JP2002022238A - Comfortable feeling estimation device and air conditioning control device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a comfortable feeling estimation device capable of accurately estimating comfortable feeling of a human in view of warm heat from a warm heat environment factor around a human body, and provide an air conditioning control device capable of ensuring a comfortable warm heat environment based upon an estimation result of the warm heat comfortable feeling of a human. SOLUTION: A comfortable feeling estimation device comprises warm heat environment detection means 10 disposed in an automobile room, etc., for detecting a warm heat environment element around a human body, a human body heat model 10 connected with the warm heat environment detection means 10 for estimating skin temperature of a human body face part based upon a signal outputted by the warm heat environment detection means, warm feeling estimation means 12 for estimating whole body warm feeling such as hot and cold, etc., based upon the face part skin temperature estimated with the human body heat model 11 and its change rate, and comfortable feeling estimation means 13 for quantitatively estimating the level of comfortableness such as uncomfortable, no select, and comfortableness based upon a relationship between the whole body warm feeling and the comfortable feeling. Further, skin temperature of a specific location of a human body is estimated, and the level of the comfortableness is estimated on the basis of a relationship among the warm feeling of the specific location of a human body, the whole body warm feeling, and the comfortable feeling.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a comfort evaluation device and an air conditioning control device, and more particularly, to a thermal comfort (comfortable, uncomfortable) in a time and space complicated thermal environment such as a vehicle interior. The present invention relates to a comfort sensation evaluation device for estimating based on a human warm sensation (warm or cool) or a warm sensation distribution, and an air conditioning control device for controlling air conditioning based on the estimated thermal comfort to provide a comfortable thermal environment.

[0002]

2. Description of the Related Art Conventionally, the comfort level of air conditioning has been estimated from the correlation between a feeling of comfort and physical quantities such as air temperature.
It was generally estimated from the sense of temperature, such as hot or cold. For example, JP-A-7-98142 discloses that
An environment measurement unit for measuring environmental quantities such as wind temperature, wind speed, humidity, and solar radiation; and a temperature for calculating a human state quantity and a change rate of the human state quantity based on the environmental quantity and estimating a feeling of warmth based on these. A thermal sensation evaluation device including a sensation estimating means has been proposed.

In Japanese Patent Application Laid-Open No. Hei 8-189683, an indoor / outdoor environmental state and a human state detected by a sensor means, a history thereof, a remote control set temperature, and a vertical deflection blade position are input to a neural network model means. Then, a feeling of comfort corresponding to these combinations is estimated based on the learning result. An air conditioner control device that controls an air conditioner by generating a control signal for air conditioning using the estimation result has been proposed.

[0004] Japanese Patent Application Laid-Open No. 9-292149 discloses that
An air conditioner control method and an air conditioner that provide control means for an air conditioner that achieves both energy saving and improved comfort by setting the stop and operation times of the air conditioner so as not to impair comfort Has been proposed. In order to avoid compromising comfort, the present invention describes a method of periodically stopping and operating the air conditioner by setting the time to a predetermined value.

Japanese Patent Laid-Open No. 4-283340 discloses that
The physiological quantity of the individual corresponding to the external environment is calculated by a mathematical model of body temperature regulation, and the correlation between the calculated physiological quantity and the data of the sensation to the external environment is used to predict the sensation to the external environment, and based on the predicted value of the sensation. A comfortable environment design method for designing peripheral equipment for controlling an external environment has been proposed.

[0006]

However, in the apparatus described in Japanese Patent Application Laid-Open No. 7-98142, the human sense of temperature expressed by words such as "hot / cold" and "warm / cool" is estimated for each part. Yes, but there is no means to determine if the environmental conditions are comfortable for the occupant. Therefore, even if it is known whether the realized environment is hot or cold, it cannot be evaluated whether the occupants feel comfortable. Further, from the standpoint of evaluation of the air conditioner, no information is provided as to whether or not the design needs to be changed and whether or not the temperature control method needs to be changed.

In the apparatus described in Japanese Patent Application Laid-Open No. Hei 8-189683, what is estimated by the means for estimating a feeling of comfort is a predicted average vote number (PMV), a standard new effective temperature, and a surrounding wall radiation temperature. Among them, the predicted average number of votes is for estimating the sensation of the resident, and has the same problem as that of the above-described apparatus described in Japanese Patent Application Laid-Open No. 7-98142. Both the standard new effective temperature and the ambient wall radiation temperature are physical quantities indicating the thermal state of the environment, and do not directly estimate the human thermal comfort itself.

Further, the method described in Japanese Patent Application Laid-Open No. 9-292149 cannot respond to an unexpected temperature change during stoppage when the air-conditioning load fluctuates, so that comfort cannot be maintained. There's a problem.

In FIG. 1 and its description in Japanese Patent Application Laid-Open No. 4-283340, multiple regression analysis is performed by correlating seven types of physiological quantities with a sensory quantity (psychological quantity) database previously collected in subject experiments. Is performed to estimate the feeling of comfort by multiple regression analysis, but the database does not include physiological quantities, and no specific method for predicting comfort is disclosed. In addition, in this application, it is an essential component to have a database, but estimation of sensation by correlation between the calculated physiological quantity and the database is technically possible, but a huge database is required. There is a problem that it cannot be implemented practically.

SUMMARY OF THE INVENTION The present invention has been made in view of the above-mentioned problems of the prior art, and an object of the present invention is to provide a comfortable feeling evaluation capable of accurately estimating a human thermal comfort from a thermal environment element around a human body. It is to provide a device. Another object of the present invention is to provide an air-conditioning control device capable of providing a comfortable thermal environment based on the estimation result of human thermal comfort.

[0011]

According to the study of the present inventors, the comfort sensation depends not on the physiological quantity itself but on the state of the temperature sensation. The present inventors have found that they can be estimated by a simple mathematical model without having a simple database, and have completed the present invention.

In other words, the comfort evaluation apparatus according to the first aspect of the present invention comprises a thermal environment detecting means for detecting a thermal environment element around the human body, and a skin temperature of a specific part of the human body by a human body heat model based on the thermal environment element. A thermal sensation estimating means for estimating the whole body thermal sensation or the whole body thermal sensation and a specific part of the human body based on the estimated skin temperature; and And a comfort feeling estimating means for estimating a comfort feeling based on the feeling.

According to the first aspect of the present invention, when the thermal environment detecting means detects a thermal environment element around the human body, the thermal sensation distribution estimating means calculates a skin temperature of a specific part of the human body by a human body heat model based on the thermal environment element. Based on the estimated skin temperature, a whole body warm feeling or a whole body warm feeling and a warm feeling at a specific part of a human body are estimated. Next, the comfort sensation estimating means estimates the comfort sensation based on the whole body heat sensation or the whole body heat sensation and the heat sensation in a specific part of the human body. Thereby, from the thermal environment element around the human body detected by the thermal environment detecting means, the thermal sensation distribution estimating means can quantitatively estimate how a person feels as a warm and cool sensation. Thus, whether the environment is comfortable or not can be quantitatively estimated.

The comfort sensation estimating means uses a neural network that has learned the relationship between the whole body heat sensation and the comfort sensation or the relationship between the whole body heat sensation and the heat sensation of a specific part of the human body and the comfort sensation. The feeling can be quantitatively estimated.

An air conditioning control device according to a second aspect of the present invention includes a thermal environment detecting means for detecting a thermal environment element around a human body, and estimates a skin temperature of a specific part of a human body by a human body heat model based on the thermal environment element. A thermal sensation estimating means for estimating a whole body thermal sensation or a whole body thermal sensation based on the estimated skin temperature and a thermal sensation in a specific part of the human body; and A comfort sensation estimating means for estimating the comfort sensation and an air conditioning control means for controlling air conditioning based on the estimated comfort sensation.

According to the second aspect of the present invention, when the thermal environment detecting means detects a thermal environment element around the human body, the thermal sensation distribution estimating means calculates a skin temperature of a specific part of the human body by a human body heat model based on the thermal environment element. Based on the estimated skin temperature, a whole body warm feeling or a whole body warm feeling and a warm feeling at a specific part of a human body are estimated. Next, the comfort sensation estimating means estimates the comfort sensation based on the whole body warm sensation or the whole body warm sensation and the heat sensation at a specific part of the human body, and the air conditioning control means controls the air conditioning based on the comfort sensation of the air conditioning. Thereby, from the thermal environment element around the human body detected by the thermal environment detecting means, the thermal sensation distribution estimating means can quantitatively estimate how a person feels as a warm and cool sensation. Thus, whether the environment is comfortable or not can be quantitatively estimated. In addition, by controlling the air conditioning based on the quantitatively estimated comfort of the air conditioning, air conditioning control with high comfort can always be realized.

[0017] In the comfort evaluation device and the air conditioning control device, the thermal environment detecting means includes a wind speed sensor for detecting wind speed, a temperature sensor for detecting air temperature, a humidity sensor for detecting humidity, and a solar sensor for detecting the amount of solar radiation. And at least one sensor for detecting a thermal environment element around a human body installed in an automobile room, a house room, or the like.

The human body heat model divides the human body into parts such as the head, arms, torso, and legs, and regulates human body temperature such as the amount of clothes, activity level, sweating, and blood flow. The skin temperature, which is physiological information for estimating the thermal sensation based on the thermal environment element around the human body detected by the thermal environment detecting means, by calculating the heat balance between the human body and the environment while considering the characteristics of each reaction site It is a mathematical model for calculating each part of the human body.

[0019]

Embodiments of the present invention will be described below in detail with reference to the drawings. (First Embodiment) As shown in FIG. 1, a comfort evaluation apparatus according to a first embodiment detects a thermal environment element around a human body installed in an automobile room, a house room, or the like. A human body heat model 11 for estimating a skin temperature of a human body face based on a signal output from the thermal environment detection means 10 which is connected to the detection means 10 and the thermal environment detection means 10;
Based on the facial skin temperature estimated in step 1 and its rate of change,
The level of comfort such as uncomfortable, neither, or comfort is determined based on the warmth estimating means 12 for estimating the warmth of the whole body such as hot, cold, warm, and cool, and the relationship between the warmth of the whole body and the feeling of comfort. A comfortable feeling estimating means 13 for quantitatively estimating is provided. The comfort feeling estimating means 13 further includes a display device 14.
And the recording device 15 are connected.

The thermal environment detecting means 10 comprises a wind speed sensor and a temperature sensor, and detects a wind speed and a temperature every predetermined time τ.

The human body heat model 11 is calculated by calculating the heat balance between the human body and the environment, taking into account the characteristics of the human body temperature control response such as sweating and blood flow in the human face. It is a mathematical model for calculating a facial skin temperature, which is physiological information for estimating a whole body thermal sensation, based on wind speed and temperature, which are surrounding thermal environment elements.

The thermal sensation estimating means 12 detects the face part estimated this time.
Skin temperature T_skAnd the facial skin estimated this time
Warm T_skAnd the previously estimated face skin temperature T_sk-1From facial skin
Skin temperature change rate ΔT_skAnd calculate the estimated skin temperature of the face
T_skAnd facial skin temperature change rate ΔT _skAnd the following equation (1)
, And the whole body warmth S is quantitatively estimated.
That is, the warmth of the whole body is expressed numerically. However, A, B,
And C are constants.

S = A · (T _sk −B) + C · ΔT _sk Equation (1) Note that the whole-body temperature is a temperature sensation that is intuitively sensed by a human, and is focused on a specific part of the human body. Of a specific part of the human body. For example, if you feel "cool" immediately after entering an air-conditioned room from outside in the summer, the warmth of the whole body is the warmth of the toes that you feel still "hot" when you pay attention to the state of the toes (The warmth of a specific part of the human body).

The comfort sensation estimating means 13 previously stores a table shown in FIG. 2 showing the relationship between the whole body warm sensation S and the comfort sensation (comfort level) for all seasons. The level of comfort is estimated from the whole body warm feeling S estimated by the feeling estimating means 12.

The display device 14 displays the detected thermal environment factors around the human body, the estimated facial skin temperature, the estimated whole body temperature, and the estimated level of comfort. For example, as shown in FIG. 4, a time change of the estimated comfort level may be displayed on the display device 14. As can be seen from FIG. 4, the comfort level is divided into several stages (seven stages from −3 to +3 in the example shown in FIG. 4), and the estimated comfort level is expressed numerically and expressed quantitatively. I have. In this figure, the current comfort level is about halfway between "slightly uncomfortable" and "neither", and the level of comfort is about halfway between -1 and 0.

The recording device 15 stores the detected thermal environment factors around the human body, the estimated facial skin temperature, the estimated whole body warmth, and the estimated comfort level.

Next, with reference to the flowchart shown in FIG. 3, a human body heat model 1 of the comfort evaluation apparatus of the present embodiment will be described.
1. The processing operations of the warm feeling estimating means 12 and the comfort feeling estimating means 13 will be described together.

In step 100, when the wind speed and temperature detection signals detected by the wind speed sensor and the temperature sensor are input to the human body heat model 11, in step 102, the face skin is detected based on the detection signal by the human body heat model 11. Temperature is estimated.

In the next step 104, the estimated facial skin temperature _Tsk is input to the warm feeling estimating means 12 and stored in the warm feeling estimating means 12. In step 106, the thermal sensation estimating means 12 reads the previously estimated face skin temperature T _sk−1 , and _{calculates the currently} estimated face skin temperature T _sk and the previously estimated face skin temperature T _sk−. Skin temperature change rate Δ per predetermined time τ from ₁
T _sk is calculated, and in step 108, a calculation is performed from the _currently estimated face skin temperature T _sk and the rate of change in the face skin temperature ΔT _{sk according} to the above equation (1) to quantitatively estimate the whole body thermal sensation S. .

In the next step 110, when the estimated whole body warmth S is input to the comfort sensation estimating means 13, the comfort sensation estimating means 13 uses a table representing the relationship between the whole body warmth S and the comfort sensation. The level of comfort corresponding to the estimated whole body warmth S is estimated.

In the next step 112, the estimated level of comfort is output to the display device 14, and in step 114,
The estimated comfort level is output to the recording device 15.
Then, in step 116, after elapse of a predetermined time τ from the previous detection time, it is determined whether or not the end of the process has been instructed in the next step 118. Returning, a new wind speed and temperature are detected, and steps 100 to 118 are repeated.

As described above, in the present embodiment, based on the thermal environment element around the human body detected by the thermal environment detecting means, the characteristics of each part of the human body temperature regulation reaction using the human body heat model are considered. Calculate the facial skin temperature, which is physiological information for estimating whole body warmth by calculating the heat balance between the human body and the environment,
Using the calculated facial skin temperature and its rate of change, the whole body warm feeling is estimated by a predetermined relational expression, so that the whole body warm feeling, that is, how a person feels as a warm and cool feeling is quantified and quantified. Can be estimated.

Conventionally, the designer has appropriately determined the comfort according to the warm feeling, such as "comfortable when not warm or cool" and "comfortable when slightly cool". Focusing on the fact that there is a strong correlation between the feeling of comfort and the feeling of warmth of the body, the level of comfort is estimated based on the correlation between the feeling of comfort and feeling of comfort. It is possible to quantitatively estimate whether or not the environment is comfortable using a simple mathematical model without having a huge database as in the case of estimating a feeling of comfort from the values of elements.

In the above description, the level of comfort corresponding to the whole body warmth S is estimated using one type of table (for all seasons) showing the relationship between the whole body warmth S and the feeling of comfort shown in FIG. Examples have been described, but FIGS. 5 (A) and 5 (B)
As shown in FIG. 5, tables (for the cooling period and the heating period) representing the relationship between the whole body warmth S and the feeling of comfort are stored in advance for each of the cooling period and the heating period, and these two types of tables are selectively used. A level of comfort corresponding to the whole body warmth S may be estimated. In this case, the above step 110
In, determine whether the cooling period or the heating period, based on the table for the cooling period when it is determined that the cooling period, based on the table for the heating period when it is determined that the heating period,
Estimate the level of comfort for each.

When estimating the level of comfort corresponding to the whole body warmth S using the table for all seasons,
Accurate estimation can be limited to areas that are far outside the comfort range, such as "hot and uncomfortable" and "cold and uncomfortable", such as "hot" → "warm" → "neither" or "cold" → There is a problem that it is not possible to accurately estimate the feeling of comfort in a situation where the heat and cold of the whole body is mild, such as `` cool '' → `` neither '', but there are tables for the cooling period and tables for the heating period By properly using them, the feeling of comfort can be more accurately estimated. (Second Embodiment) A second embodiment is an example in which the air-conditioning control device of the present invention is applied to the control of an air conditioner installed in an automobile room, a house room, or the like. As shown in FIG.
The air-conditioning control device according to the embodiment is connected to a thermal environment detecting means 20 for detecting a thermal environment element around a human body, which is installed in an automobile room or a housing room in which an air conditioner is installed, and to a thermal environment detecting means 20. The human body heat model 21 for estimating the skin temperature of the face, upper body, and lower body of the human body based on the signal output from the thermal environment detecting means, the face skin temperature estimated by the human body heat model 21 and the rate of change thereof The body temperature is estimated based on the human body heat model 21 and the upper body skin temperature is estimated based on the human body heat model 21 and the rate of change thereof. The lower body skin temperature estimated by the human body heat model 21 and the rate of change are estimated. And a comfort feeling estimating means 23 for quantitatively estimating the comfort level of the air conditioner based on the relationship between the warm feeling and the feeling of comfort. Further, a control signal generating means 24 as an air conditioning control means is provided in the warm feeling estimating means 22 and the comfort feeling estimating means 23.
, And an air conditioner 25 to be controlled is connected to the control signal generating means 24.

The thermal environment detecting means 20 includes a thermal environment detecting means 20A installed near the head of the human body, a thermal environment detecting means 20B installed near the torso of the human body, and a thermal environment installed near the feet of the human body. It comprises a detecting means 20C. The thermal environment detecting means 20A to 20C are provided with a wind speed sensor, a temperature sensor, and a solar radiation sensor, respectively, and detect a wind speed, a temperature, and a solar radiation amount in the vicinity of the human head, the body, and the feet at predetermined time intervals τ. .

The human body heat model 21 is composed of the thermal environment detecting means 2
The face skin temperature, which is physiological information for estimating the whole body thermal sensation, and the upper body skin, which is physiological information for estimating the upper body thermal sensation, based on the wind speed, temperature, and the amount of solar radiation, which are thermal environment elements around the human body detected at 0 It is a mathematical model for calculating lower body temperature, which is physiological information for estimating temperature and lower body temperature.

The thermal sensation estimating means 22, like the thermal sensation estimating means 12 of the first embodiment, calculates the currently estimated face skin temperature, the currently estimated upper body skin temperature, and the currently estimated lower body skin temperature. The temperature is stored, and the rate of change in the skin temperature of the face, the rate of change in the temperature of the upper body skin, and the rate of change in the temperature of the lower body skin are calculated. In the present embodiment, the body temperature, the upper body temperature, and the lower body temperature are estimated using the three neural networks 26 to 28. As shown in FIG. 7A, the whole body thermal sensation is input using the neural network 26 that has learned the currently estimated face skin temperature and the relationship between the rate of change in the facial skin temperature and the whole body thermal sensation. It is quantitatively estimated from the facial skin temperature and the rate of change of the facial skin temperature.

As shown in FIG. 7 (B), the upper body temperature sensation is calculated by using the neural network 27 which has learned the upper body skin temperature estimated this time and the relationship between the upper body skin temperature change rate and the upper body temperature sensation. It is quantitatively estimated from the input upper body skin temperature and the upper body skin temperature change rate. Further, as shown in FIG. 7 (C), the lower body temperature sensation is quantitatively estimated using the neural network 28 that has learned the lower body skin temperature estimated this time and the relationship between the lower body skin temperature change rate and the lower body temperature sensation. Is done.

The comfort sensation estimating means 23 includes a neural network 29 shown in FIG. 9 which learns the relationship between the combination of the whole body heat sensation, the upper body heat sensation and the lower body heat sensation (heat sensation distribution pattern) and the comfort sensation. . As shown in FIG. 8, the relationship between the thermal sensation distribution pattern and the comfort sensation is that even when the user feels “neither (cool or warm)” in the whole body thermal sensation, the upper body thermal sensation and the lower body thermal sensation are different. Accordingly, the comfort is divided into an uncomfortable area, a neutral area, and a comfortable area. For example, "neither" for whole body warmth or upper body warmth
Even if you feel that the feet are cold and the lower body temperature feeling is "cold"
Under such circumstances, humans feel "discomfort".
Therefore, the neural network 29 has been learned in advance using the relationship shown in FIG. Comfort feeling estimation means 23
Is the neural network 2 as shown in FIG.
9, the comfort level of the air conditioning is estimated from the whole body temperature, the upper body temperature, and the lower body temperature that are estimated by the temperature estimation means 22.

The air conditioner 25 is an air conditioner in which the blowing temperature and the blowing air speed are variable. The control signal generating means 24 pre-stores an optimal warm feeling distribution pattern. The direction of the air outlet of the air conditioner 25 is changed in accordance with the distance of the thermal sensation distribution pattern from the optimum thermal sensation distribution pattern, and the air conditioner 25 is adjusted in accordance with the level of comfort of the air conditioning estimated by the comfort estimating means 23. A control signal for changing the blowing temperature and the blowing air volume stepwise is generated.

Next, with reference to the flowchart shown in FIG. 10, the human body heat model 21, the warm feeling estimating means 22, the comfortable feeling estimating means 23, and the control signal generating means 24 of the air conditioning comfort feeling evaluating apparatus of the present embodiment. Will be described together.

In step 200, the vicinity of the human head detected by the wind speed sensor, the temperature sensor, and the solar radiation sensor,
When the detection signals of the wind speed, temperature, and solar radiation near the torso and the feet are input to the human body heat model 21, step 202
Then, the human body heat model 21 estimates the face skin temperature, the upper body skin temperature, and the lower body skin temperature based on the detection signal.

In the next step 204, each of the estimated face skin temperature, upper body skin temperature and lower body skin temperature is inputted to the warm feeling estimating means 22 and stored in the warm feeling estimating means 22. Further, in step 206, the thermal sensation estimating means 22 reads the previously estimated face skin temperature, and calculates the predetermined time τ from the currently estimated face skin temperature and the previously estimated face skin temperature.
The rate of change in facial skin temperature per hit is calculated. Further, the upper body skin temperature change rate and the lower body skin temperature change rate are calculated in the same manner as in the case of the face skin temperature change rate.

In the next step 208, using the neural network, the whole body thermal sensation is quantitatively estimated from the currently estimated face skin temperature and the rate of change in the face skin temperature, and the currently estimated upper body skin temperature and upper body body temperature are estimated. The upper body temperature sensation is quantitatively estimated from the skin temperature change rate, and the lower body temperature sensation is quantitatively estimated from the lower body skin temperature and the lower body skin temperature change rate estimated this time.

In the next step 210, the estimated whole body warmth, upper body warmth and lower body warmth are estimated by the comfort feeling estimating means 23.
, The comfort feeling estimating means 23 estimates the air conditioning comfort level using a neural network. The level of comfort is divided into several levels, with 0 being neutral (neither), the minus side representing "discomfort" and the plus side representing "comfortable".

In the next step 212, it is determined whether or not the comfort level is 0 or more. If the comfort level is 0 or more, in step 214, the control signal generating means 24 A control signal for maintaining the state of the machine 25 at the current value is generated, and the process returns to step 200, and the operations of steps 200 to 212 are repeated until the comfort level becomes less than 0.

On the other hand, when the comfort level is less than 0,
In the next step 216, the control signal generating means 24 reads out the optimal thermal sensation distribution pattern stored in advance, and as shown in FIG. 11, the thermal sensation distribution pattern input from the thermal sensation estimating means 22 and the optimal thermal sensation distribution pattern. The thermal sensation distribution pattern is compared with the thermal sensation distribution pattern, and the thermal sensation having the largest difference from the optimal thermal sensation among the estimated whole body thermal sensation, upper body thermal sensation, and lower body thermal sensation is specified. In the example shown in FIG. 11, the estimated thermal sensation distribution pattern is closer to the lower temperature side than the optimal thermal sensation distribution pattern,
The largest difference between the estimated thermal sensation and the optimal thermal sensation is the lower body thermal sensation.

In the next step 218, a control signal for directing the air outlet of the air conditioner 25 to the lower body where the difference between the estimated warm feeling and the optimum warm feeling is the largest is generated.
Then, a control signal is generated to change the blowing temperature of the air conditioner 25 by one step to the high temperature side and change the blowing temperature of the air conditioner 25 by one step in a direction to increase the flow rate.

In the next step 222, it is determined whether or not the end of the process has been instructed. If the end has not been instructed, the process returns to step 200, where a new wind speed, temperature and solar radiation are detected, and step 200 is executed. Step 222 is repeated.

As described above, in the present embodiment, the whole body temperature, the upper body temperature sensation, and the body temperature are calculated by the neural network using each skin temperature calculated using the human body heat model and its rate of change.
Since the lower body temperature sensation is quantified and estimated, each temperature sensation can be quantitatively estimated.

In the past, the designer had appropriately determined the comfort according to the warm feeling, such as "it is comfortable that it is neither warm nor cool" or "it is comfortable that it is slightly cool", but in this embodiment, Focusing on the fact that there is a strong correlation between the thermal sensation distribution pattern and the comfort sensation, the level of air conditioning comfort is estimated using a neural network that has learned the relationship between this thermal sensation distribution pattern and the comfort sensation Therefore, it is possible to quantitatively estimate whether the environment is comfortable or not using a simple mathematical model without having a huge database as in the case of estimating the feeling of comfort from the value of the thermal environment element around the human body. it can.
Also, when estimating the comfort from the whole body warmth, if you look at each part, for example, "The cold body is warm and comfortable, but the feet are still cold and the comfort is shaved" In some cases, the level of comfort cannot be estimated with sufficient accuracy, but in the present embodiment, the level of comfort is estimated from the distribution pattern of thermal sensations of multiple parts of the human body, so that the level of comfort can be estimated more accurately. it can.

In addition, the air conditioner is controlled so that the air outlet of the air conditioner is directed to a portion requiring more air conditioning according to the distance of the estimated temperature distribution pattern from the optimum temperature distribution pattern. It is possible to perform air conditioning according to the thermal environment in which the air conditioner is operating, and to perform air conditioning control with high comfort. Further, since the air conditioner is controlled in accordance with the air conditioning comfort level accurately estimated by the comfort feeling estimating means, air conditioning control with high comfort can be always performed. (Third Embodiment) A third embodiment is another example in which the air-conditioning control device of the present invention is applied to control of an air conditioner installed in an automobile room, a house room, or the like. As shown in FIG. 12, the air-conditioning control device according to the third embodiment includes a thermal environment detection unit 30, a human body heat model 31, a thermal sensation estimation unit 32, and a comfortable sensation estimation, as in the second embodiment. Means 33, a control signal generating means 34, and an air conditioner 35.
4 is provided with an air-conditioning-part priority determining means 36 for determining a part in which air-conditioning is preferentially performed. Hereinafter, a description will be given focusing on differences from the air-conditioning control device of the second embodiment.

The thermal environment detecting means 30 includes a thermal environment detecting means 30A installed near the head of the human body, a thermal environment detecting means 30B installed near the torso of the human body, and a thermal environment installed near the arm of the human body. It comprises a detecting means 30C and a thermal environment detecting means 30D installed near the foot of the human body. Each of the thermal environment detecting means 30A to 30D includes a wind speed sensor, a temperature sensor, a solar radiation sensor, and a humidity sensor, and the wind speed, the temperature near the human body, the vicinity of the torso, the vicinity of the arm, and the vicinity of the foot every predetermined time τ. , Solar radiation, and humidity are detected.

The human body heat model 31 includes the thermal environment detecting means 3
Based on the wind speed, temperature, insolation, and humidity, which are the thermal environment elements around the human body detected at 0, the physiological information for estimating the skin temperature of the face, the physiological information for estimating the body temperature, and the physiological information for estimating the body temperature It is a mathematical model for calculating a certain torso skin temperature, an arm skin temperature which is physiological information for estimating an arm temperature sensation, and a foot skin temperature which is physiological information for estimating a foot temperature sensation.

The thermal sensation estimating means 32, like the thermal sensation estimating means 22 of the second embodiment, stores the currently estimated face skin temperature and calculates the rate of change in the face skin temperature, and estimates the currently estimated face skin temperature. Quantitatively the whole body thermal sensation from the facial skin temperature and the facial skin temperature change rate that was input using the neural network 37 that learned the relationship between the facial skin temperature and the rate of facial skin temperature change and the whole body thermal sensation presume. In addition, in the same manner as described above for the torso, arm, and foot, the skin temperature of the specific part estimated this time is stored and the skin temperature change rate of the specific part is calculated,
As shown in FIG. 13, the input is performed using the neural network 37 that has learned the relationship between the skin temperature of the specific part estimated this time and the skin temperature change rate of the specific part and the thermal sensation of the specific part. The thermal sensation at the specific site is quantitatively estimated from the skin temperature at the specific site and the skin temperature change rate at the specific site.

The comfort sensation estimating means 33 generates the neural network 38 which has learned the relationship between the combination of the whole body heat sensation, the body heat sensation, the arm heat sensation and the foot heat sensation (heat sensation distribution pattern) and the comfort sensation. As shown in FIG. 14, the neural network 38 is used to
, Body temperature, arm temperature, arm temperature,
And the comfort level of the air conditioning is estimated from the foot warmth.

The air-conditioning section priority determining means 36 determines the whole body temperature when estimating a feeling of comfort with the neural network 38,
The contribution of each of the body warmth, the arm warmth, and the foot warmth is analyzed. Head, 2. 2. torso, 3. foot,
The priority order is determined in the descending order of contribution, such as the arms. It is determined whether the numerical value representing the thermal sensation estimated in the descending order of priority is near the neutral region that is neither hot nor cold, and is related to the thermal sensation that is initially found not to be near the neutral region. The part is extracted as the air conditioning priority part.

The control signal generating means 34 controls the air conditioner 3 according to the air conditioning priority part extracted by the air conditioning part priority determining means 36.
5, the control signal for changing the outlet temperature and the outlet air volume of the air conditioner 35 stepwise in accordance with the air conditioning comfort level estimated by the comfort feeling estimating means 33 is generated. .

Next, with reference to the flowchart shown in FIG. 15, a human body heat model 31, a warm feeling estimating means 32, a comfortable feeling estimating means 33, a control signal generating means 34 of the air conditioning comfort feeling evaluating apparatus of the present embodiment. The processing operation of the air conditioning part priority determination means 36 will be described together.

In steps 300 to 310, the comfort level of the air conditioning is estimated in the same manner as in steps 200 to 210 of the second embodiment. The level of comfort is divided into several levels, with 0 being neutral, a minus side representing "discomfort" and a plus side representing "comfortable". Next step 312
It is determined whether or not the comfort level is 0 or more, and if the comfort level is 0 or more, step 314 is executed.
Then, the control signal generating means 34 generates a control signal for maintaining the state of the air conditioner 35 at the current value, and
And the operations of steps 300 to 312 are repeated until the comfort level becomes less than 0.

On the other hand, when the comfort level is less than 0,
In the next step 316, the air-conditioning part priority determination means 36
Extracts an air-conditioning priority site where air-conditioning should be performed with priority.
In the next step 318, the control signal generating means 34 generates a control signal for directing the air outlet of the air conditioner 35 to the extracted air conditioning priority portion.
The air outlet temperature of the air conditioner 35
A control signal for changing the amount of air blown by one step in a direction to increase the amount of blown air is generated. In the next step 322, it is determined whether or not the end of the process has been instructed. If the end has not been instructed, the process returns to step 300, and steps 200 to 222 are repeated.

As described above, in the present embodiment, the whole body temperature, body temperature, arm temperature, and foot temperature are detected by a neural network using each skin temperature and its change rate calculated using the human body heat model. Since the temperature of each part is quantified and estimated,
Each warm feeling can be estimated quantitatively.

Focusing on the fact that there is a strong correlation between the thermal sensation distribution pattern and the comfort sensation, using a neural network that has learned the relationship between the thermal sensation distribution pattern and the comfort sensation, the comfort sensation of air conditioning is obtained. , It is possible to quantitatively estimate whether the environment is comfortable or not by using a simple mathematical model without having a huge database.

Further, since the comfort level is estimated from the thermal distribution pattern of a plurality of parts of the human body subdivided into the torso, the arms, and the feet, the level of comfort can be estimated with higher accuracy. In addition, the part of the human body for estimating the thermal sensation is not limited to the torso, the arms, and the feet, but the torso, the back, the arms, the thighs, the lower thighs,
You may further subdivide, such as a toe part. In that case, the estimation accuracy of the feeling of comfort can be further improved.

In addition, the contribution of each thermal sensation when estimating a comfortable sensation by the neural network is analyzed, and the air-conditioning priority part is extracted in consideration of the contribution, and the air-conditioner blows out to the part that needs more air-conditioning. Since the control is performed so that the mouth is turned, air conditioning according to the thermal environment where the human body is placed can be performed, and air conditioning control with high comfort can be performed. Further, since the air conditioner is controlled in accordance with the air conditioning comfort level accurately estimated by the comfort feeling estimating means, air conditioning control with high comfort can be always performed. (Fourth Embodiment) The fourth embodiment is still another example in which the air-conditioning control device of the present invention is applied to the control of an air conditioner installed in an automobile room, a house room, or the like. As shown in FIG. 16, the air-conditioning control device according to the fourth embodiment includes a thermal environment detecting unit 40, a human body heat model 41, a thermal sensation estimating unit 42, and a comfortable sensation estimation, as in the second embodiment. Means 43, a control signal generating means 44, and an air conditioner 45, which are connected to the comfort sensation estimating means 43 and the control signal generating means 44 to determine whether to stop operating the air conditioner. Means 46 are provided. Hereinafter, a description will be given focusing on differences from the air-conditioning control device of the second embodiment.

As shown in FIG. 17, the air conditioner operation stop judging means 46 stores a judgment logic for determining whether to continue or stop the operation of the air conditioner according to the level of comfort. Based on this determination logic, it is determined whether to continue or stop the operation of the air conditioner according to the comfort level of the air conditioning estimated by the comfort feeling estimation means 43.

The control signal generating means 44 generates a control signal for continuing or stopping the operation of the air conditioner 45 in accordance with the judgment of the air conditioner operation stop judging means 46.

Next, with reference to the flow chart shown in FIG. 19, the human body heat model 41, the warm feeling estimating means 42, the comfortable feeling estimating means 43, the control signal generating means 44 of the air conditioning comfort feeling evaluating apparatus of the present embodiment. The processing operation of the air conditioner operation stop determination means 46 will be described together.

In steps 400 to 410, the comfort level of the air conditioning is estimated in the same manner as in steps 200 to 210 of the second embodiment. The level of comfort is divided into several levels, with 0 being neutral, a minus side representing "discomfort" and a plus side representing "comfortable". Next step 412
It is determined whether the comfort level is equal to or greater than 0, and if the comfort level is less than 0, the process proceeds to step 414.
Then, the air conditioner operation stop determination means 46 determines to continue the operation of the air conditioner based on the determination logic. Based on the judgment of the air conditioner operation stop judging means 46, the control signal generating means 44 generates a control signal for maintaining the state of the air conditioner 45 at the current value, and returns to step 400 to reduce the comfort level. Steps 400 to 41 until 0 or more
Step 2 is repeated.

On the other hand, when the comfort level becomes 0 or more,
In the next step 416, the air conditioner operation stop judging means 46
Determines that the operation of the air conditioner should be stopped based on the determination logic. Based on the judgment of the air conditioner operation stop judging means 46, the control signal generating means 44 generates a control signal for stopping the air conditioner 45. Next step 418
It is determined whether the end of the process has been instructed. If the end has not been instructed, the process returns to step 400, and
Steps 00 to 418 are repeated.

FIG. 18A shows a temporal change in the estimated comfort level, and FIG. 18B shows a control signal for operating or stopping the air conditioner 45. As can be seen from both figures, when performing power-saving air-conditioning by turning on and off the air conditioner according to the estimated level of comfort, the estimated value of the level of comfort also converges to substantially zero.

As described above, in the present embodiment, the whole body temperature, body temperature, arm temperature, and foot temperature are detected by a neural network using each skin temperature and its rate of change calculated using the human body heat model. Since the temperature of each part is quantified and estimated,
Each warm feeling can be estimated quantitatively.

Focusing on the fact that there is a strong correlation between the distribution pattern of warmth and the feeling of comfort, the comfort of air conditioning is learned using a neural network that has learned the relationship between the distribution pattern of warmth and comfort. , It is possible to quantitatively estimate whether the environment is comfortable or not by using a simple mathematical model without having a huge database.

Further, in the present embodiment, the comfort level is estimated from the distribution pattern of the thermal sensations of a plurality of parts of the human body, so that the level of the comfort level can be more accurately estimated.

Further, since the air conditioner is controlled in accordance with the air conditioning comfort level accurately estimated by the comfort feeling estimating means, it is possible to perform power-saving air conditioning by turning on and off the air conditioner without impairing comfort. .

[0077]

The comfort evaluation apparatus of the present invention quantitatively estimates how the human perceives the thermal environment around the human body detected by the thermal environment detecting means as a feeling of warm and cool by the thermal sensation distribution estimating means. In addition to this, it is possible to quantitatively estimate whether or not the environment is comfortable by the comfort feeling estimating means.

The air-conditioning control device of the present invention controls the air-conditioning based on the thermal comfort sensation quantitatively estimated by the comfort sensation estimating means, thereby realizing air-conditioning control with high comfort at all times. It has the effect of being able to.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a schematic configuration of a comfort evaluation apparatus according to a first embodiment.

FIG. 2 is a table showing a relationship between a whole body warm feeling S and a feeling of comfort stored in advance in a feeling of comfort estimating means.

FIG. 3 is a flowchart illustrating a processing operation of a main part of the comfort evaluation device according to the first embodiment;

FIG. 4 is a schematic diagram showing a temporal change of an estimated comfort level displayed on a display device.

FIGS. 5A and 5B are tables showing the relationship between the whole body warm feeling S and the comfort sensation stored in the comfort sensation estimating means in advance.

FIG. 6 is a block diagram illustrating a schematic configuration of an air-conditioning control device according to a second embodiment.

FIGS. 7A to 7C are schematic diagrams illustrating input / output relations of a neural network of a feeling sensation estimating unit according to a second embodiment.

FIG. 8 is a schematic diagram showing a relationship between a warm feeling distribution pattern and comfort.

FIG. 9 is a schematic diagram illustrating an input / output relationship of a neural network of a comfort feeling estimating unit according to the second embodiment.

FIG. 10 is a flowchart illustrating a processing operation of a main part of an air conditioning control device according to a second embodiment.

FIG. 11 is a diagram comparing an estimated thermal sensation distribution pattern with an optimal thermal sensation distribution pattern.

FIG. 12 is a block diagram illustrating a schematic configuration of an air-conditioning control device according to a third embodiment.

FIG. 13 is a schematic diagram illustrating an input / output relationship of a neural network of a thermal sensation estimating unit according to the third embodiment.

FIG. 14 is a schematic diagram illustrating an input / output relationship of a neural network of a comfort feeling estimating unit according to the third embodiment.

FIG. 15 is a flowchart illustrating a processing operation of a main part of an air conditioning control device according to a third embodiment.

FIG. 16 is a block diagram illustrating a schematic configuration of an air-conditioning control device according to a fourth embodiment.

FIG. 17 is a schematic diagram showing a determination logic for determining in advance whether to continue or stop the operation of the air conditioner according to the level of comfort.

18A is a diagram showing a temporal change in an estimated comfort level, and FIG. 18B is a diagram showing a control signal for operating or stopping an air conditioner.

FIG. 19 is a flowchart illustrating a processing operation of a main part of the air-conditioning control device according to the third embodiment.

[Explanation of symbols]

 10, 20, 30, 40 Thermal environment detecting means 11, 21, 31, 41 Human body heat model 12, 22, 32, 42 Warm feeling estimating means 13, 23, 33, 43 Comfort feeling estimating means 14 Display device 15 Recording device 24 , 34, 44 control signal generating means 25, 35, 45 air conditioner 36 air conditioning part priority determining means 46 air conditioner operation stop determining means

 ────────────────────────────────────────────────── ─── Continued on the front page (72) Inventor Katsuya Ibaraki 41-Cho, Yokomichi, Nagakute-cho, Aichi-gun, Aichi Prefecture Inside Toyota Central Research Laboratory, Inc. (72) Inventor Koichi Kurazono Nagakute-cho, Aichi-gun, Aichi Prefecture No. 41, Yojimichi, Chumoji, F-term in Toyota Central R & D Laboratories Co., Ltd. (Reference) 3L060 AA05 CC01 CC11 DD02 EE45 3L061 BA01 BA07

Claims (2)

[Claims] A thermal environment detecting means for detecting a thermal environment element around a human body; estimating a skin temperature of a specific part of a human body by a human body heat model based on the thermal environment element; and a whole body based on the estimated skin temperature. A thermal sensation estimating means for estimating a thermal sensation or a whole body thermal sensation and a thermal sensation at a specific part of the human body; and a comfort sensation estimation for estimating a comfortable sensation based on the whole body thermal sensation or the whole body thermal sensation and the thermal sensation at a specific part of the human body. Means for evaluating comfort. 2. A thermal environment detecting means for detecting a thermal environment element around a human body, a skin temperature of a specific part of a human body is estimated by a human body heat model based on the thermal environment element, and a whole body is estimated based on the estimated skin temperature. A thermal sensation estimating means for estimating a thermal sensation or a whole body thermal sensation and a thermal sensation at a specific part of the human body; and a comfort sensation estimation for estimating a comfortable sensation based on the whole body thermal sensation or the whole body thermal sensation and the thermal sensation at a specific part of the human body. And an air conditioning control unit for controlling air conditioning based on the estimated feeling of comfort.