JP7740145B2 - Charging system and charging schedule determination method - Google Patents

Description

This disclosure relates to a charging system and a method for determining a charging schedule.

JP 2021-106498 A (Patent Document 1) discloses a control device that allows a vehicle connected to power equipment to receive power if the vehicle is a pre-registered vehicle.

Japanese Patent Application Laid-Open No. 2021-106498

In a charging system that charges a power storage device, the user generally determines the charging schedule. However, to increase user convenience, if the user wishes to leave the determination of the charging schedule to a device (e.g., a computer), the device may determine the charging schedule on the user's behalf. Since the appropriate charging schedule differs for each user, the device may determine the charging schedule based on the user's characteristics. However, the device may not be in a state where it fully understands the user's characteristics and can determine an appropriate charging schedule. If the user leaves the determination of the charging schedule to the device when the device does not fully understand the user's characteristics, there is a possibility that an appropriate charging schedule will not be determined.

This disclosure has been made to solve the above problem, and its purpose is to make it easier for a device to determine an appropriate charging schedule in response to a user request.

According to an embodiment of a first aspect of the present disclosure, there is provided a charging system as described below.
(Item 1) The charging system includes a management device that manages user information related to users of resources equipped with power storage devices, and a user terminal that accepts input from users. The management device is configured to use the user information to learn about the user's resource usage schedule. The management device is configured to transmit information indicating the accuracy of the learning to the user terminal. If the accuracy of the learning exceeds a predetermined level, the user terminal accepts an input requesting charging of the power storage device according to the learned usage schedule, and if the accuracy of the learning does not exceed the predetermined level, the user terminal does not accept the input.

Hereinafter, charging the power storage device according to the learned usage schedule is also referred to as "automatic charging." In the above charging system, the management device uses user information (e.g., information indicating the user's characteristics) to learn about the user's resource usage schedule. The management device then transmits information indicating the accuracy of the learning to the user terminal. A management device in a state where the learning accuracy exceeds a predetermined level (hereinafter also referred to as a "learning completed state") is considered to be in a state where it can determine an appropriate charging schedule. The user terminal does not accept input of an automatic charging request when the management device has not yet reached the learning completed state. This prevents the user from requesting automatic charging when the management device has not yet reached the learning completed state. Then, once the management device reaches the learning completed state, the user terminal accepts input of an automatic charging request. This allows the user to request automatic charging. This makes it easier for the management device to determine an appropriate charging schedule in response to a user request.

The charging system described in paragraph 1 above may have the configuration described in any one of paragraphs 2 to 4 below.

(Section 2) The charging system described in Section 1 further has the following feature: If the accuracy of the learning exceeds a predetermined level, the user terminal is configured to display an operation unit that accepts an input requesting that the power storage device be charged in accordance with the learned usage schedule, and if the accuracy of the learning does not exceed the predetermined level, not to display the operation unit.

With the above configuration, the user terminal can easily switch whether or not to accept input of an automated charging request by switching the display/non-display of the operation unit (e.g., a button).

(Clause 3) The charging system described in paragraph 1 or 2 further has the following features: The resource is a vehicle equipped with a charging circuit that charges the power storage device using power from outside the vehicle and a charging control device that controls the charging circuit. The user information includes information indicating how the user uses the vehicle. The management device is configured to sequentially receive user information from at least one of the vehicle and the user terminal and perform learning using the received user information. The learned usage schedule indicates the scheduled departure time of the vehicle and the target storage amount of the power storage device. If the accuracy of the learning exceeds a predetermined level, the user terminal is configured, upon receiving input from the user requesting that the power storage device be charged in accordance with the learned usage schedule, to request the charging control device to control the charging circuit so that the storage amount of the power storage device is equal to or greater than the target storage amount at the scheduled departure time.

The above configuration makes it easier for the management device to determine an appropriate charging schedule that matches the vehicle's scheduled departure time and the target storage amount of the power storage device, depending on how the user uses the vehicle. Then, when the user terminal receives a request for automatic charging from the user, the vehicle's charging control device can easily control the charging circuit in accordance with the determined charging schedule.

The vehicle may also be an electric vehicle (xEV) that uses electricity as all or part of its power source. xEVs include BEVs (electric vehicles), PHEVs (plug-in hybrid vehicles), and FCEVs (fuel cell vehicles).

(4) The charging system described in any one of paragraphs 1 to 3 further has the following feature: While charging the power storage device according to the learned usage schedule, the user terminal determines whether the accuracy of the learning exceeds a predetermined level, and if it determines that the accuracy of the learning has fallen below the predetermined level, the user terminal issues a notification urging the user to stop charging the power storage device according to the learned usage schedule.

With the above configuration, if the management device is no longer in a learning-complete state during automatic charging, the user can be prompted to stop automatic charging. This prevents automatic charging from continuing when the management device has not yet completed learning. The user can stop automatic charging at their own discretion and determine their own charging schedule.

According to an embodiment of the second aspect of the present disclosure, there is provided a charging schedule determination method as shown below.

(Section 5) The charging schedule determination method includes a management device that manages user information about users of a resource equipped with a power storage device, using the user information to learn about the user's resource usage schedule; the management device transmitting information indicating the accuracy of the learning to the user terminal of the resource; the user terminal determining whether the accuracy of the learning exceeds a predetermined level; and, if it is determined that the accuracy of the learning exceeds the predetermined level, the user terminal accepting an input requesting that the power storage device be charged in accordance with the learned usage schedule.

As with the charging system described above, the charging schedule determination method described above also makes it easier for the management device to determine an appropriate charging schedule in response to user requests.

According to another aspect, there is provided a program that causes a computer to execute the method described in paragraph 5. In one aspect, there is provided a computer device that includes a storage device that stores the program and a processor that executes the program stored in the storage device. In another aspect, there is provided a computer device that distributes the program.

This disclosure makes it easier for devices to determine an appropriate charging schedule in response to user requests.

1 is a diagram illustrating a schematic configuration of an energy management system according to an embodiment of the present disclosure. FIG. 2 is a diagram showing the configuration of the vehicle and EVSE shown in FIG. 1 . FIG. 10 is a diagram illustrating a charging mode setting screen displayed on a mobile terminal in the charging system according to the embodiment of the present disclosure. 3 is a flowchart illustrating a charging schedule determination method according to an embodiment of the present disclosure. 5 is a diagram for explaining three types of charging modes (normal charging mode, smart charging mode, and automatic charging mode) set by the process shown in FIG. 4. FIG. 10 is a flowchart illustrating a process executed when learning accuracy for predicting vehicle usage is reduced after learning is completed in a charging schedule determination method according to an embodiment of the present disclosure. 7 is a flowchart showing a modified example of the process shown in FIG. 6 .

Embodiments of the present disclosure will be described in detail with reference to the drawings. In the drawings, identical or equivalent parts are designated by the same reference numerals and their description will not be repeated.

Figure 1 is a diagram showing the general configuration of an energy management system according to an embodiment of the present disclosure. Referring to Figure 1, the energy management system according to this embodiment includes a group of vehicles 1, a group of EVSEs 2, a server 700, a power generation facility 800, a server 900, and a management device 1000. The management device 1000 includes servers 200 and 500. EVSE stands for Electric Vehicle Supply Equipment. The energy management system according to this embodiment corresponds to an example of a "charging system" according to the present disclosure.

Each of the servers 200, 500, 700, and 900 is a computer equipped with, for example, an HMI (Human Machine Interface) and a communication I/F (Interface). Each computer includes a processor and a storage device. The storage device stores programs executed by the processor as well as information used by the programs (e.g., maps, formulas, and various parameters). The HMI includes an input device and a display device. The HMI may be a touch panel display.

The power grid PG is a power network constructed by power transmission and distribution facilities. Multiple power plants (not shown) are connected to the power grid PG. The power grid PG receives power from these power plants. In this embodiment, the power transmission and distribution company corresponds to the TSO (system operator) of the power grid PG (commercial power source). The power grid PG supplies AC power (e.g., single-phase or three-phase AC power). The server 700 corresponds to a computer belonging to the power transmission and distribution company.

Server 500 periodically communicates with each vehicle included in vehicle group 1. In this embodiment, each vehicle included in vehicle group 1 is an xEV and is configured to operate as a regulating power for the power grid PG. Each vehicle included in vehicle group 1 is a privately owned vehicle (POV). The user of the vehicle corresponds to the administrator who manages that vehicle. The number of vehicles included in vehicle group 1 may be between 5 and 30, between 30 and 100, or 100 or more. Vehicle group 1 includes vehicle 100 having the configuration described below (see Figure 2). The configuration of vehicle 100 and the other vehicles in vehicle group 1 may be the same or different.

EVSE group 2 includes multiple EVSEs that receive power from the power grid PG. Server 200 communicates with each EVSE as needed. EVSE group 2 includes EVSE 300 having the configuration described below (see FIG. 2). EVSE group 2 may include multiple types of EVSEs (e.g., normal chargers and rapid chargers). EVSEs may include both public EVSEs (e.g., EVSEs installed in commercial facilities, car dealerships, or highway parking areas) and non-public EVSEs (e.g., residential EVSEs). The number of EVSEs included in EVSE group 2 is arbitrary.

The management device 1000, server 700, server 900, each vehicle included in vehicle group 1, and each EVSE included in EVSE group 2 are configured to be able to communicate with each other via a communication network NW. Servers 700 and 900 communicate with server 200 via the communication network NW. In the management device 1000, server 200 and server 500 are configured to be able to communicate with each other. The communication network NW is, for example, a wide area network constructed using the Internet and wireless base stations. Each vehicle is configured to access the communication network NW via wireless communication and connect to the communication network NW. Each EVSE is connected to the communication network NW via, for example, a communication line. Note that the communication format is not limited to the above and can be changed as appropriate. For example, each EVSE may be connected to the communication network NW via wireless communication.

The power grid PG is configured to supply power to other entities besides the EVSE group 2. Specifically, the power grid PG is also electrically connected to buildings (e.g., homes, factories, or commercial facilities) not shown. The server 900 corresponds to a computer belonging to a retail electricity supplier. The retail electricity supplier pays a wheeling fee to the electricity transmission and distribution company and provides electricity to each consumer using the power grid PG. The retail electricity supplier procures electricity from an electricity market (e.g., a market established and operated by a wholesale electricity exchange) and power generation facilities 800 (e.g., power generation facilities belonging to power generation companies with which the retail electricity supplier has entered into a bilateral contract), and sells the procured electricity to multiple consumers. The power generation facilities 800 may include at least one of a pumped-storage power plant, a solar power plant, a wind power plant, a hydroelectric power plant, a geothermal power plant, a biomass power plant, and a nuclear power plant.

Figure 2 is a diagram showing the configuration of vehicle 100 and EVSE 300. Referring to Figure 2 together with Figure 1, EVSE 300 is configured to receive power from power grid PG and supply power. EVSE 300 incorporates power supply circuit 310 and includes charging cable 320. Power supply circuit 310 is electrically connected to power grid PG. Charging cable 320 has connector 320a (plug) at its tip. Power supply circuit 310 converts the power supplied from power grid PG into power suitable for supplying power to vehicle 100 and outputs the converted power to charging cable 320. EVSE 300 outputs power to be supplied to vehicle 100 from connector 320a.

Vehicle 100 is equipped with an inlet 60 to which connector 320a can be detachably attached. Inlet 60 corresponds to a charge/discharge port that functions as both a charge port and a discharge port. When connector 320a of charging cable 320 connected to the main body of EVSE 300 is connected to inlet 60 of parked vehicle 100, vehicle 100 is electrically connected to the power grid PG via EVSE 300 (hereinafter also referred to as the "plugged-in state"). On the other hand, for example, when vehicle 100 is traveling, vehicle 100 is electrically disconnected from both EVSE 300 and power grid PG (hereinafter also referred to as the "plugged-out state"). Note that while FIG. 2 shows only inlet 60 compatible with the power supply method of EVSE 300, vehicle 100 may be equipped with multiple inlets to support multiple power supply methods (e.g., AC and DC methods).

Vehicle 100 further includes battery 11, SMR (System Main Relay) 12, MG (Motor Generator) 20, PCU (Power Control Unit) 22, and electronic control unit (hereinafter referred to as "ECU (Electronic Control Unit)") 150. ECU 150 includes processor 151, RAM (Random Access Memory) 152, and storage device 153. ECU 150 may be a computer. Storage device 153 is configured to be able to save stored information. Storage device 153 stores programs as well as information used by the programs (e.g., maps, formulas, and various parameters). In this embodiment, processor 151 executes the programs stored in storage device 153, thereby performing various controls in ECU 150 (e.g., charging control and discharging control of battery 11). ECU 150 corresponds to an example of a "charging control device" according to the present disclosure.

Vehicle 100 is configured to be able to run using power stored in battery 11. Vehicle 100 according to this embodiment is an electric vehicle (BEV) that does not have an engine (internal combustion engine). A known vehicle power storage device (e.g., a liquid secondary battery, an all-solid-state secondary battery, or a battery pack) can be used as battery 11. Examples of vehicle secondary batteries include lithium-ion batteries and nickel-metal hydride batteries. Battery 11 corresponds to an example of a "power storage device" according to the present disclosure.

The vehicle 100 further includes a BMS (Battery Management System) 11a that monitors the status of the battery 11. The BMS 11a includes various sensors that detect the status of the battery 11 (e.g., voltage, current, and temperature) and outputs the detection results to the ECU 150. In addition to the above sensor functions, the BMS 11a may also have an SOC (State of Charge) estimation function, an SOH (State of Health) estimation function, a cell voltage equalization function, a diagnostic function, and a communication function. The ECU 150 can obtain the status of the battery 11 (e.g., temperature, current, voltage, SOC, and SOH) based on the output of the BMS 11a. The SOC indicates the remaining charge amount, and is, for example, the ratio of the current charge amount to the charge amount in a fully charged state, expressed on a scale of 0 to 100%. The SOH indicates the health or deterioration level, and is, for example, the ratio of the current full charge capacity to the initial full charge capacity, expressed on a scale of 0 to 100%.

The vehicle 100 further includes a charger/discharger 61 and a charge/discharge relay 62. The charger/discharger 61 and the charge/discharge relay 62 are located between the inlet 60 and the battery 11. The charger/discharger 61 and the charge/discharge relay 62 are each controlled by the ECU 150. In this embodiment, a charge/discharge line including the inlet 60, the charger/discharger 61, and the charge/discharge relay 62 is connected between the SMR 12 and the PCU 22. However, this is not limited thereto, and a charge/discharge line may also be connected between the battery 11 and the SMR 12.

In this embodiment, the charger/discharger 61 functions as both a charging circuit and a discharging circuit. The charger/discharger 61 charges the battery 11 using power input to the inlet 60 from outside the vehicle. The charger/discharger 61 discharges the power of the battery 11 to the outside of the vehicle through the inlet 60. The charger/discharger 61 includes a power conversion circuit. The power conversion circuit includes, for example, a bidirectional inverter. The power conversion circuit may perform DC (direct current)/AC (alternating current) conversion in both directions. The charge/discharge relay 62 switches between connecting and disconnecting the electrical path from the inlet 60 to the battery 11. The vehicle 100 further includes a monitoring module 61a that monitors the status of the charger/discharger 61. The monitoring module 61a includes various sensors (e.g., a current sensor and a voltage sensor) that detect the status of the charger/discharger 61 and outputs the detection results to the ECU 150.

When the vehicle 100 is plugged in, external charging (i.e., charging the battery 11 with power from outside the vehicle) and external power supply (i.e., power supply from the battery 11 to an external device) are possible. The vehicle 100 can adjust the power of the power grid PG through external charging and external power supply. Power for external charging is supplied to the inlet 60 from the power grid PG via the charging cable 320 of the EVSE 300, for example. The charger/discharger 61 converts the power received by the inlet 60 (e.g., AC power) into power (e.g., DC power) suitable for charging the battery 11 and outputs the converted power to the battery 11. Power for external power supply is supplied from the battery 11 to the charger/discharger 61. The charger/discharger 61 converts the DC power supplied from the battery 11 into power (e.g., AC power) suitable for external power supply and outputs the converted power to the inlet 60. The vehicle 100 is configured to enable reverse power flow with respect to the power grid PG. When either external charging or external power supply is being performed, the charge/discharge relay 62 is closed (connected), and when neither external charging nor external power supply is being performed, the charge/discharge relay 62 is open (disconnected).

MG20 is, for example, a three-phase AC motor generator. MG20 functions as a traction motor for vehicle 100. MG20 is driven by PCU22 and rotates the drive wheels of vehicle 100. MG20 also performs regenerative power generation and outputs the generated power to battery 11. Vehicle 100 is further equipped with a motor sensor 21 that monitors the state of MG20. Motor sensor 21 includes various sensors (e.g., a current sensor, a voltage sensor, and a temperature sensor) that detect the state of MG20 and outputs the detection results to ECU 150. Note that vehicle 100 may be equipped with any number of traction motors, and may be one, two, three, or more. The traction motors may be in-wheel motors.

The PCU 22 drives the MG 20 using power supplied from the battery 11. The SMR 12 switches between connecting and disconnecting the electrical path from the battery 11 to the PCU 22. The PCU 22 includes, for example, an inverter and a DC/DC converter. The SMR 12 and the PCU 22 are each controlled by the ECU 150. The SMR 12 is closed (connected) when the vehicle 100 is running. The SMR 12 is also closed when power is exchanged between the battery 11 and the inlet 60 (and ultimately, outside the vehicle).

The vehicle 100 further includes an HMI 81, a navigation system (hereinafter also referred to as "NAVI") 82, and a communication device 90.

The HMI 81 includes an input device and a display device. The HMI 81 may include a touch panel display. The HMI 81 may include a meter panel and/or a head-up display. The HMI 81 may include a smart speaker that accepts voice input.

NAVI82 includes, for example, a touch panel display, a GPS (Global Positioning System) module, a processor, and a storage device. The storage device stores map information. NAVI82 is configured to detect the position of vehicle 100 using GPS and display the position of vehicle 100 on a map in real time. NAVI82 refers to the map information and performs a route search to find the optimal route (e.g., the shortest route) from the current position of vehicle 100 to the destination. NAVI82 may also update the map information sequentially via OTA (Over The Air).

The communication device 90 includes a communication I/F that enables the vehicle 100 to communicate with devices external to the vehicle. Specifically, the communication device 90 includes a wireless communication device (e.g., a DCM (Data Communication Module)) that can access the communication network NW. The vehicle 100 communicates wirelessly with each of the servers 200 and 500, for example, in both the plugged-in state and the plugged-out state. In this embodiment, the vehicle 100 receives commands or notifications from each of the servers 200 and 500 via the wireless communication device. However, this is not limited to this, and the vehicle 100 may communicate wired with at least one of the servers 200 and 500 via the EVSE 300 in the plugged-in state.

The mobile terminal 400 is a terminal carried and operated by the administrator (vehicle user) of the vehicle 100. The mobile terminal 400 accepts input from the user. In this embodiment, a smartphone equipped with a touch panel display is used as the mobile terminal 400. The mobile terminal 400 has a built-in computer. However, the mobile terminal 400 is not limited to a smartphone. For example, a laptop, a tablet terminal, a wearable device (such as a smart watch or smart glasses), or an electronic key can also be used as the mobile terminal 400. The mobile terminal 400 corresponds to an example of a "user terminal" according to the present disclosure.

The communication device 90 includes a communication I/F for direct communication with a mobile terminal 400 located inside the vehicle or within the vicinity of the vehicle. The communication device 90 and the mobile terminal 400 may communicate via short-range communication such as wireless local area network (LAN), near field communication (NFC), or Bluetooth (registered trademark). However, any communication method can be used as the communication method between the vehicle 100 and the mobile terminal 400.

The mobile terminal 400 is registered in advance with the server 200, 500 and is configured to be able to communicate wirelessly with the server 200, 500. Predetermined application software (hereinafter referred to as a "mobile app") is installed on the mobile terminal 400. The server 200, 500 performs predetermined authentication before initiating communication with the mobile terminal, and communicates only with mobile terminals that have been successfully authenticated. This prevents mobile terminals not registered with the server 200, 500 from engaging in unauthorized communication. The user of the vehicle 100 can initiate communication with the server 200, 500 by inputting predetermined authentication information (information required for successful authentication) into the mobile terminal 400. Furthermore, by registering the predetermined authentication information in the mobile app, input of the authentication information can be omitted. The mobile terminal 400 can exchange information with the server 200, 500 via the mobile app.

In this embodiment, the mobile terminal 400 is equipped with a location sensor. The location sensor may be a sensor that uses GPS. The mobile terminal 400 transmits information indicating the user's location (hereinafter also referred to as "user location information") to the server 500 periodically or in response to a request from the server 500.

The vehicle system (the system that controls the vehicle 100) including the ECU 150 is switched on (operated)/off (stopped) by the user operating the start switch 70. The start switch 70 is installed, for example, inside the passenger compartment of the vehicle 100. The vehicle system starts when the start switch 70 is turned on. Furthermore, if the start switch 70 is turned off while the vehicle system is operating, the vehicle system stops. However, turning the start switch 70 off is prohibited when the vehicle 100 is moving. A vehicle start switch is generally called a "power switch" or "ignition switch."

Referring again to FIG. 1, server 200 corresponds to a computer belonging to an aggregator. The aggregator is an electric utility that provides energy management services by aggregating multiple distributed energy resources (hereinafter referred to as "DERs (Distributed Energy Resources)"). As will be described in detail below, the aggregator performs energy management using DERs. Each vehicle included in vehicle group 1 corresponds to an example of a "resource" according to the present disclosure and can function as a DER. Server 200 may remotely and integrally control multiple DERs (e.g., each vehicle included in vehicle group 1) to cause these DERs to function as a VPP (Virtual Power Plant). Note that server 500 may belong to the aggregator or the automobile manufacturer.

Server 200 may perform DR (Demand Response) for each DER to integrate and control multiple DERs as a VPP. DR requests the DER to adjust the power of the power grid PG. Server 200 is configured to be able to bid in an electricity market (e.g., a supply and demand balancing market). The supply and demand balancing market is a market where the TSO (Transmission and Distribution Operator) of the power grid PG procures adjustment capacity. Server 200 may use DR to have multiple DERs (e.g., each vehicle included in vehicle fleet 1) adjust the power of the power grid PG as requested by server 700 or server 900, or adjust the power of the power grid PG for which a bid has been made in the electricity market.

DER participation in DR (power regulation) can add flexibility and academia to the power grid PG. The administrator of a DER participating in DR authorizes remote control by server 200. When server 200 is authorized to remotely control a DER, server 200 can remotely control the DER so that the DER performs power regulation of the power grid PG (e.g., charging promotion, charging suppression, discharging, power consumption promotion, or power consumption suppression). When an imbalance is predicted to occur in the power grid PG's simultaneous balancing, server 200 may control the DER to eliminate the imbalance. For example, when server 200 remotely controls vehicle 100, ECU 150 controls charger/discharger 61 in accordance with commands from server 200. However, even if server 200 sends a command to the DER, if the DER is not ready for power regulation, the DER cannot perform power regulation through remote control. For this reason, DER administrators participating in DR are required to complete DER preparations before the DR begins.

The type of power regulation is arbitrary. For example, power regulation may be supply and demand regulation, power supply stabilization, load following, or frequency regulation. The DER may operate as a regulation capacity or reserve capacity for the power grid PG through remote control.

Before initiating the above-mentioned DR, server 200 transmits a DR request signal to the user terminal set for each vehicle included in vehicle group 1. The DR request signal is a signal requesting participation in DR (power regulation). The DR request signal includes the requested energy management content (e.g., down DR or up DR) and the DR period (DR start time and DR end time). Up DR is basically a DR that requests an increase in demand. However, if the DER receiving the request is a power generation facility, up DR may also request supply reduction from the DER. On the other hand, down DR is a DR that requests demand reduction or reverse power flow.

Server 500 manages user information related to the users of each vehicle included in vehicle group 1. Server 500 manages user information for each user, distinguishing it by user ID (user identification information). User information includes information related to the vehicle used by the user (hereinafter also referred to as "vehicle information"). Vehicle information includes information indicating the location and status transitions of the vehicle used by the user, as well as information set on the vehicle by the user. Specifically, vehicle information includes, for example, the amount of electricity stored in the power storage device (e.g., the SOC of battery 11), the grid connection status (plugged-in status/plugged-out status), the status of the vehicle system (on/off), information set in the navigation system (e.g., the driving route to the destination), and data related to vehicle usage (e.g., data linking the vehicle's location and time regarding daily vehicle use). From this information, it is possible to determine how the user operated the vehicle or how the user intends to operate the vehicle. In other words, vehicle information indicates the characteristics of the user (more specifically, the way the user uses the vehicle). The server 500 periodically communicates with each vehicle in the vehicle group 1 and sequentially receives vehicle information from each vehicle.

In addition to the vehicle information, the user information further includes the aforementioned user location information (information indicating the location of the vehicle user) and data on the vehicle user's activities (e.g., data linking the user's location with the time of day regarding the user's daily activities). The user information may also include pre-registered charging locations, specifications of the power supply equipment installed at those charging locations (e.g., information indicating the power supply capacity), and specifications of the vehicle used by the user (e.g., charging and discharging specifications).

The above user information is stored in the storage device of the server 500 and is updated sequentially. The charging location (location where the EVSE 300 is installed) of the vehicle 100 shown in FIG. 2 may be the vehicle user's home. In this embodiment, while the vehicle 100 is traveling, the location of the vehicle 100 and the SOC of the battery 11 are each sequentially transmitted from the vehicle 100 to the server 500 in real time. Furthermore, when the vehicle 100 switches between a plugged-in state and a plugged-out state, the latest grid connection status is transmitted from the vehicle 100 to the server 500. Furthermore, when the vehicle system is switched on/off in the vehicle 100, the latest vehicle system status is transmitted from the vehicle 100 to the server 500. Furthermore, when a destination is set in the NAVI 82, the driving route searched by the NAVI 82 is transmitted from the vehicle 100 to the server 500.

Server 200 can obtain the above-mentioned user information from server 500. Server 500 transmits the user information to server 200, for example, in response to a request from server 200. Server 500 may also periodically transmit the user information to server 200. The user information includes information about each vehicle included in vehicle group 1. In this embodiment, since there is a one-to-one correspondence between users and vehicles, the user ID also functions as a vehicle ID (vehicle identification information).

For example, at the start of power adjustment (DR start time), server 200 determines whether preparations for power adjustment are complete for each vehicle based on the vehicle information for each vehicle received from server 500. Server 200 then selects a vehicle for power adjustment from among the vehicles that are ready, and transmits a command for remote control (hereinafter also referred to as a "VPP command") to the selected vehicle. The required number of vehicles are selected for power adjustment. The VPP command is, for example, a command for remote charging control or remote discharging control. Server 200 remotely controls charging or discharging of the batteries of the selected vehicles, thereby adjusting the power of the power grid PG.

In the energy management system according to this embodiment, incentives are given to DER managers in exchange for energy management using DERs. For example, the users (vehicle managers) of each vehicle included in vehicle group 1 can enter into a contract with the aggregator in advance and receive a specified incentive if they meet certain requirements. Server 200 may manage the incentives given to users of each vehicle included in vehicle group 1 by distinguishing them by user ID.

Figure 3 shows a charging mode setting screen displayed on the touch panel display of mobile terminal 400. Referring to Figure 3, when the mobile app is launched on mobile terminal 400, the mobile app requests user authentication (login). The user can log in by entering specific authentication information into mobile terminal 400. Mobile terminal 400 can obtain user information about the user who has logged in to the mobile app from server 200 or 500. After logging in, mobile terminal 400 displays charging mode setting screen Sc1. Charging mode setting screen Sc1 displays information to the user and accepts input from the user.

The charge mode setting screen Sc1 includes operation units OP11 to OP14 and information units IN11 to IN13. Information unit IN11 indicates the current SOC of battery 11. Information unit IN12 indicates the charge status of battery 11 (e.g., waiting to charge, charging, or charge complete). Information unit IN13 indicates information related to the next charge (e.g., the charge end time and the SOC at the end of charge). In this embodiment, the charge end time for the next charge corresponds to the scheduled start time of use of vehicle 100 (scheduled departure time). The charge end SOC for the next charge corresponds to the target SOC for battery 11 in the next charge control.

The user can set the vehicle 100's planned usage on the mobile device 400 by operating the operation unit OP11 (setting button). Specifically, when the user touches the operation unit OP11 on the charge mode setting screen Sc1 (touch panel screen), the usage schedule setting screen Sc3 is displayed. The usage schedule setting screen Sc3 includes operation units OP21 and OP22 (drum roll) and an operation unit OP23 (confirm button). The user can input the planned departure time of the vehicle 100 using the operation unit OP21 (drum roll). The input planned departure time is set as the charging end time for the next charge. The user can also input the target SOC (charging end SOC) for the planned departure time using the operation unit OP22 (drum roll). When the operation unit OP23 (confirm button) is operated after this information has been input, the next charge is scheduled on the mobile device 400 using the input details, and information about the scheduled next charge is displayed on the information unit IN13.

The user can cancel the planned use of the vehicle 100 (and thus the next reserved charge) set in the mobile terminal 400 by operating the operation unit OP12 (cancel button). If the next charge has not been reserved, the mobile terminal 400 may display a message informing the user that the next charge has not been reserved on the information unit IN13.

In the vehicle 100 shown in FIG. 2, one of multiple charging modes is set in the ECU 150 in accordance with input from the user. Specifically, the mobile terminal 400 accepts input of the charging mode from the user on the charging mode setting screen Sc1 and sets the input charging mode in the vehicle 100 (ECU 150). The user can select any of the three charging modes and set it in the vehicle 100 using operation units OP13 and OP14 (toggle switches) on the charging mode setting screen Sc1.

For example, when both operation units OP13 and OP14 are in the OFF state, this means that the user has selected the first charging mode (hereinafter also referred to as the "normal charging mode"). When operation unit OP13 is in the ON state and operation unit OP14 is in the OFF state, this means that the user has selected the second charging mode (hereinafter also referred to as the "smart charging mode"). When operation unit OP13 is in the OFF state and operation unit OP14 is in the ON state, this means that the user has selected the third charging mode (hereinafter also referred to as the "automatic charging mode"). Note that operation units OP13 and OP14 are linked to each other. When operation unit OP13 is turned ON, operation unit OP14 is turned OFF, and when operation unit OP14 is turned ON, operation unit OP13 is turned OFF. However, if the next charge has not been scheduled for the portable terminal 400, the operation to transition to the smart charge mode (for example, turning on the operation unit OP13) is prohibited. The portable terminal 400 may hide the operation unit OP13 to prohibit transition to the smart charge mode.

In this embodiment, when the charging mode of vehicle 100 is the automatic charging mode, server 200 predicts vehicle 100 usage using a trained model (e.g., a neural network optimized by a learning process). Server 200 generates the trained model, for example, by machine learning using AI (artificial intelligence). Server 200 performs the machine learning using the user information described above. Server 200 performs the learning process, for example, based on user information received from server 500. Server 200 may perform the learning process each time it receives new user information from server 500. Server 200 improves learning accuracy by performing the learning process based on the latest user information. For example, when predetermined conditions (such as time conditions described below) are input into the trained model, server 200 performs the machine learning so that the trained model outputs a usage schedule for vehicle 100 corresponding to the conditions (e.g., the scheduled departure time and the amount of power used by vehicle 100 after departure).

The server 200 learns the user's vehicle usage schedule (e.g., future vehicle location and battery level trends) from, for example, historical data on the user's vehicle use (e.g., past location data and battery level data managed separately by weather conditions, traffic congestion, and day of the week). The input of the trained model (the above-mentioned specified conditions) may include at least one of time conditions (season, day of the week, date and time, etc.), environmental conditions (weather conditions, traffic congestion, etc.), vehicle conditions (e.g., conditions under which the vehicle will be in a specified state), a driving plan set by the user, and a user's behavior schedule. The output of the trained model (the vehicle usage schedule corresponding to the above-mentioned specified conditions) may include at least one of the parking location, scheduled parking start time, scheduled charging start time, scheduled departure time, and the amount of power used by the vehicle after departure (or the amount of power to be charged to the power storage device).

Server 200 may use vehicle location information and power storage information (e.g., SOC information) to learn the vehicle's arrival time at its destination and the power storage amount at the time of arrival. Server 200 may also learn the timing at which the vehicle system is switched on/off. Server 200 may also learn the vehicle's location when the vehicle system is switched from on to off. Server 200 may also learn the vehicle's location when the vehicle is parked. Server 200 may also learn the time from when the vehicle system is switched from off to on until the vehicle departs.

Server 200 may obtain future environmental conditions (e.g., weather forecast information and traffic congestion forecast information) using publicly known services provided on the Internet (e.g., weather information services and traffic information services). Server 200 may also obtain a driving plan from information set in a navigation system. Examples of a driving plan include the departure point, departure time from the departure point, destination, arrival time at the destination, and driving route to the destination. Server 200 may also learn the relationship between the driving plan and the vehicle usage schedule.

Server 200 may learn the user's activity schedule (e.g., future changes in the user's location) based on conditions defined by time conditions, environmental conditions, etc. Server 200 may also learn the user's activity schedule from historical data related to the user's activity (e.g., past location data managed separately by weather conditions, traffic congestion, and day of the week). Server 200 may then learn the relationship between the user's activity schedule and the vehicle usage schedule.

Figure 4 is a flowchart showing the learning process by the management device 1000 (particularly the server 200) and the charging mode setting process by the mobile terminal 400. "S" in the flowchart denotes a step. The server 200 repeatedly executes a series of processes from S11 to S16. Meanwhile, the series of processes from S21 to S27 are executed by the mobile terminal 400. In each of the server 200 and the mobile terminal 400, the processor executes a program stored in a storage device, thereby executing the processes related to each step in the flowchart. However, this is not limited to this, and each of the server 200 and the mobile terminal 400 may execute various processes using dedicated hardware (electronic circuits) rather than software.

Referring to Figure 4 along with Figures 1 to 3, in S11, server 200 determines whether the learning completion flag is OFF. In this embodiment, the storage device of server 200 pre-stores the learning completion flag. The learning completion flag is a parameter that indicates whether learning for predicting vehicle 100 usage, as described above, has been completed. When the learning completion flag is ON, it means that learning has been completed. When the learning completion flag is OFF, it means that learning has not been completed.

If the learning completion flag is OFF (YES in S11), the server 200 sends a signal (hereinafter also referred to as a "learning signal") to the mobile terminal 400 in S12 indicating that learning for usage prediction of the vehicle 100 is not complete. Next, in S13, the server 200 uses the user information to learn the model for usage prediction of the vehicle 100 described above. For example, the server 200 requests new user information from the server 500, and upon receiving the new user information, executes the learning process. The server 200 may perform machine learning of the model using the new user information as learning data (training data).

Next, in S14, server 200 determines whether learning is complete. Server 200 may determine whether learning is complete based on the current learning accuracy. Learning accuracy can be expressed by a known evaluation index. For example, the smaller the prediction error by the model, the higher the learning accuracy of the model. Server 200 may evaluate learning accuracy using a known method. Server 200 may evaluate learning accuracy using test data (evaluation data) extracted from user information (particularly, historical data related to the user's use of the vehicle). Server 200 may determine that learning is complete when the difference between the current value and the previous value of learning accuracy, represented by a predetermined evaluation index, is equal to or less than a predetermined reference value, and may determine that learning is not complete if this is not the case.

While learning is not complete (NO in S14), S12 to S14 are repeated. Then, when learning is complete (YES in S14), the server 200 turns on the learning completion flag in S15, and then in S16 sends a signal indicating that learning for predicting vehicle 100 usage has been completed (hereinafter also referred to as the "learning completion signal") to the mobile terminal 400. When the processing of S16 is executed, the series of processing steps from S11 to S16 ends, and processing returns to the first step (S11). While the learning completion flag is ON (NO in S11), the determination of S11 is repeated.

The portable terminal 400 initiates a series of processes from S21 to S27 each time it receives a learning signal (S12) or a learning completion signal (S16) from the server 200. In S21, the portable terminal 400 determines whether learning is complete. If the portable terminal 400 receives a learning completion signal, a YES determination is made in S21, and the process proceeds to S22 and S24. If the portable terminal 400 receives a learning signal, a NO determination is made in S21, and the process proceeds to S23 and S24. The portable terminal 400 may display a pop-up overview of the automatic charging mode when learning is complete.

In S22, the portable terminal 400 displays the charging mode setting screen Sc1 (hereinafter also referred to as the "first screen") shown in FIG. 3. On the other hand, in S23, the portable terminal 400 displays the charging mode setting screen Sc2 (hereinafter also referred to as the "second screen"). The display content of the second screen is the same as the display content of the first screen, except that information M1 (including operation unit OP14) regarding the automatic charging mode is not displayed.

In S24, the mobile terminal 400 accepts input from the user while displaying the first screen or second screen as a result of the processing of S22 or S23 above. The first screen displaying the operation unit OP14 accepts an operation to transition to the automatic charging mode. Therefore, if learning is complete (YES in S21), transition to the automatic charging mode is permitted. On the other hand, the second screen not displaying the operation unit OP14 does not accept an operation to transition to the automatic charging mode. Therefore, if learning is not complete (NO in S21), transition to the automatic charging mode is prohibited.

In S25, the portable terminal 400 determines whether or not it has received input from the user. If there is no input from the user to the portable terminal 400 (NO in S25), the processing related to changing the charging mode (S26, S27) is not performed, and the series of processing steps from S21 to S27 ends. On the other hand, if there is input from the user (YES in S25), the portable terminal 400 acquires the charging mode corresponding to the input from the user in S26. Specifically, the portable terminal 400 displaying the first screen acquires "normal charging mode" if both operation units OP13 and OP14 are OFF, "smart charging mode" if operation unit OP13 is ON, and "automatic charging mode" if operation unit OP14 is ON. Furthermore, the portable terminal 400 displaying the second screen acquires "normal charging mode" if operation unit OP13 is OFF, and "smart charging mode" if operation unit OP13 is ON. Then, in S27, the mobile terminal 400 sets the charging mode acquired in S26 in the vehicle 100 (ECU 150). Once the processing of S27 is executed, the series of processing steps from S21 to S27 ends.

Figure 5 is a diagram illustrating three types of charging modes (normal charging mode, smart charging mode, and automatic charging mode) that can be set for the vehicle 100. Below, an example is described in which user requirements for charging are defined by a charging end time and a target SOC. User requirements are requirements that correspond to the user's characteristics and can be set by the user themselves.

Referring to FIG. 5, the mobile terminal 400 sets the charging mode selected by the user to the vehicle 100 (ECU 150) as described above (see S27 in FIG. 4). Specifically, the mobile terminal 400 transmits the charging mode to the vehicle 100. If the selected charging mode is not the automatic charging mode, the mobile terminal 400 also transmits user requirements related to charging (e.g., the charging end time and target SOC set via operation units OP21 and OP22 shown in FIG. 2) to the vehicle 100. In addition, at least one of the mobile terminal 400 and the vehicle 100 transmits the charging mode and user requirements to at least one of the servers 200 and 500. The charging mode and user requirements received by the vehicle 100 are set in the ECU 150. The ECU 150 controls charging of the battery 11 according to the set charging mode.

When the vehicle 100 is in the normal charging mode, the vehicle 100 does not allow remote control by the server 200. The ECU 150 charges the battery 11 using local control. In the vehicle 100 set to the normal charging mode, different charging control is performed depending on whether the next charge (timer charging) is scheduled in the ECU 150. For example, when the charging end time and target SOC are set using the operation units OP21 and OP22 shown in FIG. 2, the next charge (timer charging) is scheduled in the ECU 150. An ECU 150 set to the normal charging mode and for which the next charge is not scheduled (an ECU without timer setting) performs immediate charging, as shown by line L1. Immediate charging is external charging that begins immediately when the vehicle 100 is plugged in. In this embodiment, immediate charging ends when the battery 11 is fully charged.

An ECU 150 set to the normal charging mode and for which the next charge is scheduled (an ECU with timer setting) executes the scheduled next charge, as indicated by line L2. In FIG. 5 , the charge end time and target SOC of the next charge scheduled by the user in the ECU 150 are indicated by coordinate values S _A (end time A1 and target value A2) in a two-dimensional graph of time and SOC. The coordinate values S _A define a user requirement. The user requirement according to the coordinate values S _A is that the SOC of the battery 11 be equal to or greater than the target value A2 at the end time A1. An ECU with timer setting executes charging in the period immediately before the end time A1. Charging is initiated so that the SOC of the battery 11 reaches the target value A2 at the end time A1. This satisfies the user requirement. By executing charging immediately before the end time A1, the time during which the vehicle 100 is left unattended with the battery 11 at a high SOC is shortened, thereby suppressing deterioration of the battery 11.

When the charging mode of the vehicle 100 is the smart charging mode, the vehicle 100 allows the server 200 to remotely control it. However, the vehicle 100 does not allow the server 200 to change the user requirements (coordinate value S _A ). When the smart charging mode is set, the ECU 150 allows the server 200 to smartly charge the battery 11 during a smart charging period A4 from when the vehicle 100 returns home (when plugged in) to an end time A1. During smart charging of the battery 11 in the smart charging mode, the server 200 can freely charge and discharge the battery 11 as long as the user requirements according to the coordinate value S _A are satisfied. The server 200 determines a charging schedule and a discharging schedule for the smart charging period A4 and transmits them to the vehicle 100 and the mobile terminal 400. The mobile terminal 400 displays the received charging and discharging schedule in response to a request from the user.

When the automatic charging mode is set, the ECU 150 permits the server 200 to set user requirements and charge the battery 11 in accordance with the set user requirements. The server 200 sets the user requirements (charging end time and target SOC) using the trained model described above. The server 200 inputs, for example, predetermined conditions (such as the time conditions described above) into the trained model. The trained model then outputs a usage schedule for the vehicle 100 corresponding to the conditions. The usage schedule output from the trained model corresponds to the trained usage schedule and includes, for example, a scheduled departure time (scheduled start time of the next usage) and the amount of power required for the next trip (the amount of power consumed in the next usage). The server 200 then sets the acquired scheduled departure time as the charging end time for the next charging and sets the target SOC for the next charging so that the amount of power appropriate for the next usage (the amount of power that is neither excessive nor insufficient) is stored in the battery 11. 5, the charge end time and target SOC for the next charge set in ECU 150 by server 200 are shown as coordinate values S _B (end time B1 and target value B2) in a two-dimensional graph of time and SOC. If a user requirement (coordinate value S _A ) has already been set, server 200 changes the user requirement from coordinate value S _A to coordinate value S _B. The user requirement according to coordinate value S _B is that the SOC of battery 11 be equal to or greater than target value B2 at end time B1.

When the mobile terminal 400 sets the automatic charging mode in the vehicle 100 (ECU 150), the server 200 is permitted to remotely control the battery 11. When the automatic charging mode is set, the ECU 150 permits the server 200 to automatically charge the battery 11 during an automatic charging period B4 from the time the vehicle 100 returns home (at the time of plugging in) to an end time B1. Automatic charging is charging according to a learned usage schedule (e.g., a usage schedule acquired by a learned model). During automatic charging, the ECU 150 controls the charger/discharger 61 (charging circuit) so that the amount of stored power in the battery 11 is equal to or greater than the target amount of stored power (the amount of stored power indicated by the target SOC) at the scheduled departure time. This satisfies the user requirements according to the coordinate value S _B. During automatic charging, the server 200 can freely charge and discharge the battery 11 as long as the user requirements according to the coordinate value S _B are satisfied. Server 200 determines a charging schedule and a discharging schedule for the automatic charging period B4 and transmits them to vehicle 100 and mobile terminal 400. Mobile terminal 400 displays the received charging and discharging schedule in response to a request from the user.

When vehicle 100 is selected as a resource for DR, mobile terminal 400 receives a DR request signal from server 200. During smart charging period A4 or automatic charging period B4, server 200 can control charging and discharging of battery 11 for energy management (power adjustment of power grid PG) requested by DR. During smart charging period A4 or automatic charging period B4, server 200 performs energy management (power adjustment of power grid PG) by sending the above-mentioned VPP command to vehicle 100. When vehicle 100 is participating in DR, the charging mode of vehicle 100 is smart charging mode or automatic charging mode, and vehicle 100 charges or discharges battery 11 in accordance with the VPP command from server 200. In this way, server 200 remotely controls vehicle 100, thereby performing energy management requested by DR.

Figure 6 is a flowchart illustrating the processing executed when the learning accuracy for predicting vehicle usage for the vehicle 100 decreases after the learning is completed. The server 200 repeatedly executes the series of steps S31 to S35.

Referring to FIG. 6 along with FIGS. 1 to 3, in S31, server 200 determines whether the learning completion flag is ON. If the learning completion flag is ON (YES in S31), server 200 evaluates the learning accuracy of the trained model used in the automatic charging mode in S32. Server 200 may evaluate the learning accuracy using test data extracted from past user information. Alternatively, server 200 may evaluate the learning accuracy based on the error between the value predicted by the trained model and the actual value.

Next, in S33, server 200 determines whether re-learning is necessary. Server 200 may determine whether re-learning is necessary based on the current learning accuracy. For example, server 200 may determine that re-learning is necessary if the amount of decline in learning accuracy relative to the time learning was completed exceeds a predetermined amount, and may determine that re-learning is not necessary if this is not the case. Server 200 may also determine that re-learning is necessary for a trained model if predictions made by the trained model are incorrect a predetermined number of times in a row. Server 200 may also determine that re-learning is necessary for a trained model if the error between the value predicted by the trained model and the actual value exceeds a predetermined deviation amount.

If it is determined that re-learning is necessary (YES in S33), the server 200 turns the learning completion flag OFF in S34, and then sends a learning signal to the mobile terminal 400 in S35. When the processing of S35 is executed, the series of processing steps S31 to S35 ends, and processing returns to the first step (S31). As long as the learning completion flag is OFF (NO in S31), the determination of S31 is repeated.

While it is determined that re-learning is not necessary (NO in S33), S31 to S33 are repeated. Then, if the learning accuracy falls below a predetermined level after learning for predicting vehicle 100 usage is completed, a YES determination is made in S33. As a result, the learning completion flag is turned OFF in S34, and a learning in progress signal is transmitted in S35. Then, when the learning completion flag is turned OFF, the processing from S12 onwards in Figure 4 (processing related to machine learning) is executed. In other words, re-learning is performed through the processing shown in Figure 4.

The mobile terminal 400 starts a series of processes from S41 to S46 each time it receives the learning signal (S35) from the server 200. In S41, the mobile terminal 400 determines whether the charging mode of the vehicle 100 is the automatic charging mode. If the charging mode of the vehicle 100 is not the automatic charging mode (NO in S41), the series of processes from S41 to S46 ends.

If the charging mode of the vehicle 100 is the automatic charging mode (YES in S41), the mobile terminal 400 notifies the user in S42 to prompt the user to change the charging mode. The mobile terminal 400 displays, for example, the screen Sc4 shown in FIG. 6. The screen Sc4 displays a message prompting the user to turn off the operation unit OP14 (FIG. 3). The processing of S42 can also be performed during automatic charging as shown in FIG. 5. Prompting the user to change the charging mode during automatic charging means prompting the user to stop automatic charging.

After processing S42, in S43, the portable terminal 400 displays the charging mode setting screen Sc1 shown in FIG. 3 and accepts input from the user. Subsequently, in S44, the portable terminal 400 determines whether input from the user has been received. If there is no input from the user to the portable terminal 400 (NO in S44), the process returns to S42. S42 to S44 are repeated while there is no input from the user to the portable terminal 400. The processes of S42 to S44 shown in FIG. 6 take precedence over the series of processes of S21 to S27 shown in FIG. 4. However, if the portable terminal 400 receives a learning completion signal (S16 in FIG. 4) while repeatedly executing the processes of S42 to S44 shown in FIG. 6, the portable terminal 400 forcibly terminates the series of processes of S41 to S46 shown in FIG. 6 and starts the series of processes of S21 to S27 shown in FIG. 4.

On the other hand, if input has been received from the user (YES in S44), the mobile terminal 400 acquires the charging mode corresponding to the user input in S45. Specifically, the mobile terminal 400 acquires the "normal charging mode" if both operation units OP13 and OP14 are OFF, and the "smart charging mode" if operation unit OP13 is ON. Then, in S46, the mobile terminal 400 sets the charging mode acquired in S45 in the vehicle 100 (ECU 150). When the processing of S46 is executed, the series of processing steps from S41 to S46 ends.

As described above, the charging schedule determination method according to this embodiment includes the processes of S11 to S16 and S21 to S27 shown in FIG. 4. In S13, the management device 1000 uses user information to learn about the user's usage schedule for the vehicle 100 (resource). In S12 and S16, the management device 1000 transmits information indicating the accuracy of the learning to the mobile terminal 400 (the user terminal of the vehicle 100). Specifically, in S12, a learning-in-progress signal indicating low learning accuracy is transmitted. In S16, a learning-completed signal indicating high learning accuracy is transmitted. In S21, the mobile terminal 400 determines whether the learning accuracy exceeds a predetermined level. Completion of learning means that the learning accuracy exceeds the predetermined level. If it is determined that the learning accuracy exceeds the predetermined level (YES in S21), the mobile terminal 400 accepts an input requesting automatic charging (i.e., charging the power storage device according to the learned usage schedule) through the processes of S22 and S24. The mobile terminal 400 accepts an input requesting automatic charging (turning on the operation unit OP14) by, for example, displaying the charging mode setting screen Sc1.

In the above method, the management device 1000 uses user information (e.g., information indicating the user's characteristics) to learn about the user's resource usage schedule. The management device 1000 then transmits information indicating the accuracy of the learning to the mobile terminal 400. A management device 1000 that has completed learning is considered to be in a state where it can determine an appropriate charging schedule. When the management device 1000 has completed learning (YES in S21), the mobile terminal 400 accepts input of an automatic charging request. This allows the user to request automatic charging. This makes it easier for the management device 1000 to determine an appropriate charging schedule in response to a user request. Furthermore, when the management device 1000 has not completed learning (NO in S21), the mobile terminal 400 does not accept input of an automatic charging request. This prevents the user from requesting automatic charging when the management device 1000 has not completed learning.

Figure 7 is a flowchart showing a variation of the process shown in Figure 6. When the mobile terminal 400 receives a learning signal (S35) from the server 200, it may start the series of processes S51 to S54 shown in Figure 7 instead of the series of processes S41 to S46 (Figure 6).

Referring to FIG. 7 along with FIGS. 1 to 3, in S51, the mobile terminal 400 determines whether the charging mode of the vehicle 100 is the automatic charging mode. If the charging mode of the vehicle 100 is not the automatic charging mode (NO in S51), the series of processes from S51 to S54 ends. On the other hand, if the charging mode of the vehicle 100 is the automatic charging mode (YES in S51), the mobile terminal 400 notifies the user in S52 that the charging mode will be changed. The mobile terminal 400 displays, for example, screen Sc5 shown in FIG. 7. Screen Sc5 displays a message notifying the user that the automatic charging mode will be terminated. The process of S52 can also be performed during the automatic charging shown in FIG. 5. Changing the charging mode during automatic charging means that the automatic charging will be stopped.

After processing S52, the mobile terminal 400 displays the charge mode setting screen Sc2 (see Figure 4) in S53. Next, in S54, the mobile terminal 400 sets a predetermined charge mode (e.g., smart charge mode) in the vehicle 100 (ECU 150). When processing S54 is executed, the series of processes from S51 to S54 ends.

According to the method of the above-described modified example (the process shown in FIG. 7), if the accuracy of the learning falls below a predetermined level after the learning for predicting vehicle usage of the vehicle 100 is completed (YES in S33), the automatic charging mode ends. The automatic charging mode ends automatically without the user having to change the charging mode, reducing the user's effort. Note that the charging mode set in S54 is not limited to the smart charging mode, and may also be the normal charging mode.

Note that the learning method is not limited to machine learning using AI. For example, the server 200 may derive a formula for predicting vehicle usage using the least squares method based on user information.

The user terminal is not limited to a mobile terminal, but may also be an in-vehicle terminal. For example, at least some of the functions of the mobile terminal 400 (particularly display-related functions) may be implemented in a terminal (e.g., HMI 81 or NAVI 82) installed in the vehicle 100 (resource). In this configuration, the HMI 81 or NAVI 82 functions as the user terminal. Alternatively, the mobile terminal 400 and the HMI 81 or NAVI 82 may function as a user terminal by cooperating with each other.

The power system PG (external power source) is not limited to a large-scale AC grid, but may also be a microgrid or a DC (direct current) grid. The configuration of the energy management system is not limited to that shown in FIG. 1. Server 200 may communicate with servers 700 and 900 via another server. Another server (e.g., a server of an upper aggregator) may be provided between servers 700 and 900 and server 200. Server 200 may also communicate wirelessly directly with vehicle fleet 1. The functions of server 500 may be implemented in server 200, and server 500 may be omitted. In the above embodiment, an on-premises server (servers 200 and 500 shown in FIG. 1) functions as a management computer. However, this is not limited to this, and the functions of servers 200 and 500 (particularly, functions related to resource management) may be implemented on the cloud using cloud computing. Management device 1000 may belong to another electricity utility (e.g., a retail electricity supplier or TSO) rather than to an aggregator.

The vehicle configuration is not limited to the configuration described above (see Figure 2). The vehicle may be equipped with a charger (charging circuit) instead of a charger/discharger. The power exchanged between the vehicle and the EVSE is not limited to AC power, but may be DC power. A power conversion circuit (e.g., an inverter) for charging or discharging the on-board battery may be installed in the EVSE rather than the vehicle. xEVs other than BEVs (such as PHEVs, FCEVs, and range extender EVs) may also be used as vehicles (resources).

The vehicle may be configured to be capable of wireless charging. A vehicle using wireless charging may be considered to be in a state equivalent to the "plugged-in state" described above when the alignment of the power transmission unit (e.g., a power transmission coil) on the power supply equipment side and the power receiving unit (e.g., a power receiving coil) on the vehicle side is complete. The vehicle may be equipped with solar panels. The vehicle may be configured to be capable of autonomous driving or may have flight capabilities. The vehicle is not limited to a four-wheeled passenger car, but may also be a bus or truck. The vehicle may be a MaaS (Mobility as a Service) vehicle. A MaaS vehicle is a vehicle managed by a MaaS operator. The vehicle may be an unmanned vehicle (e.g., a robotaxi, an automated guided vehicle (AGV), or agricultural machinery). The vehicle may also be an unmanned or single-seater small BEV (e.g., a three-wheeled BEV, a last-mile BEV, or an electric skater).

A resource equipped with a power storage device may be a moving object other than an automobile (such as a railroad vehicle, ship, airplane, drone, walking robot, robot cleaner, space probe, etc.). The resource may also be a stationary power storage system used in a building (such as a home or factory).

The above-described various modifications may be implemented in any combination.
The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the description of the above embodiments, and is intended to include all modifications within the meaning and scope of the claims.

1 Vehicle group, 2 EVSE group, 11 Battery, 20 MG, 60 Inlet, 61 Charger/Discharger, 81 HMI, 82 NAVI, 90 Communication device, 100 Vehicle, 150 ECU, 200, 500, 700, 900 Server, 300 EVSE, 400 Mobile terminal, 800 Power generation equipment, 1000 Management device, PG Power system.

Claims (4)

a management device that manages user information related to users of a resource that includes a power storage device;
a user terminal that accepts input from the user;
the management device is configured to use the user information to learn about a usage schedule of the resource by the user;
the management device transmits information indicating accuracy of the learning to the user terminal;
the user terminal is configured to accept an input requesting charging of the power storage device in accordance with the learned usage schedule when the accuracy of the learning exceeds a predetermined level, and not to accept the input when the accuracy of the learning does not exceed the predetermined level ;
the resource is a vehicle including a charging circuit that charges the power storage device using electric power from outside the vehicle, and a charging control device that controls the charging circuit;
the user information includes information indicating how the user uses the vehicle;
the management device sequentially receives the user information from at least one of the vehicle and the user terminal, and performs the learning using the received user information;
the learned usage schedule indicates a scheduled departure time of the vehicle and a target amount of power stored in the power storage device;
When the user terminal receives the input from the user requesting that the storage device be charged in accordance with the learned usage schedule if the accuracy of the learning exceeds the predetermined level, the user terminal requests the charging control device to control the charging circuit so that the storage amount of the storage device is equal to or greater than the target storage amount at the scheduled departure time . The charging system of claim 1, wherein the user terminal is configured to display an operation unit that accepts the input requesting charging of the power storage device in accordance with the learned usage schedule when the accuracy of the learning exceeds the predetermined level, and not display the operation unit when the accuracy of the learning does not exceed the predetermined level. 3. The charging system of claim 1, wherein the user terminal determines whether the accuracy of the learning exceeds the predetermined level while the storage device is being charged in accordance with the learned usage schedule, and when it is determined that the accuracy of the learning has fallen below the predetermined level , the user terminal issues a notification urging the user to stop charging the storage device in accordance with the learned usage schedule. a management device that manages user information related to users of a resource having a power storage device, using the user information to learn about a usage schedule of the resource by the user;
The management device transmits information indicating the accuracy of the learning to the user terminal of the resource;
A charging schedule determination method, comprising:
the resource is a vehicle including a charging circuit that charges the power storage device using electric power from outside the vehicle, and a charging control device that controls the charging circuit;
the user information includes information indicating how the user uses the vehicle;
the management device sequentially receives the user information from at least one of the vehicle and the user terminal, and performs the learning using the received user information;
the learned usage schedule indicates a scheduled departure time of the vehicle and a target amount of power stored in the power storage device;
The charging schedule determination method includes:
The user terminal determines whether or not the accuracy of the learning exceeds a predetermined level;
receiving, by the user terminal, an input requesting charging of the power storage device in accordance with the learned usage schedule when it is determined that the accuracy of the learning exceeds the predetermined level;
The user terminal that has received the input requests the charging control device to control the charging circuit so that the storage amount of the power storage device is equal to or greater than the target storage amount at the scheduled departure time;
The charging schedule determination method further includes: