GB2602901A

GB2602901A - Air-conditioning control device

Info

Publication number: GB2602901A
Application number: GB2203551.3A
Authority: GB
Inventors: Tanaka Ryuta; Mori Hiroyuki; Motodani Mio
Original assignee: Mitsubishi Electric Corp
Current assignee: Mitsubishi Electric Corp
Priority date: 2019-12-06
Filing date: 2019-12-06
Publication date: 2022-07-20
Anticipated expiration: 2039-12-06
Also published as: GB202203551D0; JP7224494B2; GB2602901B; JPWO2021111617A1; WO2021111617A1

Abstract

This air-conditioning control device comprises: an information acquisition unit that acquires invariant conditions, variable conditions, and sensor data; a model generation unit that generates a CFD model of a space to be air-conditioned on the basis of the invariant conditions; a calculation condition generation unit that generates calculation conditions for CFD simulation on the basis of the variable conditions and the sensor data; a CFD analysis unit that performs CFD simulation using the CFD model and the calculation conditions; a result extraction unit that extracts the simulation result of a first target position in the space to be air-conditioned; a correction method selection unit that selects a correction method to assess the state of an air conditioner on the basis of the sensor data or operational conditions and obtain a correction amount for the calculation conditions; a correction execution unit that obtains the amount of correction for the calculation conditions on the basis of the simulation result of the first target position, the sensor data at the same position as the first target position, and the selected correction method; and a control command determination unit that generates a control command for the air conditioner on the basis of the simulation result of the first position using the corrected calculation conditions.

Description

DESCRIPTION Title of Invention

AIR-CONDITIONING CONTROL DEVICE

Technical Field

[0001] The present disclosure relates to an air-conditioning control device that performs control using computational fluid dynamics (CFD) simulation.

Background Art

[0002] In general, air-conditioning apparatuses are provided with one or more temperature sensors to monitor temperatures. Each temperature sensor measures the temperature of air passing through the inside of an air-conditioning apparatus or other temperature. A sensor temperature that is measured by the temperature sensor is used as a control target to be controlled by the air-conditioning apparatus. That is, the air-conditioning apparatus controls a room temperature by bringing the sensor temperature closer to a control target value, such as a set temperature.

[0003] In an air-conditioning apparatus such as a spot cooler that needs to control the temperature of an air outlet, a desired temperature can be obtained by directly controlling the sensor temperature of a temperature sensor provided at the air outlet. [0004] However, in a case of an air-conditioning apparatus that controls the temperature of an entire target space, such as an indoor space, it is difficult to control the entire target space to a desired temperature by using a sensor temperature as it is as a control target because a temperature sensor measures only the temperature of a local area at which the temperature sensor is provided. For this reason, many methods using mathematical techniques have been proposed to estimate the temperature of the target space by using the sensor temperature.

[0005] In the past, various restrictions were present, such as a cost constraint like the price of a temperature sensor, a restriction on a method of communicating with a temperature sensor, and a restriction on the performance of a microcomputer installed in an air-conditioning apparatus. Consequently, a small number of temperature sensors and a simple estimated equation, which was derived from experimental data based on the sensor temperatures measured by these temperature sensors, were used to obtain an estimate value such as an average temperature of the target space, and the estimate value was used as a target to be controlled.

[0006] However, in the above method, the estimate value, such as an average temperature of an target space, can be obtained but a temperature distribution in the target space cannot be obtained. In addition, an appropriate estimate value may not be obtained in a condition different from the experimental condition in which the estimated equation was derived.

[0007] Recently, however, the cost of such sensors is lowered, and various and faster communication methods become available. In addition, the performance of microcomputers are improved and various Internet of Things (loT) technologies have been developed. Therefore, the abovementioned problems have been solved in recent years.

[0008] In a system described in Patent Literature 1, for example, a plurality of sensors are installed in a target space to directly measure the temperature, humidity, air flow and other data in the target space. Furthermore, in this system, by using sensor data obtained by these sensors, a computational fluid dynamics (CFD) simulation is performed to predict a temperature distribution and an airflow distribution in the target space. In this system, air-conditioning in the target space is performed based on these distributions.

[0009] However, when only sensor data is used as described above, a divergence between an indoor temperature obtained by the CFD simulation and the actual temperature may be generated because of measurement error of the sensors. Because a CFD simulation is performed by using sensor data as it is in a method of the system described in Patent Literature 1, an error is generated in the result of the CFD simulation due to measurement error of the sensors or other factors.

[0010] In a CFD simulation, it is said that the quality of boundary condition setting mainly affects the result of the simulation. Now, boundary conditions will be briefly explained.

In general, a flow of fluid continues infinitely but the CFD can analyze only a limited region. For this reason, in the CFD, a region to be analyzed is defined and this analysis target region is called a boundary region. To define the boundary region, a condition of boundary indicating the boundary region needs to be set. This condition is called a boundary condition. When the boundary condition is not set appropriately, an error between the result of the simulation and the sensor data, which is actually measured, becomes large. Thus, to bring the simulation result closer to the sensor data, calibration needs to be performed to correct the boundary condition.

[0011] In Patent Literature 2, for example, a method in which calibration is performed in a CFD simulation to improve the accuracy has been proposed.

Citation List Patent Literature [0012] Patent Literature 1: Japanese Unexamined Patent Application Publication No. 2001-99462 Patent Literature 2: Japanese Unexamined Patent Application Publication No. 2015-148410

Summary of Invention

Technical Problem [0013] In the calibration method described in Patent Literature 2, an initial value is adjusted and a CFD simulation is performed repeatedly until a difference between the result of the CFD simulation and sensor data that has been actually measured falls into an allowable range. In this way, in the calibration method described in Patent Literature 2, calibration is performed by repeatedly performing the CFD simulation.

Consequently, the amount of calculation is increased due to the calibration. As a result, a problem such that a calculation speed becomes slower or a problem such that calculation cannot be completed within an actual time may arise depending on the performance of an arithmetic device.

[0014] The present disclosure has been made to overcome the above-mentioned problem, and has an object to provide an air-conditioning control device capable of performing calibration at a higher speed with less calculation amount.

Solution to Problem [0015] An air-conditioning control device according to an embodiment of the present disclosure includes an information acquisition unit configured to acquire an invariable condition that includes at least one of a building condition including a dimension of a target space, a facility condition including a dimension of an air-conditioning apparatus, and a sensor coordinate value indicating an installation position of a sensor, a variable condition that includes at least one of an environmental condition of the target space and an operational condition of the air-conditioning apparatus, and sensor data of the target space measured by the sensor, a model generation unit configured to generate a CFD model for the target space based on the invariable condition acquired by the information acquisition unit, a calculation condition generation unit configured to generate, based on the variable condition and the sensor data, a calculation condition that includes a boundary condition to be used in a CFD simulation using computational fluid dynamics, a CFD analysis unit configured to perform the CFD simulation by using the CFD model generated by the model generation unit and the calculation condition generated by the calculation condition generation unit, and output simulation results, a result extraction unit configured to extract the simulation result of a first target position in the target space from among the simulation results of the CFD analysis unit, a correction method selection unit configured to determine a state of the air-conditioning apparatus based on the sensor data or the operational condition, and select a correction method for determining a correction amount for the calculation condition based on a result of the determination, a correction execution unit configured to correct the calculation condition by determining the correction amount of the calculation condition based on the simulation result of the first target position extracted by the result extraction unit, the sensor data at the same position as the first target position, and the correction method selected by the correction method selection unit, and a control command determination unit configured to generate a control command for the air-conditioning apparatus based on the simulation result of the CFD simulation performed by the CFD analysis unit. The CFD analysis unit is configured to perform the CFD simulation again by using the calculation condition corrected by the correction execution unit. The result extraction unit is configured to extract the simulation result of the first target position in the target space from among the simulation results obtained by performing the CFD simulation again by the CFD analysis unit as a corrected simulation result. The control command determination unit is configured to generate a control command for the air-conditioning apparatus based on the corrected simulation result extracted by the result extraction unit.

Advantageous Effects of Invention [0016] According to the air-conditioning control device according to an embodiment of the present disclosure, calibration can be performed at a higher speed with less calculation amount.

Brief Description of Drawings

[0017] [Fig. 1] Fig. 1 is a configuration diagram illustrating the configuration of an air-conditioning system including an air-conditioning control device according to Embodiment 1.

[Fig. 2] Fig. 2 is a diagram illustrating the configuration of actuators of a refrigerant circuit including the air-conditioning control device according to Embodiment 1.

[Fig. 3] Fig. 3 is a diagram illustrating an example of the configuration of the air-conditioning control device according to Embodiment 1.

[Fig. 4] Fig. 4 is a perspective view for illustrating an example of a CFD model generated by a model generation unit of the air-conditioning control device according to Embodiment 1.

[Fig. 5] Fig. 5 is a schematic view for illustrating an example of a determination method of a correction method selection unit in the air-conditioning control device according to Embodiment 1.

[Fig. 6] Fig. 6 is a schematic view of calibration performed by a correction execution unit of the air-conditioning control device according to Embodiment 1. [Fig. 7] Fig. 7 is a flowchart illustrating operation of the air-conditioning control device according to Embodiment 1.

[Fig. 8] Fig. 8 is a configuration diagram illustrating the configuration of the air-conditioning control device according to Embodiment 2.

[Fig. 9] Fig. 9 is a flowchart illustrating the flow of processing of a candidate generation unit of the air-conditioning control device according to Embodiment 2.

[Fig. 10] Fig. 10 is a plan view illustrating how the candidate generation unit of the air-conditioning control device divides a target space according to Embodiment 2.

[Fig. 11] Fig. 11 illustrates processing of step S1201 and step S1202 of Fig. 9.

[Fig. 12] Fig. 12 is a diagram illustrating an example of a calculation condition table generated by a calculation condition generation unit of the air-conditioning control device according to Embodiment 2.

[Fig. 13] Fig. 13 is a graph illustrating a difference between the highest and lowest temperatures in time-series temperature data of simulation results that are obtained by using the same calculation condition and extracted by a result extraction unit of the air-conditioning control device according to Embodiment 2.

[Fig. 14] Fig. 14 is a graph illustrating a difference between the highest and lowest temperatures in time-series temperature data of simulation results that are obtained by using the same calculation condition and extracted by a result extraction unit of the air-conditioning control device according to Embodiment 2.

[Fig. 15] Fig. 15 is a diagram illustrating an example of a sensor position table generated by a table generation unit of the air-conditioning control device according to Embodiment 2.

[Fig. 16] Fig. 16 is a flowchart illustrating the flow of processing from generation of a model by a model generation unit to generation of a sensor position table by a table generation unit in the air-conditioning control device according to Embodiment 2.

[Fig. 17] Fig. 17 is a flowchart illustrating the flow of processing of a sensor position derivation unit of the air-conditioning control device according to Embodiment 2.

[Fig. 18] Fig. 18 is a flowchart illustrating operation of the air-conditioning control device according to Embodiment 2.

Description of Embodiments

[0018] Embodiments will be described below with reference to the accompanying drawings. Note that the drawings are illustrated schematically and, for the sake of convenience of description, omission or simplification of the configurations is made as appropriate in the drawings. In addition, the size of the components and the positional relationship of the components shown in the drawings are not necessarily accurate and can be changed as appropriate. Moreover, in the description below, the same or similar components are denoted by the same reference symbols and have the same or similar names and functions. Therefore, the detailed description of the same or similar components may be omitted to avoid duplication of the description. The present disclosure is not limited to the following embodiments, and various modifications are conceivable without departing from the scope of the present disclosure. In addition, the present disclosure includes any combination of the configurations that can be combined with one another among the configurations described in the following embodiments.

[0019] Embodiment 1 Fig. 1 is a configuration diagram illustrating the configuration of an air-conditioning system including an air-conditioning control device 1 according to Embodiment 1. As shown in Fig. 1, the air-conditioning system includes the air-conditioning control device 1, an air-conditioning apparatus 2, a sensor group 4, and a control network 5. The air-conditioning control device 1 is connected to the air-conditioning apparatus 2 and the sensor group 4 via the control network 5 to perform communication of data. Furthermore, the air-conditioning control device 1 controls the air-conditioning apparatus 2 based on sensor data from the sensor group 4.

[0020] As shown in Fig. 1, the air-conditioning apparatus 2 includes an outdoor unit 21, an indoor unit 22, and a remote controller 23. The air-conditioning apparatus 2 performs air-conditioning of a space to be controlled. Hereinafter, the space to be controlled by the air-conditioning apparatus 2 will be referred to as a "target space".

[0021] Fig. 2 is a diagram illustrating the configuration of actuators of a refrigerant circuit including the air-conditioning control device according to Embodiment 1. The outdoor unit 21 is installed outside the target space, as shown in Fig. 2. The outdoor unit 21 has a heat exchanger R5. The heat exchanger R5 exchanges heat between refrigerant flowing therein and outdoor air to cool or heat the refrigerant. Note that the outdoor unit 21 may use heat refrigerant such as water instead of refrigerant. The indoor unit 22 is installed in the target space. The indoor unit 22 has an indoor heat exchanger R1. The indoor heat exchanger R1 exchanges heat between heat refrigerant flowing therein and indoor air. By adjusting the amount of the refrigerant by a control valve R2, the indoor unit 22 controls the indoor temperature. The outdoor unit 21 and the indoor unit 22 are connected to each other by a pipe R6 in which the refrigerant flows. The refrigerant circuit is formed by a compressor R4 configured to cause the refrigerant to flow in the pipe R6, a four-way valve R3 configured to change a flow of the refrigerant, the heat exchanger R5, the control valve R2, and the indoor heat exchanger R1. The remote controller 23 is a device that is operated by a user and receives an input from the user. By manually operating the remote controller 23, the user can turn on and off the air-conditioning apparatus 2 and can set or change temperature, airflow rate, direction of airflow, and other settings.

[0022] The sensor group 4 is installed inside and outside the target space to measure physical quantities of measurement targets. Note that the sensor group 4 comprises a single or a plurality of sensors 41. Hereinafter, the measurement target of each sensor 41 is referred to as a "target". The sensors 41 are installed, for example, inside and outside the target space to measure a temperature, a humidity, an airflow rate, an airflow velocity and other data inside and outside the target space. Alternatively, the sensors 41 are installed at an air outlet of the air-conditioning apparatus 2 to measure the temperature, the airflow rate, and the airflow velocity of air supplied from the air outlet of the air-conditioning apparatus 2. Note that, hereinafter, the temperature, the airflow rate, and the airflow velocity of the air supplied from the air outlet of the air-conditioning apparatus 2 will be referred to simply as the temperature, the airflow rate, and the airflow velocity of the air outlet. Furthermore, the sensors 41 may be installed on a wall surface and a window surface to measure the temperatures of the wall surface and window surface. In addition, the sensors 41 may be installed on a shelf, a desk and a floor provided in the target space to measure surface temperatures of objects, such as packages, placed on the shelf, the desk, and the floor. Therefore, each sensor 41 is installed as needed on at least one of the following positions: the air outlet of the air-conditioning apparatus 2, the wall surface or the window surface of the target space, the shelf or the desk provided in the target space, and other places. Note that, hereinafter, the installation position of each sensor 41 represented as a position on an XYZ three-dimensional coordinate system is referred to as a "sensor coordinate value". Thus, the sensor coordinate value is three-dimensional data of X-axis, Y-axis and Z-axis. Refer to Fig. 11(a) for more details on the X-axis, Y-axis, and the Z-axis.

Although two sensors 41 are shown in Fig. 1, any required number (but at least one) of the sensors 41 may be used. Note that a physical quantity that the sensor group 4 measures may be that of at least one of the above examples. Which physical quantity to be measured is appropriately determined as needed.

[0023] The control network 5 is a communication network that is configured to connect the air-conditioning control device 1, the air-conditioning apparatus 2, and the sensor group 4 to each other and transmit various data among them. The control network 5 is a wireless communication, such as Bluetooth (registered trademark), or a domestic local area network (LAN).

[0024] Fig. 3 is a diagram illustrating an example of the configuration of the air-conditioning control device 1 according to Embodiment 1. As shown in Fig. 3, the air-conditioning control device 1 includes an input/output device 104, a storage device 105, and an arithmetic device 106.

[0025] As shown in Fig. 3, the input/output device 104 includes an information acquisition unit 110 and a result output unit 111. The information acquisition unit 110 includes, for example, an input device configured to receive an input from the user and a reception device configured to be connected to the control network 5 and receive various data. The result output unit 111 is, for example, a display device such as a display.

[0026] The information acquisition unit 110 is configured to acquire an invariable condition 100, a variable condition 101, and sensor data 102.

[0027] The invariable condition 100 includes a building condition 100a, a facility condition 100b, and a sensor coordinate value 100c. The building condition 100a is dimension data regarding the shape of the target space or a building in which the target space is provided, such as the width, depth, and height of the target space or the size of the building. The facility condition 100b is dimension data regarding the shape of the air-conditioning apparatus 2, such as the position and the shape of the air outlet of the air-conditioning apparatus 2. The sensor coordinate value 100c is three-dimensional data indicating the coordinates of the installation position for each sensor 41. The invariable condition 100 is input into the information acquisition unit 110 by an operator when the air-conditioning control device 1 is installed, for example.

[0028] The variable condition 101 includes information on an environmental condition 101a and an operational condition 101b. The environmental condition 101a is data indicating environmental conditions such as an outdoor air temperature and an outdoor air humidity. The environmental condition 101a may be measured by a sensor installed outdoors or may be obtained by arithmetic calculation. Alternatively, when the information acquisition unit 110 is connected to the Internet, the information acquisition unit 110 may acquire the environmental condition 101a via the Internet. The environmental condition may include seasonal information such as summer, winter, and in-between season. The operational condition 101b is data to be input from the remote controller 23 by the user, such as set temperature, airflow rate, airflow velocity, operation mode. The operation mode includes a heating mode, a cooling mode, and a defrosting mode. Furthermore, the operation mode may include a business day mode and a holiday mode. The variable condition 101 is transmitted from the air-conditioning apparatus 2 to the information acquisition unit 110 via the control network 5.

[0029] Note that although the above explanation indicates that the environmental condition 101a is transmitted from the air-conditioning apparatus 2 to the information acquisition unit 110, the way in which the information acquisition unit 110 acquires the environmental condition 101a is not limited thereto. The sensor 41 may measure a part of the environmental condition 101a and transmit the measured data to the information acquisition unit 110. However, to simplify the description, the following description is made under an assumption that the environmental condition 101a is transmitted from the air-conditioning apparatus 2 to the information acquisition unit 110. [0030] The sensor data 102 is data of physical quantities measured by the sensors 41. As described above, the sensor data 102 includes at least one of the following: the temperature, the humidity, the airflow rate, the airflow velocity inside or outside of the target space, the temperature, the humidity, the airflow rate, the airflow velocity at the air outlet of the air-conditioning apparatus 2, the temperature of a wall surface or a window surface of the target space, and the surface temperature of an object placed in the target space. The sensor data 102 is transmitted from the sensors 41 to the information acquisition unit 110 via the control network 5.

[0031] The result output unit 111 is configured to output data 103. The output data 103 includes a calculation result 103a and a control command value 103b. The calculation result 103a is a simulation result, such as a temperature or a humidity calculated by simulation. The control command value 103b is, for example, a command value that specifies an operation content for a device, such as an actuator and a compressor, installed in the air-conditioning apparatus 2.

[0032] The storage device 105 functions as a storage unit that stores the invariable condition 100, the variable condition 101, and the sensor data 102 acquired by the input/output device 104. The storage device 105 also stores the output data 103.

The storage device 105 is a non-volatile or volatile semiconductor memory, such as a RAM, a ROM, a flash memory, an EPROM and an EEPROM, a magnetic disk, an optical disk, or a similar device.

[0033] The arithmetic device 106 is configured to perform the CFD simulation and output a simulation result as the calculation result 103a of the output data 103. The arithmetic device 106 is configured to also generate a control command value for the air-conditioning apparatus 2 based on the simulation result and output the control command value as the control command value 103b.

[0034] In a case where the target space of the air-conditioning apparatus 2 is a space having a high heat insulation property, such as a low-temperature warehouse, when the air-conditioning apparatus 2 is in a thermo-on state, that is, when the indoor unit 22 supplies cold air, the temperature at the air outlet of the indoor unit 22 has a greatest effect on the simulation result of the arithmetic device 106. Note that, the thermo-on state is a state in which a room temperature of the target space has not reached a set temperature and a cooling operation or a heating operation is performed in the target space by operating the outdoor unit 21 and by supplying cool air or warm air from the indoor unit 22 while the opening degree of the control valve R2, which controls the amount of the refrigerant in the indoor heat exchanger R1 in the indoor unit 22, is kept larger than a predetermined reference.

[0035] Meanwhile, when the air-conditioning apparatus 2 is in a thermo-off state, that is when supply of cold air from the indoor unit 22 is stopped, the surface temperature of a wall of the target space and the surface temperature of an object placed in the target space have greatest effects on the simulation result of the arithmetic device 106. Note that, the thermo-off state is a state in which, after a room temperature of the target space has reached a set temperature, the outdoor unit 21 is in operation but a cooling operation or a heating operation for the target space is stopped by reducing the opening degree of the control valve R2, which controls the amount of the refrigerant in the indoor heat exchanger R1 in the indoor unit 22, to a degree smaller than a predetermined reference, or the outdoor unit 21 is stopped to stop the cooling operation or the heating operation for the target space.

[0036] In Embodiment 1, attention is paid to the thermo-on and thermo-off states.

Based on whether the air-conditioning apparatus 2 is in the thermo-on state or the thermo-off state, the arithmetic device 106 selects a correction method to correct a calculation condition to be used in the CFD simulation. The arithmetic device 106 will be described in detail below.

[0037] As shown in Fig. 3, the arithmetic device 106 includes a model generation unit 120, a CFD analysis unit 121, a calculation condition generation unit 122, a result extraction unit 124, a correction execution unit 125, a control command determination unit 126, and a correction method selection unit 127.

[0038] The model generation unit 120 is configured to generate a CFD model 10 for the target space based on the invariable condition 100 stored in the storage device 105. More specifically, the model generation unit 120 generates the CFD model 10 for the target space based on the building condition 100a included in the invariable condition 100. Fig. 4 is a perspective view for illustrating an example of the CFD model 10 generated by the model generation unit 120 of the air-conditioning control device 1 according to Embodiment 1. The CFD model 10 shown in Fig. 4 is a model reflecting a geometric pattern of the target space surrounded by wall surfaces and a window surface. As shown in Fig. 4, the CFD model 10 includes models M100 to M104 and M300.

[0039] The model M100 is a model for wall surfaces surrounding the target space. The model M100 has a boundary condition M200 for the temperature of a wall surface analyzed as one of the boundaries surrounding the target space.

[0040] The model M101 is a model for a window surface provided in the target space. The model M101 has a boundary condition M201 for the temperature of the window surface analyzed as another one of the boundaries surrounding the target space. [0041] The model M102 is a model for the air-conditioning apparatus 2, and has a boundary condition M202 for the temperature and the airflow velocity at an air outlet. The air-conditioning apparatus 2 represented by the model M102 has an air outlet and an air inlet, The air-conditioning apparatus 2 has a function to perform air-conditioning in the target space and performs supply of air as specified by the boundary condition M202.

[0042] The model M103 is an internal heat source model indicating a heat source provided in the target space. The model M103 has a boundary condition M203 for internal heat generation. The model M103 analyzes generation of heat specified by the boundary condition M203 as a boundary condition. Note that, examples of the heat source include a person staying in the target space and a device such as a personal computer placed in the target space.

[0043] The model M104 is a model indicating the installation position of the sensor 41 installed in the target space. The model M104 is provided in the CFD model 10 based on the sensor coordinate value of the invariable condition 100.

[0044] The model M300 is a simulation result calculated by the CFD simulation. The model M300 is, for example, a temperature distribution in the target space.

[0045] Now return to the description of Fig. 3. The CFD analysis unit 121 is configured to perform the CFD simulation by using the CFD model 10 generated by the model generation unit 120 and a calculation condition, which will be described later, generated by the calculation condition generation unit 122. The CFD analysis unit 121 is configured to output the simulation result as the calculation result 103a of the output data 103. The calculation result 103a is stored in the storage device 105. Note that CFD is an analysis method in which a target space is discretized into grid cells and governing equations are solved for each grid cell. The governing equations for fluid used in the CFD simulation are represented by the following Equations (1) to (3), for example. Equation (1) is a continuous equation for mass conservation of fluid.

Equation (2) is an incompressible Navier-Stokes equation representing momentum conservation. Equation (3) is an energy equation. The CFD analysis unit 121 solves Equations (1) to (3) using proper initial values under appropriate boundary conditions to calculate the temperature, the humidity, the airflow velocities, and other values for each region divided in a grid shape.

[0046] Equation (1) V * u = 0 ( 1) [0047] Equation (2) + (u * VII) Paiiti Cp U * riT) = V * (k VT) Q -V p + V * (R.Vu) +(p-p 0) g ( 2) [0048] Equation (3) (3) [0049] Here, u represents a three-dimensional velocity vector, t represents a time, p represents a pressure, p represents a density, represents a viscosity coefficient, po represents a reference density, g represents a gravitational acceleration, Cp represents a constant pressure specific heat, T represents a temperature, k represents a thermal conductivity, and Q represents an amount of internal heat generation.

[0050] The calculation condition generation unit 122 is configured to generate a calculation condition including an initial value and a boundary condition to be used in the CFD simulation by using the variable condition 101 and the sensor data 102, and output the generated calculation condition to the CFD analysis unit 121. In this case, the variable condition 101 includes, for example, an outdoor temperature and an outdoor humidity. In addition, the sensor data 102 includes data on temperature, such as the temperature of a wall surface in the target space and the temperature at the air outlet. Note that the sensor data 102 may further include data on humidity and other items, in addition to temperature.

[0051] The result extraction unit 124 is configured to extract a simulation result of a desired target position in the target space from the calculation results 103a of output data 103 stored in the storage device 105. More specifically, when the air-conditioning apparatus 2 is in the thermo-on state, the result extraction unit 124 extracts a simulation result of,for example, the model M102 shown in Fig. 4 to extract a simulation result for the air outlet. Meanwhile, when the air-conditioning apparatus 2 is in the thermo-off state, the result extraction unit 124 extracts simulation results of, for example, the model M100 and the model M104 shown in Fig. 4 to extract a simulation result for a wall surface or an object. As described above, the result extraction unit 124 determines "a desired position" according to whether the air-conditioning apparatus 2 is in the thermoon state or the thermo-off state based on the operational condition 101b.

[0052] The correction method selection unit 127 is configured to determine the current state of the air-conditioning apparatus 2 based on the operational condition 101b stored in the storage device 105 and, according to the determination result, select a correction method to be used in the correction execution unit 125. More specifically, the correction method selection unit 127 determines whether the air-conditioning apparatus 2 is in the thermo-on state or the thermo-off state based on the operational condition 101b, and, according to the determination result, selects a correction method for determining a correction amount for the calculation condition.

[0053] When the air-conditioning apparatus 2 is in the thermo-on state, the correction method selection unit 127 selects a first correction method. In the first correction method, the boundary condition for the temperature at the air outlet of the air-conditioning apparatus 2 is corrected. In the first correction method, the following Equation (4), for example, is used to calculate a correction amount AToutlet_modify of the calculation condition. In this case, the correction amount AToutlet_modify is a correction amount to be used to correct the boundary condition for the temperature at the air outlet. [0054] Equation 4 AToutiel.yaniiifY[ akx AT[t] ( 4) [0055] Here, k represents a serial number of at least one air outlet provided in the target space. AToutlet_modify [k,t] represents a correction amount for the boundary condition for the temperature at the k-numbered air outlet. A coefficient ak is a constant being set in advance. The coefficient Ca is set to 1 or 0.5 by a designer in prior adjustment in consideration of an individual difference of each sensor 41. Alternatively, the coefficient CU is set to a value that is acquired in advance by using a machine learning method or a similar method. Here, a temperature difference AT[t] is an average value of a difference between the simulation result at the desired target position extracted by the result extraction unit 124 and the sensor data 102 at the same position as the desired target position at a point of time t. The temperature difference AT[t] is calculated by the following Equation (5).

[0056] Equation 5 [0057] AT[1] t) target,11 ( 5) Here, N represents the total number of the sensors 41 provided in the target space. Tsensor[0] is sensor data 102 acquired from the sensor 41 having a sensor number i. Ttarget[i,t] is the temperature of a target having a sensor number i in the CFD model 10. That is, Ttarget[i,t] is a simulation result at the target position of the sensor number i extracted by the result extraction unit 124.

[0058] Meanwhile, when the air-conditioning apparatus 2 is in the thermo-off state, the correction method selection unit 127 selects a second correction method. In the second correction method, the boundary condition for the temperature of a wall surface of the target space or the temperature of an object placed in the target space is corrected. In the second correction method, the following Equation (6), for example, is used to calculate a correction amount ATpaneLmodify of the calculation condition. In this case, the correction amount ATpanel_modify is a correction amount used to correct the boundary condition for the temperature of a wall surface or the surface temperature of an object in the target space.

[0059] Equation 6 A Tpanetunodify /3 x A Tilt, ( 6) [0060] Here, n represents a serial number given to wall surfaces and panels imposing a boundary condition on the surface temperature of an object in the target space. A coefficient 13n is a constant being set in advance. The coefficient ilk is set to 1 or 0.5 by a designer in prior adjustment in consideration of an individual difference of each sensor 41. Alternatively, the coefficient Ok is set to a value that is acquired in advance by using a machine learning method or a similar method. Note that the number n and the number i are associated with each other and stored in the storage device 105. Thus, for example, by giving the number n to the wall surface closest to the sensor 41 having the number i, and the number n and the number i are associated with each other.

[0061] Furthermore, the temperature difference AT[0] in Equation (6) is calculated by the following Equation (7).

[0062] Equation (7) AT[i 'sensor * a e [0063] Here, i represents the number given to an individual sensor 41, and t represent a time. That is, the temperature difference AT[i,t] is a difference between the simulation result at the desired target position extracted by the result extraction unit 124 and the sensor data 102 at the same position as the desired target position at a point of time t. Tsensor[i,t] is sensor data 102 acquired from the sensor 41 having a sensor number i.

Ttarget[i,t] is the temperature of a target having a sensor number i in the CFD model 10.

That is, Ttarget[0] is a simulation result at the target position of the sensor number i extracted by the result extraction unit 124.

[0064] As shown in the above Equations (4) and (6), the correction execution unit 125 obtains a difference between the simulation result at the desired target position extracted by the result extraction unit 124 and the sensor data 102 at the same position as the desired target position. Then, by multiplying the difference by the coefficient ak or the coefficient fik, which is set in advance for the corresponding correction method, the correction execution unit 125 calculates a correction amount for a boundary condition included in the calculation condition.

[0065] In addition, the above description indicates that the correction methods used in the correction execution unit 125 are those using arithmetic equations of Equations (4) and (6). However, the correction methods are not limited thereto. For example, the correction execution unit 125 may use a correction method that uses a different arithmetic equation. Furthermore, the correction execution unit 125 may use a correction method that uses a table instead of an arithmetic equation. In such a case, for example, the correction execution unit 125 stores in advance a table in which the temperature difference AT[t] of Equation (5) and the correction amount AToutlet_modify are associated with each other in the storage device 105. Then, the correction execution unit 125 uses the table to acquire the correction amount AToutiet_modify based on the temperature difference AT[t]. Similarly, the correction execution unit 125 may store in advance a table in which the temperature difference AT[i,t] of Equation (7) and the correction amount ATpanel_modify are associated with each other in the storage device 105. Then, the correction execution unit 125 uses the table to acquire the correction amount ATpanel_modify based on the temperature difference AT[i,t].

[0066] In addition, the above description indicates that the correction method selection unit 127 determines whether the air-conditioning apparatus 2 is in the thermo-on state or the thermo-off state based on the operational condition 101b. However, the determination method is not limited thereto. The correction method selection unit 127 may determine whether the air-conditioning apparatus 2 is in the thermo-on state or the thermo-off state based on the sensor data 102, as described in Fig. 5. Fig. 5 is a schematic view for illustrating an example of a determination method of the correction method selection unit 127 in the air-conditioning control device 1 according to Embodiment 1. Fig. 5 shows a case where the target space is a low-temperature warehouse. In the upper graph in Fig. 5, the horizontal axis shows a time and the vertical axis shows a temperature. In addition, in the upper graph in Fig. 5, a temperature T100 represents the temperature at an air outlet of the air-conditioning apparatus 2 measured by the corresponding sensor 41. The temperature is stored in the storage device 105 as the sensor data 102. Moreover, in the upper graph in Fig. 5, a temperature T101 represents a reference value being set in advance to determine whether the air-conditioning apparatus 2 is in the thermo-on state or the thermo-off state. For example, the temperature T101 corresponds to an average value of the temperature at the air outlet. When the temperature T100 detected by the sensor 41 is equal to or less that the reference value 1101, the correction method selection unit 127 determines that the air-conditioning apparatus 2 is in the thermo-on state. Meanwhile, when the temperature 1100 detected by the sensor 41 is higher than the reference value T101, the correction method selection unit 127 determines that the air-conditioning apparatus 2 is in the thermo-off state. Note that, in the lower graph in Fig. 5, ON indicates the thermo-on state and OFF indicates the thermo-off state.

[0067] Now, return to the description of Fig. 3. The correction execution unit 125 calculates a correction amount for the calculation condition based on the simulation result at the desired target position extracted by the result extraction unit 124, the sensor data 102 at the same position as the desired target position, and the correction method selected by the correction method selection unit 127. The correction execution unit 125 performs correction of the calculation condition by using the calculated correction amount.

[0068] For example, when the air-conditioning apparatus 2 is in the thermo-on state, the correction execution unit 125 calculates the correction amount AToutieunodify by using Equations (4) and (5) selected by the correction method selection unit 127. In addition, the correction execution unit 125 uses the following Equation (8) to add the correction amount AToutlet_modify to the boundary condition Toutlet [k,t] for the temperature at the air outlet, thereby correcting the boundary condition Toutlet [k,t]. The correction execution unit 125 outputs a boundary condition Toutiet_modify [k,t] having been corrected to the CFD analysis unit 121.

[0069] Equation 8 To u tl e Wiry [1C, t = Toutiet [AT, ti AT k t1 outleLmodify ( 8) [0070] When the air-conditioning apparatus 2 is in the thermo-off state, the correction execution unit 125 calculates the correction amount ATpanel_modify by using Equations (6) and (7) selected by the correction method selection unit 127. In addition, the correction execution unit 125 uses the following Equation (9) to add the correction amount ATpanelmodify to the boundary condition Inane! [k,t] for the temperature of a wall surface or the surface temperature of an object, thereby correcting the boundary condition Tpanel [k,t]. The correction execution unit 125 outputs a boundary condition TpaneLmodify [k,t] having been corrected to the CFD analysis unit 121.

[0071] Equation 9 Tpanel jnodrfy r n t 'panel [n, * ] + A Tp an,Isoodify (9) [0072] Fig. 6 is a schematic view of calibration performed by the correction execution unit 125 of the air-conditioning control device 1 according to Embodiment 1.

Calibration corrects a calculation condition. In Fig. 6, the air-conditioning apparatus 2 is in the thermo-on state from a point of time t2 to a point of time t3. Similarly, the air-conditioning apparatus 2 is in the thermo-off state from a point of time tl to the point of time t2 and from the point of time t3 to a point of time t4. In the upper graph in Fig. 6, a temperature T200 indicated by a solid line is the temperature of the air outlet after calibration and a temperature T201 indicated by a broken line is the temperature of the air outlet before calibration. In addition, a temperature T202 indicated by an arrow represents the correction amount ATounet_modify derived in the first correction method by using, for example, Equations (4) and (5). Similarly, in the middle graph in Fig. 6, a temperature T203 indicated by a solid line is the boundary condition for the temperature of a wall surface or a package after calibration and a temperature T204 indicated by a broken line is the boundary condition for the temperature of a wall surface or a package before calibration. In addition, a temperature T205 indicated by an arrow represents the correction amount ATpanelmodify derived in the second correction method by using, for example, Equations (6) and (7).

[0073] As shown in Fig. 6, when the air-conditioning apparatus 2 is in the thermo-on state, the correction execution unit 125 corrects the boundary condition for the temperature at the air outlet by the first correction method, and when the air-conditioning apparatus 2 is in the thermo-off state, the correction execution unit 125 corrects the boundary condition for the temperature of a wall surface or a package by the second correction condition.

[0074] The boundary condition corrected by the correction execution unit 125 is transmitted to the CFD analysis unit 121 via the calculation condition generation unit 122. The CFD analysis unit 121 performs the CFD simulation again by using the corrected boundary condition and outputs a simulation result. The simulation result is stored in the storage device 105 as the calculation result 103a of the output data 103. Note that, the boundary condition having been corrected by the correction execution unit 125 may be transmitted to the CFD analysis unit 121 directly without the calculation condition generation unit 122. The result extraction unit 124 extracts the simulation result of the desired position in the target space from the calculation result 103a of the output data 103 stored in the storage device 105.

[0075] Now, return to the description of Fig. 3. By using a predetermined method, the control command determination unit 126 is configured to generate and output a control command for the air-conditioning apparatus 2 based on the simulation result of the desired position extracted by the result extraction unit 124. Note that, the simulation result to be extracted here is a simulation result of the CFD simulation that was performed by using the boundary condition corrected by the correction execution unit 125. Hereinafter, the simulation result is referred to as a "corrected simulation result".

Furthermore, the control command is a command that specifies an operation content of a device installed in the air-conditioning apparatus 2, such as an actuator or a compressor, based on the simulation result and a set temperature. In addition, the predetermined method is a method such as a feedback control, for example, that controls the temperature at the air outlet or the frequency of the compressor in such a manner that a difference between the temperature at a desired position and the set temperature is minimized.

[0076] Note that, although the above explanation indicates that the second correction method corrects the boundary condition for the temperature of a wall surface or the surface temperature of an object, examples of the object may include a heat source body in the target space in addition to a package in the target space. In addition, in the second correction method, not only the boundary condition for a wall surface but also the boundary condition for a window surface may be corrected. That is, the second correction method corrects the boundary conditions for a wall surface and a window surface of the target space and the boundary conditions for the surface temperatures of objects, such as a package and a heat source body, in the target space.

[0077] Here, the hardware configuration of the arithmetic device 106 will be briefly described. The function of each unit of the arithmetic device 106 is achieved by a processing circuit. The processing circuit may be dedicated hardware or a processor that executes programs stored in a memory. The processing circuit achieves the function of each unit of the arithmetic device 106 by reading out and executing a corresponding program stored in the memory. The processing circuit can achieve the function of each unit of the arithmetic device 106 by hardware, software, firmware, or a combination of them.

[0078] Fig. 7 is a flowchart illustrating operation of the air-conditioning control device 1 according to Embodiment 1.

[0079] In step ST100, the information acquisition unit 110 acquires the invariable condition 100, the variable condition 101, and the sensor data 102.

[0080] In step ST101, the model generation unit 120 generates the CFD model 10 by using the invariable condition 100 acquired in step ST100. In addition, the calculation condition generation unit 122 generates a calculation condition to be used in CFD by using the variable condition 101 and the sensor data 102 acquired in step ST100. [0081] In step ST102, the CFD analysis unit 121 performs the CFD simulation by using the CFD model 10 and the calculation condition generated in step ST101.

[0082] In step ST103, the correction method selection unit 127 selects a correction method for the calculation condition according to whether the air-conditioning apparatus 2 is in the thermo-on state or the thermo-off state.

[0083] In step ST104, the correction execution unit 125 derives a correction amount of the calculation condition by using the simulation result extracted by the result extraction unit 124, the sensor data 102, and the correction method selected by the correction method selection unit 127, and then corrects the calculation condition.

[0084] In step ST105, the CFD analysis unit 121 performs the CFD simulation again by using the calculation condition having been corrected in step ST104.

[0085] In step ST106, the result extraction unit 124 extracts, as a corrected simulation result, the temperature of the desired target position in the simulation result that has been performed again.

[0086] In step ST107, the control command determination unit 126 determines a control command value for the air-conditioning apparatus 2 based on the temperature of the desired target position extracted in step ST106. As described above, the control command determination unit 126 determines a control command value for the air-conditioning apparatus 2 based on the corrected simulation result.

[0087] Advantageous Effects of Embodiment 1 In Embodiment 1, the air-conditioning control device 1 generates the CFD model 10 from the invariable condition 100, generates the calculation condition from the variable condition 101 and the sensor data 102, and performs the CFD simulation. In addition, the air-conditioning control device 1 calculates a difference between the calculation result 103a of the CFD simulation and the sensor data 102. The air-conditioning control device 1 selects a correction method that is used to calculate a correction amount of the calculation condition to be used in the CFD simulation, according to the state of the air-conditioning apparatus 2. The air-conditioning control device 1 corrects the calculation condition by using the calculated difference and the selected correction method. The air-conditioning control device 1 performs the CFD simulation again by using the corrected calculation condition. As described above, in Embodiment 1, the air-conditioning control device 1 changes the correction method that is used to calculate a correction amount of the calculation condition to be used in the CFD simulation, according to the state of the air-conditioning apparatus 2. As a result, the air-conditioning control device 1 can calculate a correction amount efficiently, thereby achieving a high-speed calibration with less calculation amount.

[0088] Furthermore, when the target space is a space under controlled conditions, such as a low-temperature warehouse, the air-conditioning control device 1 changes the correction method that is used to calculate a correction amount of the calculation condition, for each of the thermo-on and thermo-off states of the air-conditioning apparatus 2. The air-conditioning control device 1 applies the correction amount calculated by using the correction method to the calculation condition and performs the CFD simulation again. Thereby, the air-conditioning control device 1 can complete the calibration with only one repeat of the processing. Accordingly, the air-conditioning control device 1 can obtain an accurate simulation result at high speed and, by using this simulation result, can accurately control the temperature at a desired position in the target space.

[0089] Embodiment 2 Fig. 8 is a configuration diagram illustrating the configuration of the air-conditioning control device 1 according to Embodiment 2. Differences between the configuration of Embodiment 1 shown in Fig. 1 and the configuration of Embodiment 2 shown in Fig. 8 will be described below. In Embodiment 2, as shown in Fig. 8, a sensor position derivation unit 128 and a sensor position table generation unit 129 are added to the configuration of Fig. 1. The sensor position table generation unit 129 includes a candidate generation unit 129a, a change rate comparison unit 129b, a sensor position determination unit 129c, and a table generation unit 129d.

[0090] Because the configurations and operations of other components in Embodiment 2 are the same as those in Embodiment 1, the descriptions thereof will thus be omitted. The following description will be made mainly for the sensor position derivation unit 128 and the sensor position table generation unit 129.

[0091] The sensor position derivation unit 128 is configured to acquire the installation position of each sensor 41 from a sensor position table 103c stored in the storage device 105 based on a combination of at least two items of the environmental condition 101a and the operational condition 101b included in the variable condition 101. When no sensor 41 is installed at an acquired installation position, the sensor position derivation unit 128 notifies an operator of it. The operator installs one of the sensors 41 at the installation position according to the notification. The operation of the sensor position derivation unit 128 will be described later [0092] The sensor position table generation unit 129 is configured to generate the sensor position table 103c in advance and store the sensor position table 103c in the storage device 105. The sensor position table 103c is a table that specifies the installation position of each sensor 41 for each combination of at least two items of the environmental condition and the operational condition included in the variable condition 101. The sensor position table 103c will be described later [0093] The candidate generation unit 129a, the change rate comparison unit 129b, the sensor position determination unit 129c, and the table generation unit 129d provided in the sensor position table generation unit 129 will be described below.

[0094] The candidate generation unit 129a is configured to generate, in the CFD model 10, a sensor candidate position at which the sensor 41 that measures a physical quantity of a target used in calibration for correcting a calculation condition is to be installed based on the invariable condition 100.

[0095] The candidate generation unit 129a first checks the presence or absence of a sensor coordinate value in the invariable condition 100 before generating the sensor position candidate. When a sensor coordinate position is present, the candidate generation unit 129a designates the sensor coordinate position as a sensor candidate position. Meanwhile, when no sensor coordinate position is present in the invariable condition 100, the candidate generation unit 129a treats the CFD model 10 as a rectangular parallelepiped, and generates grid cells in the CFD model 10 by dividing the CFD model into a plurality of areas. The candidate generation unit 129a designates the grid points as sensor candidate positions.

[0096] Fig. 9 is a flowchart illustrating the flow of processing of the candidate generation unit 129a of the air-conditioning control device 1 according to Embodiment 2.

[0097] As shown in Fig. 9, in step ST000, the candidate generation unit 129a determines whether or not a sensor coordinate value is included in the invariable condition 100 stored in the storage device 105. When no sensor coordinate value is present, the processing of the candidate generation unit 129a proceeds to step ST200. Meanwhile, when a sensor coordinate value is present, the processing of the candidate generation unit 129a proceeds to step ST203.

[0098] In step ST200, the candidate generation unit 129a treats the target space as a rectangular parallelepiped and divides the target space into a plurality of areas. Fig. 10 is a plan view illustrating how the candidate generation unit 129a of the air-conditioning control device 1 divides a target space according to Embodiment 2. The candidate generation unit 129a treats, for example, the target space in a plan view as a rectangular shape, as shown in Fig. 10. At this time, when the number of the indoor units 22 having air outlets is N, for example, the candidate generation unit 129a divides the target space into 2N areas so that each indoor unit 22 belongs to a different area. At this time, by, for example, equally dividing each side of the target space in a plan view, as shown in Fig. 10, the candidate generation unit 129a generates 2N areas in the target space. In the example of Fig. 10, each side in the X-axis direction is equally divided into three and each side in the Y-axis direction is equally divided into two, thereby the planar face of the target space is divided into six areas. However, a dividing method by the candidate generation unit 129a is not limited to the one shown in Fig. 10, and the target space may be divided into an arbitrary number of areas.

[0099] In step ST201 shown in Fig. 9, the candidate generation unit 129a forms, in the target space, grid cells along the boundaries of the areas generated in step ST200. Intersections of the grid cells are grid points.

[0100] In step ST202, the candidate generation unit 129a arranges a sensor candidate position on each grid point in the target space.

[0101] Fig. 11 illustrates the processing of step ST201 and step ST202 of Fig. 9. Fig. 11(a) to (d) indicates the processing of step ST201, and Fig. 11(e) indicates the processing of step ST202.

[0102] In Fig. 11(a), the candidate generation unit 129a treats the target space as a rectangular parallelepiped, and sets an X-axis, a Y-axis, and a Z-axis along the width direction, the depth direction, and the height direction, respectively. In addition, the candidate generation unit 129a sets the lengths of the respective sides as x, y, and z. [0103] In Fig. 11(b), the candidate generation unit 129a draws nx straight lines orthogonal to the X-axis at equal intervals when nx sensors 41 are arranged in the X-axis direction, for example. At this time, an interval between the straight lines is x/(nx+1). When the Y-axis direction is divided into ny+1 sections, the candidate generation unit 129a draws ny straight lines orthogonal to the Y-axis at equal intervals. At this time, an interval between the straight lines is y/(ny+1).

[0104] In Fig. 11(c), the candidate generation unit 129a derives the X and Y coordinates for a sensor candidate position based on each intersection of the straight lines drawn in Fig. 11(b).

[0105] In Fig. 11(d), when the Z-axis direction is divided into n1+1 sections, the candidate generation unit 129a generates nz planar faces orthogonal to the Z-axis at equal intervals. At this time, an interval between the planar faces is z/(nz+1).

[0106] In Fig. 11(e), the sensor candidate position determined in Fig. 11(c) is arranged on each planar face generated in Fig. 11(d). The candidate generation unit 129a derives the X, Y, and Z coordinates for the sensor candidate position based on the arranged candidate position.

[0107] Meanwhile, in step ST203 of Fig. 9, the candidate generation unit 129a sets the sensor candidate position at the sensor coordinate value of the invariable condition 100.

[0108] Now, return to the description of Fig. 8. The change rate comparison unit 129b uses the result of the simulation performed by the CFD analysis unit 121 to obtain a temperature change rate of time-series temperature data for each sensor candidate position. Note that, the CFD simulation of the CFD analysis unit 121 at this time is performed for each combination of at least two items of the environmental condition and the operational condition included in the variable condition 101. The combination is, for example, a combination of a seasonal period, such as summer, winter, and in-between season, and an operational mode, such as a business day mode and a holiday mode, as shown in Fig. 12. Fig. 12 is a diagram illustrating an example of a calculation condition table 130 generated by the calculation condition generation unit 122 of the air-conditioning control device 1 according to Embodiment 2. The description for Fig. 12 will be provided later As the temperature change rate, a temperature difference between the highest temperature and the lowest temperature in the time-series temperature data is obtained for each sensor candidate position. Note that, the temperature change rate is not limited thereto. Any index indicating a temperature change rate at each sensor candidate position can be used as the temperature change rate. [0109] The change rate comparison unit 129b will be described in more detail below.

First, the change rate comparison unit 129b sets the target position at the sensor candidate position derived by the candidate generation unit 129a so that the result extraction unit 124 can acquire the simulation result. Next, the change rate comparison unit 129b transmits an instruction to the calculation condition generation unit 122. According to the instruction, the calculation condition generation unit 122 generates calculation conditions (1) to (6) shown in Fig. 12 corresponding to respective combinations of at least two items of the environmental condition and the operational condition included in the variable condition 101 and generates the calculation condition table 130. The calculation condition table 130 is stored in the storage device 105. In the calculation condition table 130, each calculation condition is set for a corresponding combination of at least two items of the environmental condition and the operational condition included in the variable condition 101. For example, as shown in Fig. 12, a calculation condition for the summer season and the business day mode is set as a calculation condition (1). Similarly, a calculation condition for the winter season and the holiday mode is set as a calculation condition (6). Next, the change rate comparison unit 129b transmits an instruction to the CFD analysis unit 121. According to the instruction, the CFD analysis unit 121 performs the CFD simulation several times for each of the calculation conditions (1) to (6) of the calculation condition table 130. As a result, time-series temperature data is generated for each of the calculation conditions (1) to (6). Then, the change rate comparison unit 129b transmits an instruction to the result extraction unit 124. According to the instruction, the result extraction unit 124 extracts time-series temperature data at the target position corresponding to each sensor candidate position.

[0110] Figs. 13 and 14 are graphs each illustrating a difference between the highest and lowest temperatures in time-series temperature data of the simulation results that are obtained by using the same calculation condition and extracted by the result extraction unit 124 of the air-conditioning control device 1 according to Embodiment 2. In each of Figs. 13 and 14, the horizontal axis shows each sensor candidate position belonging to the same area. The vertical axis shows a temperature difference between the highest temperature and the lowest temperature of time-series temperature data at the target position. Note that, Fig. 13 shows temperature differences each between the highest temperature and the lowest temperature at each of multiple sensor candidate positions belonging to area Al, obtained using the same calculate condition. Fig. 14 shows temperature differences each between the highest temperature and the lowest temperature at each of multiple sensor candidate positions belonging to area Bl, obtained using the same calculate condition.

[0111] The change rate comparison unit 129b acquires and compares temperature change rates at each sensor candidate position. This comparison is performed among sensor candidate positions belonging to the same area. In Fig. 13, the largest temperature difference occurs at a sensor candidate position P1 and the smallest temperature difference occurs at a sensor candidate position P2. In Fig. 14, the largest temperature difference occurs at a sensor candidate position P3 and the smallest temperature difference occurs at a sensor candidate position P4. Therefore, the change rate comparison unit 129b selects the sensor candidate positions P1 and Ps for area Al. In addition, the change rate comparison unit 129b selects the sensor candidate positions P3 and P4 for area Bl. Note that, at this time, when there are multiple temperature candidate positions having the highest temperature, like area B1 of Fig. 14, any one of them can be selected. Thus, one of the sensor candidate positions is randomly selected from among them. Similarly, when there are multiple temperature candidate positions having the lowest temperature, like area B1 of Fig. 14, any one of them can be selected. Thus, one of the sensor candidate positions is randomly selected from among them.

[0112] Note that, the sensor candidate position having the largest temperature change rate is considered to be a position that is most affected by blowout from the air-conditioning apparatus 2. In addition, the sensor candidate position having the smallest temperature change rate is considered to be a position that is affected by a wall surface. Thus, the change rate comparison unit 129b selects the sensor candidate position having the largest temperature change rate and the sensor candidate position having the smallest temperature change rate from among the sensors 41.

Note that, the sensor data 102 of the sensor candidate position having the largest temperature change rate is used in the first correction method described in Embodiment 1 and the sensor data 102 of the sensor candidate position having the smallest temperature change rate is used in the second correction method described in Embodiment 1.

[0113] Now, return to the description of Fig. 8. The sensor position determination unit 129c determines an installation position for each sensor 41 from among the sensor position candidates based on the temperature change rate acquired by the change rate comparison unit 129b for each combination of at least two items of the environmental condition and the operational condition included in the variable condition 101. Here, the sensor position determination unit 129c determines the sensor candidate position having the largest temperature change rate and the sensor candidate position having the smallest temperature change rate as installation positions for the sensors 41 based on the temperature change rates acquired by the change rate comparison unit 129b. For example, in the example of area Al of Fig. 13, the sensor position determination unit 129c determines a sensor candidate position P1 and a sensor candidate position P2 as positions at which the sensors 41 are actually to be installed.

[0114] The table generation unit 129d generates the sensor position table 103c in which a combination of at least two items of the environmental condition and the operational condition included in the variable condition 101 is associated with a sensor installation position determined by the sensor position determination unit 129c. More specifically, the table generation unit 129d generates the sensor position table 103c shown in Fig. 15 by combining the sensor installation position determined by the sensor position determination unit 129c and the calculation condition at that time. Fig. 15 is a diagram illustrating an example of the sensor position table 103c generated by the table generation unit 129d of the air-conditioning control device 1 according to Embodiment 2.

As shown in Fig. 15, each sensor position determined by the sensor position determination unit 129c is set in the sensor position table 103c for each season, such as summer, winter, and in-between season, and for each of the business day mode and the holiday mode. For example, in the sensor position table 103c shown in Fig. 15, a sensor installation position for summer and business day mode is set to a sensor position A. In addition, a sensor installation position for in-between season and a holiday mode is set to a sensor position F As described above, in the sensor position table 103c, each sensor installation position is determined for the corresponding combination of at least two items of the environmental condition and the operational condition included in the variable condition 101. The sensor position table 103c is stored in the storage device 105.

[0115] Fig. 16 is a flowchart illustrating the flow of processing from generation of a model by the model generation unit 120 to generation of the sensor position table 103c by the table generation unit 129d in the air-conditioning control device 1 according to Embodiment 2.

[0116] In step ST300, the model generation unit 120 generates the CFD model 10 based on the invariable condition 100 acquired by the information acquisition unit 110.

[0117] In step ST301, the calculation condition generation unit 122 generates the calculation conditions (1) to (6) by using the variable condition 101 acquired by the information acquisition unit 110 and using the combinations of the variable condition 101 shown in Fig. 12.

[0118] In step ST302, by using the CFD model 10 and the calculation conditions (1) to (6) generated as described above, the CFD analysis unit 121 performs the CFD simulation for several times.

[0119] In step ST303, the candidate generation unit 129a generates sensor candidate positions in the CFD model 10 according to the flow of Fig. 9.

[0120] In step ST304, the result extraction unit 124 extracts a simulation result at each sensor candidate position. The result extracted here contains time-series data obtained by performing the CFD simulation several times.

[0121] In step ST305, the change rate comparison unit 129b calculates a change rate for each sensor candidate position. In this case, the change rate comparison unit 129b calculates a temperature difference between the highest temperature and the lowest temperature as the change rate.

[0122] In step ST306, the sensor position determination unit 129c determines a sensor candidate position having the largest temperature difference and a sensor candidate position having the smallest temperature difference as positions at which the sensors 41 are actually to be installed, based on the temperature differences calculated by the change rate comparison unit 129b.

[0123] In step ST307, the table generation unit 129d generates the sensor position table 103c shown in Fig. 15 in which each sensor installation position determined by the sensor position determination unit 129c is set for each of the calculation conditions (1) to (6), and stores the generated sensor position table 103c in the storage device 105. [0124] Fig. 17 is a flowchart illustrating the flow of processing of the sensor position derivation unit 128 of the air-conditioning control device 1 according to Embodiment 2.

[0125] In step ST400, the sensor position derivation unit 128 derives a sensor installation position corresponding to the calculation condition determined by the variable condition 101 from a sensor arrangement table. For example, as shown in Fig. 15, when operation is performed on a business day in summer, the "sensor position A" corresponding to that condition is derived from the sensor arrangement table being generated in advance.

[0126] In step ST401, the sensor position derivation unit 128 checks whether or not a sensor coordinate value for the sensor installation position derived in step ST400 is present in the invariable condition 100 stored in the storage device 105. When a sensor coordinate value of the sensor installation position is not present in the invariable condition 100, the processing of the sensor position derivation unit 128 proceeds to step ST402. Meanwhile, when a sensor coordinate value of the sensor installation position is present, the sensor 41 has been installed already at a required place and the processing of step ST402 is not required. Thus, the processing of the sensor position derivation unit 128 proceeds to step S1403.

[0127] In step ST402, the sensor position derivation unit 128 outputs a sensor arrangement instruction 103d via the result output unit 111 to notify an operator that the sensor 41 needs to be arranged at the sensor installation position derived in step S1400. According to the notification, the operator installs one of the sensor 41 at the sensor installation position derived in step ST400.

[0128] In step ST403, the result output unit 111 outputs the sensor installation position derived by the sensor position derivation unit 128. As a result, the sensor 41 can be reliably installed at the target position for which the result extraction unit 124 should extract the simulation result for calibration.

[0129] Fig. 18 is a flowchart illustrating operation of the air-conditioning control device 1 according to Embodiment 2. Fig. 18 differs from Fig. 7 in that step ST108 is added in Fig. 18. The description for Fig. 18 will be provided below.

[0130] As shown in Fig. 18, in step ST100, the information acquisition unit 110 acquires the invariable condition 100, the variable condition 101, and the sensor data 102.

[0131] In step ST101, the model generation unit 120 generates the CFD model 10 by using the invariable condition 100 acquired in step ST100. In addition, the calculation condition generation unit 122 generates a calculation condition to be used in CFD by using the variable condition 101 and the sensor data 102 acquired in step ST100.

[0132] In step ST102, the CFD analysis unit 121 performs the CFD simulation by using the CFD model 10 and the calculation condition generated in step ST101.

[0133] In step ST108, the sensor position derivation unit 128 acquires, from the sensor position table 103c, a sensor installation position corresponding to the target position in the target space for which the result extraction unit 124 extracts the simulation result. [0134] In step ST103, the correction method selection unit 127 selects a correction method of the calculation condition according to whether the air-conditioning apparatus 2 is in the thermo-on state or the thermo-off state.

[0135] In step ST104, the correction execution unit 125 derives a correction amount of the calculation condition by using the simulation result extracted by the result extraction unit 124, the sensor data 102, and the correction method selected by the correction method selection unit 127, and then corrects the calculation condition.

[0136] In step ST105, the CFD analysis unit 121 performs the CFD simulation again by using the calculation condition having been corrected in step S1104.

[0137] In step ST106, the result extraction unit 124 extracts the temperature of the target position in the simulation result.

[0138] In step ST107, the control command determination unit 126 determines a control command value for the air-conditioning apparatus 2 based on the temperature of the target position extracted in step ST106.

[0139] Advantageous Effects of Embodiment 2 In Embodiment 2, as with Embodiment 1, a high-speed calibration with less calculation amount can be achieved.

[0140] Furthermore, in Embodiment 2, because the air-conditioning control device 1 generates the sensor position table 103c in advance, calibration can be performed more efficiently. That is, it is considered that the sensor installation position having the largest temperature change rate is a position that is most affected by blowout from the air-conditioning apparatus 2. In addition, it is considered that the sensor installation position having the smallest temperature change rate is a position that is affected by the wall surface boundary condition. Therefore, the sensor position derivation unit 128 extracts, from the sensor position table 103c generated in advance, the sensor 41 installed at the sensor installation position having the largest temperature change rate and the sensor 41 installed at the sensor installation position having the smallest temperature change rate. Then, the result extraction unit 124 extracts the simulation results of these sensors 41, and the correction execution unit 125 performs calibration.

As a result, the amount of information to be processed by the air-conditioning control device 1 can be reduced, and the air-conditioning control device 1 can thus perform calibration accurately at higher speed.

Reference Signs List [0141] 1: air-conditioning control device, 2: air-conditioning apparatus, 4: sensor group, 5: control network, 10: CFD model, 21: outdoor unit, 22: indoor unit, 23: remote controller, 41: sensor, 100: invariable condition, 100a: building condition, 100b: facility condition, 100c: sensor coordinate value, 101: variable condition, 101a: environmental condition, 101b: operational condition, 102 sensor data, 103: output data, 103a: calculation result, 103b: control command value, 103c: sensor position table, 104: input/output device, 105: storage device, 106: arithmetic device, 110: information acquisition unit, 111: result output unit, 120: model generation unit, 121: CFD analysis unit, 122: calculation condition generation unit, 124: result extraction unit, 125: correction execution unit, 126: control command determination unit, 127: correction method selection unit, 128: sensor position derivation unit, 129: sensor position table generation unit, 129a: candidate generation unit, 129b: change rate comparison unit, 129c: sensor position determination unit, 129d: table generation unit, 130: calculation condition table, R1: indoor heat exchanger, R2: control valve, R3: four-way valve, R4: compressor, R5: outdoor heat exchanger, R6: pipe

Claims

CLAIMS[Claim 1] An air-conditioning control device comprising: an information acquisition unit configured to acquire an invariable condition that includes at least one of a building condition including a dimension of a target space, a facility condition including a dimension of an air-conditioning apparatus, and a sensor coordinate value indicating an installation position of a sensor, a variable condition that includes at least one of an environmental condition of the target space and an operational condition of the air-conditioning apparatus, and sensor data of the target space measured by the sensor; a model generation unit configured to generate a CFD model for the target space based on the invariable condition acquired by the information acquisition unit; a calculation condition generation unit configured to generate, based on the variable condition and the sensor data, a calculation condition that includes a boundary condition to be used in a CFD simulation using computational fluid dynamics; a CFD analysis unit configured to perform the CFD simulation by using the CFD model generated by the model generation unit and the calculation condition generated by the calculation condition generation unit, and output simulation results; a result extraction unit configured to extract the simulation result of a first target position in the target space from among the simulation results of the CFD analysis unit; a correction method selection unit configured to determine a state of the air-conditioning apparatus based on the sensor data or the operational condition, and select a correction method for determining a correction amount for the calculation condition based on a result of the determination; a correction execution unit configured to correct the calculation condition by determining the correction amount of the calculation condition based on the simulation result of the first target position extracted by the result extraction unit, the sensor data at the same position as the first target position, and the correction method selected by the correction method selection unit; and a control command determination unit configured to generate a control command for the air-conditioning apparatus based on the simulation result of the CFD simulation performed by the CFD analysis unit, wherein the CFD analysis unit is configured to perform the CFD simulation again by using the calculation condition corrected by the correction execution unit, the result extraction unit is configured to extract the simulation result of the first target position in the target space from among the simulation results obtained by performing the CFD simulation again by the CFD analysis unit as a corrected simulation result, and the control command determination unit is configured to generate a control command for the air-conditioning apparatus based on the corrected simulation result extracted by the result extraction unit.[Claim 2] The air-conditioning control device of claim 1, wherein the correction method selection unit is configured to determine whether the air-conditioning apparatus is in a thermo-on state or a thermo-off state based on the sensor data or the operational condition, and select a correction method for determining a correction amount of the calculation condition according to the determination result. [Claim 3] The air-conditioning control device of claim 1 or 2, wherein the correction execution unit is configured to calculate a correction amount of the calculation condition by multiplying a difference between the simulation result of the first target position extracted by the result extraction unit and the sensor data at the same position as the first target position by a coefficient having been set for each correction method.[Claim 4] The air-conditioning control device of any one of claims 1 to 3, wherein the correction method includes a first correction method that corrects a boundary condition regarding a temperature of an air outlet of the air-conditioning apparatus and a second correction method that corrects a boundary condition regarding a temperature of a wall surface of the target space or a surface temperature of an object disposed in the target space, and the correction method selection unit is configured to select the first correction method when the air-conditioning apparatus is in the thermo-on state and select the second correction method when the air-conditioning apparatus is in the thermo-off state.[Claim 5] The air-conditioning control device of any one of claims 1 to 4, wherein the result extraction unit extracts, as the simulation result of the first target position, the simulation result of the temperature at the air outlet of the air-conditioning apparatus when the air-conditioning apparatus is in the thermo-on state, and the simulation result of a temperature of the wall surface of the target space or a surface temperature of an object disposed in the target space when the air-conditioning apparatus is in the thermo-off state.[Claim 6] The air-conditioning control device of any one of claims 1 to 5, further comprising: a storage unit that stores a sensor position table in which an installation position of the sensor is determined for each combination of at least two items of the environmental condition and the operational condition included in the variable condition; and a sensor position derivation unit configured to acquire an installation position of the sensor from the sensor position table based on a combination of at least two items of the environmental condition and the operational condition included in the variable condition, wherein the result extraction unit extracts, instead of the simulation result of the first target position, the simulation result of a target position corresponding to the installation position of the sensor determined by the sensor position derivation unit from among the simulation results of the CFD analysis unit.[Claim 7] The air-conditioning control device of claim 6, further comprising: a sensor position table generation unit configured to generate the sensor positiontable,the sensor position table generation unit including a candidate generation unit configured to generate a sensor candidate position in the CFD model based on the invariable condition, the sensor candidate position being used to install a sensor that measures data of the target position to be used in calculation of the correction amount, a change rate comparison unit configured to obtain a temperature change rate in time-series temperature data for each sensor candidate position by using the simulation results performed by the CFD analysis unit for each combination of at least two items of the environmental condition and the operational condition included in the variable condition, a sensor position determination unit configured to determine an installation position for the sensor based on the temperature change rate obtained by the change rate comparison unit for each combination of at least two items of the environmental condition and the operational condition included in the variable condition, and a table generation unit configured to generate the sensor position table by associating the combination of at least two items of the environmental condition and the operational condition included in the variable condition with the installation position of the sensor determined by the sensor position determination unit.[Claim 8] The air-conditioning control device of claim 7, wherein when the sensor coordinate value is present in the invariable condition, the candidate generation unit is configured to set the sensor coordinate value as the sensor candidate position, and when the sensor coordinate value is not preset in the invariable condition, the candidate generation unit is configured to treat the CFD model as a rectangular parallelepiped and divides the CFD model into a plurality of areas to generate grid cells in the CFD model, and set a grid point of the grid cells as the sensor candidate position.[Claim 9] The air-conditioning control device of claim 7 or 8, wherein the change rate comparison unit is configured to obtain, as the temperature change rate, a temperature difference between a highest temperature and a lowest temperature in the time-series temperature data of each sensor candidate position, and outputs the sensor candidate position having a largest temperature difference and the sensor candidate position having a smallest temperature difference.[Claim 10] The air-conditioning control device of any one of claims 7 to 9, wherein the sensor position determination unit is configured to determine, as installation positions of the sensor, the sensor candidate position having the largest temperature change rate and the sensor candidate position having the smallest temperature change rate based on the temperature change rates obtained by the change rate comparison unit for each of the combinations of at least two items of the environmental condition and the operational condition included in the variable condition.