A method for improving thermal comfort during the start-up phase of a household air conditioner

Abstract

This invention discloses a method for improving thermal comfort during the start-up phase of a household air conditioner, comprising the following steps: 1) calculating the optimal standard equivalent temperature using a model relating thermal sensation to standard equivalent temperature; 2) calculating the average air temperature and standard equivalent temperature in the activity area; 3) starting the household air conditioner in operating mode I until the standard equivalent temperature in the activity area reaches the optimal standard equivalent temperature; 4) changing the operating mode of the household air conditioner to operating mode II until the average air temperature in the activity area reaches the user-set temperature; 5) intermittently operating the household air conditioner in operating mode II to maintain the standard equivalent temperature in the activity area within the range of comfortable temperature for the user. This invention can be tailored to different application scenarios to reflect the adaptability to different groups of people and different scenarios, and is highly compatible with the characteristics of the thermal sensation prediction model required during the start-up phase of a household air conditioner.

Description

Technical Field

[0001] This invention relates to the field of improving thermal comfort in household air conditioners, specifically a method for improving thermal comfort during the start-up phase of a household air conditioner. Background Technology

[0002] In recent years, with the improvement of people's living standards, people are pursuing a more comfortable indoor environment, and have therefore installed various devices to create such an environment. Household air conditioners, due to their advantages of being readily available and easy to operate, are widely used for home cooling and heating. Because of this on-demand nature, household air conditioners experience multiple start-ups and shutdowns throughout the day, and the "insufficiently fast cooling and heating" during the start-up phase is one of the main pain points for users. Although some air conditioner manufacturers have introduced rapid cooling, heating, and temperature recovery modes, these modes are mainly based on the manufacturers' market research and marketing strategies, and lack experimental data to support their scientific validity. They only focus on how quickly the room temperature reaches the comfort zone. Related research has found that thermal comfort is poor during the air conditioner's start-up phase, and the rapid changes in the indoor environment at this time can cause physiological discomfort and even illness.

[0003] Existing air conditioning control methods have the following problems: 1) Controlling and adjusting the air conditioner based on fixed data (height, weight, metabolic rate, and clothing thermal resistance) cannot adapt to rapid changes in the indoor environment and cannot achieve more precise and real-time control. 2) The optimal value for human thermal comfort is determined by the influence of temperature, wind speed, and airflow velocity on PMV, which can only approximate the thermal sensation of people and cannot accurately reflect their thermal comfort. Summary of the Invention

[0004] The purpose of this invention is to provide a method for improving thermal comfort during the start-up phase of a household air conditioner, comprising the following steps:

[0005] 1) Construct a model relating thermal sensation to standard equivalent temperature;

[0006] 2) Calculate the optimal standard equivalent temperature using a model relating thermal sensation to standard equivalent temperature;

[0007] 3) Obtain environmental parameters of the personnel activity area, and calculate the average air temperature and standard equivalent temperature of the personnel activity area;

[0008] 4) Turn on the household air conditioner and set it to operating mode I until the standard equivalent temperature of the area where people are active reaches the optimal standard equivalent temperature.

[0009] 5) Change the operating mode of the household air conditioner to operate in operating mode II until the average air temperature in the area where people are active reaches the user-set temperature.

[0010] 6) Set the household air conditioner to run intermittently in operating mode II to maintain the standard equivalent temperature in the activity area within the comfortable temperature range for people.

[0011] Furthermore, the environmental parameters of the personnel activity area include one or more of the following: air temperature, relative humidity, wind speed, and mean radiant temperature.

[0012] Furthermore, the relationship model between the thermal sensation and the standard equivalent temperature is shown below:

[0013] PTS = 0.133SET - 3.42 (Summer) (SET < 30℃) (1)

[0014] PTS = 0.297SET - 8.20 (Summer) (SET ≥ 30℃) (2)

[0015] PTS = 0.207SET - 4.66 (Winter) (3)

[0016] In the formula, PTS is the average thermal sensation index; SET is the standard equivalent temperature.

[0017] Furthermore, in the model relating thermal sensation to standard equivalent temperature, the average thermal sensation index PTS is a known quantity, while the optimal standard equivalent temperature is an unknown quantity.

[0018] The steps for calculating the average thermal sensation index (PTS) include:

[0019] 1) Obtain the average thermal sensation index and the corresponding dissatisfaction rate under different seasons, and perform fitting to obtain the thermal sensation-dissatisfaction rate fitting curve for winter and the thermal sensation-dissatisfaction rate fitting curve for summer.

[0020] 2) Determine the average thermal sensation index when the dissatisfaction rate is lowest based on the current season.

[0021] Furthermore, the average thermal sensation index and dissatisfaction rate were obtained through a questionnaire.

[0022] Furthermore, the comfortable temperature range for personnel is determined using the following methods:

[0023] 1) Set the upper limit of the dissatisfaction rate and the lower limit of the average thermal sensation index, and substitute them into the thermal sensation-dissatisfaction rate fitting curve corresponding to the current season to obtain the upper limit of the average thermal sensation index and the lower limit of the average thermal sensation index.

[0024] 2) Substitute the upper limit and lower limit of the average thermal sensation index into the relationship model between thermal sensation and standard equivalent temperature to obtain the corresponding upper limit and lower limit of standard equivalent temperature, thereby constructing the comfortable temperature range for personnel.

[0025] Furthermore, when the current season is summer, operating mode I is medium air volume and large air temperature difference; operating mode II is small air volume and medium air temperature difference.

[0026] In summer, the large supply air temperature difference range is [13.18℃, 14.66℃];

[0027] In summer, the temperature difference range of the central air supply is [8.94℃, 9.80℃].

[0028] Furthermore, when the current season is winter, operating mode I is a large air volume and a large air temperature difference; operating mode II is a medium air temperature difference and a medium air volume.

[0029] In winter, the large supply air temperature difference range is [21.49℃, 23.00℃];

[0030] During winter, the temperature difference range of the central air supply is [17.26℃, 20.38℃].

[0031] Furthermore, in addition to environmental parameters, the metabolic rate of personnel and the thermal resistance of clothing were also considered to calculate the standard equivalent temperature (SET), the predicted average thermal perception vote (PMV), and the predicted percentage of thermal environmental dissatisfaction (PPD) index.

[0032] Furthermore, the airflow rate and airflow temperature difference settings for the operating modes of a household air conditioner are determined using the following methods:

[0033] The superior-inferiority distance method is used to evaluate different air volume and air temperature difference levels, and the air volume and air temperature difference levels with the highest evaluation are taken as the current air volume and air temperature difference levels.

[0034] The evaluation indicators selected for the superior-inferior solution distance method include thermal sensation vote, thermal comfort vote, dissatisfaction rate, and standard equivalent temperature.

[0035] The technical effectiveness of this invention is undeniable. This invention selects operating mode 1 based on whether it's for winter heating or summer cooling, monitors the environment in the activity area, and obtains parameters such as air temperature to calculate the standard effective temperature (SET) for the activity area. The air conditioner maintains operating mode 1 until the SET drops to the optimal SET, and then switches to operating mode 2. Once the air temperature reaches the set temperature, start-stop control is initiated to ensure the air temperature remains between the set temperature and the air temperature corresponding to the optimal SET.

[0036] The beneficial effects of this invention are as follows:

[0037] 1) This method establishes a PTS predictive thermal sensation model using standard effective temperature, which further improves the accuracy of the predicted values ​​compared to the PMV model.

[0038] 2) The PTS model constructed by this invention is highly flexible in classification and can be constructed according to different application scenarios to reflect the adaptability of different groups of people and different scenarios, which is very suitable for the thermal sensation prediction model required for the start-up phase of household air conditioners.

[0039] 3) This invention introduces the Top-to-Best Solution Distance (TOPSIS) method from the comprehensive evaluation method to evaluate the merits of each operating condition. Based on the operating condition ranking of the TOPSIS method, a comfortable operation mode for the start-up phase of the air conditioner can be proposed. Attached Figure Description

[0040] Figure 1 Flowchart of strategies to improve thermal comfort during the start-up phase of a home air conditioner;

[0041] Figure 2 Schematic diagram of the laboratory room layout;

[0042] Figure 3 (a)- Figure 3 (b) A fitted plot of average thermal perception votes versus actual dissatisfaction rate votes for summer and winter;

[0043] Figure 4 Fitting plots of the SET-PTS model for the winter and summer phases during the initial stage.

[0044] Figure 5 Hourly comparison chart of SET under different control logics for summer cooling;

[0045] Figure 6 (a)- Figure 6 (b) is a time-by-time comparison chart of satisfaction rate and thermal comfort under different control logics for summer cooling;

[0046] Figure 7 A time-by-time comparison chart of SET under different control logics for winter heating;

[0047] Figure 8 (a)- Figure 8 (b) is a time-by-hour comparison chart of satisfaction rate and thermal comfort under different control logics for winter heating;

[0048] Figure 9 Fitting plots of the SET-PTS model for the winter and summer phases during the initial stage;

[0049] Figure 10 This is a schematic diagram of a two-node model. Detailed Implementation

[0050] The present invention will be further described below with reference to embodiments, but it should not be construed that the scope of the present invention is limited to the following embodiments. Various substitutions and modifications made based on ordinary technical knowledge and common practices in the art without departing from the above-described technical concept of the present invention should be included within the scope of protection of the present invention.

[0051] Example 1:

[0052] See Figures 1 to 10 A method for improving thermal comfort during the start-up phase of a household air conditioner includes the following steps:

[0053] 1) Construct a model relating thermal sensation to standard equivalent temperature;

[0054] 2) Calculate the optimal standard equivalent temperature using a model relating thermal sensation to standard equivalent temperature;

[0055] 3) Obtain environmental parameters of the personnel activity area, and calculate the average air temperature and standard equivalent temperature of the personnel activity area;

[0056] 4) Turn on the household air conditioner and set it to operating mode I until the standard equivalent temperature of the area where people are active reaches the optimal standard equivalent temperature.

[0057] 5) Change the operating mode of the household air conditioner to operate in operating mode II until the average air temperature in the area where people are active reaches the user-set temperature.

[0058] 6) Set the household air conditioner to run intermittently in operating mode II to maintain the standard equivalent temperature in the activity area within the comfortable temperature range for people.

[0059] Example 2:

[0060] A method for improving thermal comfort during the start-up phase of a household air conditioner, with the same technical content as in Embodiment 1, further wherein the average air temperature in the area where people are active is the average air temperature at heights of 0.1m, 0.6m, and 1.1m where people are located.

[0061] Example 2:

[0062] A method for improving thermal comfort during the start-up phase of a household air conditioner, with the same technical content as in Embodiment 1, further wherein the environmental parameters of the personnel activity area include one or more of the following: air temperature, relative humidity, wind speed, and mean radiant temperature.

[0063] Example 3:

[0064] A method for improving thermal comfort during the start-up phase of a household air conditioner, with the same technical content as any one of Embodiments 1-2, further wherein the relationship model between the thermal sensation and the standard equivalent temperature is as follows:

[0065] PTS = 0.133SET - 3.42 (Summer) (SET < 30℃) (1)

[0066] PTS = 0.297SET - 8.20 (Summer) (SET ≥ 30℃) (2)

[0067] PTS = 0.207SET - 4.66 (Winter) (3)

[0068] In the formula, PTS is the average thermal sensation index; SET is the standard equivalent temperature.

[0069] Example 3:

[0070] A method for improving thermal comfort during the start-up phase of a household air conditioner, with the same technical content as any one of Embodiments 1-2, further wherein the piecewise fitting of the relationship model between thermal sensation and standard equivalent temperature is based on the following:

[0071] A linear regression analysis of the standard effective temperature (SET) and the average thermal sensation vote yields the following results:

[0072] PTS = 0.178SET - 4.52 (Summer) (5.1)

[0073] PTS = 0.207SET - 4.66 (Winter) (5.2)

[0074] As shown in the fitted line in the figure below, during summer cooling, when the set temperature (SET) is above 30°C, the accuracy of the PTS model's prediction decreases as the actual perceived heat level increases. The PTS model's fitted line slope reflects the population's adaptability. When the summer cooling temperature is in the warmer range, discomfort will lead to a decrease in the population's adaptability, resulting in a higher slope of the line. This also indicates that when the temperature is in the warmer range, the same reduction in SET will lead to a more significant decrease in perceived heat level. Therefore, piecewise fitting can be used for summer cooling.

[0075] Example 4:

[0076] A method for improving thermal comfort during the start-up phase of a household air conditioner, with the same technical content as any one of embodiments 1-3, further wherein, in the model relating thermal sensation and standard equivalent temperature, the average thermal sensation index PTS is a known quantity and the optimal standard equivalent temperature is an unknown quantity.

[0077] The steps for calculating the average thermal sensation index (PTS) include:

[0078] 1) Obtain the average thermal sensation index and the corresponding dissatisfaction rate under different seasons, and perform fitting to obtain the thermal sensation-dissatisfaction rate fitting curve for winter and the thermal sensation-dissatisfaction rate fitting curve for summer.

[0079] 2) Determine the average thermal sensation index when the dissatisfaction rate is lowest based on the current season.

[0080] in,

[0081] Example 5:

[0082] A method for improving thermal comfort during the start-up phase of a household air conditioner, with the same technical content as any one of embodiments 1-4, further wherein the average thermal sensation index and dissatisfaction rate are obtained through a questionnaire.

[0083] Example 6:

[0084] A method for improving thermal comfort during the start-up phase of a household air conditioner, with the same technical content as any one of embodiments 1-5, further wherein the comfortable temperature range for personnel is determined by the following method:

[0085] 1) Set the upper limit of the dissatisfaction rate and the lower limit of the average thermal sensation index, and substitute them into the thermal sensation-dissatisfaction rate fitting curve corresponding to the current season to obtain the upper limit of the average thermal sensation index and the lower limit of the average thermal sensation index.

[0086] 2) Substitute the upper limit and lower limit of the average thermal sensation index into the relationship model between thermal sensation and standard equivalent temperature to obtain the corresponding upper limit and lower limit of standard equivalent temperature, thereby constructing the comfortable temperature range for personnel.

[0087] Example 7:

[0088] A method for improving thermal comfort during the start-up phase of a household air conditioner, with the same technical content as any one of embodiments 1-6, further wherein, when the current season is summer, operating mode I is medium air volume and large air temperature difference; operating mode II is small air volume and medium air temperature difference.

[0089] In summer, the large supply air temperature difference range is [13.18℃, 14.66℃];

[0090] In summer, the temperature difference range of the central air supply is [8.94℃, 9.80℃].

[0091] Example 8:

[0092] A method for improving thermal comfort during the start-up phase of a household air conditioner, with the same technical content as any one of embodiments 1-7, further wherein, when the current season is winter, operating mode I is a large air volume and a large air temperature difference; operating mode II is a medium air temperature difference and a medium air volume.

[0093] In winter, the large supply air temperature difference range is [21.49℃, 23.00℃];

[0094] During winter, the temperature difference range of the central air supply is [17.26℃, 20.38℃].

[0095] Example 9:

[0096] A method for improving thermal comfort during the start-up phase of a household air conditioner, with the same technical content as any one of embodiments 1-8, further considering, in addition to environmental parameters, the metabolic rate of personnel and the thermal resistance of clothing, for calculating the standard equivalent temperature (SET), the predicted average thermal feeling vote (PMV), and the predicted percentage of thermal environmental dissatisfaction (PPD) index.

[0097] Example 9:

[0098] A method for improving thermal comfort during the start-up phase of a household air conditioner, with technical content identical to any one of embodiments 1-8, further comprising the following step: In the calculation of the SET index, a two-node model is first used to approximate the heat exchange process between the human body and the environment, obtaining the corresponding heat exchange and physiological parameters, and then equivalence between the actual environment and the SET standard environment. The two-node model is a classic human thermal physiological regulation model. It simplifies the human body into two parts: the core layer and the skin layer. It considers that the body's heat production originates from the core layer, which transfers heat to the skin layer through blood flow. The skin then exchanges heat with the external environment through clothing or directly. A schematic diagram of the two-node model is shown below. Figure 10 .

[0099] The dynamic thermal equilibrium equations for the two-node model are shown below.

[0100] For the core layer:

[0101]

[0102] For the skin layer:

[0103]

[0104] In the formula: M and ΔM are the metabolic rate and the metabolic rate increased by shivering, respectively, W / m²; W is the work done by the human body, W / m²; Cres and Ers are the sensible heat loss and latent heat loss due to respiration, respectively, W / m²; K is the heat transfer coefficient from the core layer to the skin layer, W / (m²·℃); ρ bl Blood density, kg / L; m bl Skin blood flow, L / (m²·℃); c bl c cr c sk Specific heat capacities of blood, core layer, and skin layer, respectively, in J / (kg·℃); t cr The core layer temperature is expressed in °C; t sk The average human skin temperature, in °C; m cr m sk The core layer and skin layer masses are respectively, in kg; A d Q represents the human body surface area, in square meters (m²); τ represents time, in seconds (s); Q sk Heat dissipation from the skin, W / m².

[0105] The amount of heat dissipated by the skin in a real-world environment can be obtained by calculating using a two-node model, Q. sk Skin temperature t sk And skin moisture ω. In SET calculations, the skin heat dissipation Q in the equivalent environment and the real environment is used. sk We establish the equation using the same principle. We assume that a person in the equivalent environment has the same skin temperature t as in the real environment. sk If the skin moisture ω, which is the same as the sensible heat loss and latent heat loss through the skin, is the same, then it is considered that a person in a standard environment has the same thermal sensation as in an actual environment.

[0106] Q sk =h w (t sk -t o )+wh e (p sk -p a ) = h ws (t sk -SET)+wh es (p sk -0.5p sSET (3)

[0107] Among them: Q sk Heat dissipation from the skin, W / m²; h w The combined heat transfer coefficient for convection and radiation is expressed in W / (m²·℃); wh e The comprehensive evaporative heat transfer coefficient is expressed in W / (m²·Pa); t sk Skin temperature, °C; t o Operating temperature, a weighted average of air temperature and radiant temperature, in °C; p sk The vapor pressure at the skin surface, Pa; p a The air temperature is T a The corresponding vapor pressure, Pa; h ws The heat transfer coefficient for standard environments is expressed in W / (m²·℃); wh es ΔE is the evaporative heat transfer coefficient of the standard environment, W / (m²·Pa); SET is the equivalent air temperature, °C; p sSET This represents the vapor pressure, in Pa, corresponding to temperature SET.

[0108] The formula for calculating PMV is as follows:

[0109]

[0110] Where M is the metabolic rate, W / m2; fcl is the clothing area coefficient; ta is the air temperature, °C; tcl is the average radiation temperature, °C; Pa is the water vapor partial pressure, Pa; tcl is the surface temperature of the clothing, °C.

[0111] The formula for calculating PPD is as follows:

[0112] PPD = 100 - 95exp[(0.03353PMV) 4 +0.2179PMV 2 )]

[0113] In actual calculations, SET, PMV, and PPD can be calculated using the Python thermal comfort calculation package pythermalcomfort1.3.1.

[0114] Example 10:

[0115] A method for improving thermal comfort during the start-up phase of a household air conditioner, with the same technical content as any one of embodiments 1-9, further wherein the air volume setting and air temperature difference setting of the household air conditioner operating mode are determined by the following method:

[0116] The superior-inferiority distance method is used to evaluate different air volume and air temperature difference levels, and the air volume and air temperature difference levels with the highest evaluation are taken as the current air volume and air temperature difference levels.

[0117] The evaluation indicators selected for the superior-inferior solution distance method include thermal sensation vote, thermal comfort vote, dissatisfaction rate, and standard equivalent temperature.

[0118] Example 11:

[0119] A method for improving thermal comfort during the start-up phase of a household air conditioner, comprising the following steps:

[0120] Step 1: Design and build an experimental platform based on the indoor household air conditioning environment, set up measuring points to collect parameters such as air temperature and relative humidity, and investigate the subjective feelings of the personnel;

[0121] Step 2: Determine the optimal SET value and Level I comfort zone based on the employee dissatisfaction rate, and establish a PTS model;

[0122] Step 3: Based on the superiority-inferiority distance method, determine the superiority-inferiority of the air supply mode during the start-up phase of the air conditioner, and select winter / summer operation mode 1 or operation mode 2;

[0123] Step 4: Determine the air conditioning control strategy based on the user-set temperature and the actual temperature change in the room within half an hour of the air conditioner starting.

[0124] The experimental platform should be built according to the actual conditions.

[0125] The method uses parameters such as temperature, relative humidity, wind speed, radiant temperature, and clothing status in a household air-conditioned environment to calculate the standard equivalent temperature (SET), the predicted average thermal perception vote (PMV), and the predicted percentage of thermal dissatisfaction (PPD) index.

[0126] The PTS model is established, and the optimal SET value and comfort range are determined according to the relevant indicators mentioned in claim 3.

[0127] The quality of the air supply mode during the start-up phase of the air conditioner is analyzed using the superiority-inferiority distance method to ultimately classify the air conditioner's operating mode.

[0128] The control logic for improving thermal comfort during the start-up phase of a household air conditioner is as follows: based on the user-set temperature, relevant parameters of the activity area are collected in real time. According to claim 5, the air supply mode 1 is determined according to winter and summer, the optimal SET for the current environment is calculated, and if it is reached, the air supply mode 2 is determined according to winter and summer. If the air temperature reaches the user-set temperature and the time is greater than or equal to 30 minutes, the control logic is exited.

[0129] Example 12:

[0130] A method for improving thermal comfort during the start-up phase of a household air conditioner, comprising the following steps:

[0131] Step 1: Design and build the experimental room according to the indoor household air conditioning environment, and arrange parameter measurement points.

[0132] It should be noted that this technical requirement is based on the principle of similarity. The indoor household air conditioning environment test room should meet the following conditions:

[0133] Indoor air conditioner models serving an area of ​​35m² 2 ~49m 2 between.

[0134] The room's thermal and humidity environmental parameters were measured in accordance with the requirements of the "Standard for Indoor Thermal and Humidity of Civil Buildings GB / T 50785-2012". Three equally divided points on the diagonal of the experimental platform were selected as flow field test points, and test piles were set up.

[0135] Temperature and humidity recorders and wind speed detectors were installed at the air supply and return vents of the air conditioner. The flow field measurement points were arranged at heights of 0.1m, 0.6m, 1.1m, and 1.7m on the test piles, and one measurement point was also arranged at each air supply vent of the air conditioner.

[0136] This technology provides an example, taking a household air-conditioned environment as an example, and designs and calculates based on the characteristic dimensions of the room and the location of the measuring points. The dimensions of the experimental room are 6.24m × 5.65m × 2.8m, and the air conditioner used is a 72-type vertical air conditioner. The measuring points are arranged as follows. Figure 2 As shown in Table 1, the experimental instruments are shown in Table 2, and the operating conditions are shown in Table 2.

[0137] Table 1 Parameter Table of Monitoring Instruments

[0138]

[0139] Table 2 Winter and Summer Experimental Conditions

[0140]

[0141] Step 2: Determine the optimal SET value and Level I comfort zone based on the employee dissatisfaction rate, and establish a PTS model;

[0142] The Python thermal comfort calculation package pythermalcomfort1.3.1 is used to calculate the standard effective temperature (SET) of the activity area, the predicted average thermal feeling vote (PMV), and the predicted percentage of thermal dissatisfaction (PPD) index.

[0143] Based on the PMV-PPD model formula, an unknown offset was set in the thermal sensation term for fitting. The fitting results of the average thermal sensation vote in winter and summer minus the actual dissatisfaction rate vote are as follows: Figure 3 As shown, the lowest actual dissatisfaction rate during the summer air conditioner start-up phase is achieved when the thermal perception vote is -0.16, while in winter, the lowest dissatisfaction rate occurs when the thermal perception vote is 0.56. Based on GB / T50785's standard that Grade I thermal comfort PPD < 10%, the thermal perception range for Grade I thermal comfort during the summer start-up phase is [-0.47, +0.15], and the range for Grade I thermal comfort during the winter start-up phase is [-0.04, +1.16].

[0144] The heat perception votes for summer cooling and winter heating are categorized into standard effective temperature intervals of 1℃ (±0.5℃). The average TSV within each standard effective temperature interval is used to reflect the general pattern under that scenario and equivalent temperature. The standard effective temperature (SET) is fitted to the average heat perception votes. To improve prediction accuracy, votes for summer SET above 30℃ are fitted in segments with votes for SET below 30℃. The heat perception prediction formula is:

[0145] PTS = 0.133SET - 3.42 (Summer) (SET < 30℃)

[0146] PTS = 0.297SET - 8.20 (Summer) (SET ≥ 30℃)

[0147] PTS = 0.207SET - 4.66 (Winter)

[0148] Fitting a straight line from the PTS model (e.g.) Figure 4As shown in the figure, the optimal SET when the dissatisfaction rate is lowest in summer (TS = -0.16) is 24.5℃, and the SET range of the Level I comfort zone with a dissatisfaction rate of less than 10% is [22.2℃, 26.8℃]; the optimal SET when the dissatisfaction rate is lowest in winter (TS = 0.56) is 25.2℃, and the SET range of the Level I comfort zone with a dissatisfaction rate of less than 10% is [22.3℃, 28.1℃].

[0149] Step 3: Based on the superiority / inferiority distance method, determine the superiority / inferiority of the air supply mode during the air conditioner's startup phase, and determine winter / summer operating mode 1 and operating mode 2.

[0150] During the start-up phase of an air conditioner, the indoor environment changes hourly, causing subjective thermal sensation to change hourly as well. Both the environment and subjective thermal sensation are in dynamic change. Using a single thermal comfort index or its change rate for evaluation cannot accurately assess the quality of the start-up phase under each set condition. Therefore, the Top-to-Side Solution (TOPSIS) method from the comprehensive evaluation method is introduced to judge the quality of each condition.

[0151] The TOPSIS method generally includes four steps: normalizing the original data matrix, standardizing the matrix, calculating the distance between the optimal and worst solutions, and calculating and ranking the scores.

[0152] Forwarding of the original data matrix

[0153] Forwarding the original data matrix involves unifying the different indicator types in the original data. Generally, these indicators are processed uniformly and transformed into extremely large indicators to facilitate calculation and processing. The transformation method is as follows:

[0154] For very small metrics:

[0155] x′=Mx (1)

[0156] In the formula:

[0157] x′ is the transformed index;

[0158] M is the maximum value in this indicator;

[0159] x represents the indicator before the transformation.

[0160] For intermediate indicators:

[0161] M = max{|x i -x best |} (2)

[0162]

[0163] For interval indicators:

[0164]

[0165] 1, a≤x≤b

[0166]

[0167] 2) Construct a standardized matrix

[0168] The normalized matrix is ​​then standardized, meaning the elements in each index are standardized. The formula is as follows:

[0169]

[0170] 3) Calculate the difference between each evaluation index and the optimal and worst vectors.

[0171] The distance between the i-th evaluation object and the maximum value is calculated using Euclidean distance:

[0172]

[0173] The distance between the i-th evaluation object and the minimum value is calculated using Euclidean distance:

[0174]

[0175] Where w j The weight of the j-th attribute is determined using the entropy weight method in this study.

[0176] 4) Calculate the degree of similarity between the evaluated object and the optimal solution. The calculation formula is as follows, and then sort them.

[0177]

[0178] Based on a combination of subjective and objective indicators, three subjective indicators—thermal sensation vote, thermal comfort vote, and dissatisfaction rate—and one objective indicator—SET—were selected as the four indicators for comprehensive evaluation. For the unstable thermal sensation stage, the indicators all used the magnitude of change as the measurement standard; in summer, all indicators were at their minimum values, and in winter, they were at their maximum values. The weight of each indicator was determined using the entropy weight method, dividing the evaluation into two seasons and two stages: unstable and stable thermal sensation. The weights are shown in Table 3. The practical significance of this calculation is that before thermal sensation stabilizes, the greater the overall improvement in thermal comfort brought by the air conditioner, the better; and after thermal sensation stabilizes, the closer the air conditioner is to the overall comfort value of each indicator, the better.

[0179] Table 3. Weights of Indicators Calculated Using Entropy Weight Method at Different Stages

[0180]

[0181] TOPSIS calculations and analyses were performed before and after the summer heat perception stabilized, and before and after the winter heat perception stabilized. The average supply and return air temperature difference of the air conditioner under each stage and operating condition was statistically analyzed, and the ranking of each set operating condition is shown in Table 4. The division of the average supply air temperature difference under the air conditioner operation in each stage is shown in Table 5.

[0182] Table 4. Overall Ranking of Operating Conditions Based on TOPSIS

[0183]

[0184]

[0185] Table 5. Classification of Average Supply Air Temperature Difference under Different Stages of Air Conditioning Operation

[0186]

[0187] Combining Tables 4 and 5, it can be seen that the optimal start-up mode for air conditioning in summer is medium air volume and large supply air temperature difference; the worst start-up mode is small air volume and small supply air temperature difference. After the summer heat sensation stabilizes, the most comfortable operating mode is small air volume and medium supply air temperature difference. In winter, the optimal start-up mode for air conditioning is large air volume and large supply air temperature difference; the worst mode is small air volume and small supply air temperature difference. After the winter heat sensation stabilizes, the most comfortable operating mode is medium supply air temperature difference and medium supply air volume. Therefore, considering the optimal SET, comfort range, and optimal operating mode, the main parameters of the control logic during the start-up phase are obtained, as shown in Table 6.

[0188] Table 6. Main parameters of the air conditioner start-up control logic based on the PTS model.

[0189]

[0190] Step 4: Determine the air conditioning control strategy based on the user-set temperature and the actual temperature change in the room within half an hour of the air conditioner starting.

[0191] Example 1: In summer, the user sets the operating condition to 26℃ and high wind speed.

[0192] (1) Select different operating modes according to winter heating or summer cooling 1.

[0193] Select operating mode 1 (see Table 6), which is medium air volume and large temperature difference. Therefore, operate at medium air speed to maintain the supply and return air temperature difference at 13.18–14.66℃.

[0194] (2) Environmental monitoring is conducted in the personnel activity area, and environmental parameters such as air temperature and relative humidity are collected in real time. The standard effective temperature (SET) of the personnel activity area is calculated using the Python thermal comfort calculation package pythermalcomfort1.3.1. The actual standard effective temperature of the room is compared with the optimal standard effective temperature of 24.5℃ in summer. If the temperature is higher than 24.5℃, the air conditioner operates in mode 1; if the temperature is lower than the optimal standard effective temperature in summer, it switches to mode 2. As shown in Table 6, mode 2 in summer is low air volume and medium temperature difference operation, that is, low air setting with a supply and return air temperature difference of 8.94~9.80℃.

[0195] (3) Before the air temperature reaches the set temperature, the operation mode 2 is kept running continuously; after the air temperature reaches the set temperature, the start-stop control is turned on and the operation mode 2 is run intermittently, so that the air temperature is always between the set temperature and the air temperature corresponding to the best SET, while keeping SET in the level I comfort zone.

[0196] The system collects the air temperature and compares it with the set temperature. If the room air temperature is higher than the set temperature, it maintains operating mode 2, i.e., continuous operation with low airflow and temperature difference. When the air temperature reaches the set temperature, i.e., when the air temperature is lower than the user's set temperature, the air conditioner operates intermittently to maintain the air temperature within [24.5, 26]℃.

[0197] (4) Determine if half an hour has been reached. If so, exit the running logic.

[0198] (5) Using this method, the thermal comfort is improved during the start-up phase:

[0199] The SET variation curve within 30 minutes under high wind speed at 26℃ and based on PTS model control logic is shown below. Figure 5 As shown in the figure, the set time (SET) under the PTS model control logic is basically the same as that under 26℃ high wind speed in the first 9 minutes, but differences appear between 9 and 30 minutes. Based on SET, the PTS model, and the relationship between thermal sensation and satisfaction rate / thermal comfort, the satisfaction rate and thermal comfort at each minute can be calculated. Figure 6 The graph shows the changes in dissatisfaction rate and thermal comfort under high wind speed conditions at 26℃ and PTS model control logic. As can be seen from the graph, under PTS model control, the dissatisfaction rate decreased by 0.09% to 2.71% within 9 to 30 minutes, with an average decrease of 1.52% during the entire start-up phase; the thermal comfort improved by 1.32% to 22.06%, with an average improvement of 10.76% during the entire start-up phase.

[0200] Example 2: In winter, the user sets the operating condition to 21℃ and high wind speed.

[0201] (1) Select different operating modes according to winter heating or summer cooling 1.

[0202] Select operating mode 1 (see Table 6), which is high air volume and large temperature difference. Therefore, high-speed operation is adopted to maintain the supply and return air temperature difference at 21.49~23.00℃.

[0203] (2) Environmental monitoring is conducted in the personnel activity area, and environmental parameters such as air temperature and relative humidity are collected in real time to calculate the standard effective temperature (SET) of the personnel activity area. The actual standard effective temperature of the room is compared with the optimal standard effective temperature of 25.2°C in winter. If the temperature is lower than 24.5°C, the air conditioner operates in mode 1; if the temperature is higher than the optimal standard effective temperature in winter, it switches to mode 2. As shown in Table 6, mode 2 in winter is a medium air volume and medium temperature difference operation, that is, using medium airflow with a supply and return air temperature difference of 17.26–20.38°C.

[0204] (3) Before the air temperature reaches the set temperature, the operation mode 2 is kept running continuously; after the air temperature reaches the set temperature, the start-stop control is turned on and the operation mode 2 is run intermittently, so that the air temperature is always between the set temperature and the air temperature corresponding to the best SET, while keeping SET in the level I comfort zone.

[0205] This involves collecting the air temperature and comparing it with the set temperature. If the room air temperature is higher than the set temperature, the system maintains operating mode 2, i.e., continuous operation with low airflow and temperature difference. When the air temperature reaches the set temperature, i.e., when the air temperature is lower than the user's set temperature, the air conditioner operates intermittently to maintain the air temperature at 25.2℃. The SET range for the Level I comfort zone, with a dissatisfaction rate of less than 10%, is [22.3℃, 25.2℃].

[0206] (4) Determine if half an hour has been reached. If so, exit the running logic.

[0207] (5) Using this method, the thermal comfort is improved during the start-up phase:

[0208] The SET variation curves within 30 minutes at a high wind speed of 21℃ and under the control logic based on the PTS model are as follows: Figure 7 As shown in the figure, the set time (SET) under the PTS model control logic in the first 4 minutes is basically the same as that under 21℃ high wind speed, but differences appear between 5 and 30 minutes. Based on the SET, PTS model, and the relationship between thermal sensation and satisfaction rate / thermal comfort, the satisfaction rate and thermal comfort at each minute can be calculated. Figure 8 The graph shows the changes in dissatisfaction rate and thermal comfort under high wind speed conditions at 21℃ and with the same initial conditions, controlled by the PTS model. The graph shows that, through PTS model control, the dissatisfaction rate decreases by a significant margin within 5–30 minutes.

[0209] The improvement in thermal comfort ranged from 0.05% to 2.31%, with an average decrease of 2.01% throughout the entire start-up phase; the improvement was in...

[0210] The percentage ranged from 1.40% to 26.60%, with an average increase of 15.45% throughout the entire startup phase.

Claims

1. A method for improving thermal comfort during the start-up phase of a household air conditioner, characterized in that, Includes the following steps: Step 1) Construct a model relating thermal sensation to standard equivalent temperature; Step 2) Calculate the optimal standard equivalent temperature using a model relating thermal sensation to standard equivalent temperature; Step 3) Obtain environmental parameters of the personnel activity area and calculate the average air temperature and standard equivalent temperature of the personnel activity area; Step 4) Turn on the household air conditioner and operate it in operating mode I until the standard equivalent temperature of the area where people are active reaches the optimal standard equivalent temperature. Step 5) Change the operating mode of the household air conditioner to operate in operating mode II until the average air temperature in the area where people are active reaches the user-set temperature. Step 6) Run the household air conditioner intermittently in operating mode II to maintain the standard equivalent temperature in the activity area within the comfortable temperature range for people. The relationship model between thermal sensation and standard equivalent temperature is shown below: (Summer) (SET < 30℃) (1) (Summer) (SET≥30℃) (2) (Winter) (3) In the formula, PTS is the average thermal sensation index; SET is the standard equivalent temperature. The comfortable temperature range for personnel is determined by the following methods: S1) Set the upper limit of the dissatisfaction rate and the lower limit of the dissatisfaction rate, and substitute them into the heat sensation-dissatisfaction rate fitting curve corresponding to the current season to obtain the upper limit of the average heat sensation index and the lower limit of the average heat sensation index. S2) Substitute the upper limit and lower limit of the average thermal sensation index into the relationship model between thermal sensation and standard equivalent temperature to obtain the corresponding upper limit and lower limit of the standard equivalent temperature, thereby constructing the comfortable temperature range for personnel.

2. The method for improving thermal comfort during the start-up phase of a household air conditioner according to claim 1, characterized in that, The environmental parameters of the personnel activity area include one or more of the following: air temperature, relative humidity, wind speed, and mean radiant temperature.

3. The method for improving thermal comfort during the start-up phase of a household air conditioner according to claim 1, characterized in that, In the model relating thermal sensation to standard equivalent temperature, the average thermal sensation index PTS is a known quantity, while the optimal standard equivalent temperature is an unknown quantity. The steps for calculating the average thermal sensation index (PTS) include: Step 1) Obtain the average thermal sensation index and the corresponding dissatisfaction rate for different seasons, and fit them to obtain the thermal sensation-dissatisfaction rate fitting curve for winter and the thermal sensation-dissatisfaction rate fitting curve for summer. Step 2) Determine the average thermal sensation index when the dissatisfaction rate is lowest, based on the current season.

4. The method for improving thermal comfort during the start-up phase of a household air conditioner according to claim 1, characterized in that, The average thermal sensation index and dissatisfaction rate were obtained through questionnaires.

5. The method for improving thermal comfort during the start-up phase of a household air conditioner according to claim 1, characterized in that, In addition to environmental parameters, the metabolic rate of personnel and the thermal resistance of clothing were also considered to calculate the standard equivalent temperature (SET), predict the average thermal perception vote (PMV), and predict the percentage of unsatisfactory thermal environment (PPD).

6. The method for improving thermal comfort during the start-up phase of a household air conditioner according to claim 1, characterized in that, The airflow and temperature difference settings for a household air conditioner's operating mode are determined using the following methods: The superior-inferiority distance method is used to evaluate different air volume and air temperature difference levels, and the air volume and air temperature difference levels with the highest evaluation are taken as the current air volume and air temperature difference levels. The evaluation indicators selected for the superior-inferior solution distance method include thermal sensation vote, thermal comfort vote, dissatisfaction rate, and standard equivalent temperature.

7. A method for improving thermal comfort during the start-up phase of a household air conditioner according to claim 6, characterized in that, When the current season is summer, operating mode I is medium air volume and large air temperature difference; operating mode II is small air volume and medium air temperature difference. In summer, the large supply air temperature difference range is [13.18℃, 14.66℃]; In summer, the temperature difference range of the central air supply is [8.94℃, 9.80℃].

8. A method for improving thermal comfort during the start-up phase of a household air conditioner according to claim 6, characterized in that, When the current season is winter, operating mode I is high air volume and high air temperature difference; operating mode II is medium air temperature difference and medium air volume. In winter, the large supply air temperature difference range is [21.49℃, 23.00℃]; During winter, the temperature difference range of the central air supply is [17.26℃, 20.38℃].

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