Abnormality countermeasure system and abnormality countermeasure method

Abstract

The purpose of the present invention is to, when there is an abnormality in an electric vehicle equipped with a drive system which uses a storage battery device, identify not only the abnormality location but also the cause of the abnormality, and easily acquire an abnormality countermeasure proposal including changes to the operation method of the electric vehicle.　The abnormality countermeasure system according to the present invention can be used in an electric vehicle equipped with a drive system which uses a storage battery device. A cause determination unit monitors the state of the electric vehicle and the storage battery device, and, when an abnormality flag has been outputted from at least one of the electric vehicle and the storage battery device, analyzes the state of at least one of the electric vehicle and the storage battery device to identify the cause of the abnormality indicated by the abnormality flag. A countermeasure proposal unit notifies a manager of the electric vehicle about the countermeasure proposal and the cause analysis results of the abnormality flag. The countermeasure proposal includes the following categories: changes to the operation method of the electric vehicle, changes to the control parameters of the storage battery device or the drive system, repairs to faulty software or faulty equipment in the storage battery device or the drive system, and replacement of a degraded storage battery.

Description

Abnormality countermeasure system and abnormality countermeasure method

[0001] The present invention relates to an abnormality countermeasure system used in an electric vehicle equipped with a storage battery.

[0002] Railway lines have electrified sections where rolling stock can receive power from overhead lines, and non-electrified sections where there are no overhead lines and no power supply. With conventional railway technology, rolling stock ran on diesel engines on non-electrified sections. In recent years, advances in lithium-ion battery technology have led to the introduction of vehicles that use batteries as their energy source, such as hybrid diesel railcars and battery-powered electric railcars. Hybrid diesel railcars are conventional diesel railcars equipped with a battery system that charges regenerative electricity during braking and provides assistance from the battery and motor during powering. Battery-powered electric railcars are rolling stock equipped with a rechargeable battery system that serves as their traction energy source. On electrified sections, they receive power from overhead lines, which is used for traction energy and charges the battery system, and on non-electrified sections, they run on the battery as their energy source.

[0003] Storage batteries used to drive such rail vehicles are generally used under heavy loads, and abnormalities that cause the battery condition to fall outside of its specification range can occur. Typical storage battery abnormalities include overtemperature, overvoltage, and excessive charge rate. An abnormality is detected when the control system reads measurements that monitor the battery condition and detects an abnormality by detecting a value that exceeds an abnormality threshold. The battery control system or vehicle control system takes action when an abnormality is detected. These actions typically include issuing a warning, restricting battery use, or disconnecting the battery. Taking action can result in a decrease in vehicle performance or even a suspension of operation. When an abnormality is detected, the control system issues an abnormality flag corresponding to the abnormality, notifies the driver of the type of abnormality that has occurred, and records the abnormality flag along with various vehicle data on a recording medium inside or outside the vehicle.

[0004] As an example of a system for detecting abnormalities in such railway vehicles, Patent Document 1 discloses a railway vehicle power storage facility and a railway vehicle power storage element monitoring system that include power storage elements, a battery management device that acquires power storage element information related to the state of the power storage elements, and a communication device that transmits the power storage element information acquired by the battery management device to an external device. Patent Document 2 also discloses a method of entering into various service contracts with a railway company for all or part of the devices and equipment of an electric vehicle 200, constantly monitoring the operating status of the devices and equipment on board the contracted electric vehicle 200, or recording information obtained by measuring various data using a transceiver installed on board, or providing the contracted information or service to a location designated by the railway company on the ground when a contracted event occurs.

[0005] JP 2021-019479 A JP 2002-329020 A

[0006] The inventors of the present application have thoroughly studied countermeasures for abnormalities in railway vehicles equipped with battery storage systems, and have come to the following conclusion. Even for the same abnormality flag, the effective countermeasure will differ depending on the cause. For example, suppose an abnormality flag is triggered when the battery becomes overheated (a phenomenon in which the temperature exceeds the specified range). There are various possible causes of the overheating, such as high ambient temperature, a heavy load on the battery, battery deterioration resulting in increased electrical resistance, a cooling device that is not working, or a faulty temperature sensor, and the effective countermeasure will differ depending on the cause.

[0007] On the other hand, when an abnormality flag is raised, it is not easy to identify its cause. Typically, the system only provides information on the type of abnormality flag and the date and time of its occurrence. When investigating the cause, a person with sufficient knowledge of the relevant railway vehicle and battery system carefully analyzes data at the time of the abnormality and its surroundings to identify the cause of the abnormality. In this regard, Patent Document 2 shows an example in which, when a fault flag is raised in an electric vehicle, by calling up related data and fault know-how corresponding to the fault flag, even a non-engineer can identify the fault location, provide instructions to the driver in the cab to stop the vehicle, notify the driver of the replacement location, and arrange for parts to be replaced. However, Patent Document 2 only identifies the fault location, and while it is possible to replace the faulty part, it does not further indicate the cause of the abnormality or suggest a method for continuing to use the vehicle without malfunction.

[0008] Therefore, the present invention aims to identify not only the location of the abnormality but also the cause of the abnormality when an abnormality occurs in an electric vehicle equipped with a drive system that uses a storage battery device, and to easily obtain a countermeasure against the abnormality, including changing the operating method of the electric vehicle.

[0009] In order to solve the above problems, a representative anomaly countermeasure system of the present invention is an anomaly countermeasure system used in an electric vehicle equipped with a drive system that uses a storage battery device, the anomaly countermeasure system having a cause determination unit and a countermeasure proposal unit, the cause determination unit monitors the status of the electric vehicle and the storage battery device, and when an abnormality flag is output from at least one of the electric vehicle and the storage battery device, analyzes the status of at least one of the electric vehicle and the storage battery device and identifies the cause of the abnormality indicated by the abnormality flag, the countermeasure proposal unit notifies the manager of the electric vehicle of the results of the analysis of the cause of the abnormality flag and countermeasure proposals, and the countermeasure proposals include classification into changes to the operation method of the electric vehicle, changes to control parameters of the storage battery device or the drive system, repairs to defective software or defective equipment of the storage battery device or the drive system, and replacement of degraded storage batteries.

[0010] According to the present invention, when an abnormality occurs in an electric vehicle equipped with a traction system that uses a storage battery device, it is possible to identify not only the location of the abnormality but also the cause of the abnormality, and even if a person does not have sufficient knowledge of both the traction system that uses a storage battery device and the electric vehicle equipped with that traction system, it is possible to obtain a countermeasure plan, including changing the operation method of the electric vehicle, and to achieve early recovery. Problems, configurations, and effects other than those described above will become clear from the description of the following embodiments.

[0011] FIG. 1 is a diagram illustrating the configuration of a traction system for a railway vehicle equipped with a storage battery to which an abnormality countermeasure system according to a first embodiment of the present invention is applied. FIG. 2 is a diagram illustrating the system configuration of a traction system for a hybrid diesel railcar. FIG. 3 is a basic operational block diagram of the abnormality countermeasure system according to the first embodiment of the present invention. FIG. 4 is a diagram illustrating an abnormality cause weight table when an abnormality flag indicates a battery overtemperature. FIG. 5 is an operational block diagram of a cause determination unit that calculates a cause weight by comparing with past data according to the first embodiment of the present invention. FIG. 6 is a diagram illustrating calculations performed by a cause weight calculation unit included in the cause determination unit. FIG. 7 is an operational block diagram of a cause determination unit when a digital twin according to the first embodiment of the present invention is applied. FIG. 8 is an operational block diagram of a model verification unit according to the first embodiment of the present invention. FIG. 9 is an operational block diagram of a sensitivity calculation unit according to the first embodiment of the present invention. FIG. 10 is a diagram illustrating an example of an operational block diagram of a battery digital twin according to the first embodiment of the present invention. FIG. 11 is a diagram illustrating an example of a sensitivity map when an abnormality flag indicates a battery overtemperature. FIG. 12 is an operational block diagram of a countermeasure proposal unit according to the first embodiment of the present invention. FIG. 13 is a diagram illustrating an effective countermeasure table in which countermeasures corresponding to cause categories are associated with each other. FIG. 14 is a diagram showing an example of a countermeasure effect map. FIG. 15 is a diagram showing an example of displaying countermeasure information. FIG. 16 is an operational block diagram of an abnormality countermeasure system having a true / false determination unit 33 according to a second embodiment of the present invention. FIG. 17 is an operational block diagram of an abnormality countermeasure system having a control constant change unit according to a third embodiment of the present invention. FIG. 18 is an operational block diagram of an abnormality countermeasure system having an abnormality sign diagnosis unit according to a fourth embodiment of the present invention. FIG. 19 is an operational block diagram of an abnormality countermeasure system having an emergency measure proposal unit according to a fifth embodiment of the present invention. FIG. 20 is an operational block diagram of an abnormality countermeasure system for transmitting to a manufacturer according to a sixth embodiment of the present invention. FIG. 21 is an operational block diagram of an abnormality countermeasure system having a spread evaluation unit according to the sixth embodiment of the present invention. FIG. 22 is a diagram showing the configuration of a traction system for a railway vehicle equipped with a storage battery to which an abnormality countermeasure system according to an eighth embodiment of the present invention is applied.

[0012] Hereinafter, an embodiment of an abnormality countermeasure proposal system according to the present invention will be described with reference to the accompanying drawings. Note that the present invention is not limited to this embodiment. Furthermore, in the drawings, identical parts are designated by the same reference numerals. In the embodiment described below, an abnormality countermeasure proposal system mounted on a railway vehicle will be described as an example, but the present invention is not limited thereto. The present invention can also be applied to, for example, a general stationary storage battery system. Furthermore, the embodiment described below will be described using a lithium-ion battery as an example of the storage battery, but the present invention can be similarly applied to other storage elements such as lead batteries, nickel-metal hydride batteries, or capacitors.

[0013] In addition, in this disclosure, "target parameter" refers to a direct monitoring parameter corresponding to an abnormality flag. "Related parameter" refers to a parameter other than the target parameter that is related to the abnormality flag. "Digital twin" refers to a model that reproduces the vehicle and battery.

[0014] [Example 1] (Electric vehicle to which a mobility countermeasure system is applied) Figure 1 is a diagram showing the configuration of a traction system 1A for railway vehicles equipped with a storage battery to which an anomaly countermeasure system according to Example 1 of the present invention is applied. In the figure, solid lines indicate power transmission paths, double lines indicate torque transmission paths, and dotted lines indicate transmission paths for information such as control signals and sensor values. In electrified sections, the traction system 1A is driven by power from overhead lines and charges the storage battery, and in non-electrified sections, it uses the power from the storage battery. First, the configuration of the traction system 1A for railway vehicles will be described. Note that the information includes information indicating actual measurements and control signals. The arrows at both ends of the dotted line indicate the direction in which this information is transmitted and received. Also, at least one of the components connected by the dotted line is equipped with a sensor, and the sensor detects the numerical value of the condition of the component. Solid lines are drawn between the overhead line 14 and the pantograph 2, between the pantograph 2 and the converter 5, between the converter 5 and the motor inverter 6, between the converter 5 and the auxiliary inverter 10, between the converter 5 and the battery 20, between the motor inverter 6 and the motor 7, between the motor inverter 6 and the auxiliary inverter 10, between the inverter 6 and the battery 20, between the auxiliary inverter 10 and the battery 20, and between the auxiliary inverter 10 and the auxiliary 11. Double lines are drawn between the motor 7 and the reducer 8 and between the reducer 8 and the wheelset 9. The dotted lines indicate the areas between the vehicle control device 13 and the pantograph 2, between the vehicle control device 13 and the converter 5, between the vehicle control device 13 and the inverter 6 for the electric motor, between the vehicle control device 13 and the electric motor 7, between the vehicle control device 13 and the wheelset 9, between the vehicle control device 13 and the inverter 10 for the auxiliary equipment, between the vehicle control device 13 and the auxiliary equipment 11, between the vehicle control device 13 and the cab 12, between the vehicle control device 13 and the storage battery equipment 20, between the vehicle control device 13 and the abnormality countermeasure system 30, between the cab 12 and the abnormality countermeasure system 30, and between the abnormality countermeasure system 30 and the railway operator's operation control center 40. Communication between the abnormality countermeasure system 30 and the railway operator's operation control center 40 is preferably by wireless communication.

[0015] The traction system 1A for a railway vehicle includes a pantograph 2 that connects the traction system 1A to an overhead wire 14, a converter 5 that converts overhead line power into DC power, an inverter 6 for the electric motor that converts the DC power into AC power, an electric motor 7 that outputs torque for driving the railway vehicle, a reducer 8 that reduces the output of the electric motor 7 and transmits it to a wheel set 9, an inverter 10 for the accessories, accessories 11 used for lighting, air conditioning, etc. of the vehicle, a storage battery device 20, a driver's cab 12 that has a display and generates driving commands in response to notch operation by the driver, a vehicle control device 13 that generates control commands for the converter 5, the inverter 6 for the electric motor, and the inverter 10 for the accessories based on the driving commands transmitted from the driver's cab 12 and the state of the storage battery device 20, and an abnormality countermeasure system 30 that analyzes data from at least one of the storage battery device 20 and the vehicle control device 13 and transmits proposed countermeasures to the driver's cab 12 and a train operation control center 40 managed by the railway operator.

[0016] The pantograph 2 is an electric switch that moves up and down. When the pantograph 2 rises and comes into contact with the overhead wire 14, the DC or AC power supplied by the overhead wire 14 is supplied to the converter 5 via the pantograph 2. When the pantograph 2 is in contact with the overhead wire 14, the battery-powered electric train runs on the power of the overhead wire 14 and charges the storage battery, and when the pantograph 2 is not in contact with the overhead wire 14, it uses the power of the storage battery.

[0017] The converter 5 receives DC or AC power output from the pantograph 2 as input, converts it into DC power corresponding to the commanded amount of power, and outputs it.

[0018] The motor inverter 6 converts the DC power supplied via the converter 5 into three-phase AC power. The motor 7 receives the three-phase AC power output by the motor inverter 6, converts it into axle torque, and outputs it. The speed reducer 8 reduces the rotational speed of the motor 7 by combining gears with different numbers of teeth, and the axle torque thus amplified drives the wheel set 9, accelerating and decelerating the vehicle. A tachograph (not shown) for measuring vehicle speed is also attached to the wheel set 9.

[0019] The auxiliary inverter 10 receives DC power between the converter 5 and the motor inverter 6, converts it into three-phase AC power, and outputs it. The auxiliary equipment 11 is service equipment such as lighting and air conditioning for the vehicle, and operates on the power supplied from the auxiliary inverter 10.

[0020] The driver's cab 12 is equipped with a display that displays the time, vehicle speed, battery information, etc., and an input device that allows the driver to input driving commands, etc., into the vehicle control device 13.

[0021] The storage battery equipment 20 is a device that stores energy to drive the vehicle. It is charged with DC power output from the converter 5 and discharged to the motor inverter 6 and the auxiliary inverter 10. When the vehicle is applying regenerative braking, it is charged with DC power output from the motor inverter 6. The storage battery equipment 20 is equipped with a battery control device 21. The battery control device 21 measures the state of the storage batteries contained in the storage battery equipment 20, calculates the charging rate and allowable current (current that can be safely passed), and communicates with the vehicle control device 13 to notify it of the state of the storage battery equipment 20.

[0022] The vehicle control device 13 communicates information with and controls each of the components included in the drive system 1A. For example, the vehicle control device 13 outputs control signals to the converter 5, the inverter 6 for the electric motor, and the inverter 10 for the auxiliary equipment based on a driving command, the state of the storage battery device 20, the state of the pantograph 2, etc.

[0023] The abnormality countermeasure system 30 communicates with the storage battery equipment 20 and the vehicle control device 13. When the storage battery equipment 20 or the vehicle control device 13 issues an abnormality flag, the abnormality countermeasure system 30 analyzes the status of the storage battery equipment 20 or the vehicle control device 13 and transmits a proposal for an abnormality countermeasure to the cab 12 or the train operation control center 40 of the railway operator outside the vehicle. The abnormality countermeasure system 30 does not necessarily have to be independent from the traction system 1A. It may be included in the train operation control device 13 or the battery control device 21. It may also be installed in a data center in a different location, receive data from the traction system 1A using a wireless device or the like, and process the information. The abnormality countermeasure system may also collect information directly without going through the train operation control device 13. For example, the abnormality countermeasure system 30 may be provided with an information transmission path between the abnormality countermeasure system 30 and the components included in the traction system 1A. The abnormality countermeasure system 30 may also be provided with sensors such as a GPS or an ammeter, and the abnormality condition may be estimated from the measurement results thereof. The abnormality countermeasure system 30 may also be provided with a means for communication with the outside of the vehicle, and collect information from various facilities outside the vehicle, such as a train operation control center.

[0024] The abnormality countermeasure system 30 of the first embodiment is used in an electric railcar equipped with a traction system using a storage battery device 20. The abnormality countermeasure system 30 is not limited to any particular type of railway vehicle, as long as it includes a storage battery device. Another example is a traction system for a hybrid diesel railcar. FIG. 2 is a diagram showing the system configuration of a traction system 1B for a hybrid diesel railcar. A hybrid diesel railcar is a railway vehicle that runs on power generated by an engine and a storage battery, without using power from an overhead line. A difference from FIG. 1 is that a solid line indicating the power transmission path is drawn between the engine 3 and the generator 4. Furthermore, dotted lines indicating the information transmission path are drawn between the engine 3 and the vehicle control device 13 and between the generator 4 and the vehicle control device 13. The engine 3 does not operate constantly, but is activated, for example, when a continuous acceleration command is input or when the storage battery's charge rate drops. The hybrid diesel railcar traction system 1B has an engine 3 and a generator 4 instead of the overhead line 14 and pantograph 2. The engine 3 outputs a shaft torque according to an engine speed command value from the vehicle control device 13. The generator 4 receives the shaft torque of the engine 3 as input, converts it into three-phase AC power, and outputs it. The converter 5 receives the three-phase AC power output from the generator 4 as input, converts it into DC power corresponding to the commanded amount of power, and outputs it. The rest of the system configuration is the same as that of the battery electric railcar traction system 1A.

[0025] In the following, in this embodiment, the case of a battery-powered train will be described, but the present disclosure can also be applied to hybrid diesel railcars, and to other electric vehicles equipped with batteries.

[0026] 3 is a block diagram showing the basic operation of an abnormality countermeasure system 30 according to the first embodiment of the present invention. The abnormality countermeasure system 30 includes a cause determination unit 31 and a countermeasure proposal unit 32.

[0027] The cause determination unit 31 monitors the status of the electric vehicle and the storage battery equipment 20, and when an abnormality flag is output from at least one of the electric vehicle and the storage battery equipment 20, it analyzes the status of at least one of the electric vehicle and the storage battery equipment 20 and identifies the cause of the abnormality indicated by the abnormality flag Af. The cause determination unit 31 generates a cause weighting table Wt based on inputs of the abnormality flag Af and battery data Db output from the battery control device 21 and the vehicle control device 13, and further based on inputs of the vehicle data Dv and weather data Dw in the first embodiment, and outputs the cause weighting table Wt to ​​the countermeasure proposal unit 32. In the following description, the abnormality flag Af, battery data Db, vehicle data Dv, and weather data Dw are used as inputs, but when a battery-related abnormality occurs, attention is mainly focused on the abnormality flag Af and battery data Db. The cause determination unit 31 monitors the status of the vehicle control device 13 and the storage battery equipment 20 using the abnormality flag Af, battery data Db, vehicle data Dv, and weather data Dw. The abnormality flag Af can also be calculated from the battery data Db.

[0028] Here, the abnormality flag Af is a flag indicating an abnormality issued by the battery control device 21 of the storage battery equipment 20 or the vehicle control device 13. This embodiment deals with abnormalities related to the battery, and assumes abnormalities such as battery over-temperature, over-voltage, and excessive charging rate detected by the battery control device 21, as well as abnormalities in communication with the storage battery equipment 20, but abnormalities related to vehicle performance detected by the vehicle control device 13 may also be included in the abnormalities targeted by the abnormality flag Af. For example, an abnormality such as low vehicle acceleration capability may be caused by low battery voltage or low battery allowable current, and may be related to a battery abnormality.

[0029] The battery data Db includes battery sensor actual measurement values ​​and calculated battery state values, which are actual measurement values ​​of battery sensors included in the storage battery equipment 20 and transmitted by the battery control device 21, as well as internal device state data. The battery sensor actual measurement values ​​include the battery temperature, which is the temperature of the battery, the battery current, which is the current value output from the battery, and the battery voltage, which is the voltage value generated by the battery. The calculated battery state values ​​include the battery charging rate, the battery's allowable current, the battery degradation level, etc. The internal device state data includes data on the operating and fault states of cooling devices, contactors, etc. included in the battery control device 21 and the storage battery equipment 20.

[0030] The vehicle data Dv includes driving status signals of the traction system 1A transmitted by the vehicle control device 13, actual sensor measurements, calculated status values, etc. The driving status signals include notch signals determined by input from the cab 12 or automatic calculation by the vehicle control device 13, brake signals, pantograph 2 raising / lowering signals, signals indicating the driving status of the accessories 11, modulation factors of the converter 5, motor inverter 6, and accessory inverter 10, etc. The actual sensor measurements include voltage values ​​and current values ​​of the converter 5, motor inverter 6, and accessory inverter 10, vehicle speed measured by a speedometer, etc., and vehicle position measured by a track circuit, etc. The calculated status values ​​include occupancy rate, etc.

[0031] The weather data Dw includes temperature, solar radiation, rainfall, wind speed, etc. These may be data measured on the vehicle by the vehicle control device 13, or data measured at a nearby location outside the vehicle may be obtained via the operation control center 40.

[0032] (Cause Weight Table) The cause weight table Wt shows the causes associated with a certain abnormality flag and their weights. The causes are subdivided into cause items, and then assigned cause categories and weights. FIG. 4 shows the cause weight table Wt when the abnormality flag indicates a battery overtemperature. The cause determination unit 31 subdivides and presents the causes of the abnormality flag Af using fault tree analysis (FTA). The columns labeled "Cause 1" through "Cause 5" correspond to the fault tree analysis of a battery overtemperature. Battery overtemperature occurs primarily due to high heat generation or difficulty in cooling, as shown in Cause 1. Furthermore, Cause 1 "high heat generation" is caused by high resistance or heavy battery load, as shown in Cause 2. By tracing the causes through this subdivision, it is possible to arrive at causes that are actually embodied in actionable events, such as battery degradation, as shown in Cause 3, or sudden acceleration / deceleration, as shown in Cause 5. The column labeled "Cause Category" indicates which category the end cause of the FTA falls into.

[0033] Here, if the abnormality is battery overtemperature, the causes can be classified into (1) unexpected events, (2) abnormal environments, (3) harsh vehicle operation methods, (4) battery degradation, (5) inappropriate control parameters, (6) control program malfunctions, and (7) hardware failures. (1) Unexpected events refer to transient events, such as vehicle stoppage due to an accident involving the vehicle itself or another vehicle, or excessive passenger capacity due to a large-scale event. (2) Abnormal environments refer to conditions such as abnormal temperatures or snow accumulation. (3) Harsh vehicle operation methods refer to harsh operating conditions imposed on the vehicle under normal circumstances, such as when there is no room in the schedule or when the normal occupancy rate and auxiliary power consumption exceed expected values. (4) Battery degradation refers to a state in which the battery is deteriorating, resulting in a decrease in capacity and an increase in resistance. (5) Inappropriate control parameters refer to a state in which the parameters used to operate the vehicle or battery are inappropriate, resulting in unsatisfactory performance or excessive load. (6) A control program malfunction refers to a state in which some function does not work due to a problem in the control program. In this case, the function will work if the program is corrected. (7) A hardware failure refers to a state in which some device has broken down and the function does not work. In this case, the function will work if the hardware is repaired or replaced.

[0034] As described above, the cause determination unit 31 classifies the cause of the abnormality flag Af into one of the following: (1) unexpected event, (2) abnormal environment, (3) harsh vehicle operating method, (4) battery deterioration, (5) inappropriate control parameters, (6) control program malfunction, and (7) hardware failure. However, the classification does not necessarily have to be one of these. The purpose of the classification is to determine the content of countermeasures. The cause of the abnormality is identified by analyzing the state of the vehicle or storage battery using the data described above. The classification of countermeasure proposals corresponding to the cause classification will be described later.

[0035] The countermeasure proposing unit 32 notifies the manager of the electric car of the cause analysis result of the abnormality flag Af and the proposed countermeasure. In other words, the countermeasure proposing unit 32 receives the cause weight table Wt output from the cause determining unit 31 as input, and outputs countermeasure information Ci to the cab 12 and the operation control center 40. The countermeasure information Ci includes the cause analysis result, the proposed countermeasure, and the effect of the countermeasure. The countermeasure information Ci is notified to the occupant of the electric car at the cab 12, and the countermeasure information is notified to the business operator that operates the electric car at the operation control center 40.

[0036] Here, the cause analysis results are the results of analyzing the abnormality indicated by the abnormality flag and serve as the basis for calculating the countermeasure proposals and countermeasure effects. The countermeasure proposals are proposed countermeasures for the cause of the abnormality flag, in other words, countermeasures for each cause in the cause weight table Wt. For example, if the cause is battery degradation, the countermeasure would be battery replacement. If the cause is sudden acceleration or deceleration, the countermeasure would be the change location and value of the acceleration setting parameter. The countermeasure effect indicates the expected effect of implementing the countermeasure proposed in the countermeasure proposal, i.e., how the parameter corresponding to the abnormality flag will change. Furthermore, if the countermeasure affects not only the indicator of the abnormality itself but also the condition of the vehicle or battery, the effect of the countermeasure is also indicated. For example, slowing down the vehicle's acceleration may affect the arrival time between stations.

[0037] (Calculation of Weights for Causes of Abnormality) There are multiple methods by which the cause determination unit 31 calculates the cause weights in the cause weight table Wt, and two of these methods are introduced in Example 1. The first method is a calculation technique based on a historical comparison with past data. FIG. 5 is an operational block diagram of the cause determination unit 31 that calculates cause weights based on a historical comparison with past data according to Example 1 of the present invention. In the first method, the cause determination unit 31 includes a related parameter extraction unit 311, a cause weight calculation unit 312, and a storage area 313. The storage area 313 records past abnormality flags, battery data, vehicle data, and weather data. Simply recording only unconverted data would result in an enormous amount of data, so it is also possible to apply statistical processing such as maximum, minimum, average, and square mean values ​​according to the properties of the data.

[0038] (First Weight Calculation Method) The related parameter extraction unit 311 has a function of extracting related parameters corresponding to an abnormality flag. The related parameter extraction unit 311 receives the abnormality flag, battery data, vehicle data, and weather data as input, and selects and outputs a target parameter Tpe and a related parameter Rpe when an abnormality occurs. Here, the target parameter is a direct monitoring parameter corresponding to the abnormality flag. The related parameter is a parameter separate from the target parameter and related to the abnormality flag. For example, if the abnormality indicated by the abnormality flag is a battery overtemperature, the target parameter would be the maximum battery temperature, and the related parameters would be current, air temperature, a signal indicating the operating status of the cooling device, and so on. The related parameters are further subdivided according to FTA as shown in FIG. 4 . For example, as parameters related to current, parameters such as a notch signal, inverter current, converter current, occupancy rate, auxiliary current consumption, air conditioner current consumption, and occupancy rate are further extracted and used as candidates for the related parameter.

[0039] The cause weight calculation unit 312 receives as input the target parameter Tpe at the time of abnormality obtained from the related parameter extraction unit 311, the related parameter Rpe at the time of abnormality, and the abnormality target parameter Tph and the abnormality-related parameter Rph, which are the past history of the target parameter and related parameters read from the storage area 313, and calculates and outputs the cause weight table Wt. The calculation method can be as follows: check the time evolution of the value of the related parameter Rph in the past history with respect to the target parameter Tph, add a weight to anything that evolves over time as a candidate cause of the abnormality, and calculate the ratio of the value of the related parameter at the time of the abnormality to the value of the related parameter in a state before the past abnormality occurred, and use the larger ratio as the weight.

[0040] The cause determination unit 31 checks the history of parameters related to the abnormality flag and assigns weights to parameters with large changes in the history. This will be described with reference to FIG. 6 . FIG. 6 is a diagram illustrating the calculations performed by the cause weight calculation unit 312 included in the cause determination unit 31. "Date" is the date on which the parameters were extracted. "Maximum cell temperature" is the maximum temperature of the battery cell in the battery system. "Current RMS" is the RMS (root mean square value) of the current flowing through the battery cell, "Operating hours" is the train's operating hours, and "Maximum temperature" is the temperature during the operating hours. Here, parameters are acquired for each date. When the abnormality is a battery overtemperature, the target parameter Tp is "Maximum cell temperature," and the related parameters Rp are "Current RMS," "Operating hours," and "Maximum temperature." An example is shown in which a battery overtemperature occurred on August 15, 2022. The target parameter Tpe during the abnormality was "Maximum cell temperature" of 55°C, and the related parameters Rpe were "Current RMS" of 70, "Operating hours" of 15 hours, and "Maximum temperature" of 38°C. Also, the relevant parameters Rph of the past history for the dates 22 / 08 / 13 and 22 / 08 / 14 are shown.

[0041] The cause determination unit checks the history of parameters related to the abnormality flag and determines the weight as the ratio between the past parameter value and the latest parameter value in the history. The time evolution of the past history values ​​of the related parameters is then checked. The time evolution of the "current RMS" is 51 (August 13, 2010), 50 (August 14, 2010), and 70 (August 15, 2010). The time evolution of the "operation time" is 15 hours (August 13, 2010), 15 hours (August 14, 2010), and 15 hours (August 15, 2010). The "operation time" is a common value. The time evolution of the "maximum temperature" is 35°C (August 13, 2010), 36°C (August 14, 2010), and 38°C (August 15, 2010). Considering the time evolution from the past history to the time of the abnormality, the current RMS has the largest change and is considered the first candidate for the cause of the abnormality. The maximum temperature has the next largest change and is the second candidate. Since there is no change in the operating time, it is excluded from the list of possible causes of the anomaly. Furthermore, the ratio of the relevant parameter values ​​at the time of the anomaly to the relevant parameter values ​​before the anomaly occurred is: current RMS: operating time: maximum temperature = 70 / 50 = 1.4, 15h / 15h = 1, and 38 / 36 = 1.05. The change in the anomaly based on the past history is: current RMS: operating time: maximum temperature = 0.4:0:0.05 = 0.8:0:0.2. This is used as the weight for the candidate anomaly cause. The maximum temperature may be the reciprocal of the temperature difference from the anomaly alarm temperature of 55°C, for example. In this case, (1 / (55-38)) / (1 / (55-36)) = 1.12. The change in the anomaly based on the past history is: current RMS: operating time: maximum temperature = 0.4:0:0.12 = 0.77:0:0.23 (weights with the sum of 1). In this way, the weights of the candidates for the cause of the anomaly may be determined.

[0042] (Second Weight Calculation Method) A second method uses a reproduction model (digital twin) of the battery or vehicle. Fig. 7 is an operational block diagram of the cause determination unit 31 when the digital twin according to the first embodiment of the present invention is applied. The cause determination unit 31 has a model verification unit 314, a sensitivity calculation unit 315, and a cause weight calculation unit 312. The cause determination unit 31 has a digital twin of the vehicle and a digital twin of the battery as models.

[0043] As described below, the model verification unit 314 and the sensitivity calculation unit 315 have a digital twin and perform processing using calculated values ​​that are the output of the digital twin. To identify the cause of an abnormality using a digital twin, it is first necessary to confirm whether the digital twin reproduces actual measured values. Therefore, the model verification unit 314 has a function of calculating whether the calculated state values ​​match the actual measured state values ​​when recalculating the state values ​​(calculated values) of the battery and vehicle reproduced by the digital twin. In other words, the model verification unit 314 inputs the abnormality flag Af, battery data Db, vehicle data Dv, and weather data Dw to calculate state values ​​using the digital twin, compares them with the actual measured state values, and outputs a comparison result Cr. If the comparison result Cr confirms that the accuracy of the digital twin is acceptable, the sensitivity for each parameter calculated by the sensitivity calculation unit 315 can be used as a weight. On the other hand, if there is a problem with the accuracy of the digital twin, the cause of the abnormality is identified and weighted from the discrepancies between the calculated and actual measured values ​​of the digital twin.

[0044] More specifically, the model verification unit 314 has a digital twin of the battery and vehicle and recalculates the target parameters and related parameters of the abnormality flag. The comparison result Cr is calculated for multiple target parameters and related parameters of the abnormality flag, comparing at least the target parameters and the parameters used in the calculation to see whether their actual measured values ​​match the calculated values. This process reveals whether a parameter is functioning according to the model, which is useful, for example, when detecting equipment failure. For example, battery temperature can basically be calculated from air temperature, current value, battery degradation level, and cooling device operating status signals. If the actual measured value of battery temperature is higher than the calculated value, a discrepancy occurs between the digital twin and the actual system. This basically occurs for three reasons: sensor abnormality, battery state calculation error, and equipment failure. Sensor abnormality refers to the presence of noise in the measured temperature or current values, which leads to inaccurate values. Battery state calculation error refers to the inaccuracy of parameters that cannot be directly detected by sensors, such as the charge rate or degradation level, but are calculated indirectly through calculation. Equipment failure refers to the absence of problems with the operation signal and response signal, but a problem with actual operation. In an actual storage battery equipment 20, if the measured and calculated temperature values ​​differ, it is rare for there to be an anomaly in the temperature sensor or current sensor, so investigation can proceed, suspecting a calculation error in the battery degradation level and a malfunction in the cooling device. Additionally, the three causes mentioned above can also be distinguished from the behavior of each value. For example, if the temperature sensor or current sensor repeatedly alternates between the minimum program value calculated by the model and a realistic value, poor contact can be suspected. Details of the functional blocks, etc., will be described later. In this way, when the calculation results of the digital twin and the measured values ​​disagree, the cause determination unit determines whether the cause is a sensor anomaly, a battery state calculation error, or a device malfunction. For example, if the measured temperature value is higher than the calculated temperature value of the battery digital twin 3143, the cause determination unit 31 determines that the fan is malfunctioning.

[0045] The sensitivity calculation unit 315 has a function of calculating the strength of the effect (sensitivity) that a change in each related parameter has on the target parameter of the abnormality flag. The sensitivity calculation unit 315 receives the abnormality flag Af, battery data Db, vehicle data Dv, and weather data Dw as input, and outputs a sensitivity map Sm of the related parameters. Using the digital twin, the target parameter is calculated while changing the related parameters, and the sensitivity can be calculated by taking the ratio of the amount of change in the related parameter to the amount of change in the target parameter.

[0046] The cause weight calculation unit 312 has a function of calculating cause weights and outputting a cause weight table Wt. The comparison result Cr and the sensitivity map Sm of the related parameters are input to calculate the cause weights. If the comparison result Cr indicates that the actual measured value and the calculated value do not match, and if a sensor error, a battery state calculation error, or a device malfunction is suspected, weighting is focused on the device malfunction or a problem with the state calculation program. If the comparison result Cr indicates that the actual measured value and the calculated value match, weights are determined from the sensitivity map Sm of the related parameters.

[0047] 8 is an operational block diagram of the model verification unit 314 according to the first embodiment of the present invention. The model verification unit 314 includes a vehicle digital twin 3142, a battery digital twin 3143, and a determination unit 3141.

[0048] The vehicle digital twin 3142 has a function of recalculating vehicle data, which is state values ​​calculated from a vehicle model, based on actual measurement data, which is actually measured state values ​​of the vehicle, and receives the abnormality flag Af, battery data Db, vehicle data Dv, and weather data Dw as input, and outputs the abnormality flag Afc1, which is a calculated value, and the vehicle data Dvc, which is also a calculated value. For example, the digital twin recalculates the inverter current, converter current, power consumption, fuel consumption, etc. from the vehicle speed, notch information, and brake signal.

[0049] The battery digital twin 3143 has a function of recalculating battery data, which is a state value calculated from a battery model, based on actual measurement data, which is an actually measured battery state value, and inputs an abnormality flag Af, battery data Db, vehicle data Dv, and weather data, and outputs an abnormality flag Afc2, which is a calculated value, and battery data Dbc, which is also a calculated value. For example, the battery temperature is calculated from a signal indicating the battery current, air temperature, degree of deterioration, and the operating status of the cooling device. The battery data Dbc may also include the rate of deterioration of the battery for the input usage conditions.

[0050] In the vehicle digital twin 3142 and the battery digital twin 3143, since recalculating all parameters would result in an enormous amount of calculation, they may be configured to have a calculation target designation unit 31431 that limits the calculation location in response to an abnormality flag, as described below.

[0051] The determination unit 3141 has the function of determining whether the actual measurement value matches the calculated value. It receives the abnormality flag AFc, vehicle data Dvc, and battery data Dbc as inputs and outputs a comparison result Cr. The agreement between the actual measurement and the calculation is determined, for example, by determining whether the actual measurement falls outside a predetermined accuracy range for each calculation method. The accuracy can be set by comparing the calculated value of the digital twin with the actual measurement value when all devices are operating normally. Note that the abnormality flag Afc1 output from the vehicle digital twin 3142 and the abnormality flag Afc2 output from the battery digital twin 3143 do not necessarily need to be the same. Since Example 1 describes a case in which an abnormality has occurred in the battery, the determination unit 3141 can make a determination based on the abnormality flag AFc2 output from the battery digital twin 3143, but the present disclosure is not limited to this. The determination unit 3141 may also determine whether an abnormality exists in the entire vehicle based on both abnormality flags.

[0052] (Sensitivity Calculation Method) FIG. 9 is an operational block diagram of the sensitivity calculation unit 315 according to the first embodiment of the present invention. The cause determination unit 31 calculates the sensitivity of the abnormality flag Af to the target parameter by minutely changing the parameters related to the abnormality flag Af, and calculates the weight of the cause of the abnormality flag Af. This will be described with reference to FIG. 9 . The sensitivity calculation unit 315 includes a minute change generation unit 3152, a vehicle digital twin 3142, a battery digital twin 3143, and a sensitivity map generation unit 3151. Note that the vehicle digital twin 3142 and the battery digital twin 3143 are the same as those provided in the model verification unit 314, but also have the functions of the sensitivity calculation unit 315, as described below. Furthermore, the abnormality countermeasure system 30 may include one vehicle digital twin 3142 and one battery digital twin 3143, each of which may be configured as a common component for the model verification unit 314 and the sensitivity calculation unit 315, or each of which may be provided as a separate component for the model verification unit 314 and the sensitivity calculation unit 315.

[0053] The minute change generation unit 3152 has a function of calculating minute change data to be input to the vehicle digital twin 3142 and the battery digital twin 3143, and outputs minute change battery data ΔDb, minute change vehicle data ΔDv, and minute change weather data ΔDw, which are data that have been minutely changed using the abnormality flag Af, battery data Db, vehicle data Dv, and weather data Dw as input. There are usually countless ways to determine the parameters to be minutely changed and the amount of minute change, and for example, the calculation load can be reduced if the parameters to be changed and the amount of change and ratio are determined in advance in accordance with the abnormality flag Af.

[0054] The vehicle digital twin 3142 has a function of recalculating vehicle data based on minute change data, and receives as input the abnormality flag Af, minute change battery data ΔDb, minute change vehicle data ΔDv, and minute change weather data ΔDw, and outputs the target parameter Tpc1 and minute change battery data ΔDbc, which are calculated values ​​corresponding to the input data. The minute change battery data ΔDbc output here is minute change battery data that has changed due to the influence of the minute change vehicle data ΔDv and the minute change weather data ΔDw. For example, if the vehicle notch changes, this will have an impact on the battery current, and therefore the minute change battery data will also change.

[0055] The battery digital twin 3143 has the function of recalculating battery data based on minute change data, and takes as input the abnormality flag Afc, minute change battery data ΔDb, minute change vehicle data ΔDv, and minute change weather data ΔDw, and outputs the target parameter Tpc2, which is a calculated value corresponding to the input data.

[0056] The sensitivity map generator 3151 has a function of calculating the sensitivity of related parameters to target parameters from the digital twin calculation results, and receives the abnormality flag Afc, the slight change battery data ΔDb, the slight change vehicle data ΔDv, the slight change weather data ΔDw, and the target parameters Tpc1 and Tpc2 as inputs, and outputs a sensitivity map Sm of the related parameters. For example, the sensitivity map Sm of the related parameters may be calculated when, for a certain abnormality flag, the target parameter i changes ΔXi in response to a slight change ΔXk in the related parameter k. The sensitivity map Sm may be calculated as sensitivity = ΔXi / ΔXk.

[0057] (Configuration of Battery Digital Twin) Figure 10 is a diagram showing an example of an operational block diagram of a battery digital twin 3143 according to Example 1 of the present invention. The battery digital twin 3143 has a calculation target designation unit 31431, a temperature model 31432, a closed circuit voltage model 31433, a charging rate model 31434, and a deterioration model 31435. The battery digital twin that calculates the storage battery equipment 20 includes the temperature model 31432, the closed circuit voltage model 31433, the charging rate model 31434, and the deterioration model 31435. In other words, the battery digital twin 3143 can also calculate the battery temperature, closed circuit voltage, and charging rate.

[0058] The calculation target designation unit 31431 is a switch that limits the calculation location in accordance with the abnormality flag in order to reduce the calculation load, and inputs the abnormality flag Af to select the model to be calculated. For example, if an over-temperature abnormality occurs, the temperature model 31432 and the deterioration degree model 31435 are enabled. If there is room for the calculation load, the closed circuit voltage model 31433 and the charging rate model 31434 may also be enabled.

[0059] The temperature model 31432 has a function of calculating the battery temperature, and receives the battery data Db, the vehicle data Dv, and the weather data Dw as inputs, and outputs the battery temperature Bt. The battery temperature Bt can be calculated, for example, by calculating the heat generation amount from the current value and using a thermal network model of the storage battery equipment 20.

[0060] The closed circuit voltage model 31433 has a function of calculating the closed circuit voltage of the battery, and receives battery data, vehicle data, and weather data as inputs, and outputs the closed circuit voltage Cv. A method of calculating the closed circuit voltage Cv from the state of charge, battery temperature, current value, and battery resistance is well known, and this method can be appropriately adopted in this embodiment.

[0061] The charging rate model 31434 has a function of calculating the charging rate of the battery, and receives battery data, vehicle data, and weather data as inputs, and outputs the charging rate Sc. A method of calculating the charging rate Sc from the battery voltage and current values ​​is well known, and this method can be appropriately adopted in this embodiment.

[0062] The deterioration level model 31435 has a function to calculate the battery deterioration level Dd, and inputs battery data, vehicle data, and weather data to output the deterioration level. Battery deterioration is known to cause both a decrease in capacity and an increase in resistance, and this model targets both of these phenomena. Well-known methods for calculating the deterioration level Dd from voltage, current, charging rate, temperature, etc. can be used as appropriate in this embodiment.

[0063] For all of these models, representative values ​​such as average, maximum, and minimum values ​​may be calculated for all battery cells in the storage battery equipment 20, or if the calculation load is tolerable, calculations may be performed individually for all battery cells in the storage battery equipment 20. If individual calculations can be performed, more detailed analysis of the location and cause of the abnormality flag Af can be performed.

[0064] Because the battery digital twin 3143 is a model that reproduces the state of the storage battery equipment 20, in this embodiment it is not limited to a configuration that includes the above-mentioned four models, and it is also possible to configure it to include other models. For example, it is possible to include a calculation model for the auxiliary power consumption of the storage battery equipment 20, a calculation load calculation model for the battery control device 21, a stress calculation model for the housing of the storage battery equipment 20, etc.

[0065] As described above, there are many possible models for indicating the state of the storage battery equipment 20, but the most typical abnormalities are over-temperature, over-voltage, and excessive charging rate. These are detected by the battery temperature, closed circuit voltage, and charging rate, so it is sufficient to calculate at least these three.

[0066] An overtemperature occurs when the battery temperature becomes too high or too low to be within the operating range of the storage battery equipment 20. A high temperature is basically caused by high temperatures and high battery loads, and a low temperature is caused by low temperatures.

[0067] Overvoltage occurs when the closed circuit voltage of the battery becomes too high or too low to be within the specifications of the storage battery equipment 20. The closed circuit voltage refers to the voltage between the positive and negative terminals of the battery when current is flowing. High voltages occur when the battery is charging, and low voltages occur when the battery is discharging.

[0068] An overcharge occurs when the battery charge rate becomes too high or too low to be within the operating range of the battery storage device 20. The charge rate has a one-to-one correspondence with the battery voltage when there is no current (open circuit voltage). An overcharge to a low charge rate corresponds to an energy shortage, and is called a power shortage. If this occurs in a battery-powered train, the train will be unable to run. Note that an overcharge to a high charge rate requires charging beyond the upper limit of the specifications, so this generally does not occur unless there is a control error.

[0069] Note that the vehicle digital twin 3142 also includes a calculation model for calculating important vehicle parameters, similar to the battery digital twin 3143. The vehicle digital twin may be, for example, an appropriately selected model that calculates inverter current from notch and speed information.

[0070] (Example of Sensitivity Map) FIG. 11 shows an example of the sensitivity map Sm when the abnormality flag indicates a battery overtemperature. FIG. 11( a) is a sensitivity map showing the sensitivity of related parameters to the target parameter, the maximum cell temperature. The related parameters include the battery current RMS, maximum temperature, and driving time, with sensitivities of 0.7, 0.2, and 0.1, respectively. FIG. 11( b) is a sensitivity map of the related parameter, the current RMS. The related parameters include the quick charge current, the air conditioner operation time, the vehicle acceleration performance, and the vehicle braking amount, with sensitivities of 0.1, 0.3, 0.5, and 0.1, respectively. FIG. 11( c) is a sensitivity map of the related parameter, the air conditioner operation. The related parameters include the set temperature and maximum temperature, with sensitivities of 0.6 and 0.4, respectively. Note that the sensitivities are shown in normalized form here, but are not limited to this.

[0071] When referring to the sensitivity map of the target parameter, the maximum cell temperature, the most sensitive related parameter is the RMS current, as shown in FIG. 11(a). Next, when referring to the sensitivity map of the RMS current, the most sensitive related parameter is the air conditioner operation time, as shown in FIG. 11(b). Next, when referring to the sensitivity map of the air conditioner operation, the most sensitive related parameter is the set temperature, as shown in FIG. 11(c). In this way, by tracing the highly sensitive parameters in a tree diagram, it is possible to identify parameters for which countermeasures can be taken.

[0072] 12 is an operational block diagram of the countermeasure proposal unit 32 according to the first embodiment of the present invention. The countermeasure proposal unit 32 includes a changeable range calculation unit 321, a countermeasure effect calculation unit 322, and a proposal determination unit 323.

[0073] The countermeasure proposal unit 32 sets a changeable range for parameters related to the abnormality flag Af, and sets the proposed change value for the parameter within the changeable range. More specifically, the changeable range calculation unit 321 has a function of calculating the range of change possible when changing the control method of the battery or vehicle as a countermeasure. The changeable range calculation unit 321 inputs the cause weight table Wt and past data Pd (described later) and outputs the changeable range Vr for the parameter. Even if the cause weight table Wt indicates that changing the control parameters of the storage battery equipment 20 is a viable option, there is a limit to the changeable range. The changeable range calculation unit 321 specifies the changeable range for the related parameters for which weights are set using the cause weight table Wt. There are two reasons for specifying the changeable range: the first is that each related parameter has its own changeable range limit; and the second is that changing the related parameters may cause different malfunctions or deviations from specifications.

[0074] Regarding the first designation basis, each related parameter has a set range of change. If the related parameter is related to the occurrence of an accident or is weather data Dw, the related parameter itself corresponding to the cause cannot be changed because accidents and abnormal weather cannot be manipulated. There are limits to the adjustment range for diagrams and occupancy rates that are agreed upon in advance with the railway operator. In the case of battery deterioration, the improvement value of the battery deterioration level is limited depending on whether a replacement battery is available or if the replacement is second-hand.

[0075] The second designation basis is that all related parameter changes should be verified. The countermeasure proposal unit 32 sets the changeable range based on whether the deterioration of target parameters for abnormality flags other than the abnormality flag that occurred is within a threshold. Furthermore, the countermeasure proposal unit 32 recalculates the abnormality flags from vehicle and battery data. Specifically, the countermeasure proposal unit 32 typically inputs the vector of related parameters to be verified into the vehicle digital twin and battery digital twin, and then recalculates the target parameters corresponding to all abnormality flags. For example, reducing the battery current value is an effective countermeasure for battery overtemperature and overvoltage, but this may result in a decrease in vehicle performance and failure to maintain the schedule. Similarly, increasing the battery charging rate may be an effective countermeasure for low battery, but this may result in battery overtemperature. Because the conditions for other malfunctions vary depending on the operating environment, it is necessary to verify the historical data Pd. Here, the historical data Pd is data recording past malfunctions and the battery and vehicle status values ​​at the time the malfunctions occurred. Furthermore, the changeable range calculation unit 321 specifies the changeable range of the related parameters based on the designation basis, taking into consideration the past data stored in the storage area 313. Note that the storage area 313 is configured to be shared with the cause determination unit 31, but is not limited to this. Separate storage areas may be provided for the cause determination unit 31 and the countermeasure proposal unit 32.

[0076] The range in which the related parameters can be changed is a range that is a combination of the ranges in which the related parameters can be changed based on the above two designation grounds.

[0077] (Anomaly Countermeasure System - Countermeasure Effect Calculation Unit) Generally, it is effective to simultaneously change the weight of an abnormality countermeasure by changing multiple control items, so the changeable range Vr of the related parameters is in the form of a multi-dimensional map in which multiple related parameters are changed simultaneously.

[0078] The countermeasure effect calculation unit 322 has a function of calculating the value of the target parameter and the value of the target parameter for another abnormality when the related parameter is adjusted within the changeable range Vr of the related parameter. It inputs the cause weight table Wt, the changeable range Vr of the related parameter, and past data Pd, and outputs a countermeasure effect map Cm. The countermeasure effect map Cm contains vectors of multiple related parameters, the value of the target parameter at that time, and the value of the other target parameter. The other target parameter refers to a target parameter other than the target parameter of the abnormality flag. For example, if the abnormality flag indicates overtemperature and the countermeasure is to change the current, this means that the target parameter for another abnormality, such as the charging rate or diagram compliance, is calculated. Note that the past data Pd used by the countermeasure effect calculation unit 322 is, for example, stored in association with changes that occur in the target parameter when a countermeasure for the related parameter is taken. The change may be a statistically indicated value or a theoretical value.

[0079] The proposal determination unit 323 has a function of determining the contents to be proposed to the cab 12 and the operation control center 40, and receives the cause weighting table Wt and the countermeasure effect map Cm as inputs, and outputs countermeasure information Ci including the cause analysis results, countermeasure proposals, and countermeasure effects. The countermeasure proposals are selected from the points with large weights in the cause weighting table Wt. In addition to the fact that the causes of a certain abnormality flag are subdivided as shown in FIG. 4 and weights indicating the degree of influence are assigned to each cause, there are generally multiple effective countermeasures for one cause, as shown in FIG. 12 (described later). As a result, the contents presented by the cause determination unit 31 may include multiple causes and countermeasures.

[0080] The results of parameter changes after the countermeasure, such as changes to continuous parameters, are proposed in the countermeasure effect map Cm under the condition that they affect the target parameters of the abnormality flag and that the deterioration ranges of target parameters of other abnormalities fall within acceptable ranges. The proposal determination unit 323 may input not only performance constraints of the vehicle and battery, but also commercial constraints such as the number of replaceable parts and maintenance plans, and reflect them in the proposal content. Information regarding the number and constraints may be stored, for example, in the storage area 313 and extracted by the proposal determination unit 323 as needed. The countermeasure effect is notified as the improvement effect of the target parameters under the above conditions and the deterioration effect of normal target parameters of other abnormalities. The cause-effect analysis is proposed as the output of the cause weight table Wt.

[0081] (Case Classification of Causes and Countermeasures) FIG. 13 is a diagram showing an effective countermeasure table that associates countermeasures with cause classifications according to the first embodiment of the present invention. Just as there are multiple causes for a certain abnormality flag as shown in FIG. 4, the number of effective countermeasures for a certain subdivided cause is not limited to one. The effective countermeasure table of FIG. 13 generally organizes effective countermeasures for cause classifications. There are seven types of cause classifications, while there are five types of effective countermeasure classifications. Note that this table shows an example, and the combinations are not necessarily limited to this.

[0082] The first category of countermeasures is (A) changing the vehicle operation method and / or control parameters under special conditions. Countermeasures in category (A) are techniques for changing the vehicle operation method and / or control parameters only under the same special conditions as when the abnormality flag is raised. Countermeasures in category (A) are effective for cause categories (1) unexpected events and (2) abnormal environments. In other words, the countermeasure proposal unit 32 proposes changes to the vehicle operation method and / or control parameters under special conditions when the cause is classified as either (1) unexpected events or (2) abnormal environments. This is because unexpected events such as accidents and abnormal environments are extreme conditions and rarely occur. Under such conditions, requirements differ from those during normal operation. For example, the requirement may be to safely reach the nearest major station, and acceleration performance much slower than normal is acceptable. Specific countermeasures include, for example, adopting a special schedule specialized for reaching the nearest major station, a special power usage method that supplies power only to equipment necessary for reaching the nearest major station, and control parameters suitable for these special schedules and power usage methods. The control parameters are not limited to parameters for controlling the vehicle control device 13 and the battery control device 21, but also include manually operated parameters such as vehicle acceleration. Changing the vehicle operation method and control parameters under special conditions will be performed only under special conditions, since applying such changes during normal operation would significantly restrict normal operation.

[0083] The second category of countermeasures is (B) changes to vehicle operation methods. Countermeasures in category (B) are proposed not only when an abnormality flag is raised but also during normal operation. Vehicle operation methods, in other words, are the services provided by a certain vehicle determined by the operator. Countermeasures in category (B) are effective in the cause categories of (2) abnormal environments, (3) severe vehicle operation methods, and (4) battery degradation. Specific countermeasures include, for example, relaxing the schedule, occupancy rates, and auxiliary power consumption. Relaxing the schedule means reducing the daily mileage, increasing the stop time at charging stations, and averaging the load between trains. The fact that countermeasures are effective not only for cause category (3) but also for cause categories (2) and (4) can be explained as follows: For cause category (2), if a schedule that is valid even in abnormal environments is established in advance, schedule confusion will not occur when an abnormal environment occurs. Furthermore, by changing the schedule to take into account an abnormal environment once it has occurred, schedule confusion can be eliminated or minimized even in the same abnormal environment. Regarding cause category (4), even if the malfunction is caused by battery degradation, the vehicle can be operated by relaxing the diagram, and it is possible to continue operating the vehicle while postponing expensive battery replacement.

[0084] The third category of countermeasures is (C) control parameter change. Countermeasures in category (C) are proposed not only when an abnormality flag is generated but also during normal operation. Control parameters are not limited to parameters for controlling the vehicle control device 13 and the battery control device 21, but also include manually operated parameters such as vehicle acceleration. Unlike the relaxation of vehicle operation methods in category (B), changing control parameters does not require a change to the vehicle operation method, in other words, the vehicle services determined by the operator. Countermeasures in category (C) propose changing control parameters while maintaining the vehicle operation method. Because countermeasures in category (C) can improve the situation for various causes without changing the vehicle operation method, they are effective for cause categories other than cause category (7) hardware failure. Examples of steady-state control parameters include vehicle acceleration, charging speed, target charging rate, and cooling device operation command. Furthermore, for cause categories (1) and (3), control parameters can be set in advance to deal with sudden self-proclaimed events or abnormal environments, or control parameters that take into account sudden events or abnormal environments that have occurred once. More specifically, the control parameters may be set to increase the normal charging rate to avoid running out of power, or to reduce the charging rate to avoid abnormally high temperatures.

[0085] The fourth category of countermeasures is (D) repair of faulty software and equipment. Countermeasures in category (D) involve repairing faulty software that is inoperable due to a bug or faulty hardware. For example, faulty software may cause software malfunctions in the battery cooling device control or the operation of control software for protecting the battery, resulting in the intended operation being inoperable. Hardware malfunctions may also occur in the battery cooling device, contactors, auxiliary power supplies, various control boards, connectors, various sensors, and the like. This countermeasure is prioritized because the malfunctions cause an abnormality that prevents the equipment from performing as designed, and the repair itself does not degrade vehicle performance or require restrictions on vehicle operation. Countermeasures in category (D) are effective for cause categories (6) control program malfunctions and (7) hardware failures. In other words, if the cause is classified as either (6) control program malfunctions or (7) hardware failures, the countermeasure proposal unit 32 prioritizes addressing the cause. The defective device may be replaced with a new one or a spare part, and then repaired.

[0086] The fifth category of measures is (E) battery replacement. Category (E) measures involve replacing batteries on vehicles that have deteriorated significantly with batteries that have deteriorated less. Because battery replacement is costly, if other measures that do not require changes to vehicle operation methods are available, those other measures are given priority.

[0087] As described above, the proposed measures include any of the following: changing the vehicle operation method and / or control parameters under special conditions, changing the vehicle operation method on a regular basis, changing the control parameters on a regular basis, repairing faulty software and devices, and replacing a deteriorated storage battery. In other words, the measure proposing unit 32 proposes multiple measures for each individual cause of the abnormality flag Af.

[0088] (Countermeasure Effect Map) FIG. 14 is a diagram showing an example of the countermeasure effect map Cm. Here, the countermeasure effect map Cm is schematically shown when two related parameters are extracted for the target parameter of battery overtemperature. For the target parameter of battery overtemperature, "measure A is taken" and "measure A is not taken" indicate whether a countermeasure related to a certain related parameter is taken or not taken. Furthermore, "measure B" and "measure B is not taken" indicate whether a countermeasure related to another related parameter is taken or not taken. The countermeasure effect is shown to be a 10°C decrease in battery temperature when "measure A is taken" and "measure B is not taken." Furthermore, the countermeasure effect is shown to be a 5°C decrease in battery temperature when "measure A is not taken" and "measure B is taken." In the countermeasure effect calculation unit 322, countermeasures a and b are set based on the changeable range Vr of the related parameters, and the countermeasure effect is calculated based on past data Pd.

[0089] (Countermeasure Information) Figure 15 is a diagram showing an example of displaying countermeasure information Ci. This is information output from the abnormality countermeasure system 30, and is displayed on the display unit of the cab 12 or notified to the operation control center 40. In the display, the information is divided into the items of "priority," "countermeasure," and "effect." The item "priority" indicates the order of recommended implementation. For example, the priority is indicated from the one with the greatest effect on the abnormality based on the countermeasure effect map Cm. The item "countermeasure" indicates the content to be carried out by the crew operating the cab 12 and the railway operator managing the operation control center 40. The item "effect" indicates the effect expected to be produced by the countermeasure.

[0090] For example, for priority 1, the countermeasure displayed is "Change the current rapid charge current from X [A] to Y [A]." Here, the countermeasure is to change the current value of the rapid charge current. Furthermore, while the countermeasure information Ci includes the results of cause analysis, countermeasure proposals, and countermeasure effects, priority 1 also displays that the rapid charge current is the cause.

[0091] Furthermore, the effect of the measure with priority 1 is displayed as "This will reduce the maximum battery temperature from X1°C to Y1°C under the temperature conditions today, August 15th." As the temperature drop is specifically shown, the quantitative effect of the proposed measure is notified. This is also true for the measures with priority 2 and 3.

[0092] Furthermore, for priority level 2, the countermeasure is displayed as "Please increase the stop time by 30 seconds in the timetable." This also includes proposals to relax vehicle operation methods. For priority level 3, the countermeasure is displayed as "Please replace the battery with a new one." This allows crew members and railway operators to understand that the cause of the abnormality, such as battery overheating, is the battery.

[0093] (Operations and Effects) As described above, in this embodiment, when an abnormality occurs in the vehicle's storage battery equipment 20, the crew and the railway operator can identify not only the location of the abnormality but also the cause of the abnormality without requiring a knowledgeable engineer to carefully examine the data, and can obtain countermeasures to address the cause, including changes to the operation method. In this way, according to the present invention, when an abnormality occurs in the storage battery system of an electric vehicle, it is possible to identify not only the location of the abnormality but also the cause of the abnormality, and obtain countermeasures, including changes to the operation method.

[0094] [Example 2] In Example 1, the abnormality flags were treated as correct. However, during actual operation, the vehicle control device 13 and the battery control device 21 may miscalculate the abnormality flags. Furthermore, if multiple abnormalities occur simultaneously, the abnormality flags do not represent all of the events, and only the abnormality flag corresponding to the first event or the event with the highest severity is output, which may result in some abnormal events not being recognized.

[0095] Therefore, in the second embodiment, a true / false determination of the abnormality flag is performed. The abnormality countermeasure system 30a of the second embodiment differs from the abnormality countermeasure system 30 of the first embodiment in that a true / false determination is performed before the abnormality flag is input to the cause determination unit 31. FIG. 16 is an operational block diagram of the abnormality countermeasure system 30a having the true / false determination unit 33 according to the second embodiment of the present invention. The second embodiment has the same structure and operates in the same manner as the first embodiment except for the portions of the abnormality countermeasure system 30a specifically noted. In the following description, the same or equivalent components as those of the first embodiment are designated by the same reference numerals, and their description will be simplified or omitted.

[0096] In Example 2, the abnormality flag Af, battery data Db, vehicle data Dv, and weather data Dw are stored in the storage area 313, and correlation information between the abnormality flag Af and each of the battery data Db, vehicle data Dv, and weather data Dw is also stored.

[0097] The truth / error determination unit 33 continuously acquires the abnormality flag Af, battery data Db, vehicle data Dv, and weather data Dw in a predetermined cycle. At this time, the truth / error determination unit 33 determines whether any of the battery data Db, vehicle data Dv, and weather data Dw has changed beyond a predetermined range, and detects whether the abnormality indicated by the abnormality flag Af has not changed even when a change has occurred. At this time, the truth / error determination unit 33 determines that the abnormality flag Af is incorrect and outputs truth / error determination information Ji for the abnormality flag.

[0098] Furthermore, the true / false determination unit 33 extracts an abnormality flag corresponding to each of the three pieces of data, the battery data Db, the vehicle data Dv, and the weather data Dw, when it determines, based on the correlation information in the storage area 313, that any one of the battery data Db, the vehicle data Dv, and the weather data Dw has changed beyond a predetermined range. If the abnormality flags extracted from the correlation information for each of the three pieces of data are common, the true / false determination unit 33 outputs a detailed abnormality flag sAf. The cause determination unit 31 calculates a cause weight table Wt based on the detailed abnormality flag sAf.

[0099] If the abnormality flags extracted from the correlation information of each of the three data are not common, the true / false determination unit 33 does not output the detailed abnormality flag sAf. When the cause determination unit 31 receives the true / false determination information Ji, it does not generate the cause weight table Wt. The cause determination unit 31 generates the cause weight table Wt based on the detailed abnormality flag sAf, battery data Db, vehicle data Dv, and weather data Dw sent in the next cycle.

[0100] (Operations and Effects) With the configuration shown in the second embodiment, errors in the abnormality flags are corrected, and countermeasures can be proposed for all correct abnormality flags.

[0101] [Example 3] In Example 1, the proposed countermeasures are sent to the train operation control center 40 of the railway operator, and the vehicle operation method and control program are manually switched. Meanwhile, the abnormality countermeasure system 30 is in communication with the vehicle control device 13 and the battery control device 21. Therefore, in Example 3, the abnormality countermeasure system 30b changes the control constants of the electric vehicle and the battery control device 21 corresponding to the proposed countermeasures.

[0102] 17 is an operational block diagram of an abnormality countermeasure system 30b having a control constant changing unit 34 according to a third embodiment of the present invention. The abnormality countermeasure system 30b according to the third embodiment has the same structure and operates in the same manner as the first embodiment except where specifically noted. In the following description, components that are the same as or equivalent to those in the first embodiment described above are designated by the same reference numerals, and their description will be simplified or omitted.

[0103] The control constant change unit 34 outputs a change signal Cs, which is a signal that instructs changing the control constants of the vehicle control unit 13 and the battery control unit 21. The control constant change unit 34 receives as input information related to the proposed countermeasures from the countermeasure information Ci and a change permission command Ps, and outputs the change signal Cs. The change signal Cs is a signal that changes the control constants of the vehicle control unit 13 and the battery control unit 21 in accordance with the contents of the proposed countermeasures.

[0104] Here, the modified signal Cs is usually a signal specific to each control device based on the specifications of the control device, and it is difficult for operators to use the modified signal independently without the cooperation of the manufacturer, and the modification requires time and effort to directly access the equipment on the vehicle. Not all proposed countermeasures for signal hardware failures can be addressed by changing the control constants; only items managed by constants can be modified.

[0105] The change permission command Ps is a command that permits the control constant changing unit 34 to change the control constants in accordance with the proposed countermeasures. The change permission command Ps may be output after confirmation by a person in charge at the train operation control center 40 of the railway operator, or may be output automatically when a countermeasure proposal in the countermeasure information Ci is input from the abnormality countermeasure system 30b.

[0106] (Operations and Effects) With the configuration shown in the third embodiment, the train operator's operation control center 40 can quickly and remotely implement measures to change the control constants on the vehicle control device 13 and the battery control device 21 on the vehicle.

[0107] [Example 4] In Example 1, a series of countermeasure proposals were made after an abnormality flag was raised. However, many abnormality flags are raised when a continuous quantity, such as battery temperature, exceeds a threshold, and the date of future abnormality occurrence can be predicted based on trends in past data. Diagnosing future abnormality occurrences from existing data in this way is called abnormality sign diagnosis. If abnormality sign diagnosis detects an abnormality before the flag is raised and countermeasures are implemented in advance, vehicle stoppages due to abnormalities will not occur, and vehicle maintenance for countermeasures can be planned with ample time to spare. Therefore, in Example 4, the abnormality countermeasure system 30c proposes countermeasures by raising a predictive flag that predicts the occurrence of an abnormality, rather than by raising an abnormality flag.

[0108] 18 is an operational block diagram of an abnormality countermeasure system 30c having an abnormality sign diagnosis unit 35 according to a fourth embodiment of the present invention. The fourth embodiment has the same structure and operates in the same manner as the first embodiment except for the portions of the abnormality countermeasure system 30c specifically stated. In the following description, components that are the same as or equivalent to those in the first embodiment described above are designated by the same reference numerals, and their description will be simplified or omitted.

[0109] The cause determination unit predicts the occurrence of an abnormality from the control device data and issues a predictive flag. More specifically, the abnormality predictor diagnosing unit 35 has a function for detecting abnormality predictors, and receives the battery data Db, vehicle data Dv, weather data Dq, and past data Pd read from the storage area 313 as inputs to calculate a predictive flag Sf. For example, in the case of an overtemperature abnormality, the predictive flag Sf is calculated by plotting the relationship between the daily maximum battery temperature and the maximum air temperature based on the past data Pd, predicting future values, and determining that an abnormality will occur if the threshold temperature is exceeded.

[0110] The predictive flag Si is a flag that indicates a predictive abnormality, and is triggered when, for example, the expected date and time of the abnormality occurrence is within a threshold value. The threshold value may be based on the period required to prepare countermeasures or the product usage period.

[0111] (Operations and Effects) The configuration of Example 4 enables railway operators to detect signs of abnormality through abnormality sign diagnosis before an abnormality flag is raised. By taking measures in advance, train stoppages due to abnormalities do not occur, and train maintenance for countermeasures can be planned with ample time to spare.

[0112] [Example 5] In Example 1, the abnormality countermeasure system 30 transmits the cause analysis results, countermeasure proposals, and countermeasure effects to the train operation control center 40 of the railway operator. Meanwhile, in actual operation, when an abnormality flag is raised, an emergency measure instruction is sent from the train operation control center 40 of the railway operator to the cab 12, and the emergency measure is implemented by a crew member who confirms the instruction. The emergency measure includes a decision to continue normal operation or to suspend operation and move the vehicle to a station or depot, and a decision to take life-extending measures in response to the abnormality flag. Among these, Patent Document 2 discloses an example in which, in response to an abnormality flag, a notification is sent of means to suspend operation and move the vehicle to a station or depot. Example 5 differs from Patent Document 2 in that, first, a decision on whether operation can be continued even if an abnormality flag is raised, and second, a decision on life-extending measures in response to the abnormality flag are transmitted to the cab 12.

[0113] Determining whether operation can be continued even if an abnormality flag has been raised means issuing an instruction to the cab 12 that even if an abnormality flag has been raised, the situation will not deteriorate seriously as long as the operation method for that day is continued, and operation can be continued. For example, in the case of an over-temperature, if the battery over-temperature flag is raised after the temperature has passed its peak, the temperature will drop in subsequent operations, so operation may be possible.

[0114] Furthermore, the determination of a life-extending measure corresponding to the abnormality flag means that the abnormality countermeasure system 30d instructs the cab 12 to take a measure that can be immediately implemented on a vehicle in operation from among the measures proposed by the measure proposal unit 32. For example, in the case of an overvoltage abnormality, it may be possible to continue using the vehicle by immediately adjusting the charging rate up or down.

[0115] 19 is an operational block diagram of an anomaly countermeasure system 30d having an emergency measure proposal unit 36 ​​according to a fifth embodiment of the present invention. The fifth embodiment has the same structure and operates in the same manner as the first embodiment except for the portions of the anomaly countermeasure system 30d specifically stated. In the following description, components that are the same as or equivalent to those in the first embodiment described above are designated by the same reference numerals, and their description will be simplified or omitted.

[0116] The emergency measure proposal unit 36 ​​has the function of determining whether to make a continuation of operation decision Co or an emergency measure proposal Fa. It inputs countermeasure information Ci, including the cause weight table Wt, the cause analysis results, countermeasure proposals, and countermeasure effects, and outputs the continuation of operation decision Co and the emergency measure proposal Fa to the railway operator's operation control center 40 and the cab 12. The countermeasure proposal unit 32 uses a digital twin to predict the value of a target parameter after an abnormality flag is raised. The continuation of operation decision Co instructs the cab 12 to continue operation if the predicted value of the target parameter is below a threshold for continuation of operation that is different from the threshold for raising an abnormality flag. In other words, the abnormality countermeasure system 30d instructs the cab 12 to continue operation if it determines that continuing operation will not worsen the abnormality. The emergency measure proposal Fa instructs the cab 12 to take emergency measures to resolve the abnormality if the countermeasure proposal can be immediately implemented by the cab 12 and, as a result, allows operation to continue.

[0117] (Actions and Effects) With the configuration of Example 5, even if an abnormality flag is generated, if operation can be continued or emergency measures can be taken on the vehicle, the abnormality countermeasure system 30d can automatically instruct the driver's cab 12 and the railway operator's operation control center 40 to make a decision to continue operation Co and propose emergency measures Fa, without the need for a decision to be made by the railway operator's operation control center 40.

[0118] [Example 6] In Example 1, the countermeasure proposals, countermeasure effects, and cause-and-effect analysis output by the anomaly countermeasure system 30 were directly transmitted to the train operation control center 40 of the railway operator. However, when actually implementing countermeasures, replacement, repair, and program changes other than those related to vehicle operation are carried out by the manufacturer 50. In addition, the countermeasure proposals, countermeasure effects, and cause-and-effect analysis output by the anomaly countermeasure system 30 are automatically calculated, and in order to examine their accuracy and determine whether to incorporate them into the countermeasures, a certain level of knowledge is required, although not as extensive as that required for manual analysis. Therefore, in Example 6, the countermeasure proposals, countermeasure effects, and cause-and-effect analysis output by the anomaly countermeasure system 30d are first transmitted to the manufacturer 50, and after confirmation and correction by the manufacturer 50, are transmitted to the train operation control center 40 of the railway operator.

[0119] 20 is an operational block diagram of an anomaly countermeasure system 30e for transmitting to a manufacturer 50 according to a sixth embodiment of the present invention. The sixth embodiment has the same structure and operates in the same manner as the first embodiment except where specifically noted in the anomaly countermeasure system 30e. In the following description, components that are the same as or equivalent to those in the first embodiment described above are designated by the same reference numerals, and their description will be simplified or omitted.

[0120] Here, the countermeasure information Ci including the countermeasure proposal, the countermeasure effect, and the cause and effect analysis is first transmitted to the manufacturer 50, and after confirmation and correction by the manufacturer 50, it is transmitted to the operation control center 40, but this is not limiting. The countermeasure proposal, the countermeasure effect, and the cause and effect analysis output by the anomaly countermeasure system 30e may be directly transmitted in parallel to the operation control center 40 of the railway operator and the manufacturer 50, and the manufacturer 50 may transmit the judgment result of the transmitted content to the operation control center 40.

[0121] (Actions and Effects) With the configuration of Example 6, the train operation control center 40 of the railway business operator can delegate the accuracy of the cause-and-effect analysis, countermeasure proposals, and countermeasure effects output by the abnormality countermeasure system 30e to the manufacturer 50 without having to judge for itself. Note that instead of the manufacturer 50, a railway incident party or a person entrusted with the management of all or part of the railway vehicles by the manufacturer 50 may receive the countermeasure proposals and implement various countermeasures.

[0122] [Example 7] In Example 1, when an abnormality flag is raised, a countermeasure proposal is made for the train set including the vehicle in which the abnormality was detected. However, multiple train sets are introduced to a certain line. These are manufactured and used roughly at the same time, and because they are rotated and used in a uniform manner, abnormalities often occur at the same time. Therefore, when an abnormality occurs in one train set, it is necessary to investigate whether an abnormality is likely to occur in other train sets and when the abnormality is expected to occur.

[0123] 21 is an operational block diagram of an anomaly countermeasure system 30f having a spread assessment unit 37 according to a sixth embodiment of the present invention. The sixth embodiment has the same structure and operates in the same manner as the first embodiment except where specifically noted in the anomaly countermeasure system 30f. In the following description, components that are the same as or equivalent to those in the first embodiment described above are designated by the same reference numerals, and their description will be simplified or omitted.

[0124] In response to an abnormality flag Af generated in an electric vehicle, the abnormality countermeasure system 30f analyzes data from one or both of the vehicle control devices and battery control devices of electric vehicles other than the electric vehicle, thereby diagnosing signs of an abnormality in the electric vehicles other than the electric vehicle in which the abnormality occurred and notifying the railway operator. Specifically, assume a situation in which there are any number of two or more vehicle traction systems 1A, and one of the traction systems 1A has generated an abnormality. The abnormality countermeasure system 30f of Example 6 includes a spread assessment unit 37 and a storage area 313 in addition to the cause determination unit 31 and the countermeasure proposal unit 32 of Example 1. Note that the storage area 313 may be provided in the abnormality countermeasure system 30f and shared by both the cause determination unit 31 and the countermeasure proposal unit 32, or may be provided in each of the cause determination unit 31 and the countermeasure proposal unit 32. Furthermore, since the abnormality countermeasure system 30f in Example 6 is required to analyze data from other trains, it is usually installed as a server outside the traction system 1A, but it may also be configured such that each train is equipped with an abnormality countermeasure system 30f and receives the abnormality flags and cause weight tables Wt of other trains via communication. The storage area 313 stores the abnormality flags Af, battery data Db, vehicle data Dv, and weather data Dw of multiple traction systems 1A.

[0125] The contagion evaluation unit 37 receives the anomaly flag and cause weight table Wt of the train set in which the abnormality occurred, and past data of other train sets, and outputs a sign flag Si indicating the possibility of an abnormality occurring in the other train sets and a predicted abnormality date and time Es. The contagion evaluation unit has the function of calculating whether there are signs of the same abnormality occurring in train sets other than the one in which the abnormality occurred and the predicted date and time of the abnormality. The diagnosis of an abnormality sign in the other train sets and the date and time of occurrence can be predicted from the temporal development of a target parameter for a certain abnormality flag, as in the processing by the abnormality sign diagnosis unit 35 in Example 4, for example. In addition, the parameter corresponding to the abnormality weight calculated by the cause determination unit 31 can be determined based on how similar it is to the train set in which the abnormality occurred in the other train set.

[0126] (Actions and Effects) With the configuration of Example 7, when an abnormality flag is raised for a certain train set, the railway operator's operation control center 40 can automatically grasp the occurrence of an abnormality in other train sets and the date on which the abnormality occurred, and can quickly plan maintenance work in advance.

[0127] [Embodiment 8] FIG. 22 is a diagram illustrating the configuration of a traction system for a railway vehicle equipped with a storage battery to which an abnormality countermeasure system according to embodiment 8 of the present invention is applied. Embodiment 8 illustrates a specific configuration in which the abnormality countermeasure system 30 is located outside the vehicle. The structure and operation are similar to those of embodiment 1, except where otherwise specified. In the following description, components identical or equivalent to those of embodiment 1 are denoted by the same reference numerals, and their description will be simplified or omitted. The data transmission / reception device 60 is located inside the vehicle and communicates with the storage battery device 20, the vehicle control device 13, and the driver's cab 12. The data transmission / reception device 60 also wirelessly communicates with the abnormality countermeasure system 30 located outside the vehicle, for example, on a manufacturer's server 70 or on a cloud. The wireless communication may be, for example, via a mobile phone line, the Internet, or the cloud, but is not limited thereto and may also be via an intranet using local 5G. The data transmission / reception device 60 does not necessarily have to be independent of the traction system 1A and may be included in the vehicle control device 13 or the battery control device 21. The abnormality countermeasure system may also collect information directly without going through the vehicle control device 13. Furthermore, sensors such as a GPS and an ammeter may be provided in the data transmitter / receiver 60, and the condition may be estimated from the measurement results of these sensors. The abnormality countermeasure system 30 communicates with the operation control center 40 via the Internet, for example, but is not limited to this, and communication may also be via a dedicated line, for example. Weather data Dw measured at a nearby point outside the vehicle may also be obtained directly without going through the vehicle control device 13.

[0128] (Actions and Effects) The configuration of Example 8 reduces the number of devices inside the vehicle, making it easier for the abnormality countermeasure system 30 to collect various data, thereby enabling a system for proposing countermeasures to be constructed efficiently and countermeasure proposals to be made more effectively.

[0129] Although the embodiments of the present invention have been described above, the present invention is not limited to the above-described embodiments, and various modifications are possible within the scope of the gist of the present invention.

[0130] DESCRIPTION OF SYMBOLS 1A... Drive system 1B... Drive system 2... Pantograph 3... Engine 4... Generator 5... Converter 6... Inverter for electric motor 7... Electric motor 8... Reducer 9... Wheelset 10... Inverter for auxiliary equipment 11... Auxiliary equipment 12... Driver's cab 13... Vehicle control device 14... Overhead line 20... Storage battery device 21... Battery control device 30, 30a, 30b, 30c, 30d, 30e, 30f... Abnormality countermeasure system 31... Cause determination unit 311... Related parameter extraction unit 312... Cause weight calculation unit 313... Storage area 314... Model verification unit 3141... Determination unit 3142... Vehicle digital twin 3143... Battery digital twin 31431... Calculation target designation unit 31432... Temperature model 31433... Closed circuit voltage model 31434... Charging rate model 315... Sensitivity calculation unit 3151: Sensitivity map generation unit 3152: Minute change generation unit 32: Countermeasure proposal unit 321: Changeable range calculation unit 322: Countermeasure effect calculation unit 323: Proposal decision unit 33: Correctness determination unit 34: Control constant change unit 35: Abnormality sign diagnosis unit 36: Emergency measure proposal unit 37: Impact evaluation unit 40: Operation control center 50: Manufacturer 70: Server

Claims

1. In an abnormality countermeasure system used in an electric vehicle equipped with a drive system using a storage battery device, The abnormality countermeasure system includes a cause determination unit and a countermeasure proposal unit, The cause determination unit is monitor the status of the electric vehicle and the battery equipment; When an abnormality flag is output from at least one of the electric vehicle and the storage battery device, Analyzing a state of at least one of the electric vehicle and the battery equipment, and identifying a cause of the abnormality indicated by the abnormality flag; The measure suggestion unit, notifying the manager of the electric car of the result of the analysis of the cause of the abnormality flag and the proposed countermeasures; The proposed measures include classification of changes to the operation method of the electric vehicle, changes to control parameters of the battery equipment or the drive system, repairs to defective software or devices of the battery equipment or the drive system, and replacement of deteriorated batteries. This is an abnormality countermeasure system characterized by the above.

2. 2. The abnormality countermeasure system according to claim 1, The proposed measures include a classification of changes to the operation method or changes to the control parameters under special conditions. This is an abnormality countermeasure system characterized by the above.

3. In the abnormality countermeasure system according to claim 1 or 2, The cause determination unit subdivides the causes of the abnormality flag and presents each of the causes with a weight indicating the degree of influence. This is an abnormality countermeasure system characterized by the above.

4. 4. The abnormality countermeasure system according to claim 1, The cause determination unit checks a history of parameters related to the abnormality flag, and weights parameters that have changed significantly in the history. This is an abnormality countermeasure system characterized by the above.

5. 4. The abnormality countermeasure system according to claim 1, The cause determination unit checks a history of a parameter related to the abnormality flag, and in the history, sets a ratio of a past parameter value to a latest parameter value as a weight. This is an abnormality countermeasure system characterized by the above.

6. 6. The abnormality countermeasure system according to claim 1, The cause determination unit is It has a vehicle digital twin and a battery digital twin, The sensitivity of the abnormal flag to the target parameter is calculated by slightly changing the parameter related to the abnormal flag, and the weight of the cause of the abnormal flag is calculated. This is an abnormality countermeasure system characterized by the above.

7. 7. The abnormality countermeasure system according to claim 6, The battery digital twin calculates battery temperature, closed circuit voltage, and charge rate. This is an abnormality countermeasure system characterized by the above.

8. 8. The abnormality countermeasure system according to claim 1, The abnormality countermeasure system, in response to the abnormality flag generated in the electric vehicle, By analyzing data of one or both of a vehicle control device and a battery control device of an electric vehicle different from the electric vehicle, Diagnose signs of abnormalities in electric cars other than the one where the abnormality occurred, Notify the administrator This is an abnormality countermeasure system characterized by the above.

9. 9. The abnormality countermeasure system according to claim 1, The cause determination unit classifies the cause of the abnormality flag into one of the following: (1) an unexpected event, (2) an abnormal environment, (3) a harsh vehicle operating method, (4) battery deterioration, (5) an inappropriate control parameter, (6) a malfunction of a control program, and (7) a hardware failure. This is an abnormality countermeasure system characterized by the above.

10. 10. The abnormality countermeasure system according to claim 1, The cause determination unit subdivides and presents the causes of the abnormality flags by fault tree analysis. This is an abnormality countermeasure system characterized by the above.

11. In the abnormality countermeasure system according to any one of claims 1 to 10, The countermeasure suggestion unit proposes a plurality of countermeasures for each individual cause of the abnormality flag. This is an abnormality countermeasure system characterized by the above.

12. The abnormality countermeasure system according to any one of claims 1 to 11, The measure suggestion unit sets a changeable range of a parameter related to the abnormality flag, The proposed parameter change value is within the range of the allowable change. This is an abnormality countermeasure system characterized by the above.

13. The abnormality countermeasure system according to claim 12, The measure suggestion unit sets the changeable range based on a criterion of whether deterioration of a target parameter of an abnormality flag other than the abnormality flag is within a threshold value. This is an abnormality countermeasure system characterized by the above.

14. The abnormality countermeasure system according to any one of claims 1 to 13, The measure suggestion unit changes a control constant of the electric vehicle or the storage battery equipment. This is an abnormality countermeasure system characterized by the above.

15. 15. The abnormality countermeasure system according to claim 1, The cause determination unit predicts the occurrence of an abnormality from the data of the control device and issues a prediction flag. This is an abnormality countermeasure system characterized by the above.

16. 16. The abnormality countermeasure system according to claim 1, The abnormality countermeasure system instructs a driver's cab on countermeasures that can be implemented by the electric vehicle during operation among the countermeasures proposed by the countermeasure proposal unit. This is an abnormality countermeasure system characterized by the above.

17. A method for dealing with an abnormality in an electric vehicle equipped with a drive system using a storage battery device, comprising: monitor the states of the electric vehicle and the storage battery equipment, and when an abnormality flag is output from at least one of the electric vehicle and the storage battery equipment, analyze the state of at least one of the electric vehicle and the storage battery equipment and identify the cause of the abnormality indicated by the abnormality flag; notifying the manager of the electric car of the result of the analysis of the cause of the abnormality flag and the proposed countermeasures; The proposed measures include classification of changes to the operation method of the electric vehicle, changes to control parameters of the battery equipment or the drive system, repairs of defective software or defective devices of the battery equipment or the drive system, and battery replacement. The abnormality countermeasure method is characterized by the above.