EP2944891B1 - Programme, dispositif d'estimation de température ambiante - Google Patents

Programme, dispositif d'estimation de température ambiante Download PDF

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Publication number
EP2944891B1
EP2944891B1 EP14738327.7A EP14738327A EP2944891B1 EP 2944891 B1 EP2944891 B1 EP 2944891B1 EP 14738327 A EP14738327 A EP 14738327A EP 2944891 B1 EP2944891 B1 EP 2944891B1
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EP
European Patent Office
Prior art keywords
room temperature
outside air
air temperature
prediction
prediction formula
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EP14738327.7A
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German (de)
English (en)
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EP2944891A1 (fr
EP2944891A4 (fr
Inventor
Atsushi Mise
Naoki Muro
Keiichi Maruyama
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Panasonic Intellectual Property Management Co Ltd
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Panasonic Intellectual Property Management Co Ltd
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/89—Arrangement or mounting of control or safety devices
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
    • F24F11/63—Electronic processing
    • F24F11/64—Electronic processing using pre-stored data
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F2110/00—Control inputs relating to air properties
    • F24F2110/10—Temperature
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F2110/00—Control inputs relating to air properties
    • F24F2110/10—Temperature
    • F24F2110/12—Temperature of the outside air

Definitions

  • the invention relates to a room temperature estimating device configured to estimate a room temperature at a target date and time, and a program that causes a computer to function as the room temperature estimating device.
  • Document 1 discloses a technique of measuring the room temperature as environmental information, and estimating the temporal change in the room temperature based on a history of the measured room temperatures.
  • Document 1 also discloses a technique of determining an operation start time and a heating start time of a heater, based on the estimated temporal change in the room temperature and the outside air temperature, required amount of heat for room heating (hereafter, called "heating road energy"), and heating capability of the heater.
  • heat road energy required amount of heat for room heating
  • the room temperature is estimated in order to calculate the heating road energy.
  • the room temperature is estimated based on the history data of the room temperature.
  • Document 1 does not disclose a technique for estimating the room temperature using another factor which the room temperature depends on.
  • Document 2 discloses a technique of measuring the room temperature and the outside air temperature as environmental information, and estimating a in-vehicle space temperature based on the measured in-vehicle space temperature and the measured outside air temperature along with the estimated amount of sun light.
  • the configuration described in Document 2 is directed to estimate the in-vehicle space temperature.
  • the in-vehicle space temperature follows the outside air temperature in short time when the outside air temperature changes. Therefore, it is relatively easy to estimate the in-vehicle space temperature based on the outside air temperature and the amount of sun light.
  • the temperature in a building room depends on the thermal characteristics, such as heat insulating property, of the room, and does not immediately change when the outside air temperature changes. It is therefore difficult to estimate a room temperature in a building from the outside air temperature, based on the technique described in Document 2.
  • CN 101 929 721 A describes a predicting method of a central air conditioner energy-conservation control autoregressive (AR) model load predicting system, which relates to the technical field of central air conditioners and solves the technical problem of energy-conservation control.
  • AR autoregressive
  • the method comprises the following steps: 1) acquiring the on-site heating and ventilating data of an air conditioner and indoor and outdoor temperatures, preprocessing the heating and ventilating data and the indoor and outdoor temperature data and storing the pre-processed data and indoor and outdoor temperature data in a real database; 2) setting the time length of a prediction period according to the indoor and outdoor temperature gradient value and the time lag of the cold supply of the air conditioner in a real-time database;; and 3) building an AR model according to the data in a relationship database and the time length of the prediction period, and predicting loads according to the AR model.
  • JP H11 23037 A describes a heated and cooled air outputting device to output the heated/cooled air into a dwelling space by one of the coldness and heat of at least a heat source machine and a regenerative device.
  • the outside temperature is detected as the time series data by an outside temperature time series data detecting means, and the outside temperature time series data is analyzed to estimate the temperature curve.
  • the demanded terminal load is estimated from the estimation temperature curve.
  • JP 2009 069080 A describes that a measuring target is changed in its thickness and temperature accompanied by the elapse of time is increased and decreased from an aspect of calculation on the basis of the thickness of the known data not only to calculate heat history with respect to a plurality of the increased and decreased thicknesses but also to measure the temperatures of respective regions obtained by dividing the analyzing area set to the surface of the measuring target into a plurality of regions.
  • the temperature of one region of the respective regions is measured only for a predetermined time and the thickness of the measuring target is specified on the basis of the measured value to estimate the future temperature of the measuring target with the specified thickness.
  • US 2005/192915 A describes a system for forecasting predicted thermal loads for a building that comprises a thermal condition forecaster for forecasting weather conditions to be compensated by a building environmental control system and a thermal load predictor for modeling building environmental management system components to generate a predicted thermal load for a building for maintaining a set of environmental conditions.
  • the thermal load predictor is a neural network and, preferably, the neural network is a recurrent neural network that generates the predicted thermal load from short-term data.
  • the recurrent neural network is trained by inputting building thermal mass data and building occupancy data for actual weather conditions and comparing the predicted thermal load generated by the recurrent neural network to the actual thermal load measured at the building.; Training error is attributed to weights of the neurons processing the building thermal mass data and building occupancy data.
  • An object of the invention is to provide a room temperature estimating device for estimating a temperature of a room in a building based on measured environmental information, without complicated computer simulation, and to provide a program that causes a computer to function as the room temperature estimating device.
  • a room temperature estimating device is disclosed in claim 1.
  • the prediction formula producer is configured to produce, as the prediction formula, at least first and second prediction formulae respectively corresponding to at least first and second specified times.
  • the first prediction formula is produced based on pieces of the room temperature data and pieces of the outside air temperature data corresponding to the first specified time in each of the two or more days during the given extraction period.
  • the second prediction formula is produced based on pieces of the room temperature data and pieces of the outside air temperature data corresponding to the second specified time in each of the two or more days during the given extraction period.
  • the room temperature estimator is configured to estimate a room temperature at a first target time corresponding to the first specified time by applying an outside air temperature at the first target time to the first prediction formula, and to estimate a room temperature at a second target time corresponding to the second specified time by applying an outside air temperature at the second target time to the second prediction formula.
  • the prediction formula producer is configured to produce, as the prediction formula, a regression formula from pieces of the room temperature data and pieces of the outside air temperature data.
  • the prediction formula producer is configured to produce the prediction formula by a simple linear regression analysis involving the outside air temperature data as an independent variable and the room temperature data as a dependent variable.
  • the extraction period is included in any one of division periods which a period of one year is divided into based on climatic environment.
  • the room temperature estimator is configured to apply, to prediction of a room temperature in a certain division period, a prediction formula produced based on pieces of the room temperature data and pieces of the outside air temperature data during an extraction period included in the certain division period.
  • the room temperature estimating device further includes a correction information obtainer configured to obtain correction information corresponding to one state that has been selected from two or more states.
  • the correction information is besides the outside air temperature and affects the room temperature.
  • the prediction formula producer is configured to correct the prediction formula according to the state of the correction information obtained by the correction information obtainer, and thereby to produce a corrected prediction formula.
  • the room temperature estimator is configured to estimate the room temperature based on the corrected prediction formula.
  • the room temperature estimating device further includes an information outputter configured to transmit the room temperature estimated by the room temperature estimator to an informing device.
  • the outside air temperature obtainer is configured to obtain outside air temperature data provided through a telecommunication network.
  • a program according to the invention is configured to cause a computer to function as the room temperature estimating device according to any of above described room temperature estimating devices.
  • a heat insulating property of a room is unique characteristics for a residence, and it may be possible to roughly estimate the heat insulating property of the room based on the building materials of the residence, the construction method of the residence, and the like. However, it is not easy to quantitatively determine the heat insulating property of the room. Also, although it is possible to count the number of people in the room, it is difficult to theoretically determine the relation between the room temperature and the number of people in the room because the degree of influence on the increase in the room temperature differs between persons depending on their metabolic rate, amount of clothing, and the like. Also, it is possible to monitor the sun light, the air ventilation and the rain fall, but it is not easy to theoretically determine the influence thereof on the room temperature.
  • Embodiment 1 a technique of estimating a room temperature based only on an outside air temperature is explained.
  • Embodiment 2 a technique of estimating a room temperature based on an outside air temperature taking into account the heat insulating property of the room.
  • Embodiment 3 a technique of estimating a room temperature taking into account of influence of the sun light, the air ventilation, the rain fall and the number of people in the room.
  • a room temperature estimating device 10 of the present embodiment is configured to estimate a room temperature at a target date and time from an outside air temperature, based on a prediction formula that relates the outside air temperature and the room temperature. Therefore, the room temperature estimating device 10 includes a structure configured to produce the prediction formula and a structure configured to estimate a room temperature from an outside air temperature based on the prediction formula.
  • the room temperature estimating device 10 includes a device including a processor configured to execute programs to achieve below described functions, and a device for an interface, as main hardware components.
  • the device including the processor may be a microcomputer with a built-in memory, a processor with an attached external memory, or the like.
  • a computer that executes programs for achieve the below described functions may function as the room temperature estimating device 10.
  • Such kind of programs may be provided through a computer-readable storage medium, or be provided by communication via a telecommunication network.
  • the room temperature estimating device 10 includes a room temperature obtainer 11 configured to obtain room temperature data (measured values) from a room temperature meter 21, and an outside air temperature obtainer 12 configured to obtain outside air temperature data (measured values) from an outside air temperature meter 22.
  • the room temperature estimating device 10 further includes a storage 13, a clock 14, and a prediction formula producer 15.
  • the storage 13 is configured to store the room temperature data (measured values) and the outside air temperature data (measured values) with each piece of the room temperature data and the outside air temperature data associated with a corresponding measured date and time.
  • the clock 14 is configured to measure the current date and time.
  • the prediction formula producer 15 is configured to produce two or more prediction formulae corresponding to respective two or more times of day.
  • the room temperature meter 21 is installed in a room of a building, and is configured to measure a temperature where the room temperature meter 21 is installed (i.e., measure a room temperature).
  • the outside air temperature meter 22 is installed outside the building, and is configured to measure a temperature where the outside air temperature meter 22 is installed (i.e., measure an outside air temperature).
  • Each of the room temperature meter 21 and the outside air temperature meter 22 includes a temperature sensor configured to generate an analog output that reflects an ambient temperature, such as a thermistor, and a sensor amplifier configured to amplify the output of the temperature sensor.
  • Each of the room temperature meter 21 and the outside air temperature meter 22 further includes a converter configured to convert the output of the sensor amplifier into digital data, and a communicator configured to transmit the digital data of the converter to the room temperature estimating device 10.
  • Each of the room temperature meter 21 and the outside air temperature meter 22 may not include the communicator or may not include the converter and the communicator. However, in view of transmitting measured values precisely to the room temperature estimating device 10, each of them desirably includes the converter and the communicator. In the case where the converter is not provided, the room temperature meter 21 and/or the outside air temperature meter 22 provide analog data to the room temperature estimating device 10.
  • Communication between the room temperature meter 21 or the outside air temperature meter 22 and the room temperature estimating device 10 is performed desirably through a wireless communication channel with a radio wave used as transmission medium, or through a wired communication channel.
  • the room temperature meter 21 may share a casing with the room temperature estimating device 10. In the structure where the room temperature meter 21 shares the casing with the room temperature estimating device 10, the room temperature meter 21 is not necessarily to include the communicator.
  • the room temperature data (measured values) obtained by the room temperature obtainer 11 and the outside air temperature data (measured values) obtained by the outside air temperature obtainer 12 are stored in the storage 13 with each piece of the room temperature data and the outside air temperature data associated with a corresponding measured date and time. That is, the storage 13 is configured to store two kinds of sets of two information pieces, i.e., (room temperature, date and time) and (outside air temperature, date and time); or store sets of three information pieces, i.e., (room temperature, outside air temperature, date and time). The latter case is smaller in the data amount, and can save the capacity of the storage 13.
  • the date and time to be stored in the storage 13 is measured by the clock 14 provided in the room temperature estimating device 10. Dates and times at which the room temperature data and the outside air temperature data are to be obtained are preset in the room temperature obtainer 11 and the outside air temperature obtainer 12, respectively.
  • the room temperature obtainer 11 and the outside air temperature obtainer 12 are configured to obtain room temperature data and outside air temperature data at each of the preset dates and times, respectively, based on the current date and time measured by the clock 14. In this configuration, it is desirable that the storage 13 is configured to store the sets of three information pieces, (room temperature, outside air temperature, date and time).
  • each of the room temperature obtainer 11 and the outside air temperature obtainer 12 is configured to obtain data for each hour.
  • each of the room temperature obtainer 11 and the outside air temperature obtainer 12 is configured to obtain data at each hour.
  • the room temperature obtainer 11 and the outside air temperature obtainer 12 is not necessarily to be configured to obtain data for each hour, but may obtain data for each 10 minutes, each 15 minutes, each 30 minutes, each two hours, or the like, one of which may be selected as needed. The shorter the time intervals are, the larger amount of information is obtained, which would increase the estimation accuracy of the prediction formula. However, this causes increase in the data amount to be stored in the storage 13.
  • the time intervals for obtaining data be set to a period around one hour, and be set in a range from a fraction of one hour to several hours.
  • Each of the intervals for obtaining data by the room temperature obtainer 11 and the outside air temperature obtainer 12 is preferably set to a value obtained by dividing 24 hours by an integer.
  • Each of the room temperature meter 21 and the outside air temperature meter 22 may include a dedicated clock configured to measure the current date and time.
  • the room temperature meter 21 and the outside air temperature meter 22 are configured to obtain the room temperature data and the outside air temperature data based on the dates and times measured by their own clocks, respectively, and transmit the obtained data to the room temperature estimating device 10.
  • the room temperature meter 21 and the outside air temperature meter 22 are configured to transmit their respective room temperature data and outside air temperature data to the room temperature estimating device 10 with pieces of the room temperature data and the outside air temperature data associated with the corresponding date and time measured by their own clocks, respectively.
  • the storage 13 is configured to store the two kinds of sets of two information pieces, i.e., (room temperature, date and time) and (outside air temperature, date and time).
  • each of the room temperature meter 21 and the outside air temperature meter 22 is not limited to be configured to transmit the room temperature data or the outside air temperature data at that time the room temperature or the outside air temperature is measured, but may be configured to transmit a collection of data over a half day, or one day.
  • the inventors have measured room temperatures and outside air temperatures at two or more times per day during a relatively long period. Then, by analyzing graphically a relation between room temperatures and outside air temperatures for each of the two or more times, the inventors have found that the outside air temperatures and the room temperatures show a linear relation at a specified time, as shown in FIG. 2 . That is, it has found that a room temperature at a specified time can be represented by a prediction formula of a linear function involving the outside air temperature as a variable, and that a room temperature can be estimated from an outside air temperature based on the prediction formula.
  • the outside air temperature and the room temperature measured at a first specified time in each of two or more days show a linear relation
  • the outside air temperature and the room temperature measured at a second specified time in each of the two or more days show a linear relation
  • the prediction formula producer 15 is configured to produce the prediction formula based on the outside air temperature and the room temperature at a specified time in each of two or more days.
  • the prediction formula producer 15 is configured to extract pieces of the room temperature data and pieces of the outside air temperature data corresponding to a specified time in each of two or more days during a given extraction period, which are stored in the storage 13, to produce a regression formula from the pieces of the room temperature data and the pieces of the outside air temperature data corresponding to the same time in each of two or more days, and to employ the regression formula as the prediction formula.
  • the room prediction formula producer 15 is configured, based on the pieces of the room temperature data and the pieces of the outside air temperature data corresponding to the specified time (the same time) in each of two or more days during the given extraction period, which are stored in the storage 13, to produce the prediction formulae expressing a relation between the pieces of the room temperature data and the pieces of the outside air temperature data at the specified time.
  • the pieces of the room temperature data and the pieces of the outside air temperature data for producing the prediction formula should include pieces of data for three or more days. Therefore, the extraction period should be three or more days, and be selected from a range of 15 to 90 days, for example.
  • the lower limit of the range, 15 days corresponds to one period of 24 seasons in the solar year (a half month)
  • the upper limit of the range, 90 days corresponds to one season, i.e., the spring, the summer, the autumn, or the winter.
  • the days of the period is an example, and may be 30 days (about one month), or may be one year if the outside air temperature is not so changed over year.
  • the days for obtaining data for producing the prediction formula may include consecutive days, or may be discontinuous days.
  • the prediction formula may be produced based on the room temperature data and the outside air temperature data measured: every day; or every second day; or every week, over one or more years.
  • a linear function is produced from the pieces of the room temperature data ⁇ 1(t) and the pieces of the outside air temperature data ⁇ 2(t), based on a known calculation method such as least-square method. That is, the prediction formula producer 15 is configured to produce a regression prediction formula from the pieces of the room temperature data ⁇ 1(t) and the pieces of the outside air temperature data ⁇ 2(t) corresponding to the target time (the specified time) during the extraction period.
  • the regression prediction formula involves the outside air temperature at a specified time as the explanatory variable and the room temperature at the specified time as the dependent variable.
  • the prediction formula producer 15 is configured to produce the prediction formula by a simple linear regression analysis involving the outside air temperature data as the independent variable and the room temperature data as the dependent variable.
  • the time of day (specified time) for producing the regression prediction formula is selected from a time period during which the room temperature is not affected by the sun light and relies only on the outside air temperature, but the variation of the outside air temperature is relatively gentle.
  • the prediction formula producer 15 is configured to employ the produced regression prediction formula as the prediction formula for determining the room temperature from the outside air temperature.
  • the prediction formula producer 15 is configured to produce two or more regression prediction formulae that respectively correspond to two or more times of day.
  • the prediction formula producer 15 is configured to produce the regression prediction formulae, as prediction formulae at the respective times of day.
  • the prediction formula producer 15 is configured to produce two or more prediction formulae that respectively correspond to two or more specified times of day.
  • Each of the prediction formulae is produced based on pieces of the room temperature data and pieces of the outside air temperature data corresponding to a specified time.
  • the prediction formula producer 15 is configured to produce at least first and second prediction formulae respectively corresponding to at least first and second specified times.
  • the first prediction formula is produced based on pieces of the room temperature data and pieces of the outside air temperature data corresponding to the first specified time in each of the two or more days during the extraction period.
  • the second prediction formula is produced based on pieces of the room temperature data and pieces of the outside air temperature data corresponding to the second specified time in each of the two or more days during the extraction period.
  • the room temperature estimating device 10 produces the two or more prediction formulae respectively corresponding to the two or more times of day with the above described way, and then estimates a room temperature from an outside air temperature based on a prediction formula. Specifically, the room temperature estimating device 10 produces (at least) the first prediction formula corresponding to the first specified time and the second prediction formula corresponding to the second specified time. The room temperature estimating device 10 employs the first prediction formula for estimating a room temperature at a time corresponding to the first specified time, and employs the second prediction formula for estimating a room temperature at a time corresponding to the second specified time.
  • the room temperature estimating device 10 produces the first prediction formula based on pieces of the room temperature data and pieces of the outside air temperature data obtained at 4 a.m. (first specified time) in each of two or more days, and produces the second prediction formula based on pieces of the room temperature data and pieces of the outside air temperature data obtained at 5 a.m. (second specified time) in each of the two or more days.
  • the room temperature estimating device 10 employs the first prediction formula for estimating a room temperature at 4 a.m. (a time corresponding to the first specified time) of a certain day, and employs the second prediction formula for estimating a room temperature at 5 a.m. (a time corresponding to the second specified time) of a certain day.
  • the structure configured to estimate a room temperature from an outside air temperature in the room temperature estimating device 10 is described in detail below.
  • the room temperature estimating device 10 includes a prediction change obtainer 16 and a room temperature estimator 17.
  • the prediction change obtainer 16 is configured to obtain a predicted temporal change in outside air temperature, based on time series pieces of the outside air temperature data (measured values) obtained by the outside air temperature obtainer 12 from the outside air temperature meter 22.
  • the room temperature estimator 17 is configured to estimate a room temperature using the temporal change in outside air temperature.
  • the prediction change obtainer 16 is configured to apply the time series pieces of the outside air temperature data to any of pre-registered two or more kinds of templates of temporal changes in outside air temperature, and to predict the temporal change in outside air temperature based on the applied template.
  • the prediction change obtainer 16 is configured, when applying the time series pieces of the outside air temperature data to any of templates of temporal change in outside air temperature, to limit the templates to be applied, taking into account the weather and/or season of the day.
  • the outside air temperature obtainer 12 may have a function configured to obtain outside air temperature data via a telecommunication network from a service provider that provides local weather information.
  • the prediction change obtainer 16 employs the outside air temperature data obtained by the outside air temperature obtainer 12 from the service provider.
  • the outside air temperature data provided through the telecommunication network is the data related to a specific location in an area where a target room of which room temperature is to be estimated exists, and is not the outside air temperature corresponding to the target room.
  • the room temperature estimator 17 is configured to correct, based on an actual measured value of the room temperature, a room temperature estimated using the provided outside air temperature. As a result, it is possible estimate a room temperature properly based on the outside air temperature data provided via the telecommunication network.
  • the room temperature estimator 17 determines, based on the predicted temporal change in outside air temperature obtained by the prediction change obtainer 16, an outside air temperature at a target date and time. Determined the outside air temperature, the room temperature estimator 17 estimates a room temperature by applying the determined outside air temperature to the prediction formula produced by the prediction formula producer 15. In short, the room temperature estimator 17 is configured to estimate a room temperature at a target date and time by: determining, based on the predicted temporal change in outside air temperature, an outside air temperature at the date and time of which room temperature is to be estimated; and applying the determined outside air temperature to the prediction formula.
  • the room temperature estimating device 10 desirably includes an information outputter 18 configured to transmit the room temperature estimated by the room temperature estimator 17 to an informing device 23.
  • the informing device 23 may be a dedicated device including a display, or a device including a display and communication function, such as a smart phone, a tablet, and a personal computer. In a case of adopting such devices as the informing device 23, the information outputter 18 is configured to communicate with these devices.
  • the informing device 23 may be provided integrally in a housing of the room temperature estimating device 10, as an informing device 23 in FIG. 1 shown by a broken line.
  • the room temperature estimated by the room temperature estimator 17 may, not only be notified of a user via the informing device 23, but be used for controlling a device that possibly affects the room temperature, such as a ventilating fan, an air conditioner, an electric shutter, an electric curtain and an electric window.
  • a device that possibly affects the room temperature such as a ventilating fan, an air conditioner, an electric shutter, an electric curtain and an electric window.
  • an air-conditioning apparatus(es) air conditioner
  • an extraction period for measuring the room temperature and the outside air temperature used for producing the prediction formula, is determined for each season.
  • an extraction term is given for each division period which a period of one year is divided into.
  • a length of the division period corresponds to a period (a period derived from dividing a period of one year based on climatic environment) which is appropriately selected from a range of a quarter of one year to one-twenty fourth of one year (in the case of the "quarter of one year", the division periods reflect four seasons of spring, summer, autumn, and winter; and in the case of the "one-twenty fourth of one year", each division period corresponds to a half month).
  • the length of a division period may be set to 15 to 90 days, and an extraction period for each division period may be three days or more.
  • the division periods and their extraction periods are preliminarily stored in the storage 13, for example.
  • the prediction formula producer 15 is configured to produce a plurality of prediction formulae corresponding the number of division periods. Specifically, the prediction formula producer 15 is configured to produce two or more prediction formulae respectively corresponding to two or more times of day for each division period.
  • the room temperature estimator 17 is configured, when predicting a room temperature at a certain time of a certain day, to select, from the two or more prediction formulae produced for each of the division periods, a prediction formula corresponding to a target time in a division period which a target date belongs to, and to estimate a room temperature from a temporal change in outside air temperature based on the selected prediction formula.
  • the prediction formula producer 15 is configured to newly produce two or more prediction formulae respectively corresponding to two or more times of day, at a transition from one division period to the next division period (for example, transition from a period of "the summer” to a period of "the autumn") determined based on the current date and time measured by the clock 14.
  • the room temperature estimator 17 estimates a room temperature based on the newly produced prediction formulae.
  • the prediction formula producer 15 produces prediction formulae each of which is based on the room temperature and the outside air temperature measured in a time period during which the room temperature is not affected by the sun light. Therefore, the time period which the prediction formulae are applicable to for estimating a room temperature from the outside air temperature is restricted. In other words, a room temperature in a time period during which the room temperature is affected by the sun light cannot be accurately estimated based on the prediction formulae produced according to Embodiment 1.
  • the prediction formulae according to Embodiment 1 may be applicable only for a time period during which the change in outside air temperature is comparatively gentle, such as a period from the midnight to the early morning.
  • a prediction formula producer 15 has a function configured to produce two kinds of prediction formulae.
  • the room temperature estimating device 10 includes a first prediction formula producer 151 and a second prediction formula producer 152.
  • the first prediction formula producer 151 is configured to produce prediction formulas (first kind of prediction formula) based on the same technique as that in Embodiment 1.
  • the second prediction formula producer 152 is configured to produce a prediction formula (second kind of prediction formula) based on the technique described below.
  • the first prediction formula producer 151 is configured to produce the prediction formulae as is the prediction formula producer 15 in Embodiment 1.
  • the first prediction formula producer 151 is configured to produce a regression prediction formula based on pieces of room temperature data and pieces of outside air temperature data corresponding to a specified time in each of two or more days, which are stored in the storage 13, and to employ the produced regression prediction formula as a prediction formula.
  • the second prediction formula producer 152 is configured to produce a prediction formula with the following scheme under an assumption that a relation between the room temperature and the outside air temperature depends on the thermal-characteristics (such as heat insulating property and heat storage performance) of the room. It will be assumed that the room temperature depends only on the outside air temperature, and it will be made a model in which the heat is transferred through partitions of the room such as walls, a ceiling and a floor, and the room temperature changes according to the change in the outside air temperature. In this model, the influence of the outside air temperature on the room temperature would vary according to the extent of the thermal conductivity of the partitions and the extent of the heat capacitance of the partitions. In the embodiment, the temperature of the air inside the room is regarded as the room temperature, and the radiant heat from the partitions is omitted.
  • the room temperature would change later than the change in the outside air temperature.
  • the inventors have reviewed results of experiments and found that there exist a particular relation between the change in the outside air temperature and the change in the room temperature, and that the room temperature changes later by a delay time than the change in the outside air temperature, and that the delay time depends on the thermal-characteristics (such as the heat insulating property and the heat storage performance) of the partitions. Furthermore, they have found, by determining the delay time, that a relation between a room temperature at a specific time and an outside air temperature at a time shifted by the delay time from the specific time can be expressed by a simple prediction formula, and that a room temperature at a desired dime can be estimated from an outside air temperature based on this prediction formula.
  • FIG. 5A is a graph showing points each of which is a relation between a room temperature and an outside air temperature measured at a same date and time. There seems no relationship between the room temperature and the outside air temperature with a glance of the graph. In contrast, as described above, the present embodiment is achieved based on the presumption that there is a correlation between the temporal change in room temperature and the temporal change in outside air temperature, if provided is a delay time which depends on the thermal-characteristics of the room.
  • the room temperature estimating device 10 of the present embodiment includes an evaluator 19 configured to determine a time difference, based on pieces of room temperature data (measured values), pieces of outside air temperature data (measured values), and the associated dates and times, which are stored in the storage 13, so that a correlation coefficient between the room temperature and the outside air temperature becomes maximum.
  • the evaluator 19 is configured to determine the time difference (hereinafter, also called “optimum time difference”), based on pieces of the room temperature data and pieces of the outside air temperature, during a certain focused term (hereinafter, called “extraction term”), by relatively shifting one of corresponding measured dates and times of the pieces of the room temperature data and corresponding measured dates and times of the pieces of the outside air temperature data so that a correlation coefficient between the pieces of the room temperature data and the pieces of the outside air temperature data becomes maximum.
  • the extraction term is not limited to one day, but may be two or more days.
  • the measured dates and times corresponding to the outside air temperature are shifted with respect to the measured dates and times corresponding to the room temperature.
  • the contrary case is possible in which the measured dates and times corresponding to the room temperature are shifted with respect to the measured dates and times corresponding to the outside air temperature.
  • a piece of the room temperature data and a piece of the outside air temperature data corresponding to a certain date and time “t” are represented by “ ⁇ 1(t)” and “ ⁇ 2(t)”, respectively.
  • a data obtaining interval of pieces of room temperature data " ⁇ 1(t)", or pieces of outside air temperature data " ⁇ 2(t)”, is represented by "p”.
  • pieces of room temperature data are represented by " ⁇ 1(t0+p)", “ ⁇ 1(t0+2p)", “ ⁇ 1(t0+3p)”, ...
  • pieces of outside air temperature data are represented by " ⁇ 2(t ⁇ +p)", “ ⁇ 2(t0+2p)”, “ ⁇ 2(t0+3p)”, ...
  • an average value "a( ⁇ 1)" of the pieces of the room temperature data ⁇ 1(t), during a period of the extraction term is calculated as an average of pieces of the room temperature data, ⁇ 1(t0+p), ⁇ 1(t0+2p), ..., ⁇ 1(t0+q*p) ⁇ .
  • An average value "a( ⁇ 2)" of the pieces of the outside air temperature data ⁇ 2(t), during a period which is earlier by "the time difference ⁇ t" than "the extraction term”, is calculated as an average of pieces of the outside air temperature data, ⁇ 2(t0+(1-m)p), ⁇ 2(t0+(2-m)p), ..., ⁇ 2(t0+(q-m)p) ⁇ .
  • [t0+p, t0+q*p] represents a certain closed interval, and includes discrete values of ⁇ t0+p, t0+2p, t0+3p, ..., t0+q*p ⁇ , the number of which is "q".
  • the correlation coefficient can be calculated by a known calculation method, and obtained by dividing a covariance of the pieces of data ⁇ 1(t) and the pieces of data ⁇ 2(t- ⁇ t) by a product of a standard deviation of the pieces of the data ⁇ 1(t) and a standard deviation of the pieces of the data ⁇ 2(t- ⁇ t).
  • the abovementioned average values "a( ⁇ 1)” and “a( ⁇ 2)” are used for calculating the covariance and the standard deviations.
  • the variable "t" representing the dates and times of the pieces of the room temperature data ⁇ 1(t) and the pieces of the outside air temperature data ⁇ 2(t- ⁇ t), ranges within the period of the extraction term (i.e., the closed interval [t0+p, t0+q*p]).
  • the evaluator 19 is configured to calculate a correlation coefficient for each value of the number "m", while changing the value of the number “m” to change the time difference ⁇ t.
  • the maximum value of the number “m” is limited so that a product "m*p" of the number "m” and the time interval “p" does not exceed a length of one day. For example, in a case where the time interval "p" corresponds to one hour, the maximum value of the number “m” is limited so as not to exceed "24”.
  • FIG. 5B shows points each of which is a relation between a piece of the room temperature data ⁇ 1(t) and a piece of the outside air temperature data ⁇ 2(t- ⁇ t A ) provided with the time difference (optimum time difference) ⁇ t A determined by the evaluator 19.
  • the time difference optimum time difference
  • the second prediction formula producer 152 is configured to produce, based on the relationship shown in FIG. 5B , a prediction formula for estimating a room temperature from an outside air temperature.
  • the second prediction formula producer 152 is configured to extract, from the room temperature data and the outside air temperature data stored in the storage 13, pieces of the respective data during the extraction term, and to provide the time difference (the optimum time difference) ⁇ t A determined by the evaluator 19 to the dates and times corresponding to the extracted pieces of the outside air temperature data.
  • the second prediction formula producer 152 produces the prediction formula by a simple linear regression analysis involving the outside air temperature data provided with the time difference ⁇ t A as the independent variable and the room temperature data as the dependent variable.
  • the evaluator 19 determines the time difference ⁇ t A and the second prediction formula producer 152 determines the coefficients " ⁇ ", " ⁇ ", and as a result the prediction formula (second kind of prediction formula) can be produced.
  • the coefficients " ⁇ ", “ ⁇ ” of the formula in general, are different from the coefficients " ⁇ ", " ⁇ ” in the prediction formula produced by the first prediction formula producer 151.
  • the evaluator 19 determines a time difference (optimum time difference), based on pieces of the room temperature data and pieces of the outside air temperature data, during a given extraction term, which are stored in the storage 13, and then the second prediction formula producer 152 produces a prediction formula, based on the pieces of the room temperature data and the pieces of the outside air temperature, the one of which the time difference is provided to.
  • the prediction formula produced by the second prediction formula producer 152 is applicable regardless of the influence of the sun light on the room temperature. Also, it is possible to estimate a room temperature by a single prediction formula regardless of the time of day. However, regarding a time period during which the room temperature is not affected by the sun light, it is possible to estimate a room temperature from an outside air temperature based on the prediction formula (first kind of prediction formula) produced by the first prediction formula producer 151, with a decent accuracy (possibly with an accuracy higher than that obtained by the prediction formula produced by the second prediction formula producer 152).
  • the prediction formula produced by the first prediction formula producer 151 is employed for a time period of which room temperature can be estimated by the prediction formula produced by the first prediction formula producer 151, and that the prediction formula produced by the second prediction formula producer 152 is employed for the other time period so as to divide their responsibility.
  • the prediction formula (first kind of prediction formula) produced by the first prediction formula producer 151 is employed for the time period during which the room temperature would not be affected by the sun light (i.e. a time period of no sun light) and the prediction formula (second kind of prediction formula) produced by the second prediction formula producer 152 is employed for the time period during which the room temperature would be affected by the sun light.
  • the room temperature estimating device 10 needs to obtain a piece of the outside air temperature data at a date and time which is earlier by the time difference (delay time) ⁇ t A determined by the evaluator 19 than a target date and time.
  • the "target date and time” is a date and time at which a room temperature is to be estimated.
  • the room temperature estimator 17 determines, based on a predicted temporal change in outside air temperature obtained by a prediction change obtainer 16 and the time difference (optimum time difference) determined by the evaluator 19, an outside air temperature (a measured value or a prediction value) at a date and time earlier by the time difference than the target date and time. Determined the outside air temperature, the room temperature estimator 17 estimates a room temperature by applying the determined outside air temperature to the prediction formula produced by the prediction formula producer 15.
  • the room temperature estimator 17 is configured to determine, based on the predicted temporal change in outside air temperature, an outside air temperature at a time point earlier by the time difference determined by the evaluator 19 than a date and time of which room temperature is to be estimated; and to apply the determined outside air temperature to the prediction formula, and thereby to estimate a room temperature at a target date and time.
  • the prediction formula producer 15 of the present embodiment includes the first prediction formula producer 151 and the second prediction formula producer 152.
  • the room temperature estimator 17 is configured to determine whether the current time is in the time period during which the room temperature is affected by the sun light or in the time period during which the room temperature is not affected by the sun light, based on the measured date and time of the clock 14.
  • the prediction formula produced by the first prediction formula producer 151 is used for the time period during which the room temperature is not affected by the sun light
  • the prediction formula produced by the second prediction formula producer 152 is used for the time period during which the room temperature is affected by the sun light.
  • the prediction formula produced by the first prediction formula producer 151 would vary according to the season. It is also easily supposed that the prediction formula produced by the second prediction formula producer 152 varies according to the season. It is therefore desirable that an extraction term, for measuring the room temperature and the outside air temperature used for producing the prediction formula, is determined for each season.
  • division periods which a period of one year is divided into, and an extraction term is given for each division period.
  • a length of the division period is appropriately selected from a range of a quarter of one year to one-twenty fourth of one year (in the case of the "quarter of one year", the division periods reflect four seasons of spring, summer, autumn, and winter; and in the case of the "one-twenty fourth of one year", each division period corresponds to a half month).
  • the second prediction formula producer 152 produces prediction formulae of which the number corresponds to the number of division periods.
  • the room temperature estimator 17 selects, from the respective prediction formulae corresponding to the division periods, a prediction formula corresponding to a division period which a target date and time belongs to, and estimates a room temperature based on the selected prediction formula using a temporal change in outside air temperature.
  • the room temperature estimator 17 is configured, when estimating a room temperature, to employ a time difference which is determined for each division period. Specifically, it is desirable that the evaluator 19 newly determines a time difference (optimum time difference) ⁇ t A for each elapse of a division period, that the second prediction formula producer 152 newly produces a prediction formula (second kind of prediction formula) corresponding to the newly determined time difference ⁇ t A , and that the room temperature estimator 17 estimates a room temperature based on the newly produced prediction formula (second kind of prediction formula).
  • the room temperature estimator 17 may be configured to estimate a room temperature based on a time difference determined regarding any of the division periods. It is also possible to estimate a room temperature based on an average of time differences determined regarding two or more division periods.
  • the room temperature estimator 17 in the present embodiment uses different kinds of prediction formulae according to whether the room temperature is affected by the sun light or not. Also, the outside air temperature to be applied to differs according to the kinds of the prediction formula. Accordingly, it is possible to increase the prediction accuracy of the room temperature.
  • Other structures and operations are similar to those in Embodiment 1.
  • the room temperature estimating device 10 is configured to estimate a room temperature based only on an outside air temperature.
  • factors which the room temperature depends on include the sun light, the air ventilation, the rain fall, the number of people in the room.
  • the air conditioning is performed by an air-conditioning apparatus(es) that has a function of controlling the room temperature, the temperature in the room relies on the operation state of the air-conditioning apparatus(es), and accordingly it is not possible to predict the room temperature by a prediction formula. In the explanation below, therefore, it is assumed that the air-conditioning is not performed.
  • the present embodiment treats each of the respective information as correction information, limits the number of possible states of each kind of correction information, and determines a prediction formula for each state of the correction information.
  • the prediction formula producer 15 divides, for each kind of correction information, the state of the correction information into two or more levels. Then the prediction formula producer 15 produces prediction formulae (corrected prediction formulae) each of which corresponds to a specific combination of levels of the two or more kinds of correction information.
  • two levels are defined for each of the sun light, the air ventilation, and the rain fall. Contrary, regarding the number of present people, it is assumed that the room temperature is increased by a predetermined temperature value (for example, 0.5°C) per one person.
  • a predetermined temperature value for example, 0.5°C
  • the prediction formula producer 15 is configured to determine a prediction formula according to a combination of respective states of two or more kinds of correction information.
  • the number of people in the room is reflected only on the coefficient " ⁇ " in the prediction formula. Therefore, there is no need to produce different prediction formulae according to the number of people.
  • the room temperature estimator 17 may be configured to add a product of the number of present people and the predetermined temperature value to a room temperature estimated by the prediction formula. In the above example, therefore, eight of prediction formulae are produced according to kinds of the correction information on the sun light, the air ventilation and the rain fall.
  • the prediction formula producer 15 is configured to correct the coefficients " ⁇ " and " ⁇ ” of a prediction formula according to the states of the respective correction information, and thereby to produce a corrected prediction formula. For example, correction amounts of the coefficients " ⁇ " and “ ⁇ ” are associated with the states of the respective correction information and stored in the storage 13. In a case where one kind of correction information is in a certain state (for example, in a case where the air ventilation is present), the prediction formula producer 15 retrieves correction amounts of the coefficients " ⁇ ” and " ⁇ ” corresponding to this certain state from the storage 13, and applies the retrieved correction amounts to the coefficients " ⁇ " and " ⁇ ” of the prediction formula and thereby to produce a corrected prediction formula.
  • the room temperature estimating device 10 of the present embodiment includes a correction information obtainer 32 configured to obtain respective correction information from a sun light detector 33, an air ventilation detector 34, a rain fall detector 35 and a human counter 36.
  • the sun light detector 33 may include a photo detector such as a photo diode and a photo transistor, and a judging unit configured to compare an output of the photo detector with a threshold to determine the light amount.
  • the influence of the sun light on the room depends on whether a curtain and/or a shutter is opened or closed. It is therefore desirable that the sun light detector 33 has a function configured to detect whether the curtain and/or the shutter is opened or closed.
  • the air ventilation detector 34 may be configured to detect whether a ventilation fan is operated or not, and/or to detect whether a window is opened or closed and/or to measure an airflow in the room.
  • the rain fall detector 35 may be configured to collect rain water to measure the weight of the collected rain water per certain period, and/or to detect presence or absence of rain drops from an outside room image.
  • the correction information on the rain fall may be obtained from information provided by a service provider through a telecommunication network such as internet.
  • the human counter 36 may be configured to count the number of people in the room based on an in-room image.
  • the state of the correction information on the sun light, the air ventilation and the rain fall may be divided into three or more levels according to their degrees, instead of only two levels of "present” and “absent".
  • the state of the sun light may be divided into four levels, e.g., “strong”, “medium”, “weak” and “very weak”.
  • the state of air ventilation and/or the rain fall may be divided into three or more levels.
  • the room temperature estimator 17 corrects the prediction formula based on the correction information obtained by the correction information obtainer 32 to produce a corrected prediction formula, and estimates a room temperature, from an outside air temperature, based on the corrected prediction formula. Note that the correction amounts of the coefficients " ⁇ " and " ⁇ " according to each level of the sun light, the air ventilation, the rain fall and the number of people may be determined statistically based on actual measured values. Other structures and operations are similar to those in Embodiment 1 or Embodiment 2.

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Claims (8)

  1. Dispositif d'estimation de température ambiante comprenant :
    un dispositif d'obtention de température ambiante (11) configuré pour obtenir des données de température ambiante ;
    un dispositif d'obtention de température d'air extérieur (12) configuré pour obtenir des données de température d'air extérieur ;
    une mémoire (13) configurée pour mémoriser les données de température ambiante obtenues par le dispositif d'obtention de température ambiante (11) et les données de température d'air extérieur obtenues par le dispositif d'obtention de température d'air extérieur (12) avec chaque élément des données de température ambiante et des données de température d'air extérieur associé à une date et une heure mesurées correspondantes ;
    un dispositif de production de formule de prédiction (15) configuré pour produire deux formules de prédiction ou plus exprimant chacune une relation entre des éléments de données de température ambiante et des éléments de données de température d'air extérieur à une heure du jour spécifiée, sur la base des éléments des données de température ambiante et des éléments des données de température d'air extérieur correspondant à l'heure spécifiée dans chacun de deux jours ou plus pendant une période d'extraction donnée, qui sont mémorisées dans la mémoire (13), les deux formules de prédiction ou plus correspondant à deux heures du jour spécifiées ou plus, respectivement ;
    un dispositif d'obtention de changement de prédiction (16) configuré pour obtenir un changement temporel prédit de la température d'air extérieur ;
    un dispositif d'estimation de température ambiante (17) configuré, sur la base du changement temporel de la température d'air extérieur obtenu par le dispositif d'obtention de changement de prédiction (16), pour appliquer une température d'air extérieur à une heure cible, correspondant à l'une desdites deux heures spécifiées ou plus, à la formule de prédiction produite en relation avec ladite une des deux heures spécifiées ou plus, et pour de ce fait estimer une température ambiante à l'heure cible ; et
    une horloge (14) configurée pour mesurer une date et une heure actuelles,
    dans lequel
    la période d'extraction est incluse dans l'une quelconque des périodes de division en lesquelles une période d'une année est divisée sur la base de l'environnement climatique,
    le dispositif d'estimation de température ambiante (17) est configuré pour appliquer, pour prédire une température ambiante dans une certaine période de division, une formule de prédiction de deux formules de prédiction ou plus produites sur la base des éléments des données de température ambiante et des éléments des données de température d'air extérieur pendant une période d'extraction incluse dans la certaine période de division,
    le dispositif de production de formule de prédiction (15) est configuré pour produire nouvellement deux formules de prédiction ou plus correspondant respectivement à deux heures du jour ou plus, au niveau d'une transition d'une période de division à une période de division suivante déterminée sur la base de la date et de l'heure actuelles mesurées par l'horloge (14), et
    le dispositif d'estimation de température ambiante (17) est configuré pour estimer la température ambiante sur la base de l'une des deux formules de prédiction ou plus nouvellement produites.
  2. Dispositif d'estimation de température ambiante selon la revendication 1, dans lequel
    les deux formules de prédiction ou plus produites par le dispositif de production de formule de prédiction (15) comprennent au moins des première et deuxième formules de prédiction correspondant respectivement à au moins des première et deuxième heures spécifiées, la première formule de prédiction étant produite sur la base des éléments des données de température ambiante et des éléments des données de température d'air extérieur correspondant à la première heure spécifiée dans chacun des deux jours ou plus pendant la période d'extraction donnée, la deuxième formule de prédiction étant produite sur la base des éléments des données de température ambiante et des éléments des données de température d'air extérieur correspondant à la deuxième heure spécifiée dans chacun des deux jours ou plus pendant la période d'extraction donnée, et
    le dispositif d'estimation de température ambiante (17) est configuré
    pour appliquer une température d'air extérieur à une première heure cible correspondant à la première heure spécifiée à la première formule de prédiction, et pour estimer de ce fait une température ambiante à la première heure cible, et
    pour appliquer une température d'air extérieur à une deuxième heure cible correspondant à la deuxième heure spécifiée à la deuxième formule de prédiction, et pour estimer de ce fait une température ambiante à la deuxième heure cible.
  3. Dispositif d'estimation de température ambiante selon la revendication 1 ou 2, dans lequel
    le dispositif de production de formule de prédiction (15) est configuré pour produire, en tant que chacune des deux formules de prédiction ou plus, une formule de régression à partir des éléments des données de température ambiante et des éléments des données de température d'air extérieur.
  4. Dispositif d'estimation de température ambiante selon l'une quelconque des revendications 1 à 3, comprenant en outre un dispositif d'obtention d'informations de correction (32) configuré pour obtenir des informations de correction correspondant à un état qui a été sélectionné parmi deux états ou plus, les informations de correction sont en plus la température d'air extérieur et affectent la température ambiante, dans lequel
    le dispositif de production de formule de prédiction (15) est configuré pour corriger les deux formules de prédiction ou plus conformément à l'état des informations de correction obtenues par le dispositif d'obtention d'informations de correction (32), et pour de ce fait produire deux formules de prédiction corrigées ou plus, et
    le dispositif d'estimation de température ambiante (17) est configuré pour estimer la température ambiante sur la base de l'une des deux formules de prédiction corrigées ou plus.
  5. Dispositif d'estimation de température ambiante selon l'une quelconque des revendications 1 à 4, comprenant en outre un dispositif de sortie d'informations (18) configuré pour transmettre la température ambiante estimée par le dispositif d'estimation de température ambiante (17) à un dispositif d'information.
  6. Dispositif d'estimation de température ambiante selon l'une quelconque des revendications 1 à 5, dans lequel le dispositif d'obtention de température d'air extérieur (12) est configuré pour obtenir des données de température d'air extérieur fournies par l'intermédiaire d'un réseau de télécommunication.
  7. Dispositif d'estimation de température ambiante selon l'une quelconque des revendications 1 à 6, dans lequel le dispositif de production de formule de prédiction (15) est configuré pour produire chacune des deux formules de prédiction ou plus par une simple analyse de régression linéaire impliquant les données de température d'air extérieur en tant que variable indépendante et les données de température ambiante en tant que variable dépendante.
  8. Programme configuré pour amener un ordinateur à fonctionner en tant que dispositif d'estimation de température ambiante selon l'une quelconque des revendications 1 à 7.
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EP2944891A1 (fr) 2015-11-18
EP2944891A4 (fr) 2016-04-20
JP6160945B2 (ja) 2017-07-12
WO2014109290A1 (fr) 2014-07-17
CN104919252A (zh) 2015-09-16
CN104919252B (zh) 2017-10-24
JP2014134360A (ja) 2014-07-24

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