Energy-saving monitoring method and system for heat pump air conditioner

Abstract

The application relates to the technical field of heat pump air conditioner control, and discloses a heat pump air conditioner energy-saving monitoring method and system. The method comprises the following steps: dividing an evaporator into multiple heat exchange units, constructing a heat balance equation group of each heat exchange unit, and forming a heat exchange segmentation model of the evaporator; obtaining current inlet parameters, current pipe wall heat exchange boundaries and wall temperature measurement values of the evaporator, inputting the parameters into the heat exchange segmentation model, and determining wall temperature prediction values; updating heat transfer correction coefficients of each heat exchange unit, and determining a target model; calculating a current two-phase region proportion through the target model, determining an adjustment range based on deviation from a preset optimal two-phase region proportion, taking the preset optimal two-phase region proportion as a control target, traversing each adjustment amount in the adjustment range, and selecting an adjustment amount with the minimum preset cost function value as an optimal adjustment amount; and respectively issuing the optimal adjustment amount to a compressor and an expansion valve. The application takes the two-phase region proportion as a regulation and control target, and effectively improves the energy efficiency upper limit of the heat pump air conditioner.

Description

Technical Field

[0001] This application relates to the field of heat pump air conditioning control technology, specifically to an energy-saving monitoring method and system for heat pump air conditioning. Background Technology

[0002] With the widespread application of variable frequency heat pump air conditioners, improving system energy efficiency has become a core direction for technological research and development in the industry. As the core heat exchange component of a heat pump system, the evaporator's heat exchange efficiency directly determines the overall energy efficiency level of the unit. Currently, the commonly used control scheme in the industry focuses on the superheat at the evaporator outlet as the core control target. By adjusting the opening of the electronic expansion valve, the superheat is maintained within a preset range, thereby ensuring the evaporator's heat exchange safety and basic operating efficiency.

[0003] However, the above control scheme is essentially still a passive response control based on a single-point parameter, and there are still obvious energy efficiency bottlenecks in practical applications. On the one hand, superheat is only a single-point state parameter at the evaporator outlet, which cannot reflect the phase distribution and heat exchange utilization of the refrigerant along the process. In actual operation, there are often problems such as the superheat meeting the standard, but the length of the two-phase heat exchange section being too short and a large amount of heat exchange area being occupied by the superheat section. The utilization rate of the evaporator heat exchange area is insufficient, and the potential for energy efficiency improvement is limited. On the other hand, existing heat exchange simulation models are mostly built based on ideal operating conditions and factory calibration parameters, without taking into account the heat exchange capacity decay caused by dust accumulation, frost formation, and component aging during long-term operation. The accuracy of the model gradually decreases with the running time, making it difficult to achieve high-precision dynamic control on existing hardware platforms. Summary of the Invention

[0004] The present invention aims to provide an energy-saving monitoring method and system for heat pump air conditioners, which solves the problems of insufficient evaporator heat exchange control accuracy and the decrease in accuracy of heat exchange simulation models with operation in the prior art.

[0005] In a first aspect, embodiments of the present invention provide an energy-saving monitoring method for a heat pump air conditioner, applied to a heat pump air conditioner, the heat pump air conditioner including at least an evaporator, a compressor, and an expansion valve, the method comprising: Obtain the structural parameters, refrigerant type, and refrigerant mass flow rate of the evaporator; The evaporator is divided into multiple heat exchange units. Based on the structural parameters, refrigerant type and refrigerant mass flow rate, a set of heat balance equations for each heat exchange unit is constructed to form a heat exchange segment model of the evaporator. The set of heat balance equations includes the heat transfer correction coefficients corresponding to each heat exchange unit. The inlet parameters and heat transfer boundary of the evaporator are obtained, and the inlet parameters and heat transfer boundary of the tube wall are input into the heat transfer segment model to obtain the predicted wall temperature value of each temperature measuring point in the evaporator. The wall temperature measurement values ​​at each temperature measuring point in the evaporator are obtained. With the goal of reducing the deviation between the measured wall temperature values ​​and the predicted wall temperature values, the heat transfer correction coefficients of each heat exchange unit are updated to correct the heat exchange segment model and obtain the target model. The inlet parameters and the heat exchange boundary of the pipe wall are input into the target model to obtain the current two-phase region ratio. Combined with the preset optimal two-phase region ratio, the adjustment range of compressor frequency and expansion valve opening is determined. Using the optimal two-phase region ratio as the control target, the predicted two-phase region ratio corresponding to each adjustment amount is determined through the target model. The adjustment amount that minimizes the cost value of the preset cost function is selected as the optimal adjustment amount. The cost function consists of a deviation term and a penalty term. The deviation term is used to characterize the deviation of the predicted two-phase region ratio from the optimal two-phase region ratio. The deviation term is set with different weight coefficients for positive and negative deviations. The optimal adjustment amount is issued to the compressor and the expansion valve respectively.

[0006] In conjunction with the first aspect, in one possible implementation, the evaporator is divided into multiple heat exchange units along the refrigerant flow direction, and a set of heat balance equations for each heat exchange unit is constructed based on the structural parameters, refrigerant type, and refrigerant mass flow rate, including: The total tube length and inner diameter of the evaporator are determined based on the structural parameters. Based on the total pipe length, the evaporator is divided into multiple heat exchange units of equal length according to the preset unit length. Given the refrigerant type, refrigerant mass flow rate, and pipe inner diameter, and with the refrigerant pressure and enthalpy as unknowns, a set of heat balance equations is constructed for each heat exchange unit. The set of heat balance equations includes a mass balance equation, an energy balance equation, and a pressure drop equation. The heat transfer in the energy balance equation is determined by the refrigerant-side heat transfer coefficient of the corresponding heat exchange unit, and the heat transfer correction coefficient is applied to the refrigerant-side heat transfer coefficient.

[0007] In conjunction with the first aspect, in one possible implementation, after constructing the mass balance equations, energy balance equations, and pressure drop equations for each heat exchange unit as the heat balance equation set, the following is also included: Based on the preset heat transfer coefficient benchmark value, the heat balance equations of each heat exchange unit are solved simultaneously to determine the refrigerant phase state and current heat flux density of each heat exchange unit. The refrigerant phase state includes two-phase state and single-phase state. The heat transfer coefficient reference value is updated according to the refrigerant phase state within the heat exchange unit. Specifically, for a heat exchange unit in a two-phase state, the heat transfer coefficient reference value is updated based on the current heat flux density, refrigerant mass flow rate, and pipe inner diameter. For a heat exchange unit in a single-phase state, the heat transfer coefficient reference value is updated based on the refrigerant mass flow rate, pipe inner diameter, and refrigerant physical property parameters, wherein the refrigerant physical property parameters are determined by the refrigerant type. The heat balance equations are iteratively solved based on the updated heat transfer coefficient benchmark value until the change in heat flux density obtained in two adjacent solutions is less than the preset convergence threshold, thus obtaining the converged heat balance equations for each heat exchange unit.

[0008] In conjunction with the first aspect, in one possible implementation, obtaining the current inlet parameters of the evaporator and the current tube wall heat transfer boundary includes: Obtain the current inlet pressure and inlet enthalpy of the evaporator, and use the current inlet pressure and inlet enthalpy as the inlet parameters; The current ambient temperature and air-side convective heat transfer coefficient of the evaporator are obtained, and the ambient temperature and air-side convective heat transfer coefficient are used as the heat transfer boundary of the tube wall.

[0009] In conjunction with the first aspect, in one possible implementation, the heat transfer segmentation model outputs the initial two-phase region ratio while outputting the predicted wall temperature value. The initial two-phase region ratio is used to characterize the phase constraint boundary when correcting the heat transfer segmentation model. The step of inputting the inlet parameters and the heat transfer boundary of the pipe wall into the heat transfer segment model to obtain the predicted wall temperature values ​​of each temperature measuring point in the evaporator includes: The inlet parameters are used as the inlet boundary conditions of the first heat exchange unit, and the pipe wall heat exchange boundary is used as the outer boundary conditions of each heat exchange unit. The heat balance equations of each heat exchange unit are solved sequentially along the refrigerant flow direction to determine the refrigerant enthalpy and pressure at the outlet of each heat exchange unit. The refrigerant enthalpy of each heat exchange unit is compared with the saturated vapor enthalpy at the corresponding outlet pressure to determine the phase state of the corresponding heat exchange unit and calculate the total length of the two-phase pipe section. When all heat exchange units are in a two-phase state at the outlet, the total length of the two-phase pipe section is equal to the total pipe length; when all heat exchange units are in a superheated state, the total length of the two-phase pipe section is zero. The ratio of the total length of the two-phase tube section to the total length of the evaporator tube is determined as the initial two-phase zone proportion. The calculated wall temperature at the corresponding pipe wall location is determined based on the solution results of each heat exchange unit, and the predicted wall temperature at each temperature measurement point is determined by location interpolation.

[0010] In conjunction with the first aspect, in one possible implementation, updating the heat transfer correction coefficient of each heat exchange unit with the goal of reducing the deviation between the measured wall temperature and the predicted wall temperature includes: The deviation between the predicted wall temperature value and the corresponding measured wall temperature value at each temperature measurement point is determined, and a comprehensive deviation is constructed. The comprehensive deviation is the root mean square value or weighted average value of the deviations at each temperature measurement point. When the overall deviation is greater than the preset deviation threshold, the distance between each heat exchange unit and the nearest temperature measuring point is determined according to the axial position of each heat exchange unit and the installation position of each temperature measuring point. The correction magnitude weight is determined according to the distance, and the distance is negatively correlated with the correction magnitude weight. The adjustment direction of the heat transfer correction coefficient is determined based on the relationship between the predicted wall temperature and the measured wall temperature at the corresponding location of each heat exchange unit. The adjustment direction satisfies the following: when the predicted wall temperature is greater than the measured wall temperature, the heat transfer correction coefficient is decreased; when the predicted wall temperature is less than the measured wall temperature, the heat transfer correction coefficient is increased. The basic adjustment step size is determined based on the magnitude of the comprehensive deviation. The actual adjustment amount of each heat exchange unit is determined based on the adjustment direction, the basic adjustment step size, and the correction magnitude weight, so as to update the heat transfer correction coefficient of each heat exchange unit. The updated heat transfer correction coefficient is substituted into the heat transfer segment model, and the predicted wall temperature and the comprehensive deviation are iteratively calculated until the comprehensive deviation is not greater than the preset deviation threshold, thus obtaining the target model.

[0011] In conjunction with the first aspect, in one possible implementation, determining the adjustment range of the compressor and the expansion valve based on the deviation between the current two-phase region ratio and the preset optimal two-phase region ratio includes: The deviation value is calculated by subtracting the preset optimal two-phase region ratio from the current two-phase region ratio. When the absolute value of the deviation is not less than the preset dead zone threshold, the adjustment direction is determined according to the sign of the deviation value. When the deviation value is positive, the adjustment direction is to reduce the opening of the expansion valve and reduce the compressor frequency. When the deviation value is negative, the adjustment direction is to increase the opening of the expansion valve and increase the compressor frequency. Based on the absolute value of the deviation, the adjustment range of the compressor frequency and the expansion valve opening is determined, and the adjustment range is positively correlated with the magnitude of the absolute value. Based on the adjustment direction and the adjustment range, the adjustment range of the compressor frequency and the expansion valve opening are determined respectively.

[0012] In conjunction with the first aspect, in one possible implementation, in the deviation term of the preset cost function, the first weighting coefficient corresponding to the positive deviation is greater than the second weighting coefficient corresponding to the negative deviation; The preset cost function also includes a penalty term, which includes a frequency change penalty component and an opening change penalty component. The penalty coefficient corresponding to the frequency change penalty component is greater than that of the opening change penalty component.

[0013] In conjunction with the first aspect, in one possible implementation, selecting the adjustment amount that minimizes the cost of the preset cost function as the optimal adjustment amount includes: The combination of adjustment amounts within the adjustment range is traversed at a preset first interval. Based on the cost function, the cost value corresponding to each combination of adjustment amounts is calculated sequentially, and the combination of adjustment amounts with the smallest cost value is determined as the candidate adjustment amount. Within the vicinity of the candidate adjustment amount, the combination of adjustment amounts within the vicinity is traversed at a preset second interval, and the cost value corresponding to each combination of adjustment amounts is calculated sequentially. The combination of adjustment amounts with the smallest cost value is determined as the optimal adjustment amount. The preset second interval is smaller than the preset first interval. The vicinity is centered on the candidate adjustment amount and increases or decreases by at least one preset first interval along the compressor frequency and the expansion valve opening, respectively.

[0014] In a second aspect, embodiments of the present invention also propose an energy-saving monitoring system for heat pump air conditioners, applied to heat pump air conditioners, wherein the heat pump air conditioner includes at least an evaporator, a compressor, and an expansion valve, and the system includes: The data acquisition module is configured to acquire the structural parameters, refrigerant type, and refrigerant mass flow rate of the evaporator. The model building module is configured to divide the evaporator into multiple heat exchange units, and construct a set of heat balance equations for each heat exchange unit based on the structural parameters, refrigerant type and refrigerant mass flow rate, forming a heat exchange segment model of the evaporator. The set of heat balance equations includes the heat transfer correction coefficients corresponding to each heat exchange unit. The model solving module is configured to obtain the inlet parameters and heat transfer boundary of the evaporator, input the inlet parameters and heat transfer boundary of the tube wall into the heat transfer segment model, and obtain the predicted wall temperature value of each temperature measuring point in the evaporator. The model correction module is configured to acquire the wall temperature measurement values ​​at each temperature measuring point in the evaporator, update the heat transfer correction coefficient of each heat exchange unit with the goal of reducing the deviation between the wall temperature measurement value and the predicted wall temperature value, and correct the heat exchange segment model to obtain the target model; input the inlet parameters and the tube wall heat exchange boundary into the target model to obtain the current two-phase region ratio, and determine the adjustment range of compressor frequency and expansion valve opening by combining the preset optimal two-phase region ratio; The adjustment optimization module is configured to take the optimal two-phase region ratio as the control target, determine the predicted two-phase region ratio corresponding to each adjustment amount through the target model, and select the adjustment amount that minimizes the cost value of the preset cost function as the optimal adjustment amount. The cost function consists of a deviation term and a penalty term. The deviation term is used to characterize the deviation of the predicted two-phase region ratio from the optimal two-phase region ratio. The deviation term is set with different weight coefficients for positive and negative deviations respectively. The instruction issuing module is configured to issue the optimal adjustment amount to the compressor and the expansion valve respectively.

[0015] This application can achieve the following technical effects: Traditional superheat control can only ensure that there are no liquid droplets at the evaporator outlet, but it cannot constrain the actual length of the two-phase heat exchange section. In actual operation, this often results in situations where the superheat is within acceptable limits but the proportion of the two-phase section is too low, and a large amount of heat exchange area is occupied by the single-phase superheat section. This invention takes the proportion of the two-phase region as the core control target and maximizes the utilization of the heat exchange area as the optimization direction, fully exploring the heat exchange potential of the evaporator and effectively improving the upper limit of the system's energy efficiency.

[0016] Furthermore, this application breaks down the evaporator into multiple heat exchange units and solves them sequentially to accurately reproduce the phase evolution and heat transfer law of the refrigerant along the process. At the same time, it uses the deviation between the measured wall temperature and the model prediction to iteratively correct the heat transfer coefficient of each unit, offsetting the drift in heat transfer capacity caused by equipment deterioration. This ensures that the model always fits the actual operating conditions and can maintain high calculation accuracy even under long-term operation, providing a reliable model basis for continuous energy-saving optimization. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating an energy-saving monitoring method for heat pump air conditioners according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of an energy-saving monitoring system for heat pump air conditioning according to an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without inventive effort are within the scope of protection of this invention.

[0020] It should be noted that, unless otherwise specified, the various features in the embodiments of this invention can be combined with each other, all of which are within the protection scope of this invention. Furthermore, although functional modules are divided in some schematic diagrams and logical order is shown in some flowcharts, in certain situations, the steps shown or described can be executed in a different order than the module divisions in the schematic diagrams or the order in the flowcharts. Moreover, the terms "first," "second," and "third" used in this invention do not limit the data or execution order, but only distinguish identical or similar items with essentially the same function and effect.

[0021] This embodiment provides an energy-saving monitoring method for heat pump air conditioners, which is applied to heat pump air conditioners. Specifically, it can be applied to the outdoor unit main controller of a variable frequency air source heat pump air conditioner. The main controller can be an embedded control board based on the ARM Cortex-M series core, or it can be a dedicated heat pump main control module with integrated computing power, on which an evaporator heat exchange optimization function module runs.

[0022] Based on this understanding, the main controller can be connected to the compressor drive board, electronic expansion valve drive circuit, and various sensors via wired or wireless communication. These sensors include, but are not limited to, wall temperature sensors, pressure sensors, temperature and humidity sensors, fan speed detection units, and other detection devices capable of collecting operating parameters.

[0023] Please refer to Figure 1 The energy-saving monitoring method for heat pump air conditioners provided in this embodiment includes steps S10-S70: Step S10: Obtain the structural parameters, refrigerant type, and refrigerant mass flow rate of the evaporator; This embodiment uses the above-mentioned main controller as an example for explanation. During the system power-on initialization phase, the controller can load the inherent structural parameters of the evaporator from the non-volatile storage unit of the heat pump air conditioner at one time, such as the length of the heat exchange main pipe, the inner diameter of the copper pipe, the fin spacing, the fin thickness, the total heat exchange area, the number of pipe rows, etc., as the calculation basis for subsequent model construction.

[0024] The refrigerant type can be the type of refrigerant that was charged into the system at the factory. It serves as a retrieval index for the refrigerant property database, which can use pressure and enthalpy interpolation to characterize a complete set of thermodynamic properties such as saturation temperature, saturation enthalpy, density, viscosity, and thermal conductivity under the corresponding conditions.

[0025] In this embodiment, the refrigerant mass flow rate is a core operating parameter characterizing the refrigerant circulation rate of the system. It can be indirectly calculated using the volumetric method. For example, the calculation formula is as follows: ; in, This is the refrigerant mass flow rate, expressed in kg / s. This refers to the real-time operating frequency of the compressor, measured in Hz. The theoretical exhaust volume of the compressor (working volume of a single cylinder multiplied by the number of cylinders), in m³ / r; To find the compressor volumetric efficiency under the corresponding operating conditions, you can use the two-dimensional characteristic MAP table pre-stored in the heat pump air conditioner. The input dimensions are the compressor operating frequency and the system high-low pressure ratio. Different operating conditions correspond to different efficiency values. This is the density of the refrigerant in the suction state, expressed in kg / m³, and can be determined by interpolation from the suction pressure, suction temperature, and refrigerant property table.

[0026] The above calculation process of refrigerant mass flow rate does not require the installation of a dedicated flow sensor in the pipeline. It can be achieved using only the original factory calibration parameters of the system. Generally speaking, the mass flow rate is updated in real time according to the compressor's operating status and is refreshed once per control cycle.

[0027] Step S20: Divide the evaporator into multiple heat exchange units, and construct a set of heat balance equations for each heat exchange unit based on the structural parameters, refrigerant type and refrigerant mass flow rate to form a segmented heat exchange model of the evaporator. The set of heat balance equations includes the heat transfer correction coefficients corresponding to each heat exchange unit.

[0028] In this embodiment, the controller divides the entire heat exchange pipeline in the evaporator into multiple continuous heat exchange units of equal length along the flow direction of the refrigerant in the evaporator.

[0029] Those skilled in the art will understand that as the refrigerant gradually absorbs heat from the gas-liquid two-phase state at the inlet to the superheated state at the outlet within the evaporator, its thermodynamic state and heat transfer mechanism differ significantly along the pipe. Therefore, if a lumped parameter model is used to describe the heat transfer state of the entire pipe using a single average parameter, it cannot reflect this distribution characteristic along the pipe, and the calculation error is large. Therefore, in this embodiment, the entire pipe is divided into sufficiently short heat transfer units, so that the refrigerant properties and heat transfer intensity in each unit can be approximated as uniformly distributed. Then, the distribution of the pipe's state along the pipe can be determined by recursively solving unit by unit, taking into account both the calculation accuracy and the computing power feasibility of embedded devices.

[0030] The selection of unit length can follow the principle of balancing accuracy and computing power. The shorter the unit, the higher the calculation accuracy, but the greater the amount of computation. The specific value is reasonably set in combination with the computing power of the controller and the control cycle duration. In this embodiment, 1 / 10 to 1 / 15 of the total pipe length is taken as the unit length.

[0031] It is necessary to explain that the heat exchange segment model in this embodiment is essentially a one-dimensional distributed parameter simulation model of the evaporator based on spatial discretization. Its core is to divide the evaporator heat exchange pipeline that changes continuously along the pipeline into multiple relatively independent lumped parameter calculation units. Each unit assumes that the parameters are uniformly distributed. The heat exchange and flow process in each heat exchange unit is described by a set of heat balance equations. Finally, the distributed parameters of the entire pipeline are solved by the state recursion between units. Thus, under the limited computing power of the embedded controller, the phase evolution and heat exchange characteristics of the refrigerant along the pipeline in the evaporator are accurately reproduced.

[0032] Specifically, the heat balance equation set includes a mass balance equation, an energy balance equation, and a pressure drop equation. The heat transfer in the energy balance equation is determined by the refrigerant-side heat transfer coefficient of the corresponding heat exchange unit. The heat transfer correction coefficient acts on the refrigerant-side heat transfer coefficient, and its specific form is as follows: The mass balance equation satisfies: ; In the formula, This refers to the refrigerant mass flow rate at the unit inlet. The refrigerant mass flow rate at the unit outlet is given. Under steady-state conditions, there is no refrigerant mass accumulation in each heat exchange unit, and the inlet and outlet mass flow rates are equal. The energy balance equation satisfies: ; In the formula, This is the refrigerant mass flow rate. , These are the specific enthalpy of the refrigerant at the inlet and outlet of the heat exchange unit, respectively. The total heat transfer coefficient is based on the total heat exchange area outside the tube. The total heat exchange area outside the tube (including fins) The logarithmic mean temperature difference is calculated as follows: in the two-phase region, it is calculated from the difference between the air-side temperature and the refrigerant saturation temperature; in the single-phase region, it is calculated from the inlet and outlet temperatures of the refrigerant and air sides using the logarithmic mean temperature difference formula.

[0033] The pressure drop equation satisfies: ; In the formula, , These are the inlet and outlet refrigerant pressures of the unit, respectively, in Pa. This is the loss due to frictional resistance along the path. It is the sum of local drag loss and acceleration pressure drop.

[0034] Overall heat transfer coefficient It is obtained by superimposing three layers of thermal resistance, and each thermal resistance is converted to the reference of the total heat transfer area outside the tube, satisfying: ; In the formula, This is the reference value for the heat transfer coefficient on the refrigerant side. This is the heat transfer correction factor corresponding to this heat exchange unit. The heat exchange area inside the pipe. For copper tubes with thick walls, The thermal conductivity of the copper tube is... The logarithmic mean area of ​​the pipe wall. The air-side convective heat transfer coefficient is... For fin efficiency.

[0035] Based on the aforementioned structural parameters of the evaporator, refrigerant type, and refrigerant mass flow rate, a set of heat balance equations for each heat exchange unit can be constructed. The set of heat balance equations for each heat exchange unit together constitutes the heat exchange segment model of the evaporator. Each heat exchange unit corresponds to an independent heat transfer correction coefficient, and all heat transfer correction coefficients are arranged in unit order to form a one-dimensional floating-point array.

[0036] It is worth noting that the degree of deterioration often varies at different locations of the heat exchanger. For example, dust accumulation is more severe on the windward side and frost is more likely to form in the lower area. Therefore, in this embodiment, each heat exchange unit corresponds to an independent heat transfer correction coefficient to accurately match the non-uniform operating condition drift along the process, offset the model error caused by slowly changing factors such as equipment aging, dust accumulation and frost, and uneven airflow distribution, so that the model can continuously match the actual heat exchange capacity of the heat exchanger.

[0037] In this embodiment, the model solution process adopts a unit-by-unit recursive approach. Specifically, the inlet parameters can be used as the inlet boundary conditions of the first heat exchange unit to solve and determine the outlet state of the unit. Then, the outlet state is used as the inlet boundary conditions of the next heat exchange unit, and so on, advancing segment by segment along the flow direction until all units are solved and the distribution of the pipe's friction state is determined.

[0038] Step S30: Obtain the inlet parameters and heat transfer boundary of the evaporator, input the inlet parameters and heat transfer boundary of the tube wall into the heat transfer segment model, and obtain the predicted wall temperature value of each temperature measuring point in the evaporator.

[0039] In this step, the real-time inlet parameters of the evaporator and the heat transfer boundary of the tube wall are collected by the controller and used as input conditions for the heat transfer segment model. The tube wall temperature distribution along the evaporator is obtained by solving the model, and the predicted wall temperature value corresponding to each temperature measurement point is obtained by position mapping. The predicted wall temperature value is used as the benchmark for comparison with the measured wall temperature value in the subsequent model correction step.

[0040] Specifically, the tube wall temperature of each heat exchange unit can be calculated through a series thermal resistance network. Under steady-state heat transfer conditions, the heat flux density through the tube wall is equal everywhere, so the tube wall temperature can be estimated from either the refrigerant side or the air side.

[0041] The formula for calculating the pipe wall temperature from the refrigerant side is: ; ; in, The temperature of the refrigerant in the heat exchange unit (the saturation temperature at the corresponding pressure is taken in the two-phase region, and the average temperature of the inlet and outlet is taken in the single-phase region). This is the heat flux density of the heat exchange unit (i.e., the ratio of heat exchange capacity to heat exchange area). This is the reference value for the heat transfer coefficient on the refrigerant side. This is the heat transfer correction factor for this unit. For copper tubes with thick walls, The thermal conductivity of the copper tube is... For ambient temperature, The air-side convective heat transfer coefficient is... For fin efficiency.

[0042] The process of obtaining the inlet parameters and tube wall heat transfer boundary of the evaporator includes: Obtain the inlet pressure and inlet enthalpy of the evaporator, and use the current inlet pressure and inlet enthalpy as the inlet parameters; obtain the current ambient temperature and air-side convective heat transfer coefficient of the evaporator, and use the ambient temperature and air-side convective heat transfer coefficient as the tube wall heat transfer boundary.

[0043] It is easy to understand that when the evaporator inlet is in a gas-liquid two-phase state, pressure and temperature are not independent parameters. They correspond one-to-one in the saturation region. Therefore, the dryness and thermodynamic state of the refrigerant cannot be uniquely determined by pressure and temperature alone. However, pressure and enthalpy are two independent state parameters. Regardless of whether the inlet is in a two-phase state or a subcooled state, the refrigerant state at the inlet can be uniquely determined, thus ensuring the determinism of the model inlet boundary.

[0044] Meanwhile, the heat transfer process between the outer side of the evaporator tube wall and the ambient air is a convective heat transfer process. The ambient temperature determines the driving temperature difference for heat transfer, and the air-side convective heat transfer coefficient determines the air-side heat transfer resistance. Together, they constitute the tube wall heat transfer boundary.

[0045] More specifically, assuming the evaporator main tube is 10m long and has an inner diameter of 8mm, it is divided into 10 heat exchange units of equal length along the flow direction. Four temperature measuring points are arranged on the tube wall at distances of 2.5m, 5.0m, 7.5m, and 10.0m from the inlet. The current inlet pressure of the evaporator is obtained as 0.8MPa by a pressure sensor. The current inlet enthalpy is determined to be 250kJ / kg by combining the enthalpy value of the subcooled liquid before the expansion valve with the isoenthalpy characteristics of the throttling process. These two values ​​are used as the inlet parameters.

[0046] Meanwhile, assuming the current ambient temperature is 7°C as measured by an ambient temperature sensor, and after calculating the oncoming wind speed based on the fan speed, the air-side convective heat transfer coefficient is obtained by combining the evaporator fin structure parameters and using a cross-tube bundle convective heat transfer correlation formula (other correlation formulas may be used by those skilled in the art, and this embodiment does not limit this). The result is 50 W / (m²). K), using ambient temperature and air-side convective heat transfer coefficient as the heat transfer boundary of the pipe wall.

[0047] An inlet pressure of 0.8 MPa and an inlet enthalpy of 250 kJ / kg were used as the inlet boundary conditions for the first heat exchange unit. An ambient temperature of 7℃ and an air-side convective heat transfer coefficient of 50 W / (m²) were also used. K) is used as the outer boundary condition for all heat exchange units. The heat balance equations of each heat exchange unit are solved sequentially along the refrigerant flow direction.

[0048] The solution for Unit 1 yields an outlet enthalpy of 265 kJ / kg and an outlet pressure of 0.795 MPa, which are used as the inlet boundary conditions for Unit 2. This process is repeated for each unit until Unit 10, resulting in the calculated outlet conditions and pipe wall temperatures for all units.

[0049] For example, after solving, the predicted wall temperatures at the center of each heat exchange unit are approximately 5.8℃, 5.6℃, 5.4℃, 5.2℃, 5.0℃, 4.8℃, 4.6℃, 4.4℃, 4.2℃, and 4.0℃, respectively.

[0050] Since the installation location of the temperature measuring point may not completely coincide with the boundary of the heat exchange unit, the predicted wall temperature of each unit can be mapped to the actual installation location of the temperature measuring point through position interpolation. In this embodiment, assuming that the temperature measuring point at 2.5m corresponds exactly to the center of the 3rd heat exchange unit, the calculated wall temperature of that unit, 5.4℃, can be directly taken as the predicted wall temperature value of that measuring point; the temperature measuring point at 5.0m corresponds to the center of the 5th unit, and the predicted wall temperature value is 5.0℃; the temperature measuring point at 7.5m corresponds to the center of the 7th unit, and the predicted wall temperature value is 4.6℃; the temperature measuring point at 10.0m corresponds to the center of the 10th unit, and the predicted wall temperature value is 4.0℃. If the temperature measuring point is located between two heat exchange units, the predicted wall temperature value at the corresponding location can be calculated using linear interpolation, which will not be elaborated on in this embodiment.

[0051] Step S40: Obtain the wall temperature measurement values ​​at each temperature measuring point in the evaporator. With the goal of reducing the deviation between the wall temperature measurement values ​​and the predicted wall temperature values, update the heat transfer correction coefficient of each heat exchange unit to correct the heat exchange segment model and obtain the target model.

[0052] In this embodiment, the controller compares the real-time wall temperature measurement with the predicted wall temperature output by the heat exchange segment model. Taking the reduction of the deviation between the two as the optimization objective, the heat transfer correction coefficients corresponding to each heat exchange unit are iteratively updated. After each round of updating the heat transfer correction coefficients, the updated heat transfer correction coefficients are substituted back into the heat exchange segment model, and the model is solved again with the same inlet parameters and the tube wall heat exchange boundary to obtain a new round of predicted wall temperature values. The deviation between the predicted wall temperature and the measured wall temperature is then recalculated.

[0053] The above process is repeated until the deviation meets the preset accuracy requirements. At this point, the corrected heat exchange segment model is the target model. Thus, the heat exchange segment model can continuously offset the drift in heat exchange capacity caused by slow-changing factors such as dust accumulation, frost formation, and component aging, so that the model calculation results always fit the actual operating state of the evaporator.

[0054] Specifically, with the goal of reducing the deviation between the measured wall temperature and the predicted wall temperature, the heat transfer correction coefficient of each heat exchange unit is updated, including: The deviation between the predicted wall temperature and the corresponding measured wall temperature at each temperature measurement point is determined to construct a comprehensive deviation, which is the root mean square value or weighted average of the deviations at each temperature measurement point. When the comprehensive deviation exceeds a preset deviation threshold, the distance between each heat exchange unit and the nearest temperature measurement point is determined based on the axial position of each heat exchange unit and the installation position of each temperature measurement point. A correction magnitude weight is determined based on this distance, and the distance is negatively correlated with the correction magnitude weight. The adjustment direction of the heat transfer correction coefficient is determined based on the relationship between the predicted and measured wall temperature values ​​at the corresponding positions of each heat exchange unit. The following steps are taken: when the predicted wall temperature is greater than the measured wall temperature, the heat transfer correction coefficient is decreased; when the predicted wall temperature is less than the measured wall temperature, the heat transfer correction coefficient is increased. A basic adjustment step size is determined based on the magnitude of the overall deviation. The actual adjustment amount for each heat exchange unit is determined based on the adjustment direction, the basic adjustment step size, and the correction magnitude weight, to update the heat transfer correction coefficient of each heat exchange unit. The updated heat transfer correction coefficient is substituted into the heat exchange segmentation model, and the predicted wall temperature and the overall deviation are iteratively calculated until the overall deviation is not greater than a preset deviation threshold, thus obtaining the target model.

[0055] In this embodiment, the controller calculates the deviation between the predicted and measured wall temperature values ​​at each measuring point, summarizes and determines the overall comprehensive deviation, and updates the heat transfer correction coefficient with the goal of reducing the comprehensive deviation.

[0056] The overall deviation can be calculated using the root mean square value, and the formula is as follows: ; Where n is the total number of temperature measurement points, Let i be the predicted wall temperature value at the i-th measuring point. The measured value of the wall temperature at the i-th measuring point.

[0057] The correction coefficient can be iterated using a proportional adjustment method, and the formula for calculating the correction amount in a single round is as follows: ; In the formula, The single-round adjustment amount for the correction coefficient of the j-th unit; The step size coefficient is adjusted based on the overall deviation, and can be adaptively selected according to the magnitude of the deviation; the larger the deviation, the larger the step size. The wall temperature deviation at the corresponding position of the j-th unit is the difference between the predicted value and the measured value. If the deviation is positive, the correction factor is increased; if the deviation is negative, the correction factor is decreased. Let be the correction magnitude weight for the j-th unit. This weight is negatively correlated with the distance from the unit to the nearest temperature measurement point, and its calculation formula is: ; In the formula, Let be the distance from the center of the j-th unit to the nearest temperature measurement point. The reference distance constant is used to avoid infinite weight when the distance is zero. The closer the heat exchange unit is to the nearest temperature measurement point, the higher the weight and the larger the correction range. Conversely, the farther the heat exchange unit is from the measurement point, the lower the weight and the smaller the correction range, so as to ensure the spatial rationality of the correction process.

[0058] In this embodiment, after each round of correction coefficient adjustment, the updated coefficients are substituted back into the heat exchange segment model, and the predicted wall temperature and the overall deviation are recalculated. The deviation is gradually reduced through multiple rounds of iteration until the overall deviation meets the accuracy requirements or reaches the preset maximum number of iterations (10 times in this embodiment).

[0059] Taking the evaporator of an air source heat pump air conditioner as an example, assuming that the total length of the evaporator pipe is 10m and the inner diameter of the pipe is 8mm, it is divided into 10 heat exchange units of equal length along the refrigerant flow direction. Each heat exchange unit is 1m long, and the central axial positions of each heat exchange unit are 0.5m, 1.5m, 2.5m, ..., 9.5m respectively. Assume that there are four wall temperature measuring points arranged along the refrigerant flow direction on the evaporator tube wall, with installation positions of 2.5m, 5.0m, 7.5m, and 10.0m from the inlet, respectively. The initial value of the heat transfer correction coefficient of each heat exchange unit is 1.0, and the preset deviation threshold is set to 0.5℃. Under a certain operating condition, the inlet parameters and the tube wall heat exchange boundary are input into the heat exchange segment model. After solving unit by unit and interpolating the positions, the predicted wall temperature values ​​of the four measuring points are obtained, which are 6.0℃, 5.5℃, 5.0℃, and 4.5℃, respectively. Simultaneously, the wall temperature measurements at corresponding locations were collected by the wall temperature sensor, which were 5.0℃, 4.8℃, 4.5℃, and 4.2℃, respectively. The deviation between the predicted wall temperature and the measured wall temperature at each measurement point was calculated, resulting in a deviation sequence of +1.0℃, +0.7℃, +0.5℃, and +0.3℃. The root mean square value was used to construct the comprehensive deviation, which was calculated to be approximately 0.676℃. This comprehensive deviation is greater than the preset deviation threshold of 0.5℃. At this point, the controller calculates the axial distance from each heat exchange unit to the nearest measurement point based on the central axial position of each heat exchange unit and the installation position of each measurement point.

[0060] Taking the first heat exchange unit (center position 0.5m) as an example, its distances to the four temperature measuring points are 2.0m, 4.5m, 7.0m, and 9.5m, respectively. The minimum value of 2.0m is taken as the distance from this unit to the nearest temperature measuring point. Similarly, the nearest distances of all 10 heat exchange units can be obtained, which are 2.0m, 1.0m, 0m, 1.0m, 0m, 1.0m, 0m, 1.0m, 0m, and 0.5m, respectively.

[0061] The correction magnitude weight for each heat exchange unit is determined based on the distance. The distance and correction magnitude weight are negatively correlated. The calculated correction magnitude weights for the 10 heat exchange units are 0.333, 0.5, 1.0, 0.5, 1.0, 0.5, 1.0, 0.5, 1.0, and 0.667, respectively. Simultaneously, the controller determines the adjustment direction of the heat transfer correction coefficient based on the relationship between the predicted and measured wall temperatures at the corresponding locations of each heat exchange unit.

[0062] In this embodiment, the predicted wall temperature values ​​at all temperature measurement points are greater than the measured wall temperature values, indicating that the model as a whole overestimates the heat exchange capacity of the evaporator. Therefore, the adjustment direction of the heat transfer correction coefficient for each heat exchange unit is to decrease. If the predicted wall temperature value at a certain location of a heat exchange unit is less than the measured wall temperature value, the adjustment direction for that unit is to increase, thus achieving independent direction determination for each unit. After determining the correction magnitude weight and adjustment direction, the controller determines the basic adjustment step size based on the magnitude of the overall deviation; the larger the overall deviation, the larger the basic adjustment step size.

[0063] After determining the correction magnitude weight and adjustment direction, the controller determines the basic adjustment step size based on the magnitude of the overall deviation; the larger the overall deviation, the larger the basic adjustment step size. In this embodiment, a piecewise linear mapping is used to determine the basic adjustment step size. For example, when the overall deviation is in the range of 0.5℃ to 1.0℃, the basic adjustment step size is determined by linear interpolation from 0.03 to 0.07; when the overall deviation is in the range of 1.0℃ to 2.0℃, the basic adjustment step size is determined by linear interpolation from 0.07 to 0.10; and when the overall deviation is greater than 2.0℃, the basic adjustment step size is clamped to 0.10.

[0064] In this embodiment, the overall deviation is 0.676℃, and the corresponding basic adjustment step size can be taken as 0.05. The actual adjustment amount of each heat exchange unit is calculated. Taking the first heat exchange unit as an example, its adjustment direction is decrease (negative sign), the basic adjustment step size is 0.05, and the correction magnitude weight is 0.333. Therefore, the actual adjustment amount is approximately -0.017. Similarly, the actual adjustment amounts of all 10 heat exchange units are -0.017, -0.025, -0.050, -0.025, -0.050, -0.025, -0.050, -0.025, -0.050, -0.050, and -0.033, respectively. Each actual adjustment is superimposed onto the current heat transfer correction coefficient to complete one update. After the update, the heat transfer correction coefficients of the 10 heat exchange units are 0.983, 0.975, 0.950, 0.975, 0.950, 0.975, 0.950, 0.975, 0.950, and 0.967, respectively.

[0065] This shows that the closer the heat transfer unit is to the temperature measurement point, the larger the correction range, and the farther the unit is from the measurement point, the smaller the correction range. After updating the heat transfer correction coefficient once, the updated heat transfer correction coefficient is substituted into the heat transfer segment model, and the model is resolved with the same inlet parameters and pipe wall heat transfer boundary to obtain a new predicted wall temperature value. The overall deviation is then recalculated.

[0066] If the overall deviation in the new round is still greater than the preset deviation threshold, the process of distance calculation, weight determination, direction determination, and adjustment calculation is repeated to continue updating the heat transfer correction coefficient until the overall deviation is no greater than the preset deviation threshold or the preset maximum number of iterations is reached. In this embodiment, the overall deviation after the second iteration drops to 0.35℃, which is less than the preset deviation threshold of 0.5℃, and the iteration is determined to be converged. The heat transfer segment model at this time is the target model.

[0067] Step S50: Input the inlet parameters and the heat exchange boundary of the pipe wall into the target model to obtain the current two-phase region ratio, and combine it with the preset optimal two-phase region ratio to determine the adjustment range of the compressor frequency and the expansion valve opening.

[0068] Specifically, in this embodiment, the outlet enthalpy of each unit in the entire pipe and the saturated steam enthalpy at the corresponding pressure are read through the calibrated target model. The phase state is determined by comparing each unit. When the outlet enthalpy of a unit is less than or equal to the saturated steam enthalpy, the unit is determined to be in the two-phase region. When the outlet enthalpy is greater than the saturated steam enthalpy, the unit is determined to be in the superheated region.

[0069] The boundary point between the two-phase region and the superheated region can be located using linear interpolation. This involves determining the boundary unit where the outlet enthalpy transitions from below to above the saturation enthalpy, and then calculating the relative position of the saturation point within that unit using the enthalpy difference ratio. The calculation formula is as follows: ; In the formula, The ratio of the length of the saturation point to the element inlet. For saturated vapor enthalpy, These are the inlet and outlet enthalpies of the boundary element, respectively. The ratio of the total length of the two-phase tubes to the total length of the evaporator tubes is the current two-phase zone ratio. The deviation value is calculated by aligning the current two-phase zone ratio with the preset optimal two-phase zone ratio. The value is the difference between the current two-phase zone ratio and the preset optimal two-phase zone ratio.

[0070] The preset optimal two-phase region ratio can be determined through offline calibration of bench tests. It corresponds to the two-phase region ratio when the system energy efficiency ratio is the highest under the current operating conditions. Different environmental conditions correspond to different calibration values, which are pre-stored in the controller in the form of a reference table. The typical value range under normal heating conditions is 70%~80%.

[0071] When the deviation value is positive, the current proportion of the two-phase region is higher than the optimal value, which means that the superheat is insufficient. The adjustment direction at this time is to reduce the opening of the expansion valve and reduce the compressor frequency. When the deviation value is negative, the current proportion of the two-phase region is lower than the optimal value, which means that the superheat is too large and the heat exchange area is not fully utilized. The adjustment direction at this time is to increase the opening of the expansion valve and increase the compressor frequency.

[0072] In this embodiment, the adjustment range can be determined based on the absolute value of the deviation. The larger the absolute value of the deviation, the larger the allowable adjustment range. Specifically, piecewise linear mapping can be used. For example, when the absolute value of the deviation is less than 5%, the frequency adjustment range is ±5Hz and the opening adjustment range is ±15 steps; when the deviation is between 5% and 10%, the frequency adjustment range is ±10Hz and the opening adjustment range is ±30 steps; when the deviation is greater than 10%, the frequency adjustment range is ±15Hz and the opening adjustment range is ±45 steps.

[0073] Along the aforementioned adjustment direction, starting from the current operating value, within the allowable operating range of the compressor and expansion valve (generally, the compressor frequency is 20-90Hz and the expansion valve opening is 0-480 steps), the adjustment range of the compressor frequency and expansion valve opening is defined respectively in combination with the adjustment amplitude.

[0074] Step S60: Taking the optimal two-phase region ratio as the control target, the predicted two-phase region ratio corresponding to each adjustment amount is determined through the target model. The adjustment amount that minimizes the cost value of the preset cost function is selected as the optimal adjustment amount. The cost function consists of a deviation term and a penalty term. The deviation term is used to characterize the deviation of the predicted two-phase region ratio from the optimal two-phase region ratio. The deviation term is set with different weight coefficients for positive and negative deviations.

[0075] In this embodiment, with the preset optimal two-phase region ratio as the control target, all parameter combinations of compressor frequency and expansion valve opening are traversed within the defined adjustment range. Each set of adjustment is substituted into the target model, and the corresponding predicted two-phase region ratio is calculated according to the same solution logic. Then, the preset cost function is substituted into the preset cost function to calculate the value of the preset cost function corresponding to the set of parameters.

[0076] As a feasible implementation method, the preset cost function consists of two parts: a two-phase region proportion deviation term and a regulation change penalty term. Its complete expression is: ; In the formula: The positive deviation in the proportion of the two-phase region (the portion where the actual proportion is greater than the optimal proportion) corresponds to the condition of insufficient superheat, with a weighting coefficient. The value is 1.8; The negative deviation in the proportion of the two-phase region (the portion where the actual proportion is less than the optimal proportion) corresponds to a condition with excessive superheat and wasted heat exchange area. The weighting coefficient is... The value is 1.0; The change in compressor frequency relative to the current operating value, weighted by a coefficient. The value is set to 0.5 / Hz, which is used to constrain the compressor's load variation rate; The change in expansion valve opening relative to the current operating value, weighted by a coefficient. The value is 0.1 / step, which is used to constrain the adjustment range of the expansion valve.

[0077] It is easy to understand that a positive deviation in the proportion of the two-phase region corresponds to insufficient superheat, and a deviation exceeding a certain threshold will cause liquid to be carried into the compressor intake, posing a high risk of liquid slugging and hardware damage. Conversely, a negative deviation in the proportion of the two-phase region corresponds to excessive superheat, which only reduces heat exchange efficiency and energy efficiency, without posing a risk of hardware damage. Therefore, this embodiment assigns a higher weight to positive deviations, prioritizing system reliability while optimizing energy efficiency.

[0078] In this embodiment, the differential penalty coefficient is used to limit the range of motion of mechanical components, avoid frequent and large load changes in the system, and improve operational stability and component lifespan.

[0079] Specifically, in this embodiment, the process of determining the optimal adjustment amount can adopt a traversal strategy combining large-step coarse search and small-step fine search, including: The combination of adjustment amounts within the adjustment range is traversed at a preset first interval. Based on the cost function, the cost value corresponding to each combination of adjustment amounts is calculated sequentially, and the combination of adjustment amounts with the smallest cost value is determined as the candidate adjustment amount. Within the vicinity of the candidate adjustment amount, the combination of adjustment amounts within the vicinity is traversed at a preset second interval, and the cost value corresponding to each combination of adjustment amounts is calculated sequentially. The combination of adjustment amounts with the smallest cost value is determined as the optimal adjustment amount. The preset second interval is smaller than the preset first interval. The vicinity is centered on the candidate adjustment amount and increases or decreases by at least one preset first interval along the compressor frequency and the expansion valve opening, respectively.

[0080] In the coarse search phase, the entire adjustment range is traversed with a preset first interval (e.g., frequency interval of 2Hz, opening interval of 5 steps), the cost value of each set of parameters is calculated, and the set with the smallest cost value is selected as the initial optimal adjustment amount. In the fine search phase, the preliminary optimal adjustment amount is taken as the center, and a fine search neighborhood is formed with a search radius of 1.5 times the first interval. Within this neighborhood, the calculation is performed point by point with a smaller preset second interval (frequency interval 0.5Hz, opening interval 1 step). Finally, the set with the smallest replacement value is selected as the final optimal adjustment amount.

[0081] Taking a typical working condition as an example, if a one-step fine traversal is used for the entire range, approximately 560 sets of parameters need to be calculated; while this implementation method only requires approximately 122 sets, reducing the amount of calculation by 78%, which greatly reduces the computational load of the embedded controller. It achieves a balance between high precision and low overhead under limited computing power, and has strong engineering practicality.

[0082] Step S70: The optimal adjustment amount is sent to the compressor and the expansion valve respectively.

[0083] The optimal adjustment amount is sent to the compressor and the electronic expansion valve respectively, and energy-saving control can be performed cyclically according to a fixed cycle. The controller converts the compressor frequency of the optimal adjustment amount into the target frequency command of the variable frequency drive and sends it to the compressor drive board through the communication bus; it converts the expansion valve opening of the optimal adjustment amount into the drive pulse command of the stepper motor and sends it to the electronic expansion valve drive mechanism.

[0084] After receiving the instruction, each actuator adjusts the corresponding parameters to gradually converge the proportion of the two-phase zone in the evaporator towards the optimal value, thus completing the current energy-saving control cycle.

[0085] It should be noted that in the above embodiments, there is no necessarily a certain order between the steps. Those skilled in the art can understand from the description of the embodiments of this application that the above steps may have different execution orders in different embodiments, that is, they may be executed in parallel or in turn, etc.

[0086] As a feasible implementation method, the heat transfer correction factor can be multiplied by the theoretical surface heat transfer coefficient in the form of a multiplier. The initial reference value is usually set to 1.0, and the effective adjustment range under normal operating conditions is about 0.8-1.2, which can cover the fluctuations in heat exchange capacity caused by dust accumulation, frost, and aging of the heat exchanger.

[0087] As a feasible implementation method, the heat transfer correction coefficient can also be applied in the form of offset superposition, that is, the actual heat transfer coefficient is the sum of the theoretical reference value and the correction offset. When the heat exchange capacity deviation is small, the linearity of the offset adjustment is better and the control is more stable. In addition, a unified correction coefficient can be set for the three regions of evaporator inlet, middle and outlet, and all heat exchange units in the same region share the same correction coefficient, which greatly reduces the amount of iterative calculation and is suitable for low-end controllers with weak computing power.

[0088] Furthermore, in the above embodiments, the process of constructing the heat balance equations also includes: Based on the preset heat transfer coefficient benchmark value, the heat balance equations of each heat exchange unit are solved simultaneously to determine the refrigerant phase state and current heat flux density of each heat exchange unit. The refrigerant phase state includes two-phase state and single-phase state. The heat transfer coefficient reference value is updated according to the refrigerant phase state within the heat exchange unit. Specifically, for a heat exchange unit in a two-phase state, the heat transfer coefficient reference value is updated based on the current heat flux density, refrigerant mass flow rate, and pipe inner diameter. For a heat exchange unit in a single-phase state, the heat transfer coefficient reference value is updated based on the refrigerant mass flow rate, pipe inner diameter, and refrigerant physical property parameters, wherein the refrigerant physical property parameters are determined by the refrigerant type. The heat balance equations are iteratively solved based on the updated heat transfer coefficient benchmark value until the change in heat flux density obtained in two adjacent solutions is less than the preset convergence threshold, thus obtaining the converged heat balance equations for each heat exchange unit.

[0089] It is necessary to explain that the refrigerant in the evaporator gradually absorbs heat from the gas-liquid two-phase state at the inlet to the single-phase superheated state at the outlet along the flow direction. The heat transfer mechanisms in the two-phase and single-phase regions are fundamentally different. In the two-phase region, nucleation boiling and forced convection superimpose, and its heat transfer coefficient is mainly affected by the heat flux density, refrigerant mass flow rate, and pipe inner diameter. In contrast, the single-phase region is dominated by turbulent convection heat transfer, and its heat transfer coefficient is mainly determined by the refrigerant mass flow rate, pipe inner diameter, and physical properties such as the refrigerant's thermal conductivity, dynamic viscosity, and isobaric specific heat.

[0090] Therefore, if a uniform reference value for the heat transfer coefficient is used for all heat exchange units, it will be impossible to accurately reflect the changes in the heat transfer mechanism along the process, resulting in insufficient accuracy of the model calculation. At the same time, the phase distribution of each heat exchange unit itself depends on the calculated result of the heat transfer coefficient, and the value of the heat transfer coefficient depends on the phase determination. Therefore, iterative solution is necessary to obtain a self-consistent convergent solution.

[0091] For example, this embodiment provides a specific set of parameter setting procedures: Assuming the evaporator main tube is 10m long and has an inner diameter of 8mm, it is divided into 10 equal-length heat exchange units along the refrigerant flow direction; the refrigerant type is R410A, with a mass flow rate of 0.05kg / s; the inlet pressure is 0.8MPa, the inlet enthalpy is 250kJ / kg, corresponding to an inlet dryness fraction of approximately 0.3; the ambient temperature at the tube wall heat exchange boundary is 7℃, and the air-side convective heat transfer coefficient is 50W / (m²). K).

[0092] The preset heat transfer coefficient benchmark value can be uniformly taken as 2000W / (㎡) K), the initial value is taken as the middle order of the heat transfer coefficient between the two-phase region and the single-phase region, and is used for the first round of solution to obtain the initial phase distribution; the preset convergence threshold is set to the relative change of heat flux density obtained in two adjacent solutions not exceeding 1%, and this threshold achieves a balance between calculation accuracy and number of iterations.

[0093] In the first round of solving, the aforementioned preset benchmark values ​​are substituted into the heat balance equations of each heat exchange unit, and solved sequentially along the flow direction to obtain the refrigerant enthalpy, pressure, and current heat flux density at the outlet of each unit. Based on the comparison between the outlet enthalpy and the saturated vapor enthalpy at the corresponding pressure, units 1 to 6 are determined to be in a two-phase state, unit 7 is the boundary unit between two-phase and single-phase, and units 8 to 10 are determined to be in a single-phase superheated state. The heat flux density of each unit gradually decreases from approximately 8200 W / m² to approximately 2300 W / m² along the flow direction.

[0094] After obtaining the phase distribution, the baseline values ​​of the heat transfer coefficients for each unit are updated. For units 1 to 6 in the two-phase region, the updated baseline values ​​are calculated using the two-phase boiling heat transfer correlation formula based on the current heat flux density, mass flow rate, and pipe inner diameter, from approximately 3600 W / (m²) at the inlet side. K) decreases to approximately 2600W / (㎡) along the route. K) decreases synchronously with decreasing heat flux density; for units 8 to 10 in the single-phase region, based on mass flow rate, pipe inner diameter, and parameters such as thermal conductivity, dynamic viscosity, and specific heat at constant pressure obtained from the R410A property table, the updated baseline value is approximately 1500 W / (m²) calculated using a single-phase phase heat transfer correlation formula. K); The boundary element 7 is determined by a weighted average of the length ratios of the internal two-phase segments and single-phase segments.

[0095] The updated baseline values ​​are substituted into the equations for a second round of solving, yielding a new heat flux density distribution. Compared to the first round, the heat flux density of unit 1 changes from 8200 W / m² to 7900 W / m², a relative change of approximately 3.7%, which is greater than the convergence threshold of 1%. Therefore, iteration continues. After the third round of solving, the relative change in heat flux density for each unit decreases to below 1%. For example, unit 1 becomes 7850 W / m², a relative change of approximately 0.6%, satisfying the convergence condition. The heat balance equations at this point are the converged results, which can be used for subsequent wall temperature prediction and two-phase region proportion calculation.

[0096] As a feasible implementation method, the two-phase region can be further divided into different flow pattern regions such as bubbly flow, slug flow, annular flow, and mist flow according to the refrigerant dryness. For each flow pattern, a corresponding special heat transfer correlation formula is matched. For example, for the bubbly flow region, which is dominated by nucleation boiling heat transfer, the nucleation boiling heat transfer formula is adopted; for the annular flow region, which is dominated by forced convection evaporation, the convection boiling heat transfer formula is adopted.

[0097] Furthermore, in one embodiment, the heat exchange segmentation model outputs the initial two-phase region ratio along with the predicted wall temperature, and uses the initial two-phase region ratio as the phase state constraint boundary when modifying the heat exchange segmentation model. The process of the heat exchange segmentation model outputting the two-phase region ratio and the predicted wall temperature includes: using the current inlet parameters as the inlet boundary condition of the first heat exchange unit, using the pipe wall heat exchange boundary as the outer boundary condition of each heat exchange unit, solving the heat balance equations of each heat exchange unit sequentially along the refrigerant flow direction, and determining the refrigerant enthalpy and pressure at the outlet of each heat exchange unit; comparing the outlet enthalpy of each heat exchange unit with the saturated vapor enthalpy at the corresponding outlet pressure to determine the phase state, calculating the total length of the two-phase pipe segment, and the ratio of the two-phase pipe segment to the total pipe length is the initial two-phase region ratio; determining the calculated wall temperature value at the corresponding pipe wall position based on the solution results of each heat exchange unit, and determining the predicted wall temperature value corresponding to each temperature measurement point through position interpolation.

[0098] The phase determination method is based on the relationship between enthalpy and saturated vapor enthalpy, and can be applied to both the two-phase region and the superheated region.

[0099] Actual operating conditions can generally be divided into three typical scenarios: Under low temperature and high load, the evaporator is in a two-phase state throughout, the enthalpy value at the outlet of all units is less than the saturated steam enthalpy, and the total length of the two-phase tube section is equal to the total tube length; Under high temperature and low load, the evaporator is in a superheated state throughout, the enthalpy value at the outlet of all units is greater than the saturated steam enthalpy, and the total length of the two-phase tube section is zero; Under normal operating conditions, the two-phase region and the superheated region coexist, it is necessary to locate the boundary heat exchange unit and determine the axial position of the saturation point through linear interpolation of the enthalpy value, and then accumulate to determine the total length of the two-phase section.

[0100] Using the initial two-phase region ratio as the phase constraint boundary, the specific implementation is to recalculate the two-phase region ratio after each round of correction. If the corrected phase distribution is fundamentally reversed from the initial pattern, for example, if the overheating section appears out of nowhere due to excessive correction in the two-phase operation, or if the change in the two-phase region ratio relative to the initial value exceeds ±15% and there is no corresponding change in the operation to support it, then it is determined that the correction deviates from the physical law, the correction coefficient is clamped to the value of the previous round, the iteration steps are rolled back, and the phase pattern is forcibly guaranteed not to undergo fundamental changes.

[0101] As a feasible implementation method, when the initial two-phase region ratio is within the allowable deviation range of ±3% of the optimal value and the initial wall temperature comprehensive deviation is less than 0.3℃, the model correction step can be skipped directly, and the initial model can be used directly as the target model.

[0102] Furthermore, in the above embodiments, the process of updating the heat transfer correction coefficient of each heat exchange unit and correcting the heat transfer segment model includes: The deviation between the predicted wall temperature value and the corresponding measured wall temperature value at each temperature measurement point is determined, and a comprehensive deviation is constructed. The comprehensive deviation is the root mean square value or weighted average value of the deviations at each temperature measurement point. When the overall deviation is greater than the preset deviation threshold, the distance between each heat exchange unit and the nearest temperature measuring point is determined according to the axial position of each heat exchange unit and the installation position of each temperature measuring point. The correction magnitude weight is determined according to the distance, and the distance is negatively correlated with the correction magnitude weight. The adjustment direction of the heat transfer correction coefficient is determined based on the relationship between the predicted wall temperature and the measured wall temperature at the corresponding location of each heat exchange unit. The adjustment direction satisfies the following: when the predicted wall temperature is greater than the measured wall temperature, the heat transfer correction coefficient is decreased; when the predicted wall temperature is less than the measured wall temperature, the heat transfer correction coefficient is increased. The basic adjustment step size is determined based on the magnitude of the comprehensive deviation. The actual adjustment amount of each heat exchange unit is determined based on the adjustment direction, the basic adjustment step size, and the correction magnitude weight, so as to update the heat transfer correction coefficient of each heat exchange unit. The updated heat transfer correction coefficient is substituted into the heat transfer segment model, and the predicted wall temperature and the comprehensive deviation are iteratively calculated until the comprehensive deviation is not greater than the preset deviation threshold, thus obtaining the target model.

[0103] Among them, the two calculation methods of comprehensive deviation are adapted to different application scenarios. The root mean square value is suitable for scenarios where the measuring points are evenly distributed and the importance of each position is equal. It can comprehensively reflect the overall deviation level of the entire pipe, is sensitive to large deviations, and can effectively suppress large local errors. The weighted average value is suitable for scenarios where key positions need to be given special attention. Higher weights can be set for key measuring points such as the evaporator outlet. For example, the weight of the outlet measuring point can be set to 0.4, and the weights of the other three measuring points can be set to 0.2 each. Priority is given to ensuring the calculation accuracy of the outlet area, because the outlet superheat is directly related to the compressor's suction safety.

[0104] The typical preset deviation threshold is 0.5℃, which can be adjusted according to the temperature measurement accuracy and control requirements. Its basic adjustment step size is positively correlated with the magnitude of the overall deviation: a large step size is used for rapid convergence when the deviation is large, and a small step size is used for fine-tuning when the deviation is small, avoiding overshoot. Specifically, piecewise linear mapping can be used; for example, the step size coefficient is 0.08 when the overall deviation is greater than 2℃, 0.05 when the deviation is between 1 and 2℃, and 0.02 when the deviation is less than 1℃.

[0105] The correction magnitude weight can adopt a distance-negative correlation design. For example, the calculation method can be inversely proportional to the distance. The weight of the unit 1m away from the measurement point is twice that of the unit 2m away from the measurement point. The closer the distance, the greater the correction magnitude. Compared with the global uniform correction coefficient scheme, this can effectively avoid model distortion caused by excessive correction of far-end units.

[0106] As a feasible implementation method, a correction method based on measurement point partitioning can also be adopted. This method divides the evaporator pipeline into multiple independent pipe segments based on two adjacent measurement points. All heat exchange units within each pipe segment share the same correction coefficient. The correction coefficient is adjusted by the deviation between the two measurement points of the corresponding pipe segment. This reduces the number of correction variables to be consistent with the number of measurement points, significantly reducing the complexity and computational cost of iterative calculations, while preserving the accuracy of the partitioning correction along the pipeline.

[0107] Furthermore, in the above embodiments, the process of determining the adjustment range of the compressor frequency and the expansion valve opening includes: The deviation value is calculated by subtracting the preset optimal two-phase region ratio from the current two-phase region ratio. When the absolute value of the deviation is not less than the preset dead zone threshold, the adjustment direction is determined according to the sign of the deviation value. When the deviation value is positive, the adjustment direction is to reduce the opening of the expansion valve and reduce the compressor frequency. When the deviation value is negative, the adjustment direction is to increase the opening of the expansion valve and increase the compressor frequency. Based on the absolute value of the deviation, the adjustment range of the compressor frequency and the expansion valve opening is determined, and the adjustment range is positively correlated with the magnitude of the absolute value. Based on the adjustment direction and the adjustment range, the adjustment range of the compressor frequency and the expansion valve opening are determined respectively.

[0108] There is a clear correlation between the proportion of the two-phase region and the superheat: the higher the proportion, the shorter the superheat section and the lower the outlet superheat; conversely, the lower the proportion, the greater the superheat. When the deviation is positive, the proportion of the two-phase region is higher than the optimal value, indicating that the superheat section is too short and the outlet superheat is insufficient, posing a risk of liquid carryover during suction. Therefore, it is necessary to reduce the opening of the expansion valve to reduce refrigerant supply and reduce the compressor frequency to reduce refrigerant suction, thus shortening the two-phase region and increasing the superheat through a two-pronged approach. Conversely, when the deviation is negative, it is necessary to increase the opening and increase the frequency to extend the two-phase region and improve the utilization rate of the heat exchange area.

[0109] Specifically, the optimal two-phase region ratio can be determined through offline calibration in an environmental enthalpy difference laboratory: under fixed environmental conditions, the combination of compressor frequency and expansion valve opening is traversed, and the system COP is tested as a function of the two-phase region ratio. The two-phase region ratio corresponding to the peak COP is the optimal value under that condition. The optimal ratio varies under different environmental temperatures and different load requirements. It can be stored in a two-dimensional lookup table array and interpolated and called during runtime based on real-time operating conditions.

[0110] In this embodiment, the single-sided adjustment range refers to the parameter range that only includes adjustments in the direction of deviation reduction, eliminating all invalid values ​​that are opposite to the control target. Existing technologies often use a symmetrical adjustment range centered on the current value, which increases the computational load and is prone to control oscillations. Therefore, this embodiment adopts a single-sided adjustment range design, which can effectively reduce the amount of optimization calculations while ensuring monotonic convergence of the control process.

[0111] As a feasible implementation method, a deviation dead zone mechanism can be set, that is, when the absolute value of the deviation is less than the preset dead zone threshold (typically 2%), no adjustment operation is performed, the current operating parameters are maintained, thereby suppressing frequent fine-tuning caused by small disturbances, avoiding repeated oscillations of the system near the optimal value, reducing the number of actions of the compressor and expansion valve, and improving the stability of system operation.

[0112] Furthermore, in some embodiments, in the deviation term of the preset cost function, the first weighting coefficient corresponding to the positive deviation is greater than the second weighting coefficient corresponding to the negative deviation, so as to suppress the positive deviation of the two-phase region ratio; the penalty term for the change of adjustment amount includes a frequency change penalty component and an opening change penalty component, and the penalty coefficient corresponding to the frequency change penalty component is greater than the penalty coefficient corresponding to the opening change penalty component, so as to limit the rate of change of compressor frequency; the value of the preset cost function is the sum of the value of the deviation term and the value of the penalty term.

[0113] It is easy to understand that a small positive deviation will only slightly reduce the outlet superheat and pose no substantial operational risk; however, once the positive deviation exceeds the critical value, the probability of liquid being carried in the compressor intake will increase sharply, and liquid slugging may cause irreversible damage to the compressor valve plates, cylinders, etc., with a risk level far higher than energy efficiency reduction.

[0114] For example, typical weight values ​​are 1.8 for the first weight coefficient and 1.0 for the second weight coefficient. That is, the evaluation value of a positive deviation of the same magnitude in the cost function is 1.8 times that of a negative deviation, thereby forming a strong constraint and ensuring operational reliability.

[0115] The compressor is a mechanical moving part. Frequent and large load changes will aggravate mechanical wear and shorten its service life. Moreover, frequency fluctuations have a greater impact on the refrigerant circulation system and are more likely to cause system pressure oscillations. In contrast, the electronic expansion valve is driven by a stepper motor, which has less adjustment inertia and a stronger ability to withstand frequent adjustments. Therefore, the frequency penalty coefficient in the penalty item of this embodiment is higher.

[0116] For example, typical penalty coefficients are set at 0.5 / Hz for frequency penalty and 0.1 / step for opening penalty, which can effectively limit the compressor's load rate while ensuring the adjustment effect.

[0117] As a feasible implementation method, the cost function can also include an energy consumption penalty term, which incorporates the adjusted predicted operating power of the compressor into the evaluation dimension. The predicted power is calculated based on the adjusted frequency, pressure ratio, and efficiency characteristics, and a corresponding energy consumption weighting coefficient is set. Among candidate solutions with similar proportions in the two-phase region, the energy consumption penalty term will prioritize the scheme with lower operating power consumption, further enhancing the energy-saving control effect.

[0118] As another aspect of this application, embodiments of this application also provide an energy-saving monitoring system for heat pump air conditioners, applied to the aforementioned heat pump air conditioners.

[0119] Please refer to Figure 2 , Figure 2 The diagram shows a structural schematic of an energy-saving monitoring system for heat pump air conditioners, which includes: Data acquisition module 210 is configured to acquire the structural parameters, refrigerant type and refrigerant mass flow rate of the evaporator; The model building module 220 is configured to divide the evaporator into multiple heat exchange units, and construct a set of heat balance equations for each heat exchange unit based on the structural parameters, refrigerant type and refrigerant mass flow rate, thereby forming a heat exchange segment model of the evaporator. The set of heat balance equations includes the heat transfer correction coefficients corresponding to each heat exchange unit. The model solving module 230 is configured to obtain the inlet parameters and heat transfer boundary of the evaporator, input the inlet parameters and heat transfer boundary of the tube wall into the heat transfer segment model, and obtain the predicted wall temperature value of each temperature measuring point in the evaporator. The model correction module 240 is configured to acquire the wall temperature measurement values ​​at each temperature measuring point in the evaporator, update the heat transfer correction coefficient of each heat exchange unit with the goal of reducing the deviation between the wall temperature measurement value and the predicted wall temperature value, and correct the heat exchange segment model to obtain the target model; input the inlet parameters and the tube wall heat exchange boundary into the target model to obtain the current two-phase region ratio, and determine the adjustment range of compressor frequency and expansion valve opening by combining the preset optimal two-phase region ratio; The adjustment optimization module 250 is configured to take the optimal two-phase region ratio as the control target, determine the predicted two-phase region ratio corresponding to each adjustment amount through the target model, and select the adjustment amount that minimizes the cost value of the preset cost function as the optimal adjustment amount. The cost function consists of a deviation term and a penalty term. The deviation term is used to characterize the deviation of the predicted two-phase region ratio from the optimal two-phase region ratio. The deviation term is set with different weight coefficients for positive and negative deviations respectively. The instruction issuing module 260 is configured to issue the optimal adjustment amount to the compressor and the expansion valve respectively.

[0120] Each functional module can be integrated into the air conditioner main controller in the form of software functions. Modules can pass parameters through global variables and function interfaces and work together by relying on the controller hardware resources.

[0121] As a feasible implementation method, the above system can also be configured as an independent control unit, which can interface with the existing air conditioning controller through standard communication interfaces such as RS485 and Modbus. Based on this understanding, the external unit can independently collect sensor data such as wall temperature and pressure, run segmented models and optimization logic, and finally send frequency and opening degree commands to the existing air conditioning controller for execution, which is very suitable for energy-saving retrofitting of existing air conditioning systems in commercial buildings.

[0122] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The storage medium can be a magnetic disk, optical disk, read-only memory, or random access memory, etc.

[0123] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. An energy-saving monitoring method for a heat pump air conditioner, applied to a heat pump air conditioner, the heat pump air conditioner comprising at least an evaporator, a compressor, and an expansion valve, characterized in that, The method includes: Obtain the structural parameters, refrigerant type, and refrigerant mass flow rate of the evaporator; The evaporator is divided into multiple heat exchange units. Based on the structural parameters, refrigerant type and refrigerant mass flow rate, a set of heat balance equations for each heat exchange unit is constructed to form a heat exchange segment model of the evaporator. The set of heat balance equations includes the heat transfer correction coefficients corresponding to each heat exchange unit. The inlet parameters and heat transfer boundary of the evaporator are obtained, and the inlet parameters and heat transfer boundary of the tube wall are input into the heat transfer segment model to obtain the predicted wall temperature value of each temperature measuring point in the evaporator. The wall temperature measurement values ​​at each temperature measuring point in the evaporator are obtained. With the goal of reducing the deviation between the measured wall temperature values ​​and the predicted wall temperature values, the heat transfer correction coefficients of each heat exchange unit are updated to correct the heat exchange segment model and obtain the target model. The inlet parameters and the heat exchange boundary of the pipe wall are input into the target model to obtain the current two-phase region ratio. Combined with the preset optimal two-phase region ratio, the adjustment range of compressor frequency and expansion valve opening is determined. Using the optimal two-phase region ratio as the control target, the predicted two-phase region ratio corresponding to each adjustment amount is determined through the target model. The adjustment amount that minimizes the cost value of the preset cost function is selected as the optimal adjustment amount. The cost function consists of a deviation term and a penalty term. The deviation term is used to characterize the deviation of the predicted two-phase region ratio from the optimal two-phase region ratio. The deviation term is set with different weight coefficients for positive and negative deviations. The optimal adjustment amount is issued to the compressor and the expansion valve respectively.

2. The method according to claim 1, characterized in that, The evaporator is divided into multiple heat exchange units along the refrigerant flow direction. A set of heat balance equations for each heat exchange unit is constructed based on the structural parameters, refrigerant type, and refrigerant mass flow rate, including: The total tube length and inner diameter of the evaporator are determined based on the structural parameters. Based on the total pipe length, the evaporator is divided into multiple heat exchange units of equal length according to the preset unit length. Given the refrigerant type, refrigerant mass flow rate, and pipe inner diameter, and with the refrigerant pressure and enthalpy as unknowns, a set of heat balance equations is constructed for each heat exchange unit. The set of heat balance equations includes a mass balance equation, an energy balance equation, and a pressure drop equation. The heat transfer in the energy balance equation is determined by the refrigerant-side heat transfer coefficient of the corresponding heat exchange unit, and the heat transfer correction coefficient is applied to the refrigerant-side heat transfer coefficient.

3. The method according to claim 2, characterized in that, After constructing the mass balance equation, energy balance equation, and pressure drop equation for each heat exchange unit as the heat balance equation set, the following is also included: Based on the preset heat transfer coefficient benchmark value, the heat balance equations of each heat exchange unit are solved simultaneously to determine the refrigerant phase state and current heat flux density of each heat exchange unit. The refrigerant phase state includes two-phase state and single-phase state. The heat transfer coefficient reference value is updated according to the refrigerant phase state in the heat exchange unit. Specifically, for a heat exchange unit in a two-phase state, the heat transfer coefficient reference value is updated according to the current heat flux density, refrigerant mass flow rate, and pipe inner diameter. For a heat exchange unit in a single-phase state, the heat transfer coefficient reference value is updated according to the refrigerant mass flow rate, pipe inner diameter, and refrigerant physical property parameters, wherein the refrigerant physical property parameters are determined by the refrigerant type. The heat balance equations are iteratively solved based on the updated heat transfer coefficient benchmark value until the change in heat flux density obtained in two adjacent solutions is less than the preset convergence threshold, thus obtaining the converged heat balance equations for each heat exchange unit.

4. The method according to claim 1, characterized in that, The process of obtaining the inlet parameters and tube wall heat transfer boundary of the evaporator includes: Obtain the inlet pressure and inlet enthalpy of the evaporator, and use the current inlet pressure and inlet enthalpy as the inlet parameters; The current ambient temperature and air-side convective heat transfer coefficient of the evaporator are obtained, and the ambient temperature and air-side convective heat transfer coefficient are used as the heat transfer boundary of the tube wall.

5. The method according to claim 1, characterized in that, The heat transfer segment model outputs the predicted wall temperature value and the initial two-phase region ratio, which is used to characterize the phase constraint boundary when correcting the heat transfer segment model. The step of inputting the inlet parameters and the heat transfer boundary of the pipe wall into the heat transfer segment model to obtain the predicted wall temperature values ​​of each temperature measuring point in the evaporator includes: The inlet parameters are used as the inlet boundary conditions of the first heat exchange unit, and the pipe wall heat exchange boundary is used as the outer boundary conditions of each heat exchange unit. The heat balance equations of each heat exchange unit are solved sequentially along the refrigerant flow direction to determine the refrigerant enthalpy and pressure at the outlet of each heat exchange unit. The refrigerant enthalpy of each heat exchange unit is compared with the saturated vapor enthalpy at the corresponding outlet pressure to determine the phase state of the corresponding heat exchange unit and calculate the total length of the two-phase pipe section. When all heat exchange units are in a two-phase state at the outlet, the total length of the two-phase pipe section is equal to the total pipe length; when all heat exchange units are in a superheated state, the total length of the two-phase pipe section is zero. The ratio of the total length of the two-phase tube section to the total length of the evaporator tube is determined as the initial two-phase zone proportion. The calculated wall temperature at the corresponding pipe wall location is determined based on the solution results of each heat exchange unit, and the predicted wall temperature at each temperature measurement point is determined by location interpolation.

6. The method according to claim 1, characterized in that, The step of updating the heat transfer correction coefficient of each heat exchange unit with the goal of reducing the deviation between the measured wall temperature value and the predicted wall temperature value includes: The deviation between the predicted wall temperature value and the corresponding measured wall temperature value at each temperature measurement point is determined, and a comprehensive deviation is constructed. The comprehensive deviation is the root mean square value or weighted average value of the deviations at each temperature measurement point. When the overall deviation is greater than the preset deviation threshold, the distance between each heat exchange unit and the nearest temperature measuring point is determined according to the axial position of each heat exchange unit and the installation position of each temperature measuring point. The correction magnitude weight is determined according to the distance, and the distance is negatively correlated with the correction magnitude weight. The adjustment direction of the heat transfer correction coefficient is determined based on the relationship between the predicted wall temperature and the measured wall temperature at the corresponding location of each heat exchange unit. The adjustment direction satisfies the following: when the predicted wall temperature is greater than the measured wall temperature, the heat transfer correction coefficient is decreased; when the predicted wall temperature is less than the measured wall temperature, the heat transfer correction coefficient is increased. The basic adjustment step size is determined based on the magnitude of the comprehensive deviation. The actual adjustment amount of each heat exchange unit is determined based on the adjustment direction, the basic adjustment step size, and the correction magnitude weight, so as to update the heat transfer correction coefficient of each heat exchange unit. The updated heat transfer correction coefficient is substituted into the heat transfer segment model, and the predicted wall temperature and the comprehensive deviation are iteratively calculated until the comprehensive deviation is not greater than the preset deviation threshold, thus obtaining the target model.

7. The method according to claim 1, characterized in that, The step of determining the adjustment range of the compressor and expansion valve based on the deviation between the current two-phase region ratio and the preset optimal two-phase region ratio includes: The deviation value is calculated by subtracting the preset optimal two-phase region ratio from the current two-phase region ratio. When the absolute value of the deviation is not less than the preset dead zone threshold, the adjustment direction is determined according to the sign of the deviation value. When the deviation value is positive, the adjustment direction is to reduce the opening of the expansion valve and reduce the compressor frequency. When the deviation value is negative, the adjustment direction is to increase the opening of the expansion valve and increase the compressor frequency. Based on the absolute value of the deviation, the adjustment range of the compressor frequency and the expansion valve opening is determined, and the adjustment range is positively correlated with the magnitude of the absolute value. Based on the adjustment direction and the adjustment range, the adjustment range of the compressor frequency and the expansion valve opening are determined respectively.

8. The method according to claim 7, characterized in that, In the deviation term of the preset cost function, the first weighting coefficient corresponding to the positive deviation is greater than the second weighting coefficient corresponding to the negative deviation; The preset cost function also includes a penalty term, which includes a frequency change penalty component and an opening change penalty component. The penalty coefficient corresponding to the frequency change penalty component is greater than that of the opening change penalty component.

9. The method according to claim 8, characterized in that, The selection of the adjustment amount that minimizes the cost of the preset cost function as the optimal adjustment amount includes: The combination of adjustment amounts within the adjustment range is traversed at a preset first interval. Based on the cost function, the cost value corresponding to each combination of adjustment amounts is calculated sequentially, and the combination of adjustment amounts with the smallest cost value is determined as the candidate adjustment amount. Within the vicinity of the candidate adjustment amount, the combination of adjustment amounts within the vicinity is traversed at a preset second interval, and the cost value corresponding to each combination of adjustment amounts is calculated sequentially. The combination of adjustment amounts with the smallest cost value is determined as the optimal adjustment amount. The preset second interval is smaller than the preset first interval. The vicinity is centered on the candidate adjustment amount and increases or decreases by at least one preset first interval along the compressor frequency and the expansion valve opening, respectively.

10. An energy-saving monitoring system for a heat pump air conditioner, applied to a heat pump air conditioner, wherein the heat pump air conditioner includes at least an evaporator, a compressor, and an expansion valve, characterized in that, The system includes: The data acquisition module is configured to acquire the structural parameters, refrigerant type, and refrigerant mass flow rate of the evaporator. The model building module is configured to divide the evaporator into multiple heat exchange units, and construct a set of heat balance equations for each heat exchange unit based on the structural parameters, refrigerant type and refrigerant mass flow rate, forming a heat exchange segment model of the evaporator. The set of heat balance equations includes the heat transfer correction coefficients corresponding to each heat exchange unit. The model solving module is configured to obtain the inlet parameters and heat transfer boundary of the evaporator, input the inlet parameters and heat transfer boundary of the tube wall into the heat transfer segment model, and obtain the predicted wall temperature value of each temperature measuring point in the evaporator. The model correction module is configured to acquire the wall temperature measurement values ​​at each temperature measuring point in the evaporator, update the heat transfer correction coefficient of each heat exchange unit with the goal of reducing the deviation between the wall temperature measurement value and the predicted wall temperature value, and correct the heat exchange segment model to obtain the target model; input the inlet parameters and the tube wall heat exchange boundary into the target model to obtain the current two-phase region ratio, and determine the adjustment range of compressor frequency and expansion valve opening by combining the preset optimal two-phase region ratio; The adjustment optimization module is configured to take the optimal two-phase region ratio as the control target, determine the predicted two-phase region ratio corresponding to each adjustment amount through the target model, and select the adjustment amount that minimizes the cost value of the preset cost function as the optimal adjustment amount. The cost function consists of a deviation term and a penalty term. The deviation term is used to characterize the deviation of the predicted two-phase region ratio from the optimal two-phase region ratio. The deviation term is set with different weight coefficients for positive and negative deviations respectively. The instruction issuing module is configured to issue the optimal adjustment amount to the compressor and the expansion valve respectively.

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