A control method for optimizing the self-cleaning time period of an air conditioner

Abstract

The present invention discloses a control method for optimizing the self-cleaning time period of an air conditioner, comprising the following steps: 1) electrically connecting a controller to the air conditioner to calculate the air conditioner operating time; 2) integrating a calculation model correlating indoor fungal aerosol and particulate matter concentrations with evaporator dust accumulation, and a dust accumulation calculation model; 3) calculating a dust accumulation threshold; 3) acquiring environmental parameters and inputting them into the dust accumulation calculation model to calculate a real-time dust accumulation; 4) comparing the real-time dust accumulation with the dust accumulation threshold, and the controller determining whether a self-cleaning control mode is triggered. If so, a control instruction is issued to the air conditioner to activate the self-cleaning control mode of the air conditioner. The present invention can determine the time and frequency of the air conditioner's self-cleaning operation, avoid excessive dust accumulation in the air conditioner's evaporator due to human factors, making self-cleaning difficult to perform, and constrain the air conditioner's internal pollution within a specified range, significantly improving its self-cleaning control accuracy.

Description

Technical Field

[0001] The present invention relates to the field of indoor environmental pollution control, in particular to a control method for optimizing the self-cleaning time period of an air conditioner. Background Art

[0002] With the continuous development of today's society, air conditioners are no longer simply a means of transmitting heat and cooling. The health benefits of air conditioners are gaining increasing attention, and healthy, clean air quality has become one of the hallmarks of people's pursuit of a better life. After long-term operation, air conditioners often accumulate a large amount of dust on their evaporators. Numerous bacteria, fungi, and particulate matter can attach to this dust and enter indoor spaces along with the air supplied by the air conditioner, posing a threat to the human body.

[0003] Currently, self-cleaning methods are commonly used to remove dust from air conditioner evaporators. The following are the main existing technologies: 1) To determine internal blockage in a multi-split system, the currents of multiple indoor fan motors at the same speed are obtained after multiple consecutive startups of the indoor units. Based on these motor currents, the current decay rate is calculated, and the current decay rates of multiple indoor units are used to control the multi-split system's self-cleaning. Due to factors such as the air conditioner's operating conditions, cooling mode, and motor self-attenuation, this method can determine system blockage in the short term, but inaccuracies can occur over long periods of time. 2) To effectively remove dust accumulation from the evaporator fins and copper tubes, indoor and outdoor temperatures and the internal coil temperature are collected to control the internal fan to stop. The internal coil cooling rate is calculated within the controller, and the compressor frequency and the opening of the electronic expansion valve are adjusted accordingly. This method can address dust accumulation within the air conditioner based on the cooling rate, but it does not address when to initiate self-cleaning.

[0004] Whether the air conditioner actually starts self-cleaning or not has a lot to do with the manager's willingness. There is no technology that can control when the air conditioner starts self-cleaning in a healthy and scientific way. Summary of the Invention

[0005] The object of the present invention is to provide a control method for optimizing the self-cleaning time period of an air conditioner, comprising the following steps:

[0006] 1) Electrically connect a controller with integral calculation capability to the air conditioner to calculate the air conditioner operating time;

[0007] 2) Integrate the calculation model of the correlation between indoor fungal aerosol and particulate matter concentration and evaporator dust accumulation, as well as the dust accumulation calculation model in the controller;

[0008] 3) The dust accumulation threshold is calculated using the correlation calculation model between indoor fungal aerosol and particulate matter concentrations and evaporator dust accumulation;

[0009] 3) Obtain environmental parameters and input them into the dust accumulation calculation model to calculate the real-time dust accumulation;

[0010] 4) The real-time dust accumulation amount is compared with the dust accumulation amount threshold. Based on the comparison result, the controller determines whether the self-cleaning control mode is triggered. If so, a control instruction is sent to the air conditioner to turn on the self-cleaning control mode of the air conditioner.

[0011] Furthermore, the environmental parameters include indoor dust emission sources E k , System fresh air volume V f , System return air volume V r , filter and return air duct dust effective removal rate η f , maintenance structure permeability η p .

[0012] Furthermore, the dust accumulation amount M c As shown below:

[0013]

[0014] Where, is the dust accumulation amount of the condensing coil per unit air volume and unit particle size; t is the air conditioner operation time; d p is the particle size.

[0015] Furthermore, the dust accumulation per unit air volume and per unit particle size of the condensing coil As shown below:

[0016]

[0017] Where m in is the dust accumulation distribution function near the return air outlet of the air conditioner; m out is the dust accumulation distribution function near the fresh air outlet of the air conditioner; η f is the effective removal rate of dust accumulated in the filter and return air duct; η r is the particle deposition fraction in the return air duct; V f is the fresh air volume of the primary return air system; V r is the return air volume of the primary return air system; η e is the dust emission rate of the condensing coil; η c is the particle deposition fraction of the condensing coil;

[0018] Among them, the dust accumulation distribution function m near the return air outlet of the air conditioner in As shown below:

[0019]

[0020] Where η p is the permeability of the maintenance structure; V p is the infiltration air volume; η v is the ventilation dust removal rate; V is the indoor volume; κ is the indoor dust loss rate; η rE is the return air dust loss rate; a is the particle emission rate from indoor sources; a = r, c, s, h; r represents particles emitted from wall structures; wall structures include carpets, enclosures, and ceilings; c represents particles emitted during cooking; s represents particles emitted from smoking; and h represents particles carried by humans or animals.

[0021] Among them, the particle escape rate E of the wall structure is r As shown below:

[0022] E r =L f1 A f1 (4)

[0023] Where, L f1 A is the dust load on the wall structure; f1 is the total area of ​​the wall structure;

[0024] Ventilation dust removal rate η v , return air duct particle deposition fraction η r They are as follows:

[0025] η v =1-(1-η f )(1-η e )(1-η s ) (5)

[0026] η r =1-(1-η r )(1-η f )(1-η s )(1-η c ) (6)

[0027] Where η s is the particle deposition fraction in the air supply duct.

[0028] Furthermore, when the dust accumulation amount M c When <M1, the self-cleaning control mode is not triggered;

[0029] When the dust accumulation satisfies M1<M c When <M2, the controller issues a self-cleaning operation instruction;

[0030] When the dust accumulation satisfies M2<M c When the temperature is less than M3, the controller will issue a self-cleaning operation instruction for 2 or more times;

[0031] When the dust accumulation satisfies M3<M c When the controller sounds an alarm, it prompts the cleaning staff to perform manual cleaning operations;

[0032] Among them, M1 is the first threshold value of the dust accumulation in the evaporator;

[0033] M2 is the second threshold value of dust accumulation in the evaporator;

[0034] M3 is the third threshold value of the dust accumulation in the evaporator.

[0035] Furthermore, the dust accumulation threshold is as follows:

[0036] M i =min[f(α i ),g(β 2.5,i ),m(β 10,i )] (7)

[0037] Where, positive integer i = 1, 2, 3; α i is the indoor fungal aerosol concentration; β 2.5,i is the indoor particulate matter PM2.5 concentration; β 10,i is the indoor particulate matter PM10 concentration; f(α i ) is the relationship function between indoor fungal aerosol concentration and evaporator dust accumulation; g(β 2.5,i ) is the relationship function between indoor particulate matter PM2.5 concentration and evaporator dust accumulation; m(β 10,i ) is the relationship function between indoor particulate matter PM10 concentration and evaporator dust accumulation;

[0038] Furthermore, the indoor fungal aerosol concentration, indoor particulate matter PM2.5 concentration, and indoor particulate matter PM10 concentration are as follows:

[0039] α1=50%α xianzhi (8)

[0040] α2=75%α xianzhi (9)

[0041] α3=100%α xianzhi (10)

[0042] β 2.5,1 =50%β 2.5 (11)

[0043] β 2.5,2 =75%β 2.5 (12)

[0044] β 2.5,3 =100%β 2.5 (13)

[0045] β 10,1 =50%β 10 (14)

[0046] β 10,2=75%β 10 (15)

[0047] β 10,3 =100%β 10 (16)

[0048] Where, α xianzhi is the indoor fungal aerosol limit; β 2.5 is the concentration limit of particulate matter PM2.5; β 10 It is the concentration limit of particulate matter PM10.

[0049] The technical effect of the present invention is unquestionable. The present invention can use particulate matter and fungal pollution indicators as environmental health risk thresholds, input the environmental parameters provided by the user into the integral controller, and use the integral controller to determine whether the dust accumulation in the evaporator meets the self-cleaning trigger conditions, thereby constraining the dust accumulation in the air-conditioning evaporator to within the range of the lowest health risk to the human body and significantly improving its self-cleaning control accuracy.

[0050] The present invention first inputs environmental parameters into a novel air conditioner evaporator dust accumulation model using an integral calculation method with a daily step size. Fungal aerosol and particulate matter concentrations are used as risk indicators to control the threshold for dust accumulation on the air conditioner evaporator. The optimal self-cleaning control scheme is then calculated by combining environmental parameters and related interference terms. This control method determines the timing and frequency of air conditioner self-cleaning activation, preventing excessive dust accumulation on the air conditioner evaporator due to human factors, making self-cleaning difficult. This method constrains internal air conditioner pollution within a specified range and significantly improves the accuracy of self-cleaning control. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 is a method control flow chart;

[0052] Figure 2 Figure 1 is the experimental setup diagram;

[0053] Figure 3 The graph of the total number of suspended particles changing with the amount of dust accumulation when H / D = 0.77;

[0054] Figure 4 This is the graph showing the change of the total number of suspended particles with the amount of dust accumulation when H / D=20;

[0055] Figure 5 This is a conversion chart for the total number of suspended particles and the amount of dust accumulated. DETAILED DESCRIPTION

[0056] The present invention will be further described below with reference to the following examples, but it should not be understood that the scope of the present invention is limited to the following examples. Without departing from the above technical ideas of the present invention, various substitutions and modifications can be made according to common technical knowledge and customary means in the art, and all should be included in the scope of protection of the present invention.

[0057] Example 1:

[0058] See also Figures 1 to 5 , a control method for optimizing the self-cleaning time period of an air conditioner, comprising the following steps:

[0059] 1) Electrically connect a controller with integral calculation capability to the air conditioner to calculate the air conditioner operating time;

[0060] 2) Integrate the calculation model of the correlation between indoor fungal aerosol and particulate matter concentration and evaporator dust accumulation, as well as the dust accumulation calculation model in the controller;

[0061] 3) The dust accumulation threshold is calculated using the correlation calculation model between indoor fungal aerosol and particulate matter concentrations and evaporator dust accumulation;

[0062] 3) Obtain environmental parameters and input them into the dust accumulation calculation model to calculate the real-time dust accumulation;

[0063] 4) The real-time dust accumulation amount is compared with the dust accumulation amount threshold. Based on the comparison result, the controller determines whether the self-cleaning control mode is triggered. If so, a control instruction is sent to the air conditioner to turn on the self-cleaning control mode of the air conditioner.

[0064] The environmental parameters include indoor dust emission sources E k , System fresh air volume V f , System return air volume V r , filter and return air duct dust effective removal rate η f , maintenance structure permeability η p .

[0065] Dust accumulation M c As shown below:

[0066]

[0067] Where, is the dust accumulation amount of the condensing coil per unit air volume and unit particle size; t is the air conditioner operation time; d p is the particle size.

[0068] Dust accumulation per unit air volume and particle size per condensing coil As shown below:

[0069]

[0070] Where m in is the dust accumulation distribution function near the return air outlet of the air conditioner; m out is the dust accumulation distribution function near the fresh air outlet of the air conditioner; η f is the effective removal rate of dust accumulated in the filter and return air duct; η r is the particle deposition fraction in the return air duct; V f is the fresh air volume of the primary return air system; V r is the return air volume of the primary return air system; η e is the dust emission rate of the condensing coil; η c is the particle deposition fraction of the condensing coil;

[0071] Among them, the dust accumulation distribution function m near the return air outlet of the air conditioner in As shown below:

[0072]

[0073] Where η p is the permeability of the maintenance structure; V p is the infiltration air volume; η v is the ventilation dust removal rate; V is the indoor volume; κ is the indoor dust loss rate; η r E is the return air dust loss rate; a is the particle emission rate from indoor sources; a = r, c, s, h; r represents particles emitted from wall structures; wall structures include carpets, enclosures, and ceilings; c represents particles emitted during cooking; s represents particles emitted from smoking; and h represents particles carried by humans or animals.

[0074] Among them, the particle escape rate E of the wall structure is r As shown below:

[0075] E r =L f1 A f1 (4)

[0076] Where, L f1 A is the dust load on the wall structure; f1 is the total area of ​​the wall structure;

[0077] Ventilation dust removal rate η v , return air duct particle deposition fraction η r They are as follows:

[0078] η v =1-(1-η f )(1-η e )(1-η s ) (5)

[0079] η r =1-(1-ηr )(1-η f )(1-η s )(1-η c ) (6)

[0080] Where η s is the particle deposition fraction in the air supply duct.

[0081] When the dust accumulation amount M c When <M1, the self-cleaning control mode is not triggered;

[0082] When the dust accumulation satisfies M1<M c When <M2, the controller issues a self-cleaning operation instruction;

[0083] When the dust accumulation satisfies M2<M c When the temperature is less than M3, the controller will issue a self-cleaning operation instruction for 2 or more times;

[0084] When the dust accumulation satisfies M3<M c When the controller sounds an alarm, it prompts the cleaning staff to perform manual cleaning operations;

[0085] Among them, M1 is the first threshold value of the dust accumulation in the evaporator;

[0086] M2 is the second threshold value of dust accumulation in the evaporator;

[0087] M3 is the third threshold value of the dust accumulation in the evaporator.

[0088] The dust accumulation thresholds are as follows:

[0089] M i =min[f(α i ),g(β 2.5,i ),m(β 10,i )] (7)

[0090] Where, positive integer i = 1, 2, 3; α i is the indoor fungal aerosol concentration; β 2.5,i is the indoor particulate matter PM2.5 concentration; β 10,i is the indoor particulate matter PM10 concentration; f(α i ) is the relationship function between indoor fungal aerosol concentration and evaporator dust accumulation; g(β 2.5,i ) is the relationship function between indoor particulate matter PM2.5 concentration and evaporator dust accumulation; m(β 10,i ) is the relationship function between the indoor particulate matter PM10 concentration and the evaporator dust accumulation; the dust accumulation threshold is selected as follows: the evaporator dust accumulation is calculated using the three relationship functions respectively, and the minimum value is selected as the dust accumulation threshold.

[0091] The indoor fungal aerosol concentration, indoor particulate matter PM2.5 concentration, and indoor particulate matter PM10 concentration are as follows:

[0092] α1=50%α xianzhi (8)

[0093] α2=75%α xianzhi (9)

[0094] α3=100%α xianzhi (10)

[0095] β 2.5,1 =50%β 2.5 (11)

[0096] β 2.5,2 =75%β 2.5 (12)

[0097] β 2.5,3 =100%β 2.5 (13)

[0098] β 10,1 =50%β 10 (14)

[0099] β 10,2 =75%β 10 (15)

[0100] β 10,3 =100%β 10 (16)

[0101] Where, α xianzhi is the indoor fungal aerosol limit; β 2.5 is the concentration limit of particulate matter PM2.5; β 10 It is the concentration limit of particulate matter PM10.

[0102] Example 2:

[0103] See also Figures 1 to 3 , a control method for optimizing the self-cleaning time period of an air conditioner, comprising the following steps:

[0104] (1) The degree of fungal contamination inside the air conditioner is determined by integrally calculating the amount of dust accumulated on the condensing coil inside the air conditioner; (2) The dust accumulation threshold is determined using a correlation model between indoor particulate matter concentration, fungal aerosol concentration and evaporator dust accumulation; (3) The dust accumulation threshold, indoor source, outdoor source and other parameters are input into the air conditioner internal controller, so that the air conditioner self-cleaning action can be automatically turned on before cooling or heating according to the controller instruction. The dust condenses and heats quickly, causing the ice film to fall off and fall into the water collection tray, thereby effectively controlling the fungal contamination inside the air conditioner within a certain period.

[0105] The specific steps are as follows:

[0106] Step 1: First, build a controller with integral calculation capabilities on the home air conditioner, allowing it to calculate the time the air conditioner is on and off in steps of days;

[0107] Step 2: To initialize the calculation conditions, run the air conditioner self-cleaning program once after installing the controller;

[0108] Step 3: Input the calculation formula of the correlation model between indoor fungal aerosol, particulate matter concentration and evaporator dust accumulation into the controller. The model can calculate the dust accumulation threshold value based on the pollutant concentration limit;

[0109] Step 4: The user / manager inputs the environmental parameters such as indoor furniture, floor, people in the room, indoor and outdoor dust concentration distribution function into the controller based on the original environmental characteristics;

[0110] Step 5: Compare the dust accumulation amount calculated by the controller with the threshold to determine whether the self-cleaning mode triggering condition is met;

[0111] Step 6: If the self-cleaning trigger condition is met, a command is sent to the air conditioning self-cleaning control module.

[0112] The control method calculates the self-cleaning cycle according to indoor environmental characteristics and then issues a self-cleaning instruction.

[0113] The method includes connecting an internal controller of an air conditioner to a self-cleaning start-up program of the air conditioner, and can perform parameter input and signal output.

[0114] The controller can input the indoor dust emission source E k , system fresh air volume V f , system fresh air volume V r , filter (including return air duct) dust removal rate η f , maintenance structure permeability η p and other parameters.

[0115] After the controller inputs the parameters, the dust accumulation amount M of each evaporator can be calculated by the evaporator dust accumulation formula. c , the calculation formula is shown in Formula 1.

[0116]

[0117] The controller calculates the amount of dust accumulated in the evaporator M i,tot Under the conditions, make the following judgments:

[0118] If M c <M1, the controller does not issue a self-cleaning command;

[0119] If M1<M c <M2, the controller issues a self-cleaning operation instruction;

[0120] If M2<M c <M3, the controller will issue a self-cleaning operation instruction for 2 or more times;

[0121] If M3<M c , the controller will sound an alarm to prompt the cleaning staff to perform manual cleaning operations;

[0122] Wherein, M1 is the first threshold value of dust accumulation in the evaporator, g / month;

[0123] M2 is the second threshold value of dust accumulation on the evaporator, g / month;

[0124] M3 is the third threshold of dust accumulation on the evaporator, g / month;

[0125] Evaporator dust accumulation M i , i = 1, 2, 3, are derived from the correlation model Ω between indoor hazard factors and air conditioner evaporator dust accumulation. In the correlation model Ω, indoor fungal aerosol concentration α, indoor particulate matter PM2.5 concentration β 2.5 , PM10 concentration β 10 It is in a functional relationship with the amount of dust accumulated in the evaporator M, which can be expressed as shown in Formula 2. The specific values ​​in the formula can be obtained from laboratory field tests.

[0126] M i =min[f(α i ),g(β 2.5,i ),m(β 10,i )] (2)

[0127] Where i = 1, 2, 3. Indoor fungal aerosol α i The prescribed reference limit value α xianzhi =1000 CFU / m 3 , determined by formula 3-5.

[0128] α1=50%α xianzhi (3)

[0129] α2=75%α xianzhi (4)

[0130] α3=100%α xianzhi (5)

[0131] β 2.5 , β 10 The limit value refers to the provisions of my country's "Indoor Air Quality Standard" GB18883-2022, where the concentration of particulate matter PM2.5 β 2.5 =0.05mg / m3 , PM10 concentration β 10 =0.1mg / m 3 (Use the 24-hour average value). 2.5,i According to formula 6-8, β 10,i same.

[0132] β 2.5,1 =50%β 2.5 (6)

[0133] β 2.5,2 =75%β 2.5 (7)

[0134] β 2.5,3 =100%β 2.5 (8)

[0135] The air conditioner self-cleaning mode has the function of repeating regular (preliminary and deep) cleaning and can execute cleaning operations according to different instructions.

[0136] The controller is a processor, and the processor execution meter can implement the steps defined in the above-mentioned self-cleaning control method.

[0137] Example 3:

[0138] A control method for optimizing the self-cleaning time period of an air conditioner comprises the following steps:

[0139] Step 1: First, build a controller with integral calculation capabilities on the home air conditioner, allowing it to calculate the time the air conditioner is on and off in steps of days;

[0140] It should be noted that the controller is an integrated circuit chip capable of input and output signal processing, integration operations, and model comparison. Currently, chips such as central processing units (CPUs), single-chip microcomputers, embedded ARM processors, microcontroller units (MCUs), application-specific integrated circuits (ASICs), and complex programmable logic devices (CPLDs) can implement or execute the methods, steps, and logic diagrams disclosed in this invention.

[0141] During the implementation of this controller, the memory should be used to store and retrieve the calculation results after calculation. The functions of storing and retrieving data are currently available for dynamic random access memory DRAM (Dynamic RAM), static random access memory SRAM (Static RAM), flash memory FLASH memory, electrically erasable programmable memory EEPROM (Electrically Erasable Programmable ROM), etc. The selection should be based on the controller interface and adaptation protocol.

[0142] Step 2: To initialize the calculation conditions, run the air conditioner self-cleaning program once after installing the controller;

[0143] Because a variety of installation environments may exist during controller installation, it is required to run the air conditioner self-cleaning program after the controller is installed. The following discusses operations under different installation environments: 1) If the controller is installed during assembly and commissioning of the air conditioner and it has not been sold or used, step 2 can be omitted and the management personnel will reset it to zero. 2) If the air conditioner has been sold and used for a period of time and poses an environmental health risk, management / maintenance personnel can perform an evaporator dust sampling, if conditions permit, and enter the existing evaporator dust amount into the controller when the evaporator dust amount is obtained. 3) If the air conditioner has been sold and used for a period of time and poses an environmental health risk, but management / maintenance personnel do not perform evaporator dust sampling, then the air conditioner self-cleaning program should be run after the controller is installed.

[0144] Step 3: Input the calculation formula of the correlation model between indoor particulate matter, fungal aerosol concentration and evaporator dust accumulation into the controller. The model can calculate the dust accumulation threshold based on the indoor fungal aerosol pollution limit;

[0145] This step requires establishing a correlation model between indoor particulate matter and fungal aerosol concentrations and evaporator dust accumulation in a laboratory environment. Under laboratory conditions, various operating conditions can be set based on the air conditioning system (adjusting environmental parameters such as temperature, humidity, and wind speed). Correlations under these conditions are then calculated to obtain the final model. The following example uses the process of establishing a correlation model between indoor particulate matter and evaporator dust accumulation. The correlation model between fungal aerosol concentration and evaporator dust accumulation is similar and will not be further elaborated here.

[0146] In the laboratory set up Figure 2The experimental setup shown here consists of a blower, a filtration section, a straightening section, a test section, and an outlet, designed to simulate the interaction between suspended particles and a stainless steel particle carrier. The blower provides energy for the airflow, ensuring a consistent flow rate between air entering and exiting the experimental setup. The filtration section removes impurities from the air, minimizing the amount of impurities other than suspended particles. The straightening section further adjusts the flow rate and turbulence of the air exiting the filtration section to ensure smooth flow before entering the test section. The test section contains a stainless steel particle carrier to simulate the evaporator surface material under actual operating conditions. The specific material can be adjusted based on the actual unit's condenser material. The outlet directs the airflow to ensure it does not affect the operating conditions of the test section.

[0147] Figure 3 、 Figure 4 The relationship between the number of suspended particles and the amount of accumulated dust under different H / D ratios is shown. The curve for the 1-3 μm particle size range is plotted on the left ordinate, while the curves for the remaining particle size ranges correspond to the right ordinate. This indicates that the number of suspended particles increases gradually with increasing dust accumulation. It should be noted that the curves fluctuate significantly between adjacent data points, indicating a high degree of randomness in the aggregation of settled particles that can be detected by the counter.

[0148] After determining the relationship between the number of suspended particles and the amount of dust accumulation, the total number of suspended particles can be controlled based on the amount of dust accumulation. For example, consider the curve for particles 1.0-3.0 μm in a stainless steel glass plate with H / D = 0.77. In the experimental environment, H / D = 0.77 and D = 6.5 mm. Since the experiment only provides the relationship between the total number of suspended particles and the amount of dust accumulation, it is necessary to convert this relationship into the relationship between suspended particle concentration and dust accumulation using Equation 1.

[0149]

[0150] Assuming that the total number of particles of 1.0-3.0 μm calculated by formula 1 needs to be controlled at 3.5×10 7 , then Figure 5 It can be calculated that the dust accumulation should be controlled at 2.0g / m 2 The particle concentration β of the controller can be set 2.5 The dust accumulation is 2.0g / m 2 , and then conduct relevant experiments and calculations on particulate matter PM10 and indoor fungal aerosol concentration α. i ,β 2.5,i ,β 10,i Substituting into equation 3 yields M i .

[0151] Step 4: The user / manager will use the original environmental characteristics to identify the indoor dust emission sources E k , system fresh air volume V f , system fresh air volume Vr , filter (including return air duct) dust removal rate η f , maintenance structure permeability η p By inputting environmental parameters into the integral controller, the amount of dust accumulated in the evaporator under actual environment is calculated;

[0152] It should be noted that the amount of dust accumulated on the evaporator in the above actual environment can be calculated according to formula 2-7. The dust accumulation distribution function m near the return air outlet of the air conditioner in , dust accumulation distribution function m near the fresh air outlet of the air conditioner out The relationship is calculated by formula 2. The calculation methods of the following parameters are not unique. The results can be obtained by repeated measurements combined with actual measurements, or the coefficients can be selected based on the parameters in similar scenarios.

[0153]

[0154] ——Dust accumulation per unit air volume and per unit particle size on the condensing coil, mg / (μm·m 3 );

[0155] m in ——Dust accumulation distribution function near the return air outlet of the air conditioner, mg / (μm·m 3 );

[0156] m out ——Dust accumulation distribution function near the fresh air outlet of the air conditioner, mg / (μm·m 3 );

[0157] η f ——Effective dust removal rate of the filter (including the return air duct), %;

[0158] η r ——Particle deposition fraction in the return air duct, %;

[0159] V f ——Fresh air volume of primary return air system, m 3 / h;

[0160] V r ——Return air volume of primary return air system, m 3 / h;

[0161] η e ——Dust emission rate of condensing coil, %;

[0162] η c ——Condensing coil particle deposition fraction, %;

[0163]

[0164] Μ c——Total dust accumulation in evaporator, g / m 2 ;

[0165] t——time, s;

[0166] d p ——Particle size, depending on the situation, generally 0.01-100μm;

[0167]

[0168] η p ——Permeability through maintenance structure, %;

[0169] V p ——Infiltration air volume, m 3 / h;

[0170] η v ——Dust removal rate during ventilation, %;

[0171] V——Indoor volume, m 3 ;

[0172] κ——Indoor dust loss rate, 1 / h;

[0173] η r ——Return air dust loss rate,

[0174] E a — Particle emission rate from various indoor sources, mg / (μm·h), where a = r (carpet, enclosure, ceiling, and other wall structures), c (cooking), s (smoking), and h (carried by humans or animals), selected as appropriate;

[0175] Among them E r It can be determined by formula 5, E c 、E s 、E h It can be selected based on on-site measurement.

[0176] E r =L f1 A f1 (5)

[0177] L f1 ——Dust load on carpets, enclosures, ceilings and other wall structures, mg / (μm·m 2 h);

[0178] A f1 ——Total area of ​​wall structures such as carpet, enclosure structure, ceiling, etc., m 2 ;

[0179] where η v ,η rThe calculation of is shown in Equations 6 and 7.

[0180] η v =1-(1-η f )(1-η e )(1-η s ) (6)

[0181] η r =1-(1-η r )(1-η f )(1-η s )(1-η c ) (7)

[0182] η s ——particle deposition fraction in the air supply pipe, %;

[0183] Step 5: Compare the dust accumulation amount calculated by the controller with the threshold to determine whether the self-cleaning mode triggering condition is met;

[0184] The M obtained in step 3 i With M c The specific comparison rules are as follows:

[0185] If M c <M1, the controller does not issue a self-cleaning command;

[0186] If M1<M c <M2, the controller issues a self-cleaning operation instruction;

[0187] If M2<M c <M3, the controller will issue a self-cleaning operation instruction for 2 or more times;

[0188] If M3<M c , the controller will sound an alarm to prompt the cleaning staff to perform manual cleaning operations;

[0189] Wherein, M1 is the first threshold value of dust accumulation in the evaporator, g / month;

[0190] M2 is the second threshold value of dust accumulation on the evaporator, g / month;

[0191] M3 is the third threshold of dust accumulation on the evaporator, g / month;

[0192] It should be noted that the above comparison rules are only used as examples of issuing self-cleaning instructions. The present invention claims to protect the method and concept. The specific rules should be determined by the administrator after comprehensive analysis and judgment.

[0193] Step 6: If the self-cleaning trigger condition is met, a cleaning instruction is sent to the air conditioning self-cleaning control module.

[0194] It should be noted that the input of the relevant limit relationship should be carried out in accordance with the provisions of formula (7). If the administrator / user has special or more detailed requirements, the above limit values ​​should be adjusted before use. It should be noted that this note only protects the idea of ​​limit setting, and the specific values ​​can be selected from the conventional values.

[0195] In the design ideas provided in this application, it should be understood that the disclosed parameter calculation and control methods can also be implemented in other ways. The device embodiments described above are merely schematic and theoretical. For example, the flowcharts and device diagrams in the accompanying drawings only show the feasibility of multiple embodiments according to the present invention. In addition, the functional modules in the various embodiments of the present invention can be integrated together to form an independent part, or each module can exist separately, or two or more modules can be integrated to form an independent part. If the functions are implemented in the form of software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in the various embodiments of the present invention. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk and other media that can store program code.

[0196] Example 4:

[0197] A control method for optimizing the self-cleaning time period of an air conditioner comprises the following steps:

[0198] 1) Electrically connect a controller with integral calculation capability to the air conditioner to calculate the air conditioner operating time;

[0199] 2) Integrate the calculation model of the correlation between indoor fungal aerosol and particulate matter concentration and evaporator dust accumulation, as well as the dust accumulation calculation model in the controller;

[0200] 3) The dust accumulation threshold is calculated using the correlation calculation model between indoor fungal aerosol and particulate matter concentrations and evaporator dust accumulation;

[0201] 3) Obtain environmental parameters and input them into the dust accumulation calculation model to calculate the real-time dust accumulation;

[0202] 4) The real-time dust accumulation amount is compared with the dust accumulation amount threshold. Based on the comparison result, the controller determines whether the self-cleaning control mode is triggered. If so, a control instruction is sent to the air conditioner to turn on the self-cleaning control mode of the air conditioner.

[0203] Example 5:

[0204] A control method for optimizing the self-cleaning time period of an air conditioner, the main contents of which are shown in Example 4, wherein the environmental parameters include the indoor dust emission source E k , System fresh air volume V f , System return air volume V r , filter and return air duct dust effective removal rate η f , maintenance structure permeability η p .

[0205] Example 6:

[0206] A control method for optimizing the self-cleaning time period of an air conditioner, the main contents of which are shown in Example 4, wherein the dust accumulation amount M c As shown below:

[0207]

[0208] Where, is the dust accumulation amount of the condensing coil per unit air volume and unit particle size; t is the air conditioner operation time; d p is the particle size.

[0209] Example 7:

[0210] A control method for optimizing the self-cleaning time period of an air conditioner, the main contents of which are shown in Example 4, wherein the dust accumulation amount of the condensing coil per unit air volume and unit particle size is As shown below:

[0211]

[0212] Where m in is the dust accumulation distribution function near the return air outlet of the air conditioner; m out is the dust accumulation distribution function near the fresh air outlet of the air conditioner; η f is the effective removal rate of dust accumulated in the filter and return air duct; η r is the particle deposition fraction in the return air duct; V f is the fresh air volume of the primary return air system; V r is the return air volume of the primary return air system; η e is the dust emission rate of the condensing coil; η c is the particle deposition fraction of the condensing coil;

[0213] Among them, the dust accumulation distribution function m near the return air outlet of the air conditioner in As shown below:

[0214]

[0215] Where η p is the permeability of the maintenance structure; V p is the infiltration air volume; η v is the ventilation dust removal rate; V is the indoor volume; κ is the indoor dust loss rate; η r E is the return air dust loss rate; a is the particle emission rate from indoor sources; a = r, c, s, h; r represents particles emitted from wall structures; wall structures include carpets, enclosures, and ceilings; c represents particles emitted during cooking; s represents particles emitted from smoking; and h represents particles carried by humans or animals.

[0216] Among them, the particle escape rate E of the wall structure is r As shown below:

[0217] E r =L f1 A f1 (4)

[0218] Where, L f1 A is the dust load on the wall structure; f1 is the total area of ​​the wall structure;

[0219] Ventilation dust removal rate η v , return air duct particle deposition fraction η r They are as follows:

[0220] η v =1-(1-η f )(1-η e )(1-η s ) (5)

[0221] η r =1-(1-η r )(1-η f )(1-η s )(1-η c ) (6)

[0222] Where η s is the particle deposition fraction in the air supply duct.

[0223] Example 8:

[0224] A control method for optimizing the self-cleaning time period of an air conditioner, the main contents of which are shown in Example 4, wherein when the dust accumulation amount M c When <M1, the self-cleaning control mode is not triggered;

[0225] When the dust accumulation satisfies M1<M cWhen <M2, the controller issues a self-cleaning operation instruction;

[0226] When the dust accumulation satisfies M2<M c When the temperature is less than M3, the controller will issue a self-cleaning operation instruction for 2 or more times;

[0227] When the dust accumulation satisfies M3<M c When the controller sounds an alarm, it prompts the cleaning staff to perform manual cleaning operations;

[0228] Among them, M1 is the first threshold value of the dust accumulation in the evaporator;

[0229] M2 is the second threshold value of dust accumulation in the evaporator;

[0230] M3 is the third threshold value of the dust accumulation in the evaporator.

[0231] Example 9:

[0232] A control method for optimizing the self-cleaning time period of an air conditioner, the main contents of which are shown in Example 4, wherein the dust accumulation threshold is as follows:

[0233] M i =min[f(α i ),g(β 2.5,i ),m(β 10,i )] (7)

[0234] Where, positive integer i = 1, 2, 3; α i is the indoor fungal aerosol concentration; β 2.5,i is the indoor particulate matter PM2.5 concentration; β 10,i is the indoor particulate matter PM10 concentration; f(α i ) is the relationship function between indoor fungal aerosol concentration and evaporator dust accumulation; g(β 2.5,i ) is the relationship function between indoor particulate matter PM2.5 concentration and evaporator dust accumulation; m(β 10,i ) is the relationship function between indoor particulate matter PM10 concentration and evaporator dust accumulation;

[0235] Example 10:

[0236] A control method for optimizing the self-cleaning time period of an air conditioner, the main contents of which are shown in Example 4, wherein the indoor fungal aerosol concentration, indoor particulate matter PM2.5 concentration, and indoor particulate matter PM10 concentration are respectively as follows:

[0237] α1=50%α xianzhi (8)

[0238] α2=75%α xianzhi (9)

[0239] α3=100%α xianzhi (10)

[0240] β 2.5,1 =50%β 2.5 (11)

[0241] β 2.5,2 =75%β 2.5 (12)

[0242] β 2.5,3 =100%β 2.5 (13)

[0243] β 10,1 =50%β 10 (14)

[0244] β 10,2 =75%β 10 (15)

[0245] β 10,3 =100%β 10 (16)

[0246] Where, α xianzhi is the indoor fungal aerosol limit; β 2.5 is the concentration limit of particulate matter PM2.5; β 10 It is the concentration limit of particulate matter PM10.

Claims

1. A control method for optimizing the self-cleaning time period of an air conditioner, characterized in that: The following steps are involved: 1) Electrically connect a controller with integral calculation capability to the air conditioner to calculate the air conditioner operating time; 2) Integrate the calculation model of the correlation between indoor fungal aerosol and particulate matter concentration and evaporator dust accumulation, as well as the dust accumulation calculation model in the controller; 3) The dust accumulation threshold is calculated using the correlation calculation model between indoor fungal aerosol and particulate matter concentrations and evaporator dust accumulation; 4) Obtain environmental parameters and input them into the dust accumulation calculation model to calculate the real-time dust accumulation; 5) Comparing the real-time dust accumulation amount with the dust accumulation amount threshold, the controller determines whether to trigger the self-cleaning control mode based on the comparison result. If so, it sends a control instruction to the air conditioner to turn on the self-cleaning control mode of the air conditioner; The environmental parameters include indoor dust emission sources E k , System fresh air volume V f , System return air volume V r , filter and return air duct dust effective removal rate η f , maintenance structure permeability η p ; The dust accumulation thresholds are as follows: M i =min[f(α i ),g(β 2.5,i ),m(β 10,i )] (7) Where, positive integer i = 1, 2, 3; α i is the indoor fungal aerosol concentration; β 2.5,i is the indoor particulate matter PM2.5 concentration; β 10,i is the indoor particulate matter PM10 concentration; f(α i ) is the relationship function between indoor fungal aerosol concentration and evaporator dust accumulation; g(β 2.5,i ) is the relationship function between indoor particulate matter PM2.5 concentration and evaporator dust accumulation; m(β 10,i ) is the relationship function between indoor particulate matter PM10 concentration and evaporator dust accumulation.

2. The control method for optimizing the self-cleaning time period of an air conditioner according to claim 1, characterized in that: Dust accumulation M c As shown below: Where, is the dust accumulation amount of the condensing coil per unit air volume and unit particle size; t is the air conditioner operation time; d p is the particle size; V f is the fresh air volume of the system; V r The return air volume of the system.

3. The control method for optimizing the self-cleaning time period of an air conditioner according to claim 1, characterized in that: Dust accumulation per unit air volume and particle size per condensing coil As shown below: Where m in is the dust accumulation distribution function near the return air outlet of the air conditioner; m out is the dust accumulation distribution function near the fresh air outlet of the air conditioner; η f is the effective removal rate of dust accumulated in the filter and return air duct; η r is the particle deposition fraction in the return air duct; V f is the fresh air volume of the primary return air system; V r is the return air volume of the primary return air system; η e is the dust emission rate of the condensing coil; η c is the particle deposition fraction of the condensing coil; Among them, the dust accumulation distribution function m near the return air outlet of the air conditioner in As shown below: Where η p is the permeability of the maintenance structure; V p is the infiltration air volume; η v is the ventilation dust removal rate; V is the indoor volume; κ is the indoor dust loss rate; η r E is the return air dust loss rate; a is the particle emission rate from indoor sources; a = r, c, s, h; r represents particles emitted from wall structures; wall structures include carpets, enclosures, and ceilings; c represents particles emitted during cooking; s represents particles emitted from smoking; and h represents particles carried by humans or animals. Among them, the particle escape rate E of the wall structure is r As shown below: AND r =L f1 TO f1 (4) Where, L f1 A is the dust load on the wall structure; f1 is the total area of ​​the wall structure; Ventilation dust removal rate η v , return air duct particle deposition fraction η r They are as follows: or v =1-(1-th f (1st) e (1st) s ) (5) or r =1-(1-th r (1st) f (1st) s (1st) c ) (6) Where η s is the particle deposition fraction in the air supply duct.

4. The control method for optimizing the self-cleaning time period of an air conditioner according to claim 1, characterized in that: When the dust accumulation amount M c When <M1, the self-cleaning control mode is not triggered; When the dust accumulation satisfies M1<M c When <M2, the controller issues a self-cleaning operation instruction; When the dust accumulation satisfies M2<M c When the temperature is less than M3, the controller will issue a self-cleaning operation instruction for 2 or more times; When the dust accumulation satisfies M3<M c When the controller sounds an alarm, it prompts the cleaning staff to perform manual cleaning operations; Among them, M1 is the first threshold value of the dust accumulation in the evaporator; M2 is the second threshold value of dust accumulation in the evaporator; M3 is the third threshold value of the dust accumulation in the evaporator.

5. The control method for optimizing the self-cleaning time period of an air conditioner according to claim 1, characterized in that: Indoor fungal aerosol concentration α i , indoor particulate matter PM2.5 concentration β 2.5,i , indoor particulate matter PM10 concentration β 10,i They are as follows: α1＝50％α xianzhi (8) α2＝75％α xianzhi (9) α3＝100％α xianzhi (10) β 2.5,1 ＝50％β 2.5 (11) β 2.5,2 ＝75％β 2.5 (12) β 2.5,3 ＝100％β 2.5 (13) β 10,1 ＝50％β 10 (14) β 10,2 ＝75％β 10 (15) β 10,3 ＝100％β 10 (16) Where, α xianzhi is the indoor fungal aerosol limit; β 2.5 is the concentration limit of particulate matter PM2.5; β 10 It is the concentration limit of particulate matter PM10.

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