Energy management device, energy management system, mobile device, and display device

Abstract

This system effectively allows for the estimation of future activity times for mobile objects moving according to planned route information. [Solution] The energy management device acquires planning information for the travel route, information about the mobile body, information about the current location of the mobile body, and usage information regarding the energy usage of the mobile body. Based on the planning information and the mobile body information, it calculates the amount of energy the mobile body possesses when it arrives at any point on the travel route and at the destination point as the first remaining energy amount. Based on the usage information, it calculates the amount of energy the mobile body possesses as the actual remaining energy amount. Based on the planning information, current location information, and actual remaining energy amount, it calculates the amount of energy the mobile body possesses when it arrives at the destination point as the second remaining energy amount, and outputs the actual remaining energy amount, the first remaining energy amount, and the second remaining energy amount.

Description

[Technical Field]

[0001] The present invention relates to an energy management device, an energy management system, a mobile body, and a display device for managing the energy possessed by a mobile body. [Background technology]

[0002] In recent years, battery energy density has improved, and various mobile vehicles equipped with rechargeable batteries have been proposed. Examples of such mobile vehicles include vehicles that travel on land and aircraft that fly in the air. Some of these mobile vehicles are equipped with cameras and radar, and can be remotely controlled without an operator on board by transmitting camera images and radar detection results to a remote location. Others are capable of autonomous movement using cameras and radar. Autonomous mobile vehicles are configured to be remotely controlled by an operator in a remote location in the event of any malfunction.

[0003] These mobile devices are used for purposes such as transporting passengers and goods, inspecting structures, taking photographs, and conducting searches. The devices travel or fly along pre-set routes. When providing services such as transporting goods using these devices, it is assumed that one operator remotely monitors one or more devices. Therefore, there is a need to accurately and easily determine the future activity time of the devices in order to ensure that goods are delivered reliably to their destinations.

[0004] Conventionally, technologies have been proposed to provide operators with information regarding the future activity time of a mobile vehicle, such as the remaining energy and range of travel. Patent Document 1 describes a vehicle display device that displays the remaining drive energy and range of a vehicle, comprising a display capable of simultaneously displaying a plurality of images relating to information related to the vehicle, including at least an image relating to the range, and characterized in that, in response to a change in the remaining drive energy, at least one of the position and shape of the image relating to the range is changed on the display in accordance with a visual change in the display means representing the remaining drive energy. [Prior art documents] [Patent Documents]

[0005] [Patent Document 1] Japanese Patent Publication No. 2020-132036 [Overview of the project] [Problems that the invention aims to solve]

[0006] Incidentally, mobile vehicles equipped with batteries have a limited battery capacity. Similarly, mobile vehicles that run on fuel such as gasoline are limited to the capacity of their fuel tanks. Thus, because the amount of energy that a mobile vehicle can hold is finite, the distance and time it can travel vary depending on the driving method, etc. Displaying only the remaining drive energy and remaining range, as in the technology described in Patent Document 1, makes it difficult to understand whether energy is being consumed according to the travel plan along the travel route. In other words, the technology described in Patent Document 1 cannot be said to easily predict the future activity time of a mobile vehicle.

[0007] The object of the present invention is to provide an energy management device, an energy management system, a mobile body, and a display device that can effectively determine the future activity time of a mobile body that moves according to planned information of its travel path. [Means for solving the problem]

[0008] An energy management device according to one aspect of the present invention comprises a calculation device and an output device. The calculation device acquires planning information of the movement path of a moving body to a destination point, moving body information, the current position information of the moving body, and usage information regarding the energy use of the moving body. Based on the planning information and the moving body information, it calculates the amount of energy held by the moving body when it arrives at any point on the movement path and at the destination point, respectively, as the first remaining energy. Based on the usage information, it calculates the amount of energy held by the moving body as the actual remaining energy. Based on the planning information, the current position information, and the actual remaining energy, it calculates the amount of energy held by the moving body when it arrives at the destination point after it has moved from its current position, as the second remaining energy. The output device outputs the actual remaining energy, the first remaining energy, and the second remaining energy. [Effects of the Invention]

[0009] According to the present invention, it is possible to provide an energy management device, an energy management system, a mobile body, and a display device that can effectively determine the future activity time of a mobile body moving according to planned information of its travel path. [Brief explanation of the drawing]

[0010] [Figure 1] Figure 1 shows the configuration of the energy management system for a mobile body according to the first embodiment. [Figure 2] Figure 2 is a functional block diagram of the server. [Figure 3] Figure 3 is a schematic diagram of a flight path set by a route setting device. [Figure 4A] Figure 4A is a data table of the battery consumption plan, which is the calculation result of the first calculation unit. [Figure 4B]FIG. 4B is a data table of the battery consumption record which is the calculation result of the second calculation unit. [Figure 5] FIG. 5 is a diagram showing an example of an image of the remaining battery indicator displayed on the display device. [Figure 6A] FIG. 6A is a schematic diagram for explaining information used in the surrogate model. [Figure 6B] FIG. 6B is a block diagram for explaining the calculation process of power consumption using the surrogate model. [Figure 7] FIG. 7 is a diagram showing the configuration of the energy management system of the moving body according to Modification 4 of the first embodiment. [Figure 8] FIG. 8 is a diagram showing an example of an image of a plurality of remaining battery indicators displayed on the display device. [Figure 9] FIG. 9 is a diagram showing the configuration of the energy management system of the moving body according to the second embodiment. [Figure 10] FIG. 10 is a diagram showing the configuration of the energy management system of the moving body according to the third embodiment. [Figure 11] FIG. 11 is a diagram showing the configuration of the moving body according to Modification 1.

Embodiments for Carrying Out the Invention

[0011] Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings. All the drawings are illustrative. The following description details a specific embodiment to facilitate understanding of the present invention. However, the embodiments of the present invention are not limited to the details of the following specific embodiments. In each drawing, the same reference numerals are given to the same configurations or configurations having similar functions, and detailed descriptions of overlapping parts are omitted. In addition, well-known structures and devices are schematically shown in order to simplify the drawings for effective understanding.

[0012] <First Embodiment> FIG. 1 is a diagram showing the configuration of an energy management system 2 for a moving body according to the first embodiment of the present invention. The moving body according to the first embodiment of the present invention is a drone 6 that transports cargo 69. As shown in FIG. 1, the energy management system 2 includes a server 1, a remote operation device 7, and a drone 6. The server 1, the remote operation device 7, and the drone 6 can exchange data through communication. The server 1 provides the drone 6 with information necessary for autonomous flight through a network 4 and a radio base station 5. The network 4 is a wide-area network such as a mobile phone communication network (mobile communication network) or the Internet deployed by a mobile phone carrier or the like. The remote operation device 7 has a display device 7a such as a liquid crystal monitor and an operation terminal 7b for an operator to operate. The operation terminal 7b has a lever, a switch, and the like. The remote operation device 7 provides the drone 6 with a remote operation signal corresponding to the remote operation of the drone 6 by an operator (not shown) through the network 4 and the radio base station 5. The energy management system 2 supports the transport of the cargo 69 by the drone 6 from the distribution base 8 to the delivery destination 9 by providing the drone 6 with information necessary for autonomous flight and a remote operation signal.

[0013] Server 1 manages the operation of drone 6. Server 1 consists of a computer equipped with a computing device 1c, a storage device 1d, an input / output interface 1e, and other peripheral circuits. The computing device 1c is a processing unit such as a CPU (Central Processing Unit), MPU (Micro Processing Unit), or DSP (Digital Signal Processor). The storage device 1d is a non-volatile memory such as ROM (Read Only Memory), flash memory, or a hard disk drive, and a volatile memory known as RAM (Random Access Memory). These hardware components work together to run software and realize multiple functions. Server 1 may consist of one computer or multiple computers. Furthermore, the computing device 1c can be an ASIC (application specific integrated circuit), FPGA (Field Programmable Gate Array), etc.

[0014] The non-volatile memory constituting the storage device 1d stores a program capable of performing various calculations. In other words, the non-volatile memory is a storage medium from which the program realizing the functions of this embodiment can be read. The volatile memory constituting the storage device 1d temporarily stores the calculation results from the arithmetic unit 1c and signals input from the input / output interface 1e. The arithmetic unit 1c is a device that expands the program stored in the non-volatile memory into the volatile memory and performs calculations, and performs predetermined calculation processing on data taken in from the input / output interface 1e, the non-volatile memory and the volatile memory according to the program.

[0015] The input / output interface 1e is an input device that converts signals input from the information providing device 3 into data that can be processed by the arithmetic unit 1c. Furthermore, the input / output interface 1e is an output device that generates an output signal corresponding to the calculation result of the arithmetic unit 1c and outputs that signal to the information providing device 3.

[0016] Server 1 acquires various information from information provider 3. Information provider 3 is, for example, a communication device 3a and an input device 3b. Communication device 3a is connected to network 4 and exchanges data with external devices via network 4. Input device 3b is a storage medium such as a memory stick. Input device 3b may also be an operating device such as a keyboard or mouse. The various information includes information about the drone 6, information about the delivery base 8 and delivery destination 9, information about the goods 69 transported by the drone 6, information about the terrain and structures from the delivery base 8 to the delivery destination 9, and weather information for the area and airspace surrounding the delivery base 8 and delivery destination 9.

[0017] Server 1 sets the flight path for drone 6 and provides information about the set flight path to drone 6. Server 1 also provides information about drone 6 to the operator who monitors the drone.

[0018] Drone 6 is an autonomous flying object (mobile object) capable of carrying supplies 69. Based on instructions transmitted from Server 1, Drone 6 takes off from a departure point and flies along a flight path to a destination. Drone 6 comprises, for example, a housing and multiple rotor blades 62 provided on the housing. The rotor blades 62 are driven by electric motors 61. By controlling the rotation speed of each rotor blade 62, Drone 6 ascends, descends, and flies along a flight path.

[0019] The drone 6 is equipped with a control system that controls various parts of the drone 6. The control system includes a communication device that transmits position information of the drone 6 to the server 1 and receives instructions from the server 1, a position sensor that detects the position of the drone 6, a battery 60, a voltage sensor that detects the voltage of the battery 60, a current sensor that detects the current flowing through the battery 60, and a control device 63 that controls the electric motor 61 of the blade rotor 62 based on instructions from the server 1 obtained through the communication device and the detection results of the various sensors. The drone 6 may also be equipped with auxiliary equipment such as lighting equipment and air conditioning equipment for the cargo compartment. In this case, the control system includes an interior temperature sensor that detects the temperature inside the cargo compartment and an exterior temperature sensor that detects the outside air temperature. The control device 63 also controls the auxiliary equipment such as lighting equipment and air conditioning equipment.

[0020] The position sensor includes, for example, multiple GNSS (Global Navigation Satellite System) antennas (hereinafter referred to as GNSS antennas) and a positioning calculation device that calculates the position of the drone 6, which is represented by real coordinates in three-dimensional space, based on satellite signals (GNSS radio waves) from multiple positioning satellites received by the GNSS antennas.

[0021] The control system, like server 1, consists of a computer equipped with a processing unit, memory, input / output interface, and other peripheral circuits. The control system transmits the position information of drone 6, detected by the position sensor, to server 1 via a communication device. The position information of drone 6 is, for example, the coordinates of drone 6 in a geographic coordinate system (latitude, longitude, ellipsoidal height). The control system obtains flight path (movement path) planning information from server 1 via the communication device. Based on the flight path planning information, the control system flies drone 6 along the flight path.

[0022] Figure 2 is a functional block diagram of Server 1. Server 1 functions as an energy management device 1a that manages the energy of the drone 6, and a route setting device 1b that sets the flight path of the drone 6. Based on the information provided by the information providing device 3, the route setting device 1b sets the flight path of the drone 6 and provides the energy management device 1a with the planned flight path information.

[0023] The energy management device 1a calculates the amount of power consumed when flying along the provided flight path based on the flight path planning information, and determines whether the power consumed exceeds the remaining battery capacity. In other words, the energy management device 1a determines whether the drone 6 can fly along the flight path from the starting point, delivery base 8, to the destination, delivery point 9, as shown in Figure 1, and return to delivery base 8. If the power consumed by the drone 6 from delivery base 8 to delivery point 9 and from delivery point 9 back to delivery base 8 exceeds the remaining battery capacity, i.e., if it cannot return to delivery base 8, the route setting device 1b sets an alternative flight path.

[0024] The energy management device 1a according to this embodiment generates information during the flight of the drone 6 to facilitate the understanding of the drone 6's future activity time. The energy management device 1a provides the generated information to the operator monitoring the drone 6 via the information provision device 3. The functions of the energy management device 1a will be described in detail below.

[0025] As shown in Figure 2, the energy management device 1a includes an information acquisition unit 13, a first calculation unit 10, a second calculation unit 11, a storage unit 12, a control unit 15, an output unit 14, and a determination unit 16. The information acquisition unit 13 is mainly implemented by the input / output interface (input device) 1e of the server 1. The first calculation unit 10, the second calculation unit 11, the control unit 15, and the determination unit 16 are mainly implemented by the arithmetic unit 1c of the server 1. The storage unit 12 is mainly implemented by the storage device 1d of the server 1. The output unit 14 is mainly implemented by the input / output interface (output device) 1e of the server 1.

[0026] The information acquisition unit 13 acquires information necessary for the calculations of the first calculation unit 10 and the second calculation unit 11. The information acquired by the information acquisition unit 13 is stored in the storage unit 12. The information acquisition unit 13 acquires planning information for the flight path of the drone 6 from the departure point to the destination point from the path setting device 1b. The flight path planning information includes the position of the departure point, the position of the destination point, the positions of multiple waypoints set on the flight path connecting the departure point to the destination point, and time information associated with each of those positions. In other words, the flight path planning information includes the position and planned departure time of the departure point, the positions and planned passing times of the multiple waypoints, and the position and planned arrival time of the destination point. The position information of each point (departure point, waypoint, destination point) is composed of, for example, position coordinates in a plane parallel to the horizontal plane and the flight altitude at each position coordinate.

[0027] The information acquisition unit 13 acquires drone 6's aircraft information (mobile information) from the information providing device 3. The drone 6's aircraft information includes the power consumption rate [Wh / km] of the electric motor 61 of the drone 6's rotor 62, that is, the amount of power consumed by the drone 6 per unit distance during flight. It also includes the power consumption [W] of the control system (control device 63, communication device, sensors, etc.) and auxiliary equipment (lighting equipment, air conditioning equipment, etc.) mounted on the drone 6, that is, the amount of power consumed per unit time regardless of the drone 6's flight status.

[0028] The information acquisition unit 13 acquires information about the goods 69 to be transported by the drone 6 from the information providing device 3. The information about the goods 69 includes the weight of the goods 69 and information about the shape of the goods 69. Information about the shape of the goods 69 refers, for example, to the projected area of ​​the goods 69 when viewed from the direction of travel.

[0029] The drone 6 provides its own position (self-position) information, acquired by its position sensor, to the server 1 via the information providing device 3. The information acquisition unit 13 acquires the current position information of the drone 6 from the information providing device 3. The drone 6 also provides the server 1 via the information providing device 3 with information on the voltage of the battery 60, detected by its voltage sensor, and the current flowing through the battery 60, detected by its current sensor. The information acquisition unit 13 acquires the voltage and current information of the drone 6's battery 60 from the information providing device 3 as usage information regarding the drone 6's energy usage.

[0030] The first calculation unit 10 calculates the amount of energy the drone 6 has at the time it arrives at any point along the flight path and at the destination point, based on the flight path planning information and the drone 6's aircraft information, and defines this as the first remaining energy. Any point along the flight path is, for example, a predetermined waypoint along the flight path. The amount of energy the drone 6 has has corresponds to the amount of power in the drone 6's battery 60.

[0031] The first calculation unit 10 converts the calculated first energy level, which is the electrical energy [Wh] of the battery 60, into a battery level (charge state of the battery 60) [%]. This battery level is a planned value determined at the time of departure. Hereinafter, the battery level corresponding to the first energy level calculated by the first calculation unit 10 will also be referred to as the planned battery level. In particular, the planned battery level when the drone 6 arrives at the destination will also be referred to as the planned battery level at arrival. Based on the planned battery level, the first calculation unit 10 calculates a planned value for the flight time possible with the battery level at each point (hereinafter also referred to as the planned flight time).

[0032] The second calculation unit 11 calculates the amount of energy currently held by the drone 6 as the actual remaining energy, based on energy usage information (voltage and current) during the drone 6's flight. The actual remaining energy corresponds to the measured value of the battery 60's electrical energy. The second calculation unit 11 converts the calculated actual remaining energy, which is the electrical energy [Wh] of the battery 60, into battery remaining energy (charge state of the battery 60) [%]. This battery remaining energy is calculated based on the amount of electrical energy actually used. Hereinafter, the battery remaining energy corresponding to the actual remaining energy calculated by the second calculation unit 11 will also be referred to as the measured battery remaining energy. Based on the measured battery remaining energy, the second calculation unit 11 calculates an estimated flight time (hereinafter also referred to as the estimated flight time) based on the battery remaining energy at each point passed through.

[0033] The second calculation unit 11 calculates the amount of energy the drone 6 will have when it arrives at the destination point, based on the flight path planning information, the current position information of the drone 6, and the actual remaining energy, as the second remaining energy, assuming the drone 6 moves from its current position to the destination point.

[0034] The second calculation unit 11 converts the calculated second energy remaining amount, which is the electrical energy [Wh] of the battery 60, into battery remaining amount (charge state of the battery 60) [%]. This battery remaining amount is estimated by taking into account the actual measured battery remaining amount of the drone 6 during flight. Hereafter, the battery remaining amount corresponding to the second energy remaining amount calculated by the second calculation unit 11 will also be referred to as the estimated battery remaining amount at arrival.

[0035] The memory unit 12 stores the battery remaining charge plan value and flight time plan value calculated by the first calculation unit 10 as a data table, associating them with the position and planned time of passage at each point along the flight path. This data table is held in the memory unit 12 as the battery consumption plan. The memory unit 12 outputs the battery consumption plan to the output unit 14. The memory unit 12 temporarily stores data such as the current position of the drone 6, the current time, and the current measured battery remaining charge of the drone 6, and outputs it to the output unit 14. When a waypoint is passed, the memory unit 12 stores the measured battery remaining charge value calculated by the second calculation unit 11 as a data table, associating it with the position and time of passage at that waypoint. This data table is held in the memory unit 12 as the actual battery consumption. The memory unit 12 outputs the actual battery consumption to the output unit 14.

[0036] The output unit 14 provides the battery consumption plan to the display device 7a of the remote control device 7 via the communication device 3a before the drone 6 starts flying from the departure point, or while the drone 6 is in flight. While the drone 6 is in flight, the output unit 14 provides the actual battery consumption, the current position of the drone 6, the measured battery level, and the estimated battery level at arrival to the display device 7a of the remote control device 7 via the communication device 3a. The output unit 14 outputs signals to display the calculation results of the first calculation unit 10 and the second calculation unit 11 on the display device 7a in a display mode described later. The display device 7a displays the signals (information) provided by the output unit 14, i.e., the calculation results of the first calculation unit 10 and the second calculation unit 11, on its display screen.

[0037] Furthermore, the location information of waypoints included in the actual battery consumption is included in the location information of waypoints included in the battery consumption plan. In other words, the actual battery consumption and the battery consumption plan are linked. For this reason, it can be said that the output unit 14 outputs the battery consumption plan and the actual battery consumption in association. The control unit 15 controls the timing of calculations by the first calculation unit 10 and the second calculation unit 11, controls the storage processing of calculation results to the storage unit 12, and controls the output of data from the output unit 14 to the communication device 3a. In short, the control unit 15 coordinates the aforementioned components with each other and instructs the execution of various processes.

[0038] Figure 3 is a schematic diagram of the flight path set by the route setting device 1b. Figure 3 shows the drone 6 flying along the flight path set by the route setting device 1b. As shown in Figure 3, the flight path is divided into several waypoints WP1 to WP9 from the departure point to the destination point. The drone 6 flies in ascending order of the numerical part of the code assigned to the waypoints. In the example shown in Figure 3, the drone 6 is flying near waypoint WP5. Therefore, the flight history for waypoints WP1 to WP4 before reaching waypoint WP5 is recorded.

[0039] Figure 4A is a data table of the battery consumption plan, which is the calculation result of the first calculation unit 10. As shown in Figure 4A, the battery consumption plan includes the planned battery charge value and the planned flight time value at each point along the flight path (departure point, waypoint, destination point).

[0040] Figure 4B is a data table of battery consumption results calculated by the second calculation unit 11. As shown in Figure 4B, the battery consumption results include the actual battery level and estimated flight time at the points that the drone 6 actually passed through (hereinafter also referred to as pass points). Note that in Figure 4B, the points that the drone 6 did not reach (WP5 to WP9, destination points) are left blank because the actual battery level has not been calculated.

[0041] Figure 5 shows an example of an image of the battery level indicator 100 displayed on the display device 7a. The output unit 14 outputs information such as the battery consumption plan, actual battery consumption, current measured battery level, planned battery level at arrival, and estimated battery level at arrival to the communication device 3a. The communication device 3a provides the information acquired from the output unit 14 to the display device 7a of the remote control device 7 via the network 4. Based on the provided information, the display device 7a displays the battery level indicator 100 on its display screen. The operator can obtain information such as the battery consumption plan and actual battery consumption from the battery level indicator 100 displayed on the display screen of the display device 7a.

[0042] As shown in Figure 5, the battery level indicator 100 includes a battery level gauge frame 101, a battery consumption plan indicator 102, a battery consumption actual indicator 103, a battery level gauge 104, an arrival level prediction gauge 105, and an arrival level plan gauge 106. The battery level indicator 100 shows the various battery levels of the drone 6. The battery level is represented by the charge state (SOC) of the battery 60.

[0043] The battery level gauge frame 101 is represented by a rectangular frame. The upper end of the battery level gauge frame 101 represents 100% battery level, and the lower end of the battery level gauge frame 101 represents 0% battery level. The battery consumption plan indicator 102 is located outside the battery level gauge frame 101 and is represented by multiple scales (short lines) arranged along the left side of the frame. The battery consumption plan indicator 102 represents the planned battery level at each waypoint. For example, the battery consumption plan indicator 102 represents the expected battery level at each point (see Figure 4A). In this way, the battery consumption plan indicator 102 represents the initial energy level (planned battery level) at the time the drone 6 arrives at each of the multiple waypoints on the flight path by the position of multiple images of the scale shape.

[0044] The battery consumption indicator 103 is located inside the battery level gauge frame 101 and is represented by multiple triangular marks arranged along the left-hand line of the frame. The battery consumption indicator 103 represents the measured battery level at each waypoint the drone 6 has passed through (see Figure 4B). In this way, the battery consumption indicator 103 represents the actual remaining energy (measured battery level) calculated when passing through multiple waypoints on the flight path by the positions of multiple triangular images.

[0045] The battery level gauge 104 is located inside the battery level gauge frame 101 and is represented by a light-colored bar (shown as a grid hatch in the figure) that extends upward from the lower end of the battery level gauge frame 101 along the longitudinal direction (vertical direction) of the battery level gauge frame 101. The battery level gauge 104 represents the actual battery level of the drone 6 at the present time. In this way, the battery level gauge 104 represents the actual remaining energy (actual battery level) currently held by the drone 6 by the length and area of ​​the rectangular image.

[0046] The arrival battery level prediction gauge 105 is located inside the battery level gauge frame 101 and is represented by a dark bar (shown as hatched in the figure) that extends upward from the lower end of the battery level gauge frame 101 along the longitudinal direction (vertical direction) of the battery level gauge frame 101. The arrival battery level prediction gauge 105 shows the estimated battery level at arrival, which is the expected battery level of the drone 6 when the drone 6 arrives at the destination. In this way, the arrival battery level prediction gauge 105 represents the second energy level (estimated battery level at arrival) when the drone 6 arrives at the destination by the length and area of ​​a rectangular image.

[0047] The arrival battery level planning gauge 106 is located outside the battery level gauge frame 101 and is represented by a black bar that extends upward from the lower end of the battery level gauge frame 101 along the longitudinal direction (vertical direction) of the battery level gauge frame 101. The arrival battery level planning gauge 106 represents the arrival battery level planning value (see the bottom row of Figure 4A), which is the expected battery level of the drone 6 when the drone 6 arrives at the destination. In this way, the arrival battery level planning gauge 106 represents the first energy level (arrival battery level planning value) when the drone 6 arrives at the destination by the length and area of ​​a rectangular image.

[0048] The bars representing each gauge (battery level gauge 104, estimated battery level upon arrival gauge 105, and planned battery level upon arrival gauge 106) indicate that the longer the bar in the vertical direction, the greater the remaining battery level. As the battery level decreases, the length of each gauge shortens. In other words, the upper end of each gauge moves downward.

[0049] In the battery consumption plan indicator 102, the scale (short line) representing the expected battery level at the waypoint that the drone 6 just passed (waypoint WP4 in the illustrated example) and the nearest waypoint that the drone 6 is scheduled to pass in the future (waypoint WP5 in the illustrated example) displays the symbol or name of that waypoint using text 107 and 108. Text 107 represents the waypoint that the drone 6 just passed, and text 108 represents the nearest waypoint that the drone 6 is scheduled to pass in the future.

[0050] The battery level indicator 100 is fitted with a pentagonal label 109. The label 109 is positioned such that one of its vertices, an indicator point 109a, touches the left edge of the battery level gauge frame 101. The label 109 is outside the battery level gauge frame 101 and moves continuously downward along the longitudinal direction (vertical direction) of the battery level gauge frame 101, with the upper end of the battery level gauge frame 101 as the reference point. The distance from the lower end of the battery level gauge frame 101 to the indicator point 109a of the label 109 (the height of the label 109) represents the expected battery level, which is the planned battery level at the drone 6's current position (see Figure 4A). Furthermore, the distance from the bottom edge of the battery level gauge frame 101 to the top edge of the label 109 represents the maximum battery level (see Figure 4A), and the distance from the bottom edge of the battery level gauge frame 101 to the bottom edge of the label 109 represents the minimum battery level (see Figure 4A). In other words, the vertical width of the label 109 represents the range of the planned battery level corresponding to the current position of the drone 6. Thus, the label 109 represents the first energy level (planned battery level) at the current position of the drone 6 by the position of the pentagonal image. Also, the label 109 represents the range of the planned battery level by the size of the image.

[0051] Label 109 displays text representing the range of planned battery levels and flight time corresponding to the current position of drone 6. In the example shown in Figure 5, it is indicated that drone 6 is located between waypoint WP4 and waypoint WP5.

[0052] As shown in Figure 5, the battery level indicator 100 is equipped with a battery level indicator 110. The battery level indicator 110 is located outside the battery level gauge frame 101 and is represented by an arrow image pointing to the line on the right side of the frame. The battery level indicator 110 moves continuously downward along the longitudinal direction (vertical direction) of the battery level gauge frame 101, with the upper end of the battery level gauge frame 101 as the reference point. The distance from the lower end of the battery level gauge frame 101 to the battery level indicator 110 (the height of the battery level indicator 110) represents the current measured battery level of the drone 6. The battery level indicator 110 points to the upper end of the battery level gauge 104. In this way, the battery level indicator 110 represents the actual remaining energy (measured battery level) currently held by the drone 6 by the position of the arrow-shaped image.

[0053] The battery level indicator 110 is accompanied by text 111 representing the current measured battery level of the drone 6 and text 112 representing the current estimated flight time of the drone 6. This allows the pilot to compare the current measured battery level of the drone 6 with the range of the planned battery level. The pilot can also compare the current estimated flight time of the drone 6 with the planned range of flight time.

[0054] The display device 7a displays the label 109 and the battery level indicator 110 in a comparable manner. Similarly, the display device 7a displays the label 109 and the battery level gauge 104 in a comparable manner. The operator can confirm whether the drone 6's battery 60 is being consumed according to the battery consumption plan by comparing the height (position) of the label 109 with the height (position) of the battery level indicator 110, or by comparing the height (position) of the label 109 with the height (position) of the top of the battery level gauge 104. In the example shown in Figure 5, the height of the label 109 is lower than the height of the battery level indicator 110. Therefore, the operator can confirm that the consumption of the battery 60 is lower than planned.

[0055] As the drone 6 approaches its destination from its starting point, the length of the battery level gauge 104 decreases. Each time the drone 6 passes a waypoint, the battery consumption indicator 103 is displayed and its count increases. The operator can compare the battery consumption plan indicator 102, which is displayed above the label 109 and the battery level indicator 110, with the battery consumption indicator 103. This allows the operator to see how the battery 60 was consumed during the flight to the waypoints that the drone 6 passed through.

[0056] As described above, the display screen of the display device 7a shows, in a manner that allows comparison between the actual battery level calculated when the drone 6 passes through each of the multiple waypoints on the flight path and the planned battery level at that waypoint. The battery consumption plan (planned battery level at each waypoint) and the actual battery consumption (actual battery level at the time of passing each waypoint) are displayed side by side. Therefore, the operator can compare the battery consumption plan and the actual battery consumption. Thus, the operator can easily understand whether the drone 6 has experienced power consumption different from what was expected during its previous flights.

[0057] The display device 7a displays the arrival battery level plan gauge 106 and the arrival battery level prediction gauge 105 in a display manner that allows for comparison. The operator can compare the lengths of the arrival battery level plan gauge 106 and the arrival battery level prediction gauge 105. This allows the operator to confirm whether there is sufficient battery power for the drone 6 to reach its destination. The operator can also determine whether there will be sufficient battery power when the drone 6 reaches its destination if it continues flying toward it. In other words, the operator can appropriately determine whether there is sufficient future operating time for the drone 6. For example, if the length of the arrival battery level prediction gauge 105 is longer than the arrival battery level plan gauge 106, the operator can determine that it is possible to return from the original destination (delivery destination 9) to the original departure point (delivery base 8).

[0058] As described above, the energy management device 1a provides the operator with information as illustrated in Figure 5 via the display device 7a. Specifically, the energy management device 1a displays the current actual remaining energy (measured battery level), the first remaining energy (planned battery level) when the drone 6 arrives at each waypoint and destination, and the second remaining energy (estimated battery level at arrival) when the drone 6 arrives at the destination, on the display device 7a in a comparable display format. Therefore, the operator can easily grasp information related to the future activity time of the drone 6. As a result, the operator can easily make predictions about the future activities of the drone 6. Although Figure 5 describes an example where the battery level indicator 100 is rectangular in shape, the display format is not limited to this. For example, the battery level indicator 100 may be arc-shaped or circular.

[0059] <Details of processing by the first calculation unit> The details of the processing performed by the first calculation unit 10 shown in Figure 2 will be explained below. The first calculation unit 10 estimates the power consumption of the drone 6 based on the information acquired by the information acquisition unit 13. The first calculation unit 10 also estimates the remaining battery capacity and flight time based on the estimated power consumption.

[0060] <Estimation of power consumption> The information acquisition unit 13 acquires flight path information set by the route setting device 1b from the route setting device 1b. The flight path information includes information on the position, altitude, and scheduled time of passage that the drone 6 should take. The position information is, for example, coordinates in a plane such as latitude and longitude. The altitude information is the height from a reference plane (earth surface or sea surface). The altitude information may also be the height of a rotating ellipsoid or geoid height. The position and altitude are linked to the information on the scheduled time of passage.

[0061] The first calculation unit 10 calculates the flight distance [km] corresponding to multiple locations (including waypoints and destination points) along the flight path based on the flight path information. The first calculation unit 10 multiplies the calculated flight distance by the power consumption rate [Wh / km], which is the amount of power consumed by the drone 6 per unit distance. This calculates the amount of power [Wh] consumed when the drone 6 flies from the starting point to multiple locations along the flight path. This amount of power is denoted as the reference value of power consumption Wr.

[0062] The information acquisition unit 13 acquires environmental information about the area around the flight path from an environmental information distribution server (not shown). The environmental information distribution server provides environmental information (weather information) such as wind direction, wind speed, precipitation, and temperature for each region. The information acquisition unit 13 may also acquire environmental information from environmental sensors installed around the flight path.

[0063] The first calculation unit 10 corrects the amount of power consumption calculated based on the flight distance based on environmental information along the flight path, information about the drone 6, and information about the goods 69 carried by the drone 6. The first calculation unit 10 calculates the corrected amount of power consumption Wc by multiplying the calculated reference value of power consumption Wr by a correction coefficient or by adding a correction amount.

[0064] Environmental information includes, for example, information on wind direction and wind speed when the drone 6 flies along its flight path. The determination unit 16 determines, based on the wind direction information, whether there is a headwind or a tailwind blowing towards the drone 6. The first calculation unit 10 determines, based on the determination result of the determination unit 16, whether to increase or decrease the power consumption through correction. The first calculation unit 10 also determines the magnitude of the correction coefficient based on the wind speed.

[0065] The first calculation unit 10 takes a no-wind condition as 1 and, if there is a headwind, multiplies the reference value Wr of power consumption by a correction coefficient C1 greater than 1 (for example, 1.1 or 1.5) to correct the power consumption in a way that increases it. The first calculation unit 10 corrects the power consumption in a way that decreases it by multiplying the reference value Wr of power consumption by a correction coefficient C1 less than 1 and greater than 0 (for example, 0.8 or 0.5) if there is a tailwind.

[0066] The correction factor C1 is set using a data table that corresponds to wind speed and wind direction. When the wind direction is a headwind, the correction factor C1 is set to a larger value as the wind speed increases. Conversely, when the wind direction is a tailwind, the correction factor C1 is set to a smaller value as the wind speed increases.

[0067] The first calculation unit 10 may further adjust the power consumption by taking into account rainfall or snowfall conditions as environmental information. When there is rainfall or snowfall, the weight of the drone 6 increases as rain or snow collides with the drone 6 and adheres to the aircraft during flight. For this reason, the first calculation unit 10 adjusts the power consumption in an upward direction when there is rainfall or snowfall. The greater the precipitation, the more times the aircraft collides with raindrops or snow, and the more moisture and ice / snow adheres to the aircraft. For this reason, the first calculation unit 10 adjusts the power consumption by multiplying the reference value Wr of the power consumption by a correction coefficient C2 that increases as the amount of precipitation (or snowfall) increases.

[0068] The first calculation unit 10 makes a correction based on the weight of the goods 69 carried by the drone 6. A correction coefficient C31 is set, with the value being 1 when the drone 6 does not carry goods 69, and increasing as the weight of the goods 69 increases. The first calculation unit 10 corrects the power consumption by multiplying the correction coefficient C31 by the reference value Wr of the power consumption to increase the power consumption. If the goods 69 are mounted in a way that they are exposed from the drone 6, the first calculation unit 10 may make a correction not only based on the weight of the goods 69 but also based on the shape of the goods 69. A correction coefficient C32 is set, with the value being 1 when the goods 69 are not exposed, and increasing as the projected area of ​​the exposed part of the goods 69 viewed from the direction of travel increases. The first calculation unit 10 corrects the power consumption by multiplying the correction coefficient C32 by the reference value Wr of the power consumption to increase the power consumption.

[0069] Furthermore, if the information acquisition unit 13 obtains information from the information provision device 3 indicating that the weight of the materials 69 exceeds the weight that the drone 6 can carry, it determines that the drone 6 cannot fly and stops further calculations. In this case, the output unit 14 provides information to the display device 7a of the remote control device 7 via the communication device 3a to inform the operator that flight is impossible.

[0070] The first calculation unit 10 may correct the amount of power consumed based on the ambient temperature of the flight path. To keep the temperature of the cargo 69 carried on the drone 6 within a predetermined temperature range, an air conditioning system may be installed in the cargo compartment of the drone 6. If a person is on board the drone 6, an air conditioning system will be installed in the passenger compartment. The power consumption of the air conditioning system increases as the temperature difference between the set temperature and the ambient temperature of the flight path increases.

[0071] The air conditioning system consumes power regardless of the flight status of the drone 6. Therefore, it is preferable to account for the power consumption of the air conditioning system separately from the power consumption associated with the flight (movement) of the drone 6. In other words, when correcting based on the ambient temperature, it is preferable to add the correction amount to the reference value Wr of power consumption rather than multiplying it by the correction coefficient.

[0072] A correction amount C4 is set, with the value set to 0 when the ambient temperature is equal to the set temperature, and increasing as the temperature difference between the set temperature and the ambient temperature increases. The first calculation unit 10 corrects the power consumption by adding the correction amount C4 to the reference value Wr of power consumption, thereby increasing the power consumption. The set temperature is included in the drone 6's aircraft information transmitted from the drone 6 to the server 1. The ambient temperature is included in the environmental information transmitted from the environmental information distribution server (not shown) to the server 1.

[0073] The correction amount C5 may be set by taking into account the power consumption of the lighting equipment, control system for realizing autonomous and remotely controlled flight, and communication device equipped on the drone 6. The drone's control system includes a computing device, voltage sensor, current sensor, etc. The power consumption per unit time of the lighting equipment, control system, and communication device is approximately constant. The first calculation unit 10 calculates the correction amount C5 at a given position by multiplying the power consumption per unit time of the lighting equipment, control system, and communication device by the flight time from the starting point to the position on the flight path. The first calculation unit 10 corrects the power consumption by adding the correction amount C5 to the reference value of the power consumption to increase the power consumption.

[0074] The power consumption per unit time of the lighting equipment, control system, and communication device is included in the drone 6's aircraft information. The power consumption per unit time of each piece of equipment is acquired by the information acquisition unit 13 and stored in the storage unit 12.

[0075] Flight paths are typically set over a wide area. Therefore, to accommodate changes in wind speed, wind direction, and weather distribution, the flight path may be divided into multiple sections, and correction coefficients C1 and C2 corresponding to wind speed, wind direction, and weather may be set for each corresponding section. In this case, the first calculation unit 10 calculates the corrected power consumption of the entire flight path by summing the corrected power consumption calculated for each of the multiple sections. The number of divisions is not limited. The more divisions there are, the better the accuracy of the power consumption calculation. The fewer divisions there are, the lower the computational load. It is preferable to determine the number of divisions considering the resolution of the weather information in the provided area.

[0076] As described above, the first calculation unit 10 corrects the power consumption by multiplying the reference value Wr of power consumption by a correction coefficient and adding a correction amount. The corrected power consumption Wc is calculated, for example, by the following (Equation 1). Wc=Wr×C1×C2×C31×C32+C4+C5…(Formula 1) Note that among the correction coefficients C1, C2, C31, and C32, those that are not considered should be set to 1. Also, among the correction amounts C4 and C5, those that are not considered should be set to 0.

[0077] The above describes an example in which the first calculation unit 10 determines the power consumption amount (corrected power consumption amount Wc) as information for battery consumption planning by multiplying the reference value Wr by correction coefficients C1 and C2 corresponding to environmental information such as wind speed and wind direction and weather, and correction coefficients C31 and C32 corresponding to the weight and shape of the material 69, and adding correction amounts C4 and C5 corresponding to the drone 6's aircraft information (power consumption characteristics of air conditioning equipment, control system, etc.) to the reference value Wr. However, the method by which the first calculation unit 10 determines the power consumption amount as information for the drone 6's battery consumption planning is not limited to this.

[0078] For example, the first calculation unit 10 may determine the power consumption of the drone 6 using a machine learning model that associates various information related to the drone 6's aircraft information, environmental information, and information on the materials 69 with an estimated power consumption. The training data may be the drone 6's flight history and data obtained from flight experiments. The first calculation unit 10 takes the drone 6's aircraft information, environmental information, and information on the materials 69 as input and outputs an estimated power consumption using a machine learning model. The first calculation unit 10 obtains the power consumption by integrating the estimated power consumption values.

[0079] When using data obtained from flight records and flight experiments, it is preferable to use the surrogate model described below. Figure 6A is a schematic diagram illustrating the information used in the surrogate model. A surrogate model is a method that replaces physical simulation with machine learning. The information acquisition unit 13 acquires the information necessary for computational processing using the surrogate model through the information providing device 3. In Figure 6A, the airspace 53 including the flight path 50 is represented by multiple rectangles. The information acquisition unit 13 acquires environmental information along the flight path 50 of the drone 6. The environmental information 51 is representative information of the airspace 53, and is, for example, information corresponding to the position of a point in the center of the rectangular airspace 53.

[0080] Multiple calculation points 52 are set along the flight path 50, which define the timing for calculating the power consumption of the drone 6. The calculation points 52 are set, for example, to correspond to the position of the drone 6 on the flight path 50 every second. Thus, when using a surrogate model, it is preferable to divide the flight path 50 into units of time (for example, 1 second) and set the calculation points 52 accordingly.

[0081] The surrogate model is configured to output the amount of power consumed per unit time by the drone 6 under various conditions, i.e., power consumption [W]. The first calculation unit 10 integrates the power consumption obtained using the surrogate model (power consumption calculated for each calculation point 52) ​​in the time direction and calculates the amount of power consumed [Wh]. The amount of power consumed is calculated at each of the multiple calculation points 52 along the flight path 50.

[0082] In Figure 6A, the information is illustrated as being laid out on a plane for illustrative purposes, but in reality, the information is laid out not only in the height direction but also in the time direction. As mentioned above, the flight path information of the drone 6 includes spatial position (planar position and altitude) and time. Therefore, the information acquisition unit 13 acquires wind conditions (wind speed and wind direction) and temperature information corresponding to each spatial position and time, and the acquired information can be used as input to the surrogate model.

[0083] Figure 6B is a block diagram illustrating the power consumption calculation process using a surrogate model 56. The surrogate model 56 is a proxy model that establishes the relationship between input and output. In this embodiment, the state variables of the drone 6's flight conditions are used as input. The state variables of the drone 6's flight conditions include environmental information 51 along the drone 6's flight path (wind conditions, precipitation, etc.), the drone 6's flight speed, and the weight of the materials 69 carried on the drone 6. The output is the power consumption (power consumption per unit time) P associated with the flight of the drone 6. drone That is the case.

[0084] As shown in Figure 6A, the environmental information 51 includes wind speed, wind direction (azimuth and angle of attack), ambient temperature, and precipitation at each calculation point 52. Wind direction and wind speed are given in latitude and longitude or cardinal coordinate systems (e.g., geographic coordinate systems). When using the environmental information 51 as input to the surrogate model 56, it is converted to a local coordinate system (drone reference coordinate system) starting from the direction in which the drone 6 is moving forward. For example, the wind speed and wind direction given as environmental information 51 are decomposed into components parallel to the direction of forward movement (components in the front-to-back direction of the drone 6) and components perpendicular to the direction of forward movement (components in the left-to-right direction of the drone 6, and components in the up-and-down direction of the drone 6) in the local coordinate system of the drone 6. Similarly, the flight speed on the flight path 50 is also decomposed into components parallel and perpendicular to the direction of travel of the drone 6. The weight of the materials 69 carried on the drone 6 and the precipitation are also input state variables.

[0085] In the example shown in Figure 6B, the input state variables for the surrogate model 56 are: Vx^, the flight velocity component parallel to the front-to-back direction of the drone 6; Vy^, the flight velocity component parallel to the left-to-right direction of the drone 6; Vz^, the flight velocity component parallel to the up-to-down direction of the drone 6; altitude Xz; and the weight m of the material 69. payload The wind speed components Wx^ parallel to the front-to-back direction of the drone 6, Wy^ parallel to the left-to-right direction of the drone 6, Wz^ parallel to the up-to-down direction of the drone 6, and precipitation Ap are also included. The surrogate model 56 is the power consumption P of the drone 6 when the drone 6 flies under certain flight conditions. drone Outputs.

[0086] The first calculation unit 10 calculates the power consumption P of the lighting equipment, control system, and communication device of the drone 6 const and the power consumption P of the air conditioning equipment AC and adds them to the output of the surrogate model 56 (the power consumption P of the drone 6 associated with flight drone ) to calculate the total power consumption P of the drone 6. As shown in FIG. 6B, the air conditioning power model 57 calculates the power consumption P of the air conditioning equipment of the drone 6 AC . The power consumption P AC can be calculated using a table function or regression equation that defines the relationship between the power consumption P of the air conditioning equipment AC , the outside air temperature T atm , and the temperature difference from the set temperature T of the air conditioning equipment set . The first calculation unit 10 multiplies the flight time from the departure point to the calculation point 52 by the total power consumption P [W] to calculate the total power consumption amount W [Wh] when flying to the calculation point 52.

[0087] The surrogate model 56 can be constructed by conducting a flight experiment under predetermined flight conditions and measuring the power consumption amount of the drone 6. In addition to experiments, the surrogate model 56 may be constructed using numerical simulations based on the specifications of the drone 6 or data on the flight performance of the drone 6.

[0088] For such a surrogate model 56, a Gaussian process regression model or kernel density estimation can be preferably used. The Gaussian process regression model can output the expected value of the power consumption amount and its reliability for experimental results and flight performance. Therefore, the prediction result can be obtained as a distribution. The method based on kernel density estimation can also perform similar calculations by increasing the sampling points to obtain an estimated value of the power consumption amount as a statistical population and then calculating the expected value and confidence interval for the obtained statistical population.

[0089] As shown in Figure 4A, the distribution obtained above allows us to obtain a range of prediction results, including not only the expected value of power consumption, but also the maximum value of power consumption (upper side) and the minimum value of power consumption (lower side). Therefore, the pilot can check whether the actual battery consumption of the drone 6 (measured battery level) falls within the range of the battery consumption plan (between the minimum and maximum battery levels). This allows the pilot to determine whether the drone 6 is continuing to fly under the expected power consumption conditions.

[0090] Furthermore, in the method described before the example of calculating power consumption using the surrogate model 56, namely the method of calculating power consumption using correction coefficients and correction amounts, it is possible to make predictions with a range by setting multiple correction coefficients and correction amounts. For example, it is possible to set three types of correction coefficients and correction amounts for various conditions, such as lower, middle, and upper, and obtain predictions by dividing them into worst-case (lower) and best-case (upper) scenarios.

[0091] <Setting alternative flight paths> The determination unit 16 determines whether the predicted power consumption exceeds the remaining battery capacity of the drone 6. If the determination unit 16 determines that the power consumption exceeds the remaining battery capacity, the output unit 14 requests the route setting device 1b to set an alternative flight path. The route setting device 1b sets an alternative flight path and provides the planning information to the energy management device 1a. The energy management device 1a calculates the battery consumption plan and actual battery consumption based on the planning information of the alternative flight path. This configuration prevents the setting of a path that makes it impossible for the drone 6 to perform its service.

[0092] <Planned battery charge and planned flight time> The first calculation unit 10 calculates the battery remaining charge plan value and the flight time plan value based on the flight path planning information and the total power consumption described above. First, the first calculation unit 10 calculates the average power consumption plan value Pavp of the drone 6 using the following (Equation 2). Pavp = W / (ta-td) …(Equation 2) Here, W is the amount of power consumed by the drone 6 from the departure point to the destination point (total power consumption). The total power consumption W is calculated using (Equation 1) or the surrogate model 56, as described above. ta is the scheduled arrival time, and td is the scheduled departure time. The scheduled arrival time ta and scheduled departure time td are included in the flight path planning information. In this way, the first calculation unit 10 calculates the average power consumption plan value Pavp of the drone 6 from the total power consumption W from the departure point to the destination point and the difference between the scheduled departure time td and the scheduled arrival time ta at the destination point.

[0093] The first calculation unit 10 uses the following (Equation 3) to calculate the planned remaining power amount Wrpa, which is the amount of power that the drone 6 can use after arriving at the destination point. Wrpa = Wrd - W …(Equation 3) Here, Wrd is the battery level at the starting point converted to remaining power, and W is the total power consumption as described above.

[0094] The first calculation unit 10 calculates the planned battery charge at arrival (predicted battery charge at arrival based on the plan) Brpa by converting the calculated planned battery charge at arrival Wrpa into battery charge. In this way, the first calculation unit 10 calculates the remaining power of the drone 6 when it arrives at the destination (planned battery charge at arrival Wrpa) by subtracting the total power consumption W from the departure point to the destination point from the remaining power Wrd, which is the battery charge of the drone 6 at the departure point, and calculates the planned battery charge at arrival Brpa by converting the calculated remaining power.

[0095] The first calculation unit 10 calculates the flight time plan value tp, which is the time the drone 6 can fly when it arrives at the destination point, using the following equation (4). tp=Wrpa / Pavp…(Formula 4) Here, Wrpa is the planned remaining energy at arrival calculated by (Equation 3), and Pavp is the planned average power consumption calculated by (Equation 2). In this way, the first calculation unit 10 calculates the planned flight time tp by dividing the planned remaining energy at arrival Wrpa by the planned average power consumption Pavp.

[0096] The first calculation unit 10 calculates the battery level (planned battery level) at the point where the drone 6 passes through a waypoint using the same method as the method for calculating the battery level at the point where the drone 6 arrives at the destination (planned battery level at arrival). Furthermore, the first calculation unit 10 calculates the flight time (planned flight time) at the point where the drone 6 passes through a waypoint using the same method as the method for calculating the flight time (planned flight time) at the point where the drone 6 arrives at the destination. In other words, the planned flight time at each waypoint is calculated by dividing the amount of power the drone 6 has available after passing the waypoint by the average planned power consumption value Pavp.

[0097] The first calculation unit 10 calculates the planned battery charge value and the planned flight time value at each waypoint, and generates a battery consumption plan (Figure 4A) by linking the calculation results with the planned time of passage at each waypoint.

[0098] <Details of processing by the second calculation unit> The details of the processing performed by the second calculation unit 11 shown in Figure 2 will be explained below. Based on various information about the drone 6 in flight, the second calculation unit 11 calculates the amount of electricity consumed per unit time by the drone 6 (hereinafter also referred to as the actual power consumption value Pa). The second calculation unit 11 also estimates the flight time according to the remaining battery level based on the actual power consumption value Pa of the drone 6.

[0099] <Average power consumption> The second calculation unit 11 calculates the average power consumption (hereinafter also referred to as the average power consumption Pav) for the flight of the drone 6 from the departure point to the destination point using the following equation (5). Pav=(Pa×w1+Pp×w2) / (w1+w2) …(Formula 5) Here, Pa is the actual power consumption value, which is the amount of power consumed per unit time during the flight of the drone 6 from the departure point to the calculation point. Pp is the predicted power consumption value, which is the amount of power consumed per unit time during the flight from the calculation point to the destination point. The calculation point is the position of the drone 6 at the time the second calculation unit 11 performs the calculation, i.e., the current position of the drone 6. w1 and w2 are weights, which are determined by the progress rate of the path flown by the drone 6. For example, the second calculation unit 11 uses the flight distance from the departure point to the calculation point as weight w1, and the flight distance from the calculation point to the destination point as weight w2.

[0100] In this way, the second calculation unit 11 weights the actual power consumption value Pa and the predicted power consumption value Pp at any point after the drone 6 has started flying, based on the progress of the path the drone 6 has traveled. This calculates the average power consumption value Pav for the current flight. Immediately after the start of flight, the weight w1 for the actual power consumption value Pa is small, and the weight w2 for the predicted power consumption value Pp is large. As the flight distance of the drone 6 increases, the weight w1 for the actual power consumption value Pa increases, and the weight w2 for the predicted power consumption value Pp decreases. In this way, as will be described later, the actual power consumption of the drone 6 for the current flight can be reflected in the calculation of the battery remaining charge forecast and the estimation of the flight time.

[0101] <Actual power consumption values> The control system of the drone 6 measures the voltage of the battery 60 and the current flowing through the battery 60 and provides this information to the energy management device 1a. The information acquisition unit 13 acquires the measurement results of the voltage and current of the battery 60. The second calculation unit 11 calculates the power consumption by multiplying the voltage and current acquired by the information acquisition unit 13. The second calculation unit 11 calculates at predetermined intervals (e.g., 1-second interval, 10-second interval, etc.) and obtains the actual power consumption value Pa by calculating the average value. Alternatively, the second calculation unit 11 may obtain a pseudo-average power consumption by filtering the instantaneous power consumption calculated from the voltage and current measured at predetermined timings using a low-pass filter. This method reduces the number of times power consumption is calculated in time series, thus reducing the required memory capacity.

[0102] <Predicted power consumption> The second calculation unit 11 refers to the battery consumption plan calculated by the first calculation unit 10 and calculates the power consumption for the remaining section from the point corresponding to the drone 6's current position (calculation point) to the destination point as the predicted power consumption value Pp.

[0103] The second calculation unit 11 calculates the predicted power consumption value Pp using the following (Equation 6). Pp = (Wrpc - Wrpa) / tf …(Equation 6) Here, Wrpc is the value [Wh] obtained by converting the planned battery charge value Brpc[%] at the calculation point into remaining energy, and Wrpa is the value [Wh] obtained by converting the planned battery charge value Brpa[%] at arrival, which is the planned battery charge value at the destination point, into remaining energy. tf is the planned flight time from the calculation point to the destination point. The planned battery charge value Brpc (including the planned battery charge value Brpa at arrival) is calculated by the first calculation unit 10.

[0104] The planned battery charge value Brpc (including the planned battery charge value Brpa upon arrival) uses, for example, the expected battery charge. In other words, in the example shown in Figure 4A, the planned battery charge value Brpa upon arrival is 36.4%, which is the expected battery charge at the destination. The planned battery charge value Brpc at the calculation point is the expected battery charge at the calculation point, and if the calculation point is waypoint WP4, it is 74.9%. The first calculation unit 10 may also calculate the planned battery charge value Brpc for any point other than those shown in the data table in Figure 4A. In other words, the second calculation unit 11 can calculate the predicted power consumption value Pp at any point.

[0105] <Scheduled flight time> The determination unit 16 compares the current time with the scheduled time of passage to the current position (calculation point) of the drone 6 to determine whether the actual flight of the drone 6 is behind schedule. If the current time is later than the scheduled time of passage to the current location, the determination unit 16 determines that the actual flight of the drone 6 is behind schedule. If the current time is earlier than the scheduled time of passage to the current location, the determination unit 16 determines that the actual flight of the drone 6 is not behind schedule.

[0106] If the determination unit 16 determines that the actual flight of the drone 6 is behind schedule, the second calculation unit 11 calculates the planned flight time tf, which is the time required to travel from the drone 6's current position (calculation point) to the destination point, using the following (Equation 7a). tf = Dr / va …(Equation 7a) Here, Dr is the flight distance from the calculation point to the destination point, and is calculated from the flight path. va is the average flight speed from the departure point to the calculation point, and is obtained by dividing the flight distance from the departure point to the calculation point by the flight time from the departure point to the calculation point.

[0107] If the determination unit 16 determines that the actual flight of the drone 6 is not behind schedule, the second calculation unit 11 calculates the scheduled flight time tf using the following (equation 7b). tf = Ta - Tc …(Equation 7b) Here, Ta is the estimated time of arrival at the destination, and Tc is the current time.

[0108] <Estimated power consumption> The second calculation unit 11 calculates an estimated power consumption value We, which is the amount of power consumed when the drone 6 flies from its current position (calculation point) to the destination point, using the following equation (8). We = tf × Pav …(Equation 8) tf is the planned flight time calculated by (Equation 7a) or (Equation 7b), and Pav is the average power consumption calculated by (Equation 5). The second calculation unit 11 calculates the amount of power consumed during the remaining flight (estimated power consumption We) by multiplying the planned flight time tf by the average power consumption Pav.

[0109] <Estimated battery level upon arrival> The second calculation unit 11 calculates the estimated remaining power at arrival, Wrea, using the following equation (9). Wrea = Wrac - We …(Equation 9) Here, Wrac is the value obtained by converting the measured battery level at the calculation point into remaining energy, and We is the estimated power consumption calculated by (Equation 8).

[0110] The second calculation unit 11 calculates the estimated battery remaining capacity at arrival (a predicted value of the battery remaining capacity at the time of arrival based on actual data) Brea by converting the calculated estimated remaining power capacity Wrea at arrival into battery capacity. In this way, the second calculation unit 11 calculates the remaining power capacity of the drone 6 at the time of arrival at the destination (estimated remaining power capacity at arrival Wrea) by subtracting the estimated power consumption We from the remaining power capacity Wrac, which is calculated from the current battery capacity of the drone 6, and calculates the estimated battery remaining capacity at arrival Brea by converting the calculated remaining power capacity.

[0111] <Actual battery level measurement> The second calculation unit 11 calculates the current battery level of the drone 6, the measured battery level Brac, based on the energy usage information (voltage and current information of the battery 60) acquired by the information acquisition unit 13. It is known that the voltage of the battery 60 increases as it approaches full charge. For this reason, it is conceivable to estimate the battery level from the voltage measurement result. However, this estimation method ideally requires measuring the voltage when the battery 60 is not being charged or discharged and has been left stationary for a long time. Since the drone 6 needs to constantly discharge in order to maintain flight, it is difficult to estimate the battery level of the drone 6 during flight based on voltage. For this reason, the method of estimating the battery level based on voltage is limited to before the start of flight.

[0112] The second calculation unit 11 calculates the initial value of the battery charge level (charge state) of the drone 6 from the voltage of the battery 60 before the drone 6 starts flying. During the flight of the drone 6, the second calculation unit 11 estimates the battery charge level (charge state) from the amount of electricity released by integrating the discharge current of the battery 60. This estimation method is called Coulomb counting. Alternatively, the second calculation unit 11 may construct a Thevenin equivalent model that represents the battery 60 equivalently with an ideal voltage source, resistance, and capacitance components, and estimate the battery charge level (charge state) using a state estimation means such as a Kalman filter.

[0113] An example has been described in which the estimated battery remaining capacity at arrival, Brea, based on actual performance, is calculated based on the average power consumption, Pav; however, the calculation method is not limited to this. The second calculation unit 11 may, for example, use the battery remaining capacity of the drone 6 at the calculation point as the initial value and calculate the amount of power consumed from the calculation point to the destination point as the estimated power consumption, We, using the same method as the calculation method of the first calculation unit 10. The second calculation unit 11 uses the power consumption calculated using the correction coefficient and correction amount, or the surrogate model 56, as the estimated power consumption, We, and calculates the estimated remaining power at arrival, Wrea, using (Equation 9). The estimated remaining power at arrival, Wrea, is then converted to calculate the estimated battery remaining capacity at arrival, Brea, based on actual performance.

[0114] The output unit 14 provides the display device 7a with the results calculated by the first calculation unit 10 and the second calculation unit 11. Based on the provided information, the display device 7a displays the battery level indicator 100 on its display screen.

[0115] According to the above-described embodiment, the following effects are achieved.

[0116] (1) The energy management system 2 comprises an energy management device 1a and a mobile drone 6. The energy management device 1a (server 1) comprises a computing device 1c and an input / output interface (output device) 1e. The information acquisition unit 13 of the computing device 1c acquires planning information for the flight path (movement path) of the drone 6 to the destination point, information about the drone 6 (mobile body information), the current position information of the drone 6, and usage information regarding the energy usage of the drone 6, which is the voltage and current information of the battery 60. The first calculation unit 10 of the computing device 1c calculates the amount of energy held by the drone 6 at the time the drone 6 arrives at any point on the flight path and at the destination point, based on the flight path planning information and the drone 6's information, and defines this as the first remaining energy. In this embodiment, the mobile body managed by the energy management device 1a is the drone 6 which flies using the electrical energy of the battery 60. Therefore, the amount of energy held by the drone 6 is the amount of electrical energy in the drone 6's battery 60. The first remaining energy corresponds to the battery remaining amount plan value described above. In particular, the first energy level at the time the drone 6 arrives at the destination corresponds to the planned battery level at arrival. The second calculation unit 11 of the computing device 1c calculates the amount of energy currently held by the drone 6 as the actual energy level based on energy usage information (voltage and current of the battery 60). The actual energy level corresponds to the measured battery level mentioned above. Based on the flight path planning information, the current position information of the drone 6, and the measured battery level (actual energy level), the second calculation unit 11 of the computing device 1c calculates the amount of energy held by the drone 6 at the time it arrives at the destination, assuming the drone 6 moves from its current position to the destination, as the second energy level. The second energy level corresponds to the estimated battery level at arrival mentioned above. The input / output interface 1e of the server 1, which acts as the first output device, outputs the measured battery level (actual energy level), the planned battery level (first energy level), and the estimated battery level at arrival (second energy level) to the communication device 3a. The communication device 3a, acting as a second output device, outputs information acquired from the server 1 to the display device 7a.The display device 7a displays the actual battery level (actual energy level), the planned battery level (first energy level), and the estimated battery level upon arrival (second energy level) on the display screen based on the information acquired via the communication device 3a.

[0117] This configuration provides an energy management device 1a and an energy management system 2 that can effectively determine the future activity time of a drone 6 that flies according to flight path planning information.

[0118] (2) The first calculation unit 10 and the second calculation unit 11 of the arithmetic unit 1c acquire environmental information about the surrounding area of ​​the flight path (travel path). The flight time and flight distance, depending on the remaining battery level, change not only depending on the driving method of the drone 6 but also on the environment. The arithmetic unit 1c according to this embodiment takes the acquired environmental information into account and calculates a planned battery level value (first energy level), including the planned battery level at arrival, and an estimated battery level at arrival (second energy level). With this configuration, the planned battery level value and estimated battery level can be calculated with greater accuracy compared to when environmental information is not taken into account.

[0119] (3) The display device 7a outputs various information regarding the amount of energy held by the drone 6 to the outside by displaying an image representing the remaining energy on the display screen. The computing device 1c outputs a signal to the display device 7a via the input / output interface (output device) 1e to display the actual battery remaining value, which is the actual amount of energy currently held by the drone 6, and the planned battery remaining value, which is the first amount of energy at an arbitrary point corresponding to the current position of the drone 6, in a display manner that allows for comparison.

[0120] As a result, for example, as shown in Figure 5, the actual battery level currently held by the drone 6 is displayed by the battery level indicator 110 and text 111. In addition, the planned battery level at any point corresponding to the drone 6's current position is displayed by label 109. Label 109 and battery level indicator 110 move downward along the battery level gauge frame 101 according to the planned and actual battery levels corresponding to the drone 6's current position. With this configuration, the operator can easily compare the actual battery level with the planned battery level and confirm whether the power of the drone 6's battery 60 is being consumed according to the battery consumption plan at the present time.

[0121] (4) The arithmetic unit 1c outputs a signal via the input / output interface (output device) 1e to the display device 7a in a display mode that allows comparison between the planned battery level at arrival, which is the first energy level at the time the drone 6 arrives at the destination, and the estimated battery level at arrival, which is the second energy level at the time the drone 6 arrives at the destination. As a result, for example, as shown in Figure 5, the planned battery level at arrival gauge 106 and the predicted battery level at arrival gauge 105, which extend upward from the lower end of the battery level gauge frame 101, are displayed side by side. With this configuration, the operator can confirm whether sufficient battery power is available when the drone 6 arrives at the destination.

[0122] (5) The arithmetic unit 1c outputs a signal via the input / output interface (output device) 1e to the display device 7a in a display manner that allows comparison of the measured battery level (actual energy level) calculated when the drone 6 passes through each of the multiple waypoints on the flight path with the planned battery level (first energy level) at the waypoint. As a result, for example, as shown in Figure 5, the battery consumption indicator 103 is displayed each time the drone 6 passes through a waypoint. The battery consumption plan indicator 102 and the battery consumption indicator 103 are arranged along the line on the left side of the battery level gauge frame 101. With this configuration, the measured battery level and the planned battery level can be compared at each waypoint, so the operator can confirm at each waypoint whether the amount of power in the drone 6's battery 60 is being consumed according to the battery consumption plan.

[0123] (6) The arithmetic unit 1c outputs a signal via the input / output interface (output device) 1e to the display device 7a for displaying the measured battery level (actual energy level), the planned battery level (first energy level), and the estimated battery level at arrival (second energy level) in a display manner that allows for comparison. In the above display manner, the measured battery level (actual energy level), the planned battery level (first energy level), and the estimated battery level at arrival (second energy level) are represented by the length of an image of a predetermined shape, the size of the area of ​​an image of a predetermined shape, or the position of an image of a predetermined shape. In this embodiment, the measured battery level at the present time is represented by the position on the display screen of the battery level indicator 110, which is an arrow-shaped image, and by the length and size of the area of ​​the battery level gauge 104, which is a rectangular (or strip-shaped) image. The planned battery level at the present time is represented by the position on the display screen of the label 109, which is a pentagon-shaped image. The planned remaining battery level upon arrival is represented by the length and area of ​​the planned remaining battery level gauge 106, which is a rectangular (or strip-shaped) image. The estimated remaining battery level upon arrival is represented by the length and area of ​​the predicted remaining battery level gauge 105, which is a rectangular (or strip-shaped) image. The actual battery level of the drone 6 after passing a waypoint is represented by the position on the display screen of the battery consumption indicator 103, which is a triangular mark image. The planned remaining battery level of the drone 6 at a waypoint is represented by the position on the display screen of the battery consumption indicator 102, which is a short linear image. In this configuration, by combining various display images, images that are easy for the operator to compare can be displayed on the display screen.

[0124] (7) The determination unit 16 of the arithmetic unit 1c compares the scheduled time of passage of the drone 6's current position (calculation point) with the current time to determine whether the actual flight of the drone 6 is behind schedule. If the determination unit 16 determines that the actual flight of the drone 6 is behind schedule, the second calculation unit 11 of the arithmetic unit 1c calculates the scheduled flight time tf, which is the time required for the drone 6 to travel from its current position (calculation point) to its destination, based on the flight distance from the drone 6's current position (calculation point) to the destination and the flight speed from the departure point to the current position (calculation point). If the determination unit 16 determines that the actual flight of the drone 6 is not behind schedule, the second calculation unit 11 of the arithmetic unit 1c calculates the scheduled flight time tf based on the scheduled time of arrival at the destination and the current time. Based on the scheduled flight time tf and the average power consumption Pav, the second calculation unit 11 estimates the amount of power consumed during the flight to the destination. The second calculation unit 11 calculates the estimated battery charge value Brea upon arrival based on the estimated power consumption value We, which is the estimation result.

[0125] If, when calculating the estimated power consumption We, the flight time tf is calculated based on the estimated arrival time at the destination and the current time, regardless of whether the actual flight of the drone 6 is behind schedule, there is a risk that the estimated power consumption We will be underestimated. In contrast, in this embodiment, it is determined whether the actual flight of the drone 6 is behind schedule, and if the actual flight of the drone 6 is behind schedule, the flight time tf is calculated based on the flight distance from the current position of the drone 6 to the destination and the flight speed from the departure point to the current position. This tends to increase the estimated power consumption We. In other words, it is possible to prevent the estimated power consumption We from being underestimated. As a result, the estimated battery charge at arrival, Brea, can be calculated at a conservative value.

[0126] <Modification 1 of the first embodiment> In the first embodiment described above, an example was described in which the first calculation unit 10 calculates the battery consumption plan before the drone 6 starts flying, and the second calculation unit 11 calculates an estimated battery level at the time the drone 6 arrives at the destination after the drone 6 starts flying. However, the timing of the calculation of the battery consumption plan by the first calculation unit 10 is not limited to this. The first calculation unit 10 may also calculate the battery consumption plan after the drone 6 has started flying. For example, if the flight path plan information of the drone 6 is updated for some reason after the drone 6 has started flying, the first calculation unit 10 will recalculate the battery consumption plan based on the updated plan information after the update.

[0127] <Modification 2 of the first embodiment> The second calculation unit 11 may determine whether the calculated estimated battery level at arrival, Brea, falls below a predetermined value. For example, if the estimated battery level at arrival, Brea, falls below the first threshold at a calculation point before the drone 6 arrives at the destination, the second calculation unit 11 may determine that it will be difficult to fly to another destination (e.g., delivery base 8) without recharging after arriving at the destination (e.g., delivery destination 9). In this case, the output unit 14 displays the determination result on the display device 7a. This allows the operator to arrange for charging of the drone 6's battery 60 and achieve appropriate flight to the other destination. The first threshold is, for example, the battery level that allows the drone 6 to fly the return route from delivery destination 9 to delivery base 8, with a margin added.

[0128] Furthermore, for example, the second calculation unit 11 may determine that it will be difficult for the drone 6 to reach its destination if, at a calculation point before the drone 6 arrives at the destination, the estimated battery level at arrival, Brea, falls below the second threshold. In this case, the output unit 14 requests the route setting device 1b to set an alternative route to the nearest possible landing point. Alternatively, the output unit 14 displays a request on the display device 7a to change from autonomous flight to manual control. This ensures that even if it becomes impossible for the drone 6 to reach its destination, the drone 6 can be properly flown and landed in an appropriate location. The second threshold is set to any value smaller than the first threshold.

[0129] If an alternative route is set by the route setting device 1b, the first calculation unit 10 will recalculate the battery consumption plan, similar to the modification 1 of the first embodiment described above. By generating a battery consumption plan for the remaining flight of the drone 6, it is possible to determine whether flight can continue along the alternative route.

[0130] <Modification 3 of the first embodiment> In the first embodiment described above, flight path planning information was described assuming that the drone 6 flies to the destination without replacing the battery 60. However, an arbitrary landing point may be set along the flight path of the drone 6, and the battery 60 may be replaced at the landing point. In such a case, the arbitrary landing point where the battery 60 is replaced is set as a virtual destination, and the battery consumption plan and actual battery consumption for the flight to the destination can be calculated by performing the same calculation as in the first embodiment. In this case, when the battery is replaced, the remaining battery level after replacement and the arbitrary landing point where the battery was replaced are used as initial values, and the calculation is performed again. In this way, when the drone 6 is flying and monitoring by the operator is required, the necessary information for the operator is appropriately generated, and the battery consumption plan and actual battery consumption of the drone 6 are displayed on the display screen of the display device 7a.

[0131] <Modification 4 of the First Embodiment> In the first embodiment described above, the case in which one drone 6 is managed by the energy management device 1a was explained, but multiple drones 6 may be managed. Figure 7 is a diagram showing the configuration of the energy management system 2 according to modification 4 of the first embodiment. The energy management system 2 includes a server 1, a remote control device 7, and multiple drones 6 (first drone 6a, second drone 6b, and third drone 6c). The server 1 has the functions of an energy management device 1a that manages the energy of the multiple drones 6 and a route setting device 1b that sets the flight paths of the multiple drones 6.

[0132] In this modified example, one operator controls three drones 6 by operating the control terminal 7b of the remote control device 7. Additionally, one operator monitors the three drones 6 based on information displayed on the display device 7a of the remote control device 7.

[0133] Figure 8 shows an example of an image of multiple battery level indicators 100 displayed on the display device 7a. As shown in Figure 8, the display screen of the display device 7a shows a first battery level indicator 100a corresponding to the first drone 6a, a second battery level indicator 100b corresponding to the second drone 6b, and a third battery level indicator 100c corresponding to the third drone 6c. These are displayed in a single row. Therefore, the operator can easily identify the drone 6 that requires attention.

[0134] When displaying multiple battery level indicators 100 side by side, some parts of the image shown in Figure 5 may be omitted. For example, as shown in Figure 8, texts 107, 108 and the battery level indicator 110 are omitted. Also, texts 111 and 112 are displayed above the battery level gauge frame 101. In this way, by omitting some parts of the image or changing the position of some parts of the image to above (or below) the battery level gauge frame 101, multiple battery level indicators 100 can be placed close together horizontally.

[0135] In the first battery level indicator 100a and the second battery level indicator 100b, the indicator point 109a of the label 109 is located below the upper end of the battery level gauge 104. In contrast, in the third battery level indicator 100c, the indicator point 109a of the label 109 is located above the upper end of the battery level gauge 104.

[0136] The estimated flight time of the third drone 6c (25.4 minutes) is longer than the estimated flight time of the second drone 6b (18.2 minutes). Therefore, at first glance, it might seem that attention should be paid to the second drone 6b, which has the shortest estimated flight time. However, in the example shown in Figure 8, it is more appropriate to pay attention to the third drone 6c, whose measured battery level is lower than the planned battery level.

[0137] The calculation unit 1c of the energy management device 1a in this modified example identifies the drone 6 whose current measured battery level is lower than the planned battery level, and whose difference between the planned and actual battery levels is the largest. The calculation unit 1c displays a specific image on the display screen of the display device 7a, indicating that the drone has been identified, only on the battery level indicator 100 corresponding to the identified drone 6.

[0138] In the example shown in Figure 8, the computing unit 1c identifies the third drone 6c and displays the specific image 113 on the third battery level indicator 100c. The specific image 113 is a rectangular colored image and is the background image for the text 111 and 112. With this configuration, the pilot can easily determine the single specific drone that should be the most closely monitored.

[0139] <Another example of display method> If there are multiple drones 6 whose measured battery level is lower than the planned battery level, the computing device 1c may identify all of them as the first specific drone. In this case, the computing device 1c identifies the drone 6 among the multiple first specific drones that has the largest difference between the planned battery level and the measured battery level as the second specific drone. The computing device 1c attaches a first specific image to the battery level indicator 100 of the multiple first specific drones, indicating that the measured battery level is lower than the planned battery level. The computing device 1c attaches a second specific image to the battery level indicator 100 of a single second specific drone, indicating that the difference between the planned battery level and the measured battery level is the largest. The second specific image may be a new image separate from the first specific image, or it may be an image displayed in place of the first specific image and different from the first specific image. The first specific image and the second specific image differ in at least one of their color, shape, and arrangement. With this configuration, the pilot can easily identify multiple first-specific drones that require attention, and among them, a single second-specific drone that requires the most attention.

[0140] <Another example of a different display method> The computing unit 1c may identify one or more drones 6 whose actual battery level is lower than the expected battery level of the planned battery level as first specific drones, and one or more drones 6 whose actual battery level is lower than the minimum battery level of the planned battery level as second specific drones. Thus, the second specific drones are drones 6 whose measured battery level is lower than the range of the planned battery level represented by label 109. The battery level indicator 100 of the first specific drone and the battery level indicator 100 of the second specific drone are attached with the first specific image and the second specific image, as described above. With this configuration, the operator can easily determine one or more first specific drones to pay attention to, and one or more second specific drones to pay more attention to.

[0141] When a single operator monitors multiple autonomously flying drones 6, it is difficult for the operator to continuously focus on a specific drone 6. Furthermore, it is not practical for a single operator to be aware of the flight paths of all the drones 6. According to this modified example 4, when a single operator controls and monitors multiple drones 6, it is easy to identify the drone 6 that requires attention. Therefore, the operator can make appropriate decisions, such as ending autonomous flight and taking over control of the drone 6 if necessary, or changing the destination.

[0142] <Second Embodiment> Referring to Figure 9, an energy management system 202 according to a second embodiment of the present invention will be described. Figure 9 is a diagram showing the configuration of the mobile energy management system 202 according to the second embodiment. The same reference numerals are used for configurations that are the same as or equivalent to those described in the first embodiment, and the differences will be mainly explained. In the first embodiment, the mobile body managed by the energy management device 1a was a drone 6. However, the mobile body is not limited to a drone 6. In the second embodiment, an example will be described in which the mobile body managed by the energy management device 201a is an autonomous mobile robot 206.

[0143] The autonomous mobile robot 206 may be a piloted mobile robot that carries a crew member to assist with movement, or it may be a non-piloted mobile robot that does not carry a crew member and performs tasks such as facility monitoring, security, serving food, cleaning, and lawn mowing. In the first embodiment, the route setting device 1b set the flight path planning information. In contrast, the route setting device 201b according to this second embodiment sets the travel path planning information.

[0144] In the first embodiment, various calculations were performed considering environmental information in the time direction (wind direction, wind speed, etc.) in addition to latitude, longitude, and altitude. In contrast, the mobile body according to this second embodiment moves on land. Therefore, in this second embodiment, gradient and road surface conditions are considered as environmental information in various calculations. When the mobile body's movement speed is small, the effect of wind can be considered small and ignored indoors. For this reason, in this second embodiment, environmental information in the altitude direction and time direction is omitted, and environmental information with spatial distribution of only latitude and longitude information is used. When operating the autonomous mobile robot 206 indoors, instead of latitude and longitude, each point on the travel route may be identified by coordinates of a coordinate system individually set within the facility.

[0145] As shown in Figure 9, the energy management system 202 according to this second embodiment includes a server 201 and a plurality of autonomous mobile robots 206 (first robot 206a, second robot 206b, third robot 206c) that travel within the store 221. The store 221 is a restaurant. The autonomous mobile robots 206 transport food from a kitchen (not shown) to a destination point next to a table 222. When a customer receives food from the autonomous mobile robot 206, the autonomous mobile robot 206 returns to the kitchen (not shown). The autonomous mobile robot 206 then transports food again from the kitchen to the destination point.

[0146] The server 201, multiple autonomous mobile robots 206, and multiple charging docks 223 can exchange data via communication. The server 201 manages the operation of the multiple autonomous mobile robots 206. The server 201 provides the autonomous mobile robots 206 with information necessary for autonomous driving via the in-store network 204 and wireless base station 205.

[0147] One or more wireless base stations 205 are installed within the store 221. The wireless base stations 205 communicate wirelessly with the autonomous mobile robot 206. The wireless base stations 205 are, for example, access points for a wireless LAN (Local Area Network) such as Wi-Fi (registered trademark). Note that the wireless base stations 205 are not limited to this example and may be base stations for wireless communication of other wireless communication standards.

[0148] Server 201 functions as an energy management device 201a for managing the energy of the autonomous mobile robot 206, a route setting device 201b for setting the travel path of the autonomous mobile robot 206, and a remote control device 201c for remotely controlling the autonomous mobile robot 206. Similar to the first embodiment, Server 201 is equipped with a computing device, a storage device, and an output device (input / output interface). A display device 207a, such as an LCD monitor, and an operating device 207b are connected to Server 201. The remote control device 201c, the display device 207a, and the operating device 207b constitute a remote control device 207 that can remotely operate the autonomous mobile robot 206.

[0149] Store 221 is equipped with a first charging dock 223a for charging the battery 260 of the first robot 206a, a second charging dock 223b for charging the battery 260 of the second robot 206b, and a third charging dock 223c for charging the battery 260 of the third robot 206c. Charging dock 223 serves as the base for the autonomous mobile robot 206.

[0150] The energy management device 201a, like the energy management device 1a according to the first embodiment (see Figure 2), includes an information acquisition unit 13, a first calculation unit 10, a second calculation unit 11, a storage unit 12, an output unit 14, a control unit 15, and a determination unit 16.

[0151] For example, the first calculation unit 10 calculates the battery consumption plan for one operation in which the autonomous mobile robot 206 serves food to customers in the store 221. Specifically, the first calculation unit 10 calculates the battery consumption plan for the outward journey, starting from the charging dock 223, passing through the kitchen, and passing beside the customer's table 222 as the first destination, and then returning to the charging dock 223 as the second destination. The second calculation unit 11 calculates the actual remaining battery level when the autonomous mobile robot 206 completes its delivery and arrives at the charging dock 223, the second destination. The determination unit 16 determines the degradation state of the battery 260 of the autonomous mobile robot 206 by comparing the battery consumption plan calculated by the first calculation unit 10 with the actual battery consumption calculated by the second calculation unit 11.

[0152] For example, the determination unit 16 compares the measured battery level at the time the autonomous mobile robot 206 arrives at its destination with the planned battery level (planned battery level at arrival). The smaller the measured battery level is compared to the planned battery level, the more the battery 260 is deteriorating. In this way, the energy management device 201a can understand the deterioration status of the battery 260 of the autonomous mobile robot 206.

[0153] The output unit 14 displays the determination result of the determination unit 16 on the display screen of the display device 207a. This allows the operator to check the degradation status of the battery 260 of the autonomous mobile robot 206. Since the operator is notified that the battery 260 is degrading, the operator can replace the battery 260 of the autonomous mobile robot 206 at the appropriate time.

[0154] <Third Embodiment> Referring to Figure 10, the energy management system 302 according to the third embodiment of the present invention will be described. Figure 10 is a diagram showing the configuration of the mobile energy management system 302 according to the third embodiment. The same reference numerals are used for configurations that are the same as or equivalent to those described in the first embodiment, and the differences will be mainly described. In the first and second embodiments, the objects managed by the energy management devices 1a and 201a were autonomously moving mobile objects. However, the mobile object does not have to be configured to move autonomously. In the third embodiment, the mobile object managed by the energy management device 301a is an electric motorcycle 306 that is ridden and operated by an operator.

[0155] As shown in Figure 10, the energy management system 302 according to this third embodiment includes a server 301, an electric motorcycle 306, and a portable terminal 331 carried by the operator. The server 301, like the first embodiment, is equipped with a computing device, a storage device, and an output device (input / output interface). The portable terminal 331 functions as a navigation device 331a. The portable terminal 331 is, for example, a smartphone or a tablet. The operator operates the portable terminal 331 to set the starting point, destination, and waypoints. The navigation device 331a transmits information such as the starting point, destination, and waypoints to the route setting device 301b of the server 301. The route setting device 301b sets a guided route based on the starting point, destination, and waypoints provided by the navigation device 331a. The information acquisition unit 13 acquires the planned guided route information set by the route setting device 301b. The first calculation unit 10 calculates a battery consumption plan based on the planned route information and the vehicle information of the electric motorcycle 306. The vehicle information of the electric motorcycle 306 is stored in the storage unit 12 in advance.

[0156] The mobile terminal 331, server 301, charging station 337, and map server 338 can exchange data with each other via the network 4 and wireless base station 5. Server 301 functions as an energy management device 301a that manages the energy of the electric motorcycle 306. Server 301 may also function as a device that provides services to the operator of the electric motorcycle 306, such as payment processing when charging the battery 360 of the electric motorcycle 306 using the charging station 337.

[0157] Server 301 obtains the latest map information from map server 338. Server 301 stores the latest map information obtained from map server 338. Route setting device 301b sets a route for the electric motorcycle 306 to reach the desired destination. Route setting device 301b determines whether the electric motorcycle 306 needs to stop at charging station 337 to charge along the route. If it is determined that charging is necessary, server 301 sets charging station 337 as a waypoint on the route.

[0158] The energy management device 301a, like the energy management device 1a according to the first embodiment (see Figure 2), includes an information acquisition unit 13, a first calculation unit 10, a second calculation unit 11, a storage unit 12, an output unit 14, a control unit 15, and a determination unit 16.

[0159] For example, the first calculation unit 10 calculates the battery consumption plan for the electric motorcycle 306 based on the planned route information and the vehicle information of the electric motorcycle 306. The output unit 14 provides the battery consumption plan to the mobile terminal 331. As a result, the operator of the electric motorcycle 306 can recognize the battery consumption plan through an image displayed on the display screen of the mobile terminal 331.

[0160] The second calculation unit 11 calculates the actual battery level based on energy usage information (voltage and current information). The second calculation unit 11 also calculates an estimated battery level at the destination or the location of the charging station 337. Based on the calculation results of the second calculation unit 11, the determination unit 16 determines the risk of running out of power due to the electric motorcycle 306's battery 360 being depleted, and the risk of the stay period (charging time) at the charging station 337 being prolonged. The output unit 14 transmits the determination result of the determination unit 16 to the mobile terminal 331. The mobile terminal 331 displays the determination result of the determination unit 16 on its display screen. This allows the operator to recognize the risk of running out of power, the risk of prolonged charging time, etc.

[0161] The output unit 14 may generate driving advisory information for the operator of the electric motorcycle 306 and provide the generated driving advisory information to the mobile terminal 331. The operator's driving operations of the electric motorcycle 306 vary in acceleration and deceleration compared to the autonomously moving mobile body described in the first and second embodiments. For this reason, the range that the electric motorcycle 306 can travel tends to fluctuate depending on the driving operations.

[0162] For example, if exceeding the speed limit may extend the charging time, voice guidance and warning images prompting a reduction in speed are provided to the mobile terminal 331 as driving advisory information. The warning image is, for example, an image representing a recommended speed. Voice guidance is provided by the mobile terminal 331, or warning images are displayed on the mobile terminal 331's screen, enabling the operator of the electric motorcycle 306 to take appropriate actions, such as reducing the speed.

[0163] In this third embodiment, as in the first embodiment, various data from the battery level indicator 100 are provided from the energy management device 301a to the mobile terminal 331, and the battery level indicator 100 is displayed on the display screen of the mobile terminal 331, which acts as a display device. With this configuration, the operator can effectively grasp the future activity time of the electric motorcycle 306 as it travels according to the planned route information. In addition, the energy management device 301a provides driving advisory information to the mobile terminal 331. This improves the operation of the electric motorcycle 306. Furthermore, the operator of the electric motorcycle 306 can reduce the psychological burden of the risk of running out of power. Moreover, the time spent at the charging station 337 can be shortened.

[0164] The energy management device of the present invention has been described above with examples of several embodiments. However, the present invention is not limited to the embodiments described above. The following modifications are also within the scope of the present invention, and it is possible to combine the configurations shown in the modifications with the configurations described in the embodiments described above, or to combine the configurations described in the different embodiments described above, or to combine the configurations described in the following different modifications.

[0165] <Example 1> The mobile body may also have the functions of the energy management device described in the above embodiment. Figure 11 is a diagram showing the configuration of a mobile body according to Modification 1. The mobile body according to Modification 1 is an electric motorcycle 406 that is ridden and operated by an operator. The electric motorcycle 406 has a controller 401 and a display device 407. The controller 401 is composed of a computer equipped with a processing unit, storage device, output device (input / output interface), etc., similar to the server 301. The controller 401 has the function of a display control device 401b that controls the energy management device 401a and the display device 407 that manage the energy of the electric motorcycle 406.

[0166] The modified electric motorcycle 406 (mobile unit) includes an energy management device 401a and a display device 407 that displays the calculation results of the calculation unit 1c of the energy management device 401a. With this configuration, similar to the above embodiment, the operator can effectively grasp the future activity time of the electric motorcycle 406 as it travels according to the planned information of the guided route.

[0167] The display controller of the display device 407 may also be equipped with the functions of the energy management device 401a. The display device 407 displays on its screen the following: a first energy remaining amount, which is the amount of energy the electric motorcycle 406 (mobile body) has when it arrives at any point on the travel route and at the destination point of the travel route; an actual energy remaining amount, which is the amount of energy the electric motorcycle 406 (mobile body) has; and a second energy remaining amount, which is the amount of energy the electric motorcycle 406 (mobile body) has when it arrives at the destination point after moving from its current position to the destination point.

[0168] <Modification 2> In the above embodiment, an example was described in which a mobile body equipped with a battery that converts chemical energy into electrical energy and a motor that converts the electrical energy of the battery into mechanical energy (kinetic energy) is the target of the energy management device. However, the configuration of the mobile body is not limited to this. The target of management may be, for example, a mobile body having an internal combustion engine that converts chemical energy into thermal energy by combustion and thermal energy into mechanical energy. This mobile body is equipped with an internal combustion engine such as an engine, a fuel tank that holds fuel, and a mobile mechanism that operates using power generated by burning fuel in the internal combustion engine. For example, in the third embodiment, a motorcycle equipped with a gasoline engine may be used as the mobile body instead of the electric motorcycle 306.

[0169] In this modified example, the information acquisition unit 13 acquires information on the remaining amount of fuel in the fuel tank as usage information related to the energy use of the mobile body. The first calculation unit 10 calculates the fuel remaining amount (energy amount) that the mobile body will have when it arrives at any point on the travel route and at the destination point, based on the travel route planning information and the mobile body information, as the fuel remaining amount planning value (first energy remaining amount). The second calculation unit 11 calculates the fuel remaining amount (energy amount) that the mobile body currently has, based on the fuel remaining amount information, as the fuel remaining amount measured value (actual energy remaining amount). Furthermore, the second calculation unit 11 calculates the fuel remaining amount (energy amount) that the mobile body will have when it arrives at the destination point, based on the travel route planning information, the current position information of the mobile body, and the fuel remaining amount measured value, based on the travel route planning information, the current position information of the mobile body, and the fuel remaining amount measured value, as the fuel remaining amount estimated value at arrival (second energy remaining amount), assuming the mobile body moves from its current position to the destination point. The output unit 14 (input / output interface) outputs the actual fuel level, the planned fuel level at any point including the destination (first energy level), and the estimated fuel level upon arrival (second energy level) to the display device and displays them on the display device.

[0170] With this configuration, similar to the above embodiment, it is possible to effectively determine the future activity time of a moving object that moves according to the planned information of its movement path.

[0171] <Variation 3> The display method of the remaining energy amount shown on the display screen is not limited to the examples described above. For example, in the example shown in Figure 5, the arrival energy plan gauge 106 and the arrival energy forecast gauge 105 were arranged side by side, but they may also be displayed by overlapping part or all of them and changing their colors.

[0172] The embodiments and their modifications described above are explained in detail for the purpose of clearly illustrating the present invention. Therefore, the present invention is not limited to having all the configurations described. It is possible to replace parts of the configuration of one embodiment with the configuration of another embodiment. It is also possible to add configurations from other embodiments to the configuration of one embodiment. It is possible to add, delete, replace, or omit parts of the configuration of each embodiment. The control lines and information lines shown are those deemed necessary for explanation and do not necessarily represent all control lines and information lines on the product. In practice, it can be assumed that almost all configurations are interconnected, and this does not mean that the intended configuration of the present invention is lost. [Explanation of Symbols]

[0173] 1...Server, 1a...Energy management device, 1b...Route setting device, 1c...Calculation unit, 1d...Storage device, 1e...Input / output interface (output device), 2...Energy management system, 3...Information provision device, 3a...Communication device (output device), 3b...Input device, 4...Network, 5...Wireless base station, 6...Drone (mobile device), 7...Remote control device, 7a...Display device, 7b...Operation terminal, 8...Delivery base, 9...Delivery destination, 10...First calculation unit, 11...Second calculation unit, 12...Storage unit, 13...Information acquisition unit, 14...Output unit, 15...Control unit, 16...Determination unit, 50...Flight path ( (Travel route), 51…Environmental information, 52…Calculation point, 53…Airspace, 56…Surrogate model, 57…Air conditioning power model, 60…Battery, 61…Electric motor, 62…Blade rotor, 63…Control device, 69…Materials, 100…Battery level indicator, 101…Battery level gauge frame, 102…Battery consumption plan indicator, 103…Battery consumption actual indicator, 104…Battery level gauge, 105…Expected remaining charge gauge at arrival, 106…Planned remaining charge gauge at arrival, 107,108…Text, 109…Label, 109a…Indication point, 110…Battery level Quantity indicator, 111, 112... text, 113... specific image, 201... server, 201a... energy management device, 201b... routing device, 201c... remote control device, 202... energy management system, 204... in-store network, 205... wireless base station, 206... autonomous mobile robot (mobile body), 207... remote control device, 207a... display device, 207b... operating device, 221... store, 222... table, 223... charging dock, 260... battery, 301... server, 301a... energy management device, 301b... routing device, 302... energy Energy management system, 306...Electric motorcycle (mobile unit), 331...Mobile terminal (display device), 331a...Navigation device, 337...Charging station, 338...Map server, 360...Battery, 401...Controller, 401a...Energy management device, 401b...Display control device, 406...Electric motorcycle (mobile unit), 407...Display device, Brac...Measured battery level, Brea...Estimated battery level at arrival, Brpc...Planned battery level at calculation point, Brpa...Planned battery level at arrival, P...Total power consumption, Pa...Actual power consumption, P AC...Power consumption of air conditioning equipment, Pav...Average power consumption, Pavp...Planned power consumption, Pp...Predicted power consumption, ta...Scheduled arrival time, td...Scheduled departure time, tf...Scheduled flight time, tp...Planned flight time, W...Total power consumption, Wc...Corrected power consumption (total power consumption), We...Estimated power consumption, Wr...Reference value for power consumption, Wrac...Remaining power consumption at calculation point, Wrd...Remaining power consumption at departure point, Wrea...Estimated remaining power consumption at arrival, Wrpa...Planned remaining power consumption at arrival, WP1~WP9...Waypoints

Claims

1. An energy management device comprising a computing device and an output device, The aforementioned computing device is The system acquires planning information for the movement path of the moving object to the destination, information about the moving object, the current position information of the moving object, and usage information regarding the energy usage of the moving object. Based on the planning information and the moving body information, the amount of energy the moving body possesses when it arrives at any point on the travel path and at the destination point is calculated as the first remaining energy amount. Based on the usage information, the amount of energy held by the moving body is calculated as the actual remaining energy. Based on the aforementioned planning information, the current location information, and the actual remaining energy, when the moving body moves from its current location to the destination point, the amount of energy the moving body possesses when it arrives at the destination point is calculated as the second remaining energy. The output device outputs the actual remaining energy, the first remaining energy, and the second remaining energy. Energy management device.

2. In the energy management device according to claim 1, The aforementioned computing device is Obtain environmental information about the surrounding area of ​​the aforementioned travel path, The first remaining energy and the second remaining energy are calculated taking into account the aforementioned environmental information. Energy management device.

3. In the energy management device according to claim 1, The calculation device outputs a signal via the output device to a display device for displaying the actual remaining energy currently held by the moving body and the first remaining energy at any point corresponding to the current position of the moving body in a display manner that allows for comparison. Energy management device.

4. In the energy management device according to claim 3, The calculation device outputs a signal via the output device to the display device for displaying the first remaining energy and the second remaining energy at the time the moving body arrives at the destination point in a display manner that allows for comparison. Energy management device.

5. In the energy management device according to claim 3, The calculation device outputs a signal via the output device to the display device for displaying the actual remaining energy amount calculated when the moving body passes through each of the plurality of waypoints on the movement path in a display manner that allows comparison with the first remaining energy amount at the waypoint. Energy management device.

6. In the energy management device according to claim 1, The calculation device outputs a signal via the output device to a display device for displaying the actual remaining energy, the first remaining energy, and the second remaining energy in a comparable display manner. In the above-described representation, the actual remaining energy, the first remaining energy, and the second remaining energy are represented by the length of an image of a predetermined shape, the size of the area of ​​an image of a predetermined shape, and the position of an image of a predetermined shape. Energy management device.

7. In the energy management device according to claim 1, The amount of energy held by the mobile body is the amount of power in the mobile body's battery. Energy management device.

8. The energy management device according to claim 1, The aforementioned moving body, An energy management system equipped with [specific features / features].

9. The energy management device according to claim 1, A display device for displaying the calculation results of the calculation device of the energy management device, A mobile device equipped with [something].

10. A display device that displays a first energy remaining amount, which is the amount of energy the moving body possesses when it arrives at any point on the movement path and the destination point on the movement path; an actual energy remaining amount, which is the amount of energy the moving body possesses; and a second energy remaining amount, which is the amount of energy the moving body possesses when it arrives at the destination point after moving from its current position to the destination point.

Images