A defrosting control method, device, electronic equipment and air conditioner

Abstract

This invention discloses a defrosting control method, device, electronic equipment, and air conditioner to solve the problem that existing defrosting control methods are unable to accurately determine the defrosting timing. The defrosting control method includes: acquiring the cumulative heating parameter values ​​up to the current detection time point within the heating defrosting cycle; acquiring the defrosting heat consumption parameter value corresponding to the current detection time point; determining, based on the cumulative heating parameter value and the defrosting heat consumption parameter value, whether the current detection time point is a target time point that ensures the cyclic heating parameters of the heating defrosting cycle meet target conditions; and, if the current detection time point is determined to be the target time point, determining the defrosting timing based on the current detection time point. This invention can more accurately determine the time point that optimizes or improves the heating energy consumption parameters within the cycle for defrosting, effectively solving the problems of low energy efficiency in traditional defrosting timing and "false defrosting" during frost-free defrosting.

Description

Technical Field

[0001] This invention relates to the field of equipment control, and more particularly to a defrosting control method, device, electronic equipment, and air conditioner. Background Technology

[0002] Taking air conditioners, a typical temperature control device, as an example, the outdoor unit's heat exchanger is prone to frosting under low-temperature conditions. To avoid the impact of thick frost on system performance and reliability, air conditioners generally employ a reversing defrosting control method when the frost layer is thick.

[0003] However, existing commutation defrosting control methods typically use parameters such as time, pipe temperature, and time-pipe temperature to determine defrosting. For different frosting conditions (e.g., different temperatures and humidity), it is difficult to adaptively achieve better power consumption during the heating-defrosting cycle. Summary of the Invention

[0004] In view of this, the present invention discloses a defrosting control method, device, electronic device and air conditioner to solve the problem that existing defrosting control methods are difficult to accurately grasp the defrosting time.

[0005] To achieve the above objectives, the technical solution adopted by this invention is as follows:

[0006] The first aspect of this invention discloses a defrosting control method, comprising:

[0007] During the heating and defrosting cycle, obtain the cumulative heating parameter values ​​up to the current detection time point;

[0008] Obtain the value of the defrosting heat consumption parameter corresponding to the current detection time point;

[0009] Based on the values ​​of the cumulative heating parameters and the defrosting heat consumption parameters, determine whether the current detection time point is the target time point that makes the periodic heating parameters of the heating and defrosting cycle meet the target conditions.

[0010] If the current detection time point is determined to be the target time point, the defrosting timing is determined based on the current detection time point.

[0011] Optionally, the current detection time point is after the reference time point; the reference time point is a time point that meets the following conditions: the cumulative frost amount is greater than the frost amount threshold and the difference between the exhaust temperature and the maximum exhaust temperature during air conditioner operation is greater than the difference threshold.

[0012] Optionally, the cumulative heating parameter values ​​up to the current detection time point include: the sum of the frost-free heating parameter values ​​of the first heating stage and the frosting heating parameter values ​​of the second heating stage; wherein, the first heating stage begins at the start of the heating and defrosting cycle and ends at a reference time point, and the second heating stage begins at the reference time point and ends at the current detection time point; wherein, the reference time point is the time point at which the target time point is determined.

[0013] Optionally, obtaining the cumulative heating parameter value up to the current detection time point includes: in the first heating stage, determining the value of the frost-free heating parameter based on the real-time value of the frost-free heating state parameter; and in the second heating stage, determining the value of the frosting heating parameter based on the real-time value of the frost-free heating state parameter and the corresponding attenuation coefficient.

[0014] Optionally, the method further includes: determining the value of the frost-free heating state parameter based on a heating capacity prediction model and real-time input parameters; wherein the heating capacity prediction model takes a first operating parameter and a first environmental parameter of the air conditioner as input parameters and the frost-free heating state parameter as output parameters; the frost-free heating state parameter includes frost-free heating capacity, or may also include frost-free heating power; the frost-free heating parameter includes cumulative frost-free heating capacity, or may also include cumulative frost-free heating power consumption; the frosting heating parameter includes cumulative defrosting heating capacity, or may also include cumulative defrosting heating power consumption.

[0015] Further optionally, the attenuation coefficient is a function of the cumulative frost amount, outdoor temperature, and outdoor humidity; and / or, α = a·exp(Sn) + b / To + c·Ho + d, where α represents the attenuation coefficient, a, b, c, and d are constants, Sn represents the cumulative frost amount, To represents the outdoor temperature, and Ho represents the outdoor humidity.

[0016] Further optionally, the defrosting heat consumption parameter includes the cumulative heat absorbed during defrosting, or may also include the cumulative power consumption during defrosting; and / or, obtaining the value of the defrosting heat consumption parameter corresponding to the current detection time point includes: determining the value of the defrosting heat consumption parameter based on the defrosting duration and the value of the defrosting heat consumption state parameter corresponding to the current detection time point, wherein the defrosting heat consumption state parameter includes the average heat absorbed during defrosting, or may also include the average power consumption during defrosting.

[0017] Further optionally, the cycle heating parameters include: cycle average heating capacity and / or cycle average energy efficiency; the cycle average heating capacity is determined based on the ratio of the heating capacity difference to the heating-defrosting cycle duration, the heating capacity difference being the difference between the cumulative heating capacity in the cumulative heating parameters and the cumulative defrosting heat absorption in the defrosting heat consumption parameters; the cycle average energy efficiency is determined based on the ratio of the heating capacity difference to the sum of power consumption, the power consumption sum being the sum of the cumulative heating power consumption in the cumulative heating parameters and the cumulative defrosting power consumption in the defrosting heat consumption parameters; determining whether the current detection time point is a target time point that makes the cycle heating parameters of the heating-defrosting cycle meet the target conditions includes: using a target optimization method to determine whether the value of the cycle heating parameter corresponding to the current detection time point is an optimal value.

[0018] Further optionally, the method further includes: determining the values ​​of the defrosting duration and defrosting heat consumption status parameters corresponding to the current detection time point based on the defrosting prediction model and real-time input parameters, so as to calculate the value of the defrosting heat consumption parameters corresponding to the current detection time point; wherein, the defrosting prediction model takes the second operating parameters and the second environmental parameters of the air conditioner as input parameters, and the defrosting duration and defrosting heat consumption status parameters as output parameters, and the second environmental parameters include the cumulative frost amount.

[0019] Further optionally, the method further includes: determining the value of the cumulative frost amount based on the frost amount prediction model and real-time input parameters; wherein the frost amount prediction model takes the third operating parameter and the third environmental parameter of the air conditioner as input parameters, and the frost rate and / or cumulative frost amount as output parameters, and the third environmental parameter includes the cumulative frost amount at a previous time point up to the current detection time point.

[0020] A second aspect of the present invention discloses a method for controlling defrosting, the method comprising:

[0021] During the heating and defrosting cycle, the cumulative heating parameters up to the current detection time are determined based on the real-time heating capacity.

[0022] The cumulative amount of frost up to the current detection time point is determined based on the real-time frost rate.

[0023] Based on the cumulative frost amount and the defrosting time and defrosting capacity at the current detection time point, the value of the defrosting heat consumption parameter at the current detection time point is determined;

[0024] Based on the values ​​of the cumulative heating parameters and the defrosting heat consumption parameters, it is determined whether to enter the defrosting stage.

[0025] Further optionally, the method further includes:

[0026] The real-time heating capacity is determined based on the heating capacity prediction model and the values ​​of the input parameters acquired in real time. The heating capacity prediction model uses a first operating parameter and a first environmental parameter as input parameters and the real-time heating capacity as the output parameter; and / or,

[0027] The real-time frost rate is determined based on the frost amount prediction model and the values ​​of the input parameters acquired in real time. The frost amount prediction model takes a third operating parameter and a third environmental parameter as input parameters and the frost rate as output parameters. The third environmental parameter includes the cumulative frost amount at previous detection time points up to the current detection time point; and / or

[0028] Based on the defrosting prediction model and the values ​​of the input parameters acquired in real time, the defrosting duration and defrosting capability are determined. The defrosting prediction model takes the second operating parameter and the second environmental parameter as input parameters and the defrosting duration and real-time defrosting capability as output parameters. The second environmental parameter includes the cumulative frost amount.

[0029] Optionally, the step of determining whether to enter the defrosting stage based on the values ​​of the cumulative heating parameters and the defrosting heat consumption parameters includes: calculating the value of the periodic heating parameters of the heating and defrosting cycle based on the values ​​of the cumulative heating parameters and the defrosting heat consumption parameters, wherein the periodic heating parameters include: the average heating capacity of the cycle and / or the average energy efficiency of the cycle; and determining the optimal value of the periodic heating parameters corresponding to the current detection time point using a target optimization method, thus determining that the defrosting stage has been entered.

[0030] A third aspect of the present invention discloses a defrosting control device, the device comprising:

[0031] The cumulative heating parameter acquisition module is used to acquire the cumulative heating parameter values ​​up to the current detection time point within the heating and defrosting cycle.

[0032] The defrosting heat consumption parameter acquisition module is used to acquire the value of the defrosting heat consumption parameter corresponding to the current detection time point;

[0033] The judgment module is used to determine, based on the value of the cumulative heating parameter and the value of the defrosting heat consumption parameter, whether the current detection time point is the target time point that makes the periodic heating parameter of the heating and defrosting cycle meet the target conditions.

[0034] The defrosting timing determination module is used to determine the defrosting timing based on the current detection time point when the current detection time point is determined to be the target time point.

[0035] Further optionally, the cumulative heating parameter values ​​up to the current detection time point include: the sum of the frost-free heating parameter values ​​of the first heating stage and the frosting heating parameter values ​​of the second heating stage, wherein the first heating stage begins at the start of the heating-defrosting cycle and ends at a reference time point, and the second heating stage begins at the reference time point and ends at the current detection time point, wherein the reference time point is the time point for determining the entry into the target time point; obtaining the cumulative heating parameter values ​​up to the current detection time point includes: in the first heating stage, determining the frost-free heating parameter value based on the real-time frost-free heating status parameter value; and in the second heating stage, determining the frosting heating parameter value based on the real-time frost-free heating status parameter value and the corresponding attenuation coefficient.

[0036] Further optionally, the cycle heating parameters include: cycle average heating capacity and / or cycle average energy efficiency; the cycle average heating capacity is determined based on the ratio of the heating capacity difference to the heating-defrosting cycle duration, the heating capacity difference being the difference between the cumulative heating capacity in the cumulative heating parameters and the cumulative defrosting heat absorption in the defrosting heat consumption parameters; the cycle average energy efficiency is determined based on the ratio of the heating capacity difference to the sum of power consumption, the power consumption sum being the sum of the cumulative heating power consumption in the cumulative heating parameters and the cumulative defrosting power consumption in the defrosting heat consumption parameters; determining whether the current detection time point is a target time point that makes the cycle heating parameters of the heating-defrosting cycle meet the target conditions includes: using a target optimization method to determine whether the value of the cycle heating parameter corresponding to the current detection time point is an optimal value.

[0037] A fourth aspect of the present invention discloses an electronic device, the electronic device comprising:

[0038] Memory, used to store computer instructions;

[0039] A controller is used to invoke and execute computer instructions stored in the memory to implement the defrosting control method as provided in the first or second aspect of the present invention.

[0040] The fifth aspect of the present invention discloses an air conditioner, wherein the air conditioner employs the defrosting control method provided in the first or second aspect of the present invention, or includes the defrosting control device provided in the third aspect of the present invention, or includes the electronic device provided in the fourth aspect of the present invention.

[0041] Beneficial effects: By combining the cumulative heating parameters and defrosting heat consumption parameters in the heating and defrosting cycle, and aiming at the optimal or better heating parameters of the cycle, it can more accurately determine the time point when the heating energy consumption parameters within the cycle are at their best or better for defrosting, effectively solving the problems of low energy efficiency of traditional defrosting timing and "false defrosting" when there is no frost. Attached Figure Description

[0042] The above and other objects, features, and advantages of the present invention will become more apparent from the detailed description of exemplary embodiments with reference to the accompanying drawings. The drawings described below are merely some embodiments disclosed in the present invention; those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0043] Figure 1 An exemplary neural network diagram of a heating capacity prediction model according to an embodiment of the present invention is shown;

[0044] Figure 2 A schematic diagram of a neural network for predicting frost amount according to an embodiment of the present invention is shown as an example.

[0045] Figure 3 An exemplary neural network diagram of a defrosting prediction model according to an embodiment of the present invention is shown;

[0046] Figure 4 A schematic flowchart of a defrosting control method according to an embodiment of the present invention is shown as an example;

[0047] Figure 5 A schematic flowchart of a defrosting control method according to an embodiment of the present invention is shown as an example;

[0048] Figure 6 A schematic flowchart of a defrosting control method for an air conditioner according to an embodiment of the present invention is shown as an example.

[0049] Figure 7 An exemplary schematic diagram of the frosting heating capacity involved in a defrosting control method according to an embodiment of the present invention is shown;

[0050] Figure 8 A block diagram of a defrosting control device according to an embodiment of the present invention is shown as an example. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” used in the embodiments of this invention and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. “Multiple” generally includes at least two, but does not exclude the inclusion of at least one.

[0053] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0054] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a product or system comprising a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a product or system. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the product or system that includes said element.

[0055] To further illustrate the technical solutions in this invention, we will first refer to the appendix. Figure 1-3 The "xx model" appearing in the relevant embodiments of this invention will be explained below. The heating capacity prediction model, defrosting prediction model, and frost amount prediction model proposed in this invention can be understood as a mapping relationship / functional relationship between input parameters and output parameters, such as neural network models, formulas, mapping tables, etc. The following explanation uses a neural network model as an example.

[0056] like Figure 1 The diagram shown is a neural network schematic of a heating capacity prediction model according to an embodiment of the present invention. (Refer to...) Figure 1 The heating capacity prediction model takes the first operating parameters and the first environmental parameters of the air conditioner as input parameters, and the frost-free heating state parameters, which reflect the frost-free heating capacity, as output parameters.

[0057] The first operating parameter is typically the air conditioner's input control parameter, such as compressor frequency, indoor fan speed, outdoor fan speed, and electronic expansion valve opening. The first environmental parameter may include, for example, inner ring temperature, indoor humidity, outer ring temperature, outdoor humidity, and air guide vane position. The corresponding frost-free heating status parameters may be the air conditioner's frost-free heating capacity Qhn, frost-free heating power Whn, and frost-free heating energy efficiency COP.

[0058] The heating capacity prediction model provided in this embodiment can accurately calculate the real-time frost-free heating capacity of the air conditioner, which is beneficial for accurately calculating the values ​​of the real-time cumulative heating parameters during the heating process. Corresponding to the frost-free heating state parameters, the cumulative heating parameters include cumulative heating capacity and cumulative heating power consumption.

[0059] like Figure 2 The diagram shown is a neural network schematic of a frost amount prediction model according to an embodiment of the present invention. (Refer to...) Figure 2 The frost amount prediction model takes the third operating parameter and the third environmental parameter of the air conditioner as input parameters, and the frost rate and / or cumulative frost amount as output parameters.

[0060] The third operating parameter is typically related to the operation of the outdoor unit of the air conditioner, such as the external pipe temperature Te, the outdoor fan speed No, and the outer ring temperature. The third environmental parameter is typically related to the environmental parameters of the outdoor unit of the air conditioner, such as the outdoor temperature To, the outdoor humidity Ho, and the cumulative frost amount Sn-1 from the previous detection period. Given the frost rate, the cumulative frost amount can be calculated by accumulating the real-time frost rate over time.

[0061] The frost amount prediction model provided in this embodiment introduces the cumulative frost amount of the previous detection cycle (i.e., the previous detection time point up to the current detection time point) as an input parameter, and takes the previous cumulative frost amount as a factor affecting the current frost rate, which can predict the cumulative frost amount relatively objectively and accurately, even in the face of reduced heating capacity.

[0062] like Figure 3 The diagram shown is a neural network schematic of a defrosting prediction model according to an embodiment of the present invention. (Refer to...) Figure 3 The defrosting prediction model takes the second operating parameter and the second environmental parameter of the air conditioner as input parameters, and the defrosting duration and defrosting heat consumption state parameter as output parameters.

[0063] The second operating parameter typically refers to the operating parameters of the air conditioner's outdoor unit, such as defrosting frequency and outdoor fan speed. The second environmental parameter typically refers to environmental parameters related to the air conditioner's outdoor unit, such as cumulative frost accumulation, outdoor temperature and humidity, and indoor temperature. The defrosting heat consumption state parameter in the output parameters may include the average heat absorption during defrosting, Q. d,ave Average power consumption during defrosting (W) d,ave .

[0064] The predicted cumulative frost amount is introduced into the defrosting prediction model, making the output parameters of the model more real-time and targeted. Furthermore, combined with... Figure 2 The aforementioned frost amount prediction model has the advantage of accurately outputting the cumulative frost amount. Figure 3The defrosting prediction model shown can also more accurately predict defrosting duration and defrosting heat consumption parameters, thus facilitating the accurate calculation of defrosting heat consumption parameters. Corresponding to the defrosting heat consumption parameters, the defrosting heat consumption parameters include the cumulative heat absorbed during defrosting and the cumulative power consumption during defrosting.

[0065] It should be noted that all the above models can be trained and learned through experimental data, simulation data, etc., and this invention does not limit the specific training methods. Furthermore, the descriptions of the input and output parameters of the neural network models are merely examples. Those skilled in the art can add, delete, change, or replace relevant parameters based on the disclosure of this invention, as needed or based on experiments, and all of this is within the scope of protection of this invention.

[0066] The defrosting control method according to an embodiment of the present invention will now be described with reference to the accompanying drawings.

[0067] Figure 4 This is a schematic flowchart of a defrosting control method according to an embodiment of the present invention. (Refer to...) Figure 4 Methods for controlling defrosting include:

[0068] S400: During the heating and defrosting cycle, obtain the cumulative heating parameter values ​​up to the current detection time point.

[0069] Optionally, in one implementation of this embodiment, the "current detection time point" is a time point after the reference time point. The reference time point is the time point at which the judgment of entering the target time point is made; that is, the judgment of the defrosting timing is performed after the reference time point.

[0070] Therefore, the heating process up to the current detection time can be divided into a first heating stage, which begins at the start of the heating and defrosting cycle and ends at a reference time, and a second heating stage, which begins at the reference time and ends at the current detection time. The cumulative heating parameter value can be the sum of the frost-free heating parameter value of the first heating stage and the frosting heating parameter value of the second heating stage.

[0071] In the first heating stage, the value of the frost-free heating parameter can be determined based on the real-time value of the frost-free heating state parameter. In the second heating stage, the value of the frosting heating parameter can be determined based on the real-time value of the frost-free heating state parameter and the corresponding attenuation coefficient. The attenuation coefficient is a function of the cumulative frost amount, outdoor temperature, and outdoor humidity.

[0072] The reason for segmented accumulation is that the reference time point in the embodiments of the present invention also represents the time point when the heating capacity begins to decline. Therefore, by adopting the segmented accumulation method, the value of the cumulative heating parameter can be calculated more accurately.

[0073] For example, the reference time point is a time point that meets the following conditions: the cumulative frost amount is greater than the frost amount threshold, and the difference between the exhaust temperature and the maximum exhaust temperature during air conditioner operation is greater than the difference threshold. The values ​​of the relevant parameters can be collected and calculated in real time during air conditioner operation. Using this condition allows for a more accurate assessment of the reduction in heating capacity caused by frost, and timely detection of the optimal defrosting time. Of course, in other embodiments, the "current detection time point" can also be a real-time time point delayed by a preset time from this reference time point.

[0074] S402: Obtain the value of the defrosting heat consumption parameter corresponding to the current detection time point. The defrosting heat consumption parameter is used to reflect the energy consumption during defrosting of the cumulative amount of frost up to the current detection time point.

[0075] Optionally, in one implementation of this embodiment, the value of the defrosting heat consumption parameter is determined based on the defrosting duration and the value of the defrosting heat consumption state parameter corresponding to the current detection time point. The defrosting heat consumption state parameter includes the average heat absorbed during defrosting and the average power consumption during defrosting. Correspondingly, the defrosting heat consumption parameter includes the cumulative heat absorbed during defrosting and the cumulative power consumption during defrosting.

[0076] S404: Based on the value of the cumulative heating parameter and the value of the defrosting heat consumption parameter, determine whether the current detection time point is the target time point that makes the periodic heating parameter of the heating and defrosting cycle meet the target conditions.

[0077] Optionally, in one implementation of this embodiment, the periodic heating parameters include: periodic average heating capacity and / or periodic average energy efficiency.

[0078] The average heating capacity per cycle is determined based on the ratio of the heating capacity difference to the duration of the heating and defrosting cycle. The heating capacity difference is the difference between the cumulative heating capacity in the cumulative heating parameters and the cumulative heat absorbed during defrosting in the defrosting heat consumption parameters. The duration of the heating and defrosting cycle includes the duration up to the current detection time point and the defrosting duration corresponding to the current detection time point.

[0079] The cycle average energy efficiency is determined based on the ratio of the difference in heating capacity to the sum of power consumption, where the sum of power consumption is the sum of the cumulative heating power consumption in the cumulative heating parameters and the cumulative defrosting power consumption in the defrosting heat consumption parameters.

[0080] In this implementation, when the cycle heating parameter uses any one of the cycle average heating capacity, cycle average energy efficiency, or equivalent parameters, a single-objective optimization method within the objective optimization approach can be used to determine whether the value of the cycle heating parameter corresponding to the current detection time point is the optimal value, thereby determining whether the current detection time point is the target time point. When the cycle heating parameter uses both the cycle average heating capacity and the cycle average energy efficiency, or when more energy consumption or energy efficiency-related parameters are introduced, a multi-objective optimization method can be used to determine whether the value of the cycle heating parameter corresponding to the current detection time point is the optimal value, thereby determining whether the current detection time point is the target time point.

[0081] S406: If the current detection time point is determined to be the target time point, the defrosting timing is determined based on the current detection time point. For example, it is determined that defrosting will be performed immediately after the current detection time point, although a certain time delay is also acceptable. After defrosting is completed, the current heating defrosting cycle ends, and a new heating defrosting cycle can begin.

[0082] The defrosting control method provided in this invention integrates the cumulative heating parameters and defrosting heat consumption parameters in the heating and defrosting cycle, with the goal of optimizing or improving the heating parameters of the cycle. It can more accurately determine the time point when the heating energy consumption parameters within the cycle are optimal or better, and effectively solve the problems of low energy efficiency of traditional defrosting timing and "false defrosting" when there is no frost.

[0083] Figure 5 This is a schematic flowchart of a defrosting control method according to an embodiment of the present invention, referring to... Figure 5 The method includes:

[0084] S500: During the heating and defrosting cycle, the cumulative heating parameter value up to the current detection time point is determined based on the real-time heating capacity.

[0085] Optionally, in one implementation of this embodiment, the real-time heating capacity is determined based on the heating capacity prediction model mentioned above and the values ​​of the input parameters acquired in real time.

[0086] S502: Determine the cumulative amount of frost up to the current detection time point based on the real-time frost rate.

[0087] Optionally, in one implementation of this embodiment, the real-time frost rate is determined based on the frost amount prediction model mentioned above and the values ​​of the input parameters acquired in real time.

[0088] S504: Based on the cumulative frost amount, the defrosting time and real-time defrosting capability at the current detection time point, determine the value of the defrosting heat consumption parameter at the current detection time point.

[0089] Optionally, in one implementation of this embodiment, the defrosting duration and real-time defrosting capability are determined based on the defrosting prediction model mentioned above and the values ​​of the input parameters acquired in real time.

[0090] S506: Based on the value of the cumulative heating parameter and the value of the defrosting heat consumption parameter, determine whether to enter the defrosting stage.

[0091] Optionally, in one implementation of this embodiment, processing S506 can be implemented in the following way:

[0092] Based on the values ​​of the cumulative heating parameters and the defrosting heat consumption parameters, the values ​​of the periodic heating parameters for the heating and defrosting cycle are calculated. These periodic heating parameters include: the average heating capacity per cycle and / or the average energy efficiency per cycle. An objective optimization method (including single-objective optimization methods, multi-objective optimization methods, etc.) is used to determine the optimal value (including the optimal combination) of the periodic heating parameters corresponding to the current detection time point, thus determining whether to enter the defrosting stage.

[0093] The defrosting method provided in this embodiment comprehensively considers the cumulative heating parameters, defrosting heat consumption parameters, and target optimization methods to determine whether the periodic heating parameters are optimal. This allows for a more accurate determination of the time point when the periodic heating parameters are optimal (or when the set conditions are met) for defrosting, effectively solving the problems of low energy efficiency in traditional defrosting timing and "false defrosting" when defrosting without frost.

[0094] Figure 6 This is a flowchart illustrating a defrosting control method for an air conditioner according to an embodiment of the present invention. (Refer to...) Figure 6 When the air conditioner is turned on for heating and it is determined that the current condition is frosting, the method begins to collect air conditioner operating parameters and environmental parameters. Based on these parameters, the method includes:

[0095] S600: Calculate the cumulative heating capacity Qh, cumulative heating power consumption Wh, and cumulative frost amount Sn(t1) of the air conditioner based on the capacity prediction model (i.e., heating capacity prediction model) and the frost amount prediction model.

[0096] Specifically, after the air conditioner is turned on for heating, the capacity prediction model and the frost amount prediction model begin to calculate the frost-free heating capacity Qhn, frost-free heating power consumption Whn, and frost rate Vn for each detection cycle (any point in time can be considered the end of a detection cycle) based on the air conditioner's operating parameters and environmental parameters. At the same time, the values ​​of the following parameters can be obtained by accumulating over time:

[0097] Cumulative heat output Qh = ∑Qhn·Δt;

[0098] Cumulative heating power consumption Wh = ∑Whn·Δt;

[0099] The cumulative frost amount Sn(t1) = ∑Vn·Δt; where n is 0~t1, Δt∈(0,t1), and t1 represents the time point mentioned below for entering the optimal defrosting timing judgment mode, i.e., the baseline time point mentioned earlier. The cumulative heating capacity and cumulative heating power consumption calculated at time t1 are the frost-free heating parameters for the first heating stage from 0 to t1.

[0100] S601: After running for a set time (e.g., 10 minutes, the purpose is to allow the system to enter a stable state, at which time the predicted value is more accurate), determine whether the conditions for entering the optimal defrosting timing judgment mode are met. If they are met, enter the optimal defrosting timing judgment mode and execute S602; otherwise, repeat S600.

[0101] Specifically, the conditions for entering the optimal defrosting timing judgment mode are: the cumulative frost amount Sn is greater than the preset frost amount Sn' (e.g., 1500g, or frost thickness can be used as a measure) and the difference between the real-time exhaust temperature Td and the maximum exhaust temperature Tdmax during operation is greater than the preset difference ΔTd (e.g., exhaust temperature decrease of 4℃). The condition of being greater than Sn' ensures that the frost layer on the outdoor unit reaches a certain thickness; the setting of being greater than ΔTd ensures that the outdoor unit's heating capacity decreases to a certain extent due to the thickness of the frost layer, at which point the cycle-average heating capacity efficiency is at its highest, and defrosting can begin.

[0102] S602: Calculate the cumulative heating capacity Qf and cumulative heating power consumption Wf, and simultaneously calculate the cumulative defrosting heat absorption Qd, cumulative defrosting power consumption Wd, and defrosting duration based on the cumulative frost amount Sn and the defrosting prediction model.

[0103] Specifically, when the optimal defrosting time judgment mode is met, it indicates that the accumulated frost layer has caused the power capacity to begin to decrease. At this time, the frosting heating capacity and frosting heating power are calculated as follows:

[0104] Qfn=k·Qhn, where k is the attenuation coefficient, k=a·exp(Sn)+b / To+c·Ho+d, a, b, c, d are constant coefficients, Sn is the cumulative frost amount, To is the outdoor temperature, and Ho is the outdoor humidity;

[0105] Wfn = l·Whn, where l is the attenuation coefficient, l = e·exp(Sn) + f / To + g·Ho + h, e, f, g, and h are constant coefficients, Sn is the cumulative frost amount, To is the outdoor temperature, and Ho is the outdoor humidity. All constants can be real numbers, and their values ​​can be obtained by fitting prototype laboratory data.

[0106] Therefore, the following parameters can be calculated based on the cumulative time:

[0107] Cumulative heat output Qf = ∑Qfn·Δt;

[0108] Cumulative heating power consumption Wf = ∑Wfn·Δt;

[0109] The cumulative frost amount Sn = ∑Vn·Δt; where n is t1~t2, Δt∈(t1,t2), and t2 represents the target time point, that is, the time point at which the defrosting timing is determined or the defrosting begins. The cumulative heating capacity and cumulative heating power consumption calculated at time t2 from t1 to t2 are the frost heating parameters for the second heating stage.

[0110] The cumulative heat absorbed during defrosting is Qd = Qd,ave·(t3-t2).

[0111] The cumulative defrosting power consumption is Wd = Wd,ave·(t3-t2), where t3-t2 represents the predicted defrosting time.

[0112] S603: Employ a multi-objective optimization algorithm to find the time t2 that maximizes the cycle average heating capacity and cycle average energy efficiency.

[0113] Specifically, assuming defrosting begins at time t2, the cumulative frost amount Sn(t2) at time t2 can be predicted and output. Combined with the defrosting prediction model, the defrosting time (t3-t2) corresponding to the cumulative frost amount Sn(t2), as well as the average heat absorption (or average defrosting capacity) Qd,ave and the average power consumption Wd,ave during defrosting can be predicted.

[0114] The average heating capacity during the entire heating, frosting, and defrosting cycle is then...

[0115] Q = (Qh + Qf - Qd, ave·(t3 - t2)) / t3

[0116] The average energy efficiency of the entire heating, frosting, and defrosting cycle.

[0117] COP=(Qh+Qf-Qd,ave·(t3-t2)) / (Wh+Wf+Wd,ave·(t3-t2))

[0118] Using multi-objective optimization algorithms (particle algorithm, ant colony algorithm, genetic algorithm, annealing algorithm, etc.), the heating duration t2 that maximizes the average heating capacity and energy efficiency throughout the entire heating-frosting-defrosting cycle can be easily obtained. Defrosting control is executed immediately after the air conditioner has run for t2. Afterwards, shutdown can be performed under conditions that meet the shutdown requirements, or if the system is still in a frosting state, the next heating-frosting-defrosting cycle can be continued to repeat the above control logic, thus achieving the prediction and control of the optimal heating-frosting duration.

[0119] For example, such as Figure 7 The diagram shown is a schematic representation of the frosting heating capacity of a defrosting control method according to an embodiment of the present invention. Figure 6The illustrated embodiment refers to... Figure 7 The horizontal axis t represents the operating time of the air conditioner in heating mode, and the vertical axis Q represents the heating capacity. The thin solid line represents the frost thickness, and the frost thickness (or cumulative frost amount) at time t2 is S2. t2 is the actual time to begin defrosting as determined by the embodiment of the present invention, and t3 is the actual time to end defrosting. As shown in the figure, the frost thickness becomes 0 between t2 and t3.

[0120] The thick solid line represents the actual heating capacity of the air conditioner during the defrosting cycle. In a non-defrosting environment with stable operating conditions, the actual heating capacity of the air conditioner will not decrease and will remain stable at the position indicated by the dashed line, i.e., the frost-free heating capacity Qhn. However, due to the presence of frost (refer to the change in frost thickness over time shown by the thin solid line), the actual heating capacity begins to decrease around time t1 (the baseline time point). The corresponding frosted heating capacity at this time is k·Qhn (as mentioned earlier, k represents the attenuation coefficient).

[0121] Assume that in another defrosting control process, the defrosting time is from t2' to t3'. Compared to the optimal defrosting time t2, if t2' > t2, the heating time is prolonged, the outdoor unit frosting process is aggravated, the heating capacity is reduced, the defrosting time (t3' - t2') is prolonged, and the average capacity and energy efficiency of the periodic defrosting decrease. If t2' < t2, the heating time is too short, frequent defrosting is initiated, the heating capacity is not reduced or only slightly reduced, and the average capacity and energy efficiency of the periodic defrosting are not at their maximum. Therefore, the defrosting control method provided in the various embodiments of the present invention is beneficial for determining the defrosting time point that maximizes the average capacity and / or energy efficiency of the periodic defrosting.

[0122] Figure 8 This is a block diagram of a defrosting control device according to an embodiment of the present invention, with reference to... Figure 8 The control device includes a cumulative heating parameter acquisition module 80, a defrosting heat consumption parameter acquisition module 82, a judgment module 84, and a defrosting timing determination module 86. These will be described in detail below.

[0123] In this embodiment, the cumulative heating parameter acquisition module 80 is used to acquire the value of the cumulative heating parameter up to the current detection time point within the heating and defrosting cycle. Optionally, the value of the cumulative heating parameter up to the current detection time point includes: the sum of the value of the frost-free heating parameter in the first heating stage and the value of the frosting heating parameter in the second heating stage, wherein the first heating stage begins at the start of the heating and defrosting cycle and ends at a reference time point, and the second heating stage begins at the reference time point and ends at the current detection time point, wherein the reference time point is the time point for determining whether to enter the target time point.

[0124] Optionally, in one implementation of this embodiment, the cumulative heating parameter acquisition module is specifically used to: determine the value of the frost-free heating parameter based on the real-time value of the frost-free heating state parameter during the first heating stage; and determine the value of the frosting heating parameter based on the real-time value of the frost-free heating state parameter and the corresponding attenuation coefficient during the second heating stage.

[0125] In this embodiment, the defrosting heat consumption parameter acquisition module 82 is used to acquire the value of the defrosting heat consumption parameter corresponding to the current detection time point. For example, the value of the defrosting heat consumption parameter is determined based on the defrosting duration and the value of the defrosting heat consumption state parameter corresponding to the current detection time point. The defrosting heat consumption state parameter includes the average heat absorbed during defrosting, or it may also include the average power consumption during defrosting; correspondingly, the defrosting heat consumption parameter includes the cumulative heat absorbed during defrosting, or it may also include the cumulative power consumption during defrosting.

[0126] In this embodiment, the judgment module 84 is used to determine, based on the value of the cumulative heating parameter and the value of the defrosting heat consumption parameter, whether the current detection time point is the target time point that makes the periodic heating parameter of the heating and defrosting cycle meet the target conditions.

[0127] Optionally, in one implementation of this embodiment, the cycle heating parameters include: cycle average heating capacity and / or cycle average energy efficiency. The cycle average heating capacity is determined based on the ratio of the heating capacity difference to the heating-defrosting cycle duration, where the heating capacity difference is the difference between the cumulative heating capacity in the cumulative heating parameters and the cumulative defrosting heat absorption in the defrosting heat consumption parameters. The cycle average energy efficiency is determined based on the ratio of the heating capacity difference to the sum of power consumption, where the sum of power consumption is the sum of the cumulative heating power consumption in the cumulative heating parameters and the cumulative defrosting power consumption in the defrosting heat consumption parameters.

[0128] The judgment module 84 is specifically used to: determine whether the value of the periodic heating parameter corresponding to the current detection time point is the optimal value using a target optimization method.

[0129] In this embodiment, the defrosting timing determination module 86 is used to determine the defrosting timing based on the current detection time point when the current detection time point is determined to be the target time point. For example, it may be determined that defrosting should be performed immediately after the current detection time point, although a certain time delay is also possible.

[0130] By employing the defrosting control device provided in this embodiment of the invention, which integrates the cumulative heating parameters and defrosting heat consumption parameters in the heating and defrosting cycle, and aims to optimize or improve the heating parameters of the cycle, the device can more accurately determine the time point at which the heating energy consumption parameters within the cycle are optimal or better for defrosting, effectively solving the problems of low energy efficiency in traditional defrosting and "false defrosting" when there is no frost.

[0131] According to one embodiment of the present invention, an electronic device for controlling defrosting is also provided. The electronic device includes a memory and a controller. The memory stores computer instructions / programs; the controller calls and executes the computer instructions / programs stored in the memory to implement the defrosting control method provided in any of the preceding embodiments.

[0132] According to one embodiment of the present invention, a computer-readable storage medium is also provided, wherein a computer program is stored thereon, which, when executed, implements the defrosting control method provided in any of the preceding embodiments.

[0133] According to one embodiment of the present invention, a temperature regulating device is also provided. Taking an air conditioner as an example, the air conditioner adopts the defrosting control method provided in any of the preceding embodiments; or, the air conditioner includes the defrosting control device provided in any of the preceding embodiments; or, the air conditioner includes the electronic device for defrosting control provided in any of the preceding embodiments.

[0134] In the different embodiments provided by this invention, the same parameters, terms, logic, etc. should be understood to have the same meaning, and this application does not intentionally repeat the description in each embodiment.

[0135] Exemplary embodiments of the present disclosure have been specifically shown and described above. It should be understood that the present disclosure is not limited to the detailed structures, arrangements, or implementation methods described herein; rather, the present disclosure is intended to cover various modifications and equivalent arrangements contained within the spirit and scope of the appended claims.

Claims

1. A defrosting control method, characterized in that, The method includes: During the heating and defrosting cycle, obtain the cumulative heating parameter values ​​up to the current detection time point; Obtain the value of the defrosting heat consumption parameter corresponding to the current detection time point; Based on the values ​​of the cumulative heating parameters and the defrosting heat consumption parameters, it is determined whether the current detection time point is the target time point that ensures the periodic heating parameters of the heating and defrosting cycle meet the target conditions; wherein, the periodic heating parameters include: periodic average heating capacity and / or periodic average energy efficiency; the periodic average heating capacity is determined based on the ratio of the heating capacity difference to the duration of the heating and defrosting cycle, and the heating capacity difference is the difference between the cumulative heating capacity in the cumulative heating parameters and the cumulative defrosting heat absorption in the defrosting heat consumption parameters; the periodic average energy efficiency is determined based on the ratio of the heating capacity difference to the sum of power consumption, and the sum of power consumption is the sum of the cumulative heating power consumption in the cumulative heating parameters and the cumulative defrosting power consumption in the defrosting heat consumption parameters; If the current detection time point is determined to be the target time point, the defrosting timing is determined based on the current detection time point; in: Determining whether the current detection time point is the target time point that makes the periodic heating parameters of the heating and defrosting cycle meet the target conditions includes: using a target optimization method to determine whether the value of the periodic heating parameter corresponding to the current detection time point is the optimal value.

2. The method as described in claim 1, characterized in that, The current detection time point is after the baseline time point; The reference time point is a time point that meets the following conditions: the cumulative frost amount is greater than the frost amount threshold and the difference between the exhaust temperature and the maximum exhaust temperature during the operation of the air conditioner is greater than the difference threshold.

3. The method as described in claim 1, characterized in that, The cumulative heating parameter values ​​up to the current detection time point include: The sum of the values ​​of the frost-free heating parameters in the first heating stage and the values ​​of the frosting heating parameters in the second heating stage; The first heating phase begins at the start of the heating and defrosting cycle and ends at a reference time point, while the second heating phase begins at the reference time point and ends at the current detection time point. The reference time point is the time point at which the judgment of entering the target time point is made.

4. The method as described in claim 3, characterized in that, The process of obtaining the cumulative heating parameters up to the current detection time includes: In the first heating stage, the value of the frost-free heating parameter is determined based on the real-time value of the frost-free heating status parameter; In the second heating stage, the value of the frosting heating parameter is determined based on the real-time values ​​of the frost-free heating state parameters and the corresponding attenuation coefficient.

5. The method as described in claim 4, characterized in that, The method further includes: The values ​​of the frost-free heating state parameters are determined based on the heating capacity prediction model and real-time input parameters. The heating capacity prediction model uses the first operating parameters and the first environmental parameters of the air conditioner as input parameters and the frost-free heating state parameters as output parameters. The frost-free heating status parameters include frost-free heating capacity, or may also include frost-free heating power; The frost-free heating parameters include the cumulative frost-free heating capacity, or may also include the cumulative frost-free heating power consumption; The defrosting heating parameters include the cumulative defrosting heating capacity, or may also include the cumulative defrosting heating power consumption.

6. The method as described in claim 4, characterized in that, The attenuation coefficient is a function of cumulative frost amount, outdoor temperature, and outdoor humidity; and / or, α = a·exp(Sn) + b / To + c·Ho + d, where α represents the attenuation coefficient, a, b, c, and d are constants, Sn represents the cumulative frost amount, To represents the outdoor temperature, and Ho represents the outdoor humidity.

7. The method as described in claim 1, characterized in that, The defrosting heat consumption parameters include the cumulative heat absorbed during defrosting, or may also include the cumulative power consumption during defrosting; and / or, The step of obtaining the value of the defrosting heat consumption parameter corresponding to the current detection time point includes: determining the value of the defrosting heat consumption parameter based on the defrosting duration and the value of the defrosting heat consumption state parameter corresponding to the current detection time point, wherein the defrosting heat consumption state parameter includes the average heat absorbed during defrosting, or may also include the average power consumption during defrosting.

8. The method as described in claim 7, characterized in that, The method further includes: The defrosting duration and defrosting heat consumption state parameters corresponding to the current detection time point are determined based on the defrosting prediction model and real-time input parameters, so as to calculate the value of the defrosting heat consumption parameter corresponding to the current detection time point. The defrosting prediction model uses the second operating parameter and the second environmental parameter of the air conditioner as input parameters, and the defrosting time and defrosting heat consumption status parameter as output parameters. The second environmental parameter includes the cumulative frost amount.

9. The method according to any one of claims 2-6, characterized in that, The method further includes: The cumulative frost amount is determined based on the frost amount prediction model and real-time input parameters; The frost amount prediction model uses the third operating parameter and the third environmental parameter of the air conditioner as input parameters, and the frost rate and / or cumulative frost amount as output parameters. The third environmental parameter includes the cumulative frost amount at previous time points up to the current detection time point.

10. A method for controlling defrosting, characterized in that, The method includes: During the heating and defrosting cycle, the cumulative heating parameters up to the current detection time are determined based on the real-time heating capacity. The cumulative amount of frost up to the current detection time point is determined based on the real-time frost rate. Based on the cumulative frost amount and the defrosting time and defrosting capacity at the current detection time point, the value of the defrosting heat consumption parameter at the current detection time point is determined; Based on the values ​​of the cumulative heating parameters and the defrosting heat consumption parameters, it is determined whether to enter the defrosting stage; The step of determining whether to enter the defrosting stage based on the values ​​of the cumulative heating parameters and the defrosting heat consumption parameters includes: The value of the periodic heating parameter of the heating and defrosting cycle is calculated based on the value of the cumulative heating parameter and the value of the defrosting heat consumption parameter; If the optimal value of the cycle heating parameter corresponding to the current detection time point is determined by using the target optimization method, then the defrosting stage is determined. The cycle heating parameters include: cycle average heating capacity and / or cycle average energy efficiency; the cycle average heating capacity is determined based on the ratio of the heating capacity difference to the heating-defrosting cycle duration, and the heating capacity difference is the difference between the cumulative heating capacity in the cumulative heating parameters and the cumulative defrosting heat absorption in the defrosting heat consumption parameters; the cycle average energy efficiency is determined based on the ratio of the heating capacity difference to the sum of power consumption, and the sum of power consumption is the sum of the cumulative heating power consumption in the cumulative heating parameters and the cumulative defrosting power consumption in the defrosting heat consumption parameters.

11. The method as described in claim 10, characterized in that, The method further includes: The real-time heating capacity is determined based on the heating capacity prediction model and the values ​​of the input parameters acquired in real time. The heating capacity prediction model uses a first operating parameter and a first environmental parameter as input parameters and the real-time heating capacity as the output parameter; and / or, The real-time frost rate is determined based on the frost amount prediction model and the values ​​of the input parameters acquired in real time. The frost amount prediction model takes a third operating parameter and a third environmental parameter as input parameters and the frost rate as output parameters. The third environmental parameter includes the cumulative frost amount at previous detection time points up to the current detection time point; and / or Based on the defrosting prediction model and the values ​​of the input parameters acquired in real time, the defrosting duration and defrosting capability are determined. The defrosting prediction model takes the second operating parameter and the second environmental parameter as input parameters and the defrosting duration and real-time defrosting capability as output parameters. The second environmental parameter includes the cumulative frost amount.

12. A defrosting control device, characterized in that, The device includes: The cumulative heating parameter acquisition module is used to acquire the cumulative heating parameter values ​​up to the current detection time point within the heating and defrosting cycle. The defrosting heat consumption parameter acquisition module is used to acquire the value of the defrosting heat consumption parameter corresponding to the current detection time point; The judgment module is used to determine, based on the values ​​of the cumulative heating parameters and the defrosting heat consumption parameters, whether the current detection time point is a target time point that ensures the periodic heating parameters of the heating and defrosting cycle meet the target conditions; wherein, the periodic heating parameters include: periodic average heating capacity and / or periodic average energy efficiency; the periodic average heating capacity is determined based on the ratio of the heating capacity difference to the duration of the heating and defrosting cycle, and the heating capacity difference is the difference between the cumulative heating capacity in the cumulative heating parameters and the cumulative defrosting heat absorption in the defrosting heat consumption parameters; the periodic average energy efficiency is determined based on the ratio of the heating capacity difference to the sum of power consumption, and the sum of power consumption is the sum of the cumulative heating power consumption in the cumulative heating parameters and the cumulative defrosting power consumption in the defrosting heat consumption parameters; The defrosting timing determination module is used to determine the defrosting timing based on the current detection time point when the target time point is determined to be the current detection time point. The determination module determines whether the current detection time point is the target time point that makes the periodic heating parameters of the heating and defrosting cycle meet the target conditions by using a target optimization method to determine whether the value of the periodic heating parameter corresponding to the current detection time point is the optimal value.

13. The apparatus as claimed in claim 12, characterized in that, The cumulative heating parameter values ​​up to the current detection time point include: the sum of the frost-free heating parameter values ​​of the first heating stage and the frosting heating parameter values ​​of the second heating stage, wherein the first heating stage begins at the start of the heating and defrosting cycle and ends at a reference time point, and the second heating stage begins at the reference time point and ends at the current detection time point, wherein the reference time point is the time point for determining the target time point; The cumulative heating parameter acquisition module is specifically used to: determine the value of the frost-free heating parameter based on the real-time value of the frost-free heating state parameter in the first heating stage; and determine the value of the frosting heating parameter based on the real-time value of the frost-free heating state parameter and the corresponding attenuation coefficient in the second heating stage.

14. An electronic device for controlling defrosting, characterized in that, The electronic device includes: Memory, used to store computer instructions; A controller is used to invoke and execute computer instructions stored in the memory to implement the defrosting control method as described in any one of claims 1-11.

15. An air conditioner, characterized in that, The air conditioner employs the defrosting control method as described in any one of claims 1-11; or, The air conditioner includes a defrosting control device as described in any one of claims 12-13; or, The air conditioner includes the electronic device as described in claim 14.

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