Energy management methods and systems

Abstract

To realize both the effectiveness of energy management and a user's convenience.SOLUTION: An energy management method includes: scheduling the charging of an electric vehicle for energy management to be performed at a predetermined charging spot on a predetermined execution date; calculating a recommended value of a charging amount at a location for the electric vehicle when a pre-charging action of the electric vehicle is detected on the execution date at the location other than the charging spot (S13); requesting permission from a user of the electric vehicle to set an upper limit value of the charging amount at the location other than the charging spot to the recommended value of the charging amount (S15); and setting the upper limit value of the charging amount at the location other than the charging spot to the recommended value of the charging amount when the permission is received from the user of the electric vehicle (S17).SELECTED DRAWING: Figure 5

Description

Technical Field

[0001] The present disclosure relates to an energy management method and a computer system.

Background Art

[0002] Japanese Patent Application Laid-Open No. 2016-171634 (Patent Document 1) discloses a method for performing energy management using an electric vehicle equipped with a power storage device.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the energy management method described in Patent Document 1, the behavior of the user is predicted, and based on the prediction result, the charging schedule (power supply schedule to the electric vehicle) of the power storage device mounted on the electric vehicle is managed. However, the user does not always act as predicted. In addition, when the electric vehicle is controlled so that the user can only act as predicted, the convenience of the user may be excessively impaired.

[0005] The present disclosure has been made to solve the above problems, and an object thereof is to achieve both the feasibility of energy management and the convenience of the user.

Means for Solving the Problems

[0006] In one form of this disclosure, an energy management method is provided which includes: scheduling the charging of an electric vehicle for energy management to be performed at a designated charging station on a designated execution day; calculating a recommended amount of charge for the electric vehicle at a location other than the charging station if pre-charging operations for the electric vehicle are detected at a location other than the charging station on the execution day; requesting permission from the electric vehicle user to set the upper limit of the amount of charge at locations other than the charging station to the recommended amount of charge; and, if permission is obtained from the electric vehicle user, setting the upper limit of the amount of charge at locations other than the charging station to the recommended amount of charge.

[0007] The above method makes it possible to achieve both the feasibility of energy management and user convenience.

[0008] In other forms of this disclosure, a computer system is provided comprising one or more processors and one or more storage devices that store a program causing one or more processors to perform the aforementioned energy management method.

[0009] According to the computer system described above, the energy management method described above can be suitably executed. The computer system may include multiple processors installed in separate computers and multiple storage devices installed in separate computers. [Effects of the Invention]

[0010] This disclosure makes it possible to achieve both the feasibility of energy management and user convenience. [Brief explanation of the drawing]

[0011] [Figure 1] This figure shows a schematic configuration of the energy management system according to the embodiment of the disclosure. [Figure 2] This figure shows the charging status of the electric vehicle shown in Figure 1. [Figure 3]Figure 1 illustrates the prediction of vehicle behavior by the server and the power trading based on the prediction results. [Figure 4] This diagram illustrates the overview of the tertiary adjustment capacity-2. [Figure 5] This is a flowchart showing an energy management method according to an embodiment of the present disclosure. [Figure 6] This figure shows a modified example of the energy management method shown in Figure 5. [Modes for carrying out the invention]

[0012] Embodiments of this disclosure will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals, and their descriptions will not be repeated.

[0013] Figure 1 is a diagram showing a schematic 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 performs energy management of a power grid PG. This energy management system includes a vehicle group 1, an EVSE group 2, and servers 300,700. EVSE stands for Electric Vehicle Supply Equipment.

[0014] A power grid (PG) is a power network constructed by transmission and distribution equipment. Multiple power plants are connected to a power grid (PG). Vehicle group 1 includes multiple electric vehicles (xEVs) capable of operating as a balancing force for the power grid (PG). EVSE group 2 includes multiple EVSEs that receive power from the power grid (PG).

[0015] Server 300 comprises a processor 310 and a storage device 320. Server 300 may be a computer belonging to an aggregator. Server 700 belongs to, for example, a TSO (System System Operator) of a power grid PG. Server 300 and Server 700 are configured to communicate with each other via a communication network NW. The communication network NW is, for example, a wide-area network constructed by the Internet and wireless base stations.

[0016] Each vehicle in vehicle group 1 and each EVSE in EVSE group 2 are configured to communicate with server 300 via a communication network NW. Each of these vehicles and EVSEs is registered with server 300. The storage device 320 stores information about each registered vehicle (e.g., specifications, charging stations, user information, incentive information, etc.), distinguishing it by vehicle identification information (vehicle ID). The storage device 320 also stores information about each registered EVSE (e.g., specifications, location information, etc.), distinguishing it by EVSE identification information (EVSE-ID). The configurations of each vehicle in vehicle group 1 (hereinafter referred to as "vehicle 100" unless otherwise specified) and each EVSE in EVSE group 2 (hereinafter referred to as "EVSE 200" unless otherwise specified) will be explained below using Figure 2. Figure 2 shows the state of vehicle 100 during charging.

[0017] Referring to Figure 2, the vehicle 100 includes a battery 110, an inlet 120, a charging circuit 130, an electronic control unit (hereinafter referred to as "ECU (Electronic Control Unit)") 150, a Human Machine Interface (HMI) 180, and a communication device 190. The vehicle 100 may further include an air conditioning system, which is not shown. The ECU 150 includes a processor 151 and a memory device 152. The vehicle 100 is an electric vehicle (xEV) configured to run using the power stored in the battery 110. The vehicle 100 is, for example, a battery electric vehicle (BEV) without an internal combustion engine. As the battery 110, known vehicle energy storage devices (liquid-type secondary batteries, all-solid-state secondary batteries, battery packs, etc.) can be used.

[0018] The inlet 120 includes a charging port and a charging lid. The charging lid is configured to be opened and closed by the user. In the closed state, it covers the charging port, and in the open state, it exposes the charging port. When charging the battery 110, with the charging lid open, the connector 240 of the charging cable 230 is connected to the charging port. The charging circuit 130 is a circuit that charges the battery 110 using the power supplied from outside the vehicle to the charging port. The charging circuit 130 is controlled by the ECU 150. However, the charging circuit 130 may also charge the battery 110 according to a command from outside the vehicle. Hereinafter, the charging of the battery 110 mounted on the vehicle 100 may be referred to as the charging of the vehicle 100.

[0019] The HMI 180 includes a navigation system. Hereinafter, the information set in the navigation system is referred to as "navigation information". Examples of navigation information include a driving route and a destination. The HMI 180 may include at least one of a touch panel display and a smart speaker that accepts voice input.

[0020] The detection values of various sensors (not shown) mounted on the vehicle 100 are input to the ECU 150. The vehicle 100 is equipped with a position sensor, a vehicle speed sensor, an accelerator sensor, an outside air temperature sensor, a battery sensor, a charging lid open / close sensor, a charging cable connection sensor, and the like. The position sensor may detect the position of the vehicle 100 using a positioning system such as GPS (Global Positioning System). The battery sensor includes various sensors that detect the state of the battery 110 (for example, voltage, current, temperature, and SOC). SOC (State Of Charge) indicates, for example, the ratio of the current stored power to the stored power in a fully charged state.

[0021] ECU 150 communicates with server 300 through communication device 190. Communication device 190 may include a wireless communication device (e.g., DCM (Data Communication Module)) that can access communication network NW. Vehicle 100 sequentially transmits the detection results by in-vehicle sensors (e.g., position sensor and SOC sensor) to server 300. Also, every time the navigation information is updated, the latest navigation information is transmitted from vehicle 100 to server 300.

[0022] The main body of EVSE 200 incorporates control unit 210 and circuit unit 220. EVSE 200 further includes a charging cable 230 that extends outward from the main body of EVSE 200. Control unit 210 includes a processor 211 and a storage device 212, and controls circuit unit 220. Circuit unit 220 includes a circuit (e.g., a power conversion circuit) for supplying power from power grid PG to vehicle 100. At the tip of charging cable 230, a connector 240 (plug) that can be attached to and detached from the charging port of inlet 120 is provided. When connector 240 of charging cable 230 connected to the main body of EVSE 200 is connected to inlet 120 of parked vehicle 100, vehicle 100 is in an electrically connected state (plug-in state) with EVSE 200. EVSE 200 and power grid PG are electrically connected. For this reason, vehicle 100 in the plug-in state is electrically connected to power grid PG.

[0023] A prediction program is implemented in the server 300 that predicts the future behavior (usage pattern) of vehicle 100 based on past usage data of vehicle 100. The server 300 conducts power trading based on the prediction results. Figure 3 is a diagram illustrating the prediction of vehicle behavior by the server 300 and the power trading based on the prediction results. Hereafter, the EVSE200s located in areas A, B, C, and D shown in Figure 3 will be referred to as EVSE200A, 200B, 200C, and 200D, respectively. Also, vehicle 100 belonging to a user living in house 10A in area A will be referred to as "vehicle 100A". EVSE200A corresponds to the power supply equipment installed in house 10A (the user's home). The location of house 10A (EVSE200A) is registered in the server 300 as a charging station for vehicle 100A. In this embodiment, the charging stations (for example, the user's home and / or workplace) of each vehicle included in vehicle group 1 are registered in the server 300.

[0024] In this embodiment, the user uses vehicle 100A for commuting. Vehicle 100A departs, for example, in the morning on a weekday and returns home in the evening of the same day. On weekdays, it is expected that vehicle 100A, which departs in the morning (for example, around 8:00 AM) for work, will return home in the evening (for example, around 5:00 PM) and be plugged in. However, the user may take irregular actions.

[0025] The server 300 predicts the time when the vehicle 100 will be ready to charge and the amount of charge it will receive the following day at the vehicle 100's charging station. The predicted time when the vehicle 100 will be ready to charge at the charging station. In this embodiment, the time when the vehicle 100, which has departed from the charging station, returns to the charging station after driving and connects to the EVSE 200 and enters a plugged-in state corresponds to the time when the vehicle is ready to charge. The predicted amount of charge is the amount of electricity (kWh) that will be stored in the vehicle 100 by charging using the EVSE 200 after the vehicle is ready to charge at the charging station, and corresponds to the value obtained by subtracting the amount of energy stored at the start of charging from the amount of energy stored at the end of charging.

[0026] The server 300 may acquire information for the above prediction from the vehicle 100. Specifically, the server 300 sequentially acquires various information (e.g., location information, SOC, and navigation information) from the vehicle 100 and records usage data of the vehicle 100 (e.g., data indicating the location and status of the vehicle 100 while it is in motion) in the storage device 320. The usage data may include, for example, the location and SOC of the vehicle 100 at each time.

[0027] The server 300, for example, uses the usage data (usage history) stored in the storage device 320 to predict the time of vehicle 100A's return home the following day and the amount of charge (SOC) of vehicle 100A at that time of return. The server 300 may also predict the amount of charge of vehicle 100A the following day based on the amount of charge of vehicle 100A at the time of return. Based on the usage history of vehicle 100A, the server 300 can predict the driving route and schedule for the following day, as well as the amount of power consumed by driving the following day. The server 300 may also predict the time of return from the predicted driving schedule. The server 300 may also predict the amount of charge (battery level) at the time of return from the predicted amount of power consumed. The server 300 may manage the usage history of vehicle 100A by day of the week and predict the driving route and schedule based on the cumulative probability for each day of the week. In the example shown in Figure 3, the server 300 manages the usage history separately for weekdays (Monday to Friday), Saturday, and Sunday. The server 300 then predicts the weekday route L1, the Saturday route L2, and the Sunday route L3 separately based on the corresponding usage history. However, the prediction method shown in Figure 3 is merely an example and can be modified as appropriate.

[0028] If the server 300 receives navigation information for the following day from vehicle 100A, it will take that information into consideration when predicting the time of return home and the amount of charge for the following day. If the navigation information for vehicle 100A has been updated, it is possible that the user is planning an irregular trip. Therefore, the server 300 may trust the navigation information more than the usage history and predict the time of return home and the amount of charge for vehicle 100A the following day based on the navigation information for the following day.

[0029] Server 300 can predict the time when charging preparation will be complete based on the time of arrival home. Server 300 may also estimate that vehicle 100A will be connected to EVSE 200A and enter the plugged-in state after a predetermined time (e.g., 1 to 10 minutes) has elapsed from the time of arrival home. When vehicle 100A arrives home, HMI 180 may prompt the user to prepare for charging (e.g., put the vehicle into the plugged-in state).

[0030] In this embodiment, when the vehicle 100 is connected to the EVSE 200 at the charging station and enters a plug-in state, the vehicle 100 enters a state that allows charging control from the EVSE 200 at the charging station (specifically, the control unit 210 shown in Figure 2). In this state, the charging circuit 130 (on-board charger) shown in Figure 2 charges the battery 110 according to instructions from the EVSE 200. For example, at home 10A, the EVSE 200A receives prediction results regarding vehicle 100A from the server 300. On days when energy management is not performed, the EVSE 200A charges vehicle 100A based on the predictions made by the server 300 (i.e., the predicted charging readiness time and charge amount for the previous day). For example, if vehicle 100A becomes ready to be charged at home 10A before the predicted charging readiness time, charging of vehicle 100A may start at the predicted charging readiness time. If vehicle 100A becomes ready for charging at home 10A after the predicted charging readiness completion time, charging of vehicle 100A may start immediately (when it becomes ready for charging). When the charge amount (kWh) of vehicle 100A reaches the predicted charge amount, charging of vehicle 100A may end. However, the user of vehicle 100A can also operate the charging control unit of vehicle 100A or EVSE200A to activate EVSE200A and perform battery 110 charging at the user's own discretion, regardless of instructions from EVSE200A. In this case, ECU150 controls the charging circuit 130 according to instructions from the user.

[0031] Server 300 performs the above-mentioned predictions for each vehicle included in vehicle group 1 and automatically conducts transactions (e.g., bidding and settlement) in the electricity market based on these prediction results. Server 300 then settles the electricity transactions and manages the ledger (transaction records). Below, we will describe tertiary adjustment power-2 as an example of adjustment power that is successfully bid on in the electricity market.

[0032] Figure 4 is a diagram illustrating the overview of the tertiary adjustment capacity-2. Referring to Figure 4, the tertiary adjustment capacity-2 is an adjustment capacity for the FIT (Feed-in Tariff) special system and is traded in the supply and demand adjustment market. In the supply and demand adjustment market, electricity is traded as a commodity. Each commodity is bought and sold, for example, by bidding. In the supply and demand adjustment market, trading of the tertiary adjustment capacity-2 takes place for each of the eight blocks, which are divided into 3-hour units per day.

[0033] Server 300 places bids in the supply and demand adjustment market between 12:00 and 14:00 on the day before the target block. Specifically, Server 300 transmits bid information (i.e., information indicating the bidding conditions) including the product (e.g., tertiary adjustment power-2), block (one of the eight blocks), adjustment bases within the target area, and the bid amount (ΔkW) to the market system. There may be one or more adjustment bases. Subsequently, at 15:00 on the bidding day, the results are notified to Server 300. If the bid for the product is successful, the contract is concluded. The ΔkW contract amount corresponds to the successful bid amount. The person who successfully bids for tertiary adjustment power-2 in the supply and demand adjustment market is obligated (contractual obligation) to adjust the power within the range of successful bid amounts set relative to the standard value (kW) (successful bid range).

[0034] In this embodiment, Server 300 bids on the tertiary adjustment power-2. When Server 300 wins the bid for the product it bid on, it registers the reference value in the market system by the submission deadline time t0 (for example, one hour before the start time of the target block for which the bid was won). In the example shown in Figure 4, the reference value on the charging side is registered. Charging stations specified by the bid information are also registered in the market system as adjustment stations. During the target block for which the bid was won (for example, the contract period t1 to t2), Server 300 sequentially receives target values ​​L11, which are arbitrarily requested by Server 700 within the range of the winning bid, from Server 700. During the contract period t1 to t2, Server 300 controls charging at the charging stations so that the actual charging power (actual value L12) at the charging stations follows the target charging power (target value L11) from Server 700. If multiple charging stations are specified by the bid information, Server 300 controls charging at each charging station so that the sum of the charging power at those charging stations approaches the target charging power. The difference between the benchmark value (kW) and the actual value L12 (kW) corresponds to the adjustment capacity (ΔkW) of the power grid PG provided by the charging station. If power adjustment that meets the product requirements is not performed, a penalty fee will be imposed on the successful bidder.

[0035] As described above, bidding for tertiary adjustment capacity-2 takes place the day before the energy management execution date. In this embodiment, the server 300 predicts the time when the vehicle 100 will be ready to charge and the amount of charge at the charging station on the execution date, assuming that the vehicle 100 will not be charged anywhere other than the charging station (e.g., the user's home) on the day before the execution date, and conducts power trading according to the prediction results. The server 300 determines the amount of bid to allocate to a particular charging station based on the predicted amount of charge for that charging station.

[0036] Server 300 is configured to implement a Virtual Power Plant (VPP) by aggregating multiple distributed energy resources (hereinafter referred to as "DERs"). A VPP is a mechanism that makes multiple DERs function as if they were a single power plant by remotely and integrally controlling them. For example, vehicle 100, which is electrically connected to EVSE200, can function as a DER for the VPP. For each vehicle in vehicle group 1, Server 300 plans the charging for energy management to be performed at a predetermined charging station on a predetermined execution day, based on the predicted charging readiness time and charging amount. Specifically, based on the predicted charging readiness time and charging amount for each vehicle, Server 300 selects multiple vehicles from vehicle group 1 that have charging stations within the target area where energy management is requested, and performs energy management using the selected multiple vehicles. In power trading, Server 300 determines the charging stations for multiple vehicles and the bid amounts for those charging stations based on the total value of the predicted charging amounts at each vehicle's charging station. Hereafter, energy management for power grid PG will also be referred to as "VPP".

[0037] When Server 300 wins a bid for energy management during the time period (VPP time period) corresponding to the target block on the VPP execution day, it requests the users of each vehicle corresponding to each charging station specified in the bid to perform charging at the registered charging station during the VPP time period on the VPP execution day. This request is made the day before the VPP execution day. Each vehicle that receives the request sets the VPP execution day and VPP time period in the ECU 150. During the VPP time period on the VPP execution day, Server 300 sends a charging command to the EVSE 200 of each registered charging station based on the charging power requested by Server 700 (see Figure 2). The EVSE 200 of each charging station receives the charging command from Server 300 in real time and performs charging control (remote control) of the vehicle 100 according to the charging command. Server 300 may provide incentives (for example, redeemable points or points that can be used to pay for electricity bills) to the users of the vehicle 100 that performed charging in response to the request.

[0038] In electricity trading, charging at locations other than pre-designated charging stations is not recognized as charging (energy management) in accordance with the agreement. Therefore, if vehicle 100 is charged at a location other than a charging station on the day (VPP execution day), the amount of charge may be insufficient compared to the agreed amount (auctioned amount). In this embodiment, vehicle 100, which has been requested to be charged for energy management, performs a series of processes shown in Figure 5, which will be explained below, thereby achieving both the feasibility of energy management and user convenience.

[0039] Figure 5 is a flowchart of the energy management method according to this embodiment. In the flowchart, "S" means a step. The processes (processing flow) shown in this flowchart are executed by the ECU 150 when, for example, vehicle 100 starts driving or stops driving on a set VPP execution day. The ECU 150 may also detect the start / end of driving of vehicle 100 based on the on / off operation of the vehicle's start switch. Generally, the start switch is called a "power switch" or "ignition switch". Below, we will describe an example in which the vehicle 100A shown in Figure 3 is set to a nighttime period (for example, 6pm to 9pm) as the VPP time period. Each process shown in Figure 5 is executed by the ECU 150 of vehicle 100A.

[0040] Referring to Figure 5, in S11, the ECU 150 performs a first and second determination regarding the status of vehicle 100A. The first determination is whether or not a pre-charging operation has been performed for vehicle 100A. The second determination is whether or not vehicle 100A is scheduled to be charged at a location other than the charging station (home 10A).

[0041] In the first determination at the start of driving, setting the destination of vehicle 100A to a location where charging is possible (first action) corresponds to a pre-charging action. When vehicle 100A starts driving, if the ECU 150 detects the first action, it determines that there is a "pre-charging action"; if it does not detect the first action, it determines that there is no "pre-charging action". For example, when vehicle 100A starts driving, if a supermarket equipped with an EVSE that vehicle 100A can use is set as the destination in the navigation system, a pre-charging action (first action) will be detected.

[0042] In the first determination at the end of driving, the second action is that vehicle 100A has stopped in a location where it can be charged, and the third action is that the charging lid of vehicle 100A has been opened. At the end of driving for vehicle 100A, if the ECU 150 detects either the second or third action, it determines that "a pre-charging action has been performed," and if it does not detect either the second or third action, it determines that "a pre-charging action has not been performed." A location where it can be charged is, for example, a parking lot where an EVSE (power supply equipment) usable by vehicle 100A is installed. If vehicle 100A stops in the parking lot of house 10A where EVSE 200A is installed, a pre-charging action (second action) will be detected. Also, if the user opens the charging lid of vehicle 100A at the end of driving for vehicle 100A, a pre-charging action (third action) will be detected.

[0043] The above-described first to third actions make it easier to accurately detect the pre-charging operation of an electric vehicle. However, the pre-charging operation does not have to be limited to the first to third actions, as it does not need to be an action that puts the vehicle into a state where it can be charged. Either the second or third action may be used as the pre-charging operation at the end of driving.

[0044] When a pre-charging operation is detected, the ECU150 performs a second determination. In the second determination at the start of driving, if the destination of vehicle 100A is a location other than a charging station, it is determined that "charging is planned at a location other than a charging station," and if the destination of vehicle 100A is a charging station, it is determined that "charging is not planned at a location other than a charging station." In the second determination at the end of driving, if the current location of vehicle 100A is a location other than a charging station, it is determined that "charging is planned at a location other than a charging station," and if the current location of vehicle 100A is a charging station, it is determined that "charging is not planned at a location other than a charging station."

[0045] In the subsequent S12, the ECU 150 determines whether or not a pre-charging operation has been detected at a location other than a charging station. If the first determination above determines that there is "no pre-charging operation", then the determination in S12 is NO. Similarly, if the second determination above determines that there is "no planned charging at a location other than a charging station", then the determination in S12 is also NO. If the determination in S12 is NO, the processing flow in Figure 5 ends. For example, at the end of vehicle 100A's run, during the determination period from when the vehicle 100A's start switch is turned off until a predetermined time has elapsed, the ECU 150 determines whether or not there is a pre-charging operation (second operation, third operation) (first determination), and if the determination period has elapsed without detecting a pre-charging operation, the control system of vehicle 100A may enter an inactive state (e.g., stopped or in sleep mode). On the other hand, if the determination in S12 is NO at the start of vehicle 100A's run, the ECU 150 may start control to prepare vehicle 100A for driving after the processing flow in Figure 5 has ended.

[0046] On the other hand, if the first determination determines that "preparatory charging operation is in place" and the second determination determines that "charging is planned at a location other than a charging station," then the determination in S12 is YES, and the process proceeds to S13. In S13, the ECU 150 calculates a recommended value e for the amount of charge to be taken for vehicle 100A at a location other than the charging station where the preparatory charging operation was detected (current location or destination). Hereinafter, the location other than the charging station where the preparatory charging operation was detected will be referred to as the "planned charging location." For example, the ECU 150 calculates a recommended value e for the amount of charge to be taken at the planned charging location so that the amount of charge stored in vehicle 100A (more specifically, battery 110) reaches a predetermined target value (value d) after vehicle 100A returns to the charging station and is charged at the charging station.

[0047] Specifically, the ECU 150 obtains the amount of charge stored in vehicle 100A at the planned charging location (value a) and the amount of energy consumed by vehicle 100A until it arrives at the charging station (value b). The State of Charge (SOC) value, which indicates the amount of charge stored in vehicle 100A's battery 110 at the planned charging location, corresponds to value a. The amount of energy required for vehicle 100A to return from the planned charging location to home 10A (the amount of energy required to reach the charging station) corresponds to value b. The ECU 150 obtains value X (the result of the subtraction) by subtracting value b from value a. The ECU 150 may also calculate the amount of energy required to reach the charging station by considering the distance and elevation difference between the planned charging location and the charging station. The amount of energy required to reach the charging station includes not only the energy consumed during driving, but also the energy consumed by onboard equipment (e.g., air conditioning) during driving. The ECU 150 may also estimate the amount of energy consumed by the air conditioning during driving based on the outside temperature.

[0048] Next, ECU150 obtains value Y (the result of addition) by adding the predicted charge amount for the VPP execution day (value c) to value X (the result of subtraction). Value c corresponds to the charge amount for the VPP execution day predicted the day before the VPP execution day using the method shown in Figure 3. ECU150 obtains the recommended charge amount e (the result of subtraction) by subtracting value Y from value d. Value d can be set arbitrarily and may be an amount of stored energy equivalent to a full charge, an amount of stored energy close to a full charge (for example, about 80% of the SOC value), or an amount of stored energy that will allow driving on the day after the VPP execution day.

[0049] As described above, in this embodiment, the ECU 150 calculates the recommended charge amount e using a formula such as "recommended value e = d + b - (a + c)". This method makes it easier to obtain the recommended charge amount e, which is the amount of charge that allows the electric vehicle to reach a charging station and to perform energy management. However, the method for calculating the recommended value e is not limited to the above.

[0050] In the following S14, the ECU 150 determines whether the recommended charge amount e is greater than 0. If value Y is lower than value d, that is, if the recommended charge amount e is greater than 0 (YES in S14), the recommended charge amount e becomes a positive value. In this case, the ECU 150 determines the value obtained by subtracting value Y from value d (the difference between value Y and value d) as the recommended charge amount e. Then, in the following S15, the ECU 150 requests permission from the user of vehicle 100A to set the upper limit of the charge amount at locations other than charging stations to the recommended charge amount e. Specifically, the ECU 150 controls the HMI 180 (touch panel display) so that it displays screen Sc1. Screen Sc1 includes a display unit M11 that displays a message informing the user that energy management is scheduled for today and an incentive for energy management, and a message requesting permission from the user to limit the charge amount to the recommended value e (kWh). Screen Sc1 further includes an operation unit M12 for allowing a limit on the amount of charge upon request, and an operation unit M13 for rejecting the request.

[0051] In the following step S16, the ECU 150 determines whether or not it has received permission from the user of vehicle 100A. The user can reject the request from the ECU 150 by operating the control unit M13. If the user rejects the request (NO in S16), the processing flow in Figure 5 ends. Alternatively, the user can grant permission to the ECU 150 to limit the amount of charge by operating the control unit M12. If the ECU 150 has received permission from the user of vehicle 100A (YES in S16), in the following step S17, the ECU 150 sets the upper limit of the amount of charge at the planned charging location (a location other than a charging station) to the recommended value e calculated in S13. This limits the amount of charge at the planned charging location to the recommended value e. Once the processing in S17 is executed, the processing flow in Figure 5 ends. Note that the upper limit of the amount of charge set in S17 is only valid for charging at the planned charging location and does not limit the amount of charge at charging stations. Also, the upper limit of the amount of charge set in S17 is removed after the VPP execution date has passed.

[0052] On the other hand, if value Y is greater than or equal to value d, the recommended charge amount e becomes "0" or a negative value, and S14 determines NO. The determination of NO in S14 means that value X is sufficiently large and value a is greater than value b. In this case, in the subsequent S18, ECU150 notifies the user of vehicle 100A that it is advising not to charge at the planned charging location (a location other than a charging station). Specifically, ECU150 controls HMI180 so that HMI180 displays screen Sc2. Screen Sc2 displays a message informing the user that energy management at home (home 10A) is scheduled for today and that the vehicle will not run out of power even if it does not charge at the planned charging location, and a message urging the user not to charge anywhere other than home. Once the process in S18 is executed, the processing flow in Figure 5 is completed.

[0053] A user of vehicle 100A can charge the battery 110 even outside of charging stations by operating the charging control unit of vehicle 100A or EVSE (power supply equipment). In other words, a user of vehicle 100A can charge the battery 110 not only at home but also while away from home. In this case, the ECU 150 controls the charging circuit 130 according to the user's instructions. However, when charging at a planned charging location (a location other than a charging station), if an upper limit of the charge amount (recommended value e) is set in the ECU 150, the ECU 150 controls the charging circuit 130 so that the charge amount does not exceed the upper limit. When the charge amount of battery 110 reaches the upper limit, charging of battery 110 ends.

[0054] As described above, the energy management method according to this embodiment includes the processes shown in Figures 3 to 5. Each process is executed by one or more processors executing programs stored in one or more memories. However, these processes may be executed by dedicated hardware (electronic circuits) instead of software.

[0055] The energy management method according to this embodiment includes: scheduling the charging of an electric vehicle for energy management to be performed at a predetermined charging station on a predetermined execution day (see Figures 3 and 4); calculating a recommended value for the amount of charge at a location other than the charging station if a pre-charging operation of the electric vehicle is detected at a location other than the charging station on the execution day (Figure 5, 13); requesting permission from the electric vehicle user to set the upper limit of the amount of charge at locations other than the charging station to the recommended amount of charge (Figure 5, S15); and setting the upper limit of the amount of charge at locations other than the charging station to the recommended amount of charge if permission has been received from the electric vehicle user (Figure 5, S17). With this method, by limiting the amount of charge at locations other than the charging station, it becomes easier to perform charging for energy management at the charging station. In addition, by requesting permission from the electric vehicle user before limiting the amount of charge, it is prevented from excessively impairing the user's convenience. Furthermore, since the user can perform charging up to the recommended amount of charge, it is prevented from excessively impairing the user's convenience due to the limiting of the amount of charge. This makes it possible to achieve both the feasibility of energy management and the convenience of the user. Furthermore, improved energy management capabilities through electric vehicles will make it easier to increase electricity trading volume and generate revenue. Displaying incentives can increase users' motivation to participate in energy management. Instead of incentives, the environmental benefits of energy management (e.g., reduction in carbon dioxide emissions) may be displayed.

[0056] The above energy management method further includes predicting the time and amount of charge required for electric vehicles to be ready for charging at charging stations the following day (see Figure 3), and charging electric vehicles at charging stations based on the predicted time and amount of charge required the previous day (see Figure 2). With this method, the time and amount of charge required for electric vehicles to be ready for charging are predicted the day before, and charging of electric vehicles is performed based on these predictions. This makes it easier to plan for energy management.

[0057] Notifications to the vehicle user (S15, S18 in Figure 5) may be provided by an external user terminal (e.g., a communication device with a user interface) instead of the in-vehicle HMI (HMI180). Examples of external user terminals include smartphones, portable game consoles, wearable devices (e.g., smartwatch-type communication devices), and electronic keys. Notifications to the vehicle user may be provided by voice rather than by display.

[0058] Server 300 may perform the series of processes shown in Figure 5 on behalf of the vehicle. Figure 6 shows an example in which Server 300 performs the series of processes shown in Figure 5. Server 300 may request Vehicle 100 to notify the vehicle user. Server 300 may receive a response from Vehicle 100 from the vehicle user. If the request for charge limiting is rejected in the first electric vehicle (NO in S16), Server 300 may request the second electric vehicle to perform energy management on behalf of the first electric vehicle.

[0059] The processing flow shown in Figure 5 or Figure 6 can be modified as needed. For example, the order of processing may be changed or unnecessary steps may be omitted depending on the purpose. The content of any of the processing steps may also be changed. The start timing of the processing flow is not limited to the start and end of travel, but can be set arbitrarily. The processing flow may be executed at either the start or end of travel, or only at one of them.

[0060] In the above embodiment, a predictive program that predicts future usage patterns of vehicle 100 based on past usage data of vehicle 100 is implemented on server 300 (on-premise server) (see Figure 3). However, it is not limited to this, and such a predictive program may be implemented in the EMS (Energy Management System) of vehicle 100, EVSE200, or house 10A instead of server 300. Alternatively, the functions of server 300 may be implemented on the cloud.

[0061] The configuration of the electric vehicle used for energy management is not limited to the configuration described above (see Figure 2). Other xEVs besides BEVs may be used, for example, a PHEV (plug-in hybrid vehicle) equipped with an internal combustion engine may be used. The electric vehicle may be configured to enable contactless charging. An electric vehicle that performs contactless charging may be considered to be in a state equivalent to the "plug-in state" described above when the alignment of the power transmission unit (e.g., power transmission coil) on the power supply equipment side and the power receiving unit (e.g., power receiving coil) on the vehicle side is completed. The electric vehicle is not limited to a four-wheeled passenger car, but may be a bus or truck, or a three-wheeled xEV.

[0062] The embodiments disclosed herein should be considered in all respects to be illustrative and not restrictive. The scope of the present invention is indicated by the claims rather than by the description of the embodiments above, and all modifications within the meaning and scope equivalent to the claims are intended to be included. [Explanation of symbols]

[0063] 1 Vehicle group, 2 EVSE groups, 10A House, 100, 100A Vehicle, 110 Battery, 120 Inlet, 130 Charging circuit, 150 ECU, 180 HMI, 200, 200A EVSE, 210 Control unit, 220 Circuit unit, 230 Charging cable, 240 Connector, 300, 700 Server, PG Power system.

Claims

1. The server schedules the charging of electric vehicles for energy management to be performed at a predetermined charging station on a predetermined execution day, The server predicts the time when the electric vehicle will be ready to charge the following day and the amount of charge at the charging station, The control device for the electric vehicle, when it detects a pre-charging operation for the electric vehicle at a location other than the charging station on the execution day, calculates a recommended value for the amount of charge for the electric vehicle at that location. The control device requests permission from the user of the electric vehicle to set the upper limit of the amount of charge at locations other than the charging station to the recommended value, When permission is obtained from the user of the electric vehicle, the control device sets the upper limit of the amount of charge at locations other than the charging station to the recommended value. In charging at locations other than the aforementioned charging stations, the control device controls the electric vehicle's charging circuit so that the amount of charge does not exceed the upper limit set as the recommended value. The power supply equipment connected to the electric vehicle at the charging station performs charging control of the electric vehicle based on the charging preparation completion time and the amount of charge predicted the previous day. Includes, Calculating the aforementioned recommended value is The control device subtracts the amount of power consumed by the electric vehicle until it arrives at the charging station from the amount of power stored in the electric vehicle at a location other than the charging station where the pre-charging operation was detected. The control device adds the amount of charge for the execution day predicted on the day before the execution day to the result of the subtraction, If the result of the addition is lower than a predetermined amount of stored energy, the control device shall set the difference between the result of the addition and the predetermined amount of stored energy as the recommended value. Energy management methods, including those mentioned above.

2. The energy management method according to claim 1, wherein the pre-charging operation includes at least one of the following: the electric vehicle stopping at a location where it can be charged; the charging lid of the electric vehicle opening; and the destination of the electric vehicle being set to a location where it can be charged.

3. The pre-charging operation includes stopping the electric vehicle in a location where it can be charged, opening the charging lid of the electric vehicle, and setting the destination of the electric vehicle to a location where it can be charged. If, at the end of the electric vehicle's journey, during the determination period from the time the electric vehicle's start switch is turned off until a predetermined time has elapsed, neither the electric vehicle stopping in a place where it can be charged nor the electric vehicle's charging lid being opened is detected, and the determination period has elapsed, then the electric vehicle's control system will enter a non-operating state. If the destination of the electric vehicle is not set to a location where charging is possible when the electric vehicle starts moving, the control device shall start control to prepare the electric vehicle for driving. The upper limit set in the aforementioned recommended value will be removed once the aforementioned execution date has passed. The energy management method according to claim 1, further comprising:

4. Requesting the user of the electric vehicle to grant the permission is: The control device controls the touch panel display of the electric vehicle so that the touch panel display of the electric vehicle displays a screen including a display unit and an operation unit. Includes, The display unit displays a message informing the user that energy management is scheduled for today and an incentive for energy management, and a message requesting the user permission to limit the charging amount to the recommended value. The energy management method according to claim 1, wherein the operating unit includes a first operating unit for permitting a limit on the amount of charge upon request and a second operating unit for rejecting the request.

5. A system comprising a server, an electric vehicle equipped with a control device and a charging circuit, and a power supply facility for supplying power to the electric vehicle, The aforementioned server, To schedule the charging of the electric vehicle for energy management to be carried out at a designated charging station on a designated execution day, To predict the time when the electric vehicle will be ready to charge and the amount of charge at the aforementioned charging station the following day, It is configured to perform, The control device is configured to calculate a recommended charge amount for the electric vehicle at a location other than the charging station if a pre-charging operation for the electric vehicle is detected at that location on the execution day. In calculating the recommended value, the control device Subtracting the amount of electricity consumed by the electric vehicle until it arrives at the charging station from the amount of electricity stored in the electric vehicle at a location other than the charging station where the pre-charging operation was detected, The result of the subtraction is to add the amount of charge for the execution date predicted on the day before the execution date, If the result of the addition is lower than a predetermined amount of stored energy, the difference between the result of the addition and the predetermined amount of stored energy shall be the recommended value. It is configured to perform, The control device is Requesting permission from the user of the electric vehicle to set the upper limit of the amount of charge at locations other than the aforementioned charging station to the aforementioned recommended value, When permission is obtained from the user of the electric vehicle, the upper limit of the amount of charge at locations other than the charging station is set to the recommended value, In charging at locations other than the aforementioned charging stations, the charging circuit is controlled so that the amount of charge does not exceed the upper limit set as the recommended value. It is configured to perform further actions, The power supply equipment is configured to control the charging of the electric vehicle at the charging station, based on the charging preparation completion time and the amount of charge predicted the previous day.

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