WO2015049969A1

WO2015049969A1 - Operation management device for electric vehicle, and operation planning method

Info

Publication number: WO2015049969A1
Application number: PCT/JP2014/074162
Authority: WO
Inventors: Topon PAUL; Hisashi Yamada; Hideyuki Aisu
Original assignee: Kabushiki Kaisha Toshiba
Priority date: 2013-10-04
Filing date: 2014-09-08
Publication date: 2015-04-09
Also published as: JP6301730B2; CN105637543A; JP2015092328A; WO2015049969A4

Abstract

An operation management device according to an embodiment includes vehicle information unit, charging equipment information unit, bus schedule unit, route information unit, and operation planning unit. The vehicle information unit stores vehicle information. The charging equipment information unit stores charging equipment information. The bus schedule unit stores bus schedule information. The route information unit stores route information. The operation planning unit allocates an electric vehicle to each bus schedule specified by the bus schedule information, and forms an operation plan. The operation planning unit calculates the amount of energy consumption that is consumed at a time of the electric vehicle operating along each route, calculates the amount of charging energy to be charged in the electric vehicle at each charging station, based on the amount of energy consumption, and allocates the electric vehicle to the bus schedule based on the amount of charging energy.

Description

DESCRIPTION

OPERATION MANAGEMENT DEVICE FOR ELECTRIC VEHICLE,

AND OPERATION PLANNING METHOD

FIELD

Embodiments described herein relate generally to an operation management device for electric vehicles, and an operation planning method.

BACKGROUND

In recent years, more and more business-purpose vehicles, such as city buses or shuttle buses and vehicles for Bus Rapid Transit (BRT), which operate according to a bus schedule, are getting electrified. When forming an operation plan for such electric vehicles, various dynamic factors have to be taken into account. For example, in the case of an electric bus, the number of passengers or the energy consumption rate may change, or the bus may be delayed due to a traffic jam, or the supply energy at a charging station may change due to issuance of a DR (Demand Response), based on the time of the day or an external factor. If an electric vehicle is not charged according to the operation plan at the charging station due to such dynamic factors, the electric vehicle may possibly run out of energy. ^"

Furthermore, since the charging of an electric vehicle requires a large amount of power, the constraints regarding planned peak-shifting for suppressing the charging load on charging equipment, power and energy supplied from a power supply side (a power grid or charging equipment) and the like have to be met.

However, it is difficult to form an operation plan taking into account many dynamic factors as mentioned above. For example, most of the conventional operation planning methods that take into account energy shortage of an electric vehicle only give consideration to prevention of energy shortage during operation of each electric vehicle individually.

On the other hand, an operation planning method for an electric vehicle that takes into account a charging load on charging equipment targets only a case where each targeted electric vehicle is already connected to a charger, and does not take an electric vehicle in operation into account. As described, an operation planning method that aims to realize both the prevention of energy shortage of an electric vehicle and the suppression of a charging load on charging equipment has not been proposed.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram showing a functional composition of an operation management device according to the first embodiment of the present invention.

FIGS. 2(a) to 2(c) are illustrations for describing a basic bus schedule.

FIG. 3 is a diagram showing an example of a basic bus schedule.

FIG. 4 is a diagram showing an example of operation information.

FIG. 5 is a diagram showing an example of battery information.

FIG. 6 is a diagram showing an example of route information.

FIG. 7 is a diagram showing an example of stationary battery information.

FIGS. 8(a) and 8(b) are diagrams showing an example of supply power information.

FIG. 9 is a diagram showing an example of a vehicle allocation plan.

FIG. 10 is a diagram showing an example of a charge plan. FIG. 11 is a diagram showing hardware of an operation management device.

FIGS. 12(a) and 12(b) are diagrams describing an operation planning method. FIG. 13 is a flow chart showing an operation planning process.

FIG. 14 is a diagram describing a method for calculation of required energy of a bus schedule.

FIG. 15 is a diagram showing an example of a list of required energy.

FIG. 16 is a flow chart showing a generation process of a list of electric vehicles that can be allocated.

FIG. 17 is a diagram showing an example of a list of electric vehicles that can be allocated.

FIGS. 18(a) and 18(b) are diagrams for describing an estimation method of remaining energy.

FIGS. 19(a) to 19(c) are diagrams for describing a generation method of a candidate solution.

FIGS. 20(a) and 20(b) are diagrams for describing a decoding method of a candidate solution.

FIGS. 21(a) and 21(b) are diagrams for describing a vehicle allocation method.

FIG. 22 is a flow chart showing an evaluation process of charging feasibility.

FIGS. 23(a) and 23(b) are diagrams showing an example of supply power.

FIGS. 24(a) and 24(b) are diagrams showing an example of a list of arrival points.

FIG. 25 is a flow chart showing a determination process of charging feasibility.

FIG. 26 is a flow chart showing a calculation process of remaining energy in a stationary battery.

FIG. 27 is a flow chart showing a calculation process of the amount of charging energy for an electric bus.

FIG. 28 is a flow chart showing an update process of supply power.

FIGS. 29(a) to 29(c) are diagrams for describing an updating method of supply power.

FIG. 30 is a flow chart showing an update process of remaining energy in a stationary battery. FIG. 31 is a flow chart showing an operation planning process of the second embodiment.

FIGS. 32(a) and 32(b) are diagrams showing an example of a list of candidate solutions.

FIGS. 33(a) to 33(c) are diagrams for describing a generation method of a candidate solution by a genetic algorithm.

FIGS. 34(a) to 34(d) are diagrams for describing an operation planning method according to the third embodiment.

FIG. 35 is a flow chart showing an operation planning process according to the third embodiment.

FIG. 36 is a diagram showing an example of a vehicle allocation list.

FIGS. 37(a) and 37(b) are diagrams for describing an update method of a charge list.

FIG. 38 is a flow chart showing the processing of delay corresponding to the departure time of a candidate departure point.

FIG. 39 is a flow chart showing a re-planning determination process according to the fourth embodiment.

FIG. 40 is a flow chart showing the process that determines that the remaining energy of an electric bus is low.

FIG. 41 is a flow chart showing a determination process of charging feasibility during re-planning.

FIG. 42 is a flow chart showing an adjustment process of the parameter a.

FIG. 43 is a diagram showing an example of a basic bus schedule to which an operation planning method according to the fifth embodiment is to be applied.

FIG. 44 is a flow chart showing a calculation process of required energy of a bus schedule when an arrival point is a non-charging node.

FIGS. 45(a) to 45(c) are diagrams for describing an update process of route information according to the sixth embodiment.

FIGS. 46(a) and 46(b) are diagrams showing examples of a SOH mapping table and a target SOH table according to the seventh embodiment. FIG. 47 is a diagram showing an example of an operation plan that takes wireless power transfer into account.

FIG. 48 is a flow chart showing a determination process of charging feasibility according to the eighth embodiment.

FIG. 49 is a block diagram showing a functional configuration of an operation management device according to the ninth embodiment.

FIG. 50 is a flow chart showing an operation planning process according to the ninth embodiment.

FIG. 51 is a diagram for describing an extraction method of a candidate departure point.

DETAILED DESCRIPTION

An operation management device according to an embodiment includes vehicle information unit, charging equipment information unit, bus schedule unit, route information unit, and operation planning unit. The vehicle information unit stores vehicle information about a plurality of electric vehicles each with a battery. The charging equipment information unit stores charging equipment information about charging capacity of charging equipment capable of charging electric vehicles, the charging equipment being located at a plurality of charging stations. The bus schedule unit stores bus schedule information specifying a plurality of bus schedules including at least a route connecting a plurality of stop locations along which the electric vehicles are to operate, and at least one of the departure time and the arrival time at each stop location on the route. The route information unit stores route information about a route. The operation planning unit forms an operation plan by allocating an electric vehicle to each bus schedule specified by the bus schedule information. The operation planning unit calculates the amount of energy consumption that is consumed at the time of an electric vehicle operating along each route, calculates the amount of charging energy to be charged in the electric vehicle at each charging station based on the amount of energy consumption, and allocates the electric vehicle to the bus schedule based on the amount of charging energy.

In the following, the operation management device according to the embodiment of the present invention will be described with reference to the drawings. This operation management device manages a plurality of registered electric vehicles to operate according to a predetermined bus schedule. Electric vehicles whose operation is to be managed by this operation management device include electric buses, electric cars, electric taxies, buses with batteries (battery-powered buses), and the like. Also, non-electric vehicles such as gasoline-powered vehicles may be registered in the operation management device together with electric vehicles. In the following, the operation management device will be described while citing management of operation of electric buses as an example, but the operation management device may manage the operation of any electric vehicles.

(First Embodiment)

FIG. 1 is a block diagram showing a functional configuration of the operation management device according to the embodiment of the present invention. The operation management device forms an operation plan of electric buses that operate according to a bus schedule while taking dynamic factors into account. An operation plan includes an electric bus allocation plan for each bus schedule specified by a basic bus schedule, and a charge plan regarding charging at charging stations.

The operation management device includes operation planning unit 10 for forming an operation plan, basic bus schedule unit 11 for storing a basic bus schedule specifying bus schedules for the operation of electric buses, vehicle information unit 12 for storing vehicle information about electric buses, route information unit 13 for storing route information about routes along which electric buses operate, charging equipment information unit 14 for storing charging equipment information about charging equipment provided at charging stations according to the bus schedule, plan storage unit 15 for storing an operation plan formed by the operation planning unit 10, re-planning determination unit 16 for determining whether or not to re-plan the current operation plan according to dynamic factors, and re-planning request unit 17 for notifying the re-planning determination unit 16 of a re-planning request and causing the re-planning determination unit 16 to start re-planning determination.

The operation planning unit 10 acquires, from the basic bus schedule unit 11, the vehicle information unit 12, the route information unit 13, and the charging equipment information unit 14, a basic bus schedule, vehicle information, route information, and charging equipment information, respectively and forms a vehicle allocation plan specifying allocation of electric buses to a plurality of bus schedules specified based on the basic bus schedule, and a charge plan specifying the amount of charging energy for electric buses at each charging station. The operation planning unit 10 includes vehicle allocation unit 101 for creating the vehicle allocation plan based on the remaining energy of electric buses and the like, bus schedule connection unit 102 for connecting arrival points and departure points of bus schedules, charging amount calculation unit 103 for calculating the amount of charging energy for electric buses at each charging station, and charging feasibility evaluation unit 104 for evaluating charging feasibility at a charging station. Connection of arrival points and departure points of bus schedules refers to specification of a set of one or more bus schedules according to which one electric bus is to operate and are extracted from a plurality of bus schedules specified based on the basic bus schedule. Additionally, in the case where non-electric vehicles are registered in the operation management device, the operation planning unit 10 may form the vehicle allocation plan including the non-electric vehicles.

The basic bus schedule unit 11 stores the basic bus schedule (bus schedule) for the electric buses. The basic bus schedule specifies a plurality of bus schedules; each bus schedule includes a route connecting a plurality of stop locations where the electric buses are to stop, and at least one of the arrival time and the departure time at each stop location. The operation plan for the operation of a plurality of electric buses registered in the operation management device is determined by allocating the electric buses to the bus schedules specified based on the basic bus schedule and determining the amount of charging energy at each charging station. That is, the operation plan includes a basic bus schedule, a vehicle allocation plan specifying the electric buses to be allocated to each bus schedule included in the basic bus schedule, and a charge plan specifying the amount of charging energy for each electric bus at each charging station.

FIGS. 2(a) to 2(c) are explanatory diagrams for describing the outline of the basic bus schedule, and FIG, 2(a) shows the entire bus route network. This bus route network includes stop locations, such as charging stations (bus depot, bus terminals, and the like) A and F, and bus stops B, C, D and E. Electric buses operate between the stop locations along the routes shown by solid lines in FIG. 2(a).

FIG. 2(b) is a basic bus schedule prepared for the bus route network of FIG. 2(a), and this basic bus schedule includes a plurality of bus schedules. A bus schedule here specifies a route along which electric buses are to operate and the schedule (time), and is shown in FIG. 2(b) by connecting routes between a departure point and an arrival point by solid lines. The basic bus schedule is formed by collecting a plurality of such bus schedules (for one day, for example).

On the other hand, a bus schedule is configured by including one or more paths. A path here specifies a route for stop locations of the bus schedule and the schedule (time), and is shown in FIG. 2(b) by connecting the stop locations of the bus schedule by a solid line. The bus schedule is formed by connecting such paths from the departure point to the arrival point.

Furthermore, the bus schedule (path) specifies at least one of the arrival time and the departure time (schedule) of each stop location of the bus schedule. Additionally, in FIG. 2(b), the earliest departure time is referred as a plan starting time Ts, and the last arrival time is referred to as a plan ending time Te.

FIG. 2(c) is a basic bus schedule for forming an operation plan, which is a simplified basic bus schedule of FIG. 2(b). The basic bus schedule of FIG. 2(c) shows only the departure point and the arrival point of each bus schedule, and stop locations between them are omitted. This simplified basic bus schedule for forming an operation plan will be used in the description of the action of the operation management device given below.

FIG. 3 is a diagram showing an example of the basic bus schedule. In FIG. 3, the basic bus schedule is shown as a table associating the stop location, the arrival time, and the departure time. The basic bus schedule of FIG. 3 includes a bus schedule ID for identifying each bus schedule shown in FIG. 2(b), a route ID, a node ID for indicating each stop location (node), and the departure time and the arrival time for each stop location. The route ID is used in a case where the actual bus schedule cannot be identified by only the bus schedule ID. For example, with respect to the bus route network of FIG. 2(a), if a bus schedule identified by the bus schedule ID indicates only the departure point A and the arrival point F, a plurality of actual bus schedules are conceivable (AEF, AEDF, etc.). The route ID is used in such a case to identify the bus schedule. Accordingly, the route ID does not have to be used in a case where a bus schedule may be uniquely identified by the bus schedule ID.

The vehicle information unit 12 stores vehicle information about an electric bus. The vehicle information may be stored in advance in the vehicle information unit 12, or may be updated based on information acquired by the vehicle information unit 12 from an electric bus at a predetermined timing. Also, in the case where non-electric vehicles are registered in the operation management device, vehicle information about the non-electric vehicles may also be stored. The vehicle information includes operation information of an electric bus, and battery information of a battery mounted on the electric bus.

FIG. 4 is a diagram showing an example of the operation information. As shown in FIG. 4, the operation information includes a vehicle ID for identifying each electric bus, the type of a registered vehicle, the status indicating the current state of an electric bus (running, charging, waiting, etc.), the node ID of the last stop location that an electric bus has passed, the distance (km) from the last stop location which has been passed and the current location of an electric bus, the latest location time, the node ID of the stop location that an electric bus is to pass next, the distance (km) from the current location of an electric bus to the next stop location to be passed, the latest SOC (%) of the battery mounted on an electric bus, and the like.

The type of a registered vehicle is used in a case where electric buses and non-electric vehicles are registered in the operation management device, and classification is performed such that the electric buses and the non-electric vehicles may be distinguished from each other. Also, in addition to the classification for distinguishing between electric buses and non-electric vehicles, classification according to the types of batteries mounted on the electric buses may also be performed. The latest location time is the time when the latest location information is acquired from an electric bus. The distance from the last stop location which has been passed to the current location of the electric bus, or the distance from the current location of the electric bus to the next stop location to be passed is calculated based on the location information acquired at the latest location time. The latest SOC (State of Charge) is the latest charge state of a battery acquired from an electric bus, and is expressed as a percentage (%) with respect to the effective capacity of the battery. Additionally, in the case where non-electric vehicles are registered in the operation management device, the operation information of the non-electric vehicles is also stored in the vehicle information unit 12 in the same manner as the operation information of electric buses. In this case, the latest SOC of a non-electric vehicle will be null.

FIG. 5 is a diagram showing an example of the battery information. As shown in FIG. 5, the battery information includes the vehicle ID of an electric bus, the initial capacity (kWh), the SOH (%), the lower limit of remaining energy (kWh), the upper limit of remaining energy (kWh), the maximum charge rate (kW), the maximum discharge rate (kW), and the like. The SOH (State of Health) indicates the percentage (%) of the chargeable amount of energy with respect to the initial capacity of the battery mounted on an electric bus. That is, the product of the initial capacity and the SOH is the effective capacity (kWh) of the battery. The lower limit of remaining energy and the upper limit of remaining energy are specified within the range of the effective capacity to reduce the rate of deterioration of the battery. In FIG. 5, the lower limit of remaining energy and the upper limit of remaining energy are specified by the amount of energy (kWh), but they may also be specified by the percentage (SOC) with respect to the effective capacity. The maximum charge rate and the maximum discharge rate are the maximum amount of power that can be charged or discharged with respect to the battery, and are specified in advance according to the type of the battery or the like to reduce the rate of deterioration of the battery.

The route information unit 13 stores route information about routes along which electric buses operate. The route information may be stored in advance in the route information unit 13, or may be updated based on the vehicle information acquired from the vehicle information unit 12. Also, the route information unit 13 may acquire the information from an external service provider that provides weather forecast or traffic information.

FIG. 6 is a diagram showing an example of the route information. As shown in FIG. 6, the route information includes the distance (km) between stop locations, an information update time, a required time between stop locations, energy consumption between stop locations, and the like. The route information unit 13 may update the required time and the energy consumption between stop locations based on the vehicle information. Also, the required time and the energy consumption between stop locations change according to dynamic factors such as the state of the road (traffic jam or the like), the property of the road (uphill or downhill), external environment (temperature, weather), the number of passengers, and the like, and the route information unit 13 may update the route information according to a change in these factors. Additionally, the energy consumption rate here is the average value of the amount of energy consumed per unit distance at the time of an electric bus operating along each route. Accordingly, the energy consumption rate may be calculated by dividing the amount of energy consumed at the time of an electric bus operating along each route by the distance of that route.

The charging equipment information unit 14 stores charging equipment information about the charging capacity of charging equipment installed at each charging station, and includes stationary battery information unit 141 for storing information about a stationary battery installed at a charging station, and supply power information unit 142 for storing information about power that is available from the power grid. The charging equipment information includes stationary battery information and supply power information.

The stationary battery information unit 141 stores the stationary battery information about a stationary battery. The stationary battery information may be stored in advance in the stationary battery information unit 141, or may be updated based on information acquired by the stationary battery information unit 141 from a stationary battery or the like at a predetermined interval. FIG. 7 is a diagram showing an example of the stationary battery information. As shown in FIG. 7, the stationary battery information includes a node ID for identifying a charging station where a stationary battery is installed, a battery ID for identifying the stationary battery, the initial capacity (kWh) of the stationary battery, the SOH (%), the lower limit of remaining energy (kWh), the upper limit of remaining energy (kWh), the maximum charge rate (kW), the maximum discharge rate (kW), remaining energy (kWh), and the like. In FIG. 7, one stationary battery is installed at each charging station, but a plurality of batteries may also be installed at the same charging station. In this case, the stationary battery information unit 141 may separately store the stationary battery information of each stationary battery, or may store information totaling the initial capacity and remaining energy in the stationary batteries installed at the same charging station as the stationary battery information of each charging station. The upper and lower limits of the remaining energy and the maximum charge/discharge rate are set in advance to reduce the deterioration of the battery.

The supply power information unit 142 stores supply power information about the energy (the amount of power) that is available from the power grid, and contracted power. The power information may be stored in advance in the supply power information unit 142 based on the details of the contract with the power grid, or may be updated based on a demand response (DR) issued from the power grid. FIGS. 8(a) and 8(b) are diagrams showing examples of the supply power information. The supply power information includes information about the energy that is available from the power grid and contracted power information.

As shown in FIG. 8(a), the energy information includes a node ID for identifying a charging station, a time when a use condition for each power level is applied, the electricity price (yen/kWh) and the amount of electricity (kWh) that is available at each power level, and the like. In FIG. 8(a), two power levels, power levels 1 and 2, are set with respect to the power level, but it is also possible to set one or three or more power levels. According to FIG. 8(a), a client of the power grid may use, at a charging station A, 250 kWh at a price of 25 yen per kWh from 0 :00 to 8 :00 (the power level 1), and an electricity price of 30 yen per kWh will be charged to use more energy (the power level 2). Then, when the amoun of electricity set by the power level 2 (350 kWh) is already used, electricity cannot be received from the power grid from 0 :00 to 8:00. Also, as shown in FIG. 8(b), the contracted power information includes a node ID for identifying a charging station, the contracted power (kW), and the like. The amount of electricity that is available according to each power level at each charging station is specified within the range of the amount of power that is available according to the contracted power. For example, according to FIG. 8(b), the contracted power at the charging station A is 200 kW, and thus, the amount of electricity that is available at the charging station A from 0 : 00 to 8 : 00 according to the contracted power is 1600 kWh (= 200 kW x 8h). Accordingly, the amount of electricity that is available at the charging station A from 0 :00 to 8 :00 at each power level is specified in the range of 1600 kWh or lower.

The plan storage unit 15 stores information about a vehicle allocation plan and a charge plan formed by the operation planning unit 10. FIG. 9 is a diagram showing an example of a vehicle allocation plan (a vehicle allocation list). As shown in FIG. 9, the vehicle allocation plan specifies allocation of electric buses to each bus schedule, and includes information for identifying each bus schedule specified by the basic bus schedule (the node ID, the arrival time, the departure time, etc.), a vehicle ID for identifying an electric bus allocated to each bus schedule, charging/non-charging at a stop location (charging : Y, non-charging : N), and the like. For example, in FIG. 9, an electric bus whose vehicle ID is 001 is allocated to a bus schedule AEDF according to which the electric bus operates in the order of stop locations A, E, D, and F. Additionally, a vehicle allocation plan that is shown as a table, as in FIG. 9, is referred to as a vehicle allocation list.

FIG. 10 is a diagram showing an example of a charge plan (a charge list). As shown in FIG. 10, the charge plan includes a vehicle ID for identifying an electric bus, a node ID for identifying a charging station where an electric bus is to be charged, an expected arrival time when an electric bus is expected to arrive at a charging station, an expected departure time when an electric bus is expected to leave a charging station, an expected remaining energy (kWh) of an electric bus at a time of arrival at a charging station, a target remaining energy (kWh), and the like. The target remaining energy is a target value of the remaining energy after an electric bus has been charged at a charging station. A charge plan that is shown as a table, as in FIG. 10, is referred to as a charge list.

The re-planning determination unit 16 determines whether or not to re-plan the current operation plan, when a notification regarding a re-planning request is received from the re-planning request unit 17 or at regular time intervals. Determination regarding re-planning by the re-planning determination unit 16 uses dynamic factors that change during operation of an electric bus, such as delay information or the remaining energy of an electric bus in operation, the energy that is available at a charging station, the remaining energy in a stationary battery, the energy consumption rate or the required time between stop locations, and the like. In the case where the re-planning determination unit 16 determines that re-planning is to be performed, the operation planning unit 10 forms an operation plan again.

The re-planning request unit 17 notifies the re-planning determination unit 16 of a re-planning request for starting determination regarding re-planning. The re-planning request unit 17 detects a change in a dynamic factor, such as a change in the energy that is available at a charging station, and issues the re-planning request. As shown in FIG. 1, the re-planning request unit 17 may be independently provided, or the vehicle information unit 12, the route information unit 13, the charging equipment information unit 14 or the like may function as the re-planning request unit 17. For example, in the case where the vehicle information unit 12 is to function as the re-planning request unit 17, the vehicle information unit 12 may issue the re-planning request based on the delay information or the remaining energy of the electric bus in operation. Also, in the case where the route information unit 13 is to function as the re-planning request unit 17, the route information unit 13 may issue the re-planning request by detecting a change in the energy consumption or in the required time between stop locations. Furthermore, in the case where the charging equipment information unit 14 is to function as the re-planning request unit 17, the charging equipment information unit 14 may issue the re-planning request by detecting a change in the energy that is available at a charging station or in the remaining energy in a stationary battery.

Now, FIG. 11 is a diagram showing hardware of the operation management device. This operation management device may be realized by using a computer device as basic hardware. As shown in FIG. 11, the computer device includes a CPU 111, an input unit 112, a display unit 113, a communication unit 114, a main storage unit 115, and an external storage unit 116, and these are connected with one another by a bus 117 in a manner capable of communication.

The input unit 112 includes an input device such as a keyboard, a mouse or the like, and outputs an operation signal according to an operation of the input device to the CPU 111. The display unit 113 includes a display such as an LCD (Liquid Crystal Display), a CRT (Cathode Ray Tube) or the like. The communication unit 114 includes wireless or wired communication unit, and performs communication according to a predetermined communication method. The external storage unit 116 includes a storage medium or the like, such as a hard disk, a memory device, a CD-R, a CD-RW, a DVD-RAM, or a DVD-R. The external storage unit 116 stores control programs for causing the CPU 111 to perform the processes of the operation management device. Also, data of each storage unit provided to the operation management device is stored therein. The main storage unit 115 develops a control program stored in the external storage unit 116 under the control of the CPU 111, and stores data necessary for execution of the program, data generated by execution of the program, and the like. The main storage unit 115 includes an arbitrary memory such as a non-volatile memory.

Each functional configuration of the operation management device as described above is realized by the CPU executing the control program. The control program may be installed in advance in the computer device. Also, a control program stored in a storage medium such as a CD-ROM, or a control program that is distributed over a network may be installed in the computer as appropriate and be used. Additionally, a configuration not including the input unit 112 and the display unit 113 is also allowed.

Next, an outline of an operation planning process according to the present embodiment will be given with reference to FIGS. 12(a), 12(b) and 13. FIGS. 12(a) and 12(b) are diagrams for describing an operation planning process, and FIG. 13 is a flow chart showing the operation planning process. Additionally, each of the basic bus schedules shown in FIGS. 12(a) and 12(b) is the simplified basic bus schedule described above (see FIG. 2(c)). In the following, a departure point and an arrival point of a basic bus schedule will be referred to as a departure point i and an arrival point i, respectively, according to an assigned number i, and the bus schedule from the departure point i to the arrival point i will be referred to as a bus schedule i.

First, the operation planning unit 10 calculates, using the route information, the required energy at the time of an electric bus operating from a departure point to an arrival point along a route that is specified by a bus schedule (step S101). The required energy is the amount of energy consumed at the time of operation of an electric bus. In the following, the required energy at the time of an electric bus operating from a departure point to an arrival point along a route specified by a bus schedule will be referred to as the required energy of the bus schedule.

Next, a list of electric vehicles that can be allocated is generated using the vehicle information or the like (step S102). The list of electric vehicles that can be allocated is a list collecting the battery information and the location information of electric buses that can be allocated to each bus schedule, and is used in the allocation of vehicles to each bus schedule in step 104 described below. At the time of re-planning of an operation plan, the list of electric vehicles that can be allocated may be generated by using an existing vehicle allocation list (vehicle allocation plan) or an existing charge list (charge plan).

Next, bus schedules are connected by connecting the arrival points and the departure points of the bus schedules specified by the basic bus schedule, and one or more candidate solutions for a connection method are generated (step S103). That is, a candidate solution specifies a set of one or more bus schedules according to which one electric bus operates. An arrival point and a departure point may be connected in the case where the arrival time at the arrival point is earlier than the departure time from the departure point and the arrival point and the departure point are at the same stop location.

FIG. 12(a) shows two examples of the candidate solution (a candidate solution 1, a candidate solution 2). According to the candidate solution 1, a bus schedule 1, a bus schedule 2, and a bus schedule 4 are connected. In this case, one electric bus operates according to the bus schedules 1, 2, and 4, and another electric bus operates according to a bus schedule 3. According to the candidate solution 2, the bus schedule 1 and the bus schedule 3 are connected, and the bus schedule 2 and the bus schedule 4 are connected. In this case, one electric bus operates according to the bus schedules 1 and 3, and another electric bus operates according to the bus schedules 2 and 4. In this manner, candidate solutions for a connection method specify the connection methods of the bus schedules.

Next, the operation planning unit 10 allocates an electric bus to each bus schedule of the candidate solutions which have been generated (step S104), and generates a vehicle allocation list for each candidate solution. The same electric bus is allocated to a plurality of bus schedules that are connected in a candidate solution. As shown in FIG. 12(b), according to the candidate solution 1, an electric vehicle 2 is allocated to the bus schedule 1, and an electric vehicle 3 is allocated to the bus schedule 3. Since the bus schedules 2 and 4 are connected to the bus schedule 1, the electric vehicle 2 is allocated thereto as with the bus schedule 1. Also, according to the candidate solution 2, the electric vehicle 1 is allocated to the bus schedule 1, and an electric vehicle 4 is allocated to the bus schedule 2. The bus schedule 3 is connected to the bus schedule 1, and thus, the electric vehicle 1 is allocated thereto, and the bus schedule 4 is connected to the bus schedule 2, and thus, the electric vehicle 4 is allocated thereto.

At the time of allocating an electric bus to a bus schedule, the operation planning unit 10 takes into account the effective capacity and the remaining energy of the battery of the electric bus. Specifically, each bus schedule has allocated thereto an electric bus that can be charged with the required amount of charging energy at a charging station. The required amount of charging energy is the minimum amount of charging energy that enables the electric bus to operate according to the bus schedule without running out of energy. In the case where the effective capacity of the electric bus is smaller than the required amount of charging energy of a bus schedule, the electric bus cannot be charged with the required amount of charging energy, and is highly likely to run out of energy while operating along the route specified by the bus schedule. Accordingly, the operation planning unit 10 allocates an electric bus whose effective capacity is greater than the required amount of charging energy of the bus schedule to each bus schedule.

Furthermore, the operation planning unit 10 evaluates the charging feasibility of each candidate solution to which an electric bus is allocated (step S105). That is, whether or not an electric bus that operates along a route specified by a plurality of connected bus schedules may be charged at each charging station such that the remaining energy will be equal to or greater than a predetermined amount of energy (charging feasibility) is determined, and the charging feasibility of all of the plurality of connected bus schedules is evaluated based on the determination result. The predetermined amount of energy is the lower limit of the remaining energy of the battery of the electric bus, for example.

Also, with respect to a charging station where charging is determined to be possible in the determination described above regarding the charging feasibility, the amount of charging energy at the charging station is calculated (step S105), and a charge list is generated. The amount of charging energy at a charging station is the amount of energy charged between the arrival time and the departure time in an electric bus at a charging station where the arrival point and the departure point of connected bus schedules are located. For example, according to the candidate solution 1 in FIG. 12(b), the amount of charging energy at the connection portion of the bus schedule 1 and the bus schedule 2 is 10 kWh, and this is the amount of energy that is charged in an electric bus at a charging station F from the arrival time at an arrival point 1 to the departure time from a departure point 2. In the following, the connection portion of bus schedules where an electric bus is to be charged, that is, a connection portion of an arrival point and a departure point, will be referred to as a charging point.

After vehicle allocation and calculation of the amount of charging energy with respect to each candidate solution generated in step S103 are ended, whether or not a termination condition is satisfied is determined (step S106). As the termination condition, presence of a candidate solution among the generated candidate solutions with a smaller number of allocated electric buses than the number of electric buses that can be allocated, or presence of a candidate solution according to which electric buses may be charged in such a way that a predetermined constraint is met at every charging point, may be used. Also, an upper limit, such as the number of generated candidate solutions, the processing time, the number of iterations of the process, or the like may be used as the termination condition.

In the case where the termination condition is not satisfied in step S106 (NO in step S106), one or more new candidate solutions are generated (step S107), and the process returns to step S104. On the other hand, in the case where the termination condition is satisfied in step S106 (YES in step S106), a candidate solution with the highest evaluation value among the candidate solutions which have been generated is selected, and the vehicle allocation list and the charge list generated for the candidate solution are output (step S108).

Evaluation of the candidate solutions may be performed based on a charging feasibility score that is calculated for each candidate solution according to the evaluation of the charging feasibility. The charging feasibility score is an evaluation value that is calculated according to the number of charging points where electric buses may be charged in such a way that a predetermined constraint is met. In the present embodiment, the minimum value of the charging feasibility score is zero, and the maximum value is the number of charging points of each candidate solution. A candidate solution according to which an electric bus may be charged at every charging point in such a way that a predetermined constraint is met, that is, a candidate solution whose charging feasibility score matches the number of charging points, may be selected as the candidate solution with the highest evaluation. Alternatively, a candidate solution whose number of allocated electric buses is the smallest may be selected as the candidate solution with the highest evaluation. Moreover, the charging feasibility score and the number of allocated electric buses may be used in combination.

Of the processes of steps S101 to S108 described above, the vehicle allocation process in step S104 may be performed by the vehicle allocation unit 101, evaluation of the charging feasibility in step S105 may be performed by the charging feasibility evaluation unit 104, calculation of the amount of charging energy may be performed by the charging amount calculation unit 103, and the remaining steps including generation of a candidate solution for a connection method in step S103 may be performed by the bus schedule connection unit 102.

In the following, details of each step from step S101 to step S105 of the operation planning process described above will be given.

(Step S101)

The calculation method of the required energy of each bus schedule in step S101 will be described with reference to FIGS. 14 and 15. The required energy of a bus schedule may be calculated based on the distance between the stop locations (km) and the energy consumption rate (kWh/km). The operation planning unit 10 acquires route information from the route information unit 13, and calculates the required energy between the stop locations included in the bus schedule for which the required energy is to be calculated, that is, the required energy of each path. The required energy of each path may be calculated by the distance between the stop locations χ energy consumption ratex safety parameter a. Then, the required energy of each path which has been calculated is added up, and the required energy of the bus schedule is calculated. Accordingly, the required energy of a bus schedule may be calculated by the following formula.

[Math. 1]

Required energy of bus schedule = distance (node,, node_i+i) x energy consumption rate (node,, n0¾e_i+i) x a

Here, n is the number of connections of stop locations ( = the number of connected stop locations - 1). For example, in the case of the bus schedule of FIG. 14, the required energy of the bus schedule is 42.02 kWh. In FIG. 14, the safety parameter is 1.1. This safety parameter a is a parameter for adding a surplus amount of power to the required energy of a bus schedule, and is set in the range of a > 1. In the following, the safety parameter a will be referred to simply as a parameter a. By calculating the required energy of the bus schedule which is increased in advance by using the parameter a, and performing vehicle allocation or calculation of the amount of charging energy based on this required energy, the possibility of an electric bus running out of energy may be reduced. Furthermore, by changing the parameter according to a dynamic factor as described above, appropriate required energy according to the dynamic factor may be calculated. As shown in FIG. 15, the operation planning unit 10 generates a required energy list for each bus schedule specified by the basic bus schedule.

(Step S102)

The generation process of the list of electric vehicles that can be allocated in step S102 will be described with reference to FIGS. 16, 17, 18(a) and 18(b). FIG. 16 is a flow chart showing the generation process of the list of electric vehicles that can be allocated. First, the operation planning unit 10 acquires the vehicle information of electric buses, the route information, the vehicle allocation list, the charge list, and the like (step S1021). At the time of creating a first operation plan, the vehicle allocation list and the charge list are empty. Vehicle information about those vehicles whose statuses are waiting/running/charging are extracted from the vehicle information which have been acquired (step S1022). In the case where non-electric vehicles are registered in the operation management device, vehicle information of the non-electric vehicles may be removed by extracting vehicle information whose type is EV. Next, the effective capacity of each electric bus is calculated based on the initial capacity and the SOH included in the vehicle information (step S1023). The effective capacity may be calculated by the following formula. [Math. 2]

Effective capacity (kWh) = Initial capacity (kWh) χ SOH (%)

Next, the status of each electric bus is determined (step S1024), and in the case where the status of the electric bus is waiting, the remaining energy is calculated (step S1025). The remaining energy may be calculated by the following formula based on the latest SOC included in the vehicle information and the effective capacity calculated in step S1023.

[Math. 3]

Remaining energy (kWh) = Effective capacity (kWh) χ latest SOC (%)

After the remaining energy is calculated, a list of electric vehicles that can be allocated as shown in FIG. 17 is generated based on the information extracted from the vehicle information of electric buses (the node ID, the vehicle ID, the lower limit of the remaining energy, the maximum charge rate, etc.) and the effective capacity and the remaining energy which have been calculated (step S1028). The ID of the last node which has been passed (the ID of a node in waiting) may be used as the node ID.

In step S1024, the remaining energy is set for an electric bus whose status is charging (step S1026). In the case where operation of the electric bus is already started, and the operation plan is to be re-planned, the target remaining energy (kWh) may be extracted from the charge plan, and be set as the remaining energy. Also, in the case of creating the first operation plan, the amount of energy that is planned to be charged in the electric bus before operation is started may be set as the remaining energy.

In step S1024, the remaining energy at a charging station where an electric bus is to arrive next is estimated for an electric bus whose status is running (step S1027). A case where an electric bus is running is a case where the operation of the electric bus is already started, and the operation plan is to be re-planned. In this case, the remaining energy of the electric bus is estimated based on the vehicle information, the route information, and the charge list. The remaining energy may be estimated by subtracting the required energy between the latest location and the next charging station from the remaining energy at the latest location.

Here, the estimation method of the remaining energy will be concretely described with reference to FIGS. 18(a) and 18(b). In FIGS. 18(a) and 18(b), it is assumed that an electric bus is operating according to a bus schedule of stopping at stop locations A, B, C, D, and F in this order, and is heading for a charging station F. In FIG. 18(a), it is assumed that the electric bus has just left a charging station A, and that the remaining energy at the time of departure is 50 kWh. In this case, by subtracting the required energy of the bus schedule (42.02 kWh) calculated based on the route information from the remaining energy at the time of departure (50 kWh), the remaining energy at the charging station F (7.98 kWh) may be estimated. On the other hand, in FIG. 18(b), the electric bus is running from the stop location C toward the stop location D. In this case, by subtracting the required energy from the latest location to the stop location D ((9 km - 2 km) 1.1 kWh/km) and the required energy of the path between the stop locations D and F (7 km χ 1.3 kWh/km) from the remaining energy at the latest location (45 kWh χ 60%), the remaining energy at the charging station F (8.52 kWh) may be estimated.

(Step S103)

The generation method of a candidate solution of a connection method in step S103 will be described with reference to FIGS. 19(a) to 19(b). FIGS. 19(a) to 19(c) are diagrams for describing the generation method of a candidate solution. The operation planning unit 10 encodes the arrival point and the departure point of each bus schedule to generate one or more candidate solutions for a connection method based on the basic bus schedule.

First, the operation planning unit 10 generates a candidate departure point list of candidate departure points to which each arrival point can be connected based on the basic bus schedule (see FIG. 19(a)). As shown in FIG. 19(b), the candidate departure point list is made up of arrival points arranged in the ascending order of the arrival time, candidate departure points which are the departure points to which arrival points can be connected, the charging station where each arrival point is located, and the arrival point index. In the candidate departure point list, the candidate departure points are all the departure points of departure after the arrival time at an arrival point. Also, it is possible that an arrival point is not connected to any departure point, and a candidate departure point -1 is given to each arrival point as a provisional candidate departure point expressing such a case. Accordingly, for example, the candidate departure points of an arrival point 1 are departure points 4, 6, 7, and -1. An arrival point with no candidate departure point to which the arrival point can be connected (for example, arrival points 7, 8, and 9) are deleted from the candidate departure point list.

Next, a candidate solution is generated based on the candidate departure point list. A candidate solution is generated by selecting one candidate departure point for each arrival point index, and arranging the candidate departure points in the order of the arrival point indices. Accordingly, the length of a candidate solution is the number of arrival points for which there is a candidate departure point to which the arrival point can be connected (the number of arrival point indices), and a j-th value of a candidate solution corresponds to a candidate departure point of an arrival point index j. For example, the candidate solution of FIG. 19(c) is 589476, and the third value of the candidate solution (9) is the candidate departure point of the arrival point index 3. That is, this candidate solution indicates that the arrival point 6 and the candidate departure point 9 are connected.

Selection of a candidate departure point for each arrival point index is random. However, since the same departure point cannot be connected to a plurality of arrival points, there is a constraint that candidate departure points other than the candidate departure point -1 may be selected just once in the same candidate solution. Moreover, the candidate departure point -1 may be selected several times in the same candidate solution.

(Step S104)

The vehicle allocation method in step S104 will be described with reference to FIGS. 20(a), 20(b), 21(a), and 21(b). The operation planning unit 10 allocates electric buses to one or more candidate solutions generated in step S103, and generates the vehicle allocation list.

First, the operation planning unit 10 decodes a candidate solution using the basic bus schedule. FIGS. 20(a) and 20(b) are diagrams for describing a decoding method of a candidate solution. The operation planning unit 10 generates an arrival point list by extracting arrival points corresponding to the arrival point indices from the candidate departure point list. As shown in FIG. 20(a), in the arrival point list, arrival points are arranged in the ascending order of arrival time.

Next, the generated arrival point list and a candidate solution are compared, and the arrival point of an arrival point index j in the arrival point list and the candidate departure point of the arrival point index j of the candidate solution are connected, and a charging point connection graph is generated. In the charging point connection graph in FIG. 20(b), bus schedules 1, 4, and 8 are connected, bus schedules 2, 5, 6, and 9 are connected, and bus schedules 3 and 7 are connected. The connection portion of the bus schedules is a charging point where an electric bus may be charged. In the following, the connection portion of a bus schedule X and a bus schedule Y that are connected will be referred to as a charging point X, Y.

Next, a vehicle is allocated to each bus schedule connected in the charging point connection graph. FIGS. 21(a) and 21(b) are diagrams for describing the vehicle allocation method. The operation planning unit 10 calculates, based on the route information, the total of the distances of connected bus schedules and the total of the required energy of the bus schedules. For example, according to FIG. 21(a), the total of the distances of the bus schedules 2, 5, 6, and 9 is 155 km, and the total of the required energy of the bus schedules is 90 kWh. Next, the connected bus schedules are sorted in the descending order of the total of the required energy of the bus schedules which has been calculated. That is, the connected bus schedules are sorted in the order from the largest total of the required energy of the bus schedules. This sorting is performed for each charging station at the departure point of the first of the connected bus schedules. According to FIG. 20(a), the departure points of the bus schedule 1 and the bus schedule 3 are the charging station A, and the departure point of the bus schedule 2 is the charging station F. Accordingly, sorting of the connected bus schedules is performed for the bus schedules 1, 4, and 8 and the bus schedules 3 and 7, and for the bus schedules 2, 5, 6, and 9. The total of the required energy of the bus schedules is larger for the bus schedules 1, 4, and 8 than for the bus schedules 3 and 7, and thus, the bus schedules 1, 4, and 8 are sorted to come before the bus schedules 3 and 7 (see FIG. 21(a)).

Furthermore, the required amount of charging energy is calculated for each charging point of the connected bus schedules. The required amount of charging energy is the minimum amount of charging energy that allows an electric bus to operate along the route specified by the bus schedules without running out of energy. The required amount of charging energy at a charging point p, q between a bus schedule p and a bus schedule q may be calculated by subtracting the remaining energy of an electric bus at an arrival point p of the bus schedule p from the required energy of the bus schedule q.

[Math. 4]

Required amount of charging energy (charging point p, q) (kWh) = Required energy (bus schedule q) (kWh) - remaining energy (arrival point p) (kWh)

For example, the required amount of charging energy at a charging point 1, 4 of the bus schedules 1, 4, and 8 in FIG. 21(a) may be calculated in the following manner.

[Math. 5]

Required amount of charging energy (charging point 1, 4)

= Required energy (bus schedule 4) - remaining energy (arrival point 1)

= Required energy (bus schedule 1) + required energy (bus schedule 4) - remaining energy (departure point of bus schedule

1) If it is assumed that an electric bus departs in a fully charged state, the remaining energy at the departure point of the bus schedule 1 is the effective capacity of the electric bus. Also, the required amount of charging energy at the charging point 4, 8 of the bus schedules 1, 4, and 8 may be calculated in the following manner.

[Math. 6]

Required amount of charging energy (charging point 4, 8)

= Required energy (bus schedule 8) - remaining energy (arrival point of bus schedule 4)

= Required energy (bus schedule 1) + required energy (bus schedule 4) + required energy (bus schedule 8) - remaining energy (departure point of bus schedule 1) - amount of charging energy (charging point 1, 4) Here, as the amount of charging energy at the charging point 1, 4, the required amount of charging energy at the charging point 1, 4 may be used. In this manner, the required amount of charging energy at each charging point of the connected bus schedules is calculated, and the maximum required amount of charging energy which is the maximum amount of the required amounts of charging energy of the connected bus schedules is extracted. As shown in FIG. 21(a), in the case of the bus schedules 1, 4, and 8, the maximum required amount of charging energy is 35 kWh at the charging point 4, 8.

Furthermore, a required charge rate is calculated based on the required amount of charging energy which has been calculated. A required charge rate is the minimum charge rate for charging the required amount of charging energy at a charging point, and the required charge rate at the charging point p, q may be calculated by dividing the required amount of charging energy at the charging point p, q by a chargeable period. A chargeable period is a period between the arrival time at the arrival point p to the departure time at the departure point q, that is, a period corresponding to all or a part of the stop time at the charging point. In the case where the chargeable period is the stop time, the required charge rate may be calculated by the following formula.

[Math. 7]

Required charge rate (charging point p, q) (kW) = Required amount of charging energy (charging point p, q) (kWh) x 3600 / [departure time (bus schedule q) (sec) - arrival time (bus schedule p) (sec)]

The maximum required charge rate which is the ^"maximum rate among the required charge rates is extracted from the required charge rates of the charging points. For example, the maximum required charge rate of the bus schedules 1, 4, and 8 is 90 kW (see FIG. 21(a)). Additionally, the required charge rate is dependent on the stop time at each charging point, and the required charge rate at a charging point with the maximum required amount of charging energy is not always the maximum required charge rate.

Electric buses satisfying the following conditions are allocated to the connected bus schedules based on the maximum required amount of charging energy and the maximum required charge rate which have been calculated in the above manner, and the vehicle allocation list is generated. [Math. 8]

1. Effective capacity (electric bus) (kWh) > Maximum required amount of charging energy (kWh)

2. Maximum charge rate (electric bus) (kW) > Maximum required charge rate (kW)

By allocating an electric bus satisfying such conditions, an electric bus which can be charged in such a way that the electric bus will not run out of energy during operation along a route specified by a bus schedule may be allocated to each bus schedule. FIG. 21(b) is a diagram showing electric buses which have been allocated.

Additionally, in the case where there are several electric buses that satisfy the conditions above, the vehicles are allocated in the descending order of SOH. That is, an electric bus with a high SOH is allocated to a set of bus schedules whose total of the required energy of the bus schedule is greater. The required energy of each bus schedule changes according to a dynamic factor (external environment, property of the road, etc.), and, for example, the required energy of a bus schedule of climbing a long uphill during a morning rush hour is high. On the other hand, the required energy of a bus schedule with a short distance is low. Thus, by allocating an electric bus with a higher SOH to a bus schedule with higher required energy, and allocating an electric bus with a lower SOH to a bus schedule with lower required energy, deterioration of the batteries of the electric buses may be suppressed with the dynamic factor taken into account. Additionally, the average or the total of the required energy per unit distance (for example, 1 km) may also be used instead of the total of the required energy of the bus schedules. Also, in the case where the initial capacities of the batteries of the electric buses are the same, the effective capacity may be used as a reference instead of SOH.

In the vehicle allocation described above, in the case where there is no electric bus that satisfies the conditions, but there is a non-electric bus that may be allocated, the non-electric vehicle may alternatively be allocated. In the case where there is not even a non-electric vehicle that may be allocated, the vehicle allocation is a failure, and the vehicle allocation process for the candidate solution is ended, and vehicle allocation for the next candidate solution is performed. When the vehicle allocation process described above has been performed for all the candidate solutions generated in step S103, the operation planning process proceeds to step S105.

(Step S105)

Charging feasibility evaluation and calculation of the amount of charging energy in step S105 will be described with reference to FIGS. 22 to 30. The operation planning unit 10 evaluates the charging feasibility for one or more candidate solutions with respect to which vehicle allocation has been performed in step S104, and calculates the amount of charging energy for a candidate solution according to which charging is possible. In the following, the charging feasibility evaluation method and the calculation method of the amount of charging energy for each candidate solution to which vehicle allocation has been performed will be described.

First, the charging feasibility evaluation process for each candidate solution will be described with reference to FIG. 22. FIG. 22 is a flow chart showing the charging feasibility evaluation process (hereinafter referred to simply as "evaluation process"). The operation planning unit 10 acquires a candidate solution, the candidate departure point list, the vehicle allocation list, the required energy list, the plan starting time Ts and the plan ending time Te (see FIGS. 2(a) to 2(c)), and the like (step S10501).

Next, the stationary battery information, the supply power information, the battery information, and the like are acquired (step S10502), and the charging feasibility score, which is the evaluation value of the charging feasibility, is set to zero (step S10503). Next, based on the supply power information which has been acquired, supply power P_i(1(t) (kW) that is available from the power grid at the power level 1 at a time t, and supply power Pi,2( ) (kW) that is available from the power grid at the power level 2 at the time t are calculated (step S10504). The supply power Pi,i(t) and Pi,₂(t) may be calculated in the following manner.

[Math. 9]

Ι ,ί -r S,...,l2

Here, i is the node ID of a charging station, s is the sampling interval, Ej,i(ti:t2) is the amount of supply electricity (kWh) from a time ti to a time t₂ at the power level 1, and Ei,2(ti : t₂) is the amount of supply electricity (kWh) from the time ti to the time t₂ at the power level 2. For example, in the case where energy information (supply power information) shown in FIG. 23(a) is acquired, the supply power from 7:00 (t_x) to 7:59 (t₂) is calculated as shown in FIG. 23(b). In FIG. 23(b), the sampling interval s is one minute, but the sampling interval s is not limited thereto, and may be arbitrarily set in units of seconds or minutes.

Next, the arrival point list is generated (step S10505). The arrival point list includes arrival points arranged in the ascending order of time from the plan starting time Ts to the plan ending time Te, and may be generated based on the basic bus schedule (see FIG. 20(a)). In the case where the basic bus schedule of FIG. 24(a) is acquired, the arrival point list shown in FIG. 24(b) is generated by arranging the arrival points from the earliest arrival time.

When the arrival point list is generated, an arrival point

Ta is acquired based on the ascending order of time (step S10506). In the case of the arrival point list of FIG. 24(b), an arrival point 1 is acquired as the first arrival point Ta. In the case where an arrival point Ta is not acquired (NO in step S10507), that is, in the case where the evaluation process is completed for all the arrival points in the arrival point list of a candidate solution for which the evaluation process is being performed, the operation planning unit 10 ends the evaluation process, saves the charging feasibility score and the charge list of the candidate solution (step S10514), and performs the evaluation process for the next candidate solution. In the case where there is no more candidate solution, that is, in the case where the evaluation process is completed for all the candidate solutions for which vehicle allocation has been performed in step S104, the process proceeds to the determination process in step S106.

In the case where an arrival point Ta is acquired (YES in step S10507), whether or not there is a candidate departure point Td that is connected to the arrival point Ta is determined (step S10508). In the case where there is no candidate departure point Td that is connected to the arrival point Ta (NO in step S10508), the process returns to step S10506, and the next arrival point Ta is acquired. A case where there is no candidate departure point Td is a case where the arrival point Ta is the last arrival point of a series of connected bus schedules, such as the arrival point 8 in FIG. 20(b).

In the case where there is a candidate departure point Td (YES in step S10508), the required energy Ereq (kWh) of the bus schedule starting from the candidate departure point Td is acquired from the required energy list (step S10509). In the following, a bus schedule starting from a departure point X will be expressed as a "bus schedule of a departure point X", and a bus schedule ending at an arrival point Y will be expressed as a "bus schedule of an arrival point Y".

Next, based on the required energy of the bus schedule which has been acquired, whether or not charging of a predetermined amount of energy from the arrival time at the arrival point Ta to the departure time at the candidate departure point Td is possible is determined (step S10510). The details of determination of the charging feasibility will be given below. In determination of the charging feasibility, if charging is determined to be not possible (NO in step S10510), the process proceeds to step S10514, and the evaluation process for this candidate solution is ended. On the other hand, in the case where it is determined in the determination of the charging feasibility that charging is possible (YES in step S10510), the charging feasibility score is incremented by one (step S10511).

Next, the amount of energy to be charged between the arrival point Ta and the candidate departure point Td is calculated (step S10512), and the supply power Pi,i(t), Pi,2(t), and the remaining energy in the stationary battery are updated (step S10513), and the process returns to step S10506 and the next arrival point Ta is acquired.

In the following, determination of the charging feasibility

(step S10510), calculation of the amount of charging energy (step S10512), updating of the supply power Pi,i(t), Pj,₂(t) (step S10513), and updating of the remaining energy in a stationary battery (step S10513) will be described in detail.

First, the details of determination of the charging feasibility (step S10510) will be described with reference to FIGS. 25 and 26. FIG. 25 is a flow chart showing the determination process of the charging feasibility. The operation planning unit 10 first acquires an arrival point Ta and a candidate departure point Td (step S401), and acquires the supply power Pi,i(t), Pj,₂(t), the sampling interval s (sec), the stationary battery information, the lower limit of the remaining energy EVIow of an electric bus (battery information), and the like (step S402). The sampling interval s may be arbitrarily set.

Next, the arrival time at the arrival point Ta is set as the starting time ts, and the departure time from the candidate departure point Td is set as the ending time te (step S403), and the supply power P(t) is set to the supply power P,,i(t) at the power level 1 (step S404). Then, the amount of supply energy Eg (kWh) that is to be supplied by the power grid from the starting time ts to the ending time te is calculated based on each of the parameters which have been set (step S405) . The amount of supply energy Eg may be calculated by the following formula .

[Math . 10]

le

Amount of supply energy E_g =∑P(t) x s / 3600

t=ts

The amount of supply energy Eg (kWh) that is calculated here is the energy that is available from the power grid from the starting time ts to the ending time te to charge an electric bus. Also, the amount of energy that is available from the stationary battery from the starting time ts to the ending time te is calculated (steps S406 to S408) .

First, by using the node ID of the arrival point Ta, the stationary battery information of a stationary battery SSB that can be used at the arrival point Ta (charging station) is acquired from the stationary battery information (step S406) . Next, an arrival point Tap immediately preceding the arrival point Ta is extracted from the arrival appoint list (step S407) . The arrival point Tap is the closest arrival point among the arrival points whose arrival times are before that of the arrival point Ta and whose node IDs are the same as that of the arrival point Ta . For example, in the arrival point list of FIG. 24(b), if the arrival point Ta is the arrival point 5, the arrival point Tap is the arriva l point 3.

The remaining energy E_SSB (kWh) in the stationary battery SSB at the arrival time at the arrival point Ta for a case where the stationary battery SSB is charged with the supply power at the power level 1 from the arrival time at the arrival point Tap to the arrival time at the arrival point Ta is calculated based on the arrival point Tap which has been extracted (step S408) . The remaining energy E_SSB (kWh) that is calculated here is the amount of energy that is available from the stationary battery from the starting time ts to the ending time te to charge the electric bus. Additionally, the details of the calculation method of the remaining energy E_SSB will be given below.

The energy Eavail (kWh) that is available at the arrival point Ta from the starting time ts to the ending time te is calculated based on the amount of supply power Eg (kWh) and the remaining energy E_SSB (kWh) of the stationary battery SSB calculated in the above steps (step S409) . The energy Eavail may be calculated by the following formula .

[Math . 11 ] ^EamU = ^Eg ^{+ E}SSB

Next, the remaining energy EVrem of the electric bus at the arrival point Ta is estimated (step S410) . The remaining energy EVrem may be estimated by the same estimation method as in step S 1027. That is, it is estimated by subtracting the required energy of the bus schedule of the arrival point Ta from the remaining energy at the departure point of the bus schedule of the arrival point Ta (the bus schedule ending at the arrival point Ta) .

Next, whether or not the following condition is satisfied is determined based on the lower limit of remaining energy EVIow of the electric bus, the remaining energy (the estimated value) EVrem of the electric bus at the arrival point Ta, the required energy Ereq of the bus schedule of the candidate departure point Td (the bus schedule starting from the candidate departure point Td), and the energy Eavail that is available at the arrival point Ta (step S411) .

[Math . 12]

Eavail + EVrem - EVIow≥ Ereq

Since Ereq - Evrem is the required amount of charging energy, the above formula compares the available energy Eavail, and the total value of the lower limit of the remaining energy EVIow and the required amount of charging energy (Ereq - EVrem) . In the case where the above formula is not established (NO in step S411 ), the supply power P(t) is set to Pj_/2(t) (step S413), and the determination process returns to step S405. Then, the same determination process (steps S405 to S411 ) is performed for the power level 2. In the case where the above formula is not established in step S411 of the determination process for the power level 2 (NO in step S411 ), charging of a predetermined amount of energy is determined to be not possible (step S414), and the process returns to step S 10514 of the evaluation process, and the charging feasibility of the next candidate solution is evaluated . That is, the determination process of the charging feasibility is performed separately for the power level 1 and the power level 2. Additionally, in the case where three or more power levels are set, the determination process is performed for each of the power levels in the same manner.

On the other hand, in the case where the above formula is established (YES in step S411), the energy Eavail that is available at the arrival point Ta from the starting time ts to the ending time te is greater than the total value of the lower limit of the remaining energy EVIow and the required amount of charging energy. This means that the electric bus may be charged at the arrival point Ta in such a way that the remaining energy of the electric bus does not fall below the lower limit of the remaining energy EVIow during operation along the route specified by the bus schedule of the candidate departure point Td . In this case, the required amount of discharge energy Ess_Breq is calculated (step S415) ; that charging of a predetermined amount of power is possible is sent (step S416), and the process proceeds to step S10511 of the evaluation process.

The required amount of discharge energy Essereq here is the energy that is discharged from the stationary battery SSB from the arrival time at the arrival point Ta to the departure time at the candidate departure point Td to charge the electric bus, and may be obtained by the following formula . [Math. 13]

E_SSBreq = max(0, Ereq + EVlow-EVrem- Eg)

In the above formula, Ereq is the required energy of the bus schedule, EVIow is the lower limit of the remaining energy of the electric bus, EVrem is the estimated value of the remaining energy of the electric bus at the arrival point Ta, and Eg is the energy, calculated in step S405, that is available from the power grid from the arrival time at the arrival point Ta to the departure time at the candidate departure point Td. The required amount of discharge energy Essereq that is calculated is stored in the stationary battery information unit 141.

Next, the calculation process of the remaining energy Esse (kWh) of the stationary battery SSB in step S408 of the determination process described above will be described with reference to FIG. 26. FIG. 26 is a flow chart showing the calculation process of the remaining energy E_SSB of the battery SSB.

First, the stationary battery information of the stationary battery SSB, the supply power P(t), the sampling interval s (sec), and the like are acquired (step S501). The supply power P(t) is the supply power that is used in the determination process described above. The sampling interval s may be arbitrarily set. Also, the arrival time at the arrival point Tap is set as the starting time ts, and the arrival time at the arrival point Ta is set as the ending time te.

Next, the total (Ereqtotal) of the required amount of discharge energy Essereq of the stationary battery SSB from the starting time ts to the ending time te is calculated. It is possible to calculate Ereqtotal by acquiring the required amount of discharge energy Essereq calculated in step S415 described above from the stationary battery information unit 141.

Then, the remaining energy of the stationary battery SSB at the starting time ts is set to E_SSB, and a time variable t is set to the starting time ts (step S503). The remaining energy of the stationary battery SSB at the starting time ts may be acquired from the stationary battery information, for example.

Next, the charging power Psse(t) to the stationary battery SSB at each sampling interval is calculated, the amount of charging energy E(t) (kWh) to the stationary battery SSB at each sampling interval is calculated based on the charging power Psse(t) (kW) (step S504), and E_SSB (kWh) is updated (step S505) . The charging power Psse(t), the amount of charging energy E(t), and the E_SS_B may be calculated in the following manner (step S506) .

[Math . 14]

Pss_B(t) = min(P(t), maximum charge rate of stationary battery)

E(t) = P_SSB(t) x s/3600

ESSB = min(EssB + E(t), upper limit of remaining energy of stationary battery SSB)

As described above, the charging power PS_SB ) to the stationary battery SSB is assumed to be at or below the maximum charge rate of the stationary battery SSB, and the amount of charging energy E_SSB of the stationary battery SSB is assumed to be at or below the upper limit of the remaining energy of the stationary battery. With such constraints, the deterioration of the stationary battery may be suppressed .

Updating of the remaining energy E_SSB is repeated for each sampling interval (step S508) until the time variable t becomes greater than the ending time te (YES in step S504) or ESS_B becomes equal to or greater than the upper limit of the remaining energy of the stationary battery SSB (YES in step S507), and when one of the conditions is satisfied, E_SSB - Ereqtotal is returned, and the process proceeds to step S409 of the determination process (step S509) . In step S409, E_SS_B - Ereqtotal is used as the ESSB for calculating the energy Eavail that is available.

Next, calculation of the amount of charging energy in step 10512 of the evaluation process will be described with reference to FIG. 27. FIG. 27 is a flow chart showing a calculation process of the amount of charging energy at an arrival point Ta.

First, an arrival point Ta, a candidate departure point Td, the required energy Ereq of the bus schedule of the candidate departure point Td, the remaining energy EVrem of an electric bus, the lower limit of the remaining energy EVIow of the electric bus, the upper limit of the remaining energy EVhigh of the electric bus, the maximum charge rate P_Ev( ) of the electric bus, the energy Evail that is available at the arrival point Ta, the sampling interval s (sec), and the like are acquired (step S601). Each of the vehicle information mentioned above is the vehicle information of the electric bus that is allocated to the arrival point Ta. Also, the sampling interval s may be arbitrarily set.

Next, the arrival time at the arrival point Ta is set as the starting time ts, and the departure time at the candidate departure point Td is set as the ending time te (step S602), and the amount of energy Einmax (kWh) that can be charged in the electric bus from the starting time ts to the ending time te is calculated (step S603). The amount of energy Einmax is the amount of energy that can be charged in the electric bus in the case where charging is performed at the maximum charge rate from the starting time ts to the ending time te. The amount of energy Einmax may be calculated by the following formula.

[Math. 15]

Einmax = P_EV (t) (t_e - t_s) s/3600 ^'

The amount of charging energy is calculated in the following manner based on the required energy Ereq of the bus schedule of the candidate departure point Td, the energy Eavail that is available at the arrival point Ta, the upper limit of the remaining energy EVhigh of the electric bus, the remaining energy (estimated value) EVrem of the electric bus at the arrival point Ta, and the maximum amount of energy Einmax that can be charged in the electric bus (step S604) that are obtained in the above steps. [Math. 16]

Amount of charging energy = min (min (Ereq, Evail), EVhigh - EVrem, Einmax) The amount of charging energy calculated by the above formula is the amount of energy that can be charged in the electric bus at the arrival point Ta from the starting time ts to the ending time te at a charge rate at or below the maximum charge rate of the electric bus. Also, charging the electric bus with this amount of charging energy reduces the possibility of the remaining energy of the electric bus falling below the lower limit of the remaining energy EVIow even after operation along the route specified by the bus schedule of the candidate departure point Td. Furthermore, the remaining energy of the electric bus does not exceed the upper limit of the remaining energy after charging of the amount of charging energy. A charge list is generated based on the amount of charging energy calculated in the above manner.

In this manner, according to the present embodiment, it is possible to calculate the amount of charging energy that can be charged at a charging station, that is, the amount of charging energy that takes into account the charging load of the charging station. It is also possible to calculate the amount of charging energy that takes into account the remaining energy of the electric bus, according to which the possibility of running out of energy is low. It is also possible to calculate the amount of charging energy that takes into account the upper and lower limits of the remaining energy, the maximum charge rate, and the like set in advance for the electric bus. The upper and lower limits of the remaining energy and the maximum charge/discharge rates are battery life-related parameters set to suppress deterioration of the battery of the electric bus and to extend the life span, and by charging the amount of charging energy that takes into account these battery life-related parameters, the deterioration of the battery of the electric bus may be suppressed, and the life span of the battery may be extended .

Next, update of the supply power Pi,i(t), Pi,₂(t) in step S 10513 of the evaluation process will be described with reference to FIGS. 28, and 29(a) to 29(c) . FIG. 28 is a flow chart showing an updating process of supply power. Additionally, this updating is temporary updating for the evaluation process of each candidate solution and the calculation of the amount of charging energy, and the actual supply power is updated every time the evaluation process of a candidate solution is ended. That is, this updating is valid only while the evaluation process is being performed for the same candidate solution.

First, an arrival point Ta, a candidate departure point Td, the supply power level, the supply power Pi,i(t) , Pi,2(t), the sampling interval s (sec), and the like are acquired (step S701) . The sampling interval s may be arbitrarily set.

Next, the arrival time at the arrival point Ta is set as the starting time ts, and the departure time at the candidate departure point Td is set as the ending time te (step S702), and the supply power P(t) is set (steps S703 to S705) . The supply power P(t) that is set here is the supply power P(t) which is used at the time of determining that charging is possible in step S416 of the determination process described above (see FIG. 25) . Then, the amount of supply energy Eg is calculated based on the supply power P(t) which is set (step S706) . The calculation method of the amount of supply power Eg is the same as in step S405.

Next, the amount of supply energy Eg and the amount of charging energy calculated in step 10512 of the evaluation process are compared (step S707), and in the case where the amount of supply energy Eg is at or below the amount of charging energy (NO in step S707), the supply power P(t) after charging is set to zero (step S709), the supply power P(t) is updated (step S714), and the process proceeds to the updating process of the remaining energy of the stationary battery. Since the supply power P(t) is preferentially used for charging of the electric bus, in the case where the amount of supply energy Eg is at or below the amount of charging energy, all of the amount of supply energy Eg is used for charging the electric bus, and the shortfall of the amount of charging energy is charged from the remaining energy of the stationary battery.

In the case where the amount of supply energy Eg is greater than the amount of charging energy (YES in step S707), the amount of charging energy calculated in step 10512 of the evaluation process is set as the amount of energy E (step S708), and the average required charging power Pc(t) is calculated (step S710). The average required charging power Pc(t) is the average power that is supplied by the power grid to charge the electric bus with the amount of charging energy from the starting time ts (the arrival time at the arrival point Ta) to the ending time te (departure time at the candidate departure point Td). In FIG. 29(a), the amount of charging energy is the area of the portion surrounded by the thick line. The average required charging power Pc(t) may be calculated by the following formula.

[Math. 17]

Average required charging power Pc(t) = E x 3600/(te - ts) ^χ s)

Next, the insufficient amount of energy Einsuff is calculated (step S711). The insufficient amount of energy Einsuff is the amount of energy that falls short when performing charging with the average required amount of charging power Pc(t), due to the supply power P(t) being smaller than the average required charging power Pc(t). In FIG. 29(a), the insufficient amount of energy Einsuff is the area of the shaded portion on the left side. The insufficient amount of energy Einsuff may be calculated by the following formula.

[Math. 18]

te

Insufficient amount of energy Einsuff = ^max(0, c( - -P( ) ^x s /3600 t=ts

Furthermore, the surplus amount of energy Esurplus is calculated (step S712). The surplus amount of energy Esurplus is the amount of energy that is left over after charging by the average required charging power Pc(t), due to the supply power P(t) being greater than the average required charging power Pc(t). In FIG. 29(a), the surplus amount of energy Esurplus is the area of the shaded portion on the right side. The surplus amount of energy Esurplus may be calculated by the following formula.

[Math. 19]

Surplus amount Of energy Esurplus =∑max(0,P(t) - Pc(t)) x s/ 3600

Next, the supply power P(t)' from the starting time ts after charging of the electric bus with the amount of charging energy to the ending time te is calculated based on the insufficient amount of energy Einsuff and the surplus amount of energy Esurplus which have already been calculated (step S713). The amount of supply power P(t) ^' may be calculated by the following formula.

[Math. 20]

0 where P t)≤ Pc(t)

- Pc(t))(l - Einsuff I Esurplus) where P(t) > Pc(t)

As shown in FIG. 29(c), in a time range where the supply power P(t) is at or below the average required charging power Pc(t), it is assumed that all the supply power P(t) is used, and the P(t)' after charging is calculated to be 0 (kw). On the other hand, in a time range where the supply power P(t) is greater than the average required charging power Pc(t), the supply power P(t)' after charging is calculated by (P(t) - Pc(t)) x (1 - Einsuff/Esurplus). That is, as shown in FIG. 29(b), the supply power P(t)' is calculated as the power that is left over after performing charging with the surplus amount of energy Esurplus to make up for the insufficient amount of energy Einsuff.

Lastly, the supply power P(t) is updated to the supply power P(t)' which has been calculated (step S714), and the process proceeds to the updating process of the remaining energy of the stationary battery. Additionally, the amount of supply power P(t) that is updated is the supply power P(t) of the time range from the starting time ts to the ending time te at the power level set in steps S703 to S705.

Next, update of the remaining energy of the stationary battery in step S10513 of the evaluation process will be described with reference to FIG. 30. FIG. 30 is a flow chart showing an updating process of the remaining energy of a stationary battery. Additionally, this update is temporary update for the evaluation process of each candidate solution and calculation of the amount of charging energy, and the actual remaining energy is updated every time the evaluation process of a candidate solution is ended. That is, this update is valid only while the evaluation process is performed for the same candidate solution.

First, an arrival point Ta, a departure point Td, an arrival point list, stationary battery information, supply power Pi,i(t), the required amount of discharge energy Essereq from a stationary battery SSB, and the like are acquired (step S801). Next, the stationary battery information of a stationary battery SSB that can be used at the arrival point Ta is acquired from the stationary battery information by using the node ID of the arrival point Ta (step S802), an arrival point Tap immediately preceding the arrival point Ta is extracted from the arrival point list (step S803),^" and the remaining energy Esse (kWh) of the stationary battery SSB that can be used at the arrival point Ta where the stationary battery SSB is charged with the supply power at the power level 1 from the arrival time at the arrival point Tap to the arrival time at the arrival point Ta is calculated (step S804). Steps S802 to S804 described above are the same as steps S406 to S408 described above.

Next, the remaining energy E_SSB,T_CI of the stationary battery SSB at the departure time from the candidate departure point Td is calculated (step S805). This E_SSB,T_CI may be calculated by subtracting the required amount of discharge energy Essereq from the remaining energy E_SSB- After the EssBjd is calculated, all of the required amount of discharge energy Essereq of the stationary battery SSB, stored in the stationary battery information unit 141, from the arrival time at the arrival point Tap to the arrival time at the arrival point Ta is set to zero (step S806) . Then, the remaining energy E_SSB of the stationary battery SSB at the departure time from the candidate departure point Td is updated to the remaining energy E_SSB₍T_CI calculated in step S805 (step S807) . When the remaining energy E_SSB of the stationary battery SSB is updated, the process proceeds to step S 10506 of the evaluation process.

As described above, according to the operation management device of the present embodiment, vehicle allocation and calculation of the amount of charging energy are performed in such a way that the remaining energy of an electric bus (electric vehicle) in operation is greater than the lower limit of the remaining energy, and thus, an operation plan according to which a plurality of electric buses may operate without running out of energy may be formed . Also, the operation plan may be formed in such a way that constraints regarding the amount of energy that is available at a charging station (the amount of energy that is available from the power grid, the remaining energy of a stationary battery, etc. ) and the charging load (the supply power, and the like) are met. Accordingly, the charging load on each charging station may be distributed and peak-shifting is enabled . Also, since the amount of charging energy for an electric bus is calculated based on the battery life-related parameters, the deterioration of the battery mounted on the electric bus may be suppressed, and the life span of the battery may be extended .

(Second Embodiment)

In the following, a second embodiment of the present invention will be described with reference to FIGS. 31, 32(a) and 32(b), and 33(a) to 33(c) . Here, FIG . 31 is a flow chart showing an operation planning process of the second embodiment. In the second embodiment, the operation planning unit 10 generates a candidate solution using a genetic algorithm (GA) (step S903). Vehicle allocation for a generated candidate solution (steps S901, 904), evaluation of charging feasibility (steps S901, 904), determination of a termination condition (step S902), and selection of a candidate solution with high evaluation (step S906) may be performed by the same method as in the first embodiment.

First, the operation planning unit 10 generates a plurality of candidate solutions for a connection method (step S901). Candidate solutions are randomly generated under a constraint that candidate departure points other than -1 (no connection) may be selected just once. FIGS. 32(a) and 32(b) are diagrams showing examples of a candidate solution list. FIG. 32(a) is a candidate solution list including a plurality of candidate solutions generated in step S901, and N pieces of candidate solutions (hereinafter referred to as "N candidate solutions") are included therein. In step S901, the operation planning unit 10 allocates electric buses to the N candidate solutions, and performs the charging feasibility evaluation process for the candidate solutions to which electric buses have been allocated. The allocation of electric buses and the charging feasibility evaluation process may be performed by the same method as in the first embodiment. Accordingly, determination process of the charging feasibility, calculation of the amount of charging energy, update of the supply power P(t), ^"and update of the remaining energy of a stationary battery may also be performed. As shown in FIG. 32(a), as an evaluation value of a candidate solution, the charging feasibility score and the number of allocated electric buses may be used.

Next, whether or not the N candidate solutions satisfy the termination condition is determined (step S902), and in the case where the termination condition is satisfied (YES in step S902), the candidate solution whose evaluation value is the highest among the N candidate solutions is selected, and the candidate solution and the vehicle allocation list and the charging energy amount list generated for the candidate solution are outputted (step S906). In the case where the termination condition is not satisfied (NO in step S902), selection based on the genetic algorithm, crossover and mutation operations are performed on the N candidate solutions described above M/2 times (M is an even number), and M pieces of candidate solutions (hereinafter referred to as "M candidate solutions") are newly generated (step S903).

Here, the generation method of the M candidate solutions will be described. First, two candidate solutions are selected from the N candidate solutions generated in step S901 according to the evaluation values. The selection method of the candidate solutions is arbitrary, and roulette wheel selection of selecting a candidate solution based on the selection probability calculated based on the evaluation value may be used, for example. Alternatively, methods such as rank selection of selecting a candidate solution based on the selection probability that is set in advance according to the place in the ranking of evaluation values or a tournament selection of selecting a candidate solution with the highest evaluation value from a subset of randomly selected N candidate solutions may also be used. Here, it is assumed that candidate solutions 2 and 3 in FIG. 32(a) have been selected.

Next, as shown in FIG. 33(a), one crossover point is randomly set for the two selected candidate solutions 2 and 3, at an arbitrary position within the length of the candidate solutions (one-point crossover). Then, a crossover operation is performed on the candidate solutions 2 and 3 before and after the crossover point, and new candidate solutions 2 and 3 are generated. A crossover operation refers to switching of portions of the two selected candidate solutions before or after the crossover point. Then, as shown in FIG. 33(b), a new candidate solution formed from a portion of the candidate solution 2 before the crossover point and a portion of the candidate solution 3 after the crossover point (a new candidate solution 2), and a new candidate solution formed from a portion of the candidate solution 2 after the crossover point and a portion of the candidate solution 3 before the crossover point (a new candidate solution 3) are generated. Such a crossover operation is performed with a crossover probability Pc. Additionally, the crossover operation is not limited to the one-point crossover described above, and two-point crossover setting two crossover points, N-point crossover setting three or more crossover points, or uniform crossover where a change takes place with a predetermined probability separately for each candidate departure point included in the candidate solutions may also be used.

Moreover, a mutation operation is performed on the two new candidate solutions generated in the above manner with a mutation probability Pm. A mutation operation refers to selecting of one arbitrary position within the length of the candidate solution, and random changing of the candidate departure point at the selected position to another candidate departure point. FIG. 33(c) shows two new candidate solutions generated by performing the mutation operation on the new candidate solution 2.

By repeating the operations described above M/2 times, M pieces of new candidate solutions (M candidate solutions) are generated. Next, electric buses are allocated, and charging feasibility is evaluated, for the M candidate solutions (step S904). Then, N pieces of candidate solutions with high evaluation values are selected from the N candidate solutions and the M candidate solutions and N candidate solutions are newly generated (step S905), and whether or not the N new candidate solutions satisfy the termination condition is determined (step S902). FIG. 32(b) is a candidate solution list showing the N new candidate solutions. As shown in FIG. 32(b), the N new candidate solutions include, in a mixed manner, candidate solutions included in the original N candidate solutions and candidate solutions included in the newly generated M candidate solutions.

As described above, according to the second embodiment, a candidate solution with a high evaluation value is retrieved using the genetic algorithm. Accordingly, a high-quality candidate solution may be efficiently found in a short time.

Additionally, in the present embodiment, at the time of generating a new candidate solution by the crossover operation or the mutation operation, a constraint that candidate departure points other than -1 (no connection) may be selected just once in the same candidate solution may be imposed on the candidate solution. In this case, a new candidate solution is randomly generated within a range where the constraint may be met. Alternatively, a new candidate solution may be randomly generated without such constraints, and then, whether or not the new candidate solution which has been generated is a candidate solution that satisfies the constraint may be determined. In this case, a candidate solution which does not satisfy the constraint is removed from the M candidate solutions. Moreover, it is also possible to perform either the crossover operation or the mutation operation.

(Third Embodiment)

In the following, a third embodiment of the present invention will be described with reference to FIGS. 34(a) to 34(d), 35, 36, 37(a) and 37(b), and 38. First, the outline of an operation planning method will be given with reference to FIGS. 34(a) to 34(d). FIGS. 34(a) to 34(d) are schematic diagrams for describing an operation planning method.

In the present embodiment, an arrival point list in which arrival points of each bus schedule are arranged in the ascending order of arrival time is generated based on a basic bus schedule, and the arrival points are selected according to the order in the generated arrival point list, and are connected to departure points. That is, the arrival points and the departure points are connected in the ascending order of arrival time at the arrival points. In the case where vehicle allocation is not performed for a bus schedule according to which the departure time at a departure point is earlier than the arrival time at a selected arrival point, an electric bus is allocated to this bus schedule.

For example, in the case of the basic bus schedule shown in FIG. 34(a), an arrival point list in which arrival points are arranged in the order of arrival points 1, 2, 3, and 4, as shown in FIG. 34(b), is generated, and the arrival point 1 is selected first. Bus schedules 1 and 2 are bus schedules according to which the departure time at the departure point is earlier than the arrival time at the selected arrival point 1, but vehicles are not allocated thereto. Accordingly, electric buses are allocated to the bus schedules 1 and 2. In FIG. 34(c), an electric bus 1 is allocated to the bus schedule 1, and an electric bus 4 is allocated to the bus schedule 2.

Next, the selected arrival point is connected with the closest candidate departure point. The departure points that can be connected to the arrival point are those departure points each of whose departure time is after the arrival time at the arrival point, and are located at the same stop location as the arrival point. A candidate departure point closest to the arrival point is a candidate departure point among the candidate departure points satisfying the conditions described above and whose departure time is the closest to the arrival time at the arrival point,.

Next, the charging feasibility of a predetermined amount of energy at a charging point between connected bus schedules is determined. In the case where charging is possible, the amount of charging energy at the charging point is calculated. In the case where charging is not possible, connection between the arrival point and the candidate departure point is canceled, and whether or not the candidate departure point can be connected to another arrival point is determined. In the case where the candidate departure point cannot be connected to another arrival point, another electric bus that can be allocated to the candidate departure point is allocated thereto. In the case where there is no electric bus that can be allocated to the candidate departure point, a non-electric vehicle registered in the operation management device may be allocated. In the case where there is no electric bus or a non-electric vehicle that can be allocated, the departure time from the candidate departure point is delayed (shifted), and the candidate departure point is re-connected to the arrival point the connection to which has been canceled, and the charging feasibility is determined .

In FIG . 34(c), the candidate departure point which is closest to the arrival point 1 is the departure point 4, and thus, the arrival point 1 and the candidate departure point 4 are connected, and the charging feasibility at the charging point is determined . As shown in FIG . 34(d), in the case where charging is possible, the amount of charging energy at the charging point is calculated. Also, in the case where charging is not possible, the connection between the arrival point 1 and the departure point 4 is canceled . Then, since there is no arrival point that can be connected to the departure point 4, an electric bus 3 which can be allocated to the bus schedule 4 is allocated .

When the process for the first arrival point in the arrival point list is completed, the next arrival point in the arrival point list is selected, and the same process is repeated . The vehicle allocation list and the charge list are thereby generated . That is, in the present embodiment, vehicle allocation and connection of bus schedules are performed in parallel .

Next, an operation planning process of the present embodiment will be described in detail with reference to FIG. 35. FIG. 35 is a flow chart showing an operation planning process of the third embodiment. First, the operation planning unit 10 acquires pieces of information such as a basic bus schedule, vehicle information, route information, charging equipment information, a vehicle allocation list, a charge list, and the like (step S2001 ), calculates the required energy of each bus schedule specified by the basic bus schedule and generates a required energy list (step S2002), generates a list of electric vehicles that can be allocated (step S2003), generates a candidate departure point list (step S2004), and calculates supply power Pi,i(t), P (t) at power levels 1 and 2 (step S2005) . Each of the steps mentioned above may be performed by the same method as described in the first embodiment.

Next, an arrival point list in which arrival points are arranged in the ascending order of arrival time is generated, and an arrival point Ta is acquired in the order according to the arrival point list which has been generated (in the ascending order of arrival time) (step S2006). A bus schedule according to which the departure time at a departure point is earlier than the arrival time at the arrival point Ta is acquired, and if vehicle allocation is not performed for the bus schedule, whether or not vehicle allocation for the bus schedule is possible is determined (step S2007).

In the case where vehicle allocation is not possible (NO in step S2007), this operation plan is a failure, and the operation planning process is ended (step S2008). A case where vehicle allocation is not possible in step S2007 is a case where, in FIG. 34(c), the arrival point 1 is selected and electric buses cannot be allocated to the departure points 1 and 2. For example, if no electric bus is stopped at the charging station A, an electric bus cannot be allocated to the departure point 1. In such a case, an operation plan cannot be formed unless the basic bus schedule is changed or an electric bus that can be allocated is added, and thus, the operation plan is a failure. However, in the case where the operation plan is re-planned, the operation plan may become possible due to the number of electric buses that can be allocated being changed by shifting of the arrival time or the departure time of the bus schedule, and the operation planning process may be continued.

On the other hand, in the case where vehicle allocation is possible (YES in step S2007), vehicle allocation is performed for the departure point, and the vehicle allocation list is updated (step S2009). FIG. 36 shows an example of the vehicle allocation list, and every time an electric bus is allocated to a bus schedule, a record is added and the list is updated. Additionally, the method described in the first embodiment may be used in the vehicle allocation for a departure point in step S2007. That is, the maximum required amount of charging energy is calculated based on the required energy of the bus schedule of the departure point, and an electric bus whose effective capacity is greater than the maximum required amount of charging energy may be allocated .

Next, whether or not a termination condition is satisfied is determined (step S2010) . A termination condition is the acquired arrival point Ta being the last arrival point in the arrival point list, for example. In the case where the termination condition is satisfied (YES in step S2010), the charge list and the vehicle allocation list are output, and the operation planning process is ended (step S2012) . On the other hand, in the case where the termination condition is not satisfied (NO in step S2010), a candidate departure point Td is extracted for the arrival point Ta from the candidate departure point list in the ascending order of departure time (step S2011 ) . In the present embodiment, only the candidate departure point Td closest to the arrival point Ta may be connected to the arrival point Ta .

In the case where there is no candidate departure point Td (NO in step S2013), the operation planning process returns to step S2006, and acquires the next arrival point Ta from the arrival point list. In the case where there is a candidate departure point Td (YES in step S2013), whether or not charging of a predetermined amount of energy between the arrival point Ta and the candidate departure point Td is possible is determined (step S2014) . Determination of the charging feasibility may be performed by the same method as in the first embodiment. That is, the supply energy Eg that is supplied by the power grid from the arrival time at the arrival point Ta to the departure time at the candidate departure point Td and the remaining energy E_SSB of the stationary battery are calculated, and these are added up to calculate the energy Eavail that is available at the arrival point Ta . Then, the energy Eavail, the remaining energy (the estimated value) EVrem of the electric bus, the lower limit of the remaining energy EVIow of the electric bus, and the required energy Ereq of the bus schedule of the candidate departure point Td are compared to thereby determine the charging feasibility between the arrival point Ta and the candidate departure point Td.

In the case where charging is possible (YES in step S2014), the amount of charging energy to be charged between the arrival point Ta and the candidate departure point Td is calculated (step S2018). The amount of charging energy may be calculated by the same method as in the first embodiment. That is, the required energy Ereq of the bus schedule of the candidate departure point Td, the energy Eavail that is available at the arrival point Ta, the upper limit of the remaining energy EVhigh of the electric bus, the remaining energy (the estimated value) EVrem of the electric bus at the arrival point Ta, and the maximum amount of energy Einmax that can be charged in the electric bus are compared to thereby calculate the amount of charging energy between the arrival point Ta and the candidate departure point Td.

Next, the supply power and the remaining energy of the stationary battery are updated (step S2019). Updating of the supply power may be performed by the same method as that described in the first embodiment. That is, the amount of supply energy Eg is first calculated based on the supply power P(t). Next, the amount of supply energy Eg and the amount of charging energy calculated in step S2018 are compared, and if ^"the amount of supply energy Eg is at or below the amount of charging energy, the supply power P(t) is updated to zero. In the case where the amount of supply energy Eg is greater than the amount of charging energy, the average required charging power Pc(t) is calculated, and the insufficient amount of energy Einsuff and the surplus amount of energy Esurplus are calculated based on the average required charging power Pc(t). Then, the supply power P(t) in the time range where the supply power P(t) is at or below the average required charging power Pc(t) is updated to zero, and the supply power P(t) in the time range where the supply power P(t) is greater than the average required charging power Pc(t) is updated to a value that is calculated based on the insufficient amount of energy Einsuff and the surplus amount of energy Esurplus.

Updating of the remaining energy of the stationary battery may also be performed by the same method as that described in the first embodiment. That is, first, the required amount of discharge energy Essereq from a stationary battery SSB that may be used at the arrival point Ta and the remaining energy E_SSB of the stationary battery SSB are calculated . Next, whether or not there is the required amount of discharge energy EssE$req is determined, and in the case where there is not available the required amount of discharge energy Essereq, the remaining energy is updated to the remaining energy E_SSB, and in the case where there is the required amount of discharge energy Essereq, the remaining energy is updated by deducting the required amount of discharge energy Essefeq from the remaining energy E_SSB-

Lastly, the vehicle allocation list and the charge list are updated (step S2020), and the operation planning process returns to step 2006. Additionally, the updating method of the charge list will be described later.

In the case where charging of a predetermined amount of energy between the arrival point Ta and the candidate departure point Td is determined in step S2014 to be not possible (NO in step S2014), whether or not there is an arrival point Ta', other than the currently processed arrival point Ta, that can be connected with the candidate departure point Td is determined (step S2015) . The arrival point Ta' is an arrival point that satisfies all the following conditions.

Condition 1. Arrival time at arrival point Ta < arrival time at arrival point Ta' < departure time from candidate departure point Td

Condition 2. Node ID of arrival point Ta = node ID of arrival point Ta'

In the case where there is an arrival point Ta' that satisfies the above conditions (YES in step S2015), the operation planning process returns to step S2006, and the next arrival point Ta is acquired from the arrival point list. On the other hand, in the case where there is no arrival point Ta' (NO in step S2015), whether or not vehicle allocation may be performed for the candidate departure point Td is determined (step S2016). In the case where vehicle allocation for the candidate departure point Td is possible (YES in step S2016), an electric bus is allocated to the candidate departure point Td, and the vehicle allocation list is updated. Then, the operation planning process returns to step S2006, and the next arrival point Ta is acquired from the arrival point list. In step S2016, in the case where there is a non-electric vehicle that may be allocated to the candidate departure point Td, the non-electric vehicle may be allocated.

On the other hand, in the case where vehicle allocation for the candidate departure point Td is not possible (NO in step S2016), the departure time from the candidate departure point Td is delayed so as to enable charging of a predetermined amount of power between the arrival point Ta and the candidate departure point Td (step S2017). The delay process of the departure time from the candidate departure point Td will be described later.

In step S2017, after the departure time from the candidate departure point Td is delayed, the operation planning process proceeds to step S2019, and the amount of charging energy that is to be charged from the arrival time at the arrival point Ta to the new departure time at the candidate departure point Td is calculated.

Next, the updating method of the charge list in step S2020 will be described. FIG. 37(a) is a flow chart showing the update method of the charge list. First, an arrival point Ta, a candidate departure point Td, an arrival point Ta' of the bus schedule of the candidate departure point Td, the vehicle ID of an electric bus allocated to the arrival point Ta, and the like are acquired (step S2101). Next, a new charge record is generated (step S2102), and a value is set in each field of the charge record (step S2013). The fields are the vehicle ID, the node ID, the expected arrival time, the expected departure time, the expected remaining energy on arrival, the target remaining energy, and the like, and values may be set in these fields in the following manner.

Vehicle ID = ID of vehicle allocated to arrival point Ta

Node ID = Node ID of arrival point Ta

Expected arrival time = Arrival time at arrival point Ta Expected departure time = Departure time from candidate departure point Td

Expected remaining energy on arrival (kWh) = Remaining energy of electric vehicle allocated to arrival point Ta (kWh)

Target remaining energy (kWh) = Expected remaining energy on arrival (kWh) + amount of charging energy (kWh)

When a value is set in each field of a new record, the new record is added to the charge list (step S2014), and the charge list is updated. FIG. 37(b) is a diagram showing an example of the charge list.

Next, the delay process of the departure time from the candidate departure point Td in step S2017 will be described. FIG. 38 is a flow chart showing the delay process of the departure time at the candidate departure point Td. First, an arrival point Ta, a candidate departure point Td, the required energy Ereq of the bus schedule of the candidate departure point Td, the energy Evail that is available at a charging station, the remaining energy EVrem at the time of arrival at the arrival point Ta, the lower limit of the remaining energy EVIow of the battery of an electric bus, the sampling interval s (sec), and the like are acquired (step S3101). The sampling interval s may be arbitrarily set.

Next, the arrival time at the arrival point Ta is set as a time ta, and the departure time from the candidate departure point Td is set as a time td (step S3102). Then, energy Eneed (kWh) that is lacking with respect to a predetermined amount of energy that is to be charged between the arrival point Ta and the candidate departure point Td is calculated (step S3103). The lacking energy Eneed may be calculated by the following formula.

[Math. 21]

Eneed = Ereq + EVlow - Eavail - EVrem Next, a time tdc when the lacking energy Eneed may be charged using the supply power P_i(1(t) at the power level 1 is retrieved. That is, the time tdc is the time when charging of a predetermined amount of energy that is to be charged between the arrival point Ta and the candidate departure point Td may be completed by charging with the supply power Pi,i(t), and departure time of tdc > departure time of td is true.

Retrieval of the time tdc will be described. First, a time td is set as the time tdc, and the energy E (kWh) to be supplied from the supply power P,,i(t) from the time td to the time tdc is set to zero (step S31041). Next, one minute is added to the time tdc, and the time tdc is updated (step S31042). The time to be added to the time tdc may be arbitrarily set. Then, the energy E to be supplied by the power grid is calculated by the following formula (step S31043).

[Math. 22]

E = E + P(tdc ) x s /3600

The energy E which has been calculated and the lacking energy Eneed are compared (step S31044), and in the case the energy E is smaller than the lacking energy Eneed (NO in step S31044), the process returns to step S31042 and the time tdc is updated, and in the case where the energy E is equal to or greater than the lacking energy Eneed (YES in step S31044), the tdc is returned (step S31045), and the process proceeds to step S3105.

Then, an arrival time tai and a departure time tdci of an electric bus on each node of the bus schedule of the candidate departure point Td are calculated by the following formulae, and are updated (step S3105). [Math. 23]

tai = tai + tdc - td

tdci = tdci + tdc - td

That is, the arrival time and the departure time of each node of the bus schedule, specified by the basic bus schedule, are delayed by tdc - td. The entire bus schedule is thereby moved backward by tdc - td. At this time, the departure time from the candidate departure point Td is also delayed by tdc - td, and a new departure time is set. New route information obtained by such a change is returned (step S3106), and calculation of the amount of charging energy in step S2018 is performed based on the new route information (the departure time and the arrival time).

(Fourth Embodiment)

In the following, a fourth embodiment of the present invention will be described with reference to FIGS. 39 to 42. The operation management device of the present embodiment re-plans an operation plan by detecting a dynamic factor such as the energy that is available at a charging station or the operation state. Whether or not to perform re-planning is determined by the re-planning determination unit 16. The re-planning determination unit 16 performs determination regarding re-planning when a notification of a re-planning request is received from the re-planning request unit 17 or at regular intervals. Then, when re-planning is determined to be performed, the operation planning unit 10 is instructed to perform re-planning, and the operation planning unit 10 re-plans the operation plan after the time point when re-planning is determined. Determination regarding re-planning by the re-planning determination unit 16 uses dynamic factors that change during operation of an electric bus such as delay information or the remaining energy of an electric bus in operation, the energy that is available at a charging station, the remaining energy of a stationary battery, energy consumption rate or required time between stop locations, and the like. In the following, the re-planning determination process of the present embodiment will be described with reference to FIG. 39.

First, the re-planning determination unit 16 acquires the current time t, the previous re-planning determination time tprev, a parameter aprev, and the like (step S4001). In the case of performing the first re-planning determination, the re-planning determination time tprev is null. Additionally, the parameter aprev is a safety parameter that is set at the time of the previous operation planning or at the time of re-planning, to calculate the required energy of the bus schedule.

Next, whether or not a notification of a re-planning request is received from the re-planning request unit 17 is determined (step S4002). Information included in the re-planning request notified by the re-planning request unit 17 is different depending on the reason for the re-planning request. For example, a re-planning request that is issued when the charging power to an electric bus at a charging station has exceeded the contracted power includes the node ID of the charging station, the level of charged power, contract-deviated power, and the like. The contract-deviated power refers to the power among the charging power at the charging station which exceeds the contracted power. Also, a re-planning request that is issued when an electric bus is delayed includes information such as the node ID of each stop location along which the delayed electric bus operates, the vehicle ID of the delayed electric bus, the delay time with respect to the operation plan, and the like.

In the following, a case where a notification of a re-planning request is not issued in step S4002 (NO in step S4002) will be described first, and then, a case where a notification of the re-planning request is issued (YES in step S4002) will be described.

In the case where a notification of a re-planning request is not issued in step S4002, the re-planning determination unit 16 determines whether or not a predetermined period of time has elapsed from the time tprev when previous re-planning determination was performed (step S4003). In the case where a predetermined period of time has not elapsed from the re-planning determination time tprev (NO in step S4003), a re-planning flag is set to false (step S4013), and the re-planning determination unit ends the re-planning determination process (step S4021).

In the case where a predetermined period of time has passed from the re-planning determination time tprev (YES in step S4003), the re-planning determination unit 16 acquires vehicle information (step S4004), and determines whether or not the latest location time of each electric bus is delayed from the time that is scheduled in the operation plan (step S4005). Specifically, the latest location information of an electric bus acquired from the vehicle information and the expected arrival time at the current location of the electric bus according to the vehicle allocation plan are compared, and whether or not there is a delay is determined.

In the case where there is a delay (YES in step S4005), whether or not the delay time is greater than a threshold value is determined (step S4016), and in the case where there is no delay (NO in step S4005), whether or not the remaining energy of the electric bus at the next arrival charging station will be low is determined (step S4006). Determination regarding whether or not the remaining energy of the electric bus will be low (step S4006) will be described below in detail.

In the case where it is determined in step S4006 that the remaining energy will be low (YES in step S4006), the charging feasibility at the charging station where the electric bus will arrive next is determined (step S4017). Determination regarding the charging feasibility at the next charging station (step S4017) will be described later in detail.

In the case where it is determined in step S4006 that the remaining energy will not be low (NO in step S4006), information about the energy that is available at each charging station is acquired (step S4007), and whether or not there is a change in the available energy information is determined (step S4008). For example, the available energy information may be changed when a DR is issued from the power grid. In the case where there is a change in the available energy information (YES in step S4008), the re-planning flag is set to true (step

54019) , and the re-planning determination unit 16 instructs the operation planning unit 10 to re-plan the operation plan (step

54020) , and the re-planning determination process is ended (step S4021). The operation planning unit 10 carries out re-planning of the operation plan taking each arrival point after the re-planning determination has been made as a re-planning target.

In the case where there is no change in the available energy information (NO in step S4008), the re-planning determination unit 16 acquires stationary battery information (step 4009), and determines whether or not the remaining energy of the stationary battery at a charging station which an electric bus has passed in the immediate past is lower than the expected remaining energy based on the current operation plan (step S4010). In the case where it is determined that the remaining energy of the stationary battery is lower (YES in step S4010), the re-planning flag is set to true (step S4019), the re-planning determination unit 16 instructs the operation planning unit 10 to re-plan the operation plan (step S4020), and the re-planning determination process is ended (step S4021).

In the case where it is determined in step S4010 that the remaining energy of the stationary battery is not lower (NO in step S4010), the re-planning determination unit 16 acquires the route information (step S4011), and determines whether or not there is a change in at least one of the energy consumption rate and the required time between the stop locations (step S4012). In the case where there is a change in at least one of the energy consumption rate and the required time between the stop locations (YES in step S4012), the re-planning flag is set to true (step S4019), the re-planning determination unit 16 instructs the operation planning unit 10 to re-plan the operation plan (step S4020), and the re-planning determination process is ended (step S4021). in the case where there is no change in the energy consumption rate and the required time between the stop locations (NO in step S4012), the re-planning flag is set to false (step S4013), and the re-planning determination unit 16 ends the re-planning determination process (step S4021).

Next, a case where a re-planning request is issued in step S4002 (YES in step S4002) will be described. Additionally, step S4016 described below is the same process as that performed in the case where it is determined in step S4005 that there is a delay (YES in step S4005). Also, step S4017 described below is the same process as that performed in the case where it is determined in step S4006 that the remaining energy of an electric bus will be low (YES in step S4006).

In the case where a re-planning required is issued in step

S4002 (YES in step S4002), the re-planning determination unit 16 adjusts a parameter a to be used at the time of re-planning, based on the parameter aprev that is acquired (step S4014). Furthermore, in step S4014, elimination of an overlapping re-planning request is performed along with adjustment of the parameter a. Details of adjustment of the parameter in step S4014 will be given later.

Next, whether or not the charging power to an electric bus at a charging station is exceeding the contracted power, that is, whether or not there is contract-deviated power, is determined (step S4015). In the case where there is contract-deviated power (YES in step S4015), the re-planning flag is set to true (step S4019), the re-planning determination unit 16 instructs the operation planning unit 10 to re-plan the operation plan (step S4020), and the re-planning determination process is ended (step S4021). The operation planning unit 10 re-plans the operation plan by using the parameter a which was adjusted in steps S4014.

In the case where there is no contract-deviated power in step S4015 (NO in step S4015), whether or not the delay time is greater than a threshold value is determined (step S4016). In the case where the delay time is at or below the threshold value (NO in step S4016), the re-planning flag is set to false, and the re-planning determination unit 16 ends the re-planning determination process (step S4021). The delay time may occur frequently due to influences of the road conditions and the like, and if re-planning is performed every time there is a slight delay time, this results in frequent re-planning of the operation plan and is not desirable. However, by performing determination regarding re-planning by comparing the delay time and the threshold value, the number of times of re-planning may be reduced.

In the case where the delay time is greater than the threshold value in step S4016 (YES in step S4016), the charging feasibility at the next charging station is determined (step S4017). In step S4017, the charging feasibility at the next arrival charging station of the electric bus is determined, and if charging is possible, the re-planning flag is set to true, and if charging is not possible, the re-planning flag is set to false. In the case where the re-planning flag is set to true, the re-planning determination unit 16 instructs the operation planning unit 10 to re-plan the operation plan (step S4020), and ends the re-planning determination process (step S4021). The operation planning unit 10 re-plans the operation plan by using the parameter a adjusted in step S4014. Also, in the case where the re-planning flag is false, the re-planning determination unit 16 ends the re-planning determination process (step S4021).

Additionally, the parameter a may be adjusted, and re-planning may be performed by using the adjusted parameter a also in the case where a re-planning request is not issued (NO in step S4002), and re-planning is determined by the re-planning determination process performed after a predetermined time has elapsed from the last re-planning. The adjustment method of the parameter a may be the same as in step S4014.

Next, determination in step S4006 of whether the remaining energy of an electric bus will be low at the next charging station will be described with reference to FIG. 40. FIG. 40 is a flow chart showing the determination process of whether or not the remaining energy of an electric bus at the next charging station will be low.

First, the operation information (the ID of a node to be passed next, the distance to the node to be passed next, the latest SOC), the parameter a used in the calculation of the required energy of the bus schedule of the departure point, the remaining energy Eplan at the next charging station calculated at the time of forming the current operation plan, the threshold value β (%) of the remaining energy, and the like are acquired (step S5001).

Next, the amount of remaining energy Epred (kWh) of the electric bus at a charging station where the electric bus is to arrive next is estimated (step S5002). The remaining energy Epred may be estimated by the method described with reference to step S1027 described above. That is, the remaining energy Epred may be estimated by subtracting the required energy from the latest location to the next charging station from the remaining energy at the latest location.

Then, the remaining energy Epred and the remaining energy Eplan are compared (step S5003), and in the case where the remaining energy Epred is equal to or greater than the remaining energy Eplan (YES in step S5003), a low remaining energy flag is set to NO (step S5004), and the low remaining energy flag is returned (step S5007). When the low remaining energy flag which is set to NO is returned, the re-planning determination process proceeds to step S4007.

On the other hand, in the case where the remaining energy Epred is smaller than the remaining energy Eplan (NO in step S5003), the difference between the remaining energy Epred and the remaining energy Eplan and the threshold value β of the remaining energy are compared (step S5005). In the case where (Eplan - Epred)/Eplan is at or below the threshold value β of the remaining energy (YES in step S5005), the low remaining energy flag is set to NO (step S5004), and the low remaining energy flag is returned (step S5007). When the low remaining energy flag which is set to NO is returned, the re-planning determination process proceeds to step S4007.

In the case where (Eplan - Epred)/Eplan is greater than the threshold value β of the remaining energy (NO in step

55005) , the low remaining energy flag is set to YES (step

55006) , and the low remaining energy flag is returned (step

55007) . When the low remaining energy flag which is set to YES is returned, the re-planning determination process proceeds to step S4017.

Now, the setting method of the threshold value β of the remaining energy will be described. The threshold value β of the remaining amount may be set based on the minimum value of the parameter a set in advance and the value of the parameter a that is used at the time of calculating the remaining energy Eplan, by calculating (parameter a that is used - the minimum value of parameter a)/parameter a that is used. For example, in the case where the minimum value of the parameter a is set to 1.1, and the value of the parameter a that is used is 1.25, the threshold value β of the remaining energy may be set to 12% (= (1.25 - 1.1)/1.25). The threshold value β of the remaining energy may be set for the value of each parameter a to be used, or may be newly set for each re-planning determination process.

The reduction in the remaining energy Epred may occur frequently due to influences of the road conditions and the like, and it is not desirable to perform re-planning every time there is a slight reduction in the remaining energy Epred. However, by performing determination regarding re-planning by comparing the remaining energy and the threshold value, the number of times of re-planning may be reduced.

Next, determination in step S4017 of the charging feasibility at a charging station where the electric bus is to arrive next will be described with reference to FIG. 41. In the re-planning determination process, if there is a delay in an electric bus, or if the remaining energy Epred of the electric bus is lower than the remaining energy Eplan which was expected at the time of forming the operation plan, the charging feasibility at the next arrival point is determined. FIG. 41 is a flow chart showing the determination process of the charging feasibility at a charging station where an electric bus is to arrive next.

First, the vehicle allocation plan, the charge plan, the current location information, and the like are acquired (step S6001). Next, the next arrival point (the charging station) of an electric bus is extracted from the vehicle allocation plan (step S6002), and the charge plan at the charging station is extracted from the charge plan which was acquired (step S6003). In the case where there is no charge plan at the charging station, that is, in the case where the extracted charge plan is null (YES in step S6004), the re-planning flag is set to false (step S6005), and the re-planning flag is returned (step S6009). When the re-planning flag that is set to false is returned, the re-planning determination process is ended (step S4021). A case where there is no charge plan at the charging station is a case where the operation of the electric bus ends at the next charging station, for example.

In the case where there is a charge plan at the next charging station (NO in step S6004), the arrival time at the next charging station and the remaining energy Epred at the next charging station are estimated (step S6006). Then, the charging feasibility at the next station is determined based on the charging plan at the charging station, and the arrival time and the remaining energy Epred which have been estimated (step S6007).

In the case where it is determined that charging is possible at the next charging station (YES in step S6007), the re-planning flag is set to false (step S6005), and the re-planning flag is returned (step S6009). When the re-planning flat that is set to false is returned, the re-planning determination process is ended (step S4021).

In the case where it is determined that charging is not possible at the next charging station (NO in step S6007), the re-planning flag is set to true (step S6008), and the re-planning flag is returned (step S6009). When the re-planning flat that is set to true is returned, the re-planning determination unit 16 instructs the operation planning unit 10 to re-plan the operation plan (step S4020), and the re-planning determination process is ended (step S4021).

The determination of charging feasibility in step S6007 may be performed by the same method as in step S10510 described above. That is, the estimated arrival time at the next charging station is set as the starting time ts, and the departure time from the next charging station scheduled in the vehicle allocation plan is set as the ending time te (step S403), the supply power P(t) is set to the supply power Pi,i(t) at the power level 1 (step S404), and the amount of supply energy Eg (kWh) to be supplied by the power grid from the starting time ts to the ending time te is calculated based on each parameter that is set (step S405).

Furthermore, the amount of energy that is available from the stationary battery from the starting time ts to the ending time te is calculated (steps S406 to S408), and the energy Eavail (kWh) that is available at the next charging station from the starting time ts to the ending time te is calculated based on the amount of supply energy Eg (kWh) and the remaining energy E_SSB (kWh) of the stationary battery SSB installed at the next charging station (step S409).

Then, whether or not charging of a predetermined amount of charging energy from the arrival time (the estimated value) at the next charging station to the departure time is possible is determined based on the lower limit of the remaining energy EVIow of the electric bus, the remaining energy (the estimated value) Epred at the next charging station, the required energy Ereq of the bus schedule starting from the next charging station, and the energy Eavail that is available at the next charging station (step S411). In the case where Eavail + Epred - EVIow > Ereq is established, charging is determined to be possible; otherwise, it is determined that charging is not possible.

Next, adjustment of the parameter a in step S4014 will be described with reference to FIG. 42. In step S4014, the parameter a that is used at the time of re-planning is adjusted. FIG. 42 is a flow chart showing an adjustment process of the parameter a. First, the re-planning determination unit 16 acquires the current time t, the previous re-planning determination time tprev, the parameter aprev which was used in the previous re-planning determination or the operation planning, the default value ad of the parameter a, and the like (step S7001). The default value ad is set to be greater than one, and is set to 1.25, for example.

Next, the current time t and the previous re-planning time tprev are compared, and in the case where it is determined that the current time t is different from the re-planning time tprev (NO in step S7002), a new re-planning request is determined and the parameter a is set to the default value ad (step S7003), the value of the parameter a that is set is returned (step S7007), and the re-planning determination process proceeds to step S4015.

In the case where it is determined in step S7002 that the current time t is the same as the re-planning time tprev (YES in step S7002), the re-planning request is judged as a repeated , and it is determined whether or not the previous parameter aprev is 1.0 (step S7004). If the elapsed time from the re-planning time tprev to the current time t is within a predetermined period of time, it is determined in step S7002 that the current time t is the same as the re-planning time tprev.

In the case where the parameter aprev is 1.0 in step S7004 (YES in step S7004), the value of the parameter a cannot be further reduced, and thus, the re-planning flag is set to false (step S7005), and the re-planning determination unit 16 ends the re-planning process (step S4021).

In the case where the parameter aprev is not 1.0 in step S7004 (NO in step S7004), the parameter a is set to a value smaller than the parameter aprev (step S7006), and the parameter a is returned (step S7007), and the re-planning determination process proceeds to step S4015. Additionally, the parameter a to be newly set is set within the range of aprev > a > 1.0.

As described above, every time a repeated re-planning request is issued, the re-planning determination unit 16 gradually reduces the parameter a. Accordingly, re-planning of an operation plan that is based on a possible greater parameter a is returned.

(Fifth Embodiment)

In the following, an operation planning process according to a fifth embodiment will be described with reference to FIGS. 43 and 44. Here, FIG. 43 shows an example of a basic bus schedule to which the operation planning process of the fifth embodiment is to be applied, and FIG. 44 is a flow chart showing a calculation process of the required energy of a bus schedule according to which the arrival point is a non-charging node (a non-charging station). According to the basic bus schedule in FIG. 43, nodes A and C are charging stations, and the node B is a non-charging node, which is not capable of charging an electric bus. In the present embodiment, when connecting an arrival point and a departure point of bus schedules, if the arrival point of the bus schedule of the departure point is a non-charging node, an operation plan is formed taking into account the required energy from the non-charging node to a charging station which can be reached.

In the case of connecting an arrival point 11 and a departure point 32 in FIG. 43, an arrival point 32 of a bus schedule 32 is located on the non-charging node B. In this case, the total of the required energy of the bus schedule 32 and the required energy from the non-charging node B to the charging station A or the charging station C is calculated as the required energy of the bus schedule 32.

Specifically, first, the required energy El (kWh) of the bus schedule 32 from the charging station C to the non-charging node B is calculated (step S8001). Next, the charging stations A and C which can be reached from the non-charging node B are acquired (step S8002), and the bus schedule to each of the charging stations A and C is acquired (step S8003). The bus schedule that is acquired in step S8003 is the bus schedule which can be connected to the bus schedule 32 and whose arrival point is on the charging station A or the charging station C. In the case of the basic bus schedule of FIG. 43, a bus schedule 23 and a bus schedule 24 are acquired.

Next, the required energy to each of the charging stations A and C, that is, the required energy of the bus schedule 23 and the bus schedule 24 acquired in step S8003, is calculated (step S8004), and the maximum value E2 (kWh) of the required energy to each charging station is acquired (step S8005). The maximum value E2 of the required energy is the greater of the required energy of the bus schedule 23 and the required energy of the bus schedule 24.

Then, as the required energy of the bus schedule 32, the total value of the required energy El and the required energy E2 is calculated (step S8006). According to the present embodiment, determination of the charging feasibility, calculation of the amount of charging energy, and the like are performed based on the required energy calculated in this manner.

According to the configuration as described above, even if a bus schedule whose arrival point is on a non-charging node is included in the basic bus schedule, since an operation plan taking the required energy from a non-charging node to a charging node into account may be formed, an electric bus may be prevented from running out of energy while running from a non-charging node to a charging station.

(Sixth Embodiment)

In the following, a sixth embodiment of the present invention will be described with reference to FIGS. 45(a) to 45(c). In the present embodiment, the route information stored in the route information unit 13 is updated based on the vehicle information or the like. The route information is updated by the route information unit 13 or the operation planning unit 10, and the updated route information is stored in the route information unit 13. In the following, the update process of the route information according to the present embodiment will be described. Here, FIGS. 45(a) to 45(c) are diagrams for describing the update process of the route information of the sixth embodiment.

First, pieces of operation information acquired from electric buses in operation are sorted based on the vehicle IDs and the latest location times (timestamps). FIG. 45(a) shows an example of pieces of operation information which have been sorted. The pieces of operation information are sorted by the vehicle IDs, and are then sorted by the latest location times. An electric bus transmits the operation information of itself to the vehicle information unit 12 at predetermined intervals, and the vehicle information unit 12 stores the operation information acquired at each timing. An electric bus may transmit the latest operation information of itself at predetermined intervals, or may transmit the information at the timing of arrival at each stop location or at the timing of departure from each stop location.

Next, the route information unit 13 calculates, based on the pieces of operation information which have been sorted, the required time between stop locations and the amount of change in the SOC (%). The required time between stop locations is calculated by subtracting the departure time at a departure point from the arrival time at an arrival point. Also, the amount of change in the SOC is calculated by subtracting the SOC of the arrival point from the SOC of the departure point. The arrival time and the departure time of each stop location are acquired based on the latest location time. As shown in FIG. 45(b), the required time between nodes A and B calculated based on the operation information in FIG. 45(a) is 19 minutes, and the amount of change in the SOC of an electric bus which has operated between the nodes A and B is 10%.

Next, the route information unit 13 acquires the distance (km) between stop locations from the route information, acquires the initial capacity (kWh) and the SOH (%) from the battery information, and calculates the energy consumption (kWh) between the stop locations. As the battery information, information with the same vehicle ID as the operation information is used. Then, the energy consumption between the stop locations is calculated based on the calculated energy consumption and the distance between the stop locations. The energy consumption and the energy consumption may be calculated in the following manner.

[Math. 24]

Energy consumption (kWh) = Initial capacity (kWh) χ SOH (%) x amount of change in SOC (%)

Energy consumption rate (kWh/km) = Energy consumption (kWh)/Distance between stop locations (km)

In the examples of FIGS. 45(a) to 45(c), when the initial capacity of an electric bus (vehicle ID 001) is 50kWh, the SOH is 90%, and the distance between the nodes A and B is 4 km, the amount of change in the SOC is 10%, as shown in FIG. 45(b), and the energy consumption rate is 1.125 kWh/km. Additionally, the energy consumption rate that is calculated here is the average energy consumption between the nodes A and B.

The route information is updated by the required time and the energy consumption obtained in the above manner. The route information may be updated by adding newly calculated route information or by overwriting by the same. For example, as shown in FIG. 45(c), the route information may be updated by overwriting each field of the route information by the newly calculated route information. Alternatively, pieces of newly calculated route information may be sequentially added to past route information, and the route information with the latest information update time may be used at the time of forming an operation plan or at the time of re-planning. Lastly, the route information unit 13 deletes the operation information which was acquired for updating the route information, and ends the update process of the route information. In this manner, by updating the route information to the latest information, the remaining energy of an electric bus or the like may be accurately estimated. Thus, an appropriate operation plan which is not much deviated from the actual operation state may be formed.

(Seventh Embodiment)

Next, a seventh embodiment of the present invention will be described with reference to FIGS. 46(a) and 46(b). In the present embodiment, the vehicle information unit 12 calculates the battery life-related parameter that takes into account the actual deterioration state (SOH) of an electric bus based on an SOH mapping table and a target SOH table prepared in advance. The battery life-related parameter (hereinafter referred to as "life parameter") refers to each parameter that is set to extend the battery life of an electric bus, such as the upper and lower limits of the remaining energy and the maximum charge/discharge rate. In the following, first, the SOH mapping table and the target SOH table will be described. Here, FIGS. 46(a) and 46(b) show an example of the SOH mapping table and the target SOH table.

As shown in FIG. 46(a), in the SOH mapping table, the actual SOH of the battery of an electric bus (actual SOH) and the life parameter that is set for the actual SOH are mapped for each electric bus. The life parameter of each electric bus is set based on the SOH mapping table, and the life parameter that is set is stored as the battery information. For example, according to the SOH mapping table of FIG. 46(a), the lower limit of the remaining energy of the electric bus whose vehicle ID is 001 is set with reference to 6 kWh when the SOH is 95%.

In the SOH mapping table, the actual SOHs (and the life parameters) are discretely mapped at arbitrary intervals (for example, every 5%). Since the appropriate life parameter changes according to the actual SOH, for example, the lower limit of the remaining energy (kWh) is mapped in such a way as to be increased in accordance with the reduction in the actual SOH, as shown in FIG. 46(a). Also, the upper limit of the remaining energy (kWh), the maximum charge rate (kW), and the maximum discharge rate (kW) are mapped in such a way as to be reduced in accordance with the reduction in the actual SOH. Additionally, the SOH mapping table may be prepared for each electric bus, or a common SOH mapping table may be prepared for a plurality of electric buses of the same vehicle type.

As shown in FIG. 46(b), in the target SOH table, the accumulated traveling distance (km) of an electric bus, and the target SOH according to the accumulated traveling distance are mapped for each electric bus. The target SOH is the reference SOH that is set according to the accumulated traveling distance of each electric bus. In the case where the actual SOH is higher than the target SOH, the deterioration of the battery is assumed to be suppressed, and in the case where the actual SOH is lower than the target SOH, the battery is assumed to be deteriorated. For example, according to the target SOH table of FIG. 46(b), the target SOH of the electric bus whose vehicle ID is 001 is set to 95% when the accumulated traveling distance is 1000 km.

In the target SOH table, the accumulated traveling distances are discretely mapped at arbitrary intervals (for example, every 1000 km). Additionally, the target SOH table may be prepared for each electric bus, or a common target SOH table may be prepared for a plurality of electric buses of the same vehicle type.

Next, the method of calculating the life parameter of an electric bus by the vehicle information unit 12 will be described. In the following, a case of calculating the life parameter for an electric bus whose vehicle ID is 001 (hereinafter referred to as an "electric vehicle 1") will be described. It is assumed with respect to the electric vehicle 1 that the actual accumulated traveling distance is 1400 km and the actual SOH is 91%. First, the vehicle information unit 12 refers to the target SOH table, and calculates the target SOH according to the accumulated traveling distance of the electric bus. The target SOH may be calculated by the following formula.

[Math. 25]

_♦ ^ SOnHu _{t t} cm _■ ^{(actual D} - ^tar§^et AJ(target

= target SOH_low + SOH_low - target target SOH_hig·_h)

(target D_low - target D_hi . )

Here, the actual D is the actual accumulated traveling distance, and the target D|_0W and the target D_hi₉h are accumulated traveling distances mapped on the target SOH table according to which target D|_0W < actual D < target Dhigh is true. In the case of the electric vehicle 1, since the actual D is 1400 km, when referring to the target SOH table in FIG. 46(b), the target D|_0W is 1000 km, and the target D_high is 2000 km.

Also, the target SOH|_OW and the target SOH_high are target

SOHs corresponding to the target D|_0W and the target D_hi₉h in the target SOH table, respectively. The target D|_0W of the electric vehicle 1 is 1000 km and the target D_high is 2000 km, and thus, the target SOHi_ow is 95% and the target SOHhigh is 90%. When these values are substituted in the formula above, the target SOH of the electric vehicle 1 is 93%. Since the actual SOH of the electric vehicle 1 is 91%, the battery of the electric vehicle ^" 1 is assumed to be deteriorated.

Next, the vehicle information unit 12 refers to the SOH mapping table, and calculates a life parameter y according to the actual SOH of the electric bus. The life parameter y may be calculated by the following formula.

[Math. 26]

(actual SOH - actual SOH_low)(y_low - y_hlgh)

(actual SOH_low - actual SOH_high )

Here, y is the upper or lower limit of the remaining energy or the maximum charge or discharge rate, and the actual SO Hiow and the actual SOH_high are actual SOHs mapped on the SOH mapping table according to which actual SOH|_OW < actual SOH < actual SOH_high is true. In the case of the electric vehicle 1, since the actual SOH is 91%, when referring to the SOH mapping table of FIG. 46(a), the actual SOH|_OW is 90%, and the actual SOH_high is 95%.

Also, yiow and ymgh are life parameters y corresponding to the actual SOH|_OW and the actual SOHhigh in the SOH mapping table. The actual SOH|_OW of the electric vehicle 1 is 90% and the actual SO H high is 95%, and thus, in the case where the life parameter y is the lower limit of the remaining energy, yi_ow is 7 kWh and y_high is 6 kWh, and the lower limit of the remaining energy y of the electric vehicle 1 is 6.8 kWh.

The vehicle information unit 12 calculates a life parameter yadjusted that takes into account the deterioration of the battery based on the target SOH and the battery life-related parameter y calculated in the above manner. In the case where the life parameter y is the lower limit of the remaining energy, the life parameter yadjusted may be calculated by the following formula.

[Math. 27]

Yadjusted = y(l - (actual SOH - target SOr/)/Target SOH)

Since the lower limit of the remaining energy y of the electric vehicle 1^" is 6.8 kWh, the actual SOH is 91%, and the target SOH is 93%, the lower limit of the remaining energy yadjusted is about 6.9 kWh. Accordingly, the lower limit of the remaining energy of the battery information of the electric vehicle 1 is set to about 6.9 kWh.

Also, in the case where the life parameter y is the upper limit of the remaining energy or the maximum charge or discharge rate, the life parameter yad usted may be calculated by the following formula.

[Math. 28]

yad_justed = K(l + (actual SOH - target SOH)/Target SOH) In this manner, by comparing the actual SOH (actual SOH) and the SOH that is set in advance as the reference (target SOH), and setting the battery life-related parameter according to the deterioration of the battery, the rate of deterioration of the battery may be reduced, and the deterioration may be suppressed.

(Eighth Embodiment)

In the following, an eighth embodiment of the present invention will be described with reference to FIGS. 47 and 48. In the present embodiment, the operation planning unit 10 forms an operation plan that takes into account wireless power transfer or non-contact power transfer at a stop location (a bus stop or the like) other than the charging station. Specifically, the remaining energy EVrem of an electric bus that is to be used at the time of evaluation of the charging feasibility or calculation of the amount of charging energy at a charging station is calculated while taking into account the amount of charging energy by wireless power transfer at a stop location.

FIG. 47 is a diagram showing an example of an operation plan that is formed while taking into account wireless power transfer or the like at a stop location. In FIG. 47, charging stations A and F are provided with charging equipment capable of quick charging and slow charging, and a bus stop D is provided with wireless power transfer equipment capable of wirelessly transferring power to an electric bus. An electric bus is wirelessly charged with power by the wireless power transfer equipment while stopping at the bus stop D. As shown in FIG. 47, in this operation plan, not only the amount of charging energy at a charging station, but also the amount of charging energy at the bus stop D is planned.

The operation planning process of the present embodiment will be described in detail with reference to FIG. 48. Here, FIG. 48 is a flow chart showing a determination process of the charging feasibility of the present embodiment. As shown in FIG. 48, steps S401 to S409 are the same as those of the determination process of the charging feasibility according to the first embodiment described with reference to FIG. 25.

That is, first, the operation planning unit 10 acquires an arrival point Ta and a candidate departure point Td (step S401), the supply power Pj,i(t) (kW), Pj,₂(t) (kW), the sampling interval s (sec), the stationary battery information, the lower limit of the remaining energy EVIow (kWh) of an electric bus, and the like (step S402). Next, the arrival time at the arrival point Ta is set as the starting time ts, and the departure time at the candidate departure point Td is set as the ending time te (step S403), the supply power P(t) is set to the supply power Pi,i(t) at the power level 1 (step S404), and the amount of supply energy Eg (kWh) to be supplied by the power grid from the starting time ts to the ending time te is calculated based on each parameter which has been set (step S405). Then, the stationary battery information of a stationary battery SSB that may be used at the arrival point Ta is extracted from the stationary battery information by using the node ID of the arrival point Ta (step S406), an arrival point Tap immediately preceding the arrival point Ta is extracted from the arrival point list (step S407), and the remaining energy E_SSB (kWh) for a case where the stationary battery SSB is charged with the supply power at the power level 1 from the arrival time at the arrival point Tap to the arrival time at the arrival point Ta is calculated based on the extracted arrival point Tap (step S408). Furthermore, the energy Eavail (kWh) that is available at the arrival point Ta from the starting time ts to the ending time te is calculated based on the amount of supply energy Eg (kWh) and the remaining energy E_SSB (kWh) of the stationary battery SSB calculated in the above steps (step S409).

When the energy Evail that is available is calculated, a factor R of the amount of charging energy by the wireless power transfer is set (step S41001). The factor R is the fraction of the maximum amount of charging energy by the wireless power transfer, and is used to estimate the remaining energy EVrem at the arrival point Ta. In the case where the factor R is set to one, the remaining energy EVrem is estimated while assuming that the electric bus is to be charged with the maximum amount of charging power by the wireless power transfer, and in the case where the factor R is set to zero, the remaining energy EVrem is estimated while assuming that the electric bus is not charged by the wireless power transfer.

Next, the remaining energy EVrem (kWh) of the electric bus at the arrival point Ta that takes the wireless power transfer into account is estimated by using the factor R which has been set (step S41002). The remaining energy EVrem may be calculated by the following formula.

[Math. 29]

EVrem (kWh) = EVrem_TD (kWh) - required energy of bus schedule (kWh) + R χ Ewe (kWh)

Here, EVrem_To is the remaining energy at the departure point of the bus schedule of the arrival point Ta. Accordingly, the EVrem that is calculated in the present embodiment is the EVrem calculated in the first embodiment (remaining energy at departure point of bus schedule of arrival point Ta - required energy of bus schedule) to which R χ Ewe has been added. Here, the Ewe is the maximum amount of charging energy by the wireless power transfer, and is calculated by the following formula on the assumption that the electric bus is to be charged with the maximum output power of the wireless power transfer equipment while the electric bus is stopping at the bus stop. [Math. 30] ^'

The P_mc,i (kW) is the maximum output power of the wireless power transfer equipment at a bus stop i, and the T_s,i (sec) is the stop time at the bus stop i. That is, the Ewe (kWh) is the maximum amount of charging energy that can be charged in the case where the electric bus stops at the stop location according to the operation plan, and the electric bus is constantly charged with the maximum output power of the wireless power transfer equipment during the stop. Additionally, information about the power transfer capacity of the wireless power transfer equipment, such as the P_mc,i (kW), is stored in the charging equipment information unit 14, for example.

When the electric bus actually operates, the stop time at a bus stop may change depending on the number of passengers, or the electric bus may pass through a bus stop where no passenger gets off or on, and charging by Ewe (kWh) may not be always possible. Accordingly, the factor R is set while taking into account such dynamic factors. In the present embodiment, the factor R is set within the range of 0.5 < R < 1.0, and in step

541001, the R is set to 0.5. Additionally, the factor R may be arbitrarily set within the range of 0 < R < 1.

In steps S411 to S416, whether or not charging of a predetermined amount of charging energy at a charging point is possible is determined based on the EVrem calculated in step

541002. Steps S411 to S416 are the same as those of the determination process of the charging feasibility in the first embodiment. That is, the lower limit of the remaining energy EVIow of an electric bus, the remaining energy EVrem of the electric bus at the arrival point Ta, the required energy Ereq of the bus schedule of the departure point Td, and the energy Eavail that is available at the arrival point Ta are compared (step S411), and in the case where Eavail + EVrem - Evlow > Ereq is established (YES in step S411), the required amount of discharge energy Essereq is calculated (step S415), and charging of the predetermined amount of energy is determined to be possible (step S416), and the process proceeds to step S10511 of the evaluation process. On the other hand, in the case where Eavail + EVrem - Evlow > Ereq is not established (NO in step S411), the supply power P(t) is set to Pi,₂(t) (step S413), and the same process as above is performed also at the power level 2 (steps S405 to S411). If the formula mentioned above is not established in step S411 at the power level 2, charging is determined to be not possible (step S414).

In the present embodiment, the process does not directly proceeds to step S412 when the formula of step S411 is not established, and first, whether or not the R is smaller than one is determined (step S41003) . In the case where the R is one (NO in step S41003), the process proceeds to step S412, and in the case where the R is smaller than one (YES in step S41003), the factor R is increased by a predetermined amount AR (R = R + AR) (step S41004), and the process returns to step S41002. Also, in the case where charging is determined to be possible (step S416), calculation of the amount of charging energy is performed using the factor R that is set at the time point.

As described above, according to the present embodiment, charging feasibility is determined while gradually increasing the EVrem by gradually increasing the amount of charging energy Ewe by the wireless power transfer from half the amount (R = 0.5) to full amount (R = 1.0). Charging feasibility may thereby be determined while taking into account dynamic factors such as a change in the stop time at a bus station and passing through of a bus station . Additiona lly, in the determination in step S41003, a threshold value r smaller than one (for example, 0.9 or 0.8) may be set, and R < r may be determined. An operation plan according to which charging is possible may thereby be formed with ease.

(Ninth Embodiment)

In the following, a ninth embodiment of the present ^~ invention will be described with reference to FIGS. 49 to 51. In the present embodiment, as in the third embodiment, an arrival point is acquired in the ascending order of time, and is connected to candidate departure points. At this time, a predetermined number of candidate departure points where charging is possible are extracted from the candidate departure points for an acquired arrival point. Then, a candidate departure point satisfying a predetermined condition is selected from the extracted candidate departure points and is connected to the arrival point so that an operation plan is created . The operation pla nning unit 10 creates a plurality of operation plans while changing the number of candidate departure points to be extracted, calculates the evaluation value of each operation plan, and selects, according to the evaluation values, the operation plan that is to be actually used.

Now, FIG. 49 is a block diagram showing a functional configuration of the operation management device according to the ninth embodiment. As shown in FIG. 49, the operation planning unit 10 according to the present embodiment further includes bus schedule selection unit 105 and operation plan evaluation unit 106. Other structural elements are the same as those in the first embodiment.

The bus schedule selection unit 105 selects a candidate departure point satisfying a predetermined condition from a predetermined number of candidate departure points that are evaluated to be able to perform charging. The predetermined condition is set according to the aim of the operation plan that is to be formed. The predetermined condition may be that the distance of the bus schedule is the longest, that the distance of the bus schedule is the shortest, that the length of a traffic jam occurring in the bus schedule is the shortest, or that the duration of a traffic jam occurring in the bus schedule is the shortest, for example.

For example, in the case of forming an operation plan aiming at reducing the fuel cost or CO2 emissions, the bus schedule selection unit 105 selects a candidate departure point included in a bus schedule with the longest traveling distance, from a predetermined number of candidate departure points. By allocating an electric bus to the bus schedule including the selected candidate departure point with the vehicle allocation unit 101 preferentially, the traveling distance of a non-electric vehicle may be minimized, and the fuel cost and the CO2 emissions may be reduced.

Also, in the case of forming an operation plan aiming at extending the life of the battery of an electric bus, the bus schedule selection unit 105 selects a candidate departure point included in a bus schedule with the shortest traveling distance, from a predetermined number of candidate departure points. By preferentially allocating an electric bus with deteriorated battery to the bus schedule including the selected candidate departure point with the vehicle allocation unit 101, the degrees of deterioration of batteries of electric buses may be homogenized, and the life of batteries may be extended for the entire bus route network.

Furthermore, in the case of forming an operation plan aiming at preventing energy shortage of an electric bus, the bus schedule selection unit 105 selects a candidate departure point included in a bus schedule with a traffic jam of the shortest length and the shortest duration, from a predetermined number of candidate departure points. By preferentially allocating an electric bus with a battery with a low remaining energy or small effective capacity to the bus schedule including the selected candidate departure point with the vehicle allocation unit 101, energy shortage may be prevented.

Additionally, the predetermined condition is not limited to those described above, and may be arbitrarily set according to the aim of the operation plan to be formed. Also, in the present embodiment, the vehicle allocation unit 101 sets, according to the aim of the operation plan to be formed, degrees of priority to vehicles registered in the operation management device, and allocate the vehicles according to the degrees of priority.

The operation plan evaluation unit 106 calculates the evaluation values of the operation plans which have been created, and selects an operation plan that is to be actually used, according to the evaluation values. As the evaluation value, the length of the traveling distance of the electric bus, or the number of allocated vehicles may be used, for example. The evaluation value may be arbitrarily set according to the aim of the operation plan to be formed.

Next, an operation planning process of the present embodiment will be described with reference to FIG. 50. FIG. 50 is a flow chart showing an operation planning process of the present embodiment. In the following, a process for a case where an operation plan aiming at reducing the fuel cost or C02 emissions is to be formed will be described.

As shown in FIG. 50, first, the operation planning unit 10 sets a parameter k to one (step S9001). The parameter k is the number of candidate departure points to be extracted. Here, k is set to one as an initial value, but the initial value of k may be arbitrarily set.

Next, the operation planning unit 10 generates an arrival point list, a candidate departure point list, and a list of electric vehicles that can be allocated (step S9002), and acquires an arrival point in the order according to the generated arrival point list, that is, in the ascending order of the arrival time at the arrival point (step S9003). An electric bus is allocated to a bus schedule of the departure point whose departure time is earlier than the arrival time at the acquired arrival point and has not yet been allocated an electric bus (step S9004).

In the case of forming an operation plan aiming at reducing fuel cost and CO2 emissions, it is desirable to allocate an electric vehicle to the bus schedules as much as possible, rather than a non-electric vehicle. To this end, the degree of priority of an electric bus is set to be higher than the degree of priority of a non-electric vehicle. The vehicle allocation unit 101 allocates an electric vehicle to the bus schedule according to such degree of priority, and if there is no electric vehicle that can be allocated, vehicle allocation is not performed.

Next, the charging feasibility evaluation unit 104 refers to the candidate departure point list, and extracts k candidate departure points where charging is possible from the candidate departure points for the acquired arrival point (step S9005). Here, FIG. 51 is a diagram for describing an extraction method of the candidate departure point. In FIG. 51, the arrival point acquired in step S9003 is 1, and the candidate departure points for the arrival point 1 are departure points 2 to 7, and k is three.

The charging feasibility evaluation unit 104 evaluates the charging feasibility of each candidate departure point for the arrival point 1 in turn until three candidate departure points where charging is possible are found. In FIG. 51, charging is not possible at the departure points 2 and 3, and charging is possible at the departure points 4 to 6. Accordingly, the charging feasibility evaluation unit 104 evaluates the charging feasibility for the departure point 2 to the departure point 6 in turn, and when the departure point 6 has been evaluated and three departure points 4 to 6 where charging is possible have been found, the evaluation is ended, and the departure points 4 to 6 are extracted.

Additionally, in FIG. 51, k departure points are extracted from the candidate departure points, but in the case where there are not k candidate departure points where charging is possible, the charging feasibility evaluation unit 104 ends the evaluation when the charging feasibility of all the candidate departure points has been evaluated, and extracts all the candidate departure points where charging is possible which have been found. In this case, the number of candidate departure points to be extracted is less than k.

In step S9005 if one or more candidate departure points are extracted (YES in step S9006), the bus schedule selection unit 105 selects, from the extracted candidate departure points, a bus schedule with the longest traveling distance, and the vehicle allocation unit 101 allocates an electric bus to the selected bus schedule (step S9007). In the case of FIG. 51, a bus schedule 5 from the departure point 5 with the longest traveling distance (15 km) is selected from the departure points 4 to 6 which have been extracted.

In step S9007, the vehicle allocation unit 101 allocates an electric bus according to the degree of priority set for each electric bus. As the electric vehicle allocation method, a method of preferentially allocating an electric vehicle whose battery has a low degree of deterioration is conceivable, for example. Then, the degrees of deterioration of batteries of electric buses may be homogenized, and the life of batteries may be extended for all the electric buses. After step S9007 has been performed, or when there was no candidate departure point where charging is possible (NO in step S9006), the operation planning unit 10 updates the electric bus battery information, the stationary battery information, the vehicle allocation list, the charge list, and various parameters such as the supply power Pi, 1 (t), Pi,2(t) and the like (step S9008).

If there is a next arrival point in the arrival point list (YES in step S9009), the process returns to step S9003, and the operation planning unit 10 acquires the next arrival point (step S9003), and repeats steps S9004 to S9008.

On the other hand, in the case where there is no next arrival point in the arrival point list (NO in step S9009), that is, in the case where the process is completed for all the arrival points in the arrival point list, the vehicle allocation unit 101 allocates a non-electric vehicle to a bus schedule to which an electric bus is not allocated (step S9010). An operation plan for a case where k is one is thereby generated.

In step S9010, a bus schedule to which an electric bus is not allocated is a bus schedule for which there is no electric bus that can be allocated. The vehicle allocation unit 101 connects such bus schedules, and allocates a non-electric vehicle according to the degree of priority of each vehicle. As the allocation method of a non-electric vehicle, a method of preferentially allocating a diesel-powered vehicle rather than a gasoline-powered vehicle, or a method of preferentially allocating a non-electric vehicle with lower energy consumption rate is conceivable, for example. Thus, fuel cost and CO2 emissions may be further reduced.

Moreover, any method may be used as the connection method of bus schedules to which a non-electric vehicle is to be allocated. As the connection method, there may be cited a method of connecting a candidate departure point closest to the arrival point, for example.

Next, the operation planning unit 10 increments the parameter k by one (step S9011), and sets the parameter k to 2. The amount of increase in the parameter k is not limited to one, and may be arbitrarily set. Also, the initial value of k may be set to a value of two or more, and be gradually reduced by the amount of one.

In the case where the parameter k set in step S9011 is equal to or less than a maximum value kmax of the parameter k set in advance (YES in step S9012), the process returns to step S9002, and the processes from step S9002 to step S9011 are repeated. An operation plan for a case where k is two is thereby generated.

The maximum value kmax of the parameter k may be determined by the following formula according to the number of candidate departure points for each arrival point included in the basic bus schedule.

kmax = max(NCDP(apl), NCDP(ap2),..., NCDP(apn))

In the above formula, NCDP(apn) is the number of candidate departure points for an arrival point apn.

On the other hand, in the case where the parameter k set in step S9011 is greater than the maximum value kmax of the parameter k set in advance (NO in step S9012), the operation plan evaluation unit 106 selects, according to the evaluation values, an operation plan from a plurality of operation plans generated for respective values of k (step S9013). The operation plan selected by the operation plan evaluation unit 106 is stored -in the plan storage unit 15 as the operation plan that is to be actually used (step S9014).

In step S9013, the operation plan evaluation unit 106 may use the traveling distance of an electric bus as the evaluation value and select an operation plan with the greatest evaluation value, or may use the traveling distance of a non-electric vehicle as the evaluation value and select an operation plan with the smallest evaluation value, for example. Also, the number of allocated vehicles may be used as the evaluation value in combination with the evaluation values mentioned above.

As described above, according to the present embodiment, a plurality of operation plans may be generated while changing the number of candidate departure points to be extracted, and an operation plan with the best evaluation value may be selected. Moreover, the evaluation value may be maximized by allocating a vehicle to a bus schedule according to the degree of priority of each vehicle.

For example, in the case of allocating an electric bus and a non-electric vehicle to a bus schedule at the same time without setting the degree of priority to each vehicle, the number of bus schedules (candidate departure points) to which an electric bus may be allocated may be reduced, and the traveling distance of an electric bus may not be maximized. However, according to the present embodiment, the traveling distance of an electric bus may be maximized by preferentially allocating the electric bus, and fuel cost and C02 emissions may be effectively reduced.

Additionally, in FIG. 50, the operation plan evaluation unit 106 selects an operation plan with a good evaluation value after operation plans for all the k values have been created, but an operation plan may be selected every time an operation plan for a k value is created. That is, after an operation plan for a k value is created in step S9010, the evaluation value of this operation plan and the evaluation value of the operation plan created for the previous k value are compared, and the operation plan with the better evaluation value is selected. This is repeated for each k value, and the operation plan that is finally selected is stored in the plan storage unit 15 as the operation plan to be actually used.

Also, the operation plan may be created not only for the k value, but also for each power level of a charging station. That is, an operation plan for a case of performing charging at the power level 1 and an operation plan for a case of performing charging at the power level 2 may be created for each k value.

Moreover, in the description above, two types of degrees of priority are set for a vehicle to be allocated to a bus schedule, namely, the degree of priority based on the vehicle types, and the degree of priority set within each vehicle type, but the method of setting the degree of priority is not limited to such approach, and it is also possible to set only the degree of priority based on each vehicle, for example. In this case, an electric bus or a non-electric vehicle is allocated, in steps S9004 and S9007, to a bus schedule including a candidate departure point according to the degree of priority of the vehicle, and step S9010 is omitted.

In step S9004, if a non-electric vehicle is allocated to a bus schedule including the arrival point acquired in step S9003, k closest candidate departure points may be extracted (step S9005), a candidate departure point satisfying a predetermined condition may be selected (step S9005), and the non-electric vehicle may be allocated to the bus schedule including the selected candidate departure point (step S9007). In the case of creating an operation plan aiming at reducing fuel cost and CO2 emissions, the predetermined condition may be that the traveling distance of the bus schedule is the shortest, for example.

That is, in the case of allocating an electric bus to a bus schedule including the arrival point, this bus schedule and a bus schedule with the longest traveling distance, among the bus schedules including the candidate departure points, are connected, and in the case of allocating a non-electric vehicle to ^" a bus schedule, this bus schedule and a^" bus schedule with^" the shortest traveling distance, among the bus schedules including the candidate departure points, are connected. Then, the traveling distance of an electric bus may be increased, and the traveling distance of a non-electric vehicle may be reduced.

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 inventions. Indeed, the novel methods and systems described herein may be embodied in a variety of other forms; furthermore, various omissions, substitutions and changes in the form of the methods and systems described herein may be made without departing from the spirit of the inventions. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the inventions.

Claims

1. An operation management device comprising :

vehicle information unit for storing vehicle information about a plurality of electric vehicles each with a battery;

charging equipment information unit for storing charging equipment information about charging capacity of charging equipment capable of charging the electric vehicles, with the charging equipment being located at a plurality of charging stations;

bus schedule unit for storing bus schedule information specifying a plurality of bus schedules, each of which includes a route connecting a plurality of stop locations where the electric vehicles are to stop, and at least one of a departure time and an arrival time at each stop location on the route;

route information unit for storing route information about the route; and

operation planning unit for forming an operation plan by allocating the electric vehicles to each bus schedule specified by the bus schedule information,

wherein the operation planning unit calculates an amount of energy consumption that is consumed by the electric vehicle at the time of operating along the route, calculates an amount of charging energy to be charged in the electric vehicle at each charging station based on the amount of energy consumption and allocates the electric vehicle to the bus schedule based on the amount of charging energy.

2. The operation management device according to claim 1, wherein the operation planning unit allocates the electric vehicle to the bus schedule in such a way that the remaining energy of the battery after charging of the amount of charging energy in the battery does not exceed the effective capacity of the battery.

3. The operation management device according to claim 1 or 2, wherein the operation planning unit allocates the electric vehicle to the bus schedule in such a way that the minimum charge rate, necessary for charging the amount of charging energy in the electric vehicle during a chargeable period that is all or a part of the period from the arrival time to the departure time of the electric vehicle at the charging station, is equal to or less than the maximum charge rate that is set in advance for the battery.

4. The operation management device according to any one of claims 1 to 3,

wherein the operation planning unit allocates an electric vehicle with the battery with higher effective capacity to the bus schedule for which the total of the amount of energy consumption necessary for an operation along the route is higher.

5. The operation management device according to any one of claims 1 to 4,

wherein the operation planning unit calculates the amount of energy consumption by adding a predetermined amount of surplus energy to the amount of energy obtained by multiplying the distance of the route included in the bus schedule with the energy consumption rate of the electric vehicle.

6. The operation management device according to any one of claims 2 to 5,

wherein the operation planning unit calculates the amount of charging energy in such a way that the remaining energy of the electric vehicle in operation is at or above a lower limit of remaining energy specified in advance for the battery of the electric vehicle, or is at or below an upper limit of remaining energy specified in advance for the battery, or is at or above the lower limit of remaining energy and at or below the upper limit of remaining energy.

7. The operation management device according to any one of claims 3 to 6,

wherein the operation planning unit includes evaluation unit for evaluating whether charging of the amount of charging energy in the electric vehicle within the chargeable period at the charging station is possible or not and allocates the electric vehicle to the bus schedule based on the evaluation by the evaluation unit.

8. The operation management device according to any one of claims 1 to 7, further comprising :

re-planning determination unit for determining whether or not to re-plan an operation plan formed by the operation planning unit,

wherein the re-planning determination unit determines re-planning of the operation plan based on information that changes during operation of the electric vehicle, with the information that changes includes at least one of the vehicle information, the charging equipment information, and the route information, and

wherein in a case where the re-planning determination unit has determined that the operation plan is to be re-planned, the operation planning unit forms the operation plan again.

9. The operation management device according to claim 8, wherein the re-planning determination unit calculates the delay time of the electric vehicle that is operating according to the operation plan, compares the delay time with a threshold value specified in advance and determines whether to re-plan the operation plan or not.

10. The operation management device according to claim 8 or 9,

wherein the re-planning determination unit acquires remaining energy of the electric vehicle that is operating according to the operation plan, compares the remaining energy with a threshold value specified in advance and determines whether to re-plan the operation plan or not.

11. The operation management device according to any one of claims 7 to 10,

wherein in a case where the evaluation unit evaluates that charging is possible, the operation planning unit selects one bus schedule from the bus schedules according to an ascending order of arrival time at an arrival point, takes an arrival point of the selected bus schedule as a departure point, and allocates the same electric vehicle of the selected bus schedule to a bus schedule of that departure time that is after the arrival time at the arrival point and that is the closest to the arrival time.

12. The operation management device according to any one of claims 1 to 11,

wherein at least one of a departure point and an arrival point of at least part of bus schedules is a non-charging station that does not have any charging equipment, and

wherein in a case where the arrival point of the bus schedule is the non-charging station, the operation planning unit calculates amounts of energy consumption at the time of operation from the non-charging station to each charging station and calculates the amount of charging energy based on the maximum amount of energy consumption among the amounts of energy consumption calculated and an amount of energy consumption that is consumed at the time of the electric vehicle operating until arriving at the arrival point.

13. The operation management device according to any one of claims 1 to 12,

wherein at least one of a lower limit of remaining energy, an upper limit of remaining energy, a maximum charge rate, and a maximum discharge rate specified in advance for the battery of the electric vehicle is calculated according to a state of deterioration of the battery.

14. The operation management device according to any one of claims 1 to 13,

wherein wireless power transfer equipment for wirelessly transferring power to the electric vehicle while the electric vehicle is stopped is installed at least part of stop locations where the electric vehicle is to stop,

wherein the charging equipment information unit stores information about power transfer capacity of the wireless power transfer equipment, and

wherein the operation planning unit calculates an amount of energy to be charged in the electric vehicle by wireless power transfer at the stop location, and based on the amount of the energy, calculates an amount of charging energy to be charged in the electric vehicle at the charging station.

15. The operation management device according to any one of claims 1 to 14,

wherein the operation planning unit forms an operation plan by acquiring one arrival point in an ascending order of arrival time, extracts a predetermined number of candidate departure points for the acquired arrival point, selects a candidate departure point satisfying a predetermined condition from the extracted candidate departure points, and allocates the same electric vehicle as that of the bus schedule including the acquired arrival point to a bus schedule including the selected candidate departure point.

16. The operation management device according to claim 15, wherein the operation planning unit forms a plurality of operation plans while changing the predetermined number of candidate departure points for the acquired arrival point, calculates evaluation value for each operation plan formed, and selects an operation plan according to the evaluation values.

17. The operation management device according to claim 15 or 16, wherein the predetermined condition is that the distance of a bus schedule is the longest, that the distance of a bus schedule is the shortest, that the length of a traffic jam occurring in a bus schedule is the shortest, or that the duration of a traffic jam occurring in a bus schedule is the shortest.

18. The operation management device according to any one of claims 15 to 17,

wherein the operation planning unit extracts a candidate departure point that is evaluated to be able to charge an electric vehicle within the chargeable period.

19. The operation management device according to any one of claims 15 to 18,

wherein the operation planning unit allocates a non-electric vehicle to a bus schedule including the candidate departure point in a case where there is no electric vehicle that can be allocated.

20. An operation planning method for allocating an electric vehicle to each bus schedule specified by bus schedule information and forming an operation plan based on:

vehicle information about a plurality of electric vehicles each with a battery,

charging equipment information about charging capacity of charging equipment capable of charging the electric vehicles, the charging equipment being located at a plurality of charging stations,

the bus schedule information specifying a plurality of bus schedules each including a route connecting a plurality of stop locations along which the electric vehicles are to operate, and at least one of a departure time and an arrival time at each stop location on the route, and

route information about the route,

wherein an amount of energy consumption that is consumed at a time of the electric vehicle operating along each route is calculated, an amount of charging energy to be charged in the electric vehicle at each charging station is calculated based on the amount of energy consumption, and the electric vehicle is allocated to the bus schedule based on the amount of charging energy.