JP6192351B2 - Air conditioning system - Google Patents

Description

  The present invention relates to an air conditioning system.

  Conventionally, there has been an air conditioning system that selectively uses fuzzy control and area proportional control based on the comparison result between the in-vehicle temperature and the cooling reference temperature in order to enhance responsiveness to a sudden temperature change (see, for example, Patent Document 1). .

JP 2012-240571 A (paragraph [0068])

  The air conditioning system described in Patent Document 1 selects either fuzzy control or area proportional control in order to control the temperature for a rapid temperature change, that is, a transient state.

  However, in the air conditioning system described in Patent Document 1, in order to control the temperature other than the transient state, after the vehicle is delivered, data is accumulated using the current vehicle, the accumulated data is analyzed, and the analyzed data is converted into the analyzed data. Based on the manual tuning of various settings, an appropriate control method was selected from various control methods such as fuzzy control and area proportional control.

  Therefore, in the conventional air conditioning system as described in Patent Document 1, the optimum control method has not been automatically selected.

  In other words, the optimal control method has been manually selected. Therefore, there is a problem that the operation load required for selecting an optimal control method is large.

  The present invention has been made to solve the above-described problems, and an object of the present invention is to provide an air conditioning system capable of reducing an operation load required for selecting an optimal control method.

An air conditioning system according to the present invention includes an air conditioning controller provided with at least two control modules for controlling an air conditioner mounted on a vehicle, selection of the control module corresponding to the air conditioner, and air conditioning corresponding to the air conditioner. And an automatic adjustment unit that adjusts the control parameters, each of the control modules controls the air conditioner with a different algorithm, the automatic adjustment unit, for each of the control modules, The air conditioner is controlled, and at least the in-vehicle temperature of the vehicle and the reference temperature of the vehicle are accumulated for each control module as the operation data of the air conditioner, the in-vehicle temperature for each control module, and the reference The control module is selected based on a comparison between the temperature and the difference, and the air conditioning controller is selected by the automatic adjustment unit. In accordance with the control module, the inside temperature of the vehicle, a reference temperature determined corresponding to the vehicle, on the basis, and controls the air conditioning system.

  In the present invention, the optimum control method is automatically selected. Therefore, there is an effect that it is possible to provide an air conditioning system that can reduce an operation load required for selecting an optimal control method.

It is a figure which shows an example of the train set 10 in which the air conditioner 16 and the air-conditioning controller 17 in Embodiment 1 of this invention are mounted. It is a figure which shows an example of the air conditioning system 50 in Embodiment 1 of this invention. It is a figure which shows an example of the refrigerant circuit 31 of the air conditioner 16 in Embodiment 1 of this invention. It is a figure which shows an example of a function structure of the air-conditioning controller 17 in Embodiment 1 of this invention. It is a figure which shows an example of a function structure of the fuzzy control module 74 in Embodiment 1 of this invention. It is a figure which shows an example of a function structure of the area | region proportional control module 73 in Embodiment 1 of this invention. It is a figure which shows an example of the driving | running pattern of the area | region proportional control in Embodiment 1 of this invention. It is a figure which shows an example of a function structure of the automatic adjustment part 76 in Embodiment 1 of this invention. It is a flowchart explaining the operation example of the air conditioning system 50 which determines the control system for every time slot | zone in Embodiment 1 of this invention. It is a flowchart explaining the operation example of the air conditioning system 50 which determines the control system for every time slot | zone including the air conditioning control parameter in Embodiment 1 of this invention. It is a flowchart explaining the operation example of the air conditioning system 50 which determines the control system for every season in Embodiment 2 of this invention. It is a flowchart explaining the example of control of the air conditioning system 50 which determines the control system for every season including the air conditioning control parameter in Embodiment 2 of this invention. It is a flowchart explaining the operation example of the air conditioning system 50 which determines the control system for every kind of train in Embodiment 3 of this invention. It is a flowchart explaining the operation example of the air conditioning system 50 which determines the control system for every kind of train including the air conditioning control parameter in Embodiment 3 of this invention.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. In addition, although the step which describes the program which performs operation | movement of Embodiment 1-3 of this invention is a process performed in time series along the order described, it is not necessarily processed in time series, it is parallel Processing that is executed manually or individually may also be included.

  It does not matter whether each function described in the first embodiment is realized by hardware or software. That is, each block diagram described in the first embodiment may be considered as a hardware block diagram or a software functional block diagram. For example, each block diagram may be realized by hardware such as a circuit device, or may be realized by software executed on an arithmetic device such as a processor (not shown).

  In addition, each block in the block diagram described in the first embodiment only needs to perform its function, and the configuration may not be separated by each block.

  In addition, the refrigerant circuit 31 (described later) described in the first embodiment is an example, and is not limited to the illustrated items.

  In each of the first to third embodiments, items not particularly described are the same as those in the first to third embodiments, and the same functions and configurations are described using the same reference numerals.

  Further, Embodiments 1 to 3 may be implemented alone or in combination. In either case, the advantageous effects described below can be obtained.

  In addition, the setting examples of various values and flags described in each of the first to third embodiments are merely examples, and are not particularly limited thereto.

Embodiment 1 FIG.
FIG. 1 is a diagram illustrating an example of a train train 10 on which an air conditioner 16 and an air conditioning controller 17 according to Embodiment 1 of the present invention are mounted. As illustrated in FIG. 1, the train set 10 includes, for example, a vehicle 11_1, a vehicle 11_2, and a vehicle 11_3, and the vehicle 11_1, the vehicle 11_2, and the vehicle 11_3 are connected and formed.

  Note that the vehicle 11_1, the vehicle 11_2, and the vehicle 11_3 will be referred to as the vehicle 11 unless otherwise distinguished. Moreover, it does not specifically limit about the kind, the number, etc. of the vehicle 11 which forms the train 10.

  Of each vehicle 11, for example, a vehicle 11_1 that is organized as a leading vehicle includes a crew room 12 and a cabin 13_1. In the crew room 12, for example, a train information management device 15 is provided. The guest room 13_1 includes, for example, a humidity sensor 20_1 and a wall temperature sensor 22_1. On the attic side of the guest room 13_1, for example, an air conditioner controller 17_1 and a return temperature sensor 21_1 are provided. For example, an air conditioner 16_1 is mounted on the roof side of the vehicle 11_1. For example, a vehicle information control device 14_1 is provided below the vehicle 11_1. For example, a variable load sensor 23_1 is provided in the vehicle information control device 14_1.

  Of each vehicle 11, for example, a vehicle 11_2 that is organized as an intermediate vehicle includes a cabin 13_2. The guest room 13_2 includes, for example, a humidity sensor 20_2 and a wall temperature sensor 22_2. On the attic side of the guest room 13_2, for example, an air conditioning controller 17_2 and a return temperature sensor 21_2 are provided. For example, an air conditioner 16_2 is mounted on the roof side of the vehicle 11_2. Below the vehicle 11_1, for example, a vehicle information control device 14_2 is provided. For example, a variable load sensor 23_2 is provided in the vehicle information control device 14_2.

  Note that the humidity sensor 20_1 and the humidity sensor 20_2 are referred to as the humidity sensor 20 when they are not particularly distinguished from each other. The wall temperature sensor 22_1 and the wall temperature sensor 22_2 will be referred to as the wall temperature sensor 22 unless otherwise distinguished. In addition, the air conditioning controller 17_1 and the air conditioning controller 17_2 are referred to as an air conditioning controller 17 unless particularly distinguished from each other. Further, the return temperature sensor 21_1 and the return temperature sensor 21_2 will be referred to as the return temperature sensor 21 when not particularly distinguished from each other. In addition, the air conditioner 16_1 and the air conditioner 16_2 are referred to as an air conditioner 16 unless particularly distinguished from each other. In addition, the vehicle information control device 14_1 and the vehicle information control device 14_2 are referred to as the vehicle information control device 14 unless particularly distinguished from each other. In addition, when there is no particular distinction between the variable load sensor 23_1 and the variable load sensor 23_2, they are referred to as the variable load sensor 23.

  In addition, the various apparatuses demonstrated above, the number of various apparatuses, the arrangement configuration of various apparatuses, etc. show an example, and are not particularly limited thereto. For example, the air conditioner 16_1, the air conditioner 16_2, the air conditioner controller 17_1, and the air conditioner controller 17_2 may be provided in the lower portion of the vehicle 11. For example, one vehicle 11 may be provided with a plurality of air conditioners 16.

  FIG. 2 is a diagram illustrating an example of the air conditioning system 50 according to Embodiment 1 of the present invention. As shown in FIG. 2, the air conditioning system 50 includes a vehicle information control device 14, a load sensor 23, an air conditioning controller 17, a humidity sensor 20, a return temperature sensor 21, a wall temperature sensor 22, and an air conditioner for each vehicle 11. A device 16 is provided. The air conditioning system 50 includes a train information management device 15 that transmits and receives various signals to and from the vehicle information control device 14. In addition, the structure of the air conditioning system 50 demonstrated above shows an example, and is not specifically limited to this. For example, the air conditioning controller 17 may not be provided for each vehicle 11. In this case, the air conditioner 16 mounted on a certain vehicle 11 may be remotely controlled from the air conditioning controller 17 mounted on another vehicle 11.

  The train information management device 15 holds various data collected from the vehicle information control device 14 of each vehicle 11, the door opening / closing state of each vehicle 11, the air conditioning operation state of each vehicle 11, the boarding rate of each vehicle 11, not shown. The outside temperature measured by the outside temperature sensor is managed. The air conditioning operation state is, for example, various data such as in-vehicle temperature, in-vehicle humidity, cooling, heating, air blowing, dehumidification, strong air conditioning operation, weak air conditioning operation, fine air conditioning operation, and air conditioning stop.

  The variable load sensor 23 detects a substantially vertical pressure applied to the vehicle 11 and supplies the detected pressure data to the vehicle information control device 14.

  The vehicle information control device 14 manages various data of the vehicle 11 and mutually communicates various data with the vehicle information control device 14 or the train information management device 15 provided in the other vehicle 11. The vehicle information control device 14 calculates the boarding rate based on the pressure data supplied from the variable load sensor 23, and supplies the calculated boarding rate to the air conditioning controller 17. In addition to the boarding rate, the vehicle information control device 14 supplies an air conditioning command such as a cooling command, a heating command, and a set temperature supplied from the train information management device 15 to the air conditioning controller 17. The vehicle information control device 14 may autonomously supply an air conditioning command to the air conditioning controller 17.

  The boarding rate indicates the ratio of the actual number of passengers to the boarding capacity of the vehicle 11. For example, a boarding rate of 100% indicates a situation where all seats are filled and straps are filled. The occupancy rate is obtained by detecting the pressure when the vehicle is empty and the current pressure, respectively, and calculating the difference, dividing the difference by the pressure value corresponding to the weight of passengers of standard physique, and calculating the current number of passengers. Calculate the current number of passengers divided by the number of passengers. The boarding rate is, for example, a value at 1 second after the door is closed, and is maintained until the next door opening / closing.

  The humidity sensor 20 detects the humidity of the in-vehicle air and supplies the detected humidity data of the in-vehicle air to the air conditioning controller 17. The return temperature sensor 21 detects the temperature of in-vehicle air flowing from a return filter (not shown) provided on the ceiling inside the vehicle 11, and the temperature data of the in-vehicle air flowing from the detected return filter is sent to the air conditioning controller 17. Supply. The wall temperature sensor 22 detects the temperature of the in-vehicle air and supplies the detected temperature data of the in-vehicle air to the air conditioning controller 17.

  The air conditioning controller 17 controls the air conditioner 16 based on the boarding rate, the detection result of the humidity sensor 20, the detection result of the return temperature sensor 21, the detection result of the wall temperature sensor 22, etc. Control the air inside the car. In the above description, an example in which the air conditioning controller 17 operates in response to an air conditioning command from a device such as the vehicle information control device 14 has been described, but the air conditioning controller 17 depends on the situation of the cabin 13 of the vehicle 11. The cooling command and the heating command may be generated autonomously.

  The air conditioner 16 includes an air conditioner inverter 41, an air conditioner compressor (CP1) 51_1, an air conditioner compressor (CP2) 51_2, an outdoor fan (CF1) 62_1, an outdoor fan (CF2) 62_2, an indoor fan (EF) 61, and the like. ing.

  The air conditioning inverter device 41 is an inverter that performs variable frequency variable voltage control of an auxiliary power supply device (not shown). The air conditioning compressor (CP1) 51_1, the air conditioning compressor (CP2) 51_2, the outdoor fan (CF1) 62_1, and the outdoor fan (CF2). ) 62_2, the indoor blower (EF) 61 and the like are supplied with electric power.

  The rotational speeds of the outdoor fan (CF1) 62_1, outdoor fan (CF2) 62_2, and indoor fan (EF) 61 are controlled based on the operating frequency supplied as a command value from the air conditioning inverter device 41, the air conditioning controller 17, and the like. Thus, driving of the outdoor fan (CF1) 62_1, the outdoor fan (CF2) 62_2, and the indoor fan (EF) 61 is controlled. The air conditioning inverter device 41 may not be provided. In this case, the air conditioning controller 17 only has to function as the air conditioning inverter device 41.

  In the following description, the air conditioning compressor (CP1) 51_1 and the air conditioning compressor (CP2) 51_2 will be referred to as the air conditioning compressor 51 unless otherwise distinguished. In addition, when the outdoor blower (CF1) 62_1 and the outdoor blower (CF2) are not particularly distinguished, they are referred to as outdoor blowers 62.

  FIG. 3 is a diagram illustrating an example of the refrigerant circuit 31 of the air conditioner 16 according to Embodiment 1 of the present invention. As shown in FIG. 3, the refrigerant circuit 31 includes an air conditioning compressor 51, an indoor heat exchanger 52, an expansion device 53, an outdoor heat exchanger 54, and the like, and is formed by being connected through a refrigerant pipe. Yes.

  The air-conditioning compressor 51 is a compressor having a variable operating capacity, and is composed of, for example, a positive displacement compressor driven by a DC brushless motor (not shown) whose operating frequency is controlled by an inverter.

  The indoor heat exchanger 52 functions as a use side heat exchanger. The indoor heat exchanger 52 is provided with an indoor blower 61. The indoor heat exchanger 52 functions as a refrigerant evaporator during cooling operation, and cools the air in the vehicle 11. The indoor heat exchanger 52 is formed of, for example, a cross fin type fin-and-tube heat exchanger composed of a heat transfer tube and a large number of fins. Here, the refrigerant circuit 31 without the four-way valve is described, but when the four-way valve is provided, the indoor heat exchanger 52 functions as a refrigerant condenser during the heating operation, and the vehicle 11 Heat the air in the car.

  The indoor blower 61 supplies the air exchanged between the air in the vehicle 11 and the refrigerant flowing through the indoor heat exchanger 52 into the vehicle 11 as supply air. The indoor blower 61 is a fan capable of changing the flow rate of air supplied to the indoor heat exchanger 52, for example, a centrifugal fan driven by an indoor blower drive unit (not shown) configured by a DC fan motor or It is formed from a multiblade fan.

  The expansion device 53 depressurizes the high-pressure refrigerant to a low-pressure state. The expansion device 53 is formed by, for example, an electronic expansion valve that can variably control the opening degree.

  The outdoor heat exchanger 54 functions as a heat source side heat exchanger. The outdoor heat exchanger 54 is provided with an outdoor fan 62. The outdoor heat exchanger 54 functions as a refrigerant condenser during cooling operation, and is formed of, for example, a cross fin type fin-and-tube heat exchanger formed of a heat transfer tube and a large number of fins. Yes. In addition, although the refrigerant circuit 31 which does not provide a four-way valve is demonstrated here, when a four-way valve is provided, the outdoor heat exchanger 54 functions as an evaporator of a refrigerant | coolant at the time of heating operation.

  The outdoor blower 62 is sucked from an outdoor air intake (not shown) outside the vehicle 11 and discharges the air exchanged between the outdoor air and the refrigerant flowing through the outdoor heat exchanger 54 to the outside. The outdoor blower 62 is a fan capable of varying the flow rate of air supplied to the outdoor heat exchanger 54, for example, a centrifugal fan or a multiblade fan driven by an outdoor blower driving unit 63 configured by a DC fan motor. Formed from.

  FIG. 4 is a diagram illustrating an example of a functional configuration of the air-conditioning controller 17 according to Embodiment 1 of the present invention. As shown in FIG. 4, the air conditioning controller 17 includes an input unit 71, a control switching unit 72, an area proportional control module 73, a fuzzy control module 74, an output unit 75, and an automatic adjustment unit 76. Although details of the automatic adjustment unit 76 will be described later, it is not particularly necessary to be incorporated in the air conditioning controller 17. Here, the term module is used to mean an entity that executes at least one function.

  For example, each of the area proportional control module 73 and the fuzzy control module 74 may be implemented as a so-called application. Further, for example, each of the area proportional control module 73 and the fuzzy control module 74 may be realized as hardware in which a function is incorporated in a control circuit or the like. In any case, any entity that can update functions such as version upgrades and operations as appropriate can be used. That is, the module is only used as a term as a replaceable functional unit, and the function or the like is not limited thereby.

  The input unit 71 converts various input data from the outside into a data format used by the air conditioning controller 17. The control switching unit 72 includes an air conditioning control parameter 80. Based on the various data supplied from the input unit 71 and the various data supplied from the automatic adjustment unit 76, the control switching unit 72 sets the control method to either the area proportional control module 73 or the fuzzy control module 74. Switch. Here, as an example of the control method, a module incorporating the area proportional control method and a module incorporating the fuzzy control method have been described, but the present invention is not particularly limited thereto. In short, any module in which different algorithms are implemented may be used.

  The air conditioning control parameters 80 are various data groups used in each of the area proportional control module 73 and the fuzzy control module 74. The air conditioning control parameter 80 is a fine setting parameter for adapting to various vehicles 11 and various environments in the respective controls of the area proportional control module 73 and the fuzzy control module 74. The air conditioning control parameter 80 is, for example, a rule that the set temperature is lowered by 1 ° C. when the boarding rate is 200%. As another example of the air conditioning control parameter 80, for example, when the outside air temperature is 30 ° C. or higher, a rule that the set temperature is lowered by 1 ° C. may be used.

  As will be described in detail later, the area proportional control module 73 is a control in which driving ability is assigned to each range based on whether or not the in-vehicle temperature belongs to a predetermined range. Although the details will be described later, the fuzzy control module 74 obtains the difference between the set temperature and the in-vehicle temperature, obtains the suitability of the difference to various conditions, and based on the result of applying the suitability to the inference rule, This is control for selecting the air conditioning capacity. The output unit 75 converts various commands from the area proportional control module 73 or various commands from the fuzzy control module 74 into a data format used at the output destination and outputs the data format.

  FIG. 5 is a diagram illustrating an example of a functional configuration of the fuzzy control module 74 according to Embodiment 1 of the present invention. The fuzzy control module 74 includes a reference temperature correction unit 81, a fuzzy inference unit 82, and a step calorie calculation unit 83.

  The reference temperature correction unit 81 corrects the reference temperature based on a preset reference temperature and a clothing amount correction that takes into consideration that the comfortable temperature of the human body fluctuates from a year-round passenger clothing amount. For example, in the spring season, the reference temperature is corrected by correcting various parameters related to matters such as a large amount of clothing compared to the summer season.

  The fuzzy inference unit 82 includes a capability change amount correction unit 91, a capability change amount calculation unit 92, and a linear calorie calculation unit 93. The ability change amount correction unit 91 applies the reference temperature corrected by the reference temperature correction unit 81, the in-vehicle temperature, the in-vehicle temperature change time using the change gradient of the in-vehicle temperature as parameters, and the in-vehicle humidity to the membership function. Then, correct the air conditioning capacity change amount. The corrected air conditioning capacity change amount is, for example, mapped to a fitness level that is a value between 0 and 1 as a level belonging to various in-vehicle information.

  The capacity change amount calculation unit 92 calculates the air conditioning capacity change amount by applying the fitness to the inference rules. Further, the capacity change amount calculation unit 92 may map the boarding rate, door information, and the like to the degree of fitness using a membership function. The linear calorie calculation unit 93 calculates linear calories based on the air conditioning capacity change amount. That is, the fuzzy inference unit 82 obtains the air conditioning capability change amount by mapping the degree of fit of various in-vehicle information to a preset range and applying the suitability to the inference rule. .

  Next, fuzzy inference will be specifically described. There are two stages in fuzzy inference, for example. That is, a step of calculating a fitness based on a membership function relating to a physical quantity of the vehicle 11 and a step of calculating a control amount of the air conditioning capacity based on an inference rule inferring the calculated fitness based on a precondition, that is, a cooling capacity correction amount. .

  Based on a membership function relating to a change amount as a physical quantity related to the vehicle 11, for example, a temperature difference between a reference temperature that is a target value and a detected current temperature that is a current value, each condition for the in-vehicle environment, for example, a reference The degree of fitness for temperature is calculated. Further, for example, the fitness is calculated in the same manner even for a membership function of a temperature change situation.

  Next, fuzzy inference is performed by applying the calculated fitness to an inference rule. By executing this operation, even if the control condition is in the vicinity of the boundary value, the control amount is automatically calculated and the air conditioner 16 is controlled. For example, by using fuzzy control, fine control between the cooling reference temperature ± 1.0 ° C. is automatically performed.

  The membership function of the temperature difference from the reference temperature maps the input value to a fitness between 0 and 1. Further, for example, the membership function of the temperature change situation maps the input value to a fitness between 0 and 1. In addition, you may set a boarding rate, door information, etc. as conditions. In that case, the membership function of the occupancy rate maps the input occupancy rate to a fitness between 0 and 1, and the membership function of the door information converts the input door information to a fitness between 0 and 1. Map.

  In short, the membership function maps each variable to the degree of fitness of how much it belongs to the set. As a result, even if the condition is ambiguous, the control result is automatically calculated by applying it to the inference rule in which such a condition is set. Further, for example, when a plurality of combined conditions overlap with the same target value, more accurate control can be performed on the target value by adopting a condition with a higher degree of fitness.

  Next, the fitness of each condition mapped by the membership function is applied to a predetermined inference rule. The fitness described above may belong to any of a plurality of ranges. For example, if the temperature difference from the reference temperature is in the range of 0 ° C. to 0.2 ° C., the fitness is “high”, and if the temperature difference is in the range of 0.2 ° C. to 0.4 ° C., the fitness is “slightly”. If it is in the “high” region, and the range is 0.4 ° C. to 0.6 ° C., the fitness is in the “medium” region, and if it is in the range of 0.6 ° C. to 0.8 ° C., the fitness is “slightly low” The degree of conformity may be in the “low” region as long as it is within the range of 0.8 ° C. to 1.0 ° C. Each of “high”, “slightly high”, “medium”, “slightly low”, and “low” defined in this way is applied to the premise of the inference rule. The same processing is performed for other membership functions. At this time, for example, when the temperature difference from the reference temperature is in the range of 0 ° C. to 0.2 ° C., the fitness does not have to be a constant value. You may make it decrease.

  Separately, the temperature difference from the reference temperature is classified as 0.2 ° C., 0.4 ° C., 0.6 ° C., 0.8 ° C., and 1.0 ° C. At that time, 0.2 ° C is “high”, 0.4 ° C is “slightly high”, 0.6 ° C is “medium”, 0.8 ° C is “slightly low”, and 1.0 ° C is “low”. Suppose that At this time, the fitness of the “high” region decreases as the distance from 0.2 ° C., the fitness of the “slightly” region decreases as the distance from 0.4 ° C., and the “medium” region decreases as the distance from 0.6 ° C. The fitness decreases, and the fitness of the “slightly low” region decreases as the distance from 0.8 ° C. increases, and the fitness of the “low” region decreases as the distance from 1.0 ° C. increases.

  Therefore, it may be considered that the temperature difference between the reference temperature and the in-vehicle temperature belongs to both the “high” region and the “slightly high” region. At this time, a condition with a higher degree of fitness is employed. For example, if the fitness level of the “high” region is 0.85 and the fitness level of the “slightly high” region is 0.25 for the same temperature difference, it is regarded as belonging to the “high” region. The goodness of fit is applied to the precondition of the inference rule as “high”. As a result of such an example of operation, fuzzy control can continue arithmetic processing even when the boundary value is ambiguous.

  Further, for example, a membership function of the amount of clothes can be considered as another condition. In this case, since it is the amount of clothes, for example, it is assumed that classification is made as “thick clothes”, “slightly thick clothes”, “medium”, “slightly light clothes”, “light clothes”. At this time, a case where the “thickly worn” region and the “slightly thickened” region overlap may be considered. At this time, the one with a higher fitness is adopted as a condition. For example, if the fitness level of the “thick clothing” region is 0.8 and the fitness level of the “slightly thick clothing” region is 0.2, it is regarded as being in the “thick clothing” region, and the fitness level is 0.8. It is processed as an inference rule.

  Next, for example, the correction amount for the current cooling capacity is calculated according to the following inference rule (Equation 1).

if (Temperature difference from the reference temperature is “Low”) and (Temperature change is “Small”) and (Riding rate is “Full”) and (Door information is “Open”) then Air conditioning capacity 100% (Equation 1 )

  The above formula is only an example, and a solution is obtained by sequentially searching a number of rules that satisfy each condition of goodness of fit. Therefore, in some cases, it takes a long time to search for a solution. In other words, the fuzzy control is an accumulative calculation process and is suitable for fine fine control, but has low response to a sudden change. Therefore, when responsiveness of abrupt changes is required, processing may be assigned to the area proportional control module 73 described later.

  In addition, the condition of the “if” statement (temperature difference from the reference temperature is “low”) does not mean that the temperature difference from the reference temperature is low, but the degree of conformance to the temperature difference from the reference temperature is low, that is, This means that it is far from the reference temperature, and other conditions are interpreted in the same manner.

  More specifically, the “if” sentence as the inference rule is a calculation of the fitness converted into a numerical value. Then, the final control amount is calculated by cumulatively adding the results of the operations by a large number of if statements. That is, cumulative calculation processing is executed. Therefore, the final control amount calculation processing is awaited until all the calculation results of the respective if statements are obtained. Therefore, the calculation of fuzzy control requires processing time depending on conditions.

  The step calorie calculating unit 83 calculates step calories that are stages of air conditioning capability. As a result, a step calorie for air conditioning control corresponding to a change in the vehicle interior is calculated based on fuzzy inference.

  FIG. 6 is a diagram illustrating an example of a functional configuration of the area proportional control module 73 according to the first embodiment of the present invention. As shown in FIG. 6, the area proportional control module 73 includes a cooling reference temperature determination unit 101, an in-vehicle temperature range determination unit 102, a step calorie setting unit 103, an in-vehicle humidity range determination unit 104, an air blowing operation determination unit 105, and an air blowing operation. A setting unit 106 is provided.

  The cooling reference temperature determination unit 101 determines whether the in-vehicle temperature exceeds the cooling reference temperature. When the vehicle interior temperature exceeds the cooling reference temperature, the cooling reference temperature determination unit 101 causes the vehicle interior temperature range determination unit 102 to determine a finer temperature range. When the vehicle interior temperature does not exceed the cooling reference temperature, the cooling reference temperature determination unit 101 causes the vehicle interior humidity range determination unit 104 to determine the range of vehicle interior humidity.

  The vehicle interior temperature range determination unit 102 determines which region the vehicle interior temperature belongs to. The area referred to here is an area determined according to the degree of separation between the vehicle interior temperature and the cooling reference temperature, which will be described later with reference to FIG.

  The step calorie setting unit 103 sets a step calorie that is a stage of the air conditioning capability based on the determined area.

  The in-vehicle humidity range determination unit 104 determines to which region the in-vehicle humidity belongs. The region here will be described later with reference to FIG. The air blowing operation determination unit 105 determines whether or not to perform the air blowing operation by applying the vehicle interior temperature and the vehicle interior humidity to a range defined by the region outlined above. The blower operation setting unit 106 generates a blower operation command.

  FIG. 7 is a diagram showing an example of an operation pattern of region proportional control in Embodiment 1 of the present invention. As shown in FIG. 7, a temperature region and a humidity region are respectively set as a band-shaped range based on a control temperature (° C.) that is a vehicle interior temperature and a vehicle humidity (% RH) that is a relative humidity. The air conditioner 16 is controlled by assigning the operating capacity of the air conditioner, specifically, the operating rate of the compressor. TSC is the cooling reference temperature.

  For example, step calories are set in five stages. Specifically, in the first stage P1, the air conditioning capacity is 0%, that is, the air blowing operation is performed, in the second stage P2, the air conditioning capacity is 25%, in the third stage P3, the air conditioning capacity is 50%, and in the fourth stage. In a certain P4, the air conditioning capacity is 75%, and in the fifth stage P5, the air conditioning capacity is 100%. In this way, a total of five stages of air conditioning capability control can be set.

  More specifically, when the vehicle interior temperature is within the range between the cooling reference temperature and the cooling reference temperature + 0.5 ° C., the air conditioning capacity is 50%, and when the vehicle interior temperature is within the range of + 0.5 ° C. and + 1.0 ° C. with respect to the cooling reference temperature. Air conditioning capacity is 75%, air conditioning capacity is 100% in the range of + 1.0 ° C and + 2.0 ° C relative to the cooling reference temperature, -0.5 ° C from the cooling reference temperature and the cooling reference temperature, and the inside humidity is 60% RH When it is in the range of 100% RH, the air conditioning capacity is 25%. When the inside humidity is 60% RH or less and the inside temperature is in the range of −1.5 ° C. with respect to the cooling reference temperature and the cooling reference temperature, the air conditioning capacity is 0%. Blowing operation, when the inside humidity is in the range of 60% RH and 100% RH and the inside temperature is in the range of −0.5 ° C. and −1.5 ° C. with respect to the cooling reference temperature, the blowing operation having an air conditioning capacity of 0%, As shown in Fig. It is.

  In both the fuzzy control and the area proportional control, when the humidity is high during the cooling operation, the dehumidifying operation may be performed to deal with the heat of sultry.

  FIG. 8 is a diagram illustrating an example of a functional configuration of the automatic adjustment unit 76 according to Embodiment 1 of the present invention. As shown in FIG. 8, the automatic adjustment unit 76 includes a storage unit 111, a timing unit 151, an operation cycle determination unit 152, a control flag determination unit 153, a number determination unit 154, a temperature comparison unit 155, and the like.

  The storage unit 111 includes a region proportional control flag 121, a fuzzy control flag 122, operation cycle data 123, number-of-times upper limit data 124, number-of-times determination value data 125, operation data 126, and the like. The driving data 126 includes train-related data 131, control-related data 132, calendar data 133, time data 134, in-vehicle temperature data 135, reference temperature data 136, and the like.

  The area proportional control flag 121 is a flag for determining whether or not the area proportional control is executed. The fuzzy control flag 122 is a flag for determining whether or not fuzzy control is executed. The operation cycle data 123 is data in which an operation cycle that is a timing for performing a data accumulation process described later is set. For example, the operation cycle is set to one day. In this case, it is set so that data accumulation and comparison processing of the data of a plurality of different control methods can be automatically executed every day.

  The upper limit number of times data 124 is data in which an upper limit value of the number of times of performing data accumulation processing to be described later is set. The number-of-times determination value data 125 is data for counting the number of times of performing data accumulation processing described later. The number determination value data 125 is associated with, for example, one time as an initial value.

  The operation data 126 is various data stored during a data storage process described later. The train-related data 131 is associated with the type of train at the time of executing the data accumulation process, for example, the type of structure of the vehicle 11 such as the Shinkansen. The control related data 132 is associated with the control related data 132 at the time of executing the data accumulation process, for example, the type of driving during operation of the vehicle 11 such as high speed driving. The calendar data 133 is associated with the calendar when the data storage process is executed. The time data 134 is associated with the time when the data accumulation process is executed. The in-vehicle temperature data 135 is associated with the in-vehicle temperature of the vehicle 11 when the data accumulation process is executed. The reference temperature data 136 is associated with the reference temperature data 136 applied in the vehicle 11 at the time of executing the data accumulation process, for example, the cooling reference temperature.

  The timer 151 measures the operation cycle. The operation cycle determination unit 152 determines whether or not the operation cycle has arrived based on the result of the timer unit 151. The control flag determination unit 153 determines a control method such as region proportional control or fuzzy control flag 122. As the control method, the area proportional control method and the fuzzy control method have been described as examples, but the control method is not particularly limited thereto. In short, any control method may be used as long as it controls the air conditioner 16 with a different algorithm.

  The number determination unit 154 determines the number of executions of data storage processing to be described later. The temperature comparison unit 155 determines which of the difference between the vehicle temperature and the reference temperature during the area proportional control and the difference between the vehicle temperature and the reference temperature during the fuzzy control is smaller during the data comparison process described later. judge.

  FIG. 9 is a flowchart for explaining an operation example of the air conditioning system 50 that determines the control method for each time period in the first embodiment of the present invention. The time zone is not particularly limited. For example, the time zone may be every hour. Further, the time zone may be divided into a plurality of hours, 24 hours a day, such as a morning time zone, a noon time zone, and a night time zone. In short, it is only necessary to set a reference time as a minimum unit of time and set each of a plurality of different time zones by using the reference time. The reference time is, for example, 1 hour. When set in this way, the day can be divided into three times as described above. In addition, the setting and setting method of the time zone demonstrated above show an example, and are not specifically limited to these.

  Note that when executing the data comparison process, it is assumed that the comparison process is executed when the boarding ratio is the same and the outside air temperature is the same. By providing such a restriction, a more accurate comparison process is executed.

(Data accumulation processing)
(Step S11)
The automatic adjustment unit 76 determines whether or not an operation cycle has arrived. The automatic adjustment unit 76 proceeds to step S12 when the operation cycle has arrived. On the other hand, when the operation cycle does not arrive, the automatic adjustment unit 76 returns to step S11.

(Step S12)
The automatic adjustment unit 76 acquires a control flag.

(Step S13)
The automatic adjustment unit 76 determines whether or not the region proportional control flag 121 is 1. If the area proportional control flag 121 is 1, the automatic adjustment unit 76 proceeds to step S14. On the other hand, if the area proportional control flag 121 is not 1, the automatic adjustment unit 76 proceeds to step S22.

(Step S14)
The automatic adjustment unit 76 supplies a region proportional control command.

(Step S15)
The automatic adjustment unit 76 sets the area proportional control flag 121 to 0.

(Step S16)
The automatic adjustment unit 76 sets the fuzzy control flag 122 to 1.

(Step S17)
The automatic adjustment unit 76 acquires the operation data 126.

(Step S18)
The automatic adjustment unit 76 acquires a number determination value.

(Step S19)
The automatic adjustment unit 76 acquires the number of times upper limit value.

(Step S20)
The automatic adjustment unit 76 determines whether or not the number determination value is equal to or less than the number upper limit value. The automatic adjustment unit 76 proceeds to step S21 when the number determination value is equal to or less than the number upper limit value. On the other hand, when the number determination value is not less than or equal to the upper limit value, the automatic adjustment unit 76 proceeds to step S26.

(Step S21)
The automatic adjustment unit 76 increments the number determination value and returns to step S11.

(Step S22)
The automatic adjustment unit 76 determines whether or not the fuzzy control flag 122 is 1. If the fuzzy control flag 122 is 1, the automatic adjustment unit 76 proceeds to step S23. On the other hand, when the fuzzy control flag 122 is not 1, the automatic adjustment unit 76 returns to step S11.

(Step S23)
The automatic adjustment unit 76 supplies a fuzzy control command.

(Step S24)
The automatic adjustment unit 76 sets the fuzzy control flag 122 to 0.

(Step S25)
The automatic adjustment unit 76 sets the area proportional control flag 121 to 1 and proceeds to step S17.

(Data comparison process)
(Step S26)
The automatic adjustment unit 76 acquires the operation data 126 of the area proportional control in a predetermined time zone.

(Step S27)
The automatic adjustment unit 76 acquires the operation data 126 of fuzzy control in a predetermined time zone.

(Step S28)
The automatic adjustment unit 76 determines whether the boarding rate is within a predetermined range. If the boarding rate is within a predetermined range, the automatic adjustment unit 76 proceeds to step S29. On the other hand, when the boarding rate is not within the predetermined range, the automatic adjustment unit 76 proceeds to step S38.

(Step S29)
The automatic adjustment unit 76 determines whether or not the outside air temperature is within a predetermined range. If the outside air temperature is within a predetermined range, the automatic adjustment unit 76 proceeds to step S30. On the other hand, if the outside air temperature is not within the predetermined range, the automatic adjustment unit 76 proceeds to step S38.

(Step S30)
The automatic adjustment unit 76 obtains the difference between the in-vehicle temperature and the reference temperature in the case of area proportional control.

(Step S31)
The automatic adjustment unit 76 sets the obtained difference as the first value.

(Step S32)
The automatic adjustment unit 76 obtains the difference between the vehicle interior temperature and the reference temperature in the case of fuzzy control.

(Step S33)
The automatic adjustment unit 76 sets the obtained difference as the second value.

(Step S34)
The automatic adjustment unit 76 determines whether or not the first value is smaller than the second value. If the first value is smaller than the second value, the automatic adjustment unit 76 proceeds to step S35. On the other hand, if the first value is not smaller than the second value, the automatic adjustment unit 76 proceeds to step S36.

(Step S35)
The automatic adjustment unit 76 associates a predetermined time zone with area proportional control.

(Step S36)
The automatic adjustment unit 76 determines whether or not the second value is smaller than the first value. If the second value is smaller than the first value, the automatic adjustment unit 76 proceeds to step S37. On the other hand, if the second value is not smaller than the first value, the automatic adjustment unit 76 proceeds to step S38.

(Step S37)
The automatic adjustment unit 76 associates a predetermined time zone with fuzzy control.

(Step S38)
The automatic adjustment unit 76 determines whether there is a predetermined time period during which no data comparison is performed. If there is a predetermined time zone during which no data comparison is performed, the automatic adjustment unit 76 proceeds to step S39. On the other hand, the automatic adjustment unit 76 ends the process when there is no predetermined time period during which data comparison is not performed.

(Step S39)
The automatic adjustment unit 76 shifts the predetermined time zone and returns to step S26. Here, the shift means that the automatic adjustment unit 76 sets another predetermined time zone. That is, it is used in the sense that the processing after step S26 is executed for a time zone for which data comparison has not yet been performed among a plurality of set time zones. For example, 24 hours a day is set as a time zone every hour, and when data comparison is performed for a time zone from 11:00 to 12:00, the next time zone for data comparison is from 13:00 to 14:00 Therefore, the data shift is performed by shifting to the time zone from 13:00 to 14:00.

  As a result of the above processing, the control method with the smaller difference between the in-vehicle temperature and the reference temperature is associated with each time zone. Therefore, the automatic adjustment unit 76 can confirm the control method associated with each time zone, so that the control method with the smaller difference between the in-vehicle temperature and the reference temperature can be confirmed, so the optimum control method is selected. can do.

  FIG. 10 is a flowchart illustrating an operation example of the air conditioning system 50 that determines the control method for each time zone including the air conditioning control parameter 80 according to Embodiment 1 of the present invention. Here, the process of step S54 and the process of step S64 are additional processes as processes including the air conditioning control parameter 80. That is, the air conditioning control parameter 80 is changed in order to reduce the difference between the in-vehicle temperature and the reference temperature, regardless of whether the control is area proportional control or fuzzy control.

  The method of changing is not particularly limited. For example, if the difference between the in-vehicle temperature and the reference temperature is large, the fluctuation range of the air conditioning control parameter 80 is set to be large again in order to quickly reduce the difference. Specifically, the rule that the set temperature is lowered by 1 ° C. when the boarding rate is 200% is changed to the rule that when the boarding rate is 200%, the set temperature is lowered by 2 ° C. when the difference is not reduced.

  Further, for example, in the rule that the set temperature is lowered by 1 ° C. when the outside air temperature is 30 ° C. or higher, the rule is changed to the rule that the set temperature is lowered by 2 ° C. when the outside temperature is 30 ° C. or higher. . Here, the process of each step of the difference will be described.

(Data accumulation processing)
(Step S54)
The automatic adjustment unit 76 changes the air conditioning control parameter 80.

(Step S64)
The automatic adjustment unit 76 changes the air conditioning control parameter 80.

  From the above description, the air conditioning system 50 automatically selects an optimal control method. Therefore, the air conditioning system 50 can reduce the operating load required for selecting an optimal control method.

  Further, the air conditioning system 50 can be tuned to the optimum control method and the optimum air conditioning control parameter 80 without performing tests and analysis of test results in the current vehicle.

  Moreover, the air conditioning system 50 can perform tuning suitable for the conditions for each time zone.

  As described above, in the first embodiment, the air conditioning controller 17 provided with at least two control modules for controlling the air conditioner 16 mounted on the vehicle 11, the selection of the control module corresponding to the air conditioner 16, and the air conditioner 16. And an automatic adjustment unit 76 that adjusts the air-conditioning control parameter 80 corresponding to each of the control modules. Each of the control modules controls the air-conditioning device 16 with a different algorithm. According to the control module selected by the adjusting unit 76, the air conditioner 16 is controlled based on the in-vehicle temperature of the vehicle 11 and the reference temperature determined corresponding to the vehicle 11, and the automatic adjusting unit 76 As the operation data 126 of 16, at least the in-vehicle temperature of the vehicle 11 and the reference temperature of the vehicle 11 are accumulated for each control module, and the in-vehicle temperature and the reference temperature If, based on the difference of the air conditioning system 50 is configured to select the control module.

  Because of the above configuration, the air conditioning system 50 can automatically select an optimal control method, and thus can reduce the operating load required to select the optimal control method.

  In the first embodiment, the air conditioning controller 17 associates each of the control modules with an air conditioning control parameter 80 determined in advance corresponding to the air conditioner 16, and the automatic adjustment unit 76 The control parameter 80 and the operation data 126 are linked and accumulated, and the air conditioning control parameter 80 is adjusted according to the operation data 126 so that the difference is minimized.

  In the first embodiment, the automatic adjustment unit 76 compares the difference between the in-vehicle temperature and the reference temperature for each of a plurality of different time zones, and selects and selects the control module that minimizes the difference. The air conditioning control parameter 80 is adjusted according to the control module.

  In the first embodiment, the automatic adjustment unit 76 sets a reference time as a minimum unit of time, and sets each of a plurality of different time zones by using the reference time.

  Moreover, in this Embodiment 1, the air-conditioning controller 17 is provided with the area | region proportional control module 73 controlled by the step-wise capability value of the air conditioner 16 based on the vehicle interior temperature and the vehicle interior humidity of the vehicle 11 as a control module. The automatic adjustment unit 76 selects the area proportional control module 73 based on the difference between the in-vehicle temperature and the reference temperature.

  Moreover, in this Embodiment 1, the air-conditioning controller 17 is a control module, and fuzzy control which controls with the step-wise capability value of the air-conditioning apparatus 16 based on at least a vehicle interior temperature, a membership function, and a fuzzy inference rule. The automatic adjustment unit 76 includes a module 74 and selects the fuzzy control module 74 based on the difference between the in-vehicle temperature and the reference temperature.

  Therefore, since the air conditioning system 50 can automatically select the optimal control method, the operating load required for selecting the optimal control method can be particularly remarkably reduced.

Embodiment 2. FIG.
The difference from the first embodiment is that data is determined for each season. FIG. 11 is a flowchart for explaining an operation example of the air conditioning system 50 that determines the control method for each season in the second embodiment of the present invention. In the second embodiment, the process for determining for each time zone in the first embodiment is changed to the process for determining for each season. Here, the process of each step of the difference will be described.

(Data comparison process)
(Step S106)
The automatic adjustment unit 76 acquires the operation data 126 of the predetermined region proportional control for the season.

(Step S107)
The automatic adjustment unit 76 acquires operation data 126 of fuzzy control for a predetermined season.

(Step S115)
The automatic adjustment unit 76 associates a predetermined season with area proportional control.

(Step S117)
The automatic adjustment unit 76 associates a predetermined season with fuzzy control.

(Step S118)
The automatic adjustment unit 76 determines whether there is a predetermined season for which data comparison is not performed. If there is a predetermined season in which data comparison is not performed, the automatic adjustment unit 76 proceeds to step S119. On the other hand, the automatic adjustment unit 76 ends the process when there is no predetermined season in which data comparison is not performed.

(Step S119)
The automatic adjustment unit 76 shifts a predetermined season. The shift here means that the automatic adjustment unit 76 sets another predetermined season.

  FIG. 12 is a flowchart for explaining a control example of the air conditioning system 50 that determines the control method for each season including the air conditioning control parameter 80 according to the second embodiment of the present invention. Here, the processing in step S134 and the processing in step S144 are additional processing as processing including the air conditioning control parameter 80. That is, the air conditioning control parameter 80 is changed in order to reduce the difference between the in-vehicle temperature and the reference temperature, regardless of whether the control is area proportional control or fuzzy control.

  The method of changing is not particularly limited. For example, if the difference between the in-vehicle temperature and the reference temperature is large, the fluctuation range of the air conditioning control parameter 80 is set to be large again in order to quickly reduce the difference. Specifically, the rule that the set temperature is lowered by 1 ° C. when the boarding rate is 200% is changed to the rule that when the boarding rate is 200%, the set temperature is lowered by 2 ° C. when the difference is not reduced.

  Further, for example, in the rule that the set temperature is lowered by 1 ° C. when the outside air temperature is 30 ° C. or higher, the rule is changed to the rule that the set temperature is lowered by 2 ° C. when the outside temperature is 30 ° C. or higher. . Here, the process of each step of the difference will be described.

(Data accumulation processing)
(Step S134)
The automatic adjustment unit 76 changes the air conditioning control parameter 80.

(Data accumulation processing)
(Step S144)
The automatic adjustment unit 76 changes the air conditioning control parameter 80.

  From the above description, the air conditioning system 50 automatically selects an optimal control method for each season. Therefore, the air conditioning system 50 can reduce the operating load required for selecting an optimal control method.

  Further, the air conditioning system 50 can perform tuning suitable for seasonal conditions.

  As described above, in the second embodiment, the automatic adjustment unit 76 compares the difference between the vehicle interior temperature and the reference temperature for each predetermined season, selects the control module that minimizes the difference, and selects the selected control. The air conditioning control parameter 80 is adjusted according to the module.

  Because of the above configuration, the air conditioning system 50 can automatically select the optimal control method for each season, and thus the operating load required for selecting the optimal control method can be particularly reduced.

Embodiment 3 FIG.
The difference from Embodiment 1 and Embodiment 2 is that data is determined for each type of train. FIG. 13 is a flowchart illustrating an operation example of the air conditioning system 50 that determines the control method for each type of train in the third embodiment of the present invention. In the first embodiment, the process is determined for each time zone. In the second embodiment, the process is determined for each season. However, in the third embodiment, the process is changed to the process for determining each type of train. Yes.

  The types of trains are assumed to be, for example, the types of structures such as commuter trains, bullet trains, and trams, and the types of driving during operations such as high speed, limited express, and each station. In addition, the kind of train demonstrated above is an example, Comprising: It does not specifically limit to these. Here, the process of each step of the difference will be described.

(Data comparison process)
(Step S206)
The automatic adjustment unit 76 acquires the operation data 126 of the area proportional control of a predetermined type of train.

(Step S207)
The automatic adjustment unit 76 acquires operation data 126 for fuzzy control of a predetermined type of train.

(Step S215)
The automatic adjustment unit 76 associates a predetermined type of train with area proportional control.

(Step S217)
The automatic adjustment unit 76 associates a predetermined type of train with fuzzy control.

(Step S218)
The automatic adjustment unit 76 determines whether or not there is a predetermined type of train for which data comparison is not performed. If there is a predetermined type of train that has not been compared, the automatic adjustment unit 76 proceeds to step S219. On the other hand, the automatic adjustment unit 76 ends the process when there is no predetermined type of train for which no data comparison is performed.

(Step S219)
The automatic adjustment unit 76 shifts a predetermined type of train. The shift here means that the automatic adjustment unit 76 sets another predetermined type of train.

  FIG. 14 is a flowchart illustrating an operation example of the air conditioning system 50 that determines the control method for each type of train including the air conditioning control parameter 80 according to Embodiment 3 of the present invention. Here, the processing in step S234 and the processing in step S244 are additional processing as processing including the air conditioning control parameter 80. That is, the air conditioning control parameter 80 is changed in order to reduce the difference between the in-vehicle temperature and the reference temperature, regardless of whether the control is area proportional control or fuzzy control.

  The method of changing is not particularly limited. For example, if the difference between the in-vehicle temperature and the reference temperature is large, the fluctuation range of the air conditioning control parameter 80 is set to be large again in order to quickly reduce the difference. Specifically, the rule that the set temperature is lowered by 1 ° C. when the boarding rate is 200% is changed to the rule that when the boarding rate is 200%, the set temperature is lowered by 2 ° C. when the difference is not reduced.

  Further, for example, in the rule that the set temperature is lowered by 1 ° C. when the outside air temperature is 30 ° C. or higher, the rule is changed to the rule that the set temperature is lowered by 2 ° C. when the outside temperature is 30 ° C. or higher. . Here, the process of each step of the difference will be described.

(Data accumulation processing)
(Step S234)
The automatic adjustment unit 76 changes the air conditioning control parameter 80.

(Data accumulation processing)
(Step S244)
The automatic adjustment unit 76 changes the air conditioning control parameter 80.

  From the above description, the air conditioning system 50 automatically selects an optimal control method for each type of train. Therefore, the air conditioning system 50 can reduce the operating load required for selecting an optimal control method.

  Further, the air conditioning system 50 can perform tuning suitable for the conditions for each type of train.

  As described above, in Embodiment 3, the automatic adjustment unit 76 compares the difference between the in-vehicle temperature and the reference temperature for each predetermined type of train, selects the control module that minimizes the difference, and selects the control module. The air conditioning control parameter 80 is adjusted according to the control module.

  Further, in the third embodiment, the automatic adjustment unit 76 sets the predetermined train type based on at least one of the type of structure of the vehicle 11 and the type of driving during operation of the vehicle 11. To set.

  Because of the above configuration, the air conditioning system 50 can automatically select the optimal control method for each type of train, and therefore the operating load required for selecting the optimal control method can be particularly reduced.

  10 trains, 11, 11_1, 11_2, 11_3 vehicles, 12 crew members, 13, 13_1, 13_2 guest rooms, 14, 14_1, 14_2 vehicle information control devices, 15 train information management devices, 16, 16_1, 16_2 air conditioning devices, 17, 17_1, 17_2 Air conditioning controller, 20, 20_1, 20_2 Humidity sensor, 21, 21_1, 21_2 Return temperature sensor, 22, 22_1, 22_2 Wall temperature sensor, 23, 23_1, 23_2 Variable load sensor, 31 Refrigerant circuit, 41 Air conditioning inverter Equipment, 50 air conditioning system, 51, 51_1, 51_2 air conditioning compressor, 52 indoor heat exchanger, 53 expansion device, 54 outdoor heat exchanger, 61 indoor blower, 62, 62_1, 62_2 outdoor blower, 63 outdoor blower drive unit, 71 Input part, 7 2 control switching unit, 73 area proportional control module, 74 fuzzy control module, 75 output unit, 76 automatic adjustment unit, 80 air conditioning control parameter, 81 reference temperature correction unit, 82 fuzzy inference unit, 83 step calorie calculating unit, 91 capability change Amount correction unit, 92 capacity change amount calculation unit, 93 linear calorie calculation unit, 101 cooling reference temperature determination unit, 102 in-vehicle temperature range determination unit, 103 step calorie setting unit, 104 in-vehicle humidity range determination unit, 105 blower operation determination unit, 106 air blow operation setting unit, 111 storage unit, 121 area proportional control flag, 122 fuzzy control flag, 123 operation cycle data, 124 times upper limit value data, 125 times determination value data, 126 operation data, 131 train related data, 132 control related Data, 133 calendar data, 1 4 hours data, 135 interior temperature data, 136 the reference temperature data, 151 clock unit, 152 operation cycle determining unit, 153 control flag determining unit, 154 times judging unit, 155 temperature comparing section.

Claims (8)

An air-conditioning controller provided with at least two control modules for controlling an air-conditioning device mounted on the vehicle;
An automatic adjustment unit that performs selection of the control module corresponding to the air conditioner and adjustment of an air conditioning control parameter corresponding to the air conditioner;
With
Each of the control modules
The air conditioner is controlled by a different algorithm,
The automatic adjustment unit
For each control module, the air conditioner is controlled,
As the operation data of the air conditioner, at least the interior temperature of the vehicle and the reference temperature of the vehicle are accumulated for each control module,
Based on a comparison of the difference between the in-vehicle temperature for each control module and the reference temperature, the control module is selected,
The air conditioning controller
According to the control module selected by the automatic adjustment unit, the air conditioner is controlled based on an in-vehicle temperature of the vehicle and a reference temperature determined corresponding to the vehicle. system. The air conditioning controller
Linking each of the control modules with a predetermined air conditioning control parameter corresponding to the air conditioner,
The automatic adjustment unit
While storing the previous SL operation data, the selection of the control module, repeated at set headway,
2. The air conditioning system according to claim 1 , wherein the air conditioning control parameter is changed to reduce a difference between the in-vehicle temperature and the reference temperature based on the accumulated operation data. The air conditioning system according to claim 1 or 2, wherein the selection of the control module by the automatic adjustment unit is performed for a plurality of different time zones . The automatic adjustment unit
The reference time is set as the minimum unit of time,
The air conditioning system according to claim 3, wherein each of the plurality of different time zones is set by using the reference time. The air conditioning system according to claim 1 or 2, wherein the selection of the control module by the automatic adjustment unit is performed for each predetermined season . The air conditioning system according to claim 1 or 2, wherein the selection of the control module by the automatic adjustment unit is performed for each predetermined type of train . The automatic adjustment unit
7. The predetermined type of train is set based on at least one of the type of structure of the vehicle and the type of driving during operation of the vehicle. Air conditioning system. The control module is
An area proportional control module that controls the air conditioner in stepwise capacity values based on the in-vehicle temperature and the in-vehicle humidity of the vehicle;
A fuzzy control module that controls at least stepwise capacity values of the air conditioner based on the in-vehicle temperature, a membership function, and fuzzy inference rules
The air conditioning system according to any one of claims 1 to 7, wherein

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