JP7126897B2 - Server, Charging Station Guidance System, Charging Station Guidance Method, and Program - Google Patents

Description

The present invention relates to technology for guiding a charging station.

When trying to charge an electric vehicle at a certain charging station, if another electric vehicle has already been charged at that charging station, the vehicle must wait until the charging of that electric vehicle is completed. In general, charging an electric vehicle takes a longer time than refueling a gasoline vehicle. The need to wait until charging is completed is a factor that makes users feel inconvenient, especially in comparison with gasoline vehicles.

In order to reduce waiting time at a charging station, Patent Literature 1 describes a technique of creating predicted operation information of a charging station in consideration of predicted arrival time to the charging station. Further, Patent Literature 2 discloses a technique for calculating a predicted value of power demand for a specific charging facility (charging station).

JP 2014-225167 A JP 2017-112830 A

A user may wish to charge at a charging station that completes charging quickly. However, the performance of each charging station is different, and there is a problem that the usage situation changes from moment to moment.

In contrast, the present invention provides the user with a predicted charging completion time.

According to one aspect of the present disclosure, a time required for a target electric vehicle corresponding to a target user terminal among a plurality of user terminals to reach a target charging station selected from among a plurality of charging stations is acquired. 1 acquisition means, a second acquisition means for acquiring a waiting time at the target charging station, a third acquisition means for acquiring a charging time required for charging the target electric vehicle, the required time, the waiting time, and the A server is provided that has prediction means for predicting completion time at which charging of the target electric vehicle is completed using charging time, and notification means for notifying the target user terminal of the completion time.

Further, according to one aspect of the present disclosure, the time required for the target electric vehicle corresponding to the target user terminal among the plurality of user terminals to reach the target charging station selected from among the plurality of charging stations is acquired. a second acquisition means for acquiring a waiting time at the target charging station; a third acquisition means for acquiring a charging time required for charging the target electric vehicle; the required time, the waiting time, and a prediction means for predicting completion time of charging of the target electric vehicle using the charging time, and a notification means for notifying the target user terminal of the completion time.

Furthermore, according to one aspect of the present disclosure, the time required for the target electric vehicle corresponding to the target user terminal among the plurality of user terminals to reach the target charging station selected from among the plurality of charging stations is acquired. acquiring a waiting time at the target charging station; acquiring a charging time required for charging the target electric vehicle; and using the required time, the waiting time, and the charging time to A charging station guidance method is provided that includes the steps of predicting a completion time at which charging of an electric vehicle will be completed, and notifying the target user terminal of the completion time.

Further, according to one aspect of the present disclosure, the computer is configured to display the time required for a target electric vehicle corresponding to a target user terminal among a plurality of user terminals to reach a target charging station selected from among a plurality of charging stations. acquiring a waiting time at the target charging station; acquiring a charging time required for charging the target electric vehicle; and using the required time, the waiting time, and the charging time. a step of estimating a completion time at which charging of the target electric vehicle is completed, and a step of notifying the target user terminal of the completion time.

Further, according to one aspect of the present disclosure, the computer is configured to display the time required for a target electric vehicle corresponding to a target user terminal among a plurality of user terminals to reach a target charging station selected from among a plurality of charging stations. a first acquisition means for acquiring a time, a second acquisition means for acquiring a waiting time at the target charging station, a third acquisition means for acquiring a charging time required for charging the target electric vehicle, the required time, the waiting time, and a charging station information provision request to a server having predicting means for predicting a charging completion time of the target electric vehicle using the charging time, and notification means for notifying the target user terminal of the charging completion time. receiving a notification including the completion time at the target charging station as a response to the information provision request; and displaying information including the completion time. be done.

Furthermore, according to one aspect of the present disclosure, the required time until the target fuel cell vehicle corresponding to the target user terminal among the plurality of user terminals reaches the target hydrogen station selected from among the plurality of hydrogen stations a first acquiring means for acquiring, a second acquiring means for acquiring the waiting time at the target hydrogen station, a third acquiring means for acquiring the replenishment time required for replenishing the hydrogen of the target fuel cell vehicle, the required time, A server is provided having prediction means for predicting completion time of completion of replenishment of the target fuel cell vehicle using the waiting time and the replenishment time, and notification means for notifying the target user terminal of the completion time. be.

ADVANTAGE OF THE INVENTION According to this invention, a user can be provided with the predicted charging completion time.

The figure which shows the outline|summary of the charging station guidance system which concerns on one Embodiment. The figure which illustrates the functional structure of a charging station guidance system. The figure which illustrates the functional structure of a charging station. The figure which illustrates the hardware constitutions of a server. The figure which illustrates the hardware constitutions of a user terminal. 4 is a sequence chart illustrating the operation of the charging station guidance system; The figure which illustrates a stand database. The figure which illustrates an operation result database. The figure which illustrates the screen which shows the search result of a charging station. FIG. 10 is a flow chart showing a process when waiting for an instruction on the screen of FIG. 9; FIG. The figure which shows the process which displays the detailed information of a charging station. The figure which illustrates the display screen of detailed information. The figure which illustrates the screen which displays the more detailed information of a charging station. 4 is a sequence chart illustrating processing of a provisional reservation; The figure which illustrates a tentative reservation database. The figure which illustrates the screen which shows the provisionally reserved charging station. The figure which illustrates the screen which notifies a situation change. 4 is a flowchart showing charging processing at the charging station.

1. Configuration FIG. 1 is a diagram showing an outline of a charging station guidance system 1 according to one embodiment. The charging station guidance system 1 has a server 10 , a user terminal 20 , an electric vehicle 30 and a charging station 40 . The charging station guidance system 1 is a system that provides information on the charging station 40 to the user of the electric vehicle 30 . Here, the user means the driver or fellow passenger of the electric vehicle 30 . An electric vehicle is a vehicle that runs by rotating an electric motor using a secondary battery that is charged by connecting an electric plug to the vehicle body as an energy source. A charging station is a charging device for charging an electric vehicle. A network N is a network for communication among a plurality of devices, such as the Internet.

The charging station guidance system 1 has a plurality of user terminals 20 , electric vehicles 30 and charging stations 40 . For example, when distinguishing each of the plurality of user terminals 20, the user terminal 20[1], the user terminal 20[2], . The same applies to the electric vehicle 30 and the charging station 40 as well.

The user terminal 20 is a terminal device for providing a user interface, receives an instruction or information input from a user, and outputs information provided from a device such as the server 10 or the like. In one example, the user terminal 20 is a mobile terminal such as a smartphone or tablet owned by the user. Alternatively, the user terminal 20 may be an in-vehicle device such as a car navigation device. The user terminal 20 corresponds to the electric vehicle 30 in the sense that it is used by the driver or passenger of the electric vehicle 30 . A user terminal corresponding to the electric vehicle 30[k] is represented as a user terminal 20[k].

FIG. 2 is a diagram illustrating the functional configuration of the charging station guidance system 1. As shown in FIG. In FIG. 2, functions of the server 10 and the user terminal 20 are illustrated. The charging station guidance system 1 includes storage means 11, reception means 12, acquisition means 13, prediction means 14, determination means 15, notification means 16, management means 17, prediction means 81, prediction means 82, prediction means 83, reception means 21. , transmitting means 22 , receiving means 23 and guiding means 24 . In this example, the storage means 11, the reception means 12, the acquisition means 13, the prediction means 14, the determination means 15, the notification means 16, the management means 17, the prediction means 81, the prediction means 82, and the prediction means 83 are mounted on the server 10. be. Receiving means 21 , transmitting means 22 , receiving means 23 and guiding means 24 are implemented in user terminal 20 .

First, functions of the server 10 will be described. The storage means 11 stores various data. The data stored by the storage means 11 includes a stand database. The stand database is a database in which information on charging stand 40 is recorded. Information about the charging station 40 includes, for example, location (address or coordinates), name ("S oil A store", etc.), facility type (gas station, convenience store, high-speed service area, shopping mall, etc.), output performance (20 kW etc.), charge information (300 yen/10 minutes, etc.), and plug shape (CHAdeMO, 200V outlet, with 200V charging cable, TeslaSC, etc.). When a plurality of charging stations 40 are installed in one area (for example, when three charging stations 40 are installed in one gas station), the charging station guidance system 1 can identify these three charging stations. 40 are treated as separate charging stations.

The receiving means 12 receives information from the user terminal 20 . The information received by the receiving means 12 includes requests or instructions to the server 10, or various data. Acquisition means 13 acquires various kinds of information from other components in server 10 or external devices. Acquisition means 13 has acquisition means 131 , acquisition means 132 , and acquisition means 133 .

Acquisition means 131 (an example of a first acquisition means) acquires the time required for target electric vehicle 30 (hereinafter referred to as "target electric vehicle") to reach target charging station 40 (hereinafter referred to as "target charging station"). Get the required time. The target electric vehicle is an electric vehicle corresponding to the target user terminal 20 (hereinafter referred to as “target user terminal”) among the plurality of user terminals 20 . Specifically, the target electric vehicle is the electric vehicle 30 in which the user who carries the target user terminal is riding when the target user terminal is a portable terminal, and the target electric vehicle is the target user terminal when the target user terminal is an in-vehicle device. It is an electric vehicle 30 on which a user terminal is mounted. The target charging station is the charging station 40 selected from the plurality of charging stations 40 . The target charging station may be selected automatically by the system or by the user. In this embodiment, the charging station guidance system 1 automatically selects the target charging station. In this example, the acquisition means 131 acquires the required time from the prediction means 81 . The prediction means 81 predicts the required time from the position of the target electric vehicle and the position of the target charging station. In one example, the prediction means 81 stores map data and predicts the required time along a given route between two points. When predicting the required time, the prediction means 81 may refer to road traffic information (information on road closures and traffic jams). By adding the required time to the current time, a predicted value of the expected arrival time (hereinafter simply referred to as "arrival time") is obtained.

Acquisition means 132 (an example of second acquisition means) acquires the waiting time at the target charging station. The waiting time is the time from arrival until charging can be started, assuming that the target electric vehicle arrives at the target charging station at a given reference time (for example, the current time). If there is another electric vehicle 30 being charged at the target charging station before the target electric vehicle, the target electric vehicle cannot start charging until the charging of the target electric vehicle 30 is completed. In this example, the acquisition means 132 acquires the waiting time from the prediction means 82 . The prediction unit 82 predicts the waiting time by referring to, for example, the status of reservations for the target charging station or the status of the electric vehicles 30 currently waiting at the target charging station. By adding the waiting time to the arrival time, a predicted value of the charging start time (hereinafter simply referred to as "charging start time") is obtained.

Here, "reservation" of charging will be described. Reservation means registering a schedule for charging at a target charging station to the charging station guidance system 1 . In this embodiment, "reservation" is subdivided into "final reservation" and "provisional reservation". The real reservation means securing the exclusive right to use the target charging station (securing the time slot of the charging station 40 for the subscriber). For example, if a user makes a permanent reservation for the target charging station from 9:00 to 10:00, other users cannot use the target charging station from 9:00 to 10:00. On the other hand, provisional reservation means registering the intention to charge at the target charging station without securing a specific time slot in the charging station guidance system 1 . The provisional reservation is an example of "registration to charge at the charging station 40". In other words, the provisional reservation is merely a declaration of intention to charge at the charging station 40 . The simple term "reservation" is a concept that encompasses permanent reservation and provisional reservation.

Acquisition means 133 (an example of a third acquisition means) acquires the charging time required for charging the target electric vehicle. The charging time refers to the time required to charge a predetermined amount (for example, full charge) after starting charging of the target electric vehicle at the target charging station. In this example, the acquisition means 133 acquires the waiting time from the prediction means 83 . The prediction means 83 predicts the charging time with reference to the output performance of the charging station 40, the remaining battery level of the target electric vehicle, the temperature at the charging station 40, and the like.

The prediction unit 14 uses the required time, the waiting time, and the charging time acquired by the acquisition unit 13 to predict the charging completion time of the target electric vehicle. Hereinafter, unless otherwise specified, the “charge completion time” refers to the charge completion time predicted by the prediction means 14 (that is, the predicted value). In one example, adding the required time, the waiting time, and the charging time to the current time gives the charging completion time. The determination means 15 determines the prediction accuracy of the prediction means 14 . In general, it is difficult to accurately predict the charging completion time, and the calculated charging completion time contains some uncertainty. Prediction accuracy indicates this uncertainty. The notification means 16 notifies the target user terminal of the charging completion time obtained by the prediction means 14 and its prediction accuracy.

Next, functions of the user terminal 20 will be described. The accepting means 21 accepts an instruction input from the user. The instruction received by the receiving means 21 includes, for example, an instruction requesting that the charging station 40 be guided. The transmitting means 22 transmits information corresponding to the instruction received by the receiving means 21 , for example, a request for guidance of the charging station 40 to the server 10 . The receiving means 23 receives various data from an external device such as the server 10 . The data received by the receiving means 23 includes guidance data as a response to the guidance request transmitted by the transmitting means 22 . The guidance data includes, for example, map data for guiding the charging station 40 .

FIG. 3 is a diagram illustrating the functional configuration of the charging station 40. As shown in FIG. The charging station 40 has charging means 41 , storage means 42 , communication means 43 and reception means 44 . The charging means 41 charges the electric vehicle 30 . The charging means 41 has, for example, an AC/DC conversion unit that converts input AC power into DC power, a control unit that starts/ends charging or detects an abnormality, and a connector that is connected to the electric vehicle 30 . The storage means 42 stores various data and programs. The communication means 43 communicates with the server 10 . The communication means 43 transmits to the server 10 information indicating the usage status of the charging means 41, for example, whether the charging means is being charged or not. The receiving means 44 provides a user interface for the user of the charging station 40 . The user inputs an instruction regarding the start or end of charging or the payment and receipt of charges via the receiving means 44 . Although not shown, the charging stand 40 may have control means for controlling other components and detection means for detecting the state of the surroundings of the charging stand 40 . The detection means includes, for example, a camera that photographs the electric vehicle 30 waiting to be charged at the charging station 40 . Further, for example, the communication means 43 may receive information on reservation of the charging means 41 from the server 10 . In this case, the receiving unit 44 performs processing corresponding to the reservation, such as not receiving an instruction to start charging from a user who has not made the reservation.

FIG. 4 is a diagram illustrating the hardware configuration of the server 10. As illustrated in FIG. The server 10 is a computer device having a CPU (Central Processing Unit) 101 , a memory 102 , a storage 103 and a communication IF (Interface) 104 . The CPU 101 is a control device that executes programs to perform various calculations and controls other hardware elements of the server 10 . The memory 102 is a main storage device that functions as a work area when the CPU 101 executes programs. The storage 103 is a non-volatile auxiliary storage device that stores various programs and data. The communication IF 104 is a communication device that communicates with other devices according to a predetermined communication standard (eg, Ethernet (registered trademark)).

In this example, the storage 103 stores a program (hereinafter referred to as “server program”) for causing the computer device to function as the server 10 in the charging station guidance system 1 . The functions shown in FIG. 2 are implemented in the computer by the CPU 101 executing the server program. At least one of the memory 102 and the storage 103 is an example of the storage unit 11 while the CPU 101 is executing the server program. Communication IF 104 is an example of receiving means 12 . The CPU 101 is an example of the acquisition means 13 , the prediction means 14 , the determination means 15 , the notification means 16 , the management means 17 , the prediction means 81 , the prediction means 82 , and the prediction means 83 .

FIG. 5 is a diagram illustrating the hardware configuration of the user terminal 20. As shown in FIG. The user terminal 20 is a computer device, such as a smart phone, having a CPU 201 , a memory 202 , a storage 203 , a communication IF 204 and a touch screen 205 . The CPU 201 is a control device that executes programs to perform various calculations and controls other hardware elements of the user terminal 20 . A memory 202 is a main storage device that functions as a work area when the CPU 201 executes a program. The storage 203 is a nonvolatile auxiliary storage device that stores various programs and data. The communication IF 204 is a communication device that communicates with other devices according to a predetermined communication standard (for example, a mobile communication standard such as LTE (Long Term Evolution)). The touch screen 205 is an input/output device that displays information to the user and receives input of information from the user.

In this example, the storage 203 stores a program (hereinafter referred to as “client program”) for causing the computer device to function as the user terminal 20 in the charging station guidance system 1 . As the CPU 201 executes the client program, the functions of FIG. 2 are implemented in the computer device. The touch screen 205 is an example of the reception means 21 and the guidance means 24 while the CPU 201 is executing the client program. Communication IF 204 is an example of transmitting means 22 and receiving means 23 .

2. Operation 2-1. Search and Guidance FIG. 6 is a sequence chart illustrating the operation of the charging station guidance system 1 . First, in step S501, the charging stand 40 detects its own state. The status of the charging station 40 includes, for example, whether or not there is an electric vehicle 30 being charged at the charging station 40 at that time, the remaining charging time if there is an electric vehicle 30 being charged, and whether the charging station 40 is waiting for charging. and the temperature at the charging station 40. The number of electric vehicles 30 waiting to be charged can be obtained, for example, by analyzing images captured by a camera installed at or near the charging station 40 . In one example, charging station 40 transmits captured images to another device (eg, server 10), which analyzes the images. The processing of step S501 is triggered by a predetermined event. This predetermined event is, for example, an event such as when a predetermined time has passed since the state was detected last time, when a predetermined time has been reached, or when there is an instruction from the server 10 . In step S<b>502 , charging station 40 transmits the detection result to server 10 . In step S503, server 10 stores the detection result received from charging station 40 in the station database. Each charging station 40 independently and repeatedly executes the processes of steps S501 and S502, and the latest information is recorded in the station database.

FIG. 7 is a diagram illustrating a stand database. In this example, the stand database includes items such as facility type, stand name, location, performance, fee, remaining charging time, number of vehicles waiting, and temperature. These items include items whose values do not change for a relatively long period of time ("fixed items") and items whose values are updated at relatively short intervals ("variable items"). The facility type, stand name, location, performance, and fee are fixed items. Remaining charging time, number of vehicles waiting, and temperature are variable items. The variable item is a record of the state detected in step S501. “Facility type”, “stand name”, and “location” indicate the facility type, name (identifier), and location of the charging station 40 . “Performance” indicates the output performance [kW] of the charging stand 40 . “Price” indicates the charging fee (for example, [yen/kW] or [yen/minute]) at the charging station 40 . The “remaining charging time” indicates the remaining charging time [time] of the electric vehicle 30 currently being charged at the charging station 40 . If there is no electric vehicle 30 being charged at the charging station 40 at that time, the remaining charging time is 0 minutes. “Waiting number” is the number of electric vehicles 30 waiting to be charged at the charging station 40 at the site. “Temperature” indicates the temperature around the charging station 40 .

Please refer to FIG. 6 again. Prior to step S101, the user has started the client program on the user terminal 20. FIG. Information about the corresponding electric vehicle 30 (hereinafter referred to as "vehicle information") is registered in advance in the client program. The vehicle information includes, for example, the vehicle model name, vehicle number (license plate number), battery capacity, and plug shape of the charging plug. In the following, a software element such as a client program may be described as a subject of processing. It means to work and execute a process. Further, in the following description, the electric vehicle 30 corresponding to the user terminal 20 executing the client program for processing is the "target electric vehicle" for the client program.

In step S101, the client program receives an instruction input from the user. This instruction is, for example, a search instruction for charging station 40 . In step S102, the client program transmits a search request for charging station 40 to server 10 in accordance with the input instruction. The search request is an example of an "information provision request" requesting provision of information on the target charging station. This search request includes, for example, identification information of the user terminal 20, vehicle information about the target electric vehicle (for example, vehicle type and remaining battery capacity or battery capacity), information about the position of the target electric vehicle (hereinafter referred to as "position information"), and other search information. Including key. The location information includes at least information indicating the current location of the target electric vehicle, and may further include information indicating the destination of the target electric vehicle. The search key is information for narrowing down the charging station 40. For example, the facility type (for example, "convenience store only"), charging fee (for example, "200 yen/10 minutes or less"), and relationship with location information (for example, "within 10 minutes from the current position", "within 15 minutes to the destination", etc.).

In step S<b>103 , the server program of the server 10 searches the station database for a charging station 40 that matches the search request received from the user terminal 20 . The charging station 40 specified (selected) by the search is the target charging station. That is, there may be a plurality of target charging stations. In step S104, the server program acquires information (charging station information) on charging stations 40 matching the search request from the station database. At this time, the server program may narrow down the number of charging stations for which information is to be acquired to a predetermined threshold value or less.

In step S105, the server program acquires (calculates) the time required for the target electric vehicle to reach the target charging station. When calculating the required time, for example, the distance from the current position of the target electric vehicle to the target charging station and road traffic information are taken into consideration.

In step S106, the server program acquires the operation record of the target charging station. The storage means 11 of the server 10 stores a database (hereinafter referred to as "operation record database") that records the operation records of the charging station 40, and the server program refers to this operation record database to obtain the operation records.

FIG. 8 is a diagram illustrating an example of an operation record database. The operation record database includes items of stand name, operating time, and operation type. "Operating time" indicates the time (start time and end time) during which one electric vehicle 30 was charged. "Operating type" refers to a permanent reservation, provisional reservation, or visitor. A "visitor" is a user who visits without making a reservation. For example, the top row of data indicates that the user who made the reservation charged from 9:00 to 10:00 on March 30th.

Please refer to FIG. 6 again. At step S107, the server program calculates the waiting time at each target charging station. When calculating the waiting time, the server program shall collect at least one of the operation record of the target charging station, the time required to reach the target charging station, the number of vehicles waiting at the target charging station, whether there is a reservation at the target charging station, and the charging fee at the target charging station. 1 may be referred to. In one example, two electric vehicles 30, an electric vehicle 30[1] and an electric vehicle 30[2], have registered provisional reservations for the target charging station,
Electric vehicle 30 [1]: Arrival time 9:30, charging time 15 minutes Electric vehicle 30 [2]: Arrival time 9:40, charging time 20 minutes Target electric vehicle: Arrival time 9:50
, and when it is predicted that two electric vehicles 30 will arrive at the target charging station before the target electric vehicle, the server program assumes that these two electric vehicles 30 will charge, Calculate the waiting time as 15 minutes. In another example, considering the time required to reach the target charging station, if the estimated arrival time at the target charging station is 10:00, the average of If the waiting time was 30 minutes, the server program will calculate the waiting time as 30 minutes. Note that these calculations are merely examples, and the server program may consider more parameters, or may consider these parameters in combination.

At step S108, the server program calculates the charging time at each target charging station. In calculating the charging time, the server program may refer to at least one of the output performance of the target charging station, the remaining battery level of the target electric vehicle, and the temperature. From the remaining battery capacity and output performance, the time to full charge can be calculated. The reason why the temperature is taken into account here is that the temperature affects the charging time.

In step S109, the server program predicts the charging completion time for each target charging station. Here, the server program adds the required time to the target charging station, the waiting time at the target charging station, and the charging time to the current time. For example, if the current time is 8:45, the required time to the target charging station is 15 minutes, the waiting time is 0 minutes, and the charging time is 20 minutes, the server program calculates the charging completion time as 9:20. . The server program calculates charging completion times for all target charging stations.

In step S110, the server program determines the accuracy of prediction of the charging completion time. In this example, the prediction accuracy is determined depending on which of the predetermined levels (for example, three levels of high, medium, and low). For example, prediction accuracy is affected by the number of visitor users at the target charging station. This is because there are more uncertain factors for visitor users than for reserved users. In one example, the server program determines the prediction accuracy as "medium" when the number of visitors in the most recent predetermined period (eg, one week) is within a predetermined range. If the number of visitors exceeds this predetermined range (greater than the upper limit), the server program determines the prediction accuracy as "low". If the number of visitors falls below this predetermined range (less than the lower limit), the server program determines the prediction accuracy as "high." In another example, if the variance of the number of visitors per unit period (e.g., one day) in the most recent predetermined period (e.g., one week) falls within a predetermined range, the server program determines that the prediction accuracy is "medium." do. If the variance of the number of visitors exceeds this predetermined range (greater than the upper limit), the server program judges the prediction accuracy to be "low". If the variance of the number of visitors falls below this predetermined range (less than the lower limit), the server program determines that the prediction accuracy is "high". Alternatively, the server program refers to at least one of the location conditions of the target charging station, the charge rate of the target charging station, the number of other nearby charging stations, the weather, the season, the time of day, and the day of the week to improve the prediction accuracy. You can judge.

Machine learning or AI (Artificial Intelligence) technology may be used in determining the prediction accuracy. For example, the server program records the degree of matching (matching status) between the predicted charging completion time and the actual charging completion time (measured value) for the provisional reservation. For example, the server program clusters matches using factors likely to affect prediction accuracy. Factors likely to affect prediction accuracy include, for example, the number of searches, vehicle type, type of facility, area, number of chargers in the area, level of charge setting, charging date and time, temperature, and the like. The server program searches for elements that are correlated with prediction accuracy from among these elements. By inputting the elements specified in this way to machine learning or the like, the server program can obtain more accurate prediction results. In determining the prediction accuracy, the server program divides the prediction accuracy into levels or quantifies them according to the degree of matching assumed from the values of the elements used to obtain the prediction result.

Note that the prediction accuracy is not limited to being divided into levels, and may be quantified based on a predetermined index. For example, the prediction accuracy of the charging completion time is affected by the prediction accuracy of the required time, the waiting time, and the charging time. The prediction accuracy of the charging completion time may be calculated by a method such as calculating the combined prediction accuracy and substituting these three prediction accuracies into a predetermined formula.

In step S111, the server program notifies the user terminal 20 of information regarding the target charging station as a response to the search request (step S102). This information includes, for example, the facility type, stand name, location, performance, charging fee, and charging completion time of the target charging station. In step S<b>112 , the client program of the user terminal 20 displays a screen showing search results of the charging station 40 .

FIG. 9 is a diagram illustrating a screen showing a search result of charging station 40. As shown in FIG. In this example, the screen showing the search results displays the positions of the target charging stations (three in this example) and related information on a map. The position of the target charging station is indicated by a dot 91 (●), and information related to the target charging station is indicated by a sub-window 92 superimposed on the map. When distinguishing between the three subwindows 92 shown in the drawing, reference numerals in parentheses are used, such as subwindow 92[1] and subwindow 92[2]. The same is true for other elements. Here, the sub-window 92[i] is a sub-window displaying information related to the charging station 40[i].

The sub-window 92 displays the stand name, charging completion time, charging fee, "details" link, "go here" link, and icon 93 . A "details" link is a UI (User Interface) object for shifting to a screen displaying detailed information about the target charging station. The "go here" link is a UI object for making a provisional reservation for charging at the target charging station.

The icon 93 is a UI object indicating the prediction accuracy of the charging completion time. In this example, prediction accuracy is represented by three levels, high, medium, and low, each using a different image. Icon 93[1] indicates a high level, icon 93[3] indicates a medium level, and icon 93[2] indicates a low level. For example, in this example, for the stand name "S Oil A" indicated by the sub-window 92[1], the charging completion time is 10:52, and the prediction accuracy is high. On the other hand, the charging completion time of "C convenience store X" indicated by the sub-window 92[2] is 10:51, and the prediction accuracy is low. The prediction accuracy is highly visible with an icon, and the user can easily recognize the prediction accuracy.

In the screen of FIG. 9, the base map portion is updated according to changes in the position of the vehicle itself (that is, according to the running of the target electric vehicle). This processing is similar to the UI in a known car navigation device. When the screen of FIG. 9 is displayed, the client program waits for input of instructions from the user. In this state, the client program accepts instructions such as moving to a screen displaying detailed information on the target charging station (selecting the "details" link) and making a provisional reservation for charging at the target charging station (selecting the "go here" link). selection) are included.

FIG. 10 is a flow chart showing the process of waiting for an instruction on the screen of FIG. At step S113, the client program waits for input. When the "details" link is selected (S113: "details"), the client program shifts the process to the flow of FIG. When the "go here" link is selected (S113: "go here"), the client program shifts the process to the flow of FIG.

FIG. 11 is a sequence chart illustrating the process of displaying detailed information on charging station 40 . In step S<b>201 , the client program transmits a request for transmitting detailed information (hereinafter referred to as “detailed request”) to the server 10 . The detailed request includes, for example, the identification information of the user terminal 20, the identification information of the charging station 40 for which the detailed information is requested, and the current position of the target electric vehicle.

Upon receiving a detailed request from the user terminal 20, the server program of the server 10 acquires information from the stand database or the like, and uses the acquired information to generate a screen displaying the detailed information (step S202). The server program transmits the generated screen data to the user terminal 20 (step S203). The client program of the user terminal 20 displays a screen according to the received data (step S204).

FIG. 12 is a diagram illustrating a detailed information display screen. Here, in addition to the charging station 40 for which display of detailed information has been requested, detailed information on two charging stations 40 recommended by the charging station guidance system 1 is displayed. This display screen has a display area 901 , buttons 902 , 903 , links 904 , buttons 905 , windows 906 and buttons 907 . A display area 901 is an area for displaying information about the charging station 40 . The information displayed here includes the stand name, output performance, facility type, arrival time, charging start time, charging completion time, and charging fee. Note that the arrival time, charging start time, charging completion time, and charging fee displayed here are predicted values obtained by the server 10 . A button 902 is a UI object for displaying more detailed information about the charging station 40 .

FIG. 13 is a diagram illustrating a screen displaying more detailed information about the charging station 40. As shown in FIG. When the button 902 is selected (tapped or clicked), the window in FIG. 13 is displayed over the screen in FIG. The window in FIG. 13 includes business hours (usable hours), charger information (plug shape/output performance), charge system (charge charge by visitor/member), address, telephone number, and remarks.

Refer to FIG. 12 again. A button 903 is a UI object for instructing provisional reservation of the charging station 40 . When button 903 is selected, the client program transmits a provisional reservation request for charging station 40 (hereinafter referred to as “provisional reservation request”) to server 10 . The provisional reservation processing will be described later. A link 904 is a UI object for displaying word-of-mouth information about the charging station 40 . When the link 904 is selected, the client program sends to the server 10 a request for word-of-mouth information on the charging station 40 (hereinafter referred to as a “word-of-mouth request”). The word-of-mouth information refers to evaluations (comments) by other users who have used the charging station 40 . A button 905 is a UI object for displaying the past congestion status of the charging station 40 . When the button 905 is selected, the client program sends a request to send the past congestion status of the charging station 40 to the server 10 (hereinafter referred to as “past information request”). A window 906 is a UI object for displaying an image showing the current or most recent state of the charging station 40 . A button 907 is a UI object for displaying surrounding facilities of the charging station 40 . When the button 907 is selected, the client program requests the server 10 to transmit the information on the surrounding facilities of the charging station 40 (hereinafter referred to as "peripheral information request").

The detailed operation of the server 10 when the link 904, button 905, and button 907 are selected will not be described, but the server program of the server 10 acquires the requested information from a database or other server device. , generate screen data to display the acquired information. The server 10 transmits the generated screen data to the user terminal 20 .

2-2. Provisional Reservation FIG. 14 is a sequence chart illustrating provisional reservation processing. This sequence is started when the "go here" link in FIG. 9 or 12 is selected. In step S<b>301 , the client program transmits a provisional reservation request to the server 10 . The provisional reservation request includes, for example, the identification information of the user terminal 20, the identification information of the charging station 40 to be provisionally reserved, and the current position of the target electric vehicle. The storage means 11 of the server 10 stores a database for recording the status of provisional reservations (hereinafter referred to as "provisional reservation database"). Upon receiving the provisional reservation request from the user terminal 20, the server program of the server 10 registers provisional reservation information in the provisional reservation database (step S302).

FIG. 15 is a diagram illustrating a tentative reservation database. The tentative reservation database includes items of stand name, user ID (IDentification), reservation number, predicted arrival time, and required time. “User ID” is user identification information in the charging station guidance system 1 . "Reservation number" is identification information for distinguishing each reservation registration from others. For example, the data in the top row of FIG. 15 indicates that the user having "ID0001" has made a provisional reservation for the charging station 40 with the stand name "S oil store A", and the predicted arrival time is 9:00 (required time 30 minutes). Note that the provisional reservation in the present embodiment is merely an expression of intention to use the charging station 40, so the user who actually reaches the charging station 40 first can charge first. In the example of FIG. 15, the user with the user ID "ID0001" has made a reservation to charge at Store S Petroleum A first. If the user arrives at the S petroleum store A first, the user who arrives first can start charging first. Further, when the user who made a provisional reservation for charging station 40[i] further makes a provisional reservation for charging station 40[j] without going to charging station 40[i], the user's reservation for charging station 40[i] is may be revoked.

Refer to FIG. 14 again. In step S303, the server program re-predicts the charging completion time. The waiting time is used to predict the charging completion time, and the reservation status is referenced to predict the waiting time. Therefore, if the reservation status is changed, it should affect the charging completion time of the user or other users. be. In this example, the server program re-predicts the charging completion time only for the user who requested the tentative reservation.

In step S304, the server program generates a screen showing charging stations 40 that have been provisionally reserved. In step S305, the server program transmits the generated screen data to the user terminal 20 that requested the provisional reservation. In step S306, the client program of the user terminal 20 uses the received data to display a screen showing the provisionally reserved charging stations 40. FIG.

FIG. 16 is a diagram illustrating a screen showing provisionally reserved charging stations 40 . In this example, only the sub-window 92[1] corresponding to the provisionally reserved charging station 40 is displayed, and the other sub-windows displayed in FIG. 9 are not displayed. The sub-window 92[1] contains a UI object indicating that the charging station 40 is tentatively reserved (in this example, the character string "tentatively reserved").

Please refer to FIG. 6 again. At a predetermined timing, the server program repeatedly executes the processes of steps S104 to S111 for users who are active at that time. The predetermined timing is, for example, timing when a predetermined time (for example, 10 minutes) has passed since the previous prediction (step S109). That is, for each user, as long as the user is active, the processes of steps S104 to S111 are repeatedly executed at predetermined time intervals. Here, an active user means a user who satisfies an active condition. Active conditions refer to, for example, at least one of the following (1) to (3).
(1) A user who has provisionally reserved one of the charging stations 40 .
(2) A user for whom a predetermined period of time has not passed since a request (search request, detailed request, etc.) to the charging station guidance system 1 was sent to the server 10;
(3) A user for whom a predetermined period of time has not elapsed since receiving notification from the user terminal 20 that the user is active.
Note that the user terminal 20 may notify the server 10 that the user has become inactive according to the user's instruction. Upon receiving this notification, server 10 determines that the user has become inactive.

In addition, in the re-prediction in step S303 or S109, if a result that is significantly different from the previous prediction is obtained, that is, if the situation has changed significantly from the time of the previous prediction, the server program notifies the user terminal 20 to that effect. good too.

FIG. 17 is a diagram exemplifying a screen for notifying a situation change. FIG. 17 shows that when the charging station 40[1] with the stand name "S oil store A" is tentatively reserved, for example, a plurality of other users make a tentative reservation for this charging station 40[1]. , shows an example in which the charging completion time at the charging station 40[1] is significantly delayed (10:52 becomes 12:00). In this example, the character string "Situation Change!" Display emphasis is at least one of, for example, changing the color of characters before the situation change or comparing with other character strings, changing the typeface, changing the size, and giving time change (for example, blinking). performed by one.

In the example of FIG. 17, information on the alternative candidate charging station 40[2] is also displayed. Sub-window 92[2] corresponding to charging station 40[2] includes a character string "another candidate" indicating that this is an alternative candidate. The processing after displaying the screen of FIG. 17 is the same as that after displaying FIG. For example, when the user selects "go here" in subwindow 92[2], charging station 40[2] is provisionally reserved. At this time, the reservation for charging station 40[1] is cancelled.

In this embodiment, the full reservation of the charging station 40 will not be described in detail, but the charging station guidance system 1 may accept the full reservation of the charging station 40 . If a permanent reservation is registered, the other electric vehicles 30 cannot be charged at least during the time slot in which the permanent reservation is entered, so the server program predicts the waiting time in consideration of this point. Furthermore, for example, if the target charging station has a main reservation from 9:30, the other electric vehicle 30 cannot be charged for more than 15 minutes from 9:15, so the server program takes this point into consideration. can predict the waiting time.

2-3. Charging FIG. 18 is a flowchart showing processing in the server 10 during charging at the charging station 40 . Before this flow starts, the charging station 40 reads the user ID of the user who has visited the store. The user ID is provided by the charging station guidance system 1 or its operator. A user ID is recorded on a predetermined recording medium. A recording medium is, for example, a card or a smart phone. The recording medium may be one that magnetically records the user ID (for example, a plastic card with a magnetic stripe), or one that displays a figure coded with the user ID (for example, a plastic card on which a two-dimensional barcode is printed, or a two-dimensional barcode ), data recorded in a memory chip (for example, a card or smartphone having an NFC (Near Field Communication) tag), or the like. The charging stand 40 has reading means corresponding to at least one of these. When charging is started, charging stand 40 transmits the read user ID to server 10 . At this time, the charging stand 40 may update its own state (the state detected in step S501) and notify the server 10 of it.

In step S<b>401 , the server program of server 10 receives a user ID from charging station 40 . In step S402, the server program determines whether the received user ID belongs to the subscriber. That is, the server program collates the user ID with the provisional reservation database. If it is determined that the received user ID belongs to the reservation person (S402: YES), the server program proceeds to step S403. If it is determined that the read user ID is not that of the subscriber (S402: NO), the server program proceeds to step S404.

In step S403, the server program deletes the target reservation from the provisional reservation database (the database is denoted as "DB" in the figure; the same applies hereinafter). That is, the server program cancels the provisional reservation when charging is started at the charging station 40 according to the provisional reservation. Note that the target reservation refers to an unprocessed provisional reservation corresponding to the user ID received in step S401.

In step S404, the server program re-predicts the charging completion times of other subscribers. The reservation status and the state of the charging station 40 are factors that affect the prediction of the charging completion time. A reflected forecast can be provided. The server program notifies other users of the re-predicted charging completion time (step S405).

In step S406, the server program determines whether charging is complete. The charging station 40 notifies the server 10 of the charging start and charging completion. The server program determines whether charging is completed based on this notification. If it is determined that charging has been completed (S406: YES), the server program proceeds to step S407. If it is determined that charging is not completed (S406: NO), the server program waits until charging is completed.

In step S407, the server program updates the performance database. Based on the notification received from the charging station 40, the server program records the station name, operation time, and operation type in the operation record database. Note that the operating time includes the charging start time and the charging completion time, but the charging start time and the charging completion time recorded here are both measured values.

According to the present embodiment, it is possible to inform the user of the time required to reach the charging station 40, the waiting time at the charging station 40, and the charging completion time predicted in consideration of the charging time.

3. Modifications The present invention is not limited to the above-described embodiments, and various modifications are possible. Some modifications will be described below. Two or more of the following modifications may be used in combination.

The event that triggers the notification of the information about the target charging station is not limited to those exemplified in the embodiment. For example, the user selects a candidate from a plurality of charging stations 40 in advance and registers it as a "favorite" in the user terminal 20 or the server 10. FIG. When the user instructs acquisition of information on the “favorite” charging station 40 , the user terminal 20 transmits a request to acquire information on the target charging station (hereinafter referred to as “acquisition request”) to the server 10 . The server 10 notifies the information about the target charging station in response to receiving the acquisition request from the user terminal 20 . The acquisition request in this example is another example of an “information provision request” to the server 10 . In this example, the target charging station is not automatically selected by the charging station guidance system 1, but is selected by the user.

The information used to determine the accuracy of prediction of the charging completion time is not limited to those exemplified in the embodiment. For example, when the charging station guidance system 1 has a search means (not shown) for searching the charging station 40 for the user, the server program refers to the search history in this search means to determine the prediction accuracy. may be determined. For example, charging stations 40 that have been searched for a large number of times (or hits in searches) are relatively likely to be visited by users (visitors) without reservation for charging. Therefore, when determining the prediction accuracy, a calculation formula or parameter may be used that lowers the prediction accuracy for the charging station 40 with a large number of searches.

The event that triggers the cancellation of the provisional reservation registration from the provisional reservation database is not limited to the examples given in the embodiments. For example, the server program may cancel the registration of the provisional reservation when the charging station 40 is canceled from the destination by the guidance means 24 of the user terminal 20 . In this case, the user terminal 20 notifies the server 10 that the charging station 40 has been released from the destination. Alternatively, when the user terminal 20 is a smartphone or a tablet terminal, the tentative reservation registration is canceled when the execution of the client program is stopped or when the execution of the client program shifts from the foreground to the background. good too. This can be achieved, for example, by sending notifications (of being in the foreground) to the server 10 at predetermined time intervals while the client program is running in the foreground.

The event that triggers the re-prediction of the charging completion time is not limited to those exemplified in the embodiment. For example, when two or more user terminals 20 make a provisional reservation for a certain charging station 40, the server program can determine the order of the electric vehicles 30 corresponding to these two or more user terminals 20 (that charging station 40 The charging completion time may be re-estimated when the ranking of the time required to the destination or the ranking of the distance) is changed. When predicting the waiting time based on the assumption that the electric vehicle 30 that arrives at the charging station 40 first among the electric vehicles 30 that have been provisionally reserved will start charging first, the arrival time between the plurality of electric vehicles is This is because the waiting time may fluctuate greatly when the terminals are replaced.

When the charging completion time is re-estimated, the server program may narrow down the electric vehicle 30 to be re-estimated or the user terminal 20 to notify the result of the re-estimation. For example, when five users (five electric vehicles 30) have tentatively reserved a charging station 40, and the charging completion time is re-estimated by some event, the server program , the electric vehicles 30 to be re-predicted may be narrowed down according to the required time (or distance) from these five electric vehicles 30 to this charging station 40 . More specifically, even if re-prediction is performed only for a predetermined number of electric vehicles 30 (for example, the closest one) in descending order of the required time to this charging station 40 among these five electric vehicles 30 . good. Alternatively, re-prediction may be performed for all of these five electric vehicles 30, and the notification destinations of the results may be narrowed down according to the required time (or distance) from these five electric vehicles 30 to this charging station 40. . Specifically, the re-predicted results may be notified in descending order of required time (preferentially).

The UI screens shown in the embodiments are merely examples, and the UI objects and combinations thereof used in these are not limited to those shown in the embodiments. For example, the screen of FIG. 12 may not include information on the charging station 40 recommended by the charging station guidance system 1 .

The technology of the present disclosure is also applicable, for example, when using a hydrogen station, which is a facility for supplying hydrogen to a fuel cell vehicle (FCV: Fuel Cell Vehicle or FCEV: Fuel Cell Electric Vehicle). At the hydrogen station, it may take a long time to start replenishing hydrogen due to pressure accumulation. However, according to the technique of the present disclosure, the waiting time is also used to predict the completion time, so the user of the fuel cell vehicle can easily grasp the predicted time when the hydrogen replenishment will be completed.

The relationship between functions and hardware in the charging station guidance system 1 is not limited to those illustrated in the embodiment. At least some of the functions implemented in the server 10 in the embodiments may be implemented in the user terminal 20, charging station 40, or other device. Further, the hardware configurations of the server 10, the user terminal 20, and the charging stand 40 are not limited to those illustrated in the embodiments, and any hardware may be used for each of these devices as long as the required functions are implemented. may have a hardware configuration.

DESCRIPTION OF SYMBOLS 1... Charging station guidance system 10... Server 11... Storage means 12... Reception means 13... Acquisition means 14... Prediction means 15... Judgment means 16... Notification means 17... Management means 20... User terminal , 21... reception means, 22... transmission means, 23... reception means, 24... guidance means, 30... electric vehicle, 40... charging station, 41... charging means, 42... storage means, 43... communication means, 44... reception means , 81... prediction means, 82... prediction means, 83... prediction means, 91... dots, 92... sub-window, 93... icon, 101... CPU, 102... memory, 103... storage, 104... communication IF, 131... acquisition means , 132... Acquisition means, 133... Acquisition means, 201... CPU, 202... Memory, 203... Storage, 204... Communication IF, 205... Touch screen, 901... Display area, 902... Button, 903... Button, 904... Link, 905...Button, 906...Window, 907...Button

Claims (18)

a first obtaining means for obtaining a time required for a target electric vehicle corresponding to a target user terminal among the plurality of user terminals to reach a target charging station selected from among the plurality of charging stations;
a second obtaining means for obtaining a waiting time at the target charging station;
a third obtaining means for obtaining a charging time required for charging the target electric vehicle;
prediction means for predicting completion time of charging of the target electric vehicle using the required time, the waiting time, and the charging time;
a notification means for notifying the target user terminal of the completion time ;
determination means for determining the prediction accuracy of the completion time;
has
The notification means notifies information indicating prediction accuracy of the completion time together with the completion time.
server. 2. The server according to claim 1 , wherein said determination means determines said prediction accuracy by referring to an operation record of said target charging station for a predetermined period in the past. 3. The server according to claim 2, wherein the determination means determines the prediction accuracy by referring to the number of users who have registered in the server that they will charge at the target charging station. storage means for storing a database relating to the plurality of charging stations;
search means for searching for a charging station that meets the search request from the plurality of charging stations in response to a search request from an external device;
4. The server according to any one of claims 1 to 3 , wherein said determination means determines said prediction accuracy by referring to a search history in said search means. 2. The determination means determines the prediction accuracy by referring to at least one of the location conditions of the target charging station, the number of other nearby charging stations, the weather, the season, the time of day, and the day of the week. 5. The server according to any one of Claims 4 . a management means for managing registration from each of the plurality of user terminals to the effect that the electric vehicle corresponding to the user terminal will be charged at a charging station selected from among the plurality of charging stations;
6. The server according to any one of claims 1 to 5 , wherein said second obtaining means obtains said waiting time calculated according to said registration status. 7. The server according to claim 6 , wherein said management means cancels said registration with a predetermined event as a trigger. The server according to claim 7 , wherein the predetermined event is an event that charging of the target electric vehicle has started. The target user terminal has guidance means for guiding a route to the target charging station,
8. The server according to claim 7 , wherein the predetermined event is an event that the guidance means receives a notification from the target user terminal that the target charging station has been released from the destination. The server according to any one of claims 1 to 5 , wherein the prediction means re-predicts the completion time with a predetermined event as a trigger. The server according to Claim 10 , wherein the predetermined event is an event that another electric vehicle has started charging at the target charging station. a management means for managing registration from each of the plurality of user terminals to the effect that the electric vehicle corresponding to the user terminal will be charged at a charging station selected from among the plurality of charging stations;
When two or more user terminals are registered to charge at the target charging station, the predetermined event is an electric vehicle corresponding to the two or more user terminals until the target charging station. The server according to claim 10 , which is an event that the order of required time or distance has changed. a management means for managing registration from each of the plurality of user terminals to the effect that the electric vehicle corresponding to the user terminal will be charged at a charging station selected from among the plurality of charging stations;
When two or more user terminals are registered to be charged at the target charging station, and the prediction means re-predicts the completion time, the notifying means may notify the two or more user terminals. 12. The server according to claim 10 or 11 , wherein the re-predicted completion time is preferentially notified to a user terminal corresponding to an electric vehicle whose required time or distance to the target charging station is short. a first obtaining means for obtaining a time required for a target electric vehicle corresponding to a target user terminal among the plurality of user terminals to reach a target charging station selected from among the plurality of charging stations;
a second obtaining means for obtaining a waiting time at the target charging station;
a third obtaining means for obtaining a charging time required for charging the target electric vehicle;
prediction means for predicting completion time of charging of the target electric vehicle using the required time, the waiting time, and the charging time;
a notification means for notifying the target user terminal of the completion time ;
determination means for determining the prediction accuracy of the completion time;
has
The notification means notifies information indicating prediction accuracy of the completion time together with the completion time.
Charging station guidance system. the computer
acquiring a time required for a target electric vehicle corresponding to the target user terminal among the plurality of user terminals to reach a target charging station selected from among the plurality of charging stations;
obtaining a waiting time at the target charging station;
obtaining a charging time required to charge the target electric vehicle;
predicting a completion time when charging of the target electric vehicle is completed using the required time, the waiting time, and the charging time;
notifying the target user terminal of the completion time ;
determining the prediction accuracy of the completion time;
A charging station guidance method for executing
In the notifying step, notifying information indicating the prediction accuracy of the completion time together with the completion time
Charging station guidance method. to the computer,
acquiring a time required for a target electric vehicle corresponding to the target user terminal among the plurality of user terminals to reach a target charging station selected from among the plurality of charging stations;
obtaining a waiting time at the target charging station;
obtaining a charging time required to charge the target electric vehicle;
predicting a completion time when charging of the target electric vehicle is completed using the required time, the waiting time, and the charging time;
notifying the target user terminal of the completion time ;
determining the prediction accuracy of the completion time;
A program for executing
In the notifying step, information indicating the prediction accuracy of the completion time is notified together with the completion time.
program. to the computer,
a first acquiring means for acquiring a time required for a target electric vehicle corresponding to a target user terminal among a plurality of user terminals to reach a target charging station selected from among a plurality of charging stations; second acquisition means for acquiring a waiting time; third acquisition means for acquiring a charging time required for charging the target electric vehicle; and charging of the target electric vehicle using the required time, the waiting time, and the charging time. Prediction means for predicting a completion time, notification means for notifying the target user terminal of the completion time , and determination means for determining the prediction accuracy of the completion time , wherein the notification means receives the completion time together with the completion time. , a step of transmitting a charging station information provision request to a server that notifies information indicating the prediction accuracy of the completion time ;
receiving a notification including the completion time at the target charging station in response to the information provision request;
A program for causing a step of displaying information including said completion time. a first acquiring means for acquiring the time required for the target fuel cell vehicle corresponding to the target user terminal among the plurality of user terminals to reach the target hydrogen station selected from among the plurality of hydrogen stations;
a second acquiring means for acquiring a waiting time at the target hydrogen station;
a third acquiring means for acquiring a replenishment time required for replenishing hydrogen in the target fuel cell vehicle;
prediction means for predicting completion time for completion of replenishment of the target fuel cell vehicle using the required time, the waiting time, and the replenishment time;
a notification means for notifying the target user terminal of the completion time ;
determination means for determining the prediction accuracy of the completion time;
has
The notification means notifies information indicating prediction accuracy of the completion time together with the completion time.
server.

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