In-vehicle device, energy consumption prediction system, energy consumption prediction method, and energy consumption prediction program

Abstract

Accurately predict energy consumption. [Solution] The in-vehicle device 9 predicts the energy consumed by the vehicle while it is moving as the vehicle's energy consumption. The in-vehicle device includes a traffic information acquisition unit 12d that acquires traffic information indicating the degree of traffic disruption, a driver characteristics acquisition unit 12e that acquires standard driver characteristics indicating the driving characteristics of a typical driver and individual driver characteristics indicating the driving characteristics of an individual driver, and an energy consumption prediction unit 12h that predicts the vehicle's energy consumption by combining the traffic information, the standard driver characteristics and the individual driver characteristics.

Description

Technical Field

[0001] The present invention relates to an in-vehicle device, a system for predicting energy consumption, a method for predicting energy consumption, and a program for predicting energy consumption.

Background Art

[0002] In order to predict the cruising range of a vehicle, it is necessary to accurately predict the energy consumed by the vehicle while it is moving. If the energy consumed by the vehicle while it is moving can be accurately predicted, for example, the cruising range of the vehicle can be predicted from the relationship with the remaining battery level at a reference point such as the departure point or the current position. In an electric vehicle, the main factors of energy consumption are driving and air conditioning. If the vehicle speed on the driving route, the set temperature of the air conditioning, the air temperature, the required time, etc. can be predicted, the energy consumption can be predicted. For example, Patent Document 1 discloses a technique for predicting the vehicle speed based on route information such as the gradient of the driving route, traffic jam information, construction information, accident information, weather information, and traffic obstacle information indicating the degree of traffic obstacles such as the presence or absence of intersections and signals, and predicting the energy consumption.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, the technology disclosed in Patent Document 1 merely predicts energy consumption based on traffic congestion information and does not adequately consider the driver's driving characteristics. As a result, when the road is relatively empty and the degree of traffic congestion is relatively low, there is a problem in that the individual driver's speed tendency becomes dominant. On the other hand, when the road is relatively congested and the degree of traffic congestion is relatively high, there is a problem in that the individual driver's speed tendency does not come into play. In other words, the individual driver's speed tendency cannot be reflected in the prediction of energy consumption, resulting in a decrease in the accuracy of the energy consumption prediction.

[0005] The present invention has been made in view of the above circumstances, and its purpose is to provide an in-vehicle device, an energy consumption prediction system, an energy consumption prediction method, and an energy consumption prediction program that can appropriately predict energy consumption. [Means for solving the problem]

[0006] The in-vehicle device (9) described in claim 1 predicts the energy consumed by the vehicle while it is moving as the vehicle's energy consumption. The in-vehicle device includes a traffic information acquisition unit (12d) that acquires traffic information indicating the degree of traffic disruption, a driver characteristics acquisition unit (12e) that acquires standard driver characteristics indicating the driving characteristics of a typical driver and individual driver characteristics indicating the driving characteristics of an individual driver, and an energy consumption prediction unit (12h) that predicts the vehicle's energy consumption by combining the traffic information, the standard driver characteristics and the individual driver characteristics.

[0007] The energy consumption prediction system described in claim 7 comprises an in-vehicle device (9) and an external device (4) capable of data communication with the in-vehicle device, and predicts the energy consumed by the vehicle while it is moving as the vehicle's energy consumption. The energy consumption prediction system comprises a traffic disruption information acquisition unit (12d) that acquires traffic disruption information indicating the degree of traffic disruption, a driver characteristic acquisition unit (12e) that acquires standard driver characteristics indicating the driving characteristics of a typical driver and individual driver characteristics indicating the driving characteristics of an individual driver, and an energy consumption prediction unit (12h) that predicts the vehicle's energy consumption by combining the traffic disruption information, the standard driver characteristics and the individual driver characteristics.

[0008] The energy consumption prediction method described in claim 13 comprises an in-vehicle device (9) and an external device (4) capable of data communication with the in-vehicle device, and is a method for predicting the energy consumed by a vehicle while it is in motion as the energy consumption of the vehicle, comprising: a traffic disruption information acquisition procedure for acquiring traffic disruption information indicating the degree of traffic disruption; a driver characteristics acquisition procedure for acquiring standard driver characteristics indicating the driving characteristics of a typical driver and individual driver characteristics indicating the driving characteristics of an individual driver; and an energy consumption prediction procedure for predicting the energy consumption of the vehicle by combining the traffic disruption information, the standard driver characteristics and the individual driver characteristics.

[0009] The energy consumption prediction program described in claim 14 causes the control unit (12) of an in-vehicle device (9) that predicts the energy consumed by the vehicle while it is moving as the vehicle's energy consumption to execute a traffic disruption information acquisition procedure for acquiring traffic disruption information indicating the degree of traffic disruption; a driver characteristics acquisition procedure for acquiring standard driver characteristics indicating the driving characteristics of a typical driver and individual driver characteristics indicating the driving characteristics of an individual driver; and an energy consumption prediction procedure for predicting the vehicle's energy consumption by combining the traffic disruption information, the standard driver characteristics, and the individual driver characteristics.

[0010] According to the above configuration, vehicle energy consumption is predicted by combining traffic information indicating the degree of traffic disruption, standard driver characteristics indicating the driving characteristics of a typical driver, and individual driver characteristics indicating the driving characteristics of an individual driver. When the degree of traffic disruption is relatively low, the weight of individual driver characteristics is relatively increased compared to standard driver characteristics, and energy consumption is predicted mainly using individual driver characteristics, thereby incorporating the individual driver's vehicle speed tendency into the energy consumption prediction. On the other hand, when the degree of traffic disruption is relatively high, the weight of standard driver characteristics is relatively increased compared to individual driver characteristics, and energy consumption is predicted mainly using standard driver characteristics, thereby avoiding excessive reflection of the individual driver's vehicle speed tendency in the energy consumption prediction. This allows for appropriate reflection of the individual driver's vehicle speed tendency in the energy consumption prediction, enabling accurate energy consumption prediction. [Brief explanation of the drawing]

[0011] [Figure 1] A diagram showing the overall configuration of one embodiment. [Figure 2] Functional block diagram showing the configuration of the vehicle system [Figure 3] Functional block diagram showing the configuration of the first domain controller. [Figure 4] Diagram showing links [Figure 5] Diagram showing the formula for calculating energy consumption. [Figure 6] Functional block diagram showing the server configuration [Figure 7] A flowchart illustrating the link ID determination process performed by the first domain controller. [Figure 8] A flowchart illustrating the energy consumption prediction process performed by the first domain controller. [Figure 9] A flowchart illustrating the standard driver characteristics calculation process performed by the server. [Figure 10] A flowchart illustrating the process of calculating individual driver characteristics performed by the server. [Figure 11] A flowchart illustrating the information distribution decision process performed by the server. [Modes for carrying out the invention]

[0012] An embodiment will be described below with reference to the drawings. As shown in Figure 1, the energy consumption prediction system 1 is configured so that a vehicle system 3, which is installed in an unspecified number of vehicles 2, and a server 4 (corresponding to an external device) can communicate data via a communication network 5 including the internet. The vehicle 2 is, for example, an electric vehicle (EV) that runs using electrical energy stored in a battery as a power source.

[0013] Server 4 can communicate data with traffic information distribution server 6, which distributes traffic information, via communication network 5. Traffic information is distributed from traffic information distribution server 6 to server 4 via communication network 5, stored in server 4, and then distributed from server 4 to vehicle system 3 via communication network 5. Traffic information is information that indicates the degree of traffic disruption on a link-by-link basis, and includes information such as route information such as the gradient of the driving route, congestion information, construction information, accident information, and information such as the presence or absence of intersections and traffic lights. For example, if there is no congestion or accident, or if the weather is sunny, there are relatively few factors that could cause traffic disruption, and the degree of traffic disruption will be relatively low. On the other hand, if there is congestion or an accident, or if there is rain or snow, there are relatively many factors that could cause traffic disruption, and the degree of traffic disruption will be relatively high. Traffic information is information that affects the energy consumption of vehicle 2.

[0014] For example, a mobile information terminal 7 such as a smartphone can perform data communication with a vehicle system 3 via a communication network 5. By launching an application that displays a predicted value of energy consumption, the mobile information terminal 7 acquires, from the vehicle system 3 via the communication network 5, the predicted value of energy consumption predicted in the vehicle system 3 as described later and displays it. If the mobile information terminal 7 can perform short-range wireless connection with the vehicle system 3, for example, it may acquire and display the predicted value of energy consumption from the vehicle system 3 without going through the communication network 5 by performing short-range wireless connection with the vehicle system 3.

[0015] The vehicle system 3 transmits vehicle information to the server 4, for example, every time the vehicle 2 exits a link. The vehicle information transmitted from the vehicle system 3 includes vehicle type, model, grade, a vehicle ID capable of specifying the vehicle 2, vehicle speed within the link, and the like. Also, the vehicle system 3 transmits a request signal to the server 4, for example, every time the vehicle 2 exits a link, thereby acquiring traffic obstacle information distributed from the server 4 and standard driver characteristics and individual driver characteristics calculated in the server 4. The request signal transmitted from the vehicle system 3 includes vehicle type, model, grade, a vehicle ID capable of specifying the vehicle 2, and the like.

[0016] The configuration of the vehicle system 3 will be described. As shown in FIG. 2, the vehicle system 3 is connected such that a communication terminal 8, a first domain controller 9 (corresponding to an in-vehicle device), and a second domain controller 10 (corresponding to a driving control device) can perform data communication via a communication bus 11. The communication bus 11 is, for example, a CAN (Controller Area Network) bus.

[0017] The communication terminal 8 controls the connection of the communication line with the communication network 5, and controls the data communication via the communication network 5 with the server 4, the traffic accident information distribution server 6, and the mobile information terminal 7 described above. The first domain controller 9 includes a functional block that controls the navigation function and a functional block that controls the prediction of the energy consumption of the vehicle 2. The second domain controller 10 includes a functional block that controls the running of the vehicle 2. In the present embodiment, an example is shown in which the functional block that controls the navigation function and the functional block that controls the prediction of the energy consumption of the vehicle 2 are aggregated in one domain controller, but a configuration in which they are arranged in separate domain controllers may also be used. Also, in the present embodiment, an example is shown in which the functional block that controls the prediction of the energy consumption of the vehicle 2 and the functional block that controls the running of the vehicle 2 are arranged in separate domain controllers, but a configuration in which they are aggregated in one domain controller may also be used.

[0018] As shown in FIG. 3, the first domain controller 9 includes a first control unit 12, a GNSS (Global Navigation Satellite System) reception unit 13, a vibration gyro 14, a vehicle speed sensor 15, a hard disk drive (HDD) 16, a display monitor 17, a speaker 18, and an input device 19. The first control unit 12 is mainly composed of a microcomputer having a CPU, a ROM, a RAM, an I / O, etc., and executes control by software processing in which a computer program stored in a non-transitory physical storage medium is executed by the CPU and hardware processing by a dedicated electronic circuit, and controls the operation of the first domain controller 9.

[0019] When the GNSS reception unit 13 receives a GNSS signal transmitted from a GNSS satellite orbiting the sky, it outputs various information included in the received GNSS signal to the first control unit 12. The various information output from the GNSS reception unit 13 to the first control unit 12 is information necessary for calculating the current position of the vehicle 2, and includes information on the position of the GNSS satellite that transmitted the GNSS signal, the transmission time, and the like.

[0020] The vibration gyro 14 is a sensor that detects the angular velocity of the vehicle 2, and when it detects the angular velocity of the vehicle 2, it outputs the detection result to the first control unit 12. The vehicle speed sensor 15 is a sensor that detects the driving speed of the vehicle 2, and when it detects the driving speed of the vehicle 2, it outputs the detection result to the first control unit 12. The first control unit 12 calculates the current position of the vehicle 2 based on various information input from the GNSS receiver 13, the detection result of the angular velocity of the vehicle 2 input from the vibration gyro 14, and the detection result of the driving speed of the vehicle 2 input from the vehicle speed sensor 15.

[0021] The HDD 16 is a non-volatile recording medium on which various data, such as control programs and map data, are stored for execution of various processes in the first control unit 12. The control programs and various data stored on the HDD 16 are read out as needed by the control of the first control unit 12 and used for various processes and controls executed by the first control unit 12.

[0022] The map data recorded on HDD16 includes route calculation data, road data, and background data. Route calculation data is used, for example, when searching for a recommended route from the current location to a destination. Road data is data that shows road shape, road type, etc. Background data is data that shows the background of the map. The background of the map refers to various elements other than roads that exist on the map, such as rivers, railways, green belts, and various structures. In the above configuration, the example shows the case where the map data is recorded on HDD16, but the map data may also be recorded on a recording medium other than HDD16, for example, on a CD-ROM, DVD-ROM, memory card, etc.

[0023] As shown in Figure 4, the smallest unit of each road in map data is called a link, and each link is assigned a unique link ID. Each road is composed of multiple links corresponding to a predetermined road section, and route calculation data and road data are represented at the link level. The points connecting links, i.e., the endpoints of each link, are called nodes, and each node is assigned a unique node ID. In Figure 4, for example, link L1 is defined as the link between nodes N1 and N3. The information of each node in the map data includes coordinate information as location information. In addition, points called shape interpolation points may be set between nodes within a link as needed. The information of each shape interpolation point in the map data includes coordinate information as location information, similar to nodes. The shape of each link is determined as the road shape based on the location information of the nodes and shape interpolation points.

[0024] The route calculation data includes a link cost for each link corresponding to each road section, based on the estimated travel time for vehicle 2 to travel that section. Based on the link costs, a combination of links is calculated according to pre-set route search conditions, and a recommended route is searched. For example, if the route search condition prioritizes the shortest travel time, the combination of links that minimizes the travel time from the starting point to the destination is calculated as the recommended route.

[0025] The display monitor 17 is positioned in a location easily visible to the user, such as on the dashboard or within the instrument panel of the vehicle 2, and consists of an LCD display or the like. When a display command is input to the display monitor 17 from the first control unit 12, it displays various screens, such as a map screen or a route guidance screen, based on the input display command. When an audio output command is input to the speaker 18 from the first control unit 12, it outputs various sounds, such as warning sounds or route guidance voices, based on the input audio output command.

[0026] The input device 19 is a device for the user to perform various input operations related to the navigation function, and consists of a touch panel or remote control integrated with the display monitor 17, and has various input switches. By operating the input device 19, the user can, for example, input the name of a facility or location to be set as a destination, set search conditions for recommended routes, select a destination from pre-registered locations, or scroll the map in any direction.

[0027] When the user operates the input device 19 to set the destination and route search conditions, the first control unit 12 uses the vehicle 2's current position as the starting point and performs a route search based on route calculation data using a predetermined algorithm to find a recommended route from the starting point to the destination. Once the first control unit 12 has found a recommended route, it displays the recommended route on the map displayed on the display monitor 17 in a way that makes it distinguishable from other roads, for example by changing the color. The first control unit 12 guides the vehicle 2 to the destination by displaying various screens on the display monitor 17 and outputting various sounds from the speaker 18 according to the recommended route.

[0028] The first control unit 12 includes a link information acquisition unit 12a, a vehicle information transmission unit 12b, a request signal transmission unit 12c, a traffic disruption information acquisition unit 12d, a driver characteristics acquisition unit 12e, a specific gravity coefficient calculation unit 12f, a vehicle speed calculation unit 12g, and an energy consumption prediction unit 12h. Parts of each of these units 12a to 12g execute procedures in the energy consumption prediction method and energy consumption prediction program.

[0029] The link information acquisition unit 12a acquires link information indicating links included in the map information described above and determines whether or not vehicle 2 has traveled across a link. The link information acquisition unit 12a acquires the link ID of vehicle 2's current position and compares the current link ID with the previous link ID to determine whether or not vehicle 2 has traveled across a link. If the link information acquisition unit 12a determines that the current link ID and the previous link ID match, it determines that vehicle 2's travel position does not cross a link. If the link information acquisition unit 12a determines that the current link ID and the previous link ID do not match, it determines that vehicle 2's travel position crossed a link and determines that vehicle 2 has traveled across a link.

[0030] When the link information acquisition unit 12a determines that vehicle 2 has traveled across a link, the vehicle information transmission unit 12b causes vehicle information to be transmitted from the communication terminal 8 to the server 4. When the link information acquisition unit 12a determines that vehicle 2 has traveled across a link, the request signal transmission unit 12c causes a request signal to be transmitted from the communication terminal 8 to the server 4.

[0031] The traffic disruption information acquisition unit 12d acquires traffic disruption information from the server 4 when the traffic disruption information distributed from the server 4 is received by the communication terminal 8. The driver characteristics acquisition unit 12e acquires standard driver characteristics and individual driver characteristics from the server 4 when the standard driver characteristics and individual driver characteristics distributed from the server 4 are received by the communication terminal 8.

[0032] When the specific gravity coefficient calculation unit 12f receives traffic disruption information from the traffic disruption information acquisition unit 12d, it calculates the specific gravity coefficient in a range from "0" to "1" based on the acquired traffic disruption information. The specific gravity coefficient calculation unit 12f calculates the specific gravity coefficient to a value close to "0" when, for example, there is no traffic congestion or accident, or the weather is sunny, and there are relatively few factors that could cause traffic disruption, resulting in a relatively low degree of traffic disruption. On the other hand, the specific gravity coefficient calculation unit 12f calculates the specific gravity coefficient to a value close to "1" when, for example, there is traffic congestion or an accident, or there is rainfall or snowfall, and there are relatively many factors that could cause traffic disruption, resulting in a relatively high degree of traffic disruption. The specific gravity coefficient calculation unit 12f may calculate the specific gravity coefficient in steps within the range from "0" to "1", or it may calculate it continuously by linear interpolation. Furthermore, the specific gravity coefficient calculation unit 12f may calculate the specific gravity coefficient using a map that shows the relationship between the degree of traffic disruption and the specific gravity coefficient.

[0033] The vehicle speed calculation unit 12g calculates the vehicle speed once the specific gravity coefficient is calculated by the specific gravity coefficient calculation unit 12f. As shown in Figure 5, the vehicle speed calculation unit 12g calculates the vehicle speed using the vehicle speed prediction formula, the vehicle speed calculation formula based on standard driver characteristics, and the vehicle speed calculation formula based on individual driver characteristics. In this case, if the degree of traffic disruption is relatively low, the specific gravity coefficient will be close to "0", so the specific gravity of the vehicle speed based on individual driver characteristics will be relatively higher. That is, individual driver characteristics will be reflected in the vehicle speed relatively more than standard driver characteristics. On the other hand, if the degree of traffic disruption is relatively high, the specific gravity coefficient will be close to "1", so the specific gravity of the vehicle speed based on standard driver characteristics will be relatively higher. That is, standard driver characteristics will be reflected in the vehicle speed relatively more than individual driver characteristics.

[0034] When the vehicle speed is calculated by the vehicle speed calculation unit 12g, the energy consumption prediction unit 12h predicts the time required to travel the target link based on the calculated vehicle speed. Based on the predicted time required, the energy consumption prediction unit 12h predicts the energy consumption for traveling the target link and the energy consumption for air conditioning, and predicts the sum of these energy consumption amounts as the total energy consumption. The energy consumption prediction unit 12h may obtain at least a portion of the power data used for predicting energy consumption from the second domain controller 10. The first control unit 12 displays the predicted energy consumption result predicted by the energy consumption prediction unit 12h, for example, on the navigation screen.

[0035] The first control unit 12 transmits the predicted energy consumption result, which has been predicted by the energy consumption prediction unit 12h, to the second domain controller 10, and reflects the predicted energy consumption result in the driving control of the vehicle 2. For example, if the first control unit 12 determines that the battery level will drop to a threshold while the vehicle 2 is driving, it performs control such as switching the driving mode from normal mode to a suppression mode that reduces energy consumption.

[0036] The second domain controller 10 includes a second control unit 20. The second control unit 20 is mainly composed of a microcontroller having a CPU, ROM, RAM, and I / O, and controls the operation of the second domain controller 10 by performing software processing by executing computer programs stored in a non-transitional physical storage medium using the CPU, and by performing hardware processing control using dedicated electronic circuits.

[0037] The second domain controller 10 is connected to the battery 22 and the electric motor 23 via the power converter 21. The second domain controller 10 manages various power data used in the calculation of statistical quantities in the first domain controller 9 and transmits these power data to the first domain controller 9. That is, in the first domain controller 9, the statistical quantity calculation unit 12b receives the various power data transmitted from the second domain controller 10 and calculates data on the vehicle 2's operation as statistical quantities by, for example, performing calculations on the acquired power data.

[0038] The battery 22 supplies power to drive the electric motor 23. The vehicle 2 moves when the electric motor 23 is driven using the power supplied from the battery 22. When the vehicle 2 decelerates, the electric motor 23 acts as a generator, generating power through regenerative braking. The power generated by regenerative braking is stored in the battery 22. The power converter 21 converts the power exchanged between the battery 22 and the electric motor 23 into a mutually usable format. For example, it converts the DC power supplied from the battery 22 into AC power and outputs it to the electric motor 23, and also converts the AC power generated by regenerative braking in the electric motor 23 into DC power and outputs it to the battery 22.

[0039] The second control unit 20 monitors the running state of the vehicle 2, the state of the battery 22, the state of the electric motor 23, etc., and controls the operation of the power converter 21 based on the monitoring results, causing power to be exchanged between the battery 22 and the electric motor 23 according to the running state of the vehicle 2. In other words, the second control unit 20 consumes the electrical energy stored in the battery 22 to generate kinetic energy for the vehicle 2 to run using the electric motor 23, or recovers at least a portion of the vehicle 2's kinetic energy using the electric motor 23 and stores the electrical energy in the battery 22 as reusable regenerative energy.

[0040] Next, the configuration of server 4 will be described. As shown in Figure 6, server 4 comprises a control unit 24 and a communication unit 25. The communication unit 25 controls data communication via the communication network 5 between server 4, traffic disruption information distribution server 6, and congestion information distribution server 7. The control unit 24 is mainly composed of a microcontroller having a CPU, ROM, RAM, and I / O, and controls the operation of server 4 by performing software processing by executing computer programs stored in a non-transitional physical storage medium on the CPU, and by performing hardware processing control using dedicated electronic circuits.

[0041] The control unit 24 includes a traffic information acquisition unit 24a, a traffic information storage unit 24b, a vehicle information acquisition unit 24c, a vehicle information storage unit 24d, a driver characteristic calculation unit 24e, a driver characteristic storage unit 24f, a request signal acquisition unit 24g, a traffic information distribution unit 24h, and a driver characteristic distribution unit 24i.

[0042] The traffic disruption information acquisition unit 24a acquires traffic disruption information from the traffic disruption information distribution server 6 when the traffic disruption information distributed from the server is received by the communication unit 25. When the traffic disruption information is acquired by the traffic disruption information acquisition unit 24a, the traffic disruption information storage unit 24b stores the acquired traffic disruption information in a predetermined storage area.

[0043] The vehicle information acquisition unit 24c acquires vehicle information from the vehicle systems 3 when the vehicle information transmitted from an unspecified number of vehicle systems 3 is received by the communication unit 25. When the vehicle information is acquired by the vehicle information acquisition unit 24b, the vehicle information storage unit 24d identifies the vehicle 2 on which the vehicle system 3 that transmitted the vehicle information is installed based on the acquired vehicle information, calculates the average vehicle speed of individual drivers in the target link, and stores the calculated average vehicle speed of individual drivers in a predetermined storage area. In addition, the vehicle information storage unit 24d calculates the average vehicle speed of all drivers in the target link and stores the calculated average vehicle speed of all drivers in a predetermined storage area.

[0044] The driver characteristics calculation unit 24e calculates standard driver characteristics by combining the traffic information for the target link stored in the traffic information storage unit 24b with the average vehicle speed of all drivers on the target link stored in the vehicle information storage unit 24d. The driver characteristics calculation unit 24e also calculates individual driver characteristics by combining the traffic information for the target link stored in the traffic information storage unit 24b with the average vehicle speed of individual drivers on the target link stored in the vehicle information storage unit 24d.

[0045] The driver characteristic storage unit 24f stores the standard driver characteristics and individual driver characteristics calculated by the driver characteristic calculation unit 24e.

[0046] The request signal acquisition unit 24g acquires a request signal from the vehicle system 3 when the request signal transmitted from the vehicle system 3 is received by the communication unit 25. When the request signal is acquired by the request signal acquisition unit 24g, the traffic disruption information distribution unit 24h reads the traffic disruption information stored in the traffic disruption information storage unit 24b and distributes the read traffic disruption information from the communication unit 25 to the vehicle system 3.

[0047] When a request signal is acquired by the request signal acquisition unit 24g, the driver characteristic distribution unit 24i identifies the vehicle 2 on which the vehicle system 3 that transmitted the request signal is installed, reads the standard driver characteristics and personal driver characteristics corresponding to the identified vehicle 2 from the standard driver characteristics and personal driver characteristics stored in the driver characteristic storage unit 24f, and has the communication unit 25 distribute the read standard driver characteristics and personal driver characteristics to the vehicle system 3.

[0048] Next, the operation of the above-described configuration will be explained with reference to Figures 7 to 11. Here, we will explain the processing performed by the first control unit 12 of the first domain controller 9 and the processing performed by the control unit 24 of the server 4.

[0049] (1) The first control unit 12 of the first domain controller 9 will perform the following processes: link ID determination processing and energy consumption prediction processing. The first control unit 12 performs the link ID determination processing and energy consumption prediction processing periodically at predetermined intervals. The first control unit 12 may perform the link ID determination processing and energy consumption prediction processing at the same predetermined interval or at different predetermined intervals.

[0050] (1-1) Link ID determination process (see Figure 7) When the conditions for starting the link ID determination process are met, the first control unit 12 starts the link ID determination process. When the first control unit 12 starts the link ID determination process, it obtains the current position (A1) and obtains the current link ID indicating the current link based on the obtained current position (A2). The first control unit 12 compares the obtained current link ID with the previous link ID indicating the link obtained in the previous link ID determination process and determines whether the current link ID and the previous link ID match (A3).

[0051] When the first control unit 12 determines that the current link ID matches the previous link ID (A3: YES), it determines that the vehicle 2 is not crossing a link. The first control unit 12 updates the previous link ID by overwriting the current link ID with the previous link ID (A5), terminates the link ID determination process, and waits for the conditions for starting the next link ID determination process to be met.

[0052] On the other hand, if the first control unit 12 determines that the current link ID and the previous link ID do not match (A3: NO), it determines that the vehicle 2's position has crossed the link, and determines that the vehicle 2 has traveled across the link. The first control unit 12 sets the execution flag for energy consumption prediction (A4). The first control unit 12 updates the previous link ID by overwriting the current link ID with the previous link ID (A5), and waits for the conditions for starting the next link ID determination process to be met.

[0053] (1-2) Energy consumption prediction processing (see Figure 8) The first control unit 12 starts the energy consumption prediction process when the conditions for starting the energy consumption prediction process are met. After starting the energy consumption prediction process, the first control unit 12 determines whether the energy consumption prediction execution flag is set (A11). If the first control unit 12 determines that the energy consumption prediction execution flag is not set (A11: NO), it terminates the energy consumption prediction process and waits for the conditions for starting the next energy consumption prediction process to be met.

[0054] When the first control unit 12 determines that the execution flag for energy consumption prediction is set (A11: NO), it obtains the planned route (A12), obtains the current location (A13), and causes the communication unit 25 to send a request signal to the server 4 (A14). The first control unit 12 obtains traffic information from the server 4 when the traffic information distributed from the server 4 is received by the communication unit 25 (A15, corresponding to the traffic information acquisition procedure).

[0055] The first control unit 12 receives the standard driver characteristics and personal driver characteristics distributed from the server 4 to the communication unit 25, thereby acquiring the standard driver characteristics and personal driver characteristics from the server 4 (corresponding to A16, driver characteristics acquisition procedure), and calculates a specific gravity coefficient based on the acquired traffic interference information (corresponding to A17, specific gravity coefficient calculation procedure). The first control unit 12 calculates the specific gravity coefficient to a value close to "0" when the degree of traffic interference is relatively low, while calculating the specific gravity coefficient to a value close to "1" when the degree of traffic interference is relatively high.

[0056] The first control unit 12 calculates the specific gravity coefficient and then calculates the vehicle speed based on the calculated specific gravity coefficient (corresponding to A18, the vehicle speed calculation procedure). That is, when the degree of traffic disruption is relatively low, the first control unit 12 calculates the vehicle speed using a relatively high specific gravity value for individual driver characteristics, while when the degree of traffic disruption is relatively high, it calculates the vehicle speed using a relatively high specific gravity value for standard driver characteristics.

[0057] The first control unit 12 calculates the vehicle speed, predicts the time required for the target link to travel based on the calculated vehicle speed (A19), predicts the energy consumption for travel of the target link based on the predicted time (A20), and predicts the energy consumption for air conditioning (A21).

[0058] The first control unit 12 determines whether the prediction of the planned route to the destination has been completed (A22). If it determines that the prediction to the destination has not been completed (A22: NO), it returns to step A14 and repeats the steps from A14 onward. If the first control unit 12 determines that the prediction of the planned route to the destination has been completed (A22: YES), it calculates the sum of the driving energy consumption and the air conditioning energy consumption, predicts the energy consumption (A23, corresponding to the energy consumption prediction procedure), terminates the energy consumption prediction process, and waits for the conditions for starting the next energy consumption prediction process to be met. The first control unit 12 sends the energy consumption predicted in this way to the second domain controller 10 and reflects it in the driving control of the vehicle 2.

[0059] (2) The processes performed by the control unit 24 of the server 4 will be described below, including the standard driver characteristic calculation process, the individual driver characteristic calculation process, and the information distribution determination process. The control unit 24 performs the standard driver characteristic calculation process, the individual driver characteristic calculation process, and the information distribution determination process periodically at predetermined intervals. The control unit 24 may perform the standard driver characteristic calculation process, the individual driver characteristic calculation process, and the information distribution determination process at the same predetermined interval, or at different predetermined intervals.

[0060] (2-1) Standard driver characteristic calculation process (see Figure 10) When the conditions for starting the standard driver characteristic calculation process are met, the control unit 24 starts the standard driver characteristic calculation process. When the control unit 24 starts the standard driver characteristic calculation process, it reads out the stored traffic interference information and the average vehicle speed of all drivers on the target link (B1). The control unit 24 calculates the standard driver characteristics by combining the read traffic interference information and the average vehicle speed of all drivers on the target link (B2). The control unit 24 saves the calculated standard driver characteristics in a predetermined storage area (B3), ends the standard driver characteristic calculation process, and waits for the conditions for starting the next standard driver characteristic calculation process to be met.

[0061] (2-2) Individual driver characteristic calculation process (see Figure 11) When the conditions for starting the individual driver characteristics calculation process are met, the control unit 24 starts the individual driver characteristics calculation process. When the control unit 24 starts the individual driver characteristics calculation process, it reads out the stored traffic interference information and the average vehicle speed of the individual drivers on the target link (B11). The control unit 24 calculates the individual driver characteristics by combining the read traffic interference information and the average vehicle speed of the individual drivers on the target link (B12). The control unit 24 saves the calculated individual driver characteristics in a predetermined storage area (B13), ends the individual driver characteristics calculation process, and waits for the conditions for starting the next individual driver characteristics calculation process to be met.

[0062] (2-3) Information distribution determination process (see Figure 12) When the conditions for starting the information distribution determination process are met, the control unit 24 starts the information distribution determination process. After starting the information distribution determination process, the control unit 24 determines whether or not it has received a request signal from the vehicle system 3 (B21). If the control unit 24 determines that it has not received a request signal from the vehicle system 3 (B21: NO), it terminates the information distribution determination process and waits for the conditions for starting the next information distribution determination process to be met.

[0063] When the control unit 24 determines that it has received a request signal from the vehicle system 3 by receiving the request signal transmitted from the vehicle system 3 in the communication unit 25 (B21:YES), it reads out the traffic disruption information, standard driver characteristics, and individual driver characteristics of the target link (B22). The control unit 24 then has the communication unit 25 transmit the read traffic disruption information, standard driver characteristics, and individual driver characteristics of the target link to the vehicle system 3 (B23), terminates the information distribution determination process, and waits for the conditions for starting the next information distribution determination process to be met.

[0064] The above example illustrates a case where the vehicle system 3 predicts the energy consumption of vehicle 2. However, the server 4 may also predict the energy consumption of vehicle 2 and distribute the prediction results to the vehicle system 3.

[0065] As described above, the embodiment provides the following advantages and benefits. In the vehicle system 3, the energy consumption of vehicle 2 is predicted by combining traffic interference information with standard driver characteristics and individual driver characteristics. When the degree of traffic interference is relatively low, the weight of individual driver characteristics is relatively increased compared to standard driver characteristics, and energy consumption is predicted mainly using individual driver characteristics, thereby incorporating the individual driver's vehicle speed tendency into the energy consumption prediction. On the other hand, when the degree of traffic interference is relatively high, the weight of standard driver characteristics is relatively increased compared to individual driver characteristics, and energy consumption is predicted mainly using standard driver characteristics, thereby avoiding excessive reflection of the individual driver's vehicle speed tendency in the energy consumption prediction. This allows the individual driver's vehicle speed tendency to be appropriately reflected in the energy consumption prediction, and enables accurate energy consumption prediction.

[0066] This disclosure includes, in addition to the claims, the following disclosures: [1] An on-board device (9) that predicts the energy consumed by a vehicle while it is in motion as the vehicle's energy consumption, A traffic information acquisition unit (12d) acquires traffic information indicating the degree of traffic disruption, A driver characteristics acquisition unit (12e) acquires standard driver characteristics that show the driving characteristics of a typical driver and individual driver characteristics that show the driving characteristics of an individual driver, An in-vehicle device comprising: an energy consumption prediction unit (12h) that predicts the energy consumption of the vehicle by combining the aforementioned traffic disruption information with the standard driver characteristics and the individual driver characteristics.

[0067] [2] The aforementioned traffic disruption information acquisition unit acquires the traffic disruption information from an external source. The in-vehicle device described in [1] predicts the energy consumption of the vehicle by combining the traffic disruption information obtained from an external source with the standard driver characteristics and the individual driver characteristics.

[0068] [3] A specific gravity coefficient calculation unit (12f) calculates a specific gravity coefficient based on the aforementioned traffic disruption information, The vehicle speed calculation unit (12g) includes a vehicle speed calculation unit that calculates the vehicle speed based on the vehicle speed based on the standard driver characteristics, the vehicle speed based on the individual driver characteristics, and the specific gravity coefficient. The in-vehicle device described in [1] or [2], wherein the energy consumption prediction unit predicts the energy consumption of the vehicle based on the vehicle speed calculated by the vehicle speed calculation unit.

[0069] [4] The specific gravity coefficient calculation unit is an in-vehicle device as described in [3] that calculates the specific gravity coefficient in steps.

[0070] [5] The specific gravity coefficient calculation unit is an in-vehicle device as described in [3] that continuously calculates the specific gravity coefficient.

[0071] [6] It is possible to communicate data with the driving control device (10) that controls the vehicle's operation using electricity, The in-vehicle device described in any one of the items [1] to [5], wherein the energy consumption prediction unit acquires at least a portion of the power data used to predict the energy consumption of the vehicle from the driving control device.

[0072] [7] An energy consumption prediction system (1) comprises an in-vehicle device (9) and an external device (4) capable of data communication with the in-vehicle device, and predicts the energy consumed by the vehicle while it is moving as the vehicle's energy consumption, A traffic information acquisition unit (12d) acquires traffic information indicating the degree of traffic disruption, A driver characteristics acquisition unit (12e) acquires standard driver characteristics that show the driving characteristics of a typical driver and individual driver characteristics that show the driving characteristics of an individual driver, An energy consumption prediction system comprising: an energy consumption prediction unit (12h) that predicts the energy consumption of the vehicle by combining the aforementioned traffic disruption information with the standard driver characteristics and the individual driver characteristics.

[0073] [8] The aforementioned traffic disruption information acquisition unit acquires the traffic disruption information from an external source. The energy consumption prediction unit predicts the energy consumption of the vehicle by combining the traffic disruption information obtained from an external source with the standard driver characteristics and the individual driver characteristics [7] Energy consumption prediction system described in [7].

[0074] [9] A specific gravity coefficient calculation unit (12f) calculates a specific gravity coefficient based on the aforementioned traffic disruption information, The vehicle speed calculation unit (12g) includes a vehicle speed calculation unit that calculates the vehicle speed based on the vehicle speed based on the standard driver characteristics, the vehicle speed based on the individual driver characteristics, and the specific gravity coefficient. The energy consumption prediction unit predicts the energy consumption of the vehicle based on the vehicle speed calculated by the vehicle speed calculation unit, as described in [7] or [8].

[0075]

[10] The gravity coefficient calculation unit is an energy consumption prediction system described in [9] that calculates the gravity coefficient in steps.

[0076]

[11] The gravity coefficient calculation unit is a system for predicting energy consumption as described in [9], which continuously calculates the gravity coefficient.

[0077]

[12] The in-vehicle device is capable of data communication with a driving control device (10) that controls the vehicle's operation using its own power. The energy consumption prediction unit obtains at least a portion of the power data used to predict the energy consumption of the vehicle from the driving control device, as described in any one of paragraphs [7] to

[11] .

[0078]

[13] A method for predicting the energy consumed by a vehicle while it is in motion, comprising an in-vehicle device (9) and an external device (4) capable of data communication with the in-vehicle device, Procedure for obtaining traffic information that shows the degree of disruption, A driver characteristics acquisition procedure for obtaining standard driver characteristics that show the driving characteristics of a typical driver and individual driver characteristics that show the driving characteristics of an individual driver, A method for predicting energy consumption, comprising: an energy consumption prediction procedure that predicts the energy consumption of the vehicle by combining the aforementioned traffic disruption information, the standard driver characteristics, and the individual driver characteristics.

[0079]

[14] The control unit (12) of the on-board device (9) predicts the energy consumed by the vehicle while it is moving as the vehicle's energy consumption, Procedure for obtaining traffic information that shows the degree of disruption, A driver characteristics acquisition procedure for obtaining standard driver characteristics that show the driving characteristics of a typical driver and individual driver characteristics that show the driving characteristics of an individual driver, An energy consumption prediction program that performs an energy consumption prediction procedure for predicting the energy consumption of the vehicle by combining the aforementioned traffic disruption information with the standard driver characteristics and the individual driver characteristics.

[0080] This disclosure is described in accordance with the embodiments, but it is understood that this disclosure is not limited to such embodiments or structures. This disclosure also includes various modifications and variations within the equivalence. In addition, various combinations and forms, as well as other combinations and forms that include only one, more, or fewer of those elements, fall within the scope and concept of this disclosure.

[0081] The control unit and its method described herein may be implemented by a dedicated computer provided by configuring a processor and memory programmed to perform one or more functions embodied by a computer program. Alternatively, the control unit and its method described herein may be implemented by a dedicated computer provided by configuring a processor by one or more dedicated hardware logic circuits. Alternatively, the control unit and its method described herein may be implemented by one or more dedicated computers configured by a combination of a processor and memory programmed to perform one or more functions and a processor configured by one or more hardware logic circuits. Furthermore, the computer program may be stored as instructions executed by the computer on a computer-readable non-transitional tangible recording medium. [Explanation of Symbols]

[0082] In the drawing, 1 is the energy consumption prediction system, 3 is the vehicle system, 4 is the server (external device), 9 is the first domain controller (in-vehicle device), 10 is the second domain controller (driving control device), 12 is the first control unit (control unit), 12d is the traffic disruption information acquisition unit, 12e is the driver characteristics acquisition unit, 12f is the specific gravity coefficient calculation unit, 12g is the vehicle speed calculation unit, and 12h is the energy consumption prediction unit.

Claims

1. An on-board device (9) that predicts the energy consumed by a vehicle while it is in motion as the vehicle's energy consumption, A traffic information acquisition unit (12d) acquires traffic information indicating the degree of traffic disruption, A driver characteristics acquisition unit (12e) acquires standard driver characteristics that show the driving characteristics of a typical driver and individual driver characteristics that show the driving characteristics of an individual driver, An in-vehicle device comprising: an energy consumption prediction unit (12h) that predicts the energy consumption of the vehicle by combining the aforementioned traffic disruption information with the standard driver characteristics and the individual driver characteristics.

2. The aforementioned traffic disruption information acquisition unit acquires the traffic disruption information from an external source. The in-vehicle device according to claim 1, wherein the energy consumption prediction unit predicts the energy consumption of the vehicle by combining the traffic disruption information obtained from an external source with the standard driver characteristics and the individual driver characteristics.

3. A specific gravity coefficient calculation unit (12f) calculates a specific gravity coefficient based on the aforementioned traffic disruption information, The vehicle speed calculation unit (12g) includes a vehicle speed calculation unit that calculates the vehicle speed based on the vehicle speed based on the standard driver characteristics, the vehicle speed based on the individual driver characteristics, and the specific gravity coefficient. The in-vehicle device according to claim 1, wherein the energy consumption prediction unit predicts the energy consumption of the vehicle based on the vehicle speed calculated by the vehicle speed calculation unit.

4. The vehicle-mounted device according to claim 3, wherein the specific gravity coefficient calculation unit calculates the specific gravity coefficient in steps.

5. The vehicle-mounted device according to claim 3, wherein the specific gravity coefficient calculation unit continuously calculates the specific gravity coefficient.

6. It is possible to communicate data with the driving control device (10) that controls the vehicle's operation using electricity, The in-vehicle device according to any one of claims 1 to 5, wherein the energy consumption prediction unit obtains at least a portion of the power data used to predict the energy consumption of the vehicle from the driving control device.

7. An energy consumption prediction system (1) comprises an in-vehicle device (9) and an external device (4) capable of data communication with the in-vehicle device, and predicts the energy consumed by the vehicle while it is moving as the vehicle's energy consumption, A traffic information acquisition unit (12d) acquires traffic information indicating the degree of traffic disruption, A driver characteristics acquisition unit (12e) acquires standard driver characteristics that show the driving characteristics of a typical driver and individual driver characteristics that show the driving characteristics of an individual driver, An energy consumption prediction system comprising: an energy consumption prediction unit (12h) that predicts the energy consumption of the vehicle by combining the aforementioned traffic disruption information with the standard driver characteristics and the individual driver characteristics.

8. The aforementioned traffic disruption information acquisition unit acquires the traffic disruption information from an external source. The energy consumption prediction system according to claim 7, wherein the energy consumption prediction unit predicts the energy consumption of the vehicle by combining the traffic disruption information obtained from an external source with the standard driver characteristics and the individual driver characteristics.

9. A specific gravity coefficient calculation unit (12f) calculates a specific gravity coefficient based on the aforementioned traffic disruption information, The vehicle speed calculation unit (12g) includes a vehicle speed calculation unit that calculates the vehicle speed based on the vehicle speed based on the standard driver characteristics, the vehicle speed based on the individual driver characteristics, and the specific gravity coefficient. The energy consumption prediction system according to claim 7, wherein the energy consumption prediction unit predicts the energy consumption of the vehicle based on the vehicle speed calculated by the vehicle speed calculation unit.

10. The gravity coefficient calculation unit is a system for predicting energy consumption according to claim 9, which calculates the gravity coefficient in steps.

11. The gravity coefficient calculation unit is a system for predicting energy consumption according to claim 9, which continuously calculates the gravity coefficient.

12. The in-vehicle device is capable of data communication with a driving control device (10) that controls the vehicle's operation using its own power. The energy consumption prediction system according to any one of claims 7 to 11, wherein the energy consumption prediction unit obtains at least a portion of the power data used to predict the energy consumption of the vehicle from the driving control device.

13. A method for predicting the energy consumed by a vehicle while it is in motion, comprising an in-vehicle device (9) and an external device (4) capable of data communication with the in-vehicle device, Procedure for obtaining traffic information that shows the degree of disruption, A driver characteristics acquisition procedure for obtaining standard driver characteristics that show the driving characteristics of a typical driver and individual driver characteristics that show the driving characteristics of an individual driver, A method for predicting energy consumption, comprising: an energy consumption prediction procedure that predicts the energy consumption of the vehicle by combining the aforementioned traffic disruption information, the standard driver characteristics, and the individual driver characteristics.

14. The control unit (12) of the on-board device (9) predicts the energy consumed by the vehicle while it is moving as the vehicle's energy consumption, Procedure for obtaining traffic information that shows the degree of disruption, A driver characteristics acquisition procedure for obtaining standard driver characteristics that show the driving characteristics of a typical driver and individual driver characteristics that show the driving characteristics of an individual driver, An energy consumption prediction program that performs an energy consumption prediction procedure for predicting the energy consumption of the vehicle by combining the aforementioned traffic disruption information, the standard driver characteristics, and the individual driver characteristics.

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