JPH07234002A - Air conditioner operation control method - Google Patents

Abstract

(57) [Abstract] [Purpose] Air that can achieve comfortable indoor temperature control by introducing the amount of change that correctly grasps the indoor temperature change state and performing control in accordance with the indoor temperature change. It is to provide an operation control method of a harmony machine. [Configuration] In an air conditioner that includes a hot water circulation circuit having a hot water valve and uses fuzzy reasoning to control the opening of the hot water valve, a fuzzy difference between the previous fuzzy calculation room temperature and the current fuzzy calculation room temperature Based on the indoor temperature change amount during calculation and the sum of short-term temperature change amount of the indoor temperature measured based on the previous fuzzy calculation room temperature at a predetermined interval between the last fuzzy calculation time and this fuzzy calculation time, The inference calculation is used to calculate the indoor temperature change state from the previous fuzzy calculation time to the current fuzzy calculation time, and the calculated indoor temperature change state and the temperature difference, which is the difference between the indoor temperature at the current fuzzy calculation and the set temperature. Based on and, the hot water valve control amount is calculated by fuzzy inference calculation.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention includes a heating heat exchanger connected to a hot water circulation circuit having a hot water valve, a cooling heat exchanger which is an evaporator connected to a refrigerant circuit, and a blower. The operation control method of the air conditioner equipped with the indoor unit
In particular, it relates to an air conditioner operation control method for adjusting the opening degree of the hot water valve of the hot water circulation circuit by using fuzzy reasoning.

[0002]

2. Description of the Related Art Conventionally, in an air conditioner equipped with a hot water circulation circuit for circulating hot water at least during heating operation,
Since the flow rate characteristic of the hot water valve of the hot water circulation circuit (flow rate characteristic with respect to the control amount) is not linear, the change amount of the hot water flow rate with respect to the change amount of the control amount is not constant, and the flow amount change amount with respect to the same control amount change is different However, since the amount of change in the room temperature Th is different, there is a problem that it is difficult to control the controlled object such as the room temperature Th quickly and with high accuracy. To solve this problem, the valve of the hot water valve is It is possible to change the method of control calculation depending on the position, but there was a problem that it became very complicated.

In order to solve this problem, there has been proposed a method for controlling a hot water valve for an air conditioner, which uses fuzzy reasoning for controlling the hot water valve. For example, the temperature difference between the set temperature and the room temperature and the room temperature change rate are detected, a table address is calculated by fuzzy inference calculation based on the detected temperature difference and the room temperature change rate, and based on the table address, This is a control method for obtaining the control amount of the hot water valve from a hot water valve characteristic table in which the hot water valve control amount for the table address is set in advance.

An example of the control method will be described in detail with reference to FIGS. 10 to 12. The indoor temperature Th is fetched as data every time a predetermined sampling time (for example, 2 minutes) elapses, and a preset temperature Ts is set. Current room temperature Thn
The temperature difference with ow fp (t) = ΔTh = Ts−Thnow is calculated, and based on the calculated temperature difference fp (t), the input membership value is calculated by the following membership function (see FIG. 11). Find temperature difference fuzzy data. NB: The current indoor temperature Thnow is higher than the set temperature Ts.
{Fp (t) =-ΔTh2 has a maximum value of 1, fp (t) =-ΔTh1
The minimum value is 0} NM: The current indoor temperature Thnow is slightly higher than the set temperature Ts. {Fp (t) =-ΔTh1 has a maximum value of 1, fp (t) =-Δ
When Th2 and fp (t) = 0, the minimum value is 0} ZO: Just right. {Fp (t) = 0 with a maximum value of 1, fp
(T) = ± ΔTh1 and minimum value 0} PM: The current room temperature Thnow is slightly lower than the set temperature Ts. {Fp (t) = ΔTh1 has a maximum value of 1, fp (t) = ΔTh2
And fp (t) = 0 and the minimum value 0} PB: The current room temperature Thnow is lower than the set temperature Ts. {Maximum value 1 when fp (t) = ΔTh2, minimum value 0 when fp (t) = ΔTh1} where ΔTh1 and ΔTh2 are predetermined temperature differences, for example, Δ
Th1 = 2.1 degrees and ΔTh2 = 4.2 degrees.

The current indoor temperature Thnow detected this time
And the previous room temperature T detected before the current room temperature Thnow
Room temperature change rate fd per unit time as a difference from hold
(T) = ΔTd = ΔTh / Δt = Thnow-Thold is calculated, and based on the calculated room temperature change rate fd (t), the input membership value is calculated by the following membership function (see FIG. 11) Obtain temperature change rate fuzzy data. N: The room temperature Th is changing in the negative direction. {Fd
(T) =-ΔTd1 has a maximum value of 1, fd (t) = 0 has a minimum value of 0} ZO: No change in room temperature Th. {Fd (t) = 0 has a maximum value of 1, fd (t) = ± ΔTd1 has a minimum value of 0} P: The room temperature Th changes in the positive direction. {Fd
(T) = ΔTd1 has a maximum value of 1 and fd (t) = 0 has a minimum value of 0} where ΔTd1 is a predetermined room temperature change rate, for example, ΔTd1 = 2.1 degrees.

From the temperature difference fuzzy data and the room temperature change rate fuzzy data, the output membership value is obtained by referring to the control rule shown as a matrix in FIG. Here, the output membership function W is NB (small hot water valve opening), NM (slightly small hot water valve opening), ZO (medium hot water valve opening), PM (slightly hot water valve opening), PB ( 5 fuzzy variables (large opening of hot water valve) are defined. The control rules are as follows. R1: Temperature difference fp (t) = NB (current room temperature Thnow is higher than set temperature Ts), and room temperature change rate fd (t) = N
If the room temperature Th changes in the negative direction, the output membership function W = NM (the hot water valve opening is slightly small). R2: Temperature difference fp (t) = NM (current room temperature Thnow is slightly higher than set temperature Ts), room temperature change rate fd (t)
= N (the room temperature Th changes in the negative direction), the output membership function W = ZO (during opening of the hot water valve).
Similarly, 15 control rules up to R15 are shown below. As the output membership value (grade value), the smaller one of the two input membership values fp (t) and fd (t) is selected. Use the grade value of (min. Calculation).

The above control rule is referred to for all the fuzzy data, and the max. Calculation is performed based on the output membership value obtained by the min. Calculation from the temperature difference fuzzy data and the room temperature change rate fuzzy data. The one-point calculation (inverse fuzzy conversion) is performed based on the combined output membership value. The one-point calculation formula is the center-of-gravity calculation formula f _w = ∫f (x)
・ By transforming xdx / ∫f (x) dx, G = (α ・ a + β ・ b + γ ・ c + δ ・ d + ε ・ e) / (a + b + c + d + e) is calculated. It becomes the control amount of the step position. However, a: N
B output membership composite value, b: NM output membership composite value, c: ZO output membership composite value, d:
PM output membership combined value, e: PB output membership combined value Further, α, β, γ, δ, ε are weighting coefficients.

The sum of the calculated step position control amount G to the previous step position (current actual step position) Go is the address of the hot water valve this time (target step position Gs).
), The target number of steps S corresponding to the target step position Gs is calculated from the prepared hot water valve characteristic table.
And the actual step number So corresponding to the previous step position Go (actual step position at the present time since the hot water valve has not been driven since the last time), the number of drive steps (control amount) for driving the stepping motor of the hot water valve this time. ) Sm (Sm = S-So), the control signal corresponding to the driving step number Sm is output to the stepping motor to drive the stepping motor to the target step position Gs, and the opening degree of the hot water valve is adjusted.

[0009]

However, in the above-mentioned conventional operation control method for the air conditioner, there is a limit in the temperature resolution of the indoor temperature detector such as the thermistor (for example, 0.35 ° C. in the thermistor). Since it is impossible to detect the temperature difference below the detection temperature resolution,
If the change in the room temperature Th from the previous fuzzy calculation is small, it is difficult to correctly grasp the state of the change in the room temperature Th only by the temperature difference, and there is a possibility that comfortable room temperature control cannot be obtained. There was a problem. Also, in FIG.
As shown in, the change state of the indoor temperature Th from the last fuzzy calculation time to the present fuzzy calculation time is not constant, and it is necessary to determine the opening degree of the hot water valve according to the change state.
For example, it is necessary to make the control amount different between a case where it greatly rises and then falls (see FIG. 8A) and a case where it continues to rise gradually (see FIG. 8B), that is, a case where it greatly rises and then falls (see FIG. In the case where the temperature continues to rise more slowly (in FIG. 8B) (in FIG. 8B), it is necessary to increase the opening degree of the hot water valve. However, as described above, when the control amount is fuzzy-calculated based only on the previous indoor temperature Thold and the current indoor temperature Thnow, a large increase and then a decrease (FIG. 13A) and a moderate continuous increase (FIG. 13D) There is a problem that it is difficult to obtain control amounts corresponding to different indoor temperature change states because the control amounts calculated by and become equal values.

An object of the present invention is to introduce a change amount that accurately grasps the state of indoor temperature change, thereby making it possible to perform control in accordance with the indoor temperature change and to obtain comfortable indoor temperature control. It is to provide an operation control method of a harmony machine.

[0011]

In order to achieve the above object, the operation control method for an air conditioner of the present invention comprises a hot water circulation circuit having at least a hot water valve, and fuzzy depending on the room temperature during operation of the hot water circulation circuit. In an air conditioner that controls the opening of the hot water valve using inference, the amount of change in room temperature during fuzzy calculation, which is the difference between the room temperature during the previous fuzzy calculation and the room temperature during this fuzzy calculation, and the time from the previous fuzzy calculation Based on the sum of the short-term temperature change amount of the indoor temperature measured with reference to the previous fuzzy calculation indoor temperature at a predetermined interval before fuzzy calculation and the temperature difference that is the difference between the current fuzzy calculation indoor temperature and the set temperature. Then, the hot water valve control amount is calculated by fuzzy inference calculation. Also, based on the indoor temperature change amount during fuzzy calculation and the sum of the short-term temperature change amount of the indoor temperature, the fuzzy inference calculation calculates the indoor temperature change state from the previous fuzzy calculation time to the current fuzzy calculation time. The hot water valve control amount is calculated by fuzzy inference calculation based on the calculated room temperature change state and the calculated temperature difference.

[0012]

[Function] The process of changing the indoor temperature is considered by calculating the hot water valve control amount by the fuzzy inference calculation based on the indoor temperature change amount during the fuzzy calculation, the short-term temperature change amount of the indoor temperature, and the temperature difference. It is possible to control the opening degree of the warm water valve, to control the opening degree of the warm water valve according to the change of the indoor temperature, and to perform comfortable operation control of the air conditioner. Also, based on the indoor temperature change amount during fuzzy calculation and the sum of the short-term temperature change amount of the indoor temperature, the fuzzy inference calculation calculates the indoor temperature change state from the previous fuzzy calculation time to the current fuzzy calculation time. By controlling the hot water valve control amount by fuzzy inference calculation based on the calculated indoor temperature change state and the temperature difference, the hot water valve opening control is performed with due consideration of the process in which the indoor temperature changes. It can be performed.

[0013]

Embodiments of the present invention will be described with reference to the drawings.
In FIG. 9, a heat exchanger for cooling, that is, an evaporator 2 and a heat exchanger 3 for heating are arranged in an indoor unit 1 in order from an upstream side in an air flow path, and an indoor fan 4 is installed at a downstream position thereof. The drain pan 5 is installed below the evaporator 2 and the heat exchanger 3 for heating. The evaporator 2, the compressor 7 arranged in the outdoor unit 6, the condenser 8 which is air-cooled by the outdoor fan 11, and the capillary tube (expansion device) 9 are connected by the refrigerant pipe 10 in the refrigerant circuit to form a refrigeration cycle. The refrigerant that is configured and compressed by the compressor 7 is stored in the condenser 8
After being liquefied by, and adiabatically expanded by the capillary tube 9, it is evaporated by the evaporator 2 and exchanges heat with the air around the evaporator 2.
The heating heat exchanger 3 is connected to a water heating heat exchanger 13 installed in the hot water heat source device 12 via a circulation pump 14 and a flow control valve (hot water valve) 15 with a hot water pipe 16 to perform hot water heating. A circuit is formed. The flow rate control valve 15 is driven by a stepping motor and the opening degree is determined by the number of steps,
It is connected to the inlet side of the heating heat exchanger 3.

The control device 17 controls the indoor temperature Th detected by the indoor temperature detecting device 18, such as an indoor temperature sensor, and the setting device 19
The set temperature Ts set by is input and the indoor fan 4
It outputs a control signal to the compressor 7 and the outdoor fan 11 of the cooling circuit, and the hot water heat source device 12, the circulation pump 14 and the hot water valve 15 of the heating circuit. During the cooling operation, the indoor fan 4, the compressor 7 and the outdoor Fan 11 is driven,
The hot water heat source device 12, the circulation pump 14, and the hot water valve 15 are turned off. Further, during the dehumidifying operation, the indoor fan 4, the compressor 7 in the cooling circuit, the outdoor fan 11, the hot water heat source device 12 in the heating circuit 12, the circulation pump 14, and the hot water valve 15 are turned on.
Further, during the heating operation, the indoor fan 4, the hot water heat source device 12 and the circulation pump 14 in the heating circuit are operated, the opening degree of the hot water valve 15 is adjusted, and the compressor 7 in the cooling circuit and the outdoor fan.
11 is turned off.

In the present invention, an example of fuzzy reasoning adopted for controlling the opening degree of the hot water valve 15 of the heating circuit will be described with reference to the algorithm of FIG. The timing of performing the fuzzy calculation is measured by a calculation timer in the control device 17, and the fuzzy calculation is performed every time a predetermined calculation time Hc (for example, 3 minutes) elapses. The room temperature Th from the time when the fuzzy calculation is performed. The sampling time in the control device 17 is measured by a sampling timer, and the calculation time Hc (3 minutes) is divided into predetermined N times (eg, 6 times) to determine a sampling time Hs (eg, 30 times). The current indoor temperature Thnow is taken as data every time (seconds), and the short-term temperature change amount ΔT (ΔT = T) is calculated as the difference from the previous calculation indoor temperature Thold at the time of the previous fuzzy calculation.
Hnow-Thold) is calculated N times (6 times), and ΔT ₁ , ..., From the calculated first time to N (6) th time,
ΔT _N is sequentially added to calculate the short-term temperature change amount sum ΣΔT (see FIG. 2).

The calculated short-term temperature change amount sum ΣΔT is applied to FIG. 3, and the input membership value is obtained by the membership function of the short-term temperature change amount sum ΣΔT to obtain short-term temperature change amount sum fuzzy data. The membership function of the short-term total temperature change amount ΣΔT is as follows. NB: The state in which the room temperature Th is lower than the previous fuzzy calculation is large. (Maximum 1.0 _{ΣΔT = -δ 3, ΣΔT = -δ} 2
The minimum value is 0) NM: The room temperature Th is lower than the previous fuzzy calculation. (ΣΔT = −δ ₂ has a maximum value of 1.0, ΣΔT = −
The minimum value of δ ₁ and −δ ₃ is 0) NS: The state in which the room temperature Th is lower than the previous fuzzy calculation is small. (ΣΔT = -δ ₁ , maximum 1.0, ΣΔT =-
minimum value δ _2, 0 0) ZO: just right. (Maximum value 1.0 when ΣΔT = 0, ΣΔ
The minimum value is 0 when T = ± δ ₁ ) PS: The room temperature Th is smaller than the previous fuzzy calculation. (ΣΔT = + δ ₁ has a maximum value of 1.0, ΣΔT = 0, +
δ ₂ is the minimum value 0) PM: The room temperature Th is higher than the previous fuzzy calculation. (ΣΔT = + δ ₂ is maximum 1.0, ΣΔT = +
The minimum value is 0 for δ ₁ and + δ ₃ ) PB: The room temperature Th is higher than the previous fuzzy calculation. (ΣΔT = + δ ₃ has a maximum value of 1.0, ΣΔT = + δ ₂
In addition, δ ₁ , δ ₂ , and δ ₃ are predetermined short-term temperature change sum total values, for example, δ ₁ = 0.35 degrees, δ ₂ = 0.70 degrees, δ
₃ = 1.05 degrees.

Calculation time Hc since the last fuzzy calculation
When (3 minutes) elapses, fuzzy calculation is started again, but the current calculation indoor temperature Thf (same as the sixth current indoor temperature Thnow) at that start time is calculated, and the previous calculation indoor temperature Thold during the previous fuzzy calculation is calculated. The difference between the fuzzy calculation and the room temperature change ΔTf (ΔTf = Thf−Thold = Δ
T _NLAST ) is calculated (ΔTf = ΔT _NLAST = Δ
T ₆ ). Next, the amount of room temperature change ΔTf during fuzzy calculation
By applying (ΔTf = ΔT _NLAST = ΔT ₆ ) to FIG. 4, the input membership value is obtained by the membership function of the room temperature change amount ΔTf during fuzzy calculation, and the room temperature change amount fuzzy data during fuzzy calculation is obtained. The membership function of the indoor temperature change amount ΔTf during the fuzzy calculation is as follows. NB: The state in which the indoor temperature Th is lower than that in the previous fuzzy calculation has passed. (At ΔTf = -t ₃ , the maximum value is 1.0, and ΔTf =-
At t ₂ , the minimum value is 0) NM: The room temperature Th has been slightly lower than the previous fuzzy calculation. (Maximum value of 1.0 in the ΔTf = -t _2, ΔTf =
-T _1, the minimum value -t ₃ 0) NS: room temperature Th is slightly lower state elapsed from the previous fuzzy calculation. (Maximum value of 1.0 in the ΔTf = -t _1, ΔTf =
-T _2, the minimum value 0 at 0) ZO: indoor temperature Th is not changed from the previous fuzzy calculation. (The maximum value is 1.0 when ΔTf = 0 and the minimum value is 0 when ΔTf = ± t ₁ ) PS: The room temperature Th has been slightly higher than that at the previous fuzzy calculation. (At ΔTf = + t ₁ , the maximum value is 1.0, ΔTf =
0, + t ₂ is the minimum value 0) PM: The room temperature Th is slightly higher than the previous fuzzy calculation. (At ΔTf = + t ₂ , the maximum value is 1.0, ΔTf =
The minimum value is 0 at + t ₁ and + t ₃ ) PB: The room temperature Th is higher than the previous fuzzy calculation. (The maximum value is 1.0 when ΔTf = + t ₃ , ΔTf = + t
₂ is the minimum value of 0) Note that t ₁ , t ₂ , and t ₃ are predetermined indoor air temperature change amounts during fuzzy calculation, for example, t ₁ = 0.7 degrees, t ₂
= 1.4 degrees and t ₃ = 2.1 degrees.

The fuzzy data of the total short-term temperature change amount ΣΔT and the fuzzy data of the room temperature change amount ΔTf during the fuzzy calculation are applied to the inference rule shown in the table of FIG. 5, and the calculation time Hc (3 minutes) from the previous fuzzy calculation is applied. After the lapse of time, the change state of the room temperature Th until the present fuzzy calculation is inferred, min.-max. Calculation is performed, and fuzzy data of the room temperature change state .DELTA.Tpr between fuzzy calculations is obtained. The fuzzy variables of the indoor temperature change state ΔTpr during the fuzzy calculation are as follows: NB: The indoor temperature Th after the previous fuzzy calculation has a tendency to continue to decrease. NM: The room temperature Th has continued to decrease since the previous fuzzy calculation. NS: The room temperature Th after the last fuzzy calculation is low and the tendency is not to decrease. ZO: No change in the room temperature Th since the last fuzzy calculation. PS: The indoor temperature Th after the last fuzzy calculation is small and the tendency that the indoor temperature Th continues to rise is small. PM: The room temperature Th has continued to rise since the previous fuzzy calculation. PB: The room temperature Th has continued to rise since the previous fuzzy calculation. There are seven types. The inference rule is R1: short-term temperature change sum ΣΔT = NB (indoor temperature Th
Is lower than that at the previous fuzzy calculation), and the indoor temperature change amount during fuzzy calculation ΔTf = NB (indoor temperature Th
Is lower than that at the time of the previous fuzzy calculation), the room temperature change state ΔTpr is considered to be NB (the indoor temperature Th after the time of the previous fuzzy calculation tends to continue to decrease). R2: Sum of short-term temperature changes ΣΔT = NM (indoor temperature Th
Is lower than that at the previous fuzzy calculation, and the indoor temperature change amount during fuzzy calculation ΔTf = NB (indoor temperature Th
Is lower than that at the time of the previous fuzzy calculation), the room temperature change state ΔTpr is regarded as NM (the room temperature Th after the time of the previous fuzzy calculation tends to continue to decrease). Similarly, 49 inference rules up to R49 are defined.

A temperature difference ΔTh (ΔTh = Ts−Thf), which is a difference between a preset set temperature Ts and a calculation indoor temperature Thf, that is, a current indoor temperature Thnow at the time of calculation is calculated. The calculated temperature difference ΔTh is applied to FIG. 6 to find the input membership value by the membership function of the temperature difference ΔTh to obtain the temperature difference fuzzy data. The membership function of the temperature difference ΔTh is as follows. N: The room temperature Thf = Thnow at the time of calculation is slightly higher than the set temperature Ts. (When ΔTh = -Δ ₁ , the maximum value is 1.0, ΔTh = 0
Minimum value 0) ZO: Just right. (When ΔTh = 0, the maximum value is 1.0, ΔT
When h = ± Δ ₁ , the minimum value is 0) PS: The room temperature Thf during calculation is slightly lower than the set temperature Ts. (The maximum value is 1.0 at ΔTh = + Δ ₁ , ΔTh = 0, + Δ
₂ is the minimum value 0) PM: The room temperature Thf at the time of calculation is slightly lower than the set temperature Ts. (At ΔTh = + Δ ₂ , the maximum value is 1.0, ΔTh = + Δ ₁ ,
The minimum value is 0 at + Δ ₃ ) PB: The indoor temperature Thf during calculation is lower than the set temperature Ts.
(ΔTh = + Δ ₃ maximum 1.0,? Th = + minimum value 0 in delta _{2) Note, Δ 1, Δ 2, Δ} 3 is the value of the predetermined temperature difference, for example, delta ₁ = 2.1 °, delta ₂ = 4.2 degrees, Δ ₃ = 6.3
I have a degree.

With respect to all the fuzzy data of the room temperature change state ΔTpr and the fuzzy data of the temperature difference ΔTh between the calculated fuzzy calculations, the output membership value is obtained by referring to the control rule shown in FIG. The output membership function is defined by the following seven types of fuzzy variables. NB: The opening degree of the hot water valve is small. NM: Hot water valve opening is a little small. NS: Hot water valve opening is slightly small. ZO: The hot water valve is open. PS: The hot water valve opening is slightly large. PM: The hot water valve opening is slightly larger. PB: The opening degree of the hot water valve is large. The control rules are as follows. R1: The indoor temperature change state ΔTpr = NB (the indoor temperature Th after the previous fuzzy calculation has a large tendency to continue decreasing), and the temperature difference ΔTh = N (the indoor temperature Thf at the time of calculation, that is, the current indoor temperature Thnow is lower than the set temperature Ts) A little higher)
The output membership function is PM (the hot water valve opening is slightly larger). In other words, the state where the indoor temperature Th after the previous fuzzy calculation is lower than that during the previous fuzzy calculation has passed, and the current indoor temperature Thnow is slightly higher than the set temperature Ts (+2.1
(° C), the opening degree of the hot water valve 15 is slightly increased. R2: When the indoor temperature change state ΔTpr = NB (the indoor temperature Th after the previous fuzzy calculation has continued to decrease greatly) and the temperature difference ΔTh = ZO (just right), the output membership function is PB (hot water valve). It opens and becomes large). In other words, when the room temperature Th after the previous fuzzy calculation is lower than that during the previous fuzzy calculation and the current room temperature Thnow is equal to the set temperature Ts, the opening degree of the hot water valve 15 is increased. Similarly, 35 control rules up to R35 are shown below (see FIG. 7). As the output membership value (grade value), the indoor membership temperature change state ΔTpr and the input membership value (grade value) of the temperature difference ΔTh are shown. ) And adopt the smaller grade value (min. Calculation).
For example, in the indoor temperature change state ΔTpr = NB shown in R3,
In the state where the temperature difference ΔTh = PS, the grade value of the fuzzy variable NB for the indoor temperature change state ΔTpr and the grade value of the fuzzy variable PS for the temperature difference ΔTh are compared, and the smaller value is adopted.

The above control rule is referred to for all the fuzzy data, and the max. Calculation is performed based on the output membership value obtained by the min. Calculation from the fuzzy data of the room temperature change state ΔTpr and the fuzzy data of the temperature difference ΔTh. Then, the obtained output membership composite value is used to perform a one-point calculation (inverse fuzzy conversion). The one-point arithmetic expression is obtained by modifying the centroid arithmetic expression f _w = ∫f (x) · xdx / ∫f (x) dx, and G = (a · A + b · B + c · C + d · D + e · E + f · F + h · H) / It is calculated by (A + B + C + D + E + F + G), and this calculated G is the control amount of the step position of the step motor that drives the hot water valve. However, A: NB output membership composite value B: NM output membership composite value C: NS output membership composite value D: ZO output membership composite value E: PS output membership composite value F: PM output membership composite value H: PB output membership composite value In addition, a, b, c, d, e, f, and g are weighting coefficients (for example, a = -6, b = -4, c = -2, d = 0, e =
+2, f = + 4, g = + 6). The step position is set so that the flow rate-step position characteristic of the hot water valve is linear, and the number of steps of the stepping motor corresponding to each step position is experimentally determined in advance according to the flow characteristic of the hot water valve. It has established.

The calculated step position control amount G is added to the previous step position (current actual step position) Go to obtain the address of the hot water valve this time (target step position Gs).
), The target number of steps S corresponding to the target step position Gs is calculated from the prepared hot water valve characteristic table.
And the actual step number So corresponding to the previous step position Go (actual step position at the present time since the hot water valve has not been driven since the last time), the number of drive steps (control amount) for driving the stepping motor of the hot water valve this time. ) Sm (Sm = S-So), the control signal corresponding to the driving step number Sm is output to the stepping motor to drive the stepping motor to the target step position Gs, and the opening degree of the hot water valve is adjusted.

With the above structure, in the room temperature change shown in FIGS. 8A and 8B, the change state of the room temperature Th from the time of fuzzy calculation to the time of the next fuzzy calculation (in FIG.
) Can be distinguished, and the fuzzy calculation is performed by taking the changed state into consideration, so that the hot water valve control can be performed in accordance with the trend of the room temperature Th. In addition, the previous calculation indoor temperature Thold during the previous fuzzy calculation and the current calculation indoor temperature T
When hf (current indoor temperature Thnow) is equal to each other, but the change state (elapsed) is different (in FIG. 8A and B or A and B), the respective indoor temperatures Th
The control amount G is calculated according to the changing state of, and the temperature can be promptly converged to the set temperature Ts.

As an example, the case of FIG. 8B and FIG. 8B will be described. Each of the previous calculation indoor temperature Thold = 27.75.
℃, room temperature Thf at this time calculation (current room temperature Thnow) =
Since 28.1 ° C and the set temperature Ts = 26 ° C, the temperature difference ΔTh
= −2.1 ° C., and the temperature difference fuzzy data are, N = 1.0 for both, and 0 for others. The amount of change in room temperature during fuzzy calculation ΔTf = Thf−Thold = + 0.35 ° C., and the fuzzy data thereof are both ZO = PS = 0.5 and 0 otherwise.

Next, for and, fuzzy data of the short-term temperature variation summation ΣΔT are obtained. In the case of: When the fuzzy data of the short-term total temperature change amount ΣΔT is obtained with the short-term total temperature change amount ΣΔT = + 1.05 ° C,
From FIG. 3, PB = 1.0, and the others are 0. Next, applying the inference rule of FIG. 5 and performing min. Calculation, NB = 0 NM = 0 NS = 0 NS = 0 NM = 0
NB = 0 NB = 0 NM = 0 NM = 0 NS = 0 ZO = 0 NS = 0
NB = 0 NB = 0 ZO = 0 NS = 0 NS = 0 ZO = 0 ZO = 0
NM = 0 NM = 0 PM = 0 PS = 0 ZO = 0 ZO = 0 ZO = 0
NS = 0 NM = 0 PM = 0 PM = 0 ZO = 0 ZO = 0 PS = 0
PS = 0 ZO = 0 PB = 0 PB = 0 PS = 0 ZO = 0 PS = 0
PM = 0 PM = 0 PB = 0 PB = 0 PM = 0 PS = 0.5 PS = 0.5
PM = 0 PB = 0 When this is calculated max., PS = 0.5 and others become 0. Next, when the rule of FIG. 7 is applied and min. Calculation is performed, the temperature difference fuzzy data is N = 1.0 and the others are 0. Therefore, R1: PM = 0, R2: PB = 0, R3: PB =
0, R4: PB = 0 R5: PB = 0, R6: PS = 0, R7: PM =
0, R8: PM = 0 R9: PB = 0, R10: PB = 0, R11: ZO =
0, R12: PS = 0 R13: PS = 0, R14: PM = 0, R15: PM =
0, R16: NS = 0, R17: ZO = 0, R18: PS = 0, R19: PS =
0, R20: PM = 0 R21: NM = 0.5, R22: NS = 0, R23: ZO =
0, R24: PS = 0 R25: PS = 0, R26: NB = 0, R27: NM =
0, R28: NM = 0 R29: ZO = 0, R30: ZO = 0, R31: NB =
0, R32: NB = 0 R33: NM = 0, R34: NS = 0, R35: NS = 0 When this is calculated max, NM = 0.5 and the others are 0. When the one-point arithmetic operation is performed by the above arithmetic expression, the control amount G is: G = (-6 * A-4 * B-2 * C + 0 * D + 2 * E + 4 * F + 6 * H) / (A + B + C + D + E + F + H) = (-6・ 0-4 ・ 0.5 -2 + 0 + 0 ・ 0 + 2 ・ 0 + 4 ・ 0 + 6.0) / (0 + 0.5 + 0 + 0 + 0 + 0 + 0) = (-2.0) / (0.5) = -4.0.

In the case of: Short-term temperature change sum ΣΔT = +
When the fuzzy data of the total short-term temperature change amount ΣΔT is obtained at 0.70 ° C., PM = 1.0 from FIG. Similar to the above case, the inference rule of FIG. 5 is applied and min.−
When max. is calculated, ZO = PS = 0.5, and others become 0. Next, when the rule of FIG. 7 is applied and min.-max. Calculation is performed, the temperature difference fuzzy data is N = 1.0, and the others are 0.
S = NM = 0.5 and others are 0.
G = -3.0. Therefore, the operation amount for closing the hot water valve 15 is slightly larger in the case of than in the case of.

[0027]

Since the present invention is constructed as described above, it has the following effects. By calculating the hot water valve control amount by fuzzy reasoning calculation based on the indoor temperature change amount during fuzzy calculation, the short-term temperature change amount of the indoor temperature, and the temperature difference, the hot water valve is considered in consideration of the process in which the indoor temperature changes. The degree of opening can be controlled, the degree of opening of the hot water valve can be controlled according to the change in the room temperature, and comfortable operation control of the air conditioner can be performed. Also, based on the indoor temperature change amount during fuzzy calculation and the sum of the short-term temperature change amount of the indoor temperature, the fuzzy inference calculation calculates the indoor temperature change state from the previous fuzzy calculation time to the current fuzzy calculation time. By controlling the hot water valve control amount by fuzzy inference calculation based on the calculated indoor temperature change state and the temperature difference, the hot water valve opening control is performed with due consideration of the process in which the indoor temperature changes. It can be performed.

[Brief description of drawings]

FIG. 1 is an algorithm for heating operation control according to the present invention.

FIG. 2 is an explanatory diagram for obtaining a sum of short-term temperature change amounts according to the present invention.

FIG. 3 is a membership function of a fuzzy variable with respect to a total sum of short-term temperature changes according to the present invention.

FIG. 4 is a membership function of a fuzzy variable with respect to an indoor temperature change amount during fuzzy calculation according to the present invention.

FIG. 5 is a diagram showing an inference rule for an indoor temperature change state based on a sum of short-term temperature changes and a room temperature change amount during fuzzy calculation according to the present invention.

FIG. 6 is a membership function of a fuzzy variable with respect to a temperature difference according to the present invention.

FIG. 7 is a control rule based on an indoor temperature change state and a temperature difference according to the present invention.

FIG. 8 is a temperature curve showing an example of room temperature change.

FIG. 9 is a schematic configuration diagram showing an example of an air conditioner to which the present invention is applied.

FIG. 10 is a fuzzy variable membership function for a conventional temperature difference.

FIG. 11 is a conventional fuzzy variable control rule for an indoor temperature change rate.

FIG. 12 is a control rule based on a conventional temperature difference and an indoor temperature change rate.

[Explanation of symbols]

1 Indoor unit, 2 Cooling heat exchanger (evaporator), 3
Heat exchanger for heating 4 Indoor fan, 5 drain pan, 6 outdoor unit,
7 Compressor 8 Condenser, 9 Capillary tube (expansion device), 10
Refrigerant piping 11 Outdoor fan, 12 Hot water heat source device, 13 Water heating heat exchanger, 14 Circulation pump 15 Flow control valve (hot water valve), 16 Hot water piping, 17 Control device 18 Indoor temperature detection device, 19 Setting device

Claims (2)

[Claims] 1. An air conditioner that includes a hot water circulation circuit having at least a hot water valve, and controls the opening of the hot water valve using fuzzy reasoning according to the room temperature during operation of the hot water circulation circuit. And the amount of room temperature change during fuzzy calculation, which is the difference between the room temperature at the time of fuzzy calculation and the indoor temperature measured at the predetermined interval between the time of the previous fuzzy calculation and the time of this fuzzy calculation, based on the room temperature at the previous fuzzy calculation. The operation of the air conditioner characterized by calculating the hot water valve control amount by fuzzy inference calculation based on the sum of the short-term temperature change amount and the temperature difference which is the difference between the indoor temperature and the set temperature during the fuzzy calculation this time. Control method. 2. The indoor temperature change state from the previous fuzzy calculation time to the current fuzzy calculation time by fuzzy inference calculation based on the indoor temperature change amount during fuzzy calculation and the sum of short-term temperature change amount of the indoor temperature. 2. The operation control method for an air conditioner according to claim 1, wherein the hot water valve control amount is calculated by fuzzy inference calculation based on the calculated indoor temperature change state and the calculated temperature difference.