CN111854063A - Control method of variable frequency air conditioner - Google Patents
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Abstract
A control method of an inverter air conditioner comprises the following steps: (1) obtaining a load calculation function of indoor load changing along with indoor temperature and humidity; (2) calculating indoor loads corresponding to all temperature and humidity combinations in a temperature and humidity parameter library according to the load calculation function obtained in the step (1); (3) calculating air conditioner energy consumption corresponding to each temperature and humidity combination according to the temperature and humidity combination in the temperature and humidity parameter library and the indoor load corresponding to the temperature and humidity combination by using a pre-established relation model of the indoor load and the air conditioner running state; (4) according to the air conditioner energy consumption and the indoor comfort level corresponding to the temperature and humidity combination in the temperature and humidity parameter library, the temperature and humidity setting function is used for determining the set temperature and humidity combination, and the air conditioner temperature and humidity control module controls the indoor temperature and humidity at the set temperature and humidity combination. Therefore, the temperature and humidity combination is determined through the temperature and humidity setting function, the indoor comfort level is met, meanwhile, the lower energy consumption is realized, and meanwhile, the comfort level and the energy consumption are considered.
Description
Technical Field
The invention relates to the technical field of air conditioner control methods, in particular to a control method of a variable frequency air conditioner.
Background
Air conditioners in the market nowadays often only have a temperature control function, and research work aiming at reducing energy consumption of the air conditioners also mostly focuses on improving equipment performance (such as improving performance of a compressor or improving efficiency of a heat exchanger). In contrast, the control objectives and strategies of air conditioners are relatively simple. On the basis that the air conditioner only has a temperature control function, if the control target is optimized to achieve energy saving, the comfort level is generally sacrificed.
In order to improve the comfort of the air conditioner and realize simultaneous temperature and humidity control, some researchers provide a PID type fuzzy logic control method based on a weight rule table, which comprises the following steps: firstly, a PID signal conversion unit converts a setting signal and a feedback signal; establishing a fuzzy set, and defining a weight value of each fuzzy description variable; determining the attribution degree of each fuzzy description variable; multiplying the attribution degree of each fuzzy description variable by a weight value corresponding to the fuzzy description variable and adding to obtain a sum signal; fifthly, outputting the addition signal to a control arithmetic unit; sixthly, controlling the arithmetic unit to output signals to the execution unit for execution and simultaneously collecting feedback signals to the PID signal conversion unit; seventhly, repeating the first step and the sixth step until the set signal is the same as the feedback signal. The method replaces the traditional complex fuzzy rule table with a simple weight rule table, so that the expert experience can be more simply and intuitively presented; a defuzzification unit is not needed, so that the overall control method is optimized; the control process has minimal overshoot and oscillation. The method realizes simultaneous temperature and humidity control by combining a frequency conversion technology and an intelligent control method on the basis of not increasing hardware cost, so that the simultaneous temperature and humidity control of the household air conditioner is possible. However, this method tends to increase the air conditioning energy consumption to some extent.
On the one hand, indoor temperature and humidity control is crucial to moulding suitable indoor thermal comfort environment and good indoor air quality, and too high or too low temperature and humidity can cause discomfort to human bodies. On the other hand, the indoor temperature and humidity control affects the indoor load and the air conditioning energy efficiency, and further affects the total energy consumption of the air conditioner.
However, at present, there is no inverter air conditioner control method that can give consideration to both temperature and humidity control and energy consumption optimization, and by optimizing a suitable indoor temperature and humidity set point, the inverter air conditioner control method has low energy consumption while meeting indoor comfort.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a control method of a variable frequency air conditioner.
A control method of an inverter air conditioner comprises the following steps: (1) obtaining a load calculation function of indoor load changing along with indoor temperature and humidity; (2) calculating indoor loads corresponding to all temperature and humidity combinations in a temperature and humidity parameter library according to the load calculation function obtained in the step (1); (3) calculating air conditioner energy consumption corresponding to each temperature and humidity combination according to the temperature and humidity combination in the temperature and humidity parameter library and the indoor load corresponding to the temperature and humidity combination by using a pre-established relation model of the indoor load and the air conditioner running state; (4) according to the air conditioner energy consumption and the indoor comfort level corresponding to the temperature and humidity combination in the temperature and humidity parameter library, the temperature and humidity setting function is used for determining the set temperature and humidity combination, and the air conditioner temperature and humidity control module controls the indoor temperature and humidity at the set temperature and humidity combination. Therefore, the temperature and humidity combination is determined through the temperature and humidity setting function, the indoor comfort level is met, meanwhile, the lower energy consumption is realized, and meanwhile, the comfort level and the energy consumption are considered.
Further, in the step (1), a load calculation function of the indoor load changing along with the indoor temperature and humidity is obtained through modeling or obtained through data fitting obtained through actual measurement of a sensor.
Further, when a load calculation function of the indoor load changing along with the indoor temperature and humidity in the step (1) is obtained through modeling, the change rule of the indoor heat load Qs along with the indoor temperature T is as follows:
the change rule of the indoor wet load Ql along with the indoor humidity h is as follows:
Further, in the step (2), the temperature range in the medium temperature and humidity parameter library is 22-28 ℃, and the humidity range is 30-70% relative humidity.
Further, the relation model of the indoor load and the air conditioner operation state in the step (3) is a mathematical model based on a physical relation between the parameters or a mathematical model trained based on existing data.
Further, when a relation model of the indoor load and the air conditioner running state is established in the step (3), a stable working condition data set is obtained through experimental measurement, each group of data comprises air conditioner return air temperature, air conditioner return air humidity, air feeder rotating speed, compressor rotating speed, indoor sensible heat load and indoor latent heat load, a neural network is established, the measured stable working condition data set is input into the neural network for training by using a BP back propagation algorithm, the input layers are the air conditioner return air temperature, the air conditioner return air humidity, the indoor sensible heat load and the indoor latent heat load, the output layers are the air feeder rotating speed and the compressor rotating speed, and the trained neural network is the relation model representing the indoor load and the air conditioner running state.
Further, the temperature and humidity setting function in step (4) is as follows: f (T, h) ═ α Comfort2+ (1- α) Ptot2, where T is the indoor temperature; h is the indoor humidity; comfort is the corresponding indoor Comfort level when the indoor temperature is T and the indoor humidity is h, and the value range is-0.5; ptot is the corresponding total energy consumption of the air conditioner when the indoor temperature is T and the indoor humidity is h; and alpha is a weight coefficient, the value range is 0-1, and the temperature and humidity combination which enables the temperature and humidity setting function to reach the minimum value in the temperature and humidity parameter library is the set temperature and humidity combination.
Further, indoor comfort is measured using an estimated average thermal sensation index.
According to the control method of the variable-frequency air conditioner, the temperature and humidity combination is determined through the temperature and humidity setting function, the indoor temperature and humidity are controlled to be in the set temperature and humidity combination through the air conditioner temperature and humidity control module, the indoor comfort level is met, meanwhile, low energy consumption is achieved, the comfort level and the energy consumption are considered under the condition that the hardware cost is not increased, energy is saved, and meanwhile, the comfort of a user is guaranteed.
Drawings
Fig. 1 is a flowchart of an embodiment of an inverter air conditioner control method according to the present invention.
Fig. 2 is a schematic diagram of a neural network model for establishing a relationship between an indoor load and an air conditioner operation condition.
Detailed Description
Fig. 1 illustrates a flowchart of an inverter air conditioner control method, which includes the steps of:
(1) obtaining a load calculation function of indoor load changing along with indoor temperature and humidity; the load calculation function is a function for calculating a load.
(2) And (3) calculating the indoor load corresponding to each temperature and humidity combination in the temperature and humidity parameter library according to the load calculation function obtained in the step (1).
(3) And calculating the air conditioner energy consumption corresponding to each temperature and humidity combination according to the temperature and humidity combination in the temperature and humidity parameter library and the indoor load corresponding to the temperature and humidity combination by using a pre-established relation model between the indoor load and the air conditioner running state. In the process, each temperature and humidity combination in the temperature and humidity parameter library corresponds to a corresponding indoor load, and each temperature and humidity combination and the corresponding indoor load correspond to corresponding air conditioner energy consumption, so that each temperature and humidity combination corresponds to corresponding air conditioner energy consumption.
(4) According to the air conditioner energy consumption and the indoor comfort level corresponding to the temperature and humidity combination in the temperature and humidity parameter library, the temperature and humidity setting function is used for determining the set temperature and humidity combination, the set temperature and humidity combination is transmitted to the air conditioner temperature and humidity control module, and the indoor temperature and humidity are controlled to be the set temperature and humidity combination. It should be noted that the control at the set temperature and humidity combination means that the indoor temperature and humidity are basically maintained near the set temperature and humidity combination, including the situation that the temperature and humidity combination normally fluctuates near the set temperature and humidity combination. For example, the temperature and humidity setting function is f (T, h) ═ α Comfort2+ (1- α) Ptot2, where T is the indoor temperature; h is the indoor humidity; comfort is the corresponding indoor Comfort level when the indoor temperature is T and the indoor humidity is h, and is measured by PMV (predicted Mean Vote), the value range is-0.5 to 0.5, Ptot is the corresponding total air conditioner energy consumption when the indoor temperature is T and the indoor humidity is h, the Comfort level is measured by a first term of a temperature and humidity setting function, the energy consumption of the air conditioner is measured by a second term, and the importance of the Comfort level and the air conditioner energy consumption is determined by a weight coefficient alpha. And the temperature and humidity combination which enables the temperature and humidity setting function to reach the minimum value in the temperature and humidity parameter library is the set temperature and humidity combination. The value range of alpha is 0 to 1, the closer to 0, the greater the influence of the energy consumption item of the air conditioner, and the more energy-saving the selected set temperature and humidity combination; the closer alpha is to 1, the greater the influence of the indoor comfort item is, and the more comfortable the selected set temperature and humidity combination is.
The load calculation function of the indoor heat and humidity load changing along with the indoor temperature and humidity in the step (1) can be obtained through modeling, and can also be obtained through fitting data obtained through sensor measurement. For example, two sets of preset temperature and humidity combinations are sequentially used as set temperature and humidity combinations to be transmitted to the air conditioner temperature and humidity control module, the indoor temperature and humidity are controlled stably, the air conditioner air supply temperature, the air conditioner air supply humidity, the air conditioner return air temperature, the air conditioner return air humidity and the air volume are measured through sensors, and the refrigerating capacity of the air conditioner when the two sets of indoor temperature and humidity are stable is calculated. When the indoor temperature and humidity are stable, the refrigerating capacity of the air conditioner is equal to that of the indoor load, so that indoor sensible heat load Qs1 and latent heat load Ql1 corresponding to a first group of stable indoor temperature and humidity T1, h1 (moisture content) are obtained; the second group of stable indoor temperature and humidity T2, indoor sensible heat load Qs2 and latent heat load Ql2 corresponding to h2 (moisture content), and the change rule of the obtained indoor heat load Qs along with the indoor temperature T is as follows:
the change rule of the indoor humidity load Ql along with the indoor humidity h (humidity content) is as follows:
and (3) in the temperature and humidity parameter library in the step (2), the temperature range is 22-28 ℃, and the humidity range is 30-70% of relative humidity.
In the step (3), the relation model is a mathematical model based on the physical relation between the parameters or a mathematical model obtained by training based on existing data. For example, for a certain air conditioner, a neural network as shown in fig. 2 is established, and 180 sets of stable condition data are obtained through experimental measurement, wherein each set of data comprises air conditioner return air temperature, air conditioner return air humidity, blower rotating speed, compressor rotating speed, indoor sensible heat load and indoor latent heat load. Under the stable working condition, the indoor sensible heat load is equal to the sensible heat refrigerating capacity of the air conditioner, and the indoor latent heat load is equal to the latent heat refrigerating capacity of the air conditioner. By utilizing a BP back propagation algorithm, 180 groups of obtained experimental data are substituted into the neural network shown in figure 2 for training, the input layer is the indoor dry bulb temperature (corresponding to the return air temperature of the air conditioner), the indoor wet bulb temperature (corresponding to the return air humidity of the air conditioner), the sensible heat refrigerating capacity (corresponding to the indoor sensible heat load) and the latent heat refrigerating capacity (corresponding to the indoor latent heat load), and the output layer is the required rotating speed of the air feeder and the rotating speed of the compressor. The trained neural network is a relational model representing the indoor load and the air conditioner running state.
The air conditioner temperature and humidity control module can adjust the rotating speed of an air conditioner compressor and a fan according to the transmitted temperature and humidity set point, so that the temperature and humidity in an air-conditioned room are stabilized on the temperature and humidity set point. For example, the chinese patent application No. 201410038997.X discloses a PID type fuzzy logic control method based on a weight rule table for an air conditioning system.
And the indoor comfort level is calculated according to the temperature and humidity combination in the temperature and humidity parameter library and the parameters acquired by the air conditioner in real time. The parameters include but are not limited to indoor radiation temperature and wind speed. Of course, the parameters may be fixed values set in advance.
In this example, the room temperature was initially 28 ℃ and the humidity was 70%. The two preset temperature and humidity combinations are (25.1 ℃, 50%), (23.3 ℃, 50%), and are sequentially transmitted to the air conditioner temperature and humidity control module as the set temperature and humidity combinations to control the indoor temperature and humidity stably. Steps (1) to (4) were sequentially performed while setting α to 0, 0.5, and 1, respectively, and the control effects are shown in table 1. Since the air conditioning components in which significant energy consumption changes occur in this embodiment are the compressor and the blower, the total energy consumption in table 1 is the sum of the compressor energy consumption and the blower energy consumption. When α is 0, the corresponding air-conditioning energy consumption is saved by 23.3% compared with that when α is 1. The experimental result achieves the expected effect of the control strategy, namely that alpha is 0 and is the most energy-saving calculated and controlled temperature and humidity set temperature and humidity combination, and alpha is 1 and is the most comfortable calculated and controlled temperature and humidity set temperature and humidity combination. The indoor temperature and humidity controlled by each group meet the requirement of comfort level. As can be seen from the foregoing analysis, the energy saving effect is achieved on one hand because the effect of the comfort level in the cost formula is reduced to allow a higher set temperature and a higher set humidity, thereby reducing the heat and humidity load in the room; on the other hand, when α is 0, the air conditioning efficiency under the set temperature and humidity combination is increased.
TABLE 1
| Alpha value | 0 | 0.5 | 1 |
| Indoor temperature (. degree.C.) | 25 | 23.9 | 23.3 |
| Indoor humidity | 55％ | 55％ | 50％ |
| Total energy consumption of air conditioner (W) | 1091 | 1201 | 1422 |
| Indoor comfort level | 0.5 | 0.2 | 0 |
Claims (8)
1. The control method of the inverter air conditioner is characterized by comprising the following steps:
(1) obtaining a load calculation function of indoor load changing along with indoor temperature and humidity;
(2) calculating indoor loads corresponding to all temperature and humidity combinations in a temperature and humidity parameter library according to the load calculation function obtained in the step (1);
(3) calculating air conditioner energy consumption corresponding to each temperature and humidity combination according to the temperature and humidity combination in the temperature and humidity parameter library and the indoor load corresponding to the temperature and humidity combination by using a pre-established relation model of the indoor load and the air conditioner running state;
(4) according to the air conditioner energy consumption and the indoor comfort level corresponding to the temperature and humidity combination in the temperature and humidity parameter library, the temperature and humidity setting function is used for determining the set temperature and humidity combination, and the air conditioner temperature and humidity control module controls the indoor temperature and humidity at the set temperature and humidity combination.
2. The inverter air conditioner control method according to claim 1, wherein the load calculation function of the indoor load varying with the indoor temperature and humidity in step (1) is obtained by modeling or fitting data obtained by actual measurement of a sensor.
3. The inverter air conditioner control method according to claim 2, wherein when the load calculation function of the indoor load varying with the indoor temperature and humidity in step (1) is obtained through modeling, the variation rule of the indoor heat load Qs with the indoor temperature T is as follows:
the change rule of the indoor wet load Ql along with the indoor humidity h is as follows:
4. The inverter air conditioner control method according to claim 1, wherein the temperature range in the moderate temperature and humidity parameter library in the step (2) is 22-28 ℃, and the humidity range is 30-70% relative humidity.
5. The inverter air conditioner control method according to claim 1, wherein the relational model of the indoor load with respect to the air conditioner operation state in the step (3) is a mathematical model based on a physical relationship between the respective parameters or a mathematical model trained based on existing data.
6. The control method of the inverter air conditioner according to claim 5, wherein when the relational model between the indoor load and the air conditioner operation state is established in step (3), a stable working condition data set is obtained through experimental measurement, each set of data comprises air conditioner return air temperature, air conditioner return air humidity, blower rotation speed, compressor rotation speed, indoor sensible heat load and indoor latent heat load, a neural network is established, the measured stable working condition data set is input into the neural network for training by using a BP back propagation algorithm, the input layers comprise air conditioner return air temperature, air conditioner return air humidity, indoor sensible heat load and indoor latent heat load, the output layers comprise blower rotation speed and compressor rotation speed, and the trained neural network is the relational model representing the indoor load and the air conditioner operation state.
7. The inverter air conditioner control method according to claim 1, wherein the moderate temperature humidity setting function in step (4) is:
f(T,h)＝αComfort2+(1-α)Ptot2，
wherein T is the indoor temperature; h is the indoor humidity; comfort is the corresponding indoor Comfort level when the indoor temperature is T and the indoor humidity is h, and the value range is-0.5; ptot is the corresponding total energy consumption of the air conditioner when the indoor temperature is T and the indoor humidity is h; alpha is a weight coefficient and has a value range of 0-1;
and the temperature and humidity combination which enables the temperature and humidity setting function to reach the minimum value in the temperature and humidity parameter library is the set temperature and humidity combination.
8. The inverter air conditioner control method according to any one of claims 1-7, wherein indoor comfort is measured using a predicted average thermal sensation index.
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| CN112923525A (en) * | 2021-02-26 | 2021-06-08 | 深圳市励科机电科技工程有限公司 | Machine learning type comfortable energy-saving air conditioner intelligent control method |
| CN113339941A (en) * | 2020-07-06 | 2021-09-03 | 浙江大学 | Control method of variable frequency air conditioner |
| CN114893859A (en) * | 2022-05-13 | 2022-08-12 | 武汉理工大学 | Ocean platform cabin air conditioning control system and method and storage medium |
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| CN114198881A (en) * | 2021-12-16 | 2022-03-18 | 珠海格力电器股份有限公司 | Air conditioner control method and device and air conditioner |
| CN114294805B (en) * | 2022-02-14 | 2023-04-21 | 珠海格力电器股份有限公司 | Air conditioner control method and device, air conditioner and nonvolatile storage medium |
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