Air source heat pump system and defrosting control method thereof

Abstract

An air source heat pump system is sequentially connected through refrigerant pipelines to form a closed cycle, used for achieving the refrigerating or heating function, configured to detect the outdoor environment temperature in real time and output environment temperature signals, arranged on the surface of an evaporator and configured to detect the surface temperature of the evaporator in real time and output surface temperature signals. The controller is configured to detect the relative humidity of outdoor air and output a humidity signal, the controller is electrically connected with the environment temperature sensor, the evaporator temperature sensor and the humidity sensor, the controller comprises a memory and a processor, the memory stores a dynamic defrosting control program, and the processor is used for processing the dynamic defrosting control program. The processor executes the program to dynamically calculate the frost layer generation rate according to the environment temperature, the evaporator surface temperature and the relative humidity and adaptively adjust defrosting control parameters based on the frost layer generation rate. The system supports the three modes of electric heating defrosting, hot air defrosting and combined defrosting, and the optimal mode is intelligently selected according to the environmental conditions.

Description

Technical Field

[0001] The present invention belongs to the technical field of air heat sources, and in particular relates to an air source heat pump system and a defrosting control method thereof. Background Art

[0002] Air-source heat pumps, as highly efficient and energy-saving heating devices, are widely used in building heating and hot water supply. However, in low-temperature, high-humidity environments, frost easily forms on the evaporator surface of air-source heat pumps. This accumulation of frost significantly reduces heat exchange efficiency, leading to increased system energy consumption and even unstable operation. Therefore, regular defrosting or defrosting according to specific conditions is key to ensuring efficient operation of heat pump systems.

[0003] Existing technologies, on the one hand, rely on fixed defrost intervals that cannot be dynamically adjusted based on actual frost formation, resulting in either overly frequent or insufficient defrosting. Frequent defrosting increases unnecessary energy consumption, while insufficient defrosting reduces system heat exchange efficiency. On the other hand, traditional defrosting methods typically only support a single defrost mode (such as electric heating or hot gas defrost), making it difficult to select the optimal defrost method based on varying environmental conditions. For example, in extremely low temperature and high humidity environments, a single defrost mode is inefficient and consumes a lot of energy. Summary of the Invention

[0004] In view of the above situation, in order to overcome the defects of the prior art, the present invention provides an air source heat pump system and a defrost control method thereof, so as to at least partially solve the above technical problems.

[0005] The technical solution adopted by the present invention is as follows:

[0006] The present invention proposes an air source heat pump system, comprising:

[0007] The compressor, condenser, throttling device and evaporator are connected in sequence through refrigerant pipes to form a closed loop for achieving cooling or heating functions;

[0008] An ambient temperature sensor is installed outdoors and is configured to detect the outdoor ambient temperature in real time and output an ambient temperature signal;

[0009] an evaporator temperature sensor, disposed on the surface of the evaporator, configured to detect the evaporator surface temperature in real time and output a surface temperature signal;

[0010] a humidity sensor, disposed outdoors, configured to detect relative humidity of outdoor air and output a humidity signal;

[0011] a controller electrically connected to the ambient temperature sensor, the evaporator temperature sensor, and the humidity sensor, the controller comprising a memory and a processor, the memory storing a dynamic defrost control program, the processor executing the program to dynamically calculate a frost layer formation rate according to the ambient temperature, the evaporator surface temperature, and the relative humidity, and adaptively adjust defrost control parameters based on the frost layer formation rate, the defrost control parameters comprising a defrost start time, a defrost duration, and a defrost mode, so as to start or stop a defrost operation;

[0012] a defrost device comprising an electric heating unit and a hot gas bypass unit disposed near the evaporator, the electric heating unit heating the evaporator surface by electric energy, the hot gas bypass unit directing high-temperature refrigerant discharged from the compressor to the evaporator via a bypass valve and a bypass line, the defrost device performing a defrost operation under instructions from the controller;

[0013] The controller uses a dynamic defrost algorithm based on the frost formation rate. The algorithm compares a preset frost thickness threshold with the real-time calculated frost thickness. When the real-time frost thickness reaches the threshold, the defrost operation is triggered, thereby achieving precise defrosting, reducing system energy consumption and improving heating efficiency.

[0014] The dynamic defrost algorithm combines the ambient temperature, relative humidity and evaporator surface temperature to calculate the frost formation rate through a mathematical model. The mathematical model is:

[0015] [R_f=k_1\cdot(T_a-T_e)\cdotRH+k_2\cdotv_a]

[0016] Wherein, (R_f) is the frost formation rate, (T_a) is the ambient temperature, (T_e) is the evaporator surface temperature, (RH) is the relative humidity, (v_a) is the outdoor air flow rate, (k_1) and (k_2) are empirical coefficients. The algorithm optimizes the defrost control accuracy by adaptively adjusting the empirical coefficients.

[0017] In one embodiment of the present invention, the controller further includes a frost thickness prediction module, which calculates the real-time frost thickness based on the frost generation rate and the running time integral. The integral formula is:

[0018] [H_f(t)=\int_^tR_f(\tau),d\tau]

[0019] Wherein, (H_f(t)) is the real-time frost thickness, (t) is the system operation time, and (R_f(\tau)) is the instantaneous frost generation rate; the frost thickness prediction module compares the calculated real-time frost thickness with a preset threshold. When the real-time frost thickness exceeds the threshold, the controller triggers the defrost operation.

[0020] In one embodiment of the present invention, the defrost mode includes an electric heating defrost mode, a hot gas defrost mode and a combined defrost mode;

[0021] In the electric heating defrost mode, the controller activates the electric heating unit to directly heat the evaporator surface by electric energy to melt the frost layer;

[0022] In the hot gas defrost mode, the controller opens the bypass valve to introduce the high-temperature refrigerant discharged from the compressor into the evaporator for defrosting;

[0023] In the combined defrost mode, the controller activates the electric heating unit and the hot gas bypass unit in stages according to the thickness of the frost layer, first reducing the density of the frost layer through hot gas defrosting, and then quickly melting the remaining frost layer through electric heating defrosting, thereby optimizing defrost efficiency and energy consumption.

[0024] In one embodiment of the present invention, the controller selects the defrost mode according to the ambient temperature and relative humidity, wherein:

[0025] When the ambient temperature is lower than a first temperature threshold and the relative humidity is higher than a first humidity threshold, the controller preferentially selects the combined defrost mode;

[0026] When the ambient temperature is higher than a first temperature threshold but lower than a second temperature threshold, the controller selects the hot gas defrost mode;

[0027] When the ambient temperature is higher than a second temperature threshold, the controller selects the electric heating defrost mode;

[0028] The first temperature threshold, the second temperature threshold, and the first humidity threshold are stored in the memory and can be adjusted by the controller according to actual application scenarios.

[0029] In one embodiment of the present invention, an air source heat pump system further includes a wind speed sensor, which is arranged outdoors and configured to detect the outdoor air flow rate and output an air flow rate signal; the controller adjusts the calculation of the frost layer generation rate according to the air flow rate signal to improve the accuracy of the frost layer thickness prediction.

[0030] In one embodiment of the present invention, the evaporator includes a plurality of heat exchange fins, the surface of which is coated with a hydrophilic coating. The hydrophilic coating is used to reduce the adhesion of water droplets on the heat exchange fins, thereby slowing down the frost formation rate and improving the defrosting efficiency.

[0031] In one embodiment of the present invention, an air source heat pump system, the controller also includes a self-learning module, which optimizes the empirical coefficients (k_1) and (k_2) of the dynamic defrost algorithm through a machine learning algorithm based on historical defrost data and environmental parameters to improve the adaptability and accuracy of defrost control.

[0032] In one embodiment of the present invention, an air source heat pump system further includes a defrost effect detection unit, the defrost effect detection unit includes an optical sensor arranged on the surface of the evaporator, the optical sensor is used to detect the residual frost layer on the surface of the evaporator after defrosting, and feed back the detection result to the controller, and the controller adjusts the control parameters of the next defrost according to the detection result.

[0033] In one embodiment of the present invention, a defrost control method for an air source heat pump system comprises the following steps:

[0034] Step 1: Collect outdoor ambient temperature, evaporator surface temperature and relative humidity in real time;

[0035] Step 2: Calculate the frost layer formation rate using the dynamic defrost algorithm based on the collected ambient temperature, evaporator surface temperature and relative humidity;

[0036] Step 3: Calculating the real-time frost layer thickness based on the frost layer generation rate and the running time integral;

[0037] Step 4: comparing the real-time frost layer thickness with a preset frost layer thickness threshold, and triggering a defrost operation when the real-time frost layer thickness reaches or exceeds the threshold;

[0038] Step 5: Select a defrost mode according to the ambient temperature and relative humidity, wherein the defrost mode includes an electric heating defrost mode, a hot air defrost mode, or a combined defrost mode;

[0039] Step 6: Execute the defrost operation and adjust the control parameters for the next defrost according to the feedback from the defrost effect detection unit.

[0040] In one embodiment of the present invention, the method further includes a self-learning step, which optimizes the empirical coefficients of the dynamic defrost algorithm using a machine learning algorithm by analyzing historical defrost data and environmental parameters to improve the accuracy and energy efficiency of defrost control.

[0041] The beneficial effects of the technical solution of the present invention are:

[0042] The present invention collects ambient temperature, evaporator surface temperature, relative humidity and air flow rate in real time, calculates the frost formation rate in combination with a mathematical model, and predicts the frost thickness through integration to achieve precise defrost triggering. Compared with the traditional defrosting method based on fixed time intervals, the present invention can dynamically adjust the defrost parameters according to the actual frost layer conditions, avoid unnecessary defrosting operations, and significantly reduce energy consumption.

[0043] The system supports three defrost modes: electric heating, hot gas defrost, and combined defrost, intelligently selecting the optimal mode based on environmental conditions. For example, in extremely low temperature and high humidity environments, the combined defrost mode reduces the frost density through hot gas defrosting, and then uses electric heating to quickly melt the frost, improving defrost efficiency while reducing energy consumption.

[0044] The present invention analyzes historical defrost data through a machine learning algorithm and optimizes the empirical coefficients of the dynamic defrost algorithm, enabling the system to adapt to different climatic conditions and operating scenarios, further improving control accuracy.

[0045] This invention uses an optical sensor to detect the amount of frost remaining after defrosting and feeds the result back to a controller, which adjusts subsequent defrosting parameters to ensure thorough and efficient defrosting. A hydrophilic coating is applied to the evaporator's heat exchange fins to reduce water droplet adhesion, slowing frost formation and facilitating frost removal, thereby improving defrosting efficiency.

[0046] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0048] Figure 1 This is a schematic diagram of a defrost control method for an air source heat pump system proposed in an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The following describes embodiments of the present invention in detail, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and are not to be construed as limiting the present invention.

[0050] An air source heat pump system and a defrost control method thereof according to an embodiment of the present invention will be described below with reference to the accompanying drawings.

[0051] like Figure 1 As shown, an embodiment of the present invention provides an air source heat pump system, comprising:

[0052] The compressor, condenser, throttling device and evaporator are connected in sequence through refrigerant pipes to form a closed loop for achieving cooling or heating functions;

[0053] An ambient temperature sensor is installed outdoors and is configured to detect the outdoor ambient temperature in real time and output an ambient temperature signal;

[0054] An evaporator temperature sensor is provided on the surface of the evaporator and is configured to detect the surface temperature of the evaporator in real time and output a surface temperature signal;

[0055] a humidity sensor, disposed outdoors, configured to detect relative humidity of outdoor air and output a humidity signal;

[0056] a controller electrically connected to the ambient temperature sensor, the evaporator temperature sensor, and the humidity sensor, the controller including a memory and a processor, the memory storing a dynamic defrost control program, the processor executing the program to dynamically calculate a frost layer formation rate according to the ambient temperature, the evaporator surface temperature, and the relative humidity, and adaptively adjust defrost control parameters based on the frost layer formation rate, the defrost control parameters including a defrost start time, a defrost duration, and a defrost mode, so as to start or stop the defrost operation;

[0057] The defrost device includes an electric heating unit and a hot gas bypass unit disposed near the evaporator. The electric heating unit heats the evaporator surface with electric energy. The hot gas bypass unit guides the high-temperature refrigerant discharged from the compressor to the evaporator through a bypass valve and a bypass pipeline. The defrost device performs the defrost operation under the instruction of the controller.

[0058] The controller uses a dynamic defrost algorithm based on the frost formation rate. The algorithm compares the preset frost thickness threshold with the real-time calculated frost thickness. When the real-time frost thickness reaches the threshold, the defrost operation is triggered, thus achieving precise defrosting, reducing system energy consumption and improving heating efficiency.

[0059] The dynamic defrost algorithm combines the ambient temperature, relative humidity, and evaporator surface temperature to calculate the frost formation rate through a mathematical model. The mathematical model is:

[0060] [R_f=k_1\cdot(T_a-T_e)\cdotRH+k_2\cdotv_a]

[0061] Among them, (R_f) is the frost formation rate, (T_a) is the ambient temperature, (T_e) is the evaporator surface temperature, (RH) is the relative humidity, (v_a) is the outdoor air flow rate, (k_1) and (k_2) are empirical coefficients. The algorithm optimizes the defrost control accuracy by adaptively adjusting the empirical coefficients.

[0062] In specific applications of embodiments of the present invention, when an air-source heat pump system operates in a low-temperature, high-humidity environment, frost is prone to forming on the evaporator surface, resulting in reduced heat exchange efficiency, deteriorated heating performance, and even unstable system operation. Traditional defrosting methods typically use fixed time intervals or a single temperature parameter to trigger defrosting, which is difficult to adapt to complex and changing environmental conditions and can easily lead to insufficient or excessive defrosting, thereby increasing energy consumption or reducing system efficiency. This system integrates an ambient temperature sensor, an evaporator temperature sensor, a humidity sensor, a controller, and a defrost device, combined with a dynamic defrost algorithm based on the frost layer formation rate, to achieve real-time monitoring and precise control of the frost layer formation process, achieving the following goals:

[0063] (1) Dynamically calculate the frost formation rate and accurately determine the defrost timing;

[0064] (2) Adaptively adjust defrost control parameters to optimize defrost start time, duration, and mode;

[0065] (3) A composite defrosting method combining electric heating and hot gas bypass reduces energy consumption and improves defrosting efficiency;

[0066] (4) Improve the heating stability and energy efficiency of the system in low temperature and high humidity environments.

[0067] The multi-sensor collaborative environmental and operational status monitoring system is equipped with an ambient temperature sensor, an evaporator temperature sensor, and a humidity sensor. These sensors collect real-time data from the outdoor ambient temperature (T_a), the evaporator surface temperature (T_e), and the outdoor relative humidity (RH), respectively. These sensors utilize high-precision signal acquisition and conversion technology to ensure real-time and accurate data, providing reliable input for subsequent calculations of the frost formation rate. Furthermore, the system obtains outdoor air velocity (v_a) using external wind speed measurement equipment or preset parameters. The sensor output signals (ambient temperature, surface temperature, and humidity) are electrically transmitted to the controller, providing the data foundation for the dynamic defrost algorithm.

[0068] A dynamic defrost algorithm controller based on frost formation rate includes a memory and a processor. The memory stores a dynamic defrost control program, and the processor executes the program to achieve dynamic calculation of the frost formation rate and adaptive adjustment of defrost control parameters. The core algorithm calculates the frost formation rate ((R_f)) based on the following mathematical model: [R_f = k_1\cdot(T_a-T_e)\cdotRH+k_2\cdotv_a] where:

[0069] (R_f): frost formation rate, which indicates the accumulation rate of frost per unit time;

[0070] (T_a): ambient temperature, reflecting the heat supply capacity of outdoor air;

[0071] (T_e): evaporator surface temperature, reflecting the working status of the evaporator;

[0072] (RH): relative humidity, which indicates the effect of water vapor content in the air on frost formation;

[0073] (v_a): outdoor air velocity, which affects the dynamic process of frost deposition;

[0074] (k_1), (k_2): Empirical coefficients, optimized and adjusted through experimental data or adaptive algorithms.

[0075] This model comprehensively considers the effects of ambient temperature difference (T_a - T_e), humidity, and air velocity on frost formation. It calculates the frost formation rate through a weighted calculation. The controller estimates the frost thickness based on the real-time calculated value (R_f) and time integral, and compares it with a preset frost thickness threshold. When the real-time frost thickness reaches or exceeds the threshold, a defrost operation is triggered.

[0076] The processor dynamically optimizes (k_1) and (k_2) based on historical operating data and real-time environmental conditions to improve the accuracy of frost formation rate calculation; it comprehensively considers ambient temperature, evaporator surface temperature, relative humidity, and air flow rate to avoid misjudgment caused by a single parameter.

[0077] The controller adaptively adjusts the defrost control parameters according to the frost layer generation rate and system operating status, including:

[0078] Defrost start time: Accurately trigger the defrost operation based on the moment when the frost thickness reaches the threshold to avoid defrosting too early or too late;

[0079] Defrost duration: Dynamically determine the defrost time based on the frost formation rate and environmental conditions to ensure that the frost is completely removed without excessive energy consumption;

[0080] Defrost mode: Select electric heating defrost, hot gas bypass defrost or a combination of the two to adapt to different frost levels and environmental conditions.

[0081] For example, under conditions of high humidity, low temperature and high frost formation rate, the controller gives priority to the composite defrost mode, which combines the fast response of electric heating and the energy-saving characteristics of hot gas bypass; under conditions of light frosting, only the hot gas bypass mode is enabled to reduce energy consumption.

[0082] The defrost device consists of an electric heating unit and a hot gas bypass unit, each of which removes frost from the evaporator surface through different mechanisms:

[0083] The electric heating unit is installed near the evaporator. It converts electrical energy into thermal energy, directly heating the evaporator surface and quickly melting the frost layer. The electric heating unit has the advantages of fast response and thorough defrosting, and is suitable for heavy frosting or emergency defrosting scenarios.

[0084] The hot gas bypass unit directs high-temperature, high-pressure refrigerant discharged from the compressor to the evaporator via a bypass valve and bypass piping, utilizing the refrigerant's waste heat for defrosting. This method fully utilizes the system's internal heat, significantly reducing energy consumption and is suitable for light to moderate frosting conditions. The controller coordinates the operation of the two based on the frost formation rate and the defrost mode command. For example, in combined defrost mode, the electric heating unit can activate first to quickly clear the majority of the frost layer, followed by switching to the hot gas bypass unit to complete the remaining defrost, achieving a balanced approach to efficiency and energy conservation.

[0085] The closed-loop optimization system for system operation forms a closed-loop control mechanism using sensors, controllers, and defrost devices. Sensors monitor environmental and operating parameters in real time. The controller processes this data and outputs control instructions based on a dynamic defrost algorithm. After the defrost device completes the defrost operation, the sensor collects data again to verify the defrost effect. If the frost layer is not completely cleared, the controller can extend the defrost time or adjust the defrost mode. Once defrost is complete, the system resumes normal heating operation.

[0086] In a possible embodiment, the controller further includes a frost thickness prediction module, which calculates the real-time frost thickness based on the frost generation rate and the running time integral. The integral formula is:

[0087] [H_f(t)=\int_^tR_f(\tau),d\tau]

[0088] Where (H_f(t)) is the real-time frost thickness, (t) is the system operating time, and (R_f(\tau)) is the instantaneous frost generation rate. The frost thickness prediction module compares the calculated real-time frost thickness with the preset threshold. When the real-time frost thickness exceeds the threshold, the controller triggers the defrost operation.

[0089] The defrost modes include electric heating defrost mode, hot gas defrost mode and combined defrost mode;

[0090] In the electric heating defrost mode, the controller activates the electric heating unit to directly heat the evaporator surface through electric energy to melt the frost layer;

[0091] In hot gas defrost mode, the controller opens the bypass valve to introduce the high-temperature refrigerant discharged from the compressor into the evaporator for defrosting;

[0092] In the combined defrost mode, the controller activates the electric heating unit and the hot gas bypass unit in stages according to the thickness of the frost layer. It first reduces the density of the frost layer through hot gas defrosting, and then quickly melts the remaining frost layer through electric heating defrosting, thereby optimizing defrost efficiency and energy consumption.

[0093] In specific applications of the embodiments of the present invention,

[0094] In one possible implementation, the controller selects a defrost mode based on ambient temperature and relative humidity, wherein:

[0095] When the ambient temperature is lower than a first temperature threshold and the relative humidity is higher than a first humidity threshold, the controller preferentially selects the combined defrost mode;

[0096] When the ambient temperature is higher than a first temperature threshold but lower than a second temperature threshold, the controller selects a hot gas defrost mode;

[0097] When the ambient temperature is higher than the second temperature threshold, the controller selects the electric heating defrost mode;

[0098] The first temperature threshold, the second temperature threshold and the first humidity threshold are stored in the memory and can be adjusted by the controller according to actual application scenarios.

[0099] In a specific application of an embodiment of the present invention, the controller of the system integrates a frost thickness prediction module for calculating the frost thickness on the evaporator surface in real time. The frost thickness prediction module accurately predicts the frost thickness by integrating the frost generation rate and the system operating time. The integral formula is as follows:

[0100] [H_f(t)=\int_^tR_f(\tau),d\tau]

[0101] in:

[0102] (H_f(t)) represents the real-time frost thickness in millimeters (mm), reflecting the degree of frost accumulation on the evaporator surface;

[0103] (t) represents the system operating time in seconds (s), starting from system startup or the end of the last defrost;

[0104] (R_f(\tau)) represents the instantaneous frost formation rate, measured in millimeters per second (mm / s), which is determined by a combination of parameters such as ambient temperature, relative humidity, evaporator surface temperature, and air flow rate.

[0105] The frost thickness prediction module uses sensors to collect environmental parameters (such as ambient temperature and humidity) and system operating parameters (such as evaporator temperature and compressor operating frequency). Combined with a preset frost formation model, it dynamically calculates the instantaneous frost formation rate (R_f(\tau)). The module then accumulates (R_f(\tau)) over time using numerical integration methods (such as trapezoidal integration or Simpson integration) to determine the real-time frost thickness (H_f(t)). The frost thickness prediction module compares the calculated (H_f(t)) with a preset frost thickness threshold (H_{th}) (typically set based on system design and operating conditions, such as 2mm). When (H_f(t)>H_{th}), the controller determines that the frost thickness has reached the critical value for triggering defrost and automatically initiates defrost mode.

[0106] This system is designed with three defrost modes: electric heating defrost mode, hot gas defrost mode and combined defrost mode. The controller dynamically selects or combines the following modes according to the frost thickness, environmental conditions and system operating status to achieve efficient defrosting and reduce energy consumption.

[0107] In the electric heating defrost mode, the controller activates the electric heating unit, which directly heats the evaporator surface with electric energy, causing the frost layer to melt quickly. The specific working process is as follows:

[0108] The controller sends a start signal to the electric heating unit to activate the electric heating element (such as a resistance wire or a PTC heater) installed on or near the surface of the evaporator; the electric heating element converts electrical energy into thermal energy and conducts it directly to the evaporator surface, quickly raising the surface temperature to above the melting point of the frost layer (usually 0°C to 5°C); the frost layer melts under the action of high temperature, and the melted water is discharged through the water collection tray at the bottom of the evaporator, completing the defrosting process; the controller monitors the surface temperature of the evaporator through a temperature sensor. When the temperature reaches a preset end value (such as 10°C) or the thickness of the frost layer drops to near zero, the electric heating unit is turned off and normal heating operation is restored.

[0109] In hot gas defrost mode, the controller controls the refrigerant flow direction and uses the high-temperature and high-pressure refrigerant discharged from the compressor for defrosting. The specific working process is as follows:

[0110] The controller opens the hot gas bypass valve, allowing the high-temperature refrigerant discharged from the compressor (usually at a temperature of 60°C to 80°C) to be directly introduced into the evaporator through the bypass pipe. The high-temperature refrigerant releases heat in the evaporator, heating the evaporator surface and gradually melting the frost layer; the melted water is discharged through the water collection tray, and the refrigerant returns to the refrigeration cycle through the throttling device; the controller determines that defrosting is complete by monitoring the evaporator temperature or the thickness of the frost layer. When the frost layer is completely melted or the evaporator temperature reaches the preset value, the bypass valve is closed to resume normal operation.

[0111] The combined defrost mode optimizes defrost efficiency and energy consumption by using hot gas defrost and electric heating defrost in stages. It is particularly suitable for complex working conditions with high frost density and thickness. The specific working process is as follows:

[0112] Stage 1: Hot gas defrosting to reduce frost density

[0113] The controller first activates hot gas defrost mode, opening the bypass valve and introducing high-temperature refrigerant into the evaporator. The high-temperature refrigerant reduces the density of the frost layer through heat conduction, making the frost layer looser and reducing the heat required for subsequent electric heating. Hot gas defrost continues until the frost layer thickness drops to a certain intermediate threshold (e.g., Hf(t)\leq1.5,\text{mm})) or a set time (e.g., 3 to 5 minutes).

[0114] The second stage: electric heating defrost quickly melts the remaining frost

[0115] The controller then activates the electric heating unit to heat the evaporator surface and quickly melt the remaining loose frost layer. Since the frost layer density has been reduced in the first stage, the energy consumption of electric heating is significantly reduced and the defrost time is shortened. The electric heating continues to operate until the frost layer is completely melted or the evaporator temperature reaches the termination value.

[0116] The controller comprehensively monitors the frost layer thickness, evaporator temperature and operating time. After confirming that defrosting is completed, it closes the hot gas bypass valve and the electric heating unit, and the system resumes normal heating operation.

[0117] The advantage of the combined defrost mode is that it takes into account the energy saving of hot gas defrost and the speed of electric heating defrost. It effectively reduces the total energy consumption through phased operation, while shortening the defrost time and reducing the impact on indoor heating.

[0118] In one possible embodiment, an air source heat pump system further includes a wind speed sensor, which is arranged outdoors and configured to detect the outdoor air flow rate and output an air flow rate signal; the controller adjusts the calculation of the frost layer generation rate according to the air flow rate signal to improve the accuracy of the frost layer thickness prediction.

[0119] The evaporator includes a plurality of heat exchange fins, the surface of which is coated with a hydrophilic coating. The hydrophilic coating is used to reduce the adhesion of water droplets on the heat exchange fins, thereby slowing down the frost formation rate and improving the defrosting efficiency.

[0120] The controller also includes a self-learning module, which optimizes the empirical coefficients (k_1) and (k_2) of the dynamic defrost algorithm through a machine learning algorithm based on historical defrost data and environmental parameters to improve the adaptability and accuracy of defrost control.

[0121] The system also includes a defrost effect detection unit, which includes an optical sensor arranged on the surface of the evaporator. The optical sensor is used to detect the residual frost layer on the surface of the evaporator after defrosting and feed back the detection results to the controller. The controller adjusts the control parameters of the next defrost according to the detection results.

[0122] In a specific application of the present invention, the system installs a wind speed sensor on the exterior of the outdoor unit to detect outdoor air velocity in real time and generate a corresponding air speed signal. Air speed is a key environmental parameter that influences the rate of frost formation on the evaporator surface. High air speeds enhance the flushing effect of air on the heat exchange fins, slowing frost accumulation. Conversely, low air speeds prolong the retention time of moist air on the heat exchange fins, accelerating frost formation. The wind speed sensor transmits the detected air speed signal to the controller, which dynamically adjusts the frost formation rate calculation model based on the signal.

[0123] For example, under high wind speed conditions, the controller will appropriately lower the estimated value of the frost layer formation rate, delay the defrost start time, and avoid energy waste caused by premature defrosting; under low wind speed conditions, the controller will increase the estimated value of the frost layer formation rate and trigger the defrost operation in advance to prevent the frost layer from being too thick and affecting the heat exchange efficiency.

[0124] The system's evaporator includes multiple heat exchange fins, each coated with a hydrophilic coating. This coating significantly reduces the adhesion of water droplets to the fin surface by lowering the contact angle. In low-temperature, high-humidity environments, water vapor in the air condenses on the surface of the heat exchange fins to form water droplets. The hydrophobic nature of traditional fin surfaces easily causes water droplets to be retained and quickly freeze into a frost layer. However, the application of a hydrophilic coating allows condensed water droplets to slide off more easily or form a thin and uniform water film, thereby slowing the process of water droplets freezing into a frost layer and reducing the rate of frost formation. Furthermore, the hydrophilic coating can further improve efficiency during the defrosting process. Since the adhesion of the frost layer to the fin surface is reduced, the frost layer is easier to peel off during defrosting, reducing the time and energy required for defrosting. The application of a hydrophilic coating not only extends the defrost cycle but also optimizes the defrost effect, ensuring the rapid recovery of the evaporator's heat exchange performance.

[0125] The controller has a built-in self-learning module, which is based on a machine learning algorithm and uses historical defrost data and environmental parameters (such as outdoor temperature, humidity, air flow rate, etc.) to optimize the empirical coefficients (k_1) and (k_2) of the dynamic defrost algorithm. The empirical coefficient (k_1) is usually related to the calculation of the frost layer formation rate and affects the judgment of the defrost start timing; the empirical coefficient (k_2) is related to the defrost duration or defrost intensity and determines the control strategy of the defrost process.

[0126] The system sets up a defrost effect detection unit on the surface of the evaporator. The unit includes an optical sensor for real-time detection of the residual frost layer on the surface of the evaporator after defrosting. The optical sensor emits a light beam of a specific wavelength and receives the reflected light signal to analyze the optical properties of the heat exchange fin surface (such as reflectivity or scattering intensity) to determine whether the frost layer is completely removed or there is any residue. The detection results are fed back to the controller in a quantitative form, and the controller adjusts the control parameters for the next defrost according to the feedback data.

[0127] For example, if the optical sensor detects that some frost remains after defrosting, the controller will extend the duration of the next defrost or increase the defrost intensity (such as increasing the heat source power). If the controller detects that the defrost is effective, it will shorten the defrost time or reduce the defrost frequency to further save energy. This closed-loop feedback mechanism ensures precise control of the defrost process, avoiding the reduction in heat exchange efficiency caused by residual frost or the energy waste caused by excessive defrosting.

[0128] After the air-source heat pump system starts, the wind speed sensor begins monitoring the outdoor air velocity. The self-learning module loads historical defrost data and initial empirical coefficients (k_1) and (k_2). Based on the wind speed sensor signal, outdoor temperature, humidity, and other parameters, the controller calculates the frost formation rate and predicts the frost thickness in real time. Hydrophilic coatings on the heat exchange fins slow frost accumulation, extending the defrost cycle. When the predicted frost thickness reaches a preset threshold, the controller triggers the defrost operation and activates the defrost heating device.

[0129] During the defrost process, the hydrophilic coating promotes rapid frost removal, reducing defrost time. After defrosting is complete, an optical sensor detects the amount of frost remaining on the evaporator surface and feeds the result back to the controller.

[0130] The self-learning module optimizes the empirical coefficients (k_1) and (k_2) based on the defrost effect feedback and environmental parameters, and updates the defrost algorithm. The controller adjusts the control parameters for the next defrost based on the feedback.

[0131] In one possible implementation, a defrost control method for an air source heat pump system includes the following steps:

[0132] Step 1: Collect outdoor ambient temperature, evaporator surface temperature and relative humidity in real time;

[0133] Step 2: Calculate the frost formation rate using a dynamic defrost algorithm based on the collected ambient temperature, evaporator surface temperature, and relative humidity;

[0134] Step 3: Calculate the real-time frost thickness based on the frost generation rate and the running time integral;

[0135] Step 4: Compare the real-time frost thickness with a preset frost thickness threshold. When the real-time frost thickness reaches or exceeds the threshold, a defrost operation is triggered.

[0136] Step 5: Select a defrost mode according to the ambient temperature and relative humidity. The defrost mode includes electric heating defrost mode, hot air defrost mode, or combined defrost mode.

[0137] Step 6: Execute the defrost operation and adjust the control parameters for the next defrost according to the feedback from the defrost effect detection unit.

[0138] The method also includes a self-learning step, which optimizes the empirical coefficients of the dynamic defrost algorithm by analyzing historical defrost data and environmental parameters using a machine learning algorithm to improve the accuracy and energy efficiency of defrost control.

[0139] In specific applications, embodiments of the present invention use temperature sensors (such as thermocouples or thermistors) installed near the outdoor unit to collect data reflecting the impact of the external environment on frost formation. Temperature sensors attached to the evaporator fins collect data to determine whether the evaporator is within the frosting temperature range. A humidity sensor collects data to reflect the potential impact of water vapor content in the air on the frost formation rate.

[0140] The acquisition frequency of the above parameters is dynamically adjusted according to the system operating status. For example, the acquisition frequency is increased under low temperature and high humidity conditions to ensure that the data can promptly reflect the environmental changes caused by frost formation. The collected data is processed by the analog-to-digital conversion module of the control unit and stored in the system's real-time database, providing a basis for subsequent calculations.

[0141] Based on the collected outdoor ambient temperature, evaporator surface temperature, and relative humidity, the system uses a dynamic defrost algorithm to calculate the frost formation rate. The algorithm comprehensively considers the nonlinear relationship between environmental parameters and frost formation, and quantifies the frost formation rate through a mathematical model. The specific implementation is as follows:

[0142] The dynamic defrost algorithm is based on thermodynamics and mass transfer theory, combined with empirical coefficients, to construct a mathematical expression for the frost formation rate:

[0143] [V_f=k_1\cdot(T_{env}-T_{evap})\cdotRH\cdotk_2], where (V_f) is the frost formation rate, (T_{env}) is the outdoor ambient temperature, (T_{evap}) is the evaporator surface temperature, (RH) is the relative humidity, and (k_1) and (k_2) are empirical coefficients.

[0144] The algorithm dynamically adjusts empirical coefficients based on real-time collected parameters to adapt to frost formation characteristics under different climate conditions. The algorithm is implemented through the fast computing module of the embedded controller, with the calculation cycle synchronized with the data collection frequency to ensure the real-time frost formation rate.

[0145] After obtaining the frost formation rate, the system calculates the real-time frost thickness by integrating the running time:

[0146] The frost thickness (D_f) is calculated using the following formula: [D_f = \int_{t_}^{t}V_f(t),dt], where (t_) is the time the system starts running or the end of the last defrost, (t) is the current time, and (V_f(t)) is the time-varying function of the frost formation rate. The system uses numerical integration methods (such as the trapezoidal method or the Simpson method) to calculate the frost thickness in real time within an embedded controller. The integration time step is dynamically adjusted based on the magnitude of the frost formation rate to balance accuracy and efficiency.

[0147] To improve calculation accuracy, the system takes into account real-time changes in the evaporator surface temperature and performs error correction on the integral results. For example, when the evaporator surface temperature approaches 0.04°C, the frost formation rate decreases due to local melting, and the system adjusts the calculation model accordingly.

[0148] The frost layer thickness threshold is pre-set based on the air source heat pump system's design parameters (such as evaporator area and heating power) and the operating environment. For example, under typical low temperature and high humidity conditions, the threshold can be set between 0.5mm and 1.0mm. When the real-time frost layer thickness (D_f) reaches or exceeds the threshold (D_{th}) (i.e., (D_f \geqD_{th})), the control unit generates a defrost trigger signal.

[0149] To avoid energy loss caused by frequent defrosting, the system introduces a time protection mechanism. For example, within a certain period of time (such as 30 minutes) after the defrost is triggered, even if the frost layer thickness reaches the threshold again, a new defrost operation will not be triggered.

[0150] According to the outdoor ambient temperature and relative humidity, the system dynamically selects the appropriate defrost mode, including electric heating defrost mode, hot gas defrost mode or combined defrost mode. The specific selection logic is as follows:

[0151] Electric heating defrost mode: Suitable for extremely low ambient temperature (e.g. below -10°C) or low relative humidity. The system directly heats the evaporator surface by activating the electric heating element to quickly melt the frost layer.

[0152] Hot gas defrost mode: Suitable for conditions with high ambient temperature (e.g. -5°C to 12°C) and moderate humidity. The system switches the four-way valve to introduce high-temperature and high-pressure refrigerant into the evaporator, using hot gas to melt the frost layer.

[0153] Combined defrost mode: Under conditions of large fluctuations in ambient temperature and humidity, the system combines the advantages of electric heating and hot gas defrost, first reducing the thickness of the frost layer through hot gas defrost, and then completing the defrost thoroughly through electric heating.

[0154] Mode switching: The system dynamically adjusts the defrost mode based on real-time environmental parameters. For example, when the ambient temperature drops from -5°C to -10°C, the system can automatically switch from hot gas defrost to electric heating defrost.

[0155] After the defrost operation is triggered, the system performs defrost according to the selected defrost mode and adjusts the control parameters for the next defrost based on the feedback from the defrost effect detection unit.

[0156] Defrost execution: The control unit coordinates the operation of related components (such as electric heaters, four-way valves, fans, etc.) according to the selected mode. For example, in hot gas defrost mode, the system suspends heating operation, starts the compressor, and switches the refrigerant flow direction.

[0157] Effect detection: The defrost effect detection unit assesses defrost completion by monitoring the evaporator surface temperature, pressure, or using a visual sensor (such as an infrared camera). For example, defrost is considered complete when the evaporator surface temperature remains above 2°C and there is no residual frost.

[0158] Parameter adjustment: Based on the defrost effect, the system adjusts control parameters (such as frost thickness threshold and defrost time). For example, if the system detects that the defrost time is too long, it will lower the frost thickness threshold for the next time to trigger defrost earlier.

[0159] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0160] The present invention and its embodiments are described above. This description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if a person skilled in the art is inspired by this and, without departing from the purpose of the present invention, designs structures and embodiments similar to this technical solution without inventiveness, they shall fall within the scope of protection of the present invention.

Claims

1. An air source heat pump system, characterized in that: include: The compressor, condenser, throttling device and evaporator are connected in sequence through refrigerant pipes to form a closed loop for achieving cooling or heating functions; An ambient temperature sensor is installed outdoors and is configured to detect the outdoor ambient temperature in real time and output an ambient temperature signal; an evaporator temperature sensor, disposed on the surface of the evaporator, configured to detect the evaporator surface temperature in real time and output a surface temperature signal; a humidity sensor, disposed outdoors, configured to detect relative humidity of outdoor air and output a humidity signal; a controller electrically connected to the ambient temperature sensor, the evaporator temperature sensor, and the humidity sensor, the controller comprising a memory and a processor, the memory storing a dynamic defrost control program, the processor executing the program to dynamically calculate a frost layer formation rate according to the ambient temperature, the evaporator surface temperature, and the relative humidity, and adaptively adjust defrost control parameters based on the frost layer formation rate, the defrost control parameters comprising a defrost start time, a defrost duration, and a defrost mode, so as to start or stop a defrost operation; a defrost device comprising an electric heating unit and a hot gas bypass unit disposed near the evaporator, the electric heating unit heating the evaporator surface by electric energy, the hot gas bypass unit directing high-temperature refrigerant discharged from the compressor to the evaporator via a bypass valve and a bypass line, the defrost device performing a defrost operation under instructions from the controller; The controller uses a dynamic defrost algorithm based on the frost formation rate. The algorithm compares a preset frost thickness threshold with the real-time calculated frost thickness. When the real-time frost thickness reaches the threshold, the defrost operation is triggered, thereby achieving precise defrosting, reducing system energy consumption and improving heating efficiency. The dynamic defrost algorithm combines the ambient temperature, relative humidity and evaporator surface temperature to calculate the frost formation rate through a mathematical model. The mathematical model is: [R_f=k_1\cdot(T_a-T_e)\cdotRH+k_2\cdotv_a] Wherein, (R_f) is the frost formation rate, (T_a) is the ambient temperature, (T_e) is the evaporator surface temperature, (RH) is the relative humidity, (v_a) is the outdoor air flow rate, (k_1) and (k_2) are empirical coefficients. The algorithm optimizes the defrost control accuracy by adaptively adjusting the empirical coefficients.

2. The air source heat pump system according to claim 1, characterized in that: The controller further includes a frost thickness prediction module, which calculates the real-time frost thickness based on the frost generation rate and the running time integral. The integral formula is: [H_f(t)=\int_^tR_f(\tau),d\tau] Wherein, (H_f(t)) is the real-time frost thickness, (t) is the system operation time, and (R_f(\tau)) is the instantaneous frost generation rate; the frost thickness prediction module compares the calculated real-time frost thickness with a preset threshold. When the real-time frost thickness exceeds the threshold, the controller triggers the defrost operation.

3. The air source heat pump system according to claim 1, characterized in that: The defrost modes include electric heating defrost mode, hot gas defrost mode and combined defrost mode; In the electric heating defrost mode, the controller activates the electric heating unit to directly heat the evaporator surface by electric energy to melt the frost layer; In the hot gas defrost mode, the controller opens the bypass valve to introduce the high-temperature refrigerant discharged from the compressor into the evaporator for defrosting; In the combined defrost mode, the controller activates the electric heating unit and the hot gas bypass unit in stages according to the thickness of the frost layer, first reducing the density of the frost layer through hot gas defrosting, and then quickly melting the remaining frost layer through electric heating defrosting, thereby optimizing defrost efficiency and energy consumption.

4. The air source heat pump system according to claim 1, characterized in that: The controller selects the defrost mode according to the ambient temperature and relative humidity, wherein: When the ambient temperature is lower than a first temperature threshold and the relative humidity is higher than a first humidity threshold, the controller preferentially selects the combined defrost mode; When the ambient temperature is higher than a first temperature threshold but lower than a second temperature threshold, the controller selects the hot gas defrost mode; When the ambient temperature is higher than a second temperature threshold, the controller selects the electric heating defrost mode; The first temperature threshold, the second temperature threshold, and the first humidity threshold are stored in the memory and can be adjusted by the controller according to actual application scenarios.

5. The air source heat pump system according to claim 1, characterized in that: The system also includes a wind speed sensor, which is arranged outdoors and configured to detect the outdoor air flow rate and output an air flow rate signal; the controller adjusts the calculation of the frost layer generation rate according to the air flow rate signal to improve the accuracy of the frost layer thickness prediction.

6. The air source heat pump system according to claim 1, characterized in that: The evaporator includes a plurality of heat exchange fins, the surfaces of which are coated with a hydrophilic coating. The hydrophilic coating is used to reduce the adhesion of water droplets on the heat exchange fins, thereby slowing down the rate of frost formation and improving defrosting efficiency.

7. The air source heat pump system according to claim 1, characterized in that: The controller also includes a self-learning module, which optimizes the empirical coefficients (k_1) and (k_2) of the dynamic defrost algorithm through a machine learning algorithm based on historical defrost data and environmental parameters to improve the adaptability and accuracy of defrost control.

8. The air source heat pump system according to claim 1, characterized in that: The system also includes a defrost effect detection unit, which includes an optical sensor arranged on the surface of the evaporator. The optical sensor is used to detect the residual frost layer on the surface of the evaporator after defrosting, and feed back the detection result to the controller. The controller adjusts the control parameters of the next defrost according to the detection result.

9. The defrost control method for an air source heat pump system according to any one of claims 1 to 8, characterized in that: The following steps are involved: Step 1: Collect outdoor ambient temperature, evaporator surface temperature and relative humidity in real time; Step 2: Calculate the frost layer formation rate using the dynamic defrost algorithm based on the collected ambient temperature, evaporator surface temperature and relative humidity; Step 3: Calculating the real-time frost layer thickness based on the frost layer generation rate and the running time integral; Step 4: comparing the real-time frost thickness with a preset frost thickness threshold, and triggering a defrost operation when the real-time frost thickness reaches or exceeds the threshold; Step 5: Select a defrost mode according to the ambient temperature and relative humidity, wherein the defrost mode includes an electric heating defrost mode, a hot air defrost mode, or a combined defrost mode; Step 6: Execute the defrost operation and adjust the control parameters for the next defrost according to the feedback from the defrost effect detection unit.

10. The defrost control method of the air source heat pump system according to claim 9, characterized in that: The method also includes a self-learning step, which optimizes the empirical coefficients of the dynamic defrost algorithm by analyzing historical defrost data and environmental parameters using a machine learning algorithm to improve the accuracy and energy efficiency of defrost control.

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