meets the liquid storage stability benchmark; a template adjustment module for adaptively matching and analyzing the liquid storage adjustment of the air conditioning system based on the evaluation results of the adaptation evaluation module (assuming compliance with the liquid storage stability benchmark); and an evaluation update module for identifying liquid storage stability periods and updating the template database based on the energy efficiency deviation corresponding to the liquid storage stability periods. This invention improves the energy-saving effect of the air conditioning system and enhances system stability under varying operating conditions through multi-dimensional liquid storage quality evaluation, qualitative feature template matching, and an energy efficiency feedback self-updating mechanism.

[0018] In particular, this invention constructs a multi-parameter comprehensive evaluation mechanism for the operating state of the liquid receiver to comprehensively quantify the thermodynamic state and flow stability of the refrigerant in the liquid receiver and its related pipelines. From a thermodynamic perspective, this invention quantifies the difference between the saturation temperature and the actual liquid temperature based on the subcooling difference at the liquid receiver outlet to determine the intensity of fluctuations in the thermodynamic state at the liquid receiver outlet. A large subcooling difference indicates potential drastic liquid level fluctuations, gas-liquid entrainment, or unstable refrigerant state from the condenser within the liquid receiver, thus affecting the quality of the refrigerant liquid before entering the throttling device and reducing the evaporator's liquid supply stability and system energy efficiency. Simultaneously, from a fluid dynamics perspective, this invention quantifies the pressure difference change between the outlet flange and the expansion valve inlet flange on the liquid receiver outlet pipeline based on the pressure difference fluctuation amplitude at the liquid receiver outlet to determine the pressure stability from the liquid receiver outlet to the downstream pipeline. Dramatic pressure difference fluctuations indicate potential rapid pressure changes within the liquid receiver, such as static pressure changes caused by liquid level fluctuations, violent oscillations in the expansion valve opening, sudden changes in refrigerant flow, or abnormal operating conditions such as the presence of gas-liquid two-phase flow in the pipeline. Such fluctuations cause the expansion valve's operating point to drift, leading to uncontrolled evaporator superheat and weakening system stability and energy efficiency. Furthermore, this invention analyzes the issue from a phase change perspective, evaluating the stability of the two-phase flow at the condenser outlet and before it enters the receiver based on the refrigerant dryness fluctuation range at the receiver inlet. Large inlet dryness fluctuations typically indicate insufficient condenser subcooling, non-condensable gas interference, abnormal refrigerant charge, or rapid load changes causing fluctuations in condensation performance. Moreover, severe dryness fluctuations can directly disrupt the receiver's liquid seal function, allowing gaseous refrigerant to enter the receiver outlet, inducing compressor liquid slugging or abnormal suction superheat. Therefore, this invention, by integrating the characteristic parameters from these three dimensions, achieves a comprehensive quantitative evaluation of the receiver's dynamic regulation quality and the stability of the air conditioning system under varying operating conditions, effectively improving the energy efficiency and operational reliability of the air conditioning system under these conditions.

[0019] In particular, this invention incorporates an adaptation evaluation module. Based on the mechanism of cross-verification of mechanical dynamic stability and thermodynamic dynamic stability, it utilizes two dynamic statistical characteristics—the frequency of liquid level changes and the amplitude of suction superheat fluctuations—to construct a two-dimensional comprehensive judgment mechanism for the stable operation of the receiver. Firstly, this invention quantifies the number of effective liquid level fluctuations within the receiver per unit time by measuring the frequency of liquid level changes, thereby determining the temporal activity of liquid level changes and the oscillation frequency of the receiver's mechanical equilibrium state. More frequent liquid level changes indicate that the refrigerant within the receiver is in a continuous oscillating state, making it difficult to form a stable liquid seal, and directly affecting the receiver's function. Secondly, this invention quantifies the dispersion of the difference between the suction temperature and the saturation temperature corresponding to the evaporation pressure over a certain period by measuring the amplitude of suction superheat fluctuations at the receiver outlet, thereby determining the degree of thermodynamic turbulence of suction superheat and the discrete stability of the low-pressure side's thermodynamic state. Large fluctuations in refrigerant level usually indicate over-adjustment of the expansion valve, improper selection, or refrigerant flow oscillations. These fluctuations can easily lead to alternating liquid carryover in the compressor suction and excessively high suction superheat, severely impacting compressor lifespan and system energy efficiency. Therefore, this invention uses a dual-indicator cross-judgment of the frequency of liquid level changes and the amplitude of suction superheat fluctuations to more accurately and reliably reflect the operational stability of the receiver and suction system, effectively improving the operational stability, energy efficiency, and lifespan of key components of the air conditioning system under varying operating conditions.

[0020] In particular, this invention incorporates a template adjustment module. Based on a fusion evaluation mechanism of time response, thermal stability, and energy impact, it performs multi-dimensional quantitative evaluation of the actual effect of adjustment commands by analyzing the characteristics of the operating conditions. This accurately determines the liquid level recovery trend, providing a reliable basis for the self-learning and self-optimization of the template database, and achieving a faster, smoother, and more energy-efficient liquid level adjustment process. On one hand, from the perspective of time response, this invention quantifies the time elapsed from the execution of the adjustment command to the first entry and maintenance of the liquid level within the preset target range by measuring the liquid level recovery time of the reservoir. This determines the dynamic time scale from abnormal to normal liquid level, measuring the timeliness of the adjustment action. A shorter recovery time indicates that the adjustment mechanism, such as a variable volume chamber or regulating valve, operates quickly without jamming or excessive mechanical inertia. On the other hand, from the perspective of thermal stability, this invention quantifies the maximum deviation of the suction superheat relative to the target value during the adjustment process by measuring the superheat fluctuation, thus determining the degree of thermal disturbance experienced by the evaporator and compressor heat absorption side during the adjustment process. Small superheat fluctuations indicate minimal impact on the evaporator and compressor during the adjustment process, which helps maintain evaporator heat transfer efficiency and compressor lubrication safety. Conversely, excessive superheat fluctuations may lead to instantaneous wet compression, jeopardizing the compressor's suction safety. Furthermore, this invention addresses the energy impact dimension by quantifying the rate of change of compressor input power per unit time using the compressor power change rate, thus determining the dynamic energy cost and instantaneous energy consumption changes associated with compressor load variations during adjustment. A low compressor power change rate indicates a smooth adjustment process, avoiding power spikes or drastic fluctuations, which is beneficial for energy saving and extending compressor lifespan. Conversely, a high power change rate accelerates compressor motor insulation aging, bearing wear, and thermal shock to the inverter power module. Therefore, this invention, through the fusion analysis of operating condition characteristics, comprehensively quantifies the dynamic quality of the liquid storage adjustment process, effectively improving the adaptability and energy-saving effect of adjustment commands, and enhancing the operational stability and equipment reliability of the air conditioning system during long-term operation.

[0021] In particular, this invention includes an evaluation and update module that uses energy efficiency deviation as direct feedback to construct a differentiated update mechanism for the template database: templates that meet energy efficiency standards are given a template matching gain to enhance their competitive advantage; templates that do not meet energy efficiency standards are given an avoidance label and counted cumulatively, and are removed after a predetermined number of times. Through the aforementioned update strategy, the template database continuously iterates during long-term operation, enabling the air conditioning system to automatically adapt to equipment aging and environmental changes during long-term operation, effectively reducing manual debugging and maintenance costs. Attached Figure Description

[0022] Figure 1 A functional block diagram of an intelligent liquid storage system for energy-saving air conditioners, according to an embodiment of the invention; Figure 2This is a logic decision diagram for evaluating the stability of the liquid storage condition of an air conditioning system according to an embodiment of the invention. Figure 3 This is a logic diagram for evaluating whether a liquid reservoir meets the liquid storage stability criteria in an embodiment of the invention. Figure 4 This is a logic diagram for identifying the stable period of the liquid storage in an embodiment of the invention. Detailed Implementation

[0023] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0024] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0025] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0026] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0027] Please see Figure 1 The diagram shown is a functional block diagram of an intelligent liquid storage system for energy-saving air conditioners according to an embodiment of the present invention. The system includes: A template storage module, which includes a template database that stores several liquid conditioning templates; The data acquisition module is used to collect the operating data of the air conditioning system during continuous operation and extract the operating deviation characteristics of the liquid receiver outlet. The storage and demand analysis module, which is connected to the data acquisition module, is used to evaluate the stability of the liquid storage condition of the air conditioning system by combining the operating deviation characteristics and the fluctuation range of refrigerant dryness at the liquid receiver inlet. An adaptation evaluation module is connected to the storage and demand analysis module to call the operating condition fluctuation characteristics of the liquid storage device and evaluate whether the liquid storage device meets the liquid storage stability benchmark. A template adjustment module, connected to both the template storage module and the adaptation evaluation module, is used to perform a matching analysis on the liquid storage adjustment of the air conditioning system based on the evaluation results of the adaptation evaluation module, which conforms to the liquid storage stability benchmark. This includes... Based on the template matching degree, the corresponding matching adjustment template is extracted, and the corresponding adjustment command is executed. Based on the execution condition characteristics corresponding to the adjustment command, the liquid storage recovery trend is analyzed. An evaluation and update module, which is connected to the template adjustment module, is used to identify the stable liquid storage period and update the template database based on the energy efficiency deviation corresponding to the stable liquid storage period.

[0028] Specifically, the liquid storage regulation templates in the template database are pre-stored and set by technicians based on historical operating data, system simulation models, or expert experience during the initial system operation phase. After the system is put into operation, the template database continuously iterates through an evaluation and update module: increasing the matching degree of templates that meet energy efficiency standards to enhance their advantages; setting avoidance tags for templates that do not meet energy efficiency standards, and removing them after accumulating a predetermined number of times, thereby achieving self-learning and self-optimization of the template database.

[0029] Specifically, the operating data includes operating deviation characteristics, refrigerant dryness fluctuation amplitude at the liquid receiver inlet, operating condition fluctuation characteristics, execution operating condition characteristics, duration of steady-state recovery trend, and energy efficiency deviation.

[0030] Specifically, there are no restrictions on the specific structure of the template storage module, data acquisition module, storage and demand analysis module, adaptation evaluation module, template adjustment module, and evaluation update module. Each module or its units can be composed of logic components or combinations of logic components. Logic components include field-programmable processors, computers, or microprocessors in computers.

[0031] Please see Figure 2 As shown, this is a logic decision diagram for evaluating the stability of the liquid storage condition of an air conditioning system according to an embodiment of the present invention. In this embodiment, the liquid storage and demand analysis module is used to evaluate the stability of the liquid storage condition of the air conditioning system, including: If the subcooling difference at the liquid reservoir outlet is less than the preset subcooling difference, it is determined that the subcooling stability requirement is met. If the differential pressure fluctuation at the reservoir outlet is less than the preset differential pressure fluctuation range, it is determined that the pressure stability requirement is met. If the refrigerant dryness fluctuation range at the liquid receiver inlet is less than the preset dryness fluctuation range, it is determined that the dryness stability requirement is met. When the requirements for subcooling stability, pressure stability, and dryness stability are met simultaneously, the air conditioning system is determined to have liquid storage stability. Among them, the operational deviation characteristics include the difference in subcooling and the amplitude of pressure difference fluctuation.

[0032] Specifically, the data acquisition module further includes a subcooling acquisition unit, which collects the actual temperature of the refrigerant and the outlet pressure of the receiver using temperature and pressure sensors installed on the outlet pipeline of the receiver. The controller then converts the results into the corresponding saturation temperature based on the outlet pressure. Furthermore, the instantaneous subcooling value is determined based on the absolute value of the difference between the saturation temperature and the actual temperature, and the standard deviation of the instantaneous subcooling value is calculated within a predetermined time window as the subcooling difference at the receiver outlet. The predetermined time window can be set according to the dynamic response characteristics of the system. For example, 4 to 6 times the system time constant can be set as the predetermined time window to ensure that the real fluctuation of relevant parameters during the dynamic adjustment process is fully reflected.

[0033] Specifically, the storage and demand analysis module also includes a subcooling calculation unit to obtain the subcooling difference, quantifying the difference between the saturation temperature and the actual liquid temperature to determine the intensity of fluctuations in the thermal state at the liquid receiver outlet. A large subcooling difference indicates that there may be drastic fluctuations in liquid level, gas-liquid entrainment, or unstable refrigerant state from the condenser inside the liquid receiver, thereby affecting the quality of the refrigerant liquid before entering the throttling device and reducing the liquid supply stability of the evaporator and system energy efficiency.

[0034] It is understandable that the preset subcooling difference can be determined based on the upper limit of the statistical fluctuation of subcooling under the rated operating conditions of the air conditioning system; or it can be determined based on the measured empirical value of the same type of unit under standard operating conditions.

[0035] Specifically, the data acquisition module further includes a pressure acquisition unit, which acquires the flange pressure value and the inlet flange pressure value through pressure sensors installed at the outlet flange of the reservoir and the inlet flange of the expansion valve, and calculates the absolute value of the instantaneous pressure difference between the flange pressure value and the inlet flange pressure value. Then, within a predetermined time window, the standard deviation of the absolute value of the instantaneous pressure difference is statistically analyzed as the pressure difference fluctuation amplitude at the reservoir outlet.

[0036] Specifically, the storage and demand analysis module also includes a pressure calculation unit to obtain the differential pressure fluctuation amplitude, thereby quantifying the pressure difference change between the outlet flange of the liquid receiver outlet pipeline and the inlet flange of the expansion valve, and determining the pressure stability from the liquid receiver outlet to the downstream pipeline. Severe differential pressure fluctuations indicate a possible rapid change in pressure within the liquid receiver, such as static pressure changes caused by liquid level fluctuations, violent oscillations in the expansion valve opening, sudden changes in refrigerant flow, or abnormal operating conditions such as the presence of gas-liquid two-phase flow in the pipeline. Such fluctuations cause the expansion valve operating point to drift, which in turn leads to uncontrolled evaporator superheat, weakening system stability and energy efficiency.

[0037] It is understandable that the preset differential pressure fluctuation range can be determined by adding an appropriate margin to the statistical upper limit of differential pressure fluctuation when the system is running stably under rated operating conditions; or it can be determined by referring to the allowable fluctuation boundary of the rated operating differential pressure range of the expansion valve.

[0038] Specifically, the data acquisition module further includes a dryness acquisition unit, used to acquire the actual temperature of the refrigerant and the inlet pressure of the receiver through temperature and pressure sensors installed on the inlet pipe of the receiver. Based on the pressure-enthalpy relationship, using the refrigerant equation of state, such as the Peng-Robinson equation or the REFPROP database, the actual enthalpy value is calculated from the inlet pressure and actual temperature. The first difference between the actual enthalpy value and the saturated liquid hanky, and the second difference between the saturated gas hanky and the saturated liquid hanky are calculated respectively. The ratio of the first difference to the second difference is taken as the refrigerant dryness. Furthermore, the standard deviation of the refrigerant dryness is statistically analyzed within a predetermined time window as the refrigerant dryness fluctuation range at the receiver inlet.

[0039] Specifically, the storage and demand analysis module also includes a dryness calculation unit to obtain the refrigerant dryness fluctuation range, in order to assess the stability of the two-phase flow at the condenser outlet and before entering the receiver. Large inlet dryness fluctuations typically indicate insufficient subcooling of the condenser, interference from non-condensable gases, abnormal refrigerant charge, or rapid load changes leading to fluctuations in condensation performance. Furthermore, drastic dryness fluctuations can directly disrupt the liquid seal function of the receiver, allowing gaseous refrigerant to enter the receiver outlet, inducing compressor liquid slugging or abnormal suction superheat.

[0040] The preset dryness fluctuation range is determined based on the dryness stability range corresponding to the normal subcooling state of the condenser outlet under rated operating conditions.

[0041] Specifically, if the air conditioning system does not have stable liquid storage conditions, the operating condition fluctuation characteristics of the liquid storage device are used to assess whether the liquid storage device meets the liquid storage stability benchmark.

[0042] Please see Figure 3As shown, this is a logic diagram for evaluating whether a liquid reservoir meets the liquid reservoir stability benchmark according to an embodiment of the present invention. In this embodiment, the adaptation evaluation module is used to evaluate whether the liquid reservoir meets the liquid reservoir stability benchmark, including: If the frequency of liquid level changes in the receiver exceeds the preset frequency, and the fluctuation range of superheat at the receiver outlet exceeds the preset superheat fluctuation range, then the air conditioning system is determined to meet the liquid storage stability benchmark. Among them, the operating condition fluctuation characteristics include the frequency of liquid level changes in the reservoir and the fluctuation range of suction superheat at the reservoir outlet.

[0043] Specifically, the data acquisition module further includes a liquid level change acquisition unit, which is used to acquire the liquid level signal of the reservoir through the liquid level sensor, perform differential processing on the liquid level signal, set a change dead zone threshold, and count an effective fluctuation when the absolute value of the first derivative of the liquid level exceeds the change dead zone threshold. The number of effective fluctuations in the liquid level in the reservoir per unit time is counted to obtain the liquid level change frequency.

[0044] The variable dead zone threshold is determined based on the statistical fluctuation baseline of the liquid level change rate of the air conditioning system under rated steady-state conditions. The standard deviation of the liquid level change rate under steady-state conditions is calculated, and 2 to 3 times the standard deviation is set as the variable dead zone threshold.

[0045] Specifically, the adaptation evaluation module also includes a liquid level determination unit, which quantifies the number of effective fluctuations in the liquid level within the receiver per unit time based on the frequency of liquid level changes in the receiver, thereby measuring the frequency of liquid level changes and determining the temporal activity of liquid level changes and the oscillation frequency of the receiver's mechanical balance state. The more frequent the liquid level changes, the more likely the refrigerant inside the receiver is in a continuous oscillating state, making it difficult to form a stable liquid seal, and directly affecting the receiver's function.

[0046] The preset frequency of change is determined based on the statistical upper limit of the natural fluctuation of the liquid level under rated steady-state conditions.

[0047] Specifically, the data acquisition module further includes a suction acquisition unit, which collects suction temperature and suction pressure through temperature and pressure sensors installed on the compressor suction line, and converts them into the corresponding saturation temperature by the controller. Then, the absolute value of the difference between the suction temperature and the saturation temperature is used as the instantaneous superheat value, and the standard deviation of the instantaneous superheat value is calculated within a predetermined time window as the suction superheat fluctuation amplitude. Furthermore, the data acquisition module also includes a superheat acquisition unit, which calls the corresponding target superheat setpoint according to the current system operating mode and conditions. Based on the aforementioned method for calculating instantaneous superheat values, the instantaneous superheat values ​​at consecutive moments within a predetermined time period after the execution of the adjustment command are determined. The absolute value of the maximum deviation relative to the target superheat is taken as the superheat fluctuation, which is used to measure the degree of extreme disturbance of thermodynamic parameters during the execution of the adjustment command, i.e., the maximum deviation of the compressor suction state relative to the target value. Further, the variance of the superheat fluctuation is used to quantify the stability of the convergence of thermodynamic parameters during the adjustment process. The smaller the variance, the more stable the superheat tends to the target value during the adjustment process, without violent fluctuations or repeated crossings, and the stable and controllable thermal state of the evaporator. The larger the variance, the more likely the superheat is repeatedly overshooting or oscillating convergence, the unstable thermal state of the evaporator, and the more likely it is to cause alternating occurrences of liquid carryover in the compressor suction or excessively high exhaust temperature, affecting the compressor reliability and system energy efficiency.

[0048] In this embodiment, the predetermined time period is determined based on a multiple of the current liquid level recovery time. For example, it is set to 2 to 4 times the current liquid level recovery time so that the predetermined time period can be adaptively adjusted according to the real-time response characteristics of the system, fully capturing the maximum deviation value of superheat during the adjustment process, while taking into account the complete coverage of the entire disturbance process, and effectively distinguishing between effective thermal signals and measurement noise.

[0049] Specifically, the adaptation evaluation module also includes a superheat determination unit, used to quantify the dispersion of the difference between the suction temperature and the saturation temperature corresponding to the evaporation pressure over a certain period of time based on the fluctuation amplitude of the suction superheat, in order to determine the degree of thermodynamic turbulence of the suction superheat and the dispersion stability of the low-pressure side thermodynamic state. Large fluctuations usually reflect over-adjustment of the expansion valve, improper selection, or refrigerant flow oscillations, which can easily lead to alternating occurrences of liquid carryover in the compressor suction and excessively high suction superheat, severely and adversely affecting the compressor life and system energy efficiency.

[0050] Understandably, the preset superheat fluctuation range can be determined based on the upper limit of the statistical fluctuation of the intake superheat when the system is running stably under rated conditions; or it can be determined by referring to the superheat control accuracy range recommended in the expansion valve selection manual.

[0051] Specifically, the template adjustment module is used to determine the template matching degree, including: This is used to obtain data sequences corresponding to the operating deviation characteristics and the refrigerant dryness fluctuation amplitude at the inlet of the receiver within a predetermined time window. This is used to divide the predetermined time window into several consecutive sub-windows, and to calculate the coefficient of variation of each feature in each sub-window respectively; The feature vectors of the corresponding data sequence are constructed based on the coefficient of variation, and together they form a feature vector group; This is used to read several template vector groups stored in the template database, calculate the overall similarity between the feature vector group and each template vector group, and use the overall similarity as the template matching degree. The overall similarity is the sum of the similarities between each feature vector in the feature vector group and the corresponding feature vector in the template vector group.

[0052] In this embodiment, a single similarity can be calculated using cosine similarity or the reciprocal of Euclidean distance.

[0053] Specifically, the template adjustment module is used to extract the corresponding matching adjustment template, including: This is used to sort the template matching degree in descending order, and the template vector group corresponding to the first template matching degree is used as the matching adjustment template.

[0054] Specifically, the template adjustment module is used to analyze the recovery trend of the reservoir fluid, including: Used to obtain the change in the operating condition characteristics of the execution over a predetermined time period, and to calculate the corresponding statistical variance as the degree of operating condition instability; If the instability of the operating condition is less than the preset instability of the operating condition, it is determined to be a steady-state recovery trend; The operating conditions characteristics include liquid level recovery time, superheat fluctuation, and compressor power change rate.

[0055] Specifically, the data acquisition module further includes a liquid level recovery acquisition unit, which uses the moment the template adjustment module issues the adjustment command as the start time and the moment the liquid level signal first enters the preset target range as the end time. The difference between the end time and the start time determines the liquid level recovery time, which is used to measure the response speed of the adjustment command execution in terms of timeliness. Furthermore, the variance of the liquid level recovery time quantifies the fluctuation of the liquid level recovery speed during the liquid storage adjustment process, used to determine whether the adjustment is smoothly converging, avoiding misjudgment of a steady-state trend due to repeated liquid level oscillations. The smaller the variance, the smoother and more stable the current adjustment process; the larger the variance, the more oscillations or overshoot still exist in the adjustment process, and a steady-state recovery trend has not yet been formed.

[0056] The target liquid level ± allowable deviation is used as the upper and lower limits corresponding to the preset target range.

[0057] Specifically, the data acquisition module also includes a power acquisition unit, used to acquire the instantaneous power of the compressor through voltage and current sensors installed on the compressor power supply line. Then, within a predetermined time window, the compressor power-time curve is linearly fitted, and the absolute value of the slope of the fitted line is taken as the compressor power change rate, used to measure the dynamic energy cost of compressor load changes during the adjustment process. The lower the change rate, the smoother the adjustment process, which is beneficial for energy saving and extending compressor life. Furthermore, the variance of the compressor power change rate quantifies the consistency of power fluctuations during the adjustment process; the smaller the variance, the more uniform the compressor power changes during the adjustment process without drastic fluctuations, and the stable system energy output; the larger the variance, the more uniform the compressor power adjustment, with drastic energy cost fluctuations, which can easily cause additional mechanical and thermal stress shocks to the compressor.

[0058] Furthermore, by normalizing the sum of the variances of the liquid level recovery time, the superheat fluctuation, and the compressor power change rate, the operating condition instability is obtained to evaluate the overall convergence stability of the liquid storage regulation process, that is, the smoothness with which the system re-enters steady state after experiencing regulation disturbances. The smaller the operating condition instability, the smoother the changes in the various operating condition characteristics of this liquid storage regulation process, the more uniform the liquid level recovery, thermodynamic parameters, and compressor load converge toward the target value, and the system is steadily approaching steady state, rather than being in an oscillating or repeatedly overshooting state.

[0059] In this embodiment, the preset operating condition instability is determined based on theoretical calculations of the system dynamic response boundary. The maximum allowable fluctuation boundary values ​​for liquid level recovery time, superheat fluctuation, and compressor power change rate are determined respectively. The operating condition instability obtained by normalizing each boundary value is used as the preset operating condition instability.

[0060] Please see Figure 4 As shown, this is a logic decision diagram for identifying stable liquid storage periods according to an embodiment of the present invention. In this embodiment, the evaluation and update module is used to identify stable liquid storage periods, including: If the liquid storage recovery trend is a steady-state recovery trend, and the duration of the steady-state recovery trend is within a preset duration, then the corresponding time period is identified as the stable liquid storage period.

[0061] Specifically, the data acquisition module further includes a steady-state acquisition unit, used to take the moment when the liquid level signal first enters a preset target range as the steady-state observation moment, and continuously monitor the operating condition instability corresponding to the liquid level signal, suction superheat, and compressor power change rate. From the steady-state observation moment, if the operating condition instability remains less than the preset operating condition instability, the duration of the steady-state recovery trend is recorded as the maintenance duration, until the steady-state maintenance moment when the operating condition instability first exceeds or equals the preset operating condition instability. Furthermore, the difference between the steady-state maintenance moment and the steady-state observation moment is taken as the maintenance duration of the steady-state recovery trend. If the aforementioned conditions are met from the steady-state observation time, the duration of maintenance will continue to accumulate.

[0062] Specifically, the evaluation and update module also includes a recovery determination unit, which is used to determine the true convergence depth and persistent stability of the system's thermodynamic and flow parameters after the liquid storage adjustment is completed by the maintenance duration, and to quantify the air conditioning system's ability to maintain balance after overcoming refrigerant migration inertia and environmental disturbances. When the maintenance duration reaches the target, the energy efficiency deviation extracted subsequently is representative and reliable, thereby ensuring that the self-learning iteration of the template database is not contaminated by transient pseudo-steady-state data.

[0063] In this embodiment, after applying a standard adjustment command under rated operating conditions, the lower limit of the preset maintenance duration range is determined by experimental measurement or dynamic simulation to obtain the time required for the system to reach equilibrium of several key thermodynamic parameters from the end of the adjustment command action; while the upper limit of the preset maintenance duration range can be determined based on the multiple of the liquid level recovery time corresponding to the current adjustment command, or based on the maximum thermal time constant of the system under extreme operating conditions. The key thermodynamic parameters include the liquid level in the receiver, the subcooling at the receiver outlet, the dryness of the refrigerant at the receiver inlet, the superheat of the compressor suction gas, and the compressor power change rate.

[0064] Specifically, the evaluation update module is used to perform differentiated update adjustments, including: If the liquid storage recovery trend is a steady-state recovery trend, but the duration of the steady-state recovery trend is less than the lower limit of the preset duration range, it is determined that the system has not yet completed the refrigerant mass redistribution, and the corresponding time period is not considered as the liquid storage stable period, and energy efficiency assessment and template update are not triggered. If the liquid storage recovery trend is a steady-state recovery trend, and the duration of the steady-state recovery trend is within a preset duration, then the corresponding time period is identified as the stable liquid storage period, and the template database is updated based on the energy efficiency deviation corresponding to the stable liquid storage period. If the liquid storage recovery trend is a steady-state recovery trend, but the duration of the steady-state recovery trend is greater than the upper limit of the preset duration range, then the corresponding time period will be identified as the stable period of the liquid storage and the energy efficiency deviation will be calculated. However, the template matching degree of the corresponding matching adjustment template will remain unchanged, and no positive gain will be given.

[0065] Specifically, the evaluation update module is used to determine the energy efficiency deviation, including: Used to obtain the actual energy efficiency of the air conditioning system in the current operating mode; Used to calculate the difference between the actual energy efficiency and the target energy efficiency corresponding to the operating mode; The absolute value of the ratio of the difference to the target energy efficiency is used to determine the energy efficiency deviation. The operating modes include a cooling mode and a heating mode; The actual energy efficiency corresponding to the cooling mode is the cooling energy efficiency ratio, which is the ratio of cooling capacity to compressor power consumption. The cooling capacity is calculated by multiplying the enthalpy difference between the inlet and outlet of the evaporator and the refrigerant mass flow rate. The actual energy efficiency corresponding to the heating mode is the heating energy efficiency ratio, which is the ratio of the heating capacity to the power consumed by the compressor. The heating capacity is calculated by multiplying the enthalpy difference between the inlet and outlet of the condenser and the refrigerant mass flow rate. The target energy efficiency can be determined by querying the energy efficiency target table stored in the system or by interpolation, based on operating conditions such as outdoor ambient temperature and indoor load.

[0066] Specifically, the evaluation and update module is used to determine whether to update the template database, including: If the energy efficiency deviation is greater than or equal to the preset energy efficiency deviation, an avoidance tag will be set for the corresponding matching adjustment template. When the matching adjustment template is set with the avoidance tag a predetermined number of times, the matching adjustment template will be removed. If the energy efficiency deviation is less than the preset energy efficiency deviation, then the template matching degree corresponding to the matching adjustment template is increased.

[0067] The preset energy efficiency deviation is determined based on the allowable energy efficiency fluctuation range in the energy efficiency rating standard for air conditioning systems.

[0068] Specifically, the predetermined number of times is a threshold for the cumulative number of times the matching adjustment template is set with avoidance tags; in this embodiment, it is set to 3 times. When the cumulative number of avoidance tags reaches this threshold, it indicates that the template has failed to achieve the expected energy efficiency in multiple independent operating cycles, and its inefficiency is statistically significant, rather than caused by occasional fluctuations, and therefore it is discarded. Furthermore, those skilled in the art can adjust this according to the stability of the air conditioning system's operating environment.

[0069] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. An intelligent liquid storage system for energy-saving air conditioners, characterized in that, include: A template storage module, which includes a template database that stores several liquid conditioning templates; The data acquisition module is used to collect the operating data of the air conditioning system during continuous operation and extract the operating deviation characteristics of the liquid receiver outlet. The storage and demand analysis module is used to evaluate the stability of the air conditioning system's liquid storage condition by combining the operating deviation characteristics and the refrigerant dryness fluctuation range at the liquid receiver inlet. The adaptation evaluation module is used to call the operating condition fluctuation characteristics of the liquid reservoir and evaluate whether the liquid reservoir meets the liquid storage stability benchmark. The template adjustment module is used to perform matching analysis on the liquid storage adjustment of the air conditioning system based on the evaluation results of the adaptation evaluation module, which conforms to the liquid storage stability benchmark. include, Based on the template matching degree, the corresponding matching adjustment template is extracted, and the corresponding adjustment command is executed. Based on the execution condition characteristics corresponding to the adjustment command, the liquid storage recovery trend is analyzed. The evaluation and update module is used to identify the stable period of the liquid storage and update the template database based on the energy efficiency deviation corresponding to the stable period of the liquid storage.

2. The intelligent liquid storage system for energy-saving air conditioning according to claim 1, characterized in that, The liquid storage and demand analysis module is used to evaluate the stability of the liquid storage condition of the air conditioning system, including: If the subcooling difference at the liquid reservoir outlet is less than the preset subcooling difference, it is determined that the subcooling stability requirement is met. If the differential pressure fluctuation at the reservoir outlet is less than the preset differential pressure fluctuation range, it is determined that the pressure stability requirement is met. If the refrigerant dryness fluctuation range at the liquid receiver inlet is less than the preset dryness fluctuation range, it is determined that the dryness stability requirement is met. When the requirements for subcooling stability, pressure stability, and dryness stability are met simultaneously, the air conditioning system is determined to have liquid storage stability. Among them, the operational deviation characteristics include the difference in subcooling and the amplitude of pressure difference fluctuation.

3. The intelligent liquid storage system for energy-saving air conditioning according to claim 2, characterized in that, If the air conditioning system does not have stable liquid storage conditions, the operating condition fluctuation characteristics of the liquid storage device are used to evaluate whether the liquid storage device meets the liquid storage stability benchmark.

4. The intelligent liquid storage system for energy-saving air conditioning according to claim 3, characterized in that, The adaptation evaluation module is used to evaluate whether the liquid reservoir meets the liquid storage stability benchmark, including: If the frequency of liquid level changes in the receiver exceeds the preset frequency, and the fluctuation range of superheat at the receiver outlet exceeds the preset superheat fluctuation range, then the air conditioning system is determined to meet the liquid storage stability benchmark. Among them, the operating condition fluctuation characteristics include the frequency of liquid level changes in the reservoir and the fluctuation range of suction superheat at the reservoir outlet.

5. The intelligent liquid storage system for energy-saving air conditioning according to claim 1, characterized in that, The template adjustment module is used to determine the template matching degree, including: This is used to obtain data sequences corresponding to the operating deviation characteristics and the refrigerant dryness fluctuation amplitude at the inlet of the receiver within a predetermined time window. This is used to divide the predetermined time window into several consecutive sub-windows, and to calculate the coefficient of variation of each feature in each sub-window respectively; The feature vectors of the corresponding data sequence are constructed based on the coefficient of variation, and together they form a feature vector group; This is used to read several template vector groups stored in the template database, calculate the overall similarity between the feature vector group and each template vector group, and use the overall similarity as the template matching degree. The overall similarity is the sum of the similarities between each feature vector in the feature vector group and the corresponding feature vector in the template vector group.

6. The intelligent liquid storage system for energy-saving air conditioning according to claim 5, characterized in that, The template adjustment module is used to extract the corresponding matching adjustment template, including: This is used to sort the template matching degree in descending order, and the template vector group corresponding to the first template matching degree is used as the matching adjustment template.

7. The intelligent liquid storage system for energy-saving air conditioning according to claim 1, characterized in that, The template adjustment module is used to analyze the recovery trend of the reservoir fluid, including: Used to obtain the change in the operating condition characteristics of the execution over a predetermined time period, and to calculate the corresponding statistical variance as the degree of operating condition instability; If the instability of the operating condition is less than the preset instability of the operating condition, it is determined to be a steady-state recovery trend; The operating conditions characteristics include liquid level recovery time, superheat fluctuation, and compressor power change rate.

8. The intelligent liquid storage system for energy-saving air conditioning according to claim 1, characterized in that, The assessment update module is used to identify periods of stable storage liquid, including: If the liquid storage recovery trend is a steady-state recovery trend, and the duration of the steady-state recovery trend is within a preset duration, then the corresponding time period is identified as the stable liquid storage period.

9. The intelligent liquid storage system for energy-saving air conditioning according to claim 1, characterized in that, The assessment update module is used to determine the energy efficiency deviation, including: Used to obtain the actual energy efficiency of the air conditioning system in the current operating mode; Used to calculate the difference between the actual energy efficiency and the target energy efficiency corresponding to the operating mode; The absolute value of the ratio of the difference to the target energy efficiency is used to determine the energy efficiency deviation. The operating modes include cooling mode and heating mode.

10. The intelligent liquid storage system for energy-saving air conditioning according to claim 9, characterized in that, The evaluation and update module is used to determine whether to update the template database, including: If the energy efficiency deviation is greater than or equal to the preset energy efficiency deviation, an avoidance tag will be set for the corresponding matching adjustment template. When the matching adjustment template is set with the avoidance tag a predetermined number of times, the matching adjustment template will be removed. If the energy efficiency deviation is less than the preset energy efficiency deviation, then the template matching degree corresponding to the matching adjustment template is increased.

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