Control methods, devices, storage media and electronic equipment for air source heat pump units

Abstract

This application discloses a control method, device, storage medium, and electronic equipment for an air source heat pump unit, relating to the field of heat pump technology. The method includes: analyzing and processing user behavior data and outdoor ambient temperature to obtain a predicted user pattern, the predicted user pattern reflecting the user's adjustment method for the air source heat pump unit; analyzing and processing the unit's operating data to obtain a predicted unit state; determining a defrost control action based on the predicted user pattern and the predicted unit state; and performing operational control of the air source heat pump unit according to the defrost control action. This application can effectively improve the defrost reliability of air source heat pump units.

Description

Technical Field

[0001] This application relates to the field of heat pump technology, specifically to a control method, device, storage medium, and electronic equipment for an air source heat pump unit. Background Technology

[0002] Traditional air source heat pump units typically employ defrosting strategies based on fixed time or temperature thresholds. This can lead to problems such as forced defrosting when there is no frost or defrosting only triggered by heavy frost buildup. Furthermore, sudden load changes caused by user adjustments result in large fluctuations in compressor frequency, leading to sluggish defrosting response. Therefore, current defrosting strategies for air source heat pump units suffer from poor defrosting reliability. Summary of the Invention

[0003] This application provides a control scheme for an air source heat pump unit, which can effectively improve the defrosting reliability of the air source heat pump unit.

[0004] The embodiments of this application provide the following technical solutions: According to one embodiment of this application, a control method for an air source heat pump unit includes: analyzing and processing user behavior data and outdoor ambient temperature to obtain an estimated user pattern, the estimated user pattern reflecting the user's adjustment method for the air source heat pump unit; analyzing and processing the unit operation data of the air source heat pump unit to obtain an estimated unit state; determining a defrost control action based on the estimated user pattern and the estimated unit state; and performing operation control on the air source heat pump unit according to the defrost control action.

[0005] According to one embodiment of this application, a control device for an air source heat pump unit is provided. The device includes: a pattern recognition module, configured to: analyze and process user behavior data and outdoor ambient temperature to obtain an estimated user pattern, the estimated user pattern reflecting the user's adjustment method for the air source heat pump unit; a status recognition module, configured to: analyze and process the unit operation data of the air source heat pump unit to obtain an estimated unit status; an action determination module, configured to: determine a defrost control action based on the estimated user pattern and the estimated unit status; and a unit control module, configured to: perform operation control on the air source heat pump unit according to the defrost control action.

[0006] According to another embodiment of this application, a storage medium stores a computer program thereon, which, when executed by a processor of an electronic device, causes the electronic device to perform the methods described in the embodiments of this application.

[0007] According to another embodiment of this application, an electronic device may include: a memory storing a computer program; and a processor reading the computer program stored in the memory to execute the methods described in the embodiments of this application.

[0008] According to another embodiment of this application, a computer program product or computer program includes computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the electronic device to perform the methods provided in the various optional implementations described in the embodiments of this application.

[0009] In this embodiment, user behavior data and outdoor ambient temperature are analyzed and processed to obtain an estimated user pattern, which reflects the user's adjustment method for the air source heat pump unit; the unit operation data of the air source heat pump unit is analyzed and processed to obtain an estimated unit status; defrost control actions are determined based on the estimated user pattern and the estimated unit status; and the air source heat pump unit is operated and controlled according to the defrost control actions.

[0010] In this embodiment of the application, the predicted user pattern can reflect the most likely adjustment method of the user to the air source heat pump unit, thereby enabling timely detection of sudden changes in user adjustment; the predicted unit status can reflect the most likely unit status of the air source heat pump unit, thereby effectively taking into account the frosting situation of the air source heat pump unit; therefore, by combining the predicted user pattern and the predicted unit status to determine the defrosting control action, the appropriate defrosting control action can be determined by taking into account both sudden changes in user adjustment and frosting situation, which can avoid unreasonable defrosting problems and respond to defrosting in a timely manner when the load changes, thus effectively improving the defrosting reliability of the air source heat pump unit overall. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 A flowchart illustrating a control method for an air source heat pump unit according to an embodiment of this application is shown.

[0013] Figure 2 A flowchart illustrating pattern determination according to an embodiment of this application is shown.

[0014] Figure 3A flowchart illustrating the state determination process according to an embodiment of this application is shown.

[0015] Figure 4 A flowchart illustrating a pattern determination process according to an embodiment of this application is shown in one scenario.

[0016] Figure 5 A flowchart illustrating a state determination process according to an embodiment of this application is shown in one scenario.

[0017] Figure 6 A block diagram of a control device for an air source heat pump unit according to an embodiment of this application is shown.

[0018] Figure 7 A block diagram of an electronic device according to an embodiment of this application is shown. Detailed Implementation

[0019] The present disclosure will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the embodiments provided herein are merely illustrative of the present disclosure and are not intended to limit the present disclosure. Furthermore, the embodiments provided below are some embodiments for implementing the present disclosure, and not all embodiments for implementing the present disclosure. Unless otherwise specified, the technical solutions described in the embodiments of the present disclosure can be implemented in any combination. It should be noted that, in the embodiments of this disclosure, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a method or apparatus that includes a list of elements includes not only the elements expressly described, but also other elements not expressly listed, or elements inherent to implementing the method or apparatus. Without further limitations, an element defined by the phrase "comprising a..." does not exclude the presence of other related elements (e.g., steps in the method or units in the apparatus; for example, a unit may be a portion of circuitry, a portion of a processor, a portion of a program or software, etc.) in the method or apparatus that includes that element. For example, the control method for an air source heat pump unit provided in this disclosure includes a series of steps. However, the control method for an air source heat pump unit provided in this disclosure is not limited to the steps described. Similarly, the control device for an air source heat pump unit provided in this disclosure includes a series of units. However, the device provided in this disclosure is not limited to the units explicitly described, but may also include units that need to be set up to obtain relevant information or to process information. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of this disclosure. It is understood that in the specific implementation of this application, relevant data is involved. When the embodiments in this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0020] Traditional air source heat pump units typically employ defrosting strategies based on fixed time intervals or temperature thresholds. This can lead to problems such as forced defrosting when there is no frost or defrosting only triggered by heavy frost buildup. Furthermore, sudden changes in user demand causing load fluctuations result in large variations in compressor frequency adjustment and delayed defrosting response. Therefore, current defrosting strategies for air source heat pump units suffer from poor defrosting reliability.

[0021] To address these issues, this application provides a control scheme for an air source heat pump unit, which can effectively improve the defrosting reliability of the air source heat pump unit.

[0022] The following describes in detail the relevant embodiments of the control scheme for the air source heat pump unit provided in this application. The air source heat pump unit can be a modular unit, a water heater, a multi-split unit, or other unit that utilizes an air source heat pump.

[0023] Figure 1 A flowchart illustrating a control method for an air source heat pump unit according to an embodiment of this application is shown. The execution entity of this control method can be a control module with processing capabilities. The control module can be installed in electronic devices such as the air source heat pump unit, remote control, wired controller, mobile phone, computer, smartwatch, and other home appliances. The control module may include at least a memory and a processor. In some embodiments, the control module can be installed on a server (such as a cloud server or physical server) for remote control of the air source heat pump unit.

[0024] In one embodiment of this application, the control module, which serves as the execution body of the control method for the air source heat pump unit, is specifically disposed within the air source heat pump unit. The control module may include a processor and a memory, i.e., the air conditioner includes the processor and memory, with the memory storing a computer program. Thus, the processor in the air source heat pump unit can read the computer program stored in the memory to execute the methods of the various embodiments of this application.

[0025] like Figure 1 As shown, the control method of the air source heat pump unit may include steps S110 to S140.

[0026] Step S110: Analyze and process user behavior data and outdoor ambient temperature to obtain the predicted user pattern. The predicted user pattern reflects the user's adjustment method for the air source heat pump unit. Step S120: Based on the analysis and processing of the unit operation data of the air source heat pump unit, the estimated unit status is obtained; Step S130: Determine the defrosting control action based on the estimated user mode and the estimated unit status; Step S140: Perform operation control of the air source heat pump unit according to the defrosting control action.

[0027] At time t, user behavior data and outdoor ambient temperature can be acquired. Based on this data, analysis and processing are performed to obtain the estimated user mode that the user is most likely to switch to at time t (i.e., the estimated user mode). The estimated user mode reflects the user's most likely adjustment method to the air source heat pump unit at time t. The user behavior data reflects the user's adjustment behavior to the air source heat pump unit, such as the amount of temperature change set and the frequency of temperature adjustments.

[0028] In one example, the estimated user mode can be one of three user modes: Mode 1 (also known as Normal Mode), Mode 2 (also known as Economic Mode), and Mode 3 (also known as Fast Response Mode). Mode 1 reflects that the user does not frequently adjust the set temperature (i.e., the set temperature is stable, such as when the user is most likely to maintain the set temperature at time t consistent with or close to the previous set temperature); Mode 2 reflects that the user lowers the set temperature (such as when the user is most likely to lower the set temperature to a low-power temperature at time t) or enables the low-electricity-price period operation mechanism (i.e., start the unit during a period of low electricity price); Mode 3 reflects that the user suddenly raises the set temperature (such as when the user is most likely to significantly raise the set temperature in a short period of time after time t).

[0029] Understandably, in other examples, more user modes can be set according to the adjustment method, and the estimated user mode can be one of more user modes.

[0030] Furthermore, the unit operation data of the air source heat pump unit can be obtained at time t. Based on the analysis and processing of the unit operation data of the air source heat pump unit, the most likely unit state that the air source heat pump unit will reach at time t (i.e., the estimated unit state) can be obtained. The estimated unit state is the estimated unit state that the air source heat pump unit is most likely to reach at time t.

[0031] In one example, the estimated unit status can be one of the following: normal operation, frosting risk, load surge, or standby / degradation. Normal operation means the air source heat pump unit is operating efficiently within its optimal operating range. Frosting risk means the air source heat pump unit is at risk of frosting; the evaporator may be frosted or already slightly frosted. Load surge means a sudden increase in user demand causes the air source heat pump unit's compressor to be overloaded. Standby / degradation means the air source heat pump unit is operating at low load or its performance is degraded.

[0032] Understandably, in other examples, more crew states can be defined, and the estimated crew state can be one of more user states.

[0033] Furthermore, defrosting control actions can be pre-defined in the action mapping table for different combinations of user modes and unit states. Then, based on the estimated combinations of user modes and unit states analyzed in this study, the corresponding defrosting control actions can be determined in the action mapping table, and the air source heat pump unit can be operated according to these determined defrosting control actions.

[0034] In this embodiment of the application, the predicted user pattern can reflect the most likely adjustment method of the user to the air source heat pump unit, thereby enabling timely detection of sudden changes in user adjustment; the predicted unit status can reflect the most likely unit status of the air source heat pump unit, thereby effectively taking into account the frosting situation of the air source heat pump unit; therefore, by combining the predicted user pattern and the predicted unit status to determine the defrosting control action, the appropriate defrosting control action can be determined by taking into account both sudden changes in user adjustment and frosting situation, which can avoid unreasonable defrosting problems and respond to defrosting in a timely manner when the load changes, thus effectively improving the defrosting reliability of the air source heat pump unit overall.

[0035] The following description Figure 1 Further optional specific embodiments are provided for the steps performed when controlling an air source heat pump unit as described in the example.

[0036] See Figure 2 In one embodiment, step S110, which analyzes and processes user behavior data and outdoor ambient temperature to obtain an estimated user pattern, may include: step S210, calculating the pattern entry probability based on user behavior data and outdoor ambient temperature; and step S220, determining the estimated user pattern based on the pattern entry probability.

[0037] At time t, the mode entry probability is calculated based on user behavior data and outdoor ambient temperature. This mode entry probability represents the probability of entering different user modes at time t. Based on the mode entry probability, the most likely user mode for the user to switch to at time t can be accurately determined (i.e., the predicted user mode).

[0038] Optionally, in other embodiments, step S110, analyzing and processing user behavior data and outdoor ambient temperature to obtain a predicted user pattern, may include: querying a user pattern that matches the user behavior data and outdoor ambient temperature from a preset pattern query table, and using the queried user pattern as the predicted user pattern.

[0039] Furthermore, in one embodiment, step S210, calculating the mode entry probability based on user behavior data and outdoor ambient temperature, may specifically include: generating a first observation vector based on user behavior data and outdoor ambient temperature; obtaining a first state transition matrix, which includes a first transition probability between different user modes; obtaining a first Gaussian distribution parameter; calculating a first observation probability matrix based on the first observation vector, the first Gaussian distribution parameter, and the first state transition matrix; and calculating the mode entry probability based on the first observation probability matrix, the historical first probability distribution, and the first transition probability.

[0040] The first observation vector is generated based on user behavior data and outdoor ambient temperature. This involves combining user behavior data and outdoor ambient temperature into a combined vector (the first observation vector). Specifically, in one example, user behavior data may include the set temperature change (°C / min) and the temperature adjustment frequency (times / h), where the set temperature change is the amount of change in the set temperature, and the temperature adjustment frequency is the frequency with which the user has adjusted the set temperature over a period of time. In this case, the first observation vector... It can be as follows: ; in, That is, set the amount of temperature change. The set temperature at time t. The set temperature is the historical time t-1 before time t. The time difference between t and t-1 can be set according to the actual situation. That is, the frequency of temperature adjustment; That is, the outdoor ambient temperature.

[0041] Then, obtain the first state transition matrix. The first state transition matrix This includes the first transition probability between different user modes. Specifically, in one example, It includes three different user modes (such as the first mode). Second Mode and the third mode The first transition probability between ) is, at this time, It can be as follows: ; in, , indicating from the i-th user mode Switch to the j-th user mode The first transition probability. Where, The initial values ​​of each first transition probability can be obtained by statistically analyzing the historical user operation data of the air source heat pump unit, and the sum of each row in the matrix is ​​1.

[0042] Then, the first Gaussian distribution parameters are obtained, and the first observation probability matrix is ​​calculated based on the first observation vector, the first Gaussian distribution parameters, and the first state transition matrix. The first observation probability matrix includes the first observation vector observed in each user mode. The probability density. The first Gaussian distribution parameter can be preset, specifically set through statistical analysis of historical user operation data. The first Gaussian distribution parameter can include preset parameters for the Gaussian distribution included in each user mode (each Gaussian distribution can correspond to a user operation scenario, such as the operation of the user regulating the unit under different weather conditions or time periods).

[0043] Specifically, in one concrete example, the first Gaussian distribution parameter may include: the number K of Gaussian distributions for each user mode (each Gaussian distribution can correspond to a user operation scenario), and the weight of the k-th Gaussian distribution for each user mode. (All under the same user mode) (sum of 1), the average of the k-th Gaussian distribution for each user pattern The covariance of the k-th Gaussian distribution under each user pattern , Can describe The range of the first observation probability matrix. The specific implementation is as follows: ; in, In user mode The following observations The probability density; Let be a Gaussian distribution function, given by the mean. Covariance Decide.

[0044] Finally, based on the first observation probability matrix, the historical first probability distribution, and the first transition probability, the mode entry probability can be accurately obtained. Specifically, in one example, at time t, based on the first observation probability matrix... Historical first probability distribution and the first transition probability Calculate the state probability distribution The details are as follows: j=1, 2, 3; in, That is, the first historical probability distribution. It can represent the probability of entering the mode corresponding to the i-th user mode at historical time t-1; That is, the probability of entering the mode corresponding to the j-th user mode at time t.

[0045] In this embodiment, the mode entry probability can be calculated more accurately based on the first observation probability matrix, the historical first probability distribution, and the first transition probability.

[0046] Optionally, in other embodiments, step S210, calculating the pattern entry probability based on user behavior data and outdoor ambient temperature, may include: using a pre-trained deep learning model such as a large language model to analyze and calculate the user behavior data and outdoor ambient temperature to obtain the pattern entry probability.

[0047] Furthermore, in one embodiment, user behavior data includes the set temperature change amount and temperature adjustment frequency; the mode entry probability includes the first mode probability. Second mode probability and the probability of the third mode Step S220: Determine the estimated user pattern based on the pattern entry probability, which may include the following three cases: When the "first mode determination condition" is met, that is, when the probability of the first mode is... The probability P of being greater than or equal to the preset pattern 设 Set the absolute value of the temperature change | | Less than the predetermined absolute value T 绝对 Temperature adjustment frequency Less than or equal to the predetermined first frequency N 预定1 And outdoor ambient temperature Located within the predetermined temperature range T 范围 If so, the estimated user mode is the first mode. ; When the "second mode determination condition" is met, that is, when the probability of the second mode is... The probability P of being greater than or equal to the preset pattern 设 Set temperature change amount Less than the predetermined first change amount ΔT1 or currently in a low electricity price period, and the temperature adjustment frequency Greater than or equal to the predetermined second frequency N 预定2 When this condition is met, the user pattern is predicted to be the second pattern. ; When the "third mode determination condition" is met, that is, when the probability of the third mode is... The probability P of being greater than or equal to the preset pattern 设 Set temperature change amount Greater than the predetermined second change amount ΔT2, temperature adjustment frequency Greater than or equal to the predetermined third frequency N 预定3 And outdoor ambient temperature Less than the predetermined ambient temperature T 环 When this condition is met, the user mode is predicted to be the third mode. .

[0048] In this embodiment, according to the above three mode determination conditions, when the set temperature change, temperature adjustment frequency and mode entry probability all meet the corresponding conditions, the estimated user mode is determined as the corresponding user mode. The multi-dimensional comprehensive judgment is made by combining the set temperature change, temperature adjustment frequency and mode entry probability to further improve the accuracy of the estimated user mode.

[0049] Among them, P 设 T 绝对 N 预定1 T 范围 , ΔT1, N 预定2 , ΔT2, N 预定3 T 环 It can be set according to the actual situation. Specifically, in a preferred embodiment of this application, P is set between 75% and 90%; T 绝对 =0.5℃ / min; N 预定1 =2;T 范围 For |T out -20℃∣<5℃; ΔT1=-1℃ / min; N 预定2 =3; ΔT2=2℃ / min; N 预定3 =5;T 环 =0℃. At this time, when ≥P 设 、 | If | < 0.5℃ / min and Nadj ≤ 2, the predicted user mode is mode 1. ;when ≥P 设 , If the current rate is <-1℃ / min or determined to be a low-electricity-price period (e.g., a period when the electricity price is lower than the predetermined price), and Nadj ≥ 3, the estimated user pattern is the second mode. ;when ≥P 设 , >2℃ / min, Nadj≥5 and <0℃, estimated user mode is third mode. .

[0050] See Figure 3 In one embodiment, step S120, which involves analyzing and processing the unit operation data of the air source heat pump unit to obtain the estimated unit state, may include: step S310, calculating the probability of reaching the state based on the unit operation data; and step S320, determining the estimated unit state based on the probability of reaching the state.

[0051] At time t, the probability of reaching a given state is calculated based on the unit's operating data. This probability represents the likelihood of reaching different unit states at time t. Based on this probability, the most likely unit state at time t can be accurately determined (i.e., the predicted unit state).

[0052] Optionally, in other embodiments, step S120, based on the analysis and processing of the unit operation data of the air source heat pump unit to obtain the estimated unit status, may include: querying the unit status that matches the unit operation data from a preset status query table, and using the queried unit status as the estimated unit status.

[0053] Furthermore, in one embodiment, step S310, calculating the state attainment probability based on unit operation data, may specifically include: generating a second observation vector based on unit operation data; obtaining a second state transition matrix, which includes second transition probabilities between different states; obtaining a second Gaussian distribution parameter and a second data range; calculating a second observation probability matrix based on the second observation vector, the second Gaussian distribution parameter, the second data range, and the second state transition matrix; and calculating the state attainment probability based on the second observation probability matrix, the historical second probability distribution, and the second transition probability.

[0054] A second observation vector is generated based on unit operation data. That is, combining the unit operation data into a combined vector (second observation vector). Specifically, in one particular example, unit operating data may include real-time compressor power Pcomp, evaporator inlet and outlet temperature difference ΔTe, defrost frequency fde, and compressor amplitude Ab. At this time, the second observation vector... It can be as follows: ; Among them, the real-time power of the compressor Pcomp can be calculated by detecting the compressor current to determine the load size; the temperature difference between the inlet and outlet of the evaporator ΔTe is the difference between the inlet and outlet temperatures of the evaporator; the defrosting frequency fde is the ratio of the number of defrosts within a predetermined time to the predetermined time; and the compressor amplitude Ab is the vibration amplitude of the compressor, which can determine the compressor's lifespan or wear level.

[0055] Then, obtain the second state transition matrix. The second state transition matrix includes the second transition probabilities between different unit states. Specifically, in one example, It includes four different unit states (such as normal operating state). Frosting risk status Sudden load increase Standby / Degradation Status The second transition probability between ) is, at this time, It can be as follows: ; in, , indicating the state of the i-th unit Transition to the j-th unit state The second transition probability. Wherein, The initial values ​​of each second transition probability can be obtained by statistically analyzing the historical user operation data of the air source heat pump unit, and the sum of each row in the matrix is ​​1.

[0056] Then, the second Gaussian distribution parameters are obtained, and the second observation probability matrix is ​​calculated based on the second observation vector, the second Gaussian distribution parameters, and the second state transition matrix. The second observation probability matrix includes the second observation vector observed in each unit state. The probability density. The second Gaussian distribution parameter can be preset, specifically set through statistical analysis of historical user operation data. The second Gaussian distribution parameter can include preset parameters for the Gaussian distribution included in each unit state (each Gaussian distribution can correspond to a user operation scenario, such as user adjustments to the unit under different weather conditions or time periods).

[0057] Specifically, in one concrete example, the second Gaussian distribution parameter may include: the number N of Gaussian distributions for each unit state (each Gaussian distribution can correspond to a user operation scenario), and the weight of the nth Gaussian distribution for each unit state. (All units under the same operating conditions) The sum of all values ​​is 1), the average value of the nth Gaussian distribution under each unit condition. The covariance of the nth Gaussian distribution under each unit condition , Can describe The range of the second observation probability matrix. The specific implementation is as follows: ; in, Indicates the status of the unit. The following observations The probability density; Let be a Gaussian distribution function, given by the mean. Covariance Decide.

[0058] Finally, based on the second observation probability matrix, the historical second probability distribution, and the second transition probability, the probability of reaching the state can be accurately calculated. Specifically, in one example, at time t, based on the second observation probability matrix... Historical second probability distribution and the second transition probability Calculate the state probability distribution The details are as follows: j=1, 2, 3; in, That is, the second historical probability distribution. It can represent the probability of the i-th unit state being reached at historical time t-1; That is, the probability of the j-th unit state being reached at time t.

[0059] In this embodiment, the probability of reaching a state can be calculated more accurately based on the second observation probability matrix, the historical second probability distribution, and the second transition probability.

[0060] Optionally, in other embodiments, step S310, calculating the probability of state attainment based on unit operation data, may specifically include: using a pre-trained deep learning model such as a large language model to analyze and calculate the unit operation data to obtain the probability of state attainment.

[0061] Furthermore, in one embodiment, step S320, the probability of reaching a state includes the probability of a first state. Second state probability Third state probability and the probability of the fourth state Based on the probability of reaching a state, the predicted unit state is determined, which may specifically include: when the probability of reaching the first state... If the probability of the second state is greater than the preset state probability E, the estimated state of the unit is normal operation; when the probability of the second state is greater than the preset state probability E, the estimated state of the unit is normal operation. If the probability is greater than the preset state probability E, the estimated unit state is a frosting risk state; when the third state probability is greater than the preset state probability E, the estimated unit state is a frosting risk state. If the probability is greater than the preset state probability E, the estimated unit state is a load surge state; when the fourth state probability is greater than the preset state probability E, the estimated unit state is a load surge state. If the probability is greater than the preset state probability E, the estimated state of the unit is standby / degradation. The preset state probability E can be set according to the actual situation. For example, in a preferred example, E is between 65% and 85%.

[0062] In one embodiment, step S130, determining the defrosting control action based on the estimated user mode and the estimated unit status, may include: if the estimated user mode is a first mode and the estimated unit status is a frosting risk state, the defrosting control action includes maintaining the compressor frequency unchanged, shortening the defrosting cycle, and setting a first temperature fluctuation range; if the estimated user mode is the first mode and the estimated unit status is a load surge state, the defrosting control action includes increasing the compressor frequency to the rated frequency, running the fan at full speed, and setting a second temperature fluctuation range; wherein, the first mode reflects that the user does not frequently adjust the set temperature. The first temperature fluctuation range is greater than the second temperature fluctuation range.

[0063] The first mode and the frost risk state conflict with the usual defrosting control strategy, as do the first mode and the load surge state. However, in this embodiment, the defrosting control actions corresponding to both the first mode and the frost risk state are determined, as well as the defrosting control actions corresponding to both the first mode and the load surge state. By controlling the operation of the air source heat pump unit according to these defrosting control actions, the conflicts can be reliably avoided, and the defrosting reliability of the air source heat pump unit can be further improved.

[0064] Specifically, in a preferred example, the defrosting control actions corresponding to the first mode and the frost risk state and the load surge state can be shown in the table below.

[0065]

[0066] Furthermore, in one embodiment, the defrosting control action may further include: if the estimated user mode is a first mode and the estimated unit state is a normal operating state, then the defrosting control action includes maintaining the compressor frequency unchanged, maintaining a preset standardized defrosting cycle, and setting a third temperature fluctuation range; if the estimated user mode is a first mode and the estimated unit state is a standby / degradation state, then the defrosting control action includes shutting down the air source heat pump unit. The third temperature fluctuation range is smaller than the second temperature fluctuation range.

[0067] There is no conflict between the first mode and the normal operation state according to the usual defrosting control strategy, and there is no conflict between the first mode and the standby / degradation state according to the usual defrosting control strategy. In this embodiment, the defrosting control action corresponding to both the first mode and the normal operation state is determined, as well as the defrosting control action corresponding to both the first mode and the standby / degradation state. The air source heat pump unit is operated according to the defrosting control action, which can further effectively improve the defrosting reliability of the air source heat pump unit.

[0068] Specifically, in a preferred example, the defrosting control actions corresponding to the first mode and the normal operation state and the standby / degradation state are shown in the table below.

[0069]

[0070] In one embodiment, step S130, determining the defrosting control action based on the estimated user mode and the estimated unit status, may include: if the estimated user mode is a second mode and the estimated unit status is a frosting risk state, the defrosting control action includes adjusting the compressor frequency to a predetermined first frequency, keeping the defrosting cycle unchanged, and setting a first temperature fluctuation range, wherein the predetermined first frequency is less than the rated frequency; if the estimated user mode is a second mode and the estimated unit status is a load surge state, the defrosting control action includes increasing the compressor frequency to the rated frequency, operating the fan at a predetermined first speed, and setting a first temperature fluctuation range; wherein the second mode reflects the user lowering the set temperature or activating the low electricity price period operation mechanism.

[0071] The second mode and the frost risk state conflict with the usual defrosting control strategy, as do the second mode and the load surge state. However, in this embodiment, the defrosting control actions corresponding to both the second mode and the frost risk state are determined, as well as the defrosting control actions corresponding to both the second mode and the load surge state. By controlling the operation of the air source heat pump unit according to these defrosting control actions, the conflicts can be reliably avoided, and the defrosting reliability of the air source heat pump unit can be further improved.

[0072] Specifically, in a preferred example, the defrosting control actions corresponding to the second mode and the frost risk state and the load surge state are shown in the table below.

[0073]

[0074] Furthermore, in one embodiment, the defrosting control action may further include: if the estimated user mode is the second mode and the estimated unit state is the normal operating state, the defrosting control action includes adjusting the compressor frequency to a predetermined second frequency, increasing the defrosting cycle, and setting a first temperature fluctuation range, wherein the predetermined second frequency is less than the predetermined second frequency; if the estimated user mode is the second mode and the estimated unit state is the standby / degradation state, the defrosting control action includes shutting down the air source heat pump unit.

[0075] There is no conflict between the second mode and the normal operation state according to the usual defrosting control strategy, and there is no conflict between the second mode and the standby / degradation state according to the usual defrosting control strategy. In this embodiment, the defrosting control action corresponding to both the second mode and the normal operation state is determined, as well as the defrosting control action corresponding to both the second mode and the standby / degradation state. The air source heat pump unit is operated according to the defrosting control action, which can further effectively improve the defrosting reliability of the air source heat pump unit.

[0076] Specifically, in a preferred example, the defrosting control actions corresponding to the second mode and the normal operation state and the standby / degradation state are shown in the table below.

[0077]

[0078] In one embodiment, step S130, determining the defrosting control action based on the user mode and unit status, may include: if the estimated user mode is the third mode and the estimated unit status is a frosting risk state, the defrosting control action includes increasing the compressor frequency to the rated frequency, running the fan at full speed, pausing the defrosting program for a first duration, and setting a fourth temperature fluctuation range, wherein the lower limit temperature of the fourth temperature fluctuation range is higher than or equal to a predetermined first temperature; if the estimated user mode is the third mode and the estimated unit status is a load surge state, the defrosting control action includes increasing the compressor frequency to a predetermined third frequency, running the fan at full speed, pausing the defrosting program for a second duration, setting a fourth temperature fluctuation range, and activating the backup electric auxiliary heating; the predetermined third frequency is greater than the rated frequency, and the second duration is greater than the first duration; wherein, the third mode reflects a sudden increase in the set temperature by the user.

[0079] The third mode and the frost risk state conflict under normal defrost control strategies. This embodiment determines the defrost control action corresponding to both the third mode and the frost risk state. Operating the air source heat pump unit according to this defrost control action reliably avoids the conflict and further improves the defrost reliability of the air source heat pump unit. The third mode and the load surge state do not conflict under normal defrost control strategies. This embodiment determines the defrost control action corresponding to both the third mode and the load surge state. Operating the air source heat pump unit according to this defrost control action further improves the defrost reliability of the air source heat pump unit.

[0080] Specifically, in a preferred example, the defrosting control actions corresponding to the third mode and the frosting risk state and the load surge state are shown in the table below.

[0081]

[0082] Furthermore, in one embodiment, the defrosting control action may further include: if the estimated user mode is the third mode and the estimated unit state is the normal operating state, the defrosting control action includes adjusting the compressor frequency to a predetermined third frequency, running the fan at full speed, pausing the defrosting program for a third duration, and setting a fourth temperature fluctuation range, wherein the predetermined third frequency is greater than the rated frequency; if the estimated user mode is the third mode and the estimated unit state is the standby / degradation state, the defrosting control action includes maintaining the compressor frequency unchanged, maintaining a preset standardized defrosting cycle, and setting a third temperature fluctuation range.

[0083] The third mode and normal operation mode do not conflict according to the usual defrosting control strategy. In this embodiment, the defrosting control action corresponding to both the third mode and normal operation mode is determined, and the air source heat pump unit is operated according to this defrosting control action, which can further effectively improve the defrosting reliability of the air source heat pump unit. The third mode and standby / degradation mode conflict according to the usual defrosting control strategy. In this embodiment, the defrosting control action corresponding to both the third mode and standby / degradation mode is determined, and the air source heat pump unit is operated according to this defrosting control action, which can reliably avoid the conflict and further effectively improve the defrosting reliability of the air source heat pump unit.

[0084] Specifically, in a preferred example, the defrosting control actions corresponding to the third mode and the normal operation state and the standby / degradation state are shown in the table below.

[0085]

[0086] Furthermore, in one embodiment of this application, a mode exit mechanism may be provided, which may include: in the first mode, if ΔTset > 1℃ or Nadj ≥ 4 is detected, the current system parameters are maintained, ready to switch to other modes at any time; in the second mode, if the low electricity price period ends or ΔTset > 0℃ is detected for 30 minutes, the compressor frequency is gradually restored to the rated frequency at a rate of 3% / min to 6% / min; in the third mode, if the indoor temperature reaches the set temperature B-0.5℃, or if the compressor operates at a high load (operating at a frequency higher than a predetermined threshold) for more than 15 minutes, a defrosting is forcibly performed, and the compressor frequency is reduced to 90% of the rated frequency.

[0087] Furthermore, in one embodiment of this application, a mode exit mechanism may be provided, which may include: under normal operating conditions, when ΔTe > set value E for 5 minutes, the current parameter is recorded as a health baseline value; under frosting risk conditions, when ΔTe fluctuates within ±0.5℃ for 3 consecutive minutes, the defrosting cycle is adjusted to Z0; under load surge conditions, when Pcomp drops to 80%~90% of rated power, gradient frequency increase is canceled, and the fan operates at rated speed; under standby / degradation conditions, when a user command or temperature demand change is received, the unit is restarted.

[0088] To facilitate better implementation of the control method for the air source heat pump unit provided in the embodiments of this application, the above embodiments are further described below with reference to a defrosting scenario. This defrosting scenario uses the aforementioned embodiments of this application to control the air source heat pump unit. The meanings of the terms used are the same as in the control method for the air source heat pump unit described above, and specific implementation details can be found in the descriptions in the method embodiments.

[0089] like Figure 4 A flowchart illustrating the determination of the predicted user pattern in this defrosting scenario is shown. Figure 5 A flowchart for determining the estimated unit status under this defrosting scenario is shown.

[0090] First, such as Figure 4 The process for determining the estimated user pattern may include steps S410 to S480.

[0091] Step S410: Obtain the parameters required for pattern determination. The parameters required for pattern determination include those described in the foregoing embodiments. 、 | |、 , K , , etc; Step S420: Calculate the mode entry probability based on the above parameters. , i=1,2,3.

[0092] Step S430, determine 、 | |、 , Does it meet the criteria for the first mode? Step S440: When the first mode determination condition is met, the estimated user mode is the first mode. ; Step S450, determine , , Does it meet the criteria for determining the second mode? Step S460: When the second mode determination condition is met, the estimated user mode is the second mode. ; Step S470, determine , , , Does it meet the criteria for the third mode? Step S480: When the third mode determination condition is met, the estimated user mode is the third mode. .

[0093] Furthermore, such as Figure 5 The process for determining the estimated unit status may include steps S510 to S560.

[0094] Step S510: Obtain the parameters required for state determination. These parameters include Pcomp, ΔTe, fde, Ab, N, as described in the preceding embodiments. , , etc; Step S520: Calculate the probability of reaching the state based on the above parameters. j=1, 2, 3, 4.

[0095] Step S530, when If the value is greater than E, the estimated unit status is normal operation. Step S540, when If the value is greater than E, the estimated unit status is a state of frost risk. Step S550, when If the value is greater than E, the estimated unit condition is a sudden load increase. Step S560, when If the value is greater than E, the estimated unit status is standby / degradation state.

[0096] Furthermore, based on different combinations of estimated unit status and estimated user modes, the corresponding defrosting control actions can be determined and executed according to the table above.

[0097] In this scenario, defrosting control is performed using the aforementioned embodiments of this application. By estimating the user pattern, the most likely adjustment method of the user to the air source heat pump unit can be reflected, thereby enabling timely detection of sudden changes in user adjustment. By estimating the unit status, the most likely unit status of the air source heat pump unit can be reflected, thereby effectively considering the frosting situation of the air source heat pump unit. Therefore, by combining the estimated user pattern and the estimated unit status to determine the defrosting control action, the appropriate defrosting control action can be determined by taking into account both sudden changes in user adjustment and frosting situation. This can avoid unreasonable defrosting problems and respond to defrosting in a timely manner when the load changes, thus effectively improving the overall defrosting reliability of the air source heat pump unit.

[0098] To facilitate better implementation of the control method for air source heat pump units provided in the embodiments of this application, the embodiments of this application also provide a control device for air source heat pump units based on the above-described control method. The meanings of the terms used are the same as in the control method for air source heat pump units described above, and specific implementation details can be found in the descriptions in the method embodiments. Figure 6 A block diagram of a control device for an air source heat pump unit according to an embodiment of this application is shown.

[0099] like Figure 6As shown, the control device 600 of the air source heat pump unit may include: a pattern recognition module 610, which can be used to analyze and process user behavior data and outdoor ambient temperature to obtain an estimated user pattern, the estimated user pattern reflecting the user's adjustment method for the air source heat pump unit; a status recognition module 620, which can be used to analyze and process the unit operation data of the air source heat pump unit to obtain an estimated unit status; an action determination module 630, which can be used to determine a defrost control action based on the estimated user pattern and the estimated unit status; and a unit control module 640, which can be used to control the operation of the air source heat pump unit according to the defrost control action.

[0100] In one embodiment, when determining the defrost control action based on the estimated user mode and the estimated unit status, the action determination module 630 can be used to: if the estimated user mode is a first mode and the estimated unit status is a frosting risk state, then the defrost control action includes maintaining the compressor frequency unchanged, shortening the defrosting cycle, and setting a first temperature fluctuation range; if the estimated user mode is the first mode and the estimated unit status is a load surge state, then the defrost control action includes increasing the compressor frequency to the rated frequency, running the fan at full speed, and setting a second temperature fluctuation range; wherein, the first mode reflects that the user does not frequently adjust the set temperature.

[0101] In one embodiment, the action determination module 630 can be used to: if the estimated user mode is the first mode and the estimated unit state is a normal operating state, then the defrosting control action includes maintaining the compressor frequency unchanged, maintaining a preset standardized defrosting cycle, and setting a third temperature fluctuation range; if the estimated user mode is the first mode and the estimated unit state is a standby / degradation state, then the defrosting control action includes shutting down the air source heat pump unit.

[0102] In one embodiment, when determining the defrosting control action based on the estimated user mode and the estimated unit status, the action determination module 630 can be used to: if the estimated user mode is a second mode and the estimated unit status is a frosting risk state, then the defrosting control action includes adjusting the compressor frequency to a predetermined first frequency, keeping the defrosting cycle unchanged, and setting a first temperature fluctuation range, wherein the predetermined first frequency is less than the rated frequency; if the estimated user mode is a second mode and the estimated unit status is a load surge state, then the defrosting control action includes increasing the compressor frequency to the rated frequency, operating the fan at a predetermined first speed, and setting the first temperature fluctuation range; wherein the second mode reflects the user lowering the set temperature or activating the low electricity price period operation mechanism.

[0103] In one embodiment, the action determination module 630 can be used to: if the estimated user mode is the second mode and the estimated unit state is a normal operating state, then the defrosting control action includes adjusting the compressor frequency to a predetermined second frequency, increasing the defrosting cycle, and setting the first temperature fluctuation range, wherein the predetermined second frequency is less than the predetermined second frequency; if the estimated user mode is the second mode and the estimated unit state is a standby / degradation state, then the defrosting control action includes shutting down the air source heat pump unit.

[0104] In one embodiment, when determining the defrosting control action based on the user mode and the unit status, the action determination module 630 can be used to: if the estimated user mode is a third mode and the estimated unit status is a frosting risk state, then the defrosting control action includes increasing the compressor frequency to the rated frequency, running the fan at full speed, pausing the defrosting program for a first duration, and setting a fourth temperature fluctuation range, wherein the lower limit temperature of the fourth temperature fluctuation range is higher than a predetermined first temperature; if the estimated user mode is a third mode and the estimated unit status is a load surge state, then the defrosting control action includes increasing the compressor frequency to a predetermined third frequency, running the fan at full speed, pausing the defrosting program for a second duration, setting the fourth temperature fluctuation range, and activating the backup electric auxiliary heating; the predetermined third frequency is greater than the rated frequency, and the second duration is greater than the first duration; wherein, the third mode reflects the user's sudden increase in the set temperature.

[0105] In one embodiment, the action determination module 630 can be used to: if the estimated user mode is the third mode and the estimated unit state is a normal operating state, then the defrosting control action includes adjusting the compressor frequency to a predetermined third frequency, running the fan at full speed, pausing the defrosting program for a third duration, and setting the fourth temperature fluctuation range, wherein the predetermined third frequency is greater than the rated frequency; if the estimated user mode is the third mode and the estimated unit state is a standby / degradation state, then the defrosting control action includes maintaining the compressor frequency unchanged, maintaining a preset standardized defrosting cycle, and setting the third temperature fluctuation range.

[0106] In one embodiment, when analyzing and processing user behavior data and outdoor ambient temperature to obtain an estimated user pattern, the pattern recognition module 610 can be used to: calculate the pattern entry probability based on the user behavior data and the outdoor ambient temperature; and determine the estimated user pattern based on the pattern entry probability.

[0107] In one embodiment, the user behavior data includes a set temperature change amount and a temperature adjustment frequency; the mode entry probability includes a first mode probability, a second mode probability, and a third mode probability; when determining the estimated user mode based on the mode entry probability, the mode recognition module 610 can be used to: when the first mode probability is greater than or equal to a preset mode probability, the absolute value of the set temperature change amount is less than a predetermined absolute value, the temperature adjustment frequency is less than or equal to a predetermined first frequency, and the outdoor ambient temperature is within a predetermined temperature range, then the estimated user mode is a first mode; when the second mode probability is greater than or equal to the preset mode probability, the set temperature change amount is less than a predetermined first change amount or the current period is a low electricity price period, and the temperature adjustment frequency is greater than or equal to a predetermined second frequency, then the estimated user mode is a second mode; when the third mode probability is greater than or equal to the preset mode probability, the set temperature change amount is greater than a predetermined second change amount, the temperature adjustment frequency is greater than or equal to a predetermined third frequency, and the outdoor ambient temperature is less than a predetermined ambient temperature, then the estimated user mode is a third mode.

[0108] In one embodiment, when calculating the pattern entry probability based on the user behavior data and the outdoor ambient temperature, the pattern recognition module 610 can be used to: generate a first observation vector based on the user behavior data and the outdoor ambient temperature; obtain a first state transition matrix, the first state transition matrix including a first transition probability between different user patterns; obtain a first Gaussian distribution parameter; calculate a first observation probability matrix based on the first observation vector, the first Gaussian distribution parameter and the first state transition matrix; and calculate the pattern entry probability based on the first observation probability matrix, the historical first probability distribution and the first transition probability.

[0109] In one embodiment, when the estimated unit state is obtained by analyzing and processing the unit operation data of the air source heat pump unit, the state identification module 620 can be used to: calculate the probability of the state being reached based on the unit operation data; and determine the estimated unit state based on the probability of the state being reached.

[0110] In one embodiment, the state attainment probability includes a first state probability, a second state probability, a third state probability, and a fourth state probability; when determining the estimated unit state based on the state attainment probability, the state identification module 620 can be used to: when the first state probability is greater than a preset state probability, the estimated unit state is a normal operating state; when the second state probability is greater than the preset state probability, the estimated unit state is a frosting risk state; when the third state probability is greater than the preset state probability, the estimated unit state is a load surge state; when the fourth state probability is greater than the preset state probability, the estimated unit state is a standby / degradation state.

[0111] In one embodiment, when calculating the probability of a state being reached based on the unit operation data, the state identification module 620 can be used to: generate a second observation vector based on the unit operation data; obtain a second state transition matrix, the second state transition matrix including a second transition probability between different unit states; obtain a second Gaussian distribution parameter; calculate a second observation probability matrix based on the second observation vector, the second Gaussian distribution parameter, and the second state transition matrix; and calculate the probability of the state being reached based on the second observation probability matrix, the historical second probability distribution, and the second transition probability.

[0112] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0113] Furthermore, embodiments of this application also provide an electronic device, such as... Figure 7 As shown, Figure 7 A block diagram of an electronic device according to an embodiment of this application is shown, specifically: The electronic device may include components such as a processor 701 with one or more processing cores, a memory 702 with one or more computer-readable storage media, a power supply 703, and an input unit 704. Those skilled in the art will understand that... Figure 7 The electronic device structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein: The processor 701 is the control center of the electronic device, connecting various parts of the computer device via various interfaces and lines. It executes various functions and processes data by running or executing software programs and / or modules stored in the memory 702, and by calling data stored in the memory 702. Optionally, the processor 701 may include one or more processing cores; preferably, the processor 701 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user page, and application programs, and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 701.

[0114] The memory 702 can be used to store software programs and modules. The processor 701 executes various functional applications and data processing by running the software programs and modules stored in the memory 702. The memory 702 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 702 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 702 may also include a memory controller to provide the processor 701 with access to the memory 702.

[0115] The electronic device also includes a power supply 703 that supplies power to the various components. Preferably, the power supply 703 can be logically connected to the processor 701 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 703 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0116] The electronic device may also include an input unit 704, which can be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0117] Although not shown, the electronic device may also include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 701 in the electronic device can load the executable files corresponding to the processes of one or more computer programs into the memory 702 according to the following instructions, and the processor 701 runs the computer programs stored in the memory 702, thereby realizing the various functions in the foregoing embodiments of this application.

[0118] For example, processor 701 can perform the following actions: analyze and process user behavior data and outdoor ambient temperature to obtain an estimated user mode, which reflects the user's adjustment method for the air source heat pump unit; analyze and process the unit operation data of the air source heat pump unit to obtain an estimated unit status; determine defrost control actions based on the estimated user mode and the estimated unit status; and perform operation control on the air source heat pump unit according to the defrost control actions.

[0119] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by a computer program, or by a computer program controlling related hardware. The computer program can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0120] Therefore, embodiments of this application also provide a storage medium storing a computer program that can be loaded by a processor to execute the steps in any of the methods provided in embodiments of this application.

[0121] The storage medium can be a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0122] Since the computer program stored in the storage medium can execute the steps of any of the methods provided in the embodiments of this application, the beneficial effects that the methods provided in the embodiments of this application can achieve can be realized. For details, please refer to the previous embodiments, which will not be repeated here.

[0123] According to another embodiment of this application, a computer program product or computer program includes computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the electronic device to perform the methods provided in the various optional implementations described in the embodiments of this application.

[0124] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0125] It should be understood that this application is not limited to the embodiments described above and shown in the accompanying drawings, but various modifications and changes can be made without departing from its scope.

Claims

1. A control method for an air source heat pump unit, characterized in that, The method includes: Based on the analysis and processing of user behavior data and outdoor ambient temperature, a predicted user pattern is obtained, which reflects the user's adjustment method to the air source heat pump unit. Based on the analysis and processing of the unit's operating data, the estimated unit status is obtained. Determine the defrosting control action based on the estimated user pattern and the estimated unit status; The air source heat pump unit is operated and controlled according to the defrosting control action.

2. The method according to claim 1, characterized in that, The step of determining the defrosting control action based on the estimated user pattern and the estimated unit status includes: If the estimated user mode is the first mode and the estimated unit status is a frosting risk state, then the defrosting control action includes maintaining the compressor frequency unchanged, shortening the defrosting cycle, and setting a first temperature fluctuation range. If the estimated user mode is the first mode and the estimated unit status is a sudden load increase state, then the defrosting control action includes increasing the compressor frequency to the rated frequency, running the fan at full speed, and setting a second temperature fluctuation range. The first mode reflects that the user does not frequently adjust the set temperature.

3. The method according to claim 2, characterized in that, The method further includes: If the estimated user mode is the first mode and the estimated unit status is normal operation, then the defrosting control action includes maintaining the compressor frequency unchanged, maintaining the preset standardized defrosting cycle, and setting a third temperature fluctuation range. If the estimated user mode is the first mode and the estimated unit state is standby / degradation state, then the defrosting control action includes shutting down the air source heat pump unit.

4. The method according to claim 1, characterized in that, The step of determining the defrosting control action based on the estimated user pattern and the estimated unit status includes: If the estimated user mode is the second mode and the estimated unit status is a frosting risk state, then the defrosting control action includes adjusting the compressor frequency to a predetermined first frequency, keeping the defrosting cycle unchanged, and setting a first temperature fluctuation range, wherein the predetermined first frequency is less than the rated frequency. If the estimated user mode is the second mode and the estimated unit status is a sudden load increase state, then the defrosting control action includes increasing the compressor frequency to the rated frequency, running the fan at a predetermined first speed, and setting the first temperature fluctuation range. The second mode reflects the user lowering the set temperature or enabling the low electricity price period operation mechanism.

5. The method according to claim 4, characterized in that, The method further includes: If the estimated user mode is the second mode and the estimated unit status is normal operation, then the defrosting control action includes adjusting the compressor frequency to a predetermined second frequency, increasing the defrosting cycle, and setting the first temperature fluctuation range, wherein the predetermined second frequency is less than the predetermined second frequency. If the estimated user mode is the second mode and the estimated unit state is standby / degradation state, then the defrosting control action includes shutting down the air source heat pump unit.

6. The method according to claim 1, characterized in that, The step of determining the defrosting control action based on the user mode and the unit status includes: If the estimated user mode is the third mode and the estimated unit status is a frosting risk state, then the defrosting control action includes increasing the compressor frequency to the rated frequency, running the fan at full speed, pausing the defrosting program for a first duration, and setting a fourth temperature fluctuation range, wherein the lower limit temperature of the fourth temperature fluctuation range is higher than the predetermined first temperature. If the estimated user mode is the third mode and the estimated unit status is a sudden load increase state, then the defrosting control action includes increasing the compressor frequency to a predetermined third frequency, running the fan at full speed, pausing the defrosting program for a second duration, setting the fourth temperature fluctuation range, and activating the backup electric auxiliary heating; the predetermined third frequency is greater than the rated frequency, and the second duration is greater than the first duration; The third mode reflects the user's sudden increase in the set temperature.

7. The method according to claim 6, characterized in that, The method further includes: If the estimated user mode is the third mode and the estimated unit status is normal operation, then the defrosting control action includes adjusting the compressor frequency to a predetermined third frequency, running the fan at full speed, pausing the defrosting program for a third duration, and setting the fourth temperature fluctuation range, wherein the predetermined third frequency is greater than the rated frequency. If the estimated user mode is the third mode and the estimated unit state is standby / degradation state, then the defrosting control action includes maintaining the compressor frequency unchanged, maintaining the preset standardized defrosting cycle, and setting the third temperature fluctuation range.

8. The method according to any one of claims 1 to 7, characterized in that, The process of analyzing and processing user behavior data and outdoor ambient temperature to obtain predicted user patterns includes: The probability of entering the mode is calculated based on the user behavior data and the outdoor ambient temperature. The estimated user pattern is determined based on the probability of entering the pattern.

9. The method according to claim 8, characterized in that, The user behavior data includes the set temperature change amount and temperature adjustment frequency; the mode entry probability includes the probability of the first mode, the probability of the second mode, and the probability of the third mode. Determining the estimated user pattern based on the pattern entry probability includes: When the probability of the first mode is greater than or equal to the probability of the preset mode, the absolute value of the set temperature change is less than the predetermined absolute value, the temperature adjustment frequency is less than or equal to the predetermined first frequency, and the outdoor ambient temperature is within the predetermined temperature range, then the estimated user mode is the first mode. When the probability of the second mode is greater than or equal to the probability of the preset mode, the change in the set temperature is less than the predetermined first change or the current period is a low electricity price period, and the frequency of temperature adjustment is greater than or equal to the predetermined second frequency, then the estimated user mode is the second mode. When the probability of the third mode is greater than or equal to the probability of the preset mode, the change in the set temperature is greater than the predetermined second change, the frequency of temperature adjustment is greater than or equal to the predetermined third frequency, and the outdoor ambient temperature is less than the predetermined ambient temperature, then the estimated user mode is the third mode.

10. The method according to claim 8, characterized in that, The step of calculating the mode entry probability based on the user behavior data and the outdoor ambient temperature includes: A first observation vector is generated based on the user behavior data and the outdoor ambient temperature. Obtain a first state transition matrix, which includes the first transition probability between different user modes; Obtain the parameters of the first Gaussian distribution; The first observation probability matrix is ​​obtained by calculating based on the first observation vector, the first Gaussian distribution parameters and the first state transition matrix. The mode entry probability is calculated based on the first observation probability matrix, the historical first probability distribution, and the first transition probability.

11. The method according to any one of claims 1 to 7, characterized in that, The step of analyzing and processing the unit's operating data to obtain the estimated unit status includes: The probability of reaching a certain state is calculated based on the unit's operating data. The estimated unit state is determined based on the probability of the state being reached.

12. The method according to claim 11, characterized in that, The probability of reaching a state includes a first state probability, a second state probability, a third state probability, and a fourth state probability; determining the estimated unit state based on the state attainment probabilities includes: When the probability of the first state is greater than the probability of the preset state, the estimated unit state is the normal operating state; When the probability of the second state is greater than the probability of the preset state, the estimated unit state is a frosting risk state. When the probability of the third state is greater than the probability of the preset state, the estimated unit state is a load surge state. When the probability of the fourth state is greater than the probability of the preset state, the estimated unit state is a standby / degradation state.

13. The method according to claim 11, characterized in that, The step of calculating the probability of reaching a certain state based on the unit's operating data includes: A second observation vector is generated based on the unit operation data; Obtain the second state transition matrix, which includes the second transition probability between different unit states; Obtain the parameters of the second Gaussian distribution; The second observation probability matrix is ​​calculated based on the second observation vector, the second Gaussian distribution parameters, and the second state transition matrix. The probability of reaching the state is calculated based on the second observation probability matrix, the historical second probability distribution, and the second transition probability.

14. A control device for an air source heat pump unit, characterized in that, The device includes: The pattern recognition module is used to: analyze and process user behavior data and outdoor ambient temperature to obtain a predicted user pattern, which reflects the user's adjustment method for the air source heat pump unit; The status recognition module is used to: analyze and process the unit operation data of the air source heat pump unit to obtain the estimated unit status; The action determination module is used to: determine the defrosting control action based on the estimated user mode and the estimated unit status; The unit control module is used to control the operation of the air source heat pump unit according to the defrosting control action.

15. A storage medium, characterized in that, It stores a computer program that, when executed by the processor of the electronic device, causes the electronic device to perform the method described in any one of claims 1 to 13.

16. An electronic device, characterized in that, include: Memory, which stores computer programs; A processor reads a computer program stored in memory to perform the method described in any one of claims 1 to 13.

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