Air conditioner defrosting control method, air conditioner and storage medium

Abstract

This invention provides an air conditioner defrosting control method, an air conditioner, and a storage medium. The method includes: in the air conditioner's heating operation state, determining whether the current operating condition meets the preset defrosting trigger condition; if so, obtaining a first objective function representing the time required for the outdoor unit pipe temperature to rise to a preset safety value after defrosting, a second objective function representing the duration between the end of the previous defrosting and the start of the current defrosting, and a third objective function representing the total energy consumption of the current defrosting process; solving the first, second, and third objective functions using a preset algorithm to obtain a Pareto optimal solution set for the defrosting strategy; obtaining the optimal defrosting strategy from the Pareto optimal solution set as the current defrosting strategy, and controlling the air conditioner to defrost according to the current defrosting strategy. Applying this air conditioner defrosting control method can reduce the total system energy consumption while ensuring thorough defrosting and continuous heating, achieving a comprehensive improvement in energy consumption, comfort, and reliability.

Description

Technical Field

[0001] This invention relates to the field of air conditioning technology, specifically to an air conditioning defrosting control method, an air conditioner using the air conditioning defrosting control method, and a computer-readable storage medium using the air conditioning defrosting control method. Background Technology

[0002] In cold climates, the heating performance and reliability of air-source heat pump air conditioners face severe challenges. When the surface temperature of the outdoor heat exchanger drops below the dew point, water vapor in the air condenses and freezes on its surface, forming a frost layer. As the frost layer continues to thicken, its thermal resistance effect significantly reduces heat exchange efficiency, leading to a sharp decline in the air conditioner's heating capacity, and in severe cases, even causing system failure. Therefore, developing efficient and precise defrosting control strategies is crucial for ensuring the stable operation of air conditioners in low-temperature environments.

[0003] Existing defrosting technologies are mainly divided into two categories. One is trigger-based control based on time or fixed temperature difference. Its logic is simple but its adaptability is poor, and it is easy to make misjudgments such as "defrosting without frost" or "not defrosting with frost". The other is dynamic judgment based on physical parameters, such as assessing the frost status by monitoring the outdoor fan current or the temperature decay rate of the indoor coil, or making predictions by integrating parameters such as ambient temperature, humidity and pressure. Some solutions even introduce neural network models to improve the accuracy of judgment.

[0004] However, existing methods generally simplify defrosting control into a single-objective optimization problem. For example, in one existing method, the defrosting control logic focuses solely on reducing energy consumption, failing to consider key performance indicators such as defrosting thoroughness and heating continuity in a unified manner. This single-objective defrosting approach is prone to the following drawbacks: to ensure thorough defrosting, the defrosting time needs to be extended, inevitably increasing energy consumption; to reduce the number of defrosting cycles to ensure heating continuity, excessively long intervals may lead to thick frost layers, which in turn exacerbates the difficulty and energy consumption of the next defrosting cycle. Furthermore, existing control strategies are mostly static rules, making it difficult to dynamically adjust according to the actual needs of users in different scenarios, lacking adaptive capabilities.

[0005] Therefore, there is an urgent need for a more optimized air conditioning defrosting control method. Summary of the Invention

[0006] The primary objective of this invention is to provide an air conditioning defrosting control method that can reduce the total energy consumption of the system while ensuring thorough defrosting and continuous heating, thereby achieving a comprehensive improvement in energy consumption, comfort, and reliability.

[0007] The second objective of this invention is to provide an air conditioner that can reduce the total energy consumption of the system while ensuring thorough defrosting and continuous heating, thereby achieving a comprehensive improvement in energy consumption, comfort, and reliability.

[0008] A third objective of this invention is to provide a computer-readable storage medium that can reduce the total energy consumption of the system while ensuring thorough defrosting and continuous heating, thereby achieving a comprehensive improvement in energy consumption, comfort, and reliability.

[0009] To achieve the aforementioned first objective, the air conditioner defrosting control method provided by the present invention includes: under the air conditioner heating operation state, determining whether the current operating condition meets the preset defrosting trigger condition; if so, obtaining a first objective function of the time required for the outdoor unit pipe temperature to rise to a preset safety value after defrosting, a second objective function of the duration between the end of the previous defrosting and the start of the current defrosting, and a third objective function of the total energy consumption of the current defrosting process; solving the first objective function, the second objective function, and the third objective function using a preset optimization algorithm to obtain the Pareto optimal solution set of the defrosting strategy; obtaining the optimal defrosting strategy from the Pareto optimal solution set as the current defrosting strategy, and controlling the air conditioner to defrost according to the current defrosting strategy.

[0010] As can be seen from the above scheme, the air conditioner defrosting control method of the present invention models the defrosting control problem as a multi-objective optimization problem including three objectives: "the time required for the outdoor unit temperature to rise to the preset safe value after defrosting", "the time from the end of the last defrosting to the start of the current defrosting", and "the total energy consumption of the current defrosting process". The problem is solved by optimization algorithm and a set of Pareto optimal solutions is obtained, which effectively solves the problem of the single defrosting control objective in the prior art, which makes it difficult to take into account the thoroughness of defrosting, the continuity of heating and energy saving, and achieves a comprehensive improvement in energy consumption, comfort and reliability.

[0011] In a further scheme, the first objective function is: Minimize F1=T1, where T1 is the time required for the outdoor unit pipe temperature to rise to the preset safe value after defrosting; the second objective function is: Minimize F2=1 / T2, where T2 is the time between the end of the previous defrosting and the start of the current defrosting; the third objective function is: Minimize F3=E3, where E3 is the total energy consumption of this defrosting process.

[0012] Therefore, the smaller the calculated value of the first objective function, the faster the defrosting speed and the higher the thoroughness of defrosting. The smaller the calculated value of the second objective function, the fewer defrosting cycles per unit time, the lower the defrosting frequency, and the better the heating continuity. The smaller the calculated value of the third objective function, the more energy-efficient the defrosting process.

[0013] In a further scheme, the steps of solving the first objective function, the second objective function, and the third objective function using a preset algorithm to obtain the Pareto optimal solution of the defrosting strategy include: encoding the control parameters in the defrosting strategy into chromosomes; using a genetic algorithm to solve the first objective function, the second objective function, and the third objective function, and performing iterative convergence to obtain the Pareto optimal solution.

[0014] In a further scheme, the steps of solving the first objective function, the second objective function, and the third objective function using a preset algorithm to obtain the Pareto optimal solution of the defrosting strategy include: treating the control parameters in the defrosting strategy as particles; using the particle swarm optimization algorithm to solve the first objective function, the second objective function, and the third objective function, and performing iterative convergence to obtain the Pareto optimal solution.

[0015] Therefore, it can be seen that the first objective function, the second objective function, and the third objective function can be solved using preset algorithms as needed, thereby increasing the application scenarios.

[0016] In a further scheme, the step of obtaining the optimal defrosting strategy from the Pareto optimal solution set as the current defrosting strategy includes: obtaining the current user preference mode, and obtaining the current defrosting strategy from the Pareto optimal solution set according to the current user preference mode.

[0017] Therefore, dynamically selecting the optimal strategy based on the user's current user preference pattern can achieve personalized and intelligent control, thereby improving the user experience.

[0018] In a further scheme, the step of obtaining the current defrosting strategy from the Pareto optimal solution set according to the current user preference mode includes: when the current user preference mode is the energy saving priority mode, obtaining the defrosting strategy with the smallest calculated value of the third objective function from the Pareto optimal solution set as the current defrosting strategy.

[0019] Therefore, since the calculated value of the third objective function represents the total energy consumption, under the energy-saving priority mode, the defrosting strategy that obtains the smallest calculated value of the third objective function from the Pareto optimal solution set is taken as the current defrosting strategy, and the energy consumption problem can be given priority.

[0020] In a further scheme, the step of obtaining the current defrosting strategy from the Pareto optimal solution set according to the current user preference mode includes: when the current user preference mode is the comfort priority mode, the defrosting strategy with the smallest weighted sum of the calculated values ​​of the first objective function and the second objective function in the Pareto optimal solution set is taken as the current defrosting strategy.

[0021] Therefore, the calculated value of the first objective function represents the defrosting time, and the calculated value of the second objective function represents the defrosting interval. Choosing a defrosting strategy with smaller defrosting time and defrosting interval can prioritize ensuring the stability of indoor heating and the comfort of users.

[0022] In a further scheme, the step of obtaining the current defrosting strategy from the Pareto optimal solution set according to the current user preference mode includes: when the current user preference mode is the balanced mode, the defrosting strategy with the smallest weighted sum of the calculated values ​​of the first objective function, the second objective function, and the third objective function in the Pareto optimal solution set is taken as the current defrosting strategy.

[0023] Therefore, by weighting and summing the calculated values ​​of the first, second, and third objective functions in the defrosting strategy, and selecting the defrosting strategy with the smallest weighted sum as the current defrosting strategy, a comprehensive optimal strategy can be chosen among the three objectives.

[0024] In a further scheme, the step of obtaining the current defrosting strategy from the Pareto optimal solution set according to the current user preference mode includes: when the current user preference mode is fast defrosting mode, obtaining the defrosting strategy with the smallest calculated value of the first objective function from the Pareto optimal solution set as the current defrosting strategy.

[0025] Therefore, the calculated value of the first objective function represents the defrosting time. Taking the defrosting strategy with the shortest defrosting time as the current defrosting strategy can ensure rapid defrosting.

[0026] To achieve the second objective of the present invention, the present invention provides an air conditioner including a processor and a memory, the memory storing a computer program, which, when executed by the processor, implements the steps of the above-described air conditioner defrosting control method.

[0027] To achieve the third objective of the present invention, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a controller, implements the steps of the above-described air conditioning defrosting control method. Attached Figure Description

[0028] Figure 1 This is a structural block diagram of an air conditioner using the defrosting control method of the present invention.

[0029] Figure 2 This is a flowchart of an embodiment of the air conditioner defrosting control method of the present invention.

[0030] Figure 3 This is a schematic diagram of the Pareto optimal solution set in an embodiment of the air conditioner defrosting control method of the present invention.

[0031] The present invention will be further described below with reference to the accompanying drawings and embodiments. Detailed Implementation

[0032] Various exemplary embodiments of the invention will now be described in detail with reference to the accompanying drawings. The descriptions of the exemplary embodiments are merely illustrative and are in no way intended to limit the invention or its application or use. The invention can be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to make the invention thorough and complete, and to fully express the scope of the invention to those skilled in the art. It should be noted that, unless otherwise specifically stated, the relative arrangement of components and steps, the composition of materials, numerical expressions, and values ​​set forth in these embodiments should be interpreted as merely exemplary and not as limiting.

[0033] The terms "first," "second," and similar words used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different parts. Words such as "including" or "comprising" mean that the element preceding the word encompasses the element listed after it, without excluding the possibility of encompassing other elements. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0034] In this invention, when a specific device is described as being located between a first device and a second device, an intermediary device may or may not be present between the specific device and the first or second device. When a specific device is described as being connected to other devices, the specific device may be directly connected to the other devices without an intermediary device, or it may be not directly connected to the other devices but have an intermediary device.

[0035] All terms used in this invention (including technical or scientific terms) have the same meaning as understood by one of ordinary skill in the art, unless otherwise specifically defined. It should also be understood that terms defined in general dictionaries should be interpreted as having the meaning consistent with their meaning in the context of the relevant art, and not as having an idealized or highly formalized meaning, unless expressly defined herein.

[0036] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0037] Example of air conditioner defrosting control method: The air conditioner defrosting control method of the present invention is an application program used in an air conditioner to control the defrosting of the air conditioner. In this embodiment, see... Figure 1The air conditioner includes a controller 1, an air conditioner operation data acquisition system 2, and an actuator 3. Both the air conditioner operation data acquisition system 2 and the actuator 3 are electrically connected to the controller 1. The air conditioner operation data acquisition system 2 is used to detect operating data during air conditioner operation, such as the outdoor unit pipe temperature, outdoor ambient temperature, compressor frequency, and electronic expansion valve opening data. The actuator 3 is used to execute control commands issued by the controller 1. The actuator 3 includes a compressor, an electronic expansion valve, and a four-way valve. The controller 1, air conditioner operation data acquisition system 2, and actuator 3 can adopt well-known air conditioner structures, which will not be described in detail here.

[0038] like Figure 2 As shown, the air conditioner defrosting control method of this embodiment first executes step S1 to determine whether the air conditioner is in heating mode. When the air conditioner is in heating mode, if the surface temperature of the outdoor heat exchanger is low, water vapor in the air will condense and freeze on its surface, forming a frost layer, thereby reducing heat exchange efficiency. Therefore, defrosting is usually required when the air conditioner is in heating mode. When heating is needed, the user can send a command to enter heating mode through the controller or control panel. After receiving the command to enter heating mode, the air conditioner controller considers it to be in heating mode and can operate according to the temperature set by the user.

[0039] If the air conditioner is not in heating mode, proceed to step S1 to continuously monitor its heating status. If the air conditioner is in heating mode, proceed to step S2 to determine if the current operating conditions meet the preset defrost trigger conditions. These preset defrost trigger conditions can be pre-set based on experimental data; for example, if the outdoor unit pipe temperature is below -5℃ and the outdoor ambient humidity is above 75%, the preset defrost trigger conditions are considered met. During heating operation, the air conditioner continuously monitors operating parameters such as the outdoor heat exchanger pipe temperature, outdoor ambient temperature, and ambient humidity, and uses these parameters to determine if the current operating conditions meet the preset defrost trigger conditions.

[0040] If the current operating conditions do not meet the preset defrost trigger conditions, proceed to step S2 to continuously monitor the preset defrost trigger conditions and maintain heating operation. If the current operating conditions meet the preset defrost trigger conditions, proceed to step S3 to obtain the first objective function of the time required for the outdoor unit pipe temperature to rise to the preset safety value after defrosting, the second objective function of the duration between the end of the last defrost and the start of the current defrost, and the third objective function of the total energy consumption of the current defrost process. The preset safety value can be preset based on experimental data; for example, the preset safety value is -10℃. To ensure thorough defrosting, continuous heating, and reduced total system energy consumption, corresponding objective functions and constraints need to be established for these three objectives.

[0041] In this embodiment, the first objective function is: Minimize F1 = T1, where T1 is the time required for the outdoor unit pipe temperature to rise to a preset safe value after defrosting; the second objective function is: Minimize F2 = 1 / T2, where T2 is the time between the end of the previous defrosting and the start of the current defrosting; the third objective function is: Minimize F3 = E3, where E3 is the total energy consumption of this defrosting process. Where T1 = T end -T start T start The outdoor unit pipe temperature at the start of the defrosting process, T end This represents the moment when the outdoor unit's pipe temperature rises to a preset safe value. The smaller the calculated value of the first objective function, the faster the defrosting speed and the more thorough the defrosting. T2=T current_defrost_start -T last_defrost_end T current_defrost_start T is the system time at which this defrosting started. last_defrost_end The system time from the end of the last defrost cycle is denoted as F3. A smaller calculated value for the second objective function indicates fewer defrost cycles per unit time, a lower defrost frequency, and better heating continuity. F3 = ∫(P(t)dt), where P(t) is the instantaneous power during the defrost process. This is measured by sampling the real-time power consumption of key components such as the compressor, fan, and four-way valve using the air conditioner's built-in energy metering module (such as a power sensor or smart meter chip) during defrost, and integrating this data over time to obtain the total energy consumption F3 for this defrost cycle. A smaller calculated value for the third objective function indicates a more energy-efficient defrost process.

[0042] In this embodiment, constraints also need to be established, as follows: T1 ≤ first preset duration; T2 ≥ second preset duration; E3 ≤ preset maximum allowable defrosting energy consumption; indoor temperature drop ΔT in ≤Preset temperature. The first preset duration, second preset duration, preset power consumption, and preset temperature can be preset based on experimental data. For example, T1 ≤ 12 minutes; T2 ≥ 45 minutes; E3 ≤ 2.5 kWh; ΔT in ≤2℃. By setting constraints on the time required for the outdoor unit pipe temperature to rise to a preset safe value after defrosting and the duration between the end of the last defrost and the start of the current defrost, thorough defrosting can be ensured, heating continuity guaranteed, and excessively frequent defrosting avoided. Simultaneously, to ensure the defrosting process operates within acceptable energy consumption limits, an energy consumption constraint is set: E3 ≤ preset maximum allowable defrosting energy consumption. This preset maximum allowable defrosting energy consumption can be set based on the air conditioner's rated power, historical operating data, and energy efficiency standards. This prevents excessive power consumption due to improper defrosting strategies, ensuring the system's economy and reliability. Furthermore, the rate of indoor temperature drop is also constrained to ensure it does not exceed the comfort threshold.

[0043] After obtaining the objective function, step S4 is executed to solve the first, second, and third objective functions using a preset algorithm, thereby obtaining the Pareto optimal solution set for the defrosting strategy. To obtain the optimal defrosting strategy, the first, second, and third objective functions are solved using a preset algorithm, thus obtaining the Pareto optimal solution set for the defrosting strategy. The number of Pareto optimal solutions in the Pareto optimal solution set can be set as needed; in this embodiment, the number of Pareto optimal solutions is 5. The obtained Pareto optimal solution set is as follows: Figure 3 As shown.

[0044] In one embodiment, the step of solving the first objective function, the second objective function, and the third objective function using a preset algorithm to obtain the Pareto optimal solution of the defrosting strategy includes: encoding the control parameters in the defrosting strategy into chromosomes; solving the first objective function, the second objective function, and the third objective function using a genetic algorithm, and performing iterative convergence to obtain the Pareto optimal solution.

[0045] Specifically, the control parameters of the defrosting strategy include defrosting duration, compressor frequency, and defrosting start timing. The solution process using a genetic algorithm is as follows: 1. Encoding: Encode a defrosting strategy S=(t,f,s) as a "chromosome". Here, t (defrosting duration) can be encoded as a real number (e.g., 300-900 seconds), f (compressor frequency) as a real number (e.g., 30-70Hz), and s (defrosting start time) as a Boolean value (0=immediate, 1=delayed) or a time offset; 2. Initialization: Randomly generate an initial population consisting of N chromosomes (e.g., N=50); 3. Fitness Assessment: For each chromosome in the population, the controller simulates the frost removal strategy or extrapolates from historical data models to calculate its corresponding F1, F2, and F3. Then, a fitness value is assigned to each individual through non-dominated sorting and crowding distance calculation. 4. Selection: Individuals are selected from the parent population based on their fitness values ​​using methods such as tournament selection. 5. Crossover and Mutation: Perform operations such as "arithmetic crossover" and "Gaussian mutation" on the selected parent generation to generate the offspring population; 6. Iteration and Convergence: Merge the parent and offspring generations, perform non-dominated sorting and crowding calculation again, and select N optimal individuals to enter the next generation. Repeat this process (e.g., 100 generations) until the population converges. The final non-dominated solution set is the Pareto optimal solution set.

[0046] In another embodiment, the step of solving the first objective function, the second objective function, and the third objective function using a preset algorithm to obtain the Pareto optimal solution of the defrosting strategy includes: treating the control parameters in the defrosting strategy as particles; solving the first objective function, the second objective function, and the third objective function using a particle swarm optimization algorithm, and performing iterative convergence to obtain the Pareto optimal solution.

[0047] Specifically, the control parameters of the defrosting strategy include defrosting duration, compressor frequency, and defrosting start timing. The solution process using the Particle Swarm Optimization (PSO) algorithm is as follows: 1. Initialization: Randomly generate N "particles" (e.g., N=50). The position X of each particle i is... i =(t i ,f i ,s i ) represents a defrosting strategy, t i For the duration of time it takes to turn into frost, f i For compressor frequency, s i For the start of frost, speed V i It is a vector; 2. Evaluation: Calculate F1, F2, and F3 for each particle; 3. Update individual and group optimal values: Record the historical best position P of each particle i. best i Record all Ps in the entire group best i The Pareto optimal solution set constituted is used as the global optimal G. best ; 4. Velocity and Position Update: For each particle, its velocity and position are updated according to the following formula: V i (k+1)=ω×V i (k)+c1×r1×(P best i -X i (k))+c2×r2×(G best -X i (k)), X i (k+1)=X i (k)+V i (k+1), where ω is the inertia weight, c1 and c2 are learning factors, and r1 and r2 are random numbers between [0,1]. 5. Iteration: Repeat steps 2-4 until the maximum number of iterations is reached (e.g., 100 generations). Ultimately, G... best The set of particles in the solution is the Pareto optimal solution set.

[0048] In this embodiment, after obtaining the Pareto optimal solution set of the defrosting strategy, step S5 is executed to obtain the optimal defrosting strategy from the Pareto optimal solution set as the current defrosting strategy, and then control the air conditioner to defrost according to the current defrosting strategy. Since there are multiple Pareto optimal solutions in the Pareto optimal solution set, in order to ensure that the defrosting strategy best matches the current operating conditions, it is necessary to obtain the optimal defrosting strategy from the Pareto optimal solution set to control the air conditioner defrosting, thereby improving the accuracy of defrosting.

[0049] In this embodiment, the step of obtaining the optimal defrosting strategy from the Pareto optimal solution set as the current defrosting strategy includes: obtaining the current user preference mode, and obtaining the current defrosting strategy from the Pareto optimal solution set according to the current user preference mode. The current user preference mode can be set by the user. Dynamically selecting the optimal strategy based on the user-defined current user preference mode enables personalized and intelligent control, improving the user experience.

[0050] In this embodiment, the step of obtaining the current defrosting strategy from the Pareto optimal solution set according to the current user preference mode includes: when the current user preference mode is energy-saving priority mode, obtaining the defrosting strategy with the smallest calculated value of the third objective function from the Pareto optimal solution set as the current defrosting strategy. Since the calculated value of the third objective function represents the total energy consumption, in energy-saving priority mode, obtaining the defrosting strategy with the smallest calculated value of the third objective function from the Pareto optimal solution set as the current defrosting strategy can prioritize energy consumption.

[0051] In this embodiment, the step of obtaining the current defrosting strategy from the Pareto optimal solution set according to the current user preference mode further includes: when the current user preference mode is comfort-first mode, the defrosting strategy with the smallest weighted sum of the calculated values ​​of the first objective function and the second objective function in the Pareto optimal solution set is selected as the current defrosting strategy. The weighted sum of the calculated values ​​of the first objective function and the second objective function is calculated using the following formula: w1×F1+w2×F2, where w1 and w2 are preset weights. The calculated value of the first objective function represents the defrosting time, and the calculated value of the second objective function represents the defrosting interval. Selecting a defrosting strategy with smaller defrosting time and defrosting interval can prioritize ensuring the stability of indoor heating and user comfort.

[0052] In this embodiment, the step of obtaining the current defrosting strategy from the Pareto optimal solution set based on the current user preference mode further includes: when the current user preference mode is a balanced mode, the defrosting strategy with the smallest weighted sum of the calculated values ​​of the first objective function, the second objective function, and the third objective function in the Pareto optimal solution set is taken as the current defrosting strategy. The weighted sum of the calculated values ​​of the first objective function, the second objective function, and the third objective function is calculated using the following formula: F = w3 × F1 + w4 × F2 + w5 × F3, where the weights w3, w4, and w5 can be based on system defaults or user settings. By performing a weighted summation of the calculated values ​​of the first objective function, the second objective function, and the third objective function in the defrosting strategy, and taking the defrosting strategy with the smallest weighted sum as the current defrosting strategy, a strategy that comprehensively optimizes the three objectives can be selected.

[0053] In this embodiment, the step of obtaining the current defrosting strategy from the Pareto optimal solution set according to the current user preference mode further includes: when the current user preference mode is a fast defrosting mode, obtaining the defrosting strategy with the smallest calculated value of the first objective function from the Pareto optimal solution set as the current defrosting strategy. The calculated value of the first objective function represents the defrosting time; using the defrosting strategy with the smallest defrosting time as the current defrosting strategy ensures fast defrosting.

[0054] After obtaining the current defrosting strategy, the air conditioner can be controlled to defrost according to this strategy. In a specific example, the determined current defrosting strategy is: defrosting duration t = 10 minutes, compressor frequency f = 40Hz, and defrosting start time s = "immediately". The air conditioner controller then executes the defrosting process according to this strategy: the compressor runs at a frequency of 40Hz for 10 minutes, and the opening of the electronic expansion valve can be controlled during this period to achieve precise management of the defrosting process. During the defrosting process, the system continuously monitors the outdoor unit pipe temperature, ensuring that it rises back to above -10℃ within 12 minutes, and that the indoor temperature drops by no more than 2℃.

[0055] As described above, the air conditioner defrosting control method of the present invention models the defrosting control problem as a multi-objective optimization problem with three objectives: "the time required for the outdoor unit temperature to rise to the preset safe value after defrosting", "the time from the end of the last defrosting to the start of the current defrosting", and "the total energy consumption of the current defrosting process". The problem is solved by an optimization algorithm and a set of Pareto optimal solutions is obtained. This effectively solves the problem in the prior art that the defrosting control objective is single and it is difficult to take into account the thoroughness of defrosting, the continuity of heating and energy saving. This achieves a comprehensive improvement in energy consumption, comfort and reliability.

[0056] Air conditioner example: The air conditioner in this embodiment includes a controller, which executes the steps in the above-described air conditioner defrosting control method embodiment when executing a computer program.

[0057] For example, a computer program can be divided into one or more modules, one or more of which are stored in memory and executed by a controller to complete the present invention. One or more modules can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in an air conditioner.

[0058] An air conditioner may include, but is not limited to, a controller and a memory. Those skilled in the art will understand that an air conditioner may include more or fewer components, or a combination of certain components, or different components; for example, an air conditioner may also include input / output devices, network access devices, buses, etc.

[0059] For example, the controller can be a Central Processing Unit (CPU), or other general-purpose controllers, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose controller can be a microcontroller or any conventional controller. The controller is the control center of the air conditioner, connecting all parts of the air conditioner through various interfaces and lines.

[0060] The memory can be used to store computer programs and / or modules. The controller implements various functions of the air conditioner by running or executing the computer programs and / or modules stored in the memory, and by calling the data stored in the memory. For example, the memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound receiving function, sound-to-text function, etc.), etc.; the data storage area may store data created based on the use of the mobile phone (such as audio data, text data, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0061] Examples of computer-readable storage media: If the modules integrated into the air conditioner in the above embodiments are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above air conditioner defrosting control method embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a controller, it can implement the steps of the above air conditioner defrosting control method embodiments. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The storage medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content contained in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0062] It should be noted that the above are only preferred embodiments of the present invention, but the design concept of the invention is not limited thereto. Any non-substantial modifications made to the present invention using this concept also fall within the protection scope of the present invention.

Claims

1. An air conditioner defrosting control method, characterized in that: include: When the air conditioner is in heating mode, determine whether the current operating condition meets the preset defrost trigger condition. If so, obtain the first objective function of the time required for the outdoor unit pipe temperature to rise to the preset safe value after defrosting, the second objective function of the time between the end of the last defrost and the start of the current defrost, and the third objective function of the total energy consumption of the current defrost process. The first objective function, the second objective function, and the third objective function are solved using a preset algorithm to obtain the Pareto optimal solution set of the defrosting strategy; The optimal defrosting strategy is obtained from the Pareto optimal solution set as the current defrosting strategy, and the air conditioner is controlled to defrost according to the current defrosting strategy.

2. The air conditioning defrosting control method according to claim 1, characterized in that: The first objective function is: Minimize F1=T1, where T1 is the time required for the outdoor unit pipe temperature to rise to the preset safe value after defrosting; The second objective function is: Minimize F2 = 1 / T2, where T2 is the time between the end of the previous defrosting and the start of the current defrosting; The third objective function is: Minimize F3 = E3, where E3 is the total energy consumption of this defrosting process.

3. The air conditioning defrosting control method according to claim 1, characterized in that: The steps for solving the first, second, and third objective functions using a pre-optimization algorithm to obtain the Pareto optimal solution for the defrosting strategy include: Encode the control parameters in the defrosting strategy into chromosomes; The first objective function, the second objective function, and the third objective function are solved using a genetic algorithm, and the solution is obtained by iterative convergence.

4. The air conditioning defrosting control method according to claim 1, characterized in that: The steps for solving the first objective function, the second objective function, and the third objective function using a preset algorithm to obtain the Pareto optimal solution of the defrosting strategy include: Treat the control parameters in the defrosting strategy as particles; The first objective function, the second objective function, and the third objective function are solved using the particle swarm optimization algorithm, and the solution is obtained by iterative convergence.

5. The air conditioning defrosting control method according to any one of claims 1 to 4, characterized in that: The steps for obtaining the optimal defrosting strategy from the Pareto optimal solution set as the current defrosting strategy include: Obtain the current user preference pattern, and obtain the current defrosting strategy from the Pareto optimal solution set based on the current user preference pattern.

6. The air conditioning defrosting control method according to claim 5, characterized in that: The steps of obtaining the current defrosting strategy from the Pareto optimal solution set based on the current user preference pattern include: When the current user preference mode is the energy-saving priority mode, the defrosting strategy with the smallest calculated value of the third objective function is obtained from the Pareto optimal solution set as the current defrosting strategy.

7. The air conditioning defrosting control method according to claim 5, characterized in that: The steps of obtaining the current defrosting strategy from the Pareto optimal solution set based on the current user preference pattern include: When the current user preference mode is comfort-first mode, the defrosting strategy with the smallest weighted sum of the calculated values ​​of the first objective function and the second objective function in the Pareto optimal solution set is taken as the current defrosting strategy.

8. The air conditioning defrosting control method according to claim 5, characterized in that: The steps of obtaining the current defrosting strategy from the Pareto optimal solution set based on the current user preference pattern include: When the current user preference mode is the balanced mode, the defrosting strategy with the smallest weighted sum of the calculated values ​​of the first objective function, the second objective function, and the third objective function in the Pareto optimal solution set is taken as the current defrosting strategy.

9. The air conditioning defrosting control method according to claim 5, characterized in that: The steps of obtaining the current defrosting strategy from the Pareto optimal solution set based on the current user preference pattern include: When the current user preference mode is fast defrost mode, the defrost strategy with the smallest calculated value of the first objective function is obtained from the Pareto optimal solution set as the current defrost strategy.

10. An air conditioner, comprising a processor and a memory, characterized in that: The memory stores a computer program that, when executed by the processor, implements the steps of the air conditioning defrosting control method as described in any one of claims 1 to 9.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the controller, it implements the steps of the air conditioning defrosting control method as described in any one of claims 1 to 9.

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