(19)
(11)EP 2 927 888 B1

(12)EUROPEAN PATENT SPECIFICATION

(45)Mention of the grant of the patent:
03.08.2022 Bulletin 2022/31

(21)Application number: 13858263.0

(22)Date of filing:  28.11.2013
(51)International Patent Classification (IPC): 
B60L 53/14(2019.01)
B60L 58/12(2019.01)
G08G 1/01(2006.01)
G08G 1/065(2006.01)
H02J 7/00(2006.01)
B60L 53/60(2019.01)
B60L 58/13(2019.01)
G08G 1/0967(2006.01)
G06Q 10/10(2012.01)
(52)Cooperative Patent Classification (CPC):
H02J 7/00; G08G 1/0112; G08G 1/0129; G08G 1/0141; G08G 1/096716; G08G 1/096741; G08G 1/096775; B60L 2240/12; B60L 2240/622; B60L 2240/68; B60L 2240/72; B60L 2240/80; B60L 2250/16; B60L 2260/44; B60L 2260/50; B60L 2260/58; Y02T 90/16; Y02T 10/7072; G08G 1/065; G06Q 10/10; B60L 58/13; B60L 53/66; Y02T 10/70; Y02T 10/72; Y02T 90/12
(86)International application number:
PCT/JP2013/082035
(87)International publication number:
WO 2014/084305 (05.06.2014 Gazette  2014/23)

(54)

CHARGE MANAGEMENT DEVICE

LADEMANAGEMENTVORRICHTUNG

DISPOSITIF DE GESTION DE CHARGE


(84)Designated Contracting States:
AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

(30)Priority: 30.11.2012 JP 2012263385

(43)Date of publication of application:
07.10.2015 Bulletin 2015/41

(73)Proprietors:
  • Kabushiki Kaisha Toshiba
    Minato-ku, Tokyo 105-8001 (JP)
  • Toshiba Solutions Corporation
    Kawasaki-shi, Kanagawa 212-8585 (JP)

(72)Inventors:
  • KANO, Makoto
    Kawasaki-shi, Kanagawa 2128585 (JP)
  • SUZUKI, Hiroyuki
    Kawasaki-shi, Kanagawa 2128585 (JP)
  • YAMAMOTO, Junichi
    Kawasaki-shi, Kanagawa 2128585 (JP)
  • SHIMADA, Tsuyoshi
    Kawasaki-shi, Kanagawa 2128585 (JP)
  • MATSUI, Kiyoshi
    Kawasaki-shi, Kanagawa 2128585 (JP)
  • NAKAMURA, Junichi
    Tokyo 105-8001 (JP)

(74)Representative: Hoffmann Eitle 
Patent- und Rechtsanwälte PartmbB Arabellastraße 30
81925 München
81925 München (DE)


(56)References cited: : 
WO-A1-2011/102515
JP-A- 2011 013 893
JP-A- 2011 214 930
US-A1- 2010 106 401
US-A1- 2012 268 061
WO-A1-2012/114381
JP-A- 2011 164 050
JP-A- 2011 238 182
US-A1- 2012 245 750
  
     
    Remarks:
    The file contains technical information submitted after the application was filed and not included in this specification
     
    Note: Within nine months from the publication of the mention of the grant of the European patent, any person may give notice to the European Patent Office of opposition to the European patent granted. Notice of opposition shall be filed in a written reasoned statement. It shall not be deemed to have been filed until the opposition fee has been paid. (Art. 99(1) European Patent Convention).


    Description

    Technical Field



    [0001] Embodiments of the present invention relate to an apparatus for providing charge recommendation information.

    Background Art



    [0002] At present, since the diffusion rate of electric cars is lower than the diffusion rate of gasoline-powered cars, it rarely happens that charge stations (CS: Charge Station), which are facilities for charging electric cars, are crowded.

    [0003] However, in the future, if electric cars will gain in popularity, the congestion at charge stations will pose a serious problem, like traffic congestion.

    [0004] Thus, in order to avoid congestion occurring when electric cars come to some charge stations, it is necessary to inform drivers of charge recommendation information which indicates which charge station can provide smooth charging, thereby leveling the congestion at charge stations.

    [0005] As a technique for informing drivers of charge recommendation information, for example, there is known a technique wherein the current positions and residual battery capacities of all electric cars are measured, and then charge recommendation information is generated based on the measured results, and the drivers are informed of the generated charge recommendation information.

    [0006] Further background art is provided in US 2012/0268061 A1, specifically a system and a method for optimizing and managing a load in an electrical grid. The method includes receiving an event notification associated with a mobile device requiring a charge and determining charging station information of at least one charging station in an electrical grid based on the event notification, the at least one charging station operable to charge the mobile device. The charging station information of the at least one charging station is sent to a user of the mobile device. Document US2012245750 A1 discloses a system for providing a charging scheduling system wherein the system determines the predicted number of EVs for a time range, obtains the number of EVs waiting at a charging station, calculates the total number of EVs ,calculates total power or energy available from the grid and provides the info to the driver in form of schedule.

    Citation List


    Patent Literature



    [0007] 

    Patent document 1: Jpn. Pat. Appln. KOKAI Publication No. 2011-191109

    Patent document 2: Jpn. Pat. Appln. KOKAI Publication No. 2012-3391

    Patent document 3: Jpn. Pat. Appln. KOKAI Publication No. 2012-48286


    Summary of Invention



    [0008] However, in the above-described technique, it is necessary to measure the current positions and residual battery capacities of all electric cars running, for example, on a toll road or the like, and there is such a problem that this is difficult to realize at present.

    [0009] Embodiments described herein provide an apparatus which can inform a driver of charge recommendation information, even without measuring the current positions and residual battery capacities of all electric cars running on a toll road or the like.

    [0010] The present invention provides an apparatus for providing charge recommendation information according to Claim 1. Optional features are set out in the remaining claims.

    Brief Description of Drawings



    [0011] 

    FIG. 1 is a schematic view illustrating a configuration example of a charge management apparatus according to a first embodiment.

    FIG. 2 is a schematic view illustrating an example of traffic demand data.

    FIG. 3 is a schematic view illustrating an example of SoC distribution data.

    FIG. 4 is a schematic view illustrating an example of link information.

    FIG. 5 is a schematic view illustrating an example of CS information.

    FIG. 6 is a schematic view illustrating an example of ITS spot/electronic bulletin board information.

    FIG. 7 is a schematic view illustrating an example of vehicle attribute information.

    FIG. 8 is a schematic view illustrating an example of a simulation model which is used by a charge station condition estimation unit according to the first embodiment.

    FIG. 9 is a schematic view illustrating an example of a notification of charge recommendation information.

    FIG. 10 is a schematic view illustrating an example of estimation result information.

    FIG. 11 is a schematic view illustrating an example of determination result information.

    FIG. 12 is a schematic view illustrating an example of charge recommendation information.

    FIG. 13 is a flowchart illustrating an operation example of the charge management apparatus according to the first embodiment.

    FIG. 14 is a schematic view illustrating an example of a simulation result by the charge management apparatus according to the first embodiment.

    FIG. 15 is a schematic view illustrating another example of the simulation result by the charge management apparatus according to the first embodiment.

    FIG. 16 is a schematic view illustrating still another example of the simulation result by the charge management apparatus according to the first embodiment.

    FIG. 17 is a schematic view illustrating a configuration example of a charge management apparatus according to a second embodiment.

    FIG. 18 is a schematic view illustrating an example of planned power supply amount information.

    FIG. 19 is a schematic view illustrating an example of number-of-available chargers information.

    FIG. 20 is a flowchart illustrating an operation example of the charge management apparatus according to this embodiment.

    FIG. 21 is a schematic view illustrating a configuration example of a charge management apparatus according to a third embodiment.

    FIG. 22 is a flowchart illustrating an operation example of the charge management apparatus according to the third embodiment.


    Description of Embodiments



    [0012] A charge management apparatus described herein includes input means, first estimation means, determination means, generation means, second estimation means, and output means.

    [0013] The input means accepts an input of traffic demand data indicative of a number of vehicles entering/exiting a plurality of interchanges of a toll road.

    [0014] The first estimation means executes simulation by using the traffic demand data the input of which was accepted, and estimates charge wait times at a plurality of charge stations provided midway along the toll road.

    [0015] The determination means compares the estimated charge wait times at the respective charge stations, and determines whether a desired condition is satisfied.

    [0016] The generation means generates charge recommendation information indicative of a charge station capable of smooth charging, if a result of determination by the determination means indicates that the desired condition is not satisfied.

    [0017] The second estimation means executes simulation by using the generated charge recommendation information in addition to the traffic demand data the input of which was accepted, and estimates once again the charge wait times at the respective charge stations.

    [0018] The output means outputs the generated charge recommendation information to an external terminal if a result of determination by the determination means indicates that the desired condition is satisfied, as a result of repeatedly executing processes by the determination means, the generation means and the second estimation means.

    [First Embodiment]



    [0019] FIG. 1 is a schematic view illustrating a configuration example of a charge management apparatus according to a first embodiment. FIG. 2 to FIG. 7, and FIG. 9 to FIG. 12 are schematic views illustrating examples of various pieces of information, which are used by the charge management apparatus according to this embodiment. FIG. 8 is a schematic view illustrating an example of a simulation model which is used by the charge management apparatus according to this embodiment. A charge management apparatus 1 illustrated in FIG. 1 includes a traffic demand data input unit 11, a charge station condition estimation unit (hereinafter referred to as "CS condition estimation unit") 12, a condition determination unit 13, a charge recommendation information generation unit 14, and a charge recommendation information output unit 15. Hereinafter, the functions of the respective components 11 to 15, which constitute the charge management apparatus 1, will be described in detail.

    [0020] Upon accepting an input of traffic demand data and SoC (State of Charge) distribution data, which are transmitted from an external terminal (not shown), the traffic demand data input unit 11 transmits to the CS condition estimation unit 12 the traffic demand data and SoC distribution data, the input of which was accepted.

    [0021] As illustrated in FIG. 2, traffic demand data D1 is data indicative of numbers of vehicles exiting/entering a plurality of interchanges (hereinafter referred to as "ICs") provided on a toll road such as a highway. In FIG. 2, an example of the traffic demand data D1, which is indicative of the numbers of exiting/entering vehicles for 24 hours at respective ICs of a certain highway, is illustrated as an OD (Origin-Destination) table. However, the format of traffic demand data is not limited to this example, and an arbitrary format may be adopted if the number of exiting/entering vehicles per unit time at an arbitrary location is indicated. Incidentally, the number of vehicles indicated by the traffic demand data D1 is the sum of the numbers of electric cars and the number of other kinds of cars (e.g. gasoline-powered cars and hybrid cars).

    [0022] SoC is indicative of the ratio of a residual battery capacity to a maximum charge capacity of a battery which is mounted on an electric car. As illustrated in FIG. 3, SoC distribution data D2 is data showing, by a probability distribution, the distribution of SoC of electric cars coming in from each IC.

    [0023] The traffic demand data D1 and SoC distribution data D2 are data which was estimated based on past data. When simulation is executed by the CS condition estimation unit 12 (to be described later), the traffic demand data input unit 11 can properly change the data, the input of which is accepted, according to days (e.g. weekday, holiday, or special day) on which the congestion condition of each CS is to be estimated. Specifically, when the congestion condition relating to holidays is to be estimated, the traffic demand data input unit 11 may accept the input of only the traffic demand data and SoC distribution data relating to holidays.

    [0024] Upon accepting an input of the traffic demand data and SoC distribution data, which were transmitted from the traffic demand data input unit 11, and charge recommendation information which is transmitted from the charge recommendation information generation unit 14 (to be described later), the CS condition estimation unit 12 executes simulation by using at least the traffic demand data and SoC distribution data, the input of which was accepted, and estimates the congestion condition of plural CSs provided at respective locations on the toll road. However, if charge recommendation information has been generated by the charge recommendation information generation unit 14 and the CS condition estimation unit 12 has accepted also the input of this charge recommendation information, the CS condition estimation unit 12 executes simulation by using this charge recommendation information in addition to the traffic demand data and SoC distribution data. In addition, if the congestion condition of each CS is estimated, the CS condition estimation unit 12 transmits estimation result information, which is indicative of the result of this estimation, to the condition determination unit 13.

    [0025] In the meantime, for example, as illustrated in FIG. 4 to FIG. 6, in order to execute simulation, link information, CS information and ITS spot/electronic bulletin board information is preset in the CS condition estimation unit 12. These pieces of information are information for forming a virtual toll road which is applied at the time of executing simulation. Incidentally, in the present embodiment, various pieces of information are set, with a single-path highway being assumed.

    [0026] For example, as illustrated in FIG. 4, link information D3 is information in which a link name, a downstream link name, a link length, an average electricity efficiency, and an average speed are associated. The link name indicates the name of a block (hereinafter referred to as "link") from one IC to a neighboring IC. The downstream link name indicates the name of a (downstream) link neighboring a link designated by the associated link name. The link length indicates the distance of a link designated by the associated link name. The average electricity efficiency indicates an average distance over which a vehicle running on a link designated by the associated link name can run by consuming electric power of 1 kWh, when simulation is executed by the CS condition estimation unit 12. The average speed indicates an average distance over which a vehicle running on a link designated by the associated link name can run per second, when simulation is executed by the CS condition estimation unit 12.

    [0027] For example, as illustrated in FIG. 5, CS information D4 is information in which a charge station name, an existing link name, a distance from a starting point, the number of chargers, and a charge speed are associated. The charge station name indicates the name of a CS provided at each location on a toll road. The existing link name indicates the name of a link on which a CS designated by the associated charge station name is provided. The distance from a starting point indicates a distance from a starting point of a link designated by the associated existing link name to a CS designated by the associated charge station name. The number of chargers indicates the number of chargers provided at a CS designated by the associated charge station name. The charge speed indicates a power amount with which a charger can charge a vehicle per second at the CS designated by the associated charge station name.

    [0028] For example, as illustrated in FIG. 6, ITS spot/electronic bulletin board information D5 is information in which an ITS spot name/electronic bulletin board name, an existing link name, a distance from a starting point, and an associated charge station name are associated. The ITS spot name/electronic bulletin board name indicates the name of an ITS spot or an electronic bulletin board. The existing link name indicates the name of a link on which an ITS spot or electronic bulletin board designated by the associated ITS spot/electronic bulletin board name is provided. The distance from a starting point indicates a distance from a starting point of a link designated by the associated existing link name to an ITS spot or electronic bulletin board designated by the ITS spot/electronic bulletin board name. The associated charge station name indicates the name of a CS, the congestion condition of which can be notified on the ITS spot or electronic bulletin board designated by the associated ITS spot/electronic bulletin board name.

    [0029] A description is now given of the simulation which is executed by the CS condition estimation unit 12. Incidentally, the simulation is composed of two stages, namely a preprocess stage and an execution stage.

    [0030] To begin with, the preprocess stage is described.

    [0031] The CS condition estimation unit 12 generates, based on traffic demand data, virtual vehicles including electric cars and other kinds of vehicles. For example, if it is assumed that the CS condition estimation unit 12 has accepted the input of the traffic demand data D1 illustrated in FIG. 2, the CS condition estimation unit 12 generates, according to the traffic demand data D1 the input of which was accepted, virtual vehicles, such as 160 virtual vehicles entering IC1 and exiting IC2, 160 virtual vehicles entering IC1 and exiting IC3, and 150 virtual vehicles entering IC2 and exiting IC3. Incidentally, it is assumed that the ratio between electric cars and other kinds of vehicles is set according to predetermined setting, and this setting can arbitrarily be made by a user.

    [0032] At this time, the CS condition estimation unit 12 imparts, to each of the generated virtual vehicles, vehicle attribute information indicative of the attribute of the virtual vehicle. For example, as illustrated in FIG. 7, vehicle attribute information D6 is information in which a vehicle ID, a departure time, an entrance IC name, an exit IC name and an SoC default value are associated. The vehicle ID is identification information for identifying a virtual vehicle, and is randomly set at a time of generating the virtual vehicle. The departure time is indicative of a time at which a virtual vehicle departs from an exit IC, and is uniquely set at a time of generating the virtual vehicle, like the vehicle ID (however, since the departure time is set according to traffic demand data of each unit time, the departure time is randomly set within the range of the unit time). The entrance IC name is indicative of the name of an IC which a virtual vehicle enters, and is set according to the traffic demand data which was used at the time of generating the virtual vehicle. The exit IC name is indicative of the name of an IC which a virtual vehicle exits, and is set, like the entrance IC name, according to the traffic demand data which was used at the time of generating the virtual vehicle. The SoC default value is indicative of an SoC at a time when a virtual vehicle departs from the entrance IC, and is randomly set according to SoC distribution data the input of which was accepted (however, the SoC default values of virtual vehicles of any kind, except electric cars, are all set at "0").

    [0033] Next, a description is given of the execution stage of the simulation which is executed by the CS condition estimation unit 12. Here, the CS condition estimation unit 12 executes simulation by using a driver model 121, a vehicle model 122, a battery model 123, a CS model 124 and an ITS spot/electronic bulletin board model 125, as illustrated in FIG. 8.

    [0034] The driver model 121 is a model which is formed by modeling a driver who drives a virtual vehicle. Upon accepting an input of various pieces of information from the vehicle model 122, battery model 123 and ITS spot/electronic bulletin board model 125, the driver model 121 executes a driving path selection process, a CS selection process and a vehicle state selection process, based on the various pieces of information the input of which was accepted.

    [0035] For example, based on position/speed information transmitted from the vehicle model 122, SoC information transmitted from the battery model 123 and charge recommendation information transmitted from the ITS spot/electronic bulletin board model 125, the driver model 121 executes a selection process of selecting a farthest CS from the present position among the CSs at which the virtual vehicle can arrive. Incidentally, in the present embodiment, although the driver model 121 selects a farthest CS from the present position among the CSs at which the virtual vehicle can arrive, the embodiment is not limited to this example. For example, even when the virtual vehicle can arrive at a CS, if the SoC decreases to less than 20%, there is a concern that the residual battery capacity becomes deficient and driving becomes impossible. Thus, such a method may be adopted that, among the CSs at which the virtual vehicle can arrive within the range of 20% or more of SoC, a farthest CS from the present position is selected.

    [0036] In addition, based on position information of a vehicle, which is transmitted from the vehicle model 122, the driver model 121 executes a selection process of selecting the state of the vehicle, which is, in this example, one of three states, namely, "driving", "charging" and "waiting for charge". For example, until the vehicle arrives at a selected CS, the driver model 121 selects "driving" as the state of the vehicle. If the vehicle arrives at the selected CS and starts charge, the driver model 121 selects "charging" as the state of the vehicle. If the vehicle has arrived at the selected CS but the chargers are occupied by other virtual vehicles, the driver model 121 selects "waiting for charge" as the state of the vehicle. Incidentally, if the driver model 121 selects one of the three vehicle states, the driver model 121 sends state information indicative of the selected vehicle state to the vehicle model 122.

    [0037] The vehicle model 122 is a virtual vehicle itself. Upon accepting an input of the state information from the driver model 121, the vehicle model 122 executes an update process of updating the position and speed of the virtual vehicle, according to a vehicle dynamics equation, if the state of the vehicle, which is indicated by the state information the input of which was accepted, is "driving". Incidentally, if the vehicle model 122 updates the position and speed of the virtual vehicle, the vehicle model 122 transmits the position/speed information, which is indicative of the position and speed of the virtual vehicle after the update, to the driver model 121 and battery model 123, and transfers the state information to the battery model 123.

    [0038] The battery model 123 is a model which is formed by modeling a battery mounted on the virtual vehicle. Upon accepting an input of the position/speed information and state information from the vehicle model 122 and charge speed information from the CS model 124, the battery model 123 executes an update process of updating the residual battery capacity in accordance with the vehicle state indicated by the state information the input of which was accepted. Specifically, when the vehicle state indicated by the state information, the input of which was accepted, is "driving", the battery model 123 calculates a power consumption amount from the position/speed information the input of which was accepted, and subtracts the power consumption amount from the SoC default value in the vehicle attribute information which was imparted to the virtual vehicle, thereby calculating (updating) the residual battery capacity. In addition, when the vehicle state indicated by the state information, the input of which was accepted, is "charging", the battery model 123 calculates (updates) the residual battery capacity in accordance with the charge speed indicated by the charge speed information the input of which was accepted. Incidentally, upon updating the residual battery capacity, the battery model 123 transmits SoC information, which is indicative of the SoC (i.e. residual battery capacity) after the update, to the driver model 121.

    [0039] The CS model 124 is a model which is formed by modeling the CS provided at each location of a toll road. The CS model 124 transmits charge speed information indicative of the charge speed to the battery model 123 in accordance with the CS information D4 which is preset in the CS condition estimation unit 12.

    [0040] The ITS spot/electronic bulletin board model 125 is a model which is formed by modeling an ITS spot and an electronic bulletin board that are provided at each location on the toll road. The ITS spot/electronic bulletin board model 125 transmits charge recommendation information to the driver model 121 when the virtual vehicle passes nearby (however, only when there is an input of charge recommendation information from the charge recommendation information generation unit 14). FIG. 9 is a schematic view illustrating a display example of charge recommendation information which is displayed on the ITS spot and electronic bulletin board. FIG. 9 illustrates not a charge wait time at a time when the virtual vehicle has passed by the vicinity of the ITS spot or electronic bulletin board, but a charge wait time at a time when the virtual vehicle has arrived at a destination CS.

    [0041] When a downstream CS, which is indicated by the charge recommendation information transmitted from the ITS spot/electronic bulletin board model 125, agrees with a CS selected by the selection process of CS, the driver model 121 changes a CS, which is visited at a desired ratio (e.g. a probability of 30%), to a CS with a less charge wait time, that is, executes the selection process of CS once again.

    [0042] In the above manner, the CS condition estimation unit 12 causes the virtual vehicle, which was generated in the preprocess stage, to run on the virtual toll road, by using the respective models 121 to 125, and simulates the congestion condition of each CS. Then, the CS condition estimation unit 12 transmits estimation result information, which is indicative of an estimation result of the congestion condition of each CS, to the condition determination unit 13.

    [0043] For example, as illustrated in FIG. 10, estimation result information D7 is information indicative of charge wait times at respective CSs at each unit time. The charge wait time is indicative of a wait time from arrival of the virtual vehicle at a CS to the start of charge. For example, in FIG. 10, it is indicated that a virtual vehicle, which departs from CS1 at 8:00, waits for 500 seconds until the start of charge, when the virtual vehicle arrives at CS3. Here, the time instant of each unit time illustrated in FIG. 10 is a time instant when the virtual vehicle passes by CS1 that is a reference. As regards CS1, a wait time of the virtual vehicle, which has arrived at this time instant, is indicated. Then, as regards each of the other charge stations, a wait time in a case in which the vehicle, which departed from CS1 at this time instant, has run at an average speed and arrived at the charge station, is indicated.

    [0044] Upon accepting an input of the estimation result information transmitted from the CS condition estimation unit 12, the condition determination unit 13 compares, at each unit time, the congestion conditions of the respective CSs indicated by the estimation result information the input of which was accepted, determines whether a desired condition is satisfied or not, and transmits the result of this determination and determination result information to the charge recommendation information generation unit 14.

    [0045] As the desired condition, the following conditions are given. If any one of these conditions is satisfied, it is assumed that the desired condition is satisfied.
    1. (1) At all unit times of the estimation result information, when the charge wait times of all neighboring CSs are compared, a value, which is calculated by subtracting a charge wait time of an upstream CS from a charge wait time of a downstream CS, is a threshold value or less.
    2. (2) The number of times of adjustment of charge recommendation information, that is, the number of times of repetition of a series of processes of the output of estimation result information by the CS condition estimation unit 12, the output of determination result information by the condition determination unit 13 and the output of charge recommendation information to the CS condition estimation unit 12 by the charge recommendation information generation unit 14, is a predetermined number or more.
    3. (3) No new charge recommendation information is generated, that is, the content of the determination result, which is indicated by the determination result information the input of which was accepted, is identical to the content of the determination result information, the input of which was already accepted and with respect to which the charge recommendation information relating to the determination result was generated.


    [0046] For example, as illustrated in FIG. 11, determination result information D8 is information which indicates "OK" if the above condition is satisfied and indicates "NG" if the above condition is not satisfied, as the result of determination by the condition determination unit 13. For example, in FIG. 11, the difference between the charge wait time "100 seconds" at a time when the virtual vehicle, which departed from CS1 at 8:10, has arrived at CS2, and the charge wait time "1800 seconds" at a time when the virtual vehicle, which departed from CS1 at 8:10, has arrived at CS3, is a threshold value or more (it is assumed, however, that the threshold value is set at "1200 seconds" in this case). Thus, the condition determination unit 13 determines that the above condition is not satisfied, and sets "NG" for the related part in the determination result information that is transmitted by the condition determination unit 13.

    [0047] In the meantime, in this embodiment, it is assumed that the condition determination unit 13 operates according to the above condition. The above condition is a condition which was set on the assumption that a virtual vehicle, which is scheduled to perform charge at a downstream CS, is guided to an upstream CS, because if a virtual vehicle, which is scheduled to perform charge at an upstream CS, is guided to a downstream CS, deficiency in electricity may possibly occur in this virtual vehicle. However, when a virtual vehicle, which is scheduled to perform charge at a crowded CS, is to be guided to an upstream or downstream CS, such a condition may be set that "when charge wait times of neighboring CSs are compared at all unit times, the difference between the charge wait times is a threshold value or less."

    [0048] Upon accepting an input of the determination result and determination result information D8 which were transmitted from the condition determination unit 13, the charge recommendation information generation unit 14 generates, if the determination result the input of which was accepted fails to meet a desired condition, charge recommendation information relating to a CS which fails to meet the desired condition, and sends this charge recommendation information to the CS condition estimation unit 12.

    [0049] However, if the charge recommendation information generation unit 14 has already generated charge recommendation information and transmitted this charge recommendation information to the CS condition estimation unit 12, the charge recommendation information generation unit 14 transmits to the CS condition estimation unit 12 a charge recommendation information set in which this generated charge recommendation information is added to at least one piece of previously transmitted charge recommendation information.

    [0050] In addition, if the determination result the input of which was accepted satisfies the desired condition, the charge recommendation information generation unit 14 transmits to the charge recommendation information output unit 15 one of the pieces of information included in the charge recommendation information set which was transmitted to the CS condition estimation unit 12. Incidentally, which charge recommendation information is to be transmitted to the charge recommendation information output unit 15 is determined according to predetermined setting, and the user can arbitrarily make this setting. Specifically, one example is that "the charge recommendation information, which was last output to the CS condition estimation unit 12, is sent to the charge recommendation information output unit 15."

    [0051] For example, as illustrated in FIG. 12, charge recommendation information D9 is information which is notified to a vehicle running on a toll road by the ITS spot or electronic bulletin board provided at each location of the toll road. In this information, an ITS spot name/electronic bulletin board name, a presentation start time instant, a presentation end time instant, and charge wait times at an upstream CS and a downstream CS are associated.

    [0052] The ITS spot name/electronic bulletin board name designates the name of an ITS spot or an electronic bulletin board. The presentation start time instant designates a time instant at which the presentation of the charge recommendation information is started on the ITS spot or electronic bulletin board indicated by the associated ITS spot name/electronic bulletin board name. The presentation end time instant designates a time instant at which the presentation of the charge recommendation information is ended on the ITS spot or electronic bulletin board indicated by the associated ITS spot name/electronic bulletin board name. The charge wait times at an upstream CS and a downstream CS designate charge wait times at the respective CSs, and are values according to the estimation result information used by the condition determination unit 13.

    [0053] Upon accepting an input of the charge recommendation information that was transmitted from the charge recommendation information generation unit 14, the charge recommendation information output unit 15 outputs the charge recommendation information, the input of which was accepted, to an external terminal (e.g. the ITS spot or electronic bulletin board provided at each location on the toll road).

    [0054] Next, referring to a flowchart of FIG. 13, a description is given of an example of the operation of the above-described charge management apparatus 1.

    [0055] To start with, upon accepting an input of the traffic demand data and SoC distribution data which were transmitted from the external terminal, the traffic demand data input unit 11 transmits the traffic demand data and SoC distribution data, the input of which was accepted, to the CS condition estimation unit 12 (step S1).

    [0056] Subsequently, upon accepting an input of the traffic demand data and SoC distribution data which were transmitted from the traffic demand data input unit 11, the CS condition estimation unit 12 executes simulation by using at least the traffic demand data and SoC distribution data the input of which was accepted, estimates the congestion condition of the respective CSs, and transmits estimation result information, which is indicative of the result of this estimation, to the condition determination unit 13 (step S2).

    [0057] Next, upon accepting an input of the estimation result information transmitted from the CS condition estimation unit 12, the condition determination unit 13 compares, at each unit time, the congestion conditions of the respective CSs indicated by the estimation result information the input of which was accepted, and determines whether a desired condition is satisfied or not (step S3).

    [0058] If the determination result by the process of step S3 indicates "No" (No in step S3), the charge recommendation information generation unit 14 generates charge recommendation information relating to a CS which fails to meet the desired condition, and sends this generated charge recommendation information to the CS condition estimation unit 12 (step S4), and then returns to the process of step S2. Specifically, the CS condition estimation unit 12 executes once again the simulation by using not only the traffic demand data and SoC distribution data the input of which was already accepted, but also the charge recommendation information which was sent from the charge recommendation information generation unit 14 (step S2). However, when either the condition (2) or condition (3) is satisfied, the charge recommendation information generation unit 14 advances to a process of step S5 (to be described later).

    [0059] If the determination result by the process of step S3 indicates that the desired condition is satisfied (Yes in step S3), the charge recommendation information output unit 15 outputs, to the external terminal, one of the pieces of information included in the charge recommendation information set, which the charge recommendation information generation unit 14 transmitted to the CS condition estimation unit 12 (step S5).

    [0060] In the meantime, in the present embodiment, the congestion condition at each CS is indicated by using the charge wait time, but there is no restriction to this. For example, the congestion condition may be indicated by using the number of vehicles which wait for charge, or the number of vehicles, per charger, which wait for charge.

    [0061] Additionally, in this embodiment, the charge wait time at each CS is indicated by the charge recommendation information, but there is no restriction to this. For example, the charging fee may be varied in accordance with the charge wait time. A higher charging fee is set for charge at a CS where the charge wait time is longer, and a lower charging fee is set for charge at a CS where the charge wait time is short. Then, the charging fee at each CS may be indicated by the charge recommendation information.

    [0062] Additionally, in this embodiment, the charge management apparatus, which provides charge recommendation information to drivers, has been described, with a single-path toll road being set as a target, but there is no restriction to this. For example, a network-like road, along which there are branch parts and confluent parts are present, may be set as a target.

    [0063] Additionally, in this embodiment, a virtual vehicle is generated in the CS condition estimation unit 12, and simulation is executed in units of this virtual vehicle. However, in a background example, simulation may be executed by using not an individual vehicle unit, but a traffic flow as a fluid model. In this case, charging actions can be expressed probabilistically.

    [0064] Additionally, in this embodiment, the charge recommendation information is notified to the driver through the ITS spot or electronic bulletin board, but the notification means for notifying the charge recommendation information to the driver is not limited to this.

    [0065] The above-described first embodiment is configured to include the CS condition estimation unit 12 which executes simulation by using at least the traffic demand data and SoC distribution data; the condition determination unit 13 which determines whether a desired condition is satisfied or not, by using the estimation result information by the CS condition estimation unit 12; and the charge recommendation information generation unit 14 and charge recommendation information output unit 15, which generate the charge recommendation information by using the determination result information by the condition determination unit 13 and outputs this charge recommendation information. By this configuration, the congestion at each CS of a toll road can be relaxed.

    [0066] For example, FIG. 14 is a schematic view illustrating an example of a transition of charge wait time, at a time when the congestion condition of each CS was estimated in the CS condition estimation unit 12 without using the charge recommendation information. FIG. 15 is a schematic view illustrating an example of a transition of charge wait time, at a time when the congestion condition of each CS was estimated in the CS condition estimation unit 12 by using the charge recommendation information. If the schematic view of FIG. 14 and the schematic view of FIG. 15 are compared, the maximum value of charge wait time in the schematic view of FIG. 14 exceeds 7000 seconds, whereas the maximum value of charge wait time in the schematic view of FIG. 15 does not exceed 7000 seconds. From this, it is understood that the maximum value of charge wait time is reduced and the relaxation of the congestion at each CS of the toll road is realized by repeatedly executing the output of the estimation result information by the CS condition estimation unit 12, the output of the determination result information by the condition determination unit 13, and the output of the charge recommendation information by the charge recommendation information generation unit 14.

    [0067] In addition, FIG. 16 is a schematic view illustrating an example of a transition of the maximum value of charge wait time at each CS estimated by the CS condition estimation unit 12. In this case, too, it is understood that the maximum value of charge wait time is reduced by repeatedly executing the output of the estimation result information by the CS condition estimation unit 12, the output of the determination result information by the condition determination unit 13, and the output of the charge recommendation information by the charge recommendation information generation unit 14. It is also understood that the variance in maximum values of charge wait time decreases. Specifically, it is understood that the relaxation of the congestion at each CS of the toll road is realized.

    [0068] Specifically, also on an actual toll road, the realization of relaxation of congestion at each CS of the toll road can be expected, as illustrated in FIG. 15 and FIG. 16, by presenting the charge recommendation information generated by the charge recommendation information generation unit 14.

    [Second Embodiment]



    [0069] FIG. 17 is a schematic view illustrating a configuration example of a charge management apparatus according to a second embodiment. Unlike the charge management apparatus according to the above-described first embodiment, a power supply input unit 16 is added to the charge management apparatus illustrated in FIG. 1.

    [0070] Incidentally, since the traffic demand data input unit 11, condition determination unit 13, charge recommendation information generation unit 14 and charge recommendation information output unit 15 have the same functions as in the above-described first embodiment, a detailed description thereof is omitted here. Hereinafter, different functions from the first embodiment will mainly be described.

    [0071] Upon accepting an input of planned power supply amount information which is transmitted from an external terminal and is indicative of a power amount which each CS can supply, the power supply input unit 16 transmits the planned power supply amount information, the input of which was accepted, to the CS condition estimation unit 12.

    [0072] For example, as illustrated in FIG. 18, planned power supply amount information D10 is information indicative of a power amount, which each CS can supply, for each unit time. For example, it is indicated that CS1 can supply power of 250 kWh during a period from 0:00 to 1:00.

    [0073] The CS condition estimation unit 12 accepts an input of the planned power supply amount information from the power supply input unit 16, in addition to the traffic demand data and SoC distribution data from the traffic demand data input unit 11 and the charge recommendation information from the charge recommendation information generation unit 14. Then, based on the planned power supply amount information the input of which was accepted, the CS condition estimation unit 12 determines the number of available chargers at each CS for each unit time (generates number-of-available chargers information D11), for example, as indicated by D11 in FIG. 19, and then executes simulation and estimates the congestion condition of each CS, like the above-described first embodiment.

    [0074] Referring now to a flowchart of FIG. 20, a description is given of an example of the operation of the charge management apparatus 1 according to the present embodiment. Incidentally, since the process of steps S1, and S3 to S5 is the same as in the above-described first embodiment, a detailed description thereof is omitted here.

    [0075] After the process of step S1, the power supply input unit 16 accepts an input of planned power supply amount information which is transmitted from the external terminal, and then transmits the planned power supply amount information, the input of which was accepted, to the CS condition estimation unit 12 (step S2').

    [0076] Subsequently, upon accepting an input of the traffic demand data and SoC distribution data transmitted from the traffic demand data input unit 11 and the planned power supply amount information transmitted from the power supply input unit 16, the CS condition estimation unit 12 determines, based on the planned power supply amount information the input of which was accepted, the number of available chargers at each CS for each unit time. Thereafter, while considering the determined number of available chargers at each CS for each unit time, the CS condition estimation unit 12 executes simulation by using at least the traffic demand data and SoC distribution data the input of which was accepted, estimates the congestion condition of each CS, and transmits the estimation result information indicative of the result of the estimation to the condition determination unit 13 (step S2").

    [0077] According to the above-described second embodiment, by the configuration which further includes the power supply input unit 16 that can input/output the planned power supply amount information, even in the case where the planned power supply amount varies depending on time slots, the number of available chargers can be varied and simulation can be executed, and thus the congestion at each CS of the toll road can be relaxed.

    [Third Embodiment]



    [0078] FIG. 21 is a schematic view illustrating a configuration example of a charge management apparatus according to a third embodiment. Unlike the charge management apparatuses according to the above-described first and second embodiments, a traffic state input unit 17 is added to the charge management apparatus illustrated in FIG. 1.

    [0079] Incidentally, since the condition determination unit 13, charge recommendation information generation unit 14 and charge recommendation information output unit 15 have the same functions as in the above-described first and second embodiments, a detailed description thereof is omitted here. Hereinafter, different functions from the first and second embodiments will mainly be described.

    [0080] Upon accepting an input of actually measured traffic demand data which was transmitted from an external terminal, the traffic state input unit 17 transmits the actually measured traffic demand data, the input of which was accepted, to the traffic demand data input unit 11. Incidentally, the actually measured traffic demand data is traffic demand data which was actually measured by an ETC (Electronic Toll System) provided, for example, at an IC or the like, and the actually measured traffic demand data is data for correcting traffic demand data.

    [0081] The traffic demand data input unit 11 accepts an input of the actually measured traffic demand data transmitted from the traffic state input unit 17, in addition to the traffic demand data and SoC distribution data transmitted from the external terminal. Then, the traffic demand data input unit 11 corrects the traffic demand data the input of which was accepted, by using the actually measured traffic demand data the input of which was accepted, and then transmits the corrected traffic demand data and the SoC distribution data, the input of which was accepted, to the CS condition estimation module 12.

    [0082] Upon accepting an input of the corrected traffic demand data and SoC distribution data transmitted from the traffic demand data input unit 11, the CS condition estimation unit 12 executes simulation by using at least the corrected traffic demand data and SoC distribution data the input of which was accepted, like the above-described first embodiment, and estimates the congestion condition of each CS.

    [0083] Referring now to a flowchart of FIG. 22, a description is given of an example of the operation of the charge management apparatus 1 according to the present embodiment. Incidentally, since the process of steps S3 to S5 is the same as in the above-described first and second embodiments, a detailed description thereof is omitted here.

    [0084] To start with, upon accepting an input of actually measured traffic demand data transmitted from the external terminal, the traffic state input unit 17 transmits the actually measured traffic demand data, the input of which was accepted, to the traffic demand data input unit 11 (step S1').

    [0085] Subsequently, upon accepting an input of the traffic demand data and SoC distribution data transmitted from the external terminal and the actually measured traffic demand data transmitted from the traffic state input unit 17, the traffic demand data input unit 11 corrects the traffic demand data the input of which was accepted, by using the actually measured traffic demand data the input of which was accepted, and then transmits the corrected traffic demand data and the SoC distribution data, the input of which was accepted, to the CS condition estimation module 12 (step S1").

    [0086] Next, upon accepting an input of the corrected traffic demand data and SoC distribution data transmitted from the traffic demand data input unit 11, CS condition estimation unit 12 executes simulation by using at least the corrected traffic demand data and SoC distribution data the input of which was accepted, estimates the congestion condition of each CS, and transmits the estimation result information indicative of the result of the estimation to the condition determination unit 13 (step S2"').

    [0087] According to the above-described third embodiment, by the configuration which further includes the traffic state input unit 17 that can input/output the actually measured traffic demand data for correcting the traffic demand data, even in the case where the traffic demand data estimated based past data deviates from the actual traffic demand data, an error can be corrected, and thus the congestion at each CS of the toll road can be relaxed.

    [0088] According to at least one of the above-described embodiments, there can be provided a charge management apparatus which can notify the charge recommendation information to the driver, even if the current positions and residual battery capacities of all electric cars running on the toll road or the like are not measured.

    [0089] In the meantime, the method that has been described in connection with each of the above embodiments may be stored as a computer-executable program in a storage medium such as a magnetic disk (e.g. a flexible disk, a hard disk), an optical disk (e.g. a CD-ROM, a DVD), a magneto-optic disc (MO), or a semiconductor memory, and may be distributed.

    [0090] Additionally, the storage form of this storage medium may be any form as long as the storage medium can store programs and is readable by a computer.

    [0091] Additionally, an OS (operating system) running on a computer based on an instruction of a program installed from the storage medium into the computer, or MW (middleware), such as database management software or network software, may execute a part of each of processes for realizing the above embodiments.

    [0092] Additionally, the storage medium in each embodiment is not limited to a medium which is independent from the computer, and includes a storage medium which stores or temporarily stores, by download, a program which is transmitted over a LAN or the Internet.

    [0093] Additionally, the number of storage media is not limited to one. The configuration of the storage media includes such a case that the process in each of the above-described embodiments is executed from a plurality of media, and the configuration of the media may be any configuration.

    [0094] Incidentally, the computer in each embodiment is a computer which executes each process in each embodiment, based on a program stored in the storage medium. The computer may have any configuration, for example, a configuration as a single apparatus such as a personal computer, or a configuration as a system in which a plurality of apparatuses are connected over a network.

    [0095] Additionally, the computer in each embodiment is not limited to a personal computer, and is a general concept of equipment and apparatuses including an arithmetic processing apparatus included in information processing equipment, a microcomputer, etc., which can realize the functions described herein by programs.

    [0096] While certain embodiments have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the invention, which is defined by the appended claims.


    Claims

    1. An apparatus for providing charge recommendation information, the apparatus comprising:

    input means (11) configured to receive traffic demand data (D1) which is data indicative of a respective number of vehicles entering and exiting each of a plurality of interchanges of a toll road per unit time, wherein the respective number of vehicles is a sum of a number of electric vehicles each having a battery mounted therein and a number of vehicles of other kinds entering and exiting each of the plurality of interchanges per unit time, and state-of-charge distribution data (D2) which is data indicating a distribution of a state-of-charge of the batteries of the electric vehicles entering from each of the plurality of interchanges, the state-of-charge distribution data having been estimated based on past data, and the traffic demand data having been estimated based on past data;

    a charge station condition estimation unit (12) configured to execute a first simulation using information pre-set in the charge station condition estimation unit (12) for forming a virtual toll road when executing the first simulation, the first simulation comprising a pre-process stage and an execution stage, wherein, during the pre-process stage, the charge station condition estimation unit (12) is configured to generate numbers of virtual electric vehicles and virtual vehicles of other kinds entering and exiting respective interchanges in accordance with the traffic demand data, wherein a battery of each generated virtual electric vehicle has a respective state-of-charge at a time when the virtual electric vehicle departs from an entrance interchange, the respective state-of-charge being randomly set according to state-of-charge distribution data, wherein virtual vehicles of the other kinds all have a state-of-charge set to zero, and wherein, during the execution stage, the charge station condition estimation unit (12) is configured to estimate a congestion condition of each of a plurality of charge stations provided at respective locations along the toll road by using:

    the received traffic demand data and the state-of-charge distribution data;

    a driver model (121) of a driver of a virtual vehicle;

    a vehicle model (122) of the virtual vehicle;

    a battery model (123) of a battery of the virtual vehicle;

    a charge station model (124) of the charge stations; and

    a notification model (125) of a notification means for notifying the charge recommendation information to drivers of electric vehicles running on the toll road, wherein
    the congestion condition is indicated by one of:

    a charge wait time at the charge station;

    a number of vehicles waiting to charge at the charge station; and

    a number of vehicles, per charger, waiting to charge at the charge station,

    the driver model (121) is configured to perform a driving path selection process, charge station selection process and a vehicle state selection process, upon accepting an input of information from the vehicle model (122), the battery model (123) and the notification model (125), wherein the driver model (121) is configured to perform the vehicle state selection process based on a position of the virtual vehicle transmitted from the vehicle model (122),

    the vehicle model (122) is configured to perform, when the vehicle state selection process provides vehicle state information indicating that the vehicle is driving, an update process of updating the position and a speed of the virtual vehicle,

    the battery model (123) is configured to perform an update process of updating an indication of residual battery capacity upon accepting an input of position and speed information and state information from the vehicle model (122) and charge speed information from the charge station model (124), the update process performed in accordance with the vehicle state indicated by the vehicle state information, and:

    the position and speed of the virtual vehicle, in a case where the vehicle state information indicates that the vehicle is driving; or

    charge speed information from the charge station model (124), in a case where the vehicle state information indicates that the vehicle is charging,

    the charge station model (124) is configured to transmit charge speed information indicative of the charge speed to the battery model (123) in accordance with charge state information (D4) which is preset in the charge station condition estimation unit (12);

    a condition determination unit (13) configured to compare the estimated congestion conditions at the respective charge stations, and determine whether a predetermined condition is satisfied;

    a charge recommendation information generation unit (14) configured to generate, using the comparison of the estimated congestion conditions at the respective charge stations made by the condition determination unit (13), charge recommendation information that is indicative of a charge station whose use is recommended to even out congestion at the charge stations, when a result of determination by the condition determination unit (13) indicates that the predetermined condition is not satisfied, wherein the predetermined condition is satisfied when:

    (1) when the congestion conditions of all neighboring charge stations are compared, a value, which is calculated by subtracting a congestion condition of an upstream charge station from a congestion condition of a downstream charge station, is a threshold value or less; or

    (2) a number of times of repetition of a series of processes of the output of estimation results by the first estimation unit (12), the output of determination result information by the condition determination unit (13) and the output of charge recommendation information by the charge recommendation information generation unit (14), is a predetermined number or more; or

    (3) no new charge recommendation information is generated by the charge recommendation information generation unit (14),

    wherein the notification model (125) is configured to transmit the charge recommendation information to the driver model (121) when the virtual vehicle passes the notification means and only when there is an input of charge recommendation information from the charge recommendation information generation unit (14),

    wherein the charge station condition estimation unit (12) is configured to execute a second simulation to estimate, using the generated charge recommendation information in addition to the received traffic demand data, once again the congestion conditions at the respective charge stations; and

    output means (15) configured to output the charge recommendation information used in the second simulation to the notification means, the output means (15) being configured to output the charge recommendation information used in the second simulation when a result of determination by the condition determination unit (13) indicates that the predetermined condition is satisfied after the condition determination unit (13) having previously determined that the predetermined condition is not satisfied, as a result of repeatedly executing processes by the condition determination unit (13), the charge recommendation information generation unit (14) and the second estimation means (12).


     
    2. The apparatus of Claim 1, further comprising a power supply input unit (16) configured to receive planned power supply amount information indicative of power amounts which the plurality of charge stations can supply,

    wherein the charge station condition estimation unit (12) is configured to execute the first simulation by using the traffic demand data and the planned power supply amount information, and

    the charge station condition estimation unit (12) is configured to execute the second simulation by using the charge recommendation information, in addition to the traffic demand data and the planned power supply amount information.


     
    3. The apparatus of Claim 1, wherein the congestion condition is indicated by a charge wait time at the charge station, and the condition determination unit (13) is configured to compare the charge wait times at the charge stations which neighbor each other, and to determine whether a value, which is calculated by subtracting a charge wait time of an upstream charge station from a charge wait time of a downstream charge station, is a threshold value or less.
     
    4. The apparatus of Claim 1, wherein the charge recommendation information generation unit (14) is configured to generate, if the result of determination by the condition determination unit (13) indicates that the predetermined condition is not satisfied, charge recommendation information indicative of at least either a charge wait time or a charging fee at a charge station capable of charging.
     


    Ansprüche

    1. Vorrichtung zum Bereitstellen einer Gebührenempfehlungsinformation, wobei die Vorrichtung umfasst:

    ein Eingabemittel (11), das konfiguriert ist zum Empfangen von Verkehrsbedarfsdaten (D1), welche Daten sind, die eine jeweilige Anzahl von Fahrzeugen anzeigen, die in jede einer Vielzahl von Kreuzungen einer Mautstraße pro Zeiteinheit einfahren und diese verlassen, wobei die jeweilige Anzahl von Fahrzeugen eine Summe aus einer Anzahl von Elektrofahrzeugen, die jeweils eine darin angebrachte Batterie aufweisen, und einer Anzahl von Fahrzeugen anderer Art ist, die in jede der Vielzahl von Kreuzungen pro Zeiteinheit einfahren und diese verlassen, und Ladezustandsverteilungsdaten (D2), welche Daten sind, die eine Verteilung eines Ladezustands der Batterien der Elektrofahrzeuge anzeigen, die von jeder der Vielzahl von Kreuzungen einfahren, wobei die Ladungszustandsverteilungsdaten auf Grundlage vergangener Daten geschätzt worden sind und die Verkehrsbedarfsdaten auf Grundlage vergangener Daten geschätzt worden sind;

    eine Ladestationszustand-Schätzeinheit (12), die konfiguriert ist zum Ausführen einer ersten Simulation unter Verwendung einer Information, die in der Ladestationszustand-Schätzeinheit (12) voreingestellt ist, um eine virtuelle Mautstraße zu bilden, wenn die erste Simulation ausgeführt wird, wobei die erste Simulation eine Vorverarbeitungsstufe und eine Ausführungsstufe umfasst, wobei während der Vorverarbeitungsstufe die Ladestationszustand-Schätzeinheit (12) konfiguriert ist zum Erzeugen von Anzahlen virtueller Elektrofahrzeuge und virtueller Fahrzeuge anderer Art, die in Übereinstimmung mit den Verkehrsbedarfsdaten in jeweilige Kreuzungen einfahren und diese verlassen, wobei eine Batterie jedes erzeugten virtuellen Elektrofahrzeugs einen jeweiligen Ladezustand zu einem Zeitpunkt aufweist, zu dem das virtuelle Elektrofahrzeug von einer Eingangskreuzung abfährt, wobei der jeweilige Ladezustand zufällig gemäß Ladezustandsverteilungsdaten eingestellt wird, wobei virtuelle Fahrzeuge der anderen Arten alle einen Ladezustand aufweisen, der auf Null eingestellt ist, und wobei während der Ausführungsstufe die Ladestationszustands-Schätzeinheit (12) konfiguriert ist zum Schätzen eines Überlastungszustands jeder einer Vielzahl von Ladestationen, die an jeweiligen Positionen entlang der Mautstraße vorgesehen sind, unter Verwendung:

    der empfangenen Verkehrsbedarfsdaten und der Ladezustandsverteilungsdaten;

    eines Fahrermodells (121) eines Fahrers eines virtuellen Fahrzeugs;

    eines Fahrzeugmodells (122) des virtuellen Fahrzeugs;

    eines Batteriemodells (123) einer Batterie des virtuellen Fahrzeugs;

    eines Ladestationsmodells (124) der Ladestationen; und

    eines Benachrichtigungsmodells (125) eines Benachrichtigungsmittels zum Benachrichtigen der Gebührenempfehlungsinformation an Fahrer von Elektrofahrzeugen, die auf der Mautstraße fahren, wobei
    der Überlastungszustand angezeigt wird durch eines von:

    einer Ladewartezeit an der Ladestation;

    einer Anzahl von Fahrzeugen, die auf das Aufladen an der Ladestation warten; und

    einer Anzahl von Fahrzeugen, pro Ladesäule, die darauf warten, an der Ladestation geladen zu werden,

    das Fahrermodell (121) konfiguriert ist zum Ausführen eines Fahrweg-Auswahlprozesses, eines Ladestation-Auswahlprozesses und eines Fahrzeugzustand-Auswahlprozesses beim Akzeptieren einer Informationseingabe von dem Fahrzeugmodell (122), dem Batteriemodell (123) und dem Benachrichtigungsmodell (125), wobei das Fahrermodell (121) konfiguriert ist zum Ausführen des Fahrzeugzustand-Auswahlprozesses auf Grundlage einer von dem Fahrzeugmodell (122) übertragenen Position des virtuellen Fahrzeugs,

    das Fahrzeugmodell (122) konfiguriert ist zum Ausführen, wenn der Fahrzeugzustand-Auswahlprozess Fahrzeugzustandsinformation liefert, die anzeigt, dass das Fahrzeug fährt, eines Aktualisierungsprozesses zum Aktualisieren der Position und einer Geschwindigkeit des virtuellen Fahrzeugs,

    das Batteriemodell (123) konfiguriert ist zum Ausführen eines Aktualisierungsprozesses zum Aktualisieren einer Anzeige der Restbatteriekapazität beim Akzeptieren einer Eingabe der Positions- und Geschwindigkeitsinformation und Zustandsinformation von dem Fahrzeugmodell (122) und Ladegeschwindigkeitsinformation von dem Ladestationsmodell (124), wobei der Aktualisierungsprozess in Übereinstimmung mit dem Fahrzeugzustand ausgeführt wird, der durch die Fahrzeugzustandsinformation angezeigt wird, und:

    der Position und der Geschwindigkeit des virtuellen Fahrzeugs in einem Fall, in dem die Fahrzeugzustandsinformation anzeigt, dass das Fahrzeug fährt; oder

    Ladegeschwindigkeitsinformation von dem Ladestationsmodell (124), wenn die Fahrzeugzustandsinformation anzeigt, dass das Fahrzeug lädt,

    das Ladestationsmodell (124) konfiguriert ist zum Übertragen der Ladegschwindigkeitsinformation, die die Ladegeschwindigkeit für das Batteriemodell (123) anzeigt, in Übereinstimmung mit Ladezustandsinformation (D4), die in der Ladestationszustand-Schätzeinheit (12) voreingestellt ist;

    eine Zustandsbestimmungseinheit (13), die konfiguriert ist zum Vergleichen der geschätzten Überlastungszustände an den jeweiligen Ladestationen und zum Bestimmen, ob eine vorbestimmte Bedingung erfüllt ist;

    eine Gebührenempfehlungsinformations-Erzeugungseinheit (14), die konfiguriert ist zum Erzeugen, unter Verwendung des von der Zustandsbestimmungseinheit (13) durchgeführten Vergleichs der geschätzten Überlastungszustände an den jeweiligen Ladestationen, der Gebührenempfehlungsinformation, die eine Ladestation angeben, deren Verwendung empfohlen wird, um eine Überlastung an den Ladestationen auszugleichen, wenn ein Ergebnis der Bestimmung durch die Zustandsbestimmungseinheit (13) anzeigt, dass die vorbestimmte Bedingung nicht erfüllt ist, wobei die vorbestimmte Bedingung erfüllt ist, wenn:

    (1) die Überlastungszustände aller benachbarten Ladestationen verglichen werden, ein Wert, der durch Subtraktion eines Überlastungszustands einer straßenaufwärts gelegenen Ladestation von einem Überlastungszustand einer straßenabwärts gelegenen Ladestation berechnet wird, ein Schwellenwert oder weniger ist; oder

    (2) eine Anzahl von Wiederholungen einer Reihe von Prozessen der Ausgabe von Schätzungsergebnissen durch die erste Schätzeinheit (12), der Ausgabe von Bestimmungsergebnisinformation durch die Zustandsbestimmungseinheit (13) und der Ausgabe der Gebührenempfehlungsinformation durch die Gebührenempfehlungsinformations-Erzeugungseinheit (14) eine vorbestimmte Anzahl oder mehr ist; oder

    (3) keine neue Gebührenempfehlungsinformation durch die Gebührenempfehlungsinformations-Erzeugungseinheit (14) erzeugt wird,

    wobei das Benachrichtigungsmodell (125) konfiguriert ist zum Senden der Gebührenempfehlungsinformation an das Fahrermodell (121), wenn das virtuelle Fahrzeug das Benachrichtigungsmittel passiert, und nur dann, wenn eine Eingabe einer Gebührenempfehlungsinformation von der Gebührenempfehlungsinformations-Erzeugungseinheit (14) vorliegt,

    wobei die Ladestationszustand-Schätzeinheit (12) konfiguriert ist zum Ausführen einer zweiten Simulation, um unter Verwendung der erzeugten Gebührenempfehlungsinformation zusätzlich zu den empfangenen Verkehrsbedarfsdaten erneut die Überlastungszustände an den jeweiligen Ladestationen zu schätzen; und

    ein Ausgabemittel (15), das konfiguriert ist zum Ausgeben der in der zweiten Simulation verwendeten Gebührenempfehlungsinformation an das Benachrichtigungsmittel, wobei das Ausgabemittel (15) konfiguriert ist zum Ausgeben der in der zweiten Simulation verwendeten Gebührenempfehlungsinformation, wenn ein Ergebnis der Bestimmung durch die Zustandsbestimmungseinheit (13) anzeigt, dass die vorbestimmte Bedingung erfüllt ist, nachdem die Zustandsbestimmungseinheit (13) zuvor bestimmt hat, dass die vorbestimmte Bedingung nicht erfüllt ist, als ein Ergebnis der wiederholten Ausführung von Prozessen durch die Zustandsbestimmungseinheit (13), die Gebührenempfehlungsinformations-Erzeugungseinheit (14) und das zweite Schätzmittel (12).


     
    2. Vorrichtung nach Anspruch 1, die ferner eine Stromversorgungs-Eingabeeinheit (16) umfasst, die konfiguriert ist zum Empfangen einer Geplante-Stromversorgungsmenge-Information, die die Strommengen anzeigt, die die Vielzahl von Ladestationen liefern kann,

    wobei die Ladestationszustand-Schätzeinheit (12) konfiguriert ist zum Ausführen der ersten Simulation unter Verwendung der Verkehrsbedarfsdaten und der Geplante-Stromversorgungsmenge-Information, und

    die Ladestationszustand-Schätzeinheit (12) konfiguriert ist zum Ausführen der zweiten Simulation unter Verwendung der Gebührenempfehlungsinformation zusätzlich zu den Verkehrsbedarfsdaten und der Geplante-Stromversorgungsmenge-Information.


     
    3. Vorrichtung nach Anspruch 1, wobei der Überlastungszustand durch eine Ladewartezeit an der Ladestation angezeigt wird und die Zustandsbestimmungseinheit (13) konfiguriert ist zum Vergleichen der Ladewartezeiten an den Ladestationen, die einander benachbart sind, und zum Bestimmen, ob ein Wert, der durch Subtraktion einer Ladewartezeit einer straßenaufwärts gelegenen Ladestation von einer Ladewartezeit einer straßenabwärts gelegenen Ladestation berechnet wird, ein Schwellenwert oder weniger ist.
     
    4. Vorrichtung nach Anspruch 1, wobei die Gebührenempfehlungsinformations-Erzeugungseinheit (14) konfiguriert ist zum Erzeugen, wenn das Ergebnis der Bestimmung durch die Zustandsbestimmungseinheit (13) anzeigt, dass die vorbestimmte Bedingung nicht erfüllt ist, einer Gebührenempfehlungsinformation, die zumindest entweder eine Ladewartezeit oder eine Ladegebühr an einer ladefähigen Ladestation angibt.
     


    Revendications

    1. Appareil pour fournir des informations de recommandation de charge, l'appareil comprenant :

    un moyen d'entrée (11) configuré pour recevoir des données de demande de trafic (D1) qui sont des données indicatives d'un nombre respectif de véhicules entrant et sortant de chacun d'une pluralité d'échangeurs d'une route à péage par unité de temps, dans lequel le nombre respectif de véhicules est une somme d'un nombre de véhicules électriques présentant chacun une batterie montée dans ceux-ci et d'un nombre de véhicules d'autres types entrant et sortant de chacun de la pluralité d'échangeurs par unité de temps, et des données de distribution d'état de charge (D2) qui sont des données indiquant une distribution d'un état de charge des batteries des véhicules électriques entrant dans chacun de la pluralité d'échangeurs, les données de distribution d'état de charge ayant été estimées sur la base de données antérieures, et les données de demande de trafic ayant été estimées sur la base de données antérieures ;

    une unité d'estimation d'état de station de charge (12) configurée pour exécuter une première simulation en utilisant des informations prédéfinies dans l'unité d'estimation d'état de station de charge (12) pour former une route à péage virtuelle lors de l'exécution de la première simulation, la première simulation comprenant une étape de pré-processus et une étape d'exécution, dans lequel, durant l'étape de pré-processus, l'unité d'estimation d'état de station de charge (12) est configurée pour générer des nombres de véhicules électriques virtuels et de véhicules virtuels d'autres types entrant et sortant d'échangeurs respectifs conformément aux données de demande de trafic, dans lequel une batterie de chaque véhicule électrique virtuel généré présente un état de charge respectif à un moment où le véhicule électrique virtuel part d'un échangeur d'entrée, l'état de charge respectif étant défini aléatoirement conformément aux données de distribution d'état de charge, dans lequel des véhicules virtuels des autres types présentent tous un état de charge défini sur zéro, et dans lequel, durant l'étape d'exécution, l'unité d'estimation d'état de station de charge (12) est configurée pour estimer un état de congestion de chacune d'une pluralité de stations de charge fournies à des emplacements respectifs le long de la route à péage en utilisant :

    les données de demande de trafic reçues et les données de distribution d'état de charge ;

    un modèle de conducteur (121) d'un conducteur d'un véhicule virtuel ;

    un modèle de véhicule (122) du véhicule virtuel ;

    un modèle de batterie (123) d'une batterie du véhicule virtuel ;

    un modèle de station de charge (124) des stations de charge ; et

    un modèle de notification (125) d'un moyen de notification pour notifier les informations de recommandation de charge à des conducteurs de véhicules électriques conduisant sur la route à péage, dans lequel
    l'état de congestion est indiqué par l'un parmi :

    un temps d'attente de charge à la station de charge ;

    un nombre de véhicules attendant de charger à la station de charge ; et

    un nombre de véhicules, par chargeur, attendant de charger à la station de charge,

    le modèle de conducteur (121) est configuré pour effectuer un processus de sélection de trajet de conduite, un processus de sélection de station de charge et un processus de sélection d'état de véhicule, lors de l'acceptation d'une entrée d'informations depuis le modèle de véhicule (122), le modèle de batterie (123) et le modèle de notification (125), dans lequel le modèle de conducteur (121) est configuré pour effectuer le processus de sélection d'état de véhicule sur la base d'une position du véhicule virtuel transmise depuis le modèle de véhicule (122),

    le modèle de véhicule (122) est configuré pour effectuer, lorsque le processus de sélection d'état de véhicule fournit des informations d'état de véhicule indiquant que le véhicule est en conduite, un processus de mise à jour consistant à mettre à jour la position et une vitesse du véhicule virtuel,

    le modèle de batterie (123) est configuré pour effectuer un processus de mise à jour consistant à mettre à jour une indication de capacité de batterie résiduelle lors de l'acceptation d'une entrée d'informations de position et de vitesse et d'informations d'état depuis le modèle de véhicule (122) et d'informations de vitesse de charge depuis le modèle de station de charge (124), le processus de mise à jour étant effectué conformément à l'état de véhicule indiqué par les informations d'état de véhicule, et :

    la position et la vitesse du véhicule virtuel, dans un cas où les informations d'état de véhicule indiquent que le véhicule est en conduite ; ou

    des informations de vitesse de charge depuis le modèle de station de charge (124), dans un cas où les informations d'état de véhicule indiquent que le véhicule est en charge,

    le modèle de station de charge (124) est configuré pour transmettre des informations de vitesse de charge indicatives de la vitesse de charge au modèle de batterie (123) conformément à des informations d'état de charge (D4) qui sont prédéfinies dans l'unité d'estimation d'état de station de charge (12) ;

    une unité de détermination d'état (13) configurée pour comparer les états de congestion estimés aux stations de charge respectives, et déterminer si un état prédéterminé est satisfait ;

    une unité de génération d'informations de recommandation de charge (14) configurée pour générer, en utilisant la comparaison des états de congestion estimés aux stations de charge respectives faite par l'unité de détermination d'état (13), des informations de recommandation de charge qui sont indicatives d'une station de charge dont l'utilisation est recommandée pour réduire la congestion aux stations de charge, lorsqu'un résultat de détermination par l'unité de détermination d'état (13) indique que l'état prédéterminé n'est pas satisfait, dans lequel l'état prédéterminé est satisfait lorsque :

    (1) lorsque les états de congestion de toutes les stations de charge voisines sont comparés, une valeur, qui est calculée en soustrayant un état de congestion d'une station de charge en amont d'un état de congestion d'une station de charge en aval, est une valeur seuil ou moins ; ou

    (2) un nombre de répétitions d'une série de processus de la sortie de résultats d'estimation par la première unité d'estimation (12), de la sortie d'informations de résultat de détermination par l'unité de détermination d'état (13) et de la sortie d'informations de recommandation de charge par l'unité de génération d'informations de recommandation de charge (14) est un nombre prédéterminé ou plus; ou

    (3) aucune nouvelle information de recommandation de charge n'est générée par l'unité de génération d'informations de recommandation de charge (14),

    dans lequel le modèle de notification (125) est configuré pour transmettre les informations de recommandation de charge au modèle de conducteur (121) lorsque le véhicule virtuel dépasse le moyen de notification et uniquement lorsqu'il y a une entrée d'informations de recommandation de charge depuis l'unité de génération d'informations de recommandation de charge (14),

    dans lequel l'unité d'estimation d'état de station de charge (12) est configurée pour exécuter une seconde simulation pour estimer, en utilisant les informations de recommandation de charge générées en plus des données de demande de trafic reçues, une fois de plus les états de congestion aux stations de charge respectives ; et

    un moyen de sortie (15) configuré pour délivrer en sortie les informations de recommandation de charge utilisées dans la seconde simulation au moyen de notification, le moyen de sortie (15) étant configuré pour délivrer en sortie les informations de recommandation de charge utilisées dans la seconde simulation lorsqu'un résultat de détermination par l'unité de détermination d'état (13) indique que l'état prédéterminé est satisfait après que l'unité de détermination d'état (13) a précédemment déterminé que l'état prédéterminé n'est pas satisfait, à la suite de l'exécution répétée de processus par l'unité de détermination d'état (13), l'unité de génération d'informations de recommandation de charge (14) et le second moyen d'estimation (12).


     
    2. Appareil selon la revendication 1, comprenant en outre une unité d'entrée d'alimentation électrique (16) configurée pour recevoir des informations de quantité d'alimentation électrique planifiée indicatives de quantités d'énergie que la pluralité de stations de charge peut fournir,

    dans lequel l'unité d'estimation d'état de station de charge (12) est configurée pour exécuter la première simulation en utilisant les données de demande de trafic et les informations de quantité d'alimentation électrique planifiée, et

    l'unité d'estimation d'état de station de charge (12) est configurée pour exécuter la seconde simulation en utilisant les informations de recommandation de charge, en plus des données de demande de trafic et des informations de quantité d'alimentation électrique planifiée.


     
    3. Appareil selon la revendication 1, dans lequel l'état de congestion est indiqué par un temps d'attente de charge à la station de charge, et l'unité de détermination d'état (13) est configurée pour comparer les temps d'attente de charge aux stations de charge qui sont voisines les unes des autres, et pour déterminer si une valeur, qui est calculée en soustrayant un temps d'attente de charge d'une station de charge en amont d'un temps d'attente de charge d'une station de charge en aval, est une valeur seuil ou moins.
     
    4. Appareil selon la revendication 1, dans lequel l'unité de génération d'informations de recommandation de charge (14) est configurée pour générer, si le résultat de détermination par l'unité de détermination d'état (13) indique que l'état prédéterminé n'est pas satisfait, des informations de recommandation de charge indicatives d'au moins soit un temps d'attente de charge soit un coût de charge à la station de charge capable de charger.
     




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    Cited references

    REFERENCES CITED IN THE DESCRIPTION



    This list of references cited by the applicant is for the reader's convenience only. It does not form part of the European patent document. Even though great care has been taken in compiling the references, errors or omissions cannot be excluded and the EPO disclaims all liability in this regard.

    Patent documents cited in the description