KR0176689B1 - Temp.control method and device thereof in ref. - Google Patents

Abstract

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for controlling the temperature of a refrigerator by controlling the speed of a rotating blade and a device for controlling the temperature of the refrigerator. A method for controlling a temperature of a refrigerator according to the present invention is a method for controlling a temperature of a refrigerator having a rotary blade rotatingly driven to discharge cold air into a refrigerating chamber and a driving motor rotating the rotary vane, The method comprising: constructing a fuzzy model; Measuring a temperature of a predetermined portion of the refrigerator; Inputting the temperature measurement value to the fuzzy model to fuzzy inference the highest temperature position in the refrigerator; And controlling the rotation speed of the rotary vane so that the rotary vane has an equilibrium speed at which cool air is discharged at the highest temperature position of the fuzzy inferred refrigerator. Thus, by using a fuzzy model, the temperature value of each part of the refrigerating compartment can be precisely deduced with only a small number of temperature sensors, and the rotating speed of the rotating blades can be adjusted according to the deduced position, It can be kept even without being concentrated on a specific site.

Description

A method of controlling the temperature of the refrigerator by the speed control of the rotating blades and a temperature control device of the refrigerator

The present invention relates to a method for controlling the temperature of a refrigerator by controlling the speed of a rotary vane and a device for controlling the temperature of the refrigerator by performing a cold distribution according to the distance from the rotary vane in the refrigerating chamber by fuzzy inference, will be.

In a refrigerator, particularly a large refrigerator, the load of foods and the like contained in the refrigerating chamber is different depending on each part of the refrigerating chamber, so that it is difficult to keep the temperature distribution in the refrigerating chamber evenly. There is a method of controlling the temperature in the refrigerating chamber to maintain a uniform temperature distribution by attaching a rotary vane to the rear surface of the refrigerating chamber, rotating the rotary vane, adjusting the discharge of the cold air, and discharging the cold air to a higher temperature side. The rotary vane determines the direction of discharging the cold air according to the position of the stop angle upon rotation, or continues to rotate to discharge the cold air at a constant speed as in the case of the blower fan.

However, in the refrigerator having such a rotary vane, the wind power due to the rotation of the rotary vane is always fixed, which disadvantageously disallows the distribution according to the distance of the region where the cool air is discharged. That is, when it is desired to discharge the cold air to the front part of the refrigerator compartment far from the rotary vane, it is necessary to rotate the rotary vane at a high speed to increase the discharge speed of the cold air, It is necessary to rotate or stop the rotating blades at a low speed to weaken the discharging speed of the cooling air. However, the conventional rotating blades can not control the rotating speed because the rotating speed is always fixed.

In addition, as a precondition for adjusting the discharge speed of the cold air by adjusting the rotation speed of the rotary blades, the temperature of each part in the refrigerating compartment, in particular, each part according to the distance from the rotary blades, must be accurately measured. Since there are only one temperature sensor at the top and bottom of the refrigerating chamber, only two temperature sensors are used, so that the temperature of each part of the refrigerating chamber is not accurately measured.

SUMMARY OF THE INVENTION It is therefore an object of the present invention to provide a method and apparatus for accurately estimating the temperature value of each portion of a refrigerating chamber by using a fuzzy model having a reasoning function and measuring the rotational speed of the rotating blades according to the estimated position, So that the temperature in the refrigerating compartment can be maintained uniformly without being deviated to a specific area, and to provide a temperature control method and a temperature control device for the refrigerator.

1 is a partial front view of a refrigerator;

FIG. 2 is an enlarged perspective view of the rotary blade. FIG.

FIG. 3 is a diagram showing the distribution of cold air according to the distance in the refrigerating compartment according to the rotation speed of the rotary blades.

FIG. 4 is a graph showing the speed at which a rotary vane must rotate to achieve cold air distribution over a distance.

Figure 5 is a table illustrating data for applying the TSK fuzzy model.

FIG. 6 is a graph showing each divided structure when the data of Table 1 of FIG.

7 is a schematic perspective view of each stage of the refrigerator compartment showing the selected points for measuring the temperature inside the refrigerator compartment;

FIG. 8 is a control block diagram of a temperature control apparatus according to the present invention; FIG.

FIG. 9 is a circuit diagram of a speed control apparatus for implementing a speed control method of a rotary vane according to the present invention; FIG.

10 is a graph showing a waveform of an AC power supply voltage.

FIG. 11 is a graph showing waveforms in which a zero voltage is detected and output from a zero voltage detecting unit; FIG.

FIG. 12 shows the waveforms of the predetermined section ) A graph showing a trigger signal generated from a microcomputer at a delayed time.

FIG. 13 is a graph showing a waveform of a power supply voltage applied to a drive motor as an AC waveform having a predetermined section;

DESCRIPTION OF THE REFERENCE NUMERALS

10: refrigerating chamber 11, 12: temperature sensor

20: Rotating blade 31: Microcomputer

37: rotary blade position sensor 41: drive motor

45: Triac 47: AC power source

49: Transformer 51: Balance speed calculating section

52: Balanced voltage calculating unit 54: Trigger pulse generating unit

56: Fuzzy reasoning part

According to the present invention, there is provided a method for controlling a temperature of a refrigerator having a rotary blade for rotary driving to discharge cold air into a refrigerating chamber and a driving motor for rotating the rotary vane, Constructing a fuzzy model; Measuring a temperature of a predetermined portion of the refrigerator; Inputting the temperature measurement value to the fuzzy model to fuzzy inference the highest temperature position in the refrigerator; And controlling the rotational speed of the rotary vane so that the rotational speed of the rotary vane is balanced so as to discharge the cool air at the highest temperature position of the fuzzy inferior room.

The step of constructing the fuzzy model may include the steps of: preparing actual measurement data of a temperature change in a plurality of radial areas partitioned around the rotary vane, based on a temperature measurement value in the refrigerating chamber; Fuzzy partitioning based on actual data of the temperature change; Selecting an optimal structure among the divided structures of the fuzzy divided area; And calculating a line form deducing a maximum temperature position of the refrigerator based on the optimal structure. Thus, the temperature of the refrigerator can be accurately deduced by the fuzzy inference by the TSK-fuzzy model.

The step of controlling the rotational speed of the rotary vane may further include calculating the equilibrium speed; Calculating a balanced voltage to cause the rotary vane to rotate at the equilibrium speed; And supplying the balanced voltage to the driving motor. Thus, the voltage of the power supply voltage supplied to the driving motor is cut off as needed, and the speed of the driving motor can be easily varied.

At this time, the step of supplying the balanced voltage may include: detecting a zero point of a predetermined AC power supply voltage; Calculating a delay time to cut the AC power supply voltage based on the zero point so that the balanced voltage is generated; And the step of cutting the AC power supply voltage from the zero point to the delay time so as to find zero crossing of the voltage and to determine the amount of the cutoff by the function related to the delay time, do.

The temperature control method includes: detecting an actual rotation speed of the rotary vane; Calculating an error between the actual rotation speed and the equilibrium speed; The method further includes correcting the rotation speed of the rotary vane so that the calculated error is reflected, thereby correcting the difference between the equilibrium speed to be controlled and the actual rotation speed to enable more accurate control .

Also, according to the present invention, there is provided an apparatus for controlling the temperature of a refrigerator that performs the method of controlling the temperature of the refrigerator.

Hereinafter, the present invention will be described in detail with reference to the drawings.

1 is a partial front view of the refrigerator; The refrigerator compartment 10 of the refrigerator is typically installed at the bottom of the refrigerator. The refrigerating compartment 10 is divided into upper and lower portions, and the lowermost portion is used as a vegetable compartment 1. Typically, the uppermost column is ¾ H (5), the second column is ½ H (6), and the third column is ⅓ H (7), except for the uppermost column 2 , And this name is used in the following description. Two temperature sensors 11 and 12 are provided in the refrigerating compartment 10 and an S1 sensor 11 is provided on the left side of the refrigerating compartment 5 to measure the temperature of the upper left portion of the refrigerating compartment, Is provided on the right side of the refrigerator compartment to measure the temperature of the lower right portion of the refrigerating compartment. A cold air discharge portion 15 is provided on the inner rear surface of the refrigerating chamber 10 and the cold air from the cold air discharge portion 15 is regulated by a rotary blade.

2 is an enlarged perspective view of the rotary vane. The rotary vane 20 is divided into three stages in the vertical direction and is composed of an upper vane 21, a middle vane 22 and a lower vane 23, and each vane is divided into three vanes 5, 5, 7). The wings 21, 22, and 23 are integrally rotated about the rotary shaft 25 as a center. The directions indicated by the respective blades 21, 22, and 23 are different from each other, and the angle of rotation between the blades is 60 Respectively. An evaporator (not shown) is provided on the rear surface of the rotary vane 20 in the refrigerating chamber 10. The chilled air from the evaporator (not shown) of the refrigerator is adjusted in accordance with the rotational speed of the rotary vane 20 so that the discharge speed of the cold air discharged to each of the chambers 5, 6, 7 of the refrigerating chamber 10 is adjusted.

The rotary vane 20 serves to discharge cold air intensively to a specific area where the temperature has been raised by blowing cold air in a state in which the rotary vane 20 is stopped in a specific direction or to rotate continuously in the refrigerating operation of the refrigerator, And to spread it evenly. The cool air is discharged toward the front portion of the refrigerating compartment 10 at a distance from the rotary vane 20 when the rotation speed of the rotary vane 20 is fast and the cold air is discharged from the refrigerating compartment 10 The cold air is discharged to the rear portion of the air conditioner.

FIG. 3 is a diagram showing a cold air distribution according to the distance in the refrigerating compartment according to the rotation speed of the rotary compartment; FIG. 4 is a view showing a region by the cross section of the refrigerating compartment; Speed.

P _R means the rear area of the refrigerator compartment close to the rotary vane, P _F means the front area of the refrigerator compartment away from the rotary vane, and P _M means the middle area. When rotating the rotary blade at a rate of 4 degrees V _L mainly the cool air is distributed to P _R region, when rotating the rotary blade at a rate of V _M is mainly cool air is distributed to P _M areas, at a speed of V _H When the rotary vane rotates, the cold air is mainly distributed to the P _F region. The rotational speed of the rotating blades is not controlled to have a discontinuous value but is controlled to rotate at a speed at which the cool air reaches a point deduced to be the highest temperature so that actually a continuous value between the minimum rotational speed and the maximum rotational speed As shown in FIG.

In the present invention, the temperature of each part in the refrigerating compartment is inferred and the learning is performed based on the data based on the estimated temperature, so that the cold air is discharged toward the portion determined to be the highest temperature. The implementation of the method is divided into two stages.

The first step is to accurately deduce the temperature at various portions in the refrigerating chamber 10, particularly at various portions having different distances from the rotary vane 20, by means of fuzzy inference only by the two temperature sensors S1 and S2. We use fuzzy inference based on the TSK fuzzy model.

The second step is to control the speed of the rotary vanes 20 so that the cool air can be discharged at an optimum speed to reach the deduced distance. The voltage of the voltage applied to the driving motor for driving the rotary vane 20 is cut as much as necessary to reduce the effective value of the voltage so as to reduce the rotational speed of the rotary vane.

Each step will be described in detail below.

The first step is the inference step by TSK fuzzy (Takagi - Sugeno - strong fuzzy). To illustrate this step, we first explain the inference process of TSK fuzzy as a general example.

Fuzzy inference requires multiple data for each of a number of variables. Table 1 is illustrated in FIG. 5 to illustrate this data. In Table 1, X1, X2, X3, and X4 are input variables and Y is an output variable. In this example, there are four input variables and one output variable. The numerical relationships shown in Table 1 for the input and output variables are obtained from measurements. It is the ultimate goal of the TSK fuzzy to express the linear relationship between the input and output variables using a formula of these multiple measurement values. Therefore, the ultimate linear form expressing the input / output relation we want to obtain is expressed as the following equation, which is the conclusion of fuzzy reasoning.

As shown in Table 1, the value of the output according to the change of each input variable differs depending on the degree of contribution of each variable to the total output, and the degree of the difference depends on each input variable (X1, X2, X3, X4) (A ₁ , a ₂ , a ₃ , a ₄ ) that are multiplied. Hereinafter, each stage is divided into stages.

[Stage 1]

First, a line form representing the input / output relationship is constructed using the data given in Table 1. The least squares method used in numerical analysis is generally used, and the least variable is reduced by using the variable reduction method by the error rate. The equation thus obtained is as follows.

This form is like equation (1), but it is not the final equation to be sought but it is the basis for constructing the fuzzy model for fuzzy reasoning. Based on this equation, we divide the region with the largest contribution, and obtain the optimal line form that most appropriately expresses the contribution of each variable. In the equation (2), the variable X4 was removed by an algorithm based on the variable reduction method.

For this equation, we apply the general inconveniences to model the input / output relationship of the nonlinear system as a polynomial of the input variable. In order to obtain the incongruence value, we divide the whole data into two groups and create group A and group B, and substitute them into the following equation.

here, Is an estimate of the output of group A by the fuzzy model obtained according to group A, Is an estimate of the output of group A by the fuzzy model obtained according to group B, Is an estimate of the output of group B by the fuzzy model obtained according to group B, N _A is the number of data in the group A, n _B is the number of data in the group B, and the first term is an estimate of the output of the group B by the fuzzy model obtained according to the group A, The difference between the estimates of the outputs by group B and the second is the difference between the estimates of the outputs by group A and group B for the input data of group B. [

The uncomfortable value thus obtained is called U.C (1). The incongruous value obtained for the data in Table 1 is,

to be.

[Stage 2]

We set up a fuzzy model with two plant laws. Here, the problem of structure setting of the preamble corresponding to the if part of the if-then rule of the fuzzy model comes out. In the structure setting, the selection of the variable and the fuzzy division are considered at the same time.

First, we consider a structure that has only one of X1, X2, X3, and X4 as a preconditioner variable, and divides the space into two. Therefore, there are four possible structures for the premise.

For example,

L1: if X1 = SMALL, then Y =

L2: if X1 = BIG, then Y =

Which is the model of the two plant laws.

In the second structure,

L1: if X2 = SMALL, then Y =

L2: if X2 = BIG, then Y =

to be.

The preconditioner parameters are set for these preconditioner structures, and the structure and parameters of the conclusion section are set based on the results. The U.C value is calculated as follows.

U.C (2-1) = 5.4

U.C (2-2) = 3.5

U.C (2-3) = 3.3

U. C (2-4) = 4.6

Here, the first number in the parentheses indicates the fuzzy 2 division, and the second number is the same numerical value as the index of the variable. For example, UC (2-4) means the incongruous value at the time of fuzzy two division about X4. (The same shall apply hereinafter)

Comparing these values, the value of U.C (2-3) is the smallest, so we construct the fuzzy model around it. The selected fuzzy model is as follows.

[Stage 3]

Since the variable X3 is entered in the precondition of stage 2, the fuzzy three-division is performed based on the variable X3. Variables to be added to the fuzzy three-partition are those whose U.C value is small in stage 2. Therefore, here, fuzzy three-division is performed around X2.

The possible structure of the preamble is divided into three areas as shown in Fig.

Taking the third of these as an example,

L1: if X3 = SMALL, then Y =

L2: if X2 = MEDIUM, then Y =

L3: if X2 = BIG, then Y =

As shown in Fig.

If the U.C value is obtained by setting the parameter setting and the conclusion part for these three structures, it can be understood that the first structure has the smallest U.C value as follows.

This is the fuzzy model partition structure of the stage 3.

[Stage 4]

The fuzzy partitioning and the process of finding the incongruity for each partition structure are repeated. This is done until the U.C value reaches the smallest value. If the value is no longer small, take the structure at that time as an optimal structure and obtain the expression of the conclusion.

The conclusion of the conclusion can be regarded as reflecting optimally the contribution of each variable, and the conclusion of the conclusion can be seen as expressing this relation sufficiently.

Hereinafter, a process of creating a line format by obtaining the conclusion of the if-then rule in the present invention will be described in detail.

In order to obtain the fuzzy model for estimating the temperature distribution in the hood by using the measured values of the S1 sensor and the S2 sensor in Fig. 1, it is necessary to first determine the temperature change at various points depending on the vertical position and the distance from the rotary vane We need data.

Figure 7 shows each point selected to measure the temperature inside the refrigerating compartment. The plane of each stage (¾H, ½H, ⅓H) in the refrigerating compartment is indicated by 9 points of 3 × 3. Therefore, the number of points to be measured is 27. These 27 points are named t1 to t27. First, the difference between the temperatures indicated by the two temperature sensors (S1, S2) and the measured values of the temperature change rate at 27 points according to the rate of change are tabulated. The table by this method is similar to Table 1 in Fig. The table thus constructed shows the temperature change rate at 27 points with respect to the temperature difference change indicated by the temperature sensors S1 and S2 in order to construct the fuzzy model for the fuzzy inference in the present invention.

Here, the input variable is a measurement value of the temperature of the 27 points (t1 to t27) with respect to the following values of the variables X1, X2, and X3.

X1 = S2 (k) - S1 (k)

X2 = S2 (k-1) - S1 (k-1)

X3 = S2 (k-2) - S1 (k-2)

to be. Here, S1 (k) is the measured value of the S1 sensor 11, S1 (k-1) is the measured value of the S1 sensor one minute ago, and S1 (k-2) is the measured value of the S1 sensor two minutes ago. S2 is the same. Therefore, X1 represents the difference between the temperature measurement values of the two temperature sensors at present, X2 represents the difference between the temperature measurement values of the two temperature sensors one minute before, and X3 represents the difference between the temperature measurement values of the two temperature sensors before two minutes.

The output variable is the highest temperature among the 27 points (t1 to t27) with respect to the measured values of the variables X1, X2, and X3. Therefore, these data have data on the temperature difference indicated by the measured values of the two temperature sensors S1 and S2 and the trends of the temperature changes of 27 points according to the temporal change of the temperature difference.

The TSK fuzzy theory as described above is applied using these tables. In other words, a fuzzy structure with the smallest U.C value is selected by performing a fuzzy two-part division for each variable and performing a fuzzy division by performing three division based on a variable having the smallest U.C value among them. The parameters of the preliminary part are obtained for the selected fuzzy structure, and the final line form to be obtained is constructed accordingly.

For convenience of explanation, it is assumed that the obtained final fuzzy structure is as follows. (The final selected fuzzy structure may vary depending on the experimental data, where the selected structure and the resulting values are not actually tested but are virtually set to represent the form of the final result.)

This equation is based on the assumption that an optimum structure is obtained in the fuzzy quadrant, and Y1 to Y4 are linear form in each region of the quadrant structure. When the output Y is calculated from the above fuzzy model,

g1 = - ( X1 + 6 - X1 - 8 ) / 14

g2 = - ( X1 + 18 - X1 - 29 ) / 11

W1 [1] = 0.5 (1 + g1)

W1 [2] = 0.5 (-g1-g2)

W1 [3] = 0.5 (1 + g2)

W2 [1] = 0.5 (1 - X2 - 2 - X2 - 16 ) / 14

W2 [2] = 1-W2 [1]

Y1 = W1 [1] Y1 + W1 [2] W2 [1] Y2 + W1 [2] W2 [

to be. Here, W represents the weight of the fuzzy inference applied by compensating for the extent to which each region contributes to the entire equation according to the formula of the general theory of TSK fuzzy. Y is a position in the refrigerating chamber where cold air is to be discharged for optimal temperature equilibrium as a final output, and the rotational speed of the rotating blades to which cool air is to be discharged toward this position is calculated by the microcomputer on the basis of the graph shown in FIG.

Hereinafter, as a second step, it is a step of controlling the rotary blades at an optimum rotation speed.

FIG. 8 is a control block diagram of the temperature control apparatus according to the present invention. FIG. The microcomputer 31 performs overall control of the refrigerator. The temperature sensor includes the S1 sensor 11 and the S2 sensor 12, and detects the temperature in the refrigerating chamber to provide data of the temperature change necessary for the fuzzy inference. The rotating blade position sensor 37 detects the rotating blades of the actual rotating blades according to the change of the position of the rotating blades, and provides data so as to control the accurate rotating speed. The F fan (33) and the R fan (34) are blower fans in the freezer compartment and blower fans in the refrigerating compartment, respectively. The microcomputer 31 controls the blowing fans 33 and 34 and the compressor 32 to control the operation of the entire refrigerator. The zero crossing detection circuit 38 will be described later.

FIG. 9 is a circuit diagram of a speed control device for implementing a speed control method of a rotary vane according to the present invention. The drive motor 41 includes an AC power supply voltage 47 And a transformer 49, a drive motor 41, a bridge circuit 46 and a transistor 48 that convert the voltage from the AC power supply voltage 47 into a small signal recognizable by the microcomputer 31 have.

The microcomputer 31 has a fuzzy inference unit 56 to calculate the equilibrium velocity in accordance with the temperature sensed by the temperature sensors S1 and S2 and to control the speed of the rotary vane accordingly.

The AC power supply voltage 47 supplies the AC voltage required to rotate the rotary vane 20. [ The voltage supplied by the AC power supply voltage 47 is a voltage for generating the maximum rotation speed in rotating the rotary vane 20 and has a sinusoidal waveform as shown in FIG. 10, The rotating speed of the rotating blades is adjusted by adjusting the effective value of the voltage actually applied to the driving motor 41 by cutting. The process is as follows.

The AC voltage from the AC power source 47 is converted into a pulse voltage that can be recognized by the microcomputer 31 by the transformer 49, the bridge circuit 46 and the transistor 48 performing the switching operation. That is, the output voltage of the transformer 49 has a magnitude of several volts. This voltage is full-wave rectified by the bridge circuit 46 and applied to the microcomputer 31 via the transistor 48 which performs the switching operation. The microcomputer 31 detects the time point when the voltage of the full-wave rectified voltage becomes zero voltage. The fuzzy inference unit 56 in the microcomputer 31 calculates the maximum value in the refrigerator compartment for rotating the rotary vane for the temperature equilibrium in the refrigerating compartment according to the above-mentioned formula of fuzzy inference according to the temperature measurement values from the respective temperature sensors 11 and 12 And outputs the temperature position. The balancing speed calculating unit 51 calculates a balancing speed at which the cool air is discharged at the highest temperature position deduced by the fuzzy inference unit 56 and the balancing voltage calculating unit 52 calculates a balancing speed at which the rotating blades 20 are rotated 20, respectively. The delay time calculating unit 53 calculates a delay time required to cut the AC power supply voltage 47 so as to supply the balanced voltage calculated by the balancing voltage calculating unit 52 to the drive motor 41 by controlling the phase of the AC power supply voltage 47 Calculate time based on zero point. The trigger pulse generator 54 generates a pulse having a predetermined magnitude in accordance with the delay time calculated by the delay time calculator 53. [

Figure 10 shows the waveform of the AC voltage. The process of cutting the waveform of FIG. 10 by a predetermined interval in order to generate the balanced voltage having the calculated effective value is performed in the waveform cut-out portion. The corrugated portion is composed of a light triac 43 and a triac 45. The triac 45 is connected in series with the AC power supply 47 and the drive motor 41 and receives the output from the optical triac 43 as a gate signal. The optical triac 43 generates a gate signal to the triac 45 by a trigger pulse from the trigger pulse generator 54. [

The trigger pulse generator 55 sets a section to cut the waveform from the detected zero voltage point and outputs a trigger signal to the optical triac 43 after a delay time corresponding to the section.

11 shows the pulse voltage waveform input from the zero voltage detection circuit 39 to the microcomputer 31. FIG. 12 shows the pulse voltage waveform from the waveform of FIG. 11 ) Trigger pulse generated from the trigger pulse generator 54 at a delayed time. Therefore, the AC voltage applied to the triac 45 is reduced from the zero voltage The effective value of the voltage supplied to the driving motor 41 is reduced and the rotation speed of the rotary vane is reduced. When the equilibrium velocity calculated by the equilibrium velocity calculator 51 is small, ), And when the equilibrium velocity is large, the cutoff period ( Becomes smaller and the rotation speed of the drive motor 41 becomes larger. In this way, the rotation speed of the rotary blades is adjusted. The equilibrium velocity calculator 51, the equilibrium voltage calculator 52, the delay time calculator 53 and the trigger pulse generator 54 are implemented using a microcomputer 31.

On the other hand, the rotating blade position sensor 37 outputs the angular position of the rotating blades for each time when the actual rotating blades are rotated, and transmits them to the microcomputer 31. The microcomputer 31 detects a change in the position of the rotating blades, calculates a speed at which the rotating blades actually rotate, and compares the speed with the equilibrium speed. If the actual rotational speed is equal to the equilibrium velocity, control is performed according to the equilibrium velocity, otherwise, the error is reflected to the equilibrium velocity. That is, when the actual rotation speed is faster than the target equilibrium speed So that the actual rotational speed is reduced by reducing the effective value of the power supply voltage further. When the actual rotational speed is slower than the target equilibrium speed Thereby making the actual rotation speed larger by increasing the effective value of the power supply voltage. This feedback process results in more accurate control at the equilibrium velocity.

The temperature control method and the temperature control device of the refrigerator as described above accurately deduce the temperature value of each part of the refrigerating chamber using only a small number of temperature sensors using the purge model and adjust the rotational speed of the rotating blades according to the deduced position So that the temperature in the refrigerating chamber can be kept uniform without being concentrated on a specific region.

Claims (10)

A method for controlling a temperature of a refrigerator having a rotary blade for rotationally driving the rotary blade to discharge cold air into a refrigerating chamber and a driving motor for rotating the rotary blade, the method comprising: constructing a fuzzy model for inferring a maximum temperature position in the refrigerator; Measuring a temperature of a predetermined portion of the refrigerator; Inputting the temperature measurement value to the fuzzy model to fuzzy inference the highest temperature position in the refrigerator; And controlling the rotational speed of the rotary vane so that the rotational speed of the rotary vane is balanced so that the cool air is discharged to the highest temperature position of the fog-inspired refrigerator. The method according to claim 1, wherein the step of constructing the fuzzy model comprises the steps of: preparing actual measurement data of a temperature change in a plurality of radial regions partitioned around the rotary vane, based on a temperature measurement value in the refrigerating chamber; Fuzzy partitioning based on actual data of the temperature change; Selecting an optimal structure among the divided structures of the fuzzy divided area; And calculating a line form deducing a maximum temperature position of the refrigerator based on the optimal structure. 3. The method of claim 1 or 2, wherein controlling the rotational speed of the rotary vane comprises: calculating the equilibrium velocity; Calculating a balanced voltage to cause the rotary vane to rotate at the equilibrium speed; And supplying the balanced voltage to the driving motor. 4. The method of claim 3, wherein the supplying of the balanced voltage comprises: detecting a zero point of a predetermined AC power supply voltage; Calculating a delay time to cut the AC power supply voltage based on the zero point so that the balanced voltage is generated; And cutting the AC power supply voltage from the zero point to the delay time. The method of claim 1 or 2, further comprising the steps of: detecting an actual rotation speed of the rotary vane; Calculating an error between the actual rotation speed and the equilibrium speed; And correcting the rotation speed of the rotary vane so that the calculated error is reflected. 1. A temperature control device for a refrigerator having a rotary blade for rotary driving to discharge cold air into a refrigerating chamber and a driving motor for rotating the rotary blades, the temperature control device comprising: a measuring part for measuring a temperature of a predetermined location in the refrigerating compartment; A fuzzy inference unit for fuzzy reasoning the maximum temperature position in the refrigerator using the temperature measurement value as an input variable; And a rotation speed controller for controlling the rotation speed of the rotary blades so as to have a balancing speed at which cool air is discharged at the highest temperature position deduced from the fuzzy inference unit. [7] The apparatus of claim 6, wherein the rotation speed control unit comprises: a balance speed calculation unit for calculating the balance speed; A balancing voltage calculating unit for calculating a balancing voltage for causing the rotating blades to rotate at the equilibrium speed; And a balanced voltage supply unit for supplying the balanced voltage to the driving motor. The plasma display apparatus according to claim 7, wherein the balanced voltage supply unit comprises: a zero voltage detection unit for detecting a zero point of a predetermined AC power supply voltage; A delay time calculating unit for calculating a delay time for cutting the AC power supply voltage based on the zero point so that the balanced voltage is generated; And a waveform cut-out unit for cutting the AC power supply voltage from the zero point to the delay time. The plasma display apparatus of claim 8, wherein the waveform cutout section comprises: a triac connected in series with the AC power supply voltage; And a trigger pulse generator for generating a trigger pulse for triggering the trigger at the delay time. 10. The automatic transmission according to any one of claims 6 to 9, further comprising: an actual speed detection unit for detecting an actual rotation speed of the rotary vane; and a speed error calculation unit for calculating an error between the actual rotation speed and the equilibrium speed ; Wherein the equilibrium velocity calculation unit calculates the equilibrium velocity by reflecting the error.