Information processing device, information processing method, and program

Abstract

This reduces the risk of users selecting an electric vehicle that does not meet the performance requirements for their intended use. [Solution] The information processing device 1b includes a driving data acquisition unit 136 that acquires driving data, a storage unit 12 that stores the battery capacity of each electric vehicle, stores prediction parameters, and stores fuel consumption conversion data, a driving distance identification unit 133 that identifies the use of a managed vehicle based on driving data or information indicating the use specified by the user, calculates the assumed fuel consumption based on the fuel consumption included in the catalog information of the managed vehicle and the prediction parameters of a gasoline vehicle corresponding to the use of the managed vehicle, converts the assumed fuel consumption to electricity consumption by referring to the fuel consumption conversion data, calculates the driving standard distance based on driving data, and calculates the drivable distance based on the assumed electricity consumption and the battery capacity corresponding to the candidate vehicle, and a display processing unit 134 that displays information based on the driving standard distance and the drivable distance on a display device.

Description

Technical Field

[0001] The present invention relates to an information processing apparatus, an information processing method, and a program.

Background Art

[0002] In recent years, the number of users switching from gasoline vehicles to electric vehicles has been increasing. Patent Document 1 discloses a technique for managing information on the performance, equipment, etc. of vehicles described in catalogs and the like (hereinafter referred to as "catalog information").

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By referring to the catalog information, the user can grasp the performance of the electric vehicle being considered for switching. However, in the performance of electric vehicles, it can vary depending on the use of the user's vehicle. Therefore, if the user selects an electric vehicle based on the catalog information, there is a high risk that an electric vehicle that does not meet the performance required in the above use will be selected.

[0005] Therefore, the present invention has been made in view of these points, and as an example, an object thereof is to reduce the risk that an electric vehicle that does not meet the performance required in the use of the user's vehicle is selected.

Means for Solving the Problems

[0006] An information processing device according to the first aspect of the present invention includes: an acquisition unit that acquires driving data showing the location history of a managed vehicle managed by a user over a predetermined period; a storage unit that stores the battery capacity of each electric vehicle, stores prediction parameters for predicting fuel consumption when a gasoline vehicle is driven for the intended use of a gasoline vehicle, and stores fuel-fuel-fuel conversion data associated with the fuel consumption of the gasoline vehicle and the electric vehicle's energy consumption for each gasoline vehicle's energy consumption; an identification unit that identifies the intended use of the managed vehicle based on the driving data or information indicating the intended use specified by the user; and the fuel consumption included in the catalog information of the managed vehicle and the managed vehicle identified by the identification unit. The system includes: a first calculation unit that calculates the expected fuel consumption when the managed vehicle travels the location history based on the predicted parameters of the gasoline vehicle corresponding to both uses, and converts the expected fuel consumption to electricity consumption by referring to the fuel consumption-electricity conversion data; a second calculation unit that calculates a standard driving distance that serves as the driving distance required for a candidate electric vehicle, which is a candidate vehicle to be presented to the user, based on the driving data; a third calculation unit that calculates the driving range at maximum charge based on the expected electricity consumption converted by the first calculation unit and the battery capacity corresponding to the candidate vehicle; and a display processing unit that displays the presentation information based on the standard driving distance and the driving range on a display device.

[0007] The storage unit may further store the prediction parameters defined for each type of gasoline vehicle, and the first calculation unit may further calculate the estimated energy consumption based on the prediction parameters corresponding to the type of candidate vehicle.

[0008] The storage unit may further store the power consumption information of each electric vehicle, the second calculation unit may calculate the maximum driving range of each of the multiple candidate vehicles at maximum charge based on the power consumption information of each of the multiple candidate vehicles and the battery capacity corresponding to each of the multiple candidate vehicles, and the display processing unit may display as the presented information the candidate vehicles whose driving range is equal to or greater than the driving standard distance among the multiple candidate vehicles.

[0009] The third calculation unit may further calculate the driving range of the candidate vehicle at maximum charge based on the degree of degradation of the battery installed in the candidate vehicle.

[0010] The storage unit may further store candidate vehicle information, including the status of the candidate vehicle and the price of the candidate vehicle, and the display processing unit may display the candidate vehicle information corresponding to the candidate vehicle as the presented information.

[0011] The display processing unit may display, as previously presented information, the comparison result obtained by comparing the running cost based on the energy consumed by the managed vehicle with the running cost based on the electricity consumed by the candidate vehicle.

[0012] The display processing unit may display the comparison result, obtained by comparing the CO2 generated in accordance with the energy consumed by the managed vehicle and the CO2 generated in accordance with the electricity consumed by the candidate vehicle, as the displayed information.

[0013] The information processing device may further include a selection unit that selects, from among a plurality of electric vehicles, an electric vehicle that satisfies at least some of the specifications of the managed vehicle as the candidate vehicle.

[0014] A second aspect of the present invention provides an information processing method that includes the steps of: acquiring driving data showing the location history of a managed vehicle managed by a user over a predetermined period of time; identifying the use of the managed vehicle based on the driving data or information indicating the use specified by the user; and using the fuel efficiency included in the catalog information of the managed vehicle, and performing the following steps: using a computer having a storage unit that stores the battery capacity of the electric vehicle for each electric vehicle, stores prediction parameters for predicting the fuel efficiency when the gasoline vehicle is driven for each use of the gasoline vehicle, and stores fuel efficiency-electricity conversion data associated with the fuel efficiency of the gasoline vehicle and the electric vehicle over a predetermined period of time; identifying the use of the managed vehicle based on the driving data or information indicating the use specified by the user; and using the fuel efficiency included in the catalog information of the managed vehicle, The system includes the steps of: calculating an estimated fuel consumption expected when the managed vehicle travels the location history based on the predicted parameters of the gasoline vehicle corresponding to the determined use of the managed vehicle; converting the estimated fuel consumption to the electric energy consumption by referring to the fuel consumption to electric energy consumption conversion data; calculating a standard driving distance that serves as a basis for the driving distance required for a candidate electric vehicle, which is a candidate vehicle to be presented to the user, based on the driving data; calculating the maximum driving distance at maximum charge based on the converted estimated electric energy consumption and the battery capacity corresponding to the candidate vehicle; and displaying presentation information based on the standard driving distance and the maximum driving distance on a display device.

[0015] A third aspect of the present invention provides a computer having a storage unit that stores the battery capacity of each electric vehicle, predictive parameters for predicting fuel consumption when a gasoline vehicle is driven for a gasoline vehicle's intended use, and fuel-fuel-conversion data for each gasoline vehicle's fuel consumption, relating the fuel consumption of the gasoline vehicle to the electric vehicle's energy consumption; an acquisition unit that acquires driving data showing the location history of a managed vehicle managed by a user over a predetermined period; an identification unit that identifies the intended use of the managed vehicle based on the driving data or information indicating the intended use specified by the user; and the fuel consumption included in the catalog information of the managed vehicle and the pipe identified by the identification unit. The system functions as a first calculation unit that calculates the expected fuel consumption when the managed vehicle travels the location history based on the predicted parameters of the gasoline vehicle corresponding to the intended use of the managed vehicle, and converts the expected fuel consumption to the electric energy consumption by referring to the fuel consumption-electric energy consumption conversion data; a second calculation unit that calculates a standard driving distance that serves as the driving distance required for a candidate electric vehicle, which is a candidate vehicle to be presented to the user, based on the driving data; a third calculation unit that calculates the maximum driving distance at maximum charge based on the expected electric energy consumption converted by the first calculation unit and the battery capacity corresponding to the candidate vehicle; and a display processing unit that displays the presentation information based on the standard driving distance and the maximum driving distance on a display device.

[0016] [Effects of the Invention]

[0017] According to the present invention, for example, it is possible to reduce the risk that a user may select an electric vehicle that does not meet the performance requirements for their intended use. [Brief explanation of the drawing]

[0018] [Figure 1] This is a diagram illustrating the overview of the information processing system. [Figure 2] This figure shows an example of a screen on an information terminal that displays a first distance image and a second distance image. [Figure 3] It is a diagram showing the configuration of an information processing apparatus. [Figure 4] It is a diagram showing an example of performance data. [Figure 5] It is a diagram showing an example of the effective coefficient for each application. [Figure 6] It is a diagram showing an example of a screen on which a first distance image and a second distance image are displayed after a vehicle type and an application are selected by a user. [Figure 7] It is a flowchart showing the processing flow in an information processing apparatus. [Figure 8] It is a diagram showing the configuration of an information processing apparatus according to a second embodiment. [Figure 9] It is a diagram showing an example of a screen for a user to input usage conditions. [Figure 10] It is a diagram showing an example of a screen for displaying a selection result. [Figure 11] It is a diagram for explaining the outline of an information processing system according to a third embodiment. [Figure 12] It is a diagram showing the configuration of an information processing apparatus according to a third embodiment. [Figure 13] It is a diagram showing an example of the configuration of a parameter management database. [Figure 14] It is a diagram showing an example of a screen for displaying presentation information. [Figure 15] It is a flowchart showing the processing flow in an information processing apparatus according to a third embodiment.

Mode for Carrying Out the Invention

[0019] <First Embodiment> [Outline of Information Processing System S in the First Embodiment] Figure 1 is a diagram illustrating the overview of the information processing system S. The information processing system S is a system for providing information about electric vehicles powered by batteries to user U. The information processing system S comprises an information processing device 1 and an information terminal 2. The information processing device 1 and the information terminal 2 can send and receive data via a network such as the Internet or an intranet. The information terminal 2 may be any display device having the function of displaying information, such as a smartphone, tablet, or personal computer.

[0020] The information processing device 1 displays a distance image on the information terminal 2 showing the driving range (e.g., maximum driving range) of electric vehicles that are candidates for use by user U, who is a prospective user of an electric vehicle. The maximum driving range is the distance that can be traveled with a battery that is fully charged. The amount of power that a battery can output when fully charged changes over time or with the cumulative mileage of the electric vehicle. Therefore, the maximum driving range of an electric vehicle running on battery power will be a different value depending on the passage of time, the cumulative mileage (which correlates with the number of charge-discharge cycles), or the environment of the driving area.

[0021] If the maximum driving range displayed by the information processing device 1 on the information terminal 2 is only the distance an electric vehicle can travel with a new battery fully charged, then user U has no choice but to judge whether the candidate electric vehicle's maximum driving range is sufficient based on that maximum driving range. If the actual maximum driving range decreases over time or as the cumulative driving distance increases (i.e., performance degradation occurs), even if user U judges that the candidate electric vehicle's maximum driving range is sufficient, there may be cases where the actual maximum driving range is shorter than the distance user U must travel on a single charge.

[0022] For example, suppose user U drives 150km in a day for work. If the maximum driving range of an electric vehicle in its new condition (i.e., using a new battery that has not degraded in performance) is 160km, then initially, if user U charges the electric vehicle before starting work each day, they can complete their work for the day without having to recharge it along the way. However, if the maximum driving range drops to 120km after 6 years, even if user U charges the electric vehicle before starting work each day, they will have to recharge it along the way, which becomes a problem.

[0023] Therefore, the information processing device 1 displays on the information terminal 2 images showing multiple maximum driving distances for multiple days, each with a different number of days elapsed since a new battery was installed in the electric vehicle. In this specification, these multiple days are referred to as the first reference date and the second reference date. The first reference date is, for example, the day immediately following the shipment of the electric vehicle, but may also be the day on which user U plans to start using the electric vehicle. The second reference date is, for example, a day after a predetermined number of years have elapsed from the first reference date. The length of the first reference date, the second reference date, or the period between the first and second reference dates may be set by user U via the information terminal 2. In addition to the first reference date, the second reference date, or the length of the period between the first and second reference dates, user U may also set usage conditions, including the type (model) or intended use of the electric vehicle.

[0024] In this specification, the maximum drivable distance on the first reference day may be referred to as the first maximum drivable distance, and the maximum drivable distance on the second reference day may be referred to as the second maximum drivable distance. Furthermore, the image corresponding to the first maximum drivable distance may be referred to as the first distance image, and the image corresponding to the second maximum drivable distance may be referred to as the second distance image.

[0025] Figure 2 shows an example of a screen where information terminal 2 displays the first and second distance images. In the upper left area R1 of Figure 2, an image is displayed for selecting the vehicle type for which the first and second distance images will be displayed. In area R2, text is displayed for user U to select the purpose for which the electric vehicle will be used. In the example shown in Figure 2, the name of the department using the electric vehicle is displayed as the purpose, but the purpose is not limited to the department name; text that directly indicates the content of the work, such as "long-distance transport" or "package delivery," may also be displayed.

[0026] Area R3 shows the maximum mileage available each month. Image G1 shows the first maximum mileage, and image G2 shows the second maximum mileage. Image G1 is an example of the first mileage image, and image G2 is an example of the second mileage image. Image G3 shows the mileage required for user U's use. The mileage required for user U's use is calculated by adding a predetermined value as a buffer during use, for example, to the mileage required for the use. Since the characteristics of the battery and electric vehicle change with temperature, the first and second maximum mileages will be different values ​​from month to month. By looking at the images displayed in area R3, user U can check whether the maximum mileage is greater than the mileage required for user U's use, even in the month with the lowest maximum mileage.

[0027] In area R4, the first and second distance images are shown overlaid on the map, starting from the reference position (Yokohama in Figure 2), which is the starting point for user U when using the electric vehicle. Image G4 (dotted line) in area R4 is the first distance image, and image G5 (dashed line) is the second distance image. It can be confirmed that the distance from Yokohama to the position shown in the first distance image is greater than the distance from Yokohama to the position shown in the second distance image. In Figure 2, the first and second distance images corresponding to the first and second maximum driving distances, calculated considering factors such as the distance along the road, the road gradient, and the degree of road congestion, are displayed. The first and second distance images may also represent the approximate positions corresponding to the first and second maximum driving distances from the starting point using concentric circles centered on the starting point.

[0028] The first and second distance images may be indicated by filling in the area corresponding to the maximum expected mileage within the period between the first reference date and the second reference date with a predetermined pattern. In this case, the area between image G4 and image G5 shown in region R4 of Figure 2 will be filled in, with the outer edge furthest from the reference position in that region corresponding to the first distance image, and the outer edge closest to the reference position in that region corresponding to the second distance image.

[0029] In area R4, place names are displayed overlaid on the first and second distance images. By viewing the first and second distance images, user U can determine whether an electric vehicle with a distance image displayed in Figure 2 can be used in user U's work.

[0030] [Configuration of the information processing device 1 in the first embodiment] Figure 3 shows the configuration of the information processing device 1. The information processing device 1 includes a communication unit 11, a storage unit 12, and a control unit 13. The control unit 13 includes a reference data acquisition unit 131, an input data acquisition unit 132, a mileage identification unit 133, and a display processing unit 134.

[0031] The communication unit 11 includes a communication interface for sending and receiving data to and from the information terminal 2 via a network. The communication unit 11 inputs the data received from the information terminal 2 to the reference data acquisition unit 131, the input data acquisition unit 132, or the mileage identification unit 133. The communication unit 11 also transmits the data input from the display processing unit 134 to the information terminal 2.

[0032] The storage unit 12 includes storage media such as ROM (Read Only Memory), RAM (Random Access Memory), and SSD (Solid State Drive). The storage unit 12 stores programs executed by the control unit 13. The storage unit 12 also stores various data used by the control unit 13 to display the first distance image and the second distance image on the information terminal 2. The storage unit 12 stores performance data showing the relationship between, for example, the elapsed time from the first reference date or the cumulative mileage of the electric vehicle from the first reference date, and the mileage of the electric vehicle at maximum charge.

[0033] Figure 4 shows an example of performance data. The horizontal axis of the graph in Figure 4 represents the elapsed time since the start of electric vehicle use. The vertical axis represents the maximum driving range when the battery is fully charged. As shown in Figure 4, the maximum driving range decreases over time. In Figure 4, T1 corresponds to the first reference day, and T2 corresponds to the second reference day. It can be seen that the second maximum driving range on the second reference day is shorter than the first maximum driving range on the first reference day.

[0034] Figures 4(a) and 4(b) show cases where the battery performance (e.g., battery capacity) differs at different first reference days T1. Battery capacity is the maximum charge amount that changes due to battery performance degradation. Figure 4(a) shows that the maximum driving distance at the first reference day T1 is L1, and the maximum driving distance at the second reference day T2 is L2.

[0035] Figure 4(b) shows performance data when time T1' in Figure 4(a) is the first reference day. In Figure 4(b), the maximum drivable distance at time T1 on the first reference day is L1', and the maximum drivable distance at elapsed time T2 is L2'. In Figure 4(b), T1 corresponds to time T1' in Figure 4(a), where L1' is smaller than L1 and L2' is smaller than L2.

[0036] Performance data is calculated based on factors such as the number of days since manufacture (degree of storage degradation), whether the vehicle is new or used (degree of storage degradation and charge / discharge cycle degradation), cumulative mileage (degree of storage degradation and charge / discharge cycle degradation), and other factors (degree of storage degradation, charge / discharge cycle degradation, charge / discharge pattern). Note that the charge / discharge pattern will vary depending on factors such as driving style and the terrain of the driving location.

[0037] Performance data varies depending on the type of battery installed in the electric vehicle, the environment in which the electric vehicle is used, or the intended use of the electric vehicle. Therefore, the memory unit 12 may store multiple performance data associated with the performance of the battery installed in the electric vehicle. The memory unit 12 may also store multiple performance data associated with temperature, or associated with intended use. Furthermore, the memory unit 12 may store multiple performance data associated with the elapsed time or cumulative mileage since the electric vehicle was manufactured. Moreover, the performance data may be the change in charging capacity due to performance degradation calculated from elapsed time, or the change in charging capacity due to performance degradation calculated based on elapsed time plus cumulative mileage (number of cycles). Furthermore, it may be calculated more precisely based on driving data (history information such as usage and driving conditions) acquired while the vehicle is running.

[0038] The configuration and operation of each part of the control unit 13 will be explained below with reference to Figure 3. The reference data acquisition unit 131 acquires processing reference data indicating the performance of the battery installed in the electric vehicle. The reference data acquisition unit 131 acquires processing reference data indicating the performance of the battery on at least the first reference day. The reference data acquisition unit 131 may also acquire processing reference data in association with the electric vehicle model or the type of battery.

[0039] The processing standard data may include any data that correlates with the performance of the battery, for example, at least one of the following: actual measurement data obtained from an electric vehicle, data indicating the manufacturing date of the electric vehicle, data indicating the mileage of the electric vehicle, or data indicating whether the electric vehicle is new or used. The standard data acquisition unit 131 may acquire processing standard data that has been previously stored in the storage unit 12, or it may acquire processing standard data from an external device that stores data related to the electric vehicle. The standard data acquisition unit 131 notifies the mileage identification unit 133 of the acquired processing standard data.

[0040] The input data acquisition unit 132 acquires various types of data entered at the information terminal 2. For example, the input data acquisition unit 132 acquires vehicle type data indicating the vehicle type selected by user U from among multiple vehicle types at the information terminal 2. The input data acquisition unit 132 may also acquire usage data from the information terminal 2 indicating the intended use of the electric vehicle by user U. The input data acquisition unit 132 notifies the mileage identification unit 133 of the acquired data.

[0041] The input data acquisition unit 132 may function as a location data acquisition unit that acquires location data indicating the reference position from which the electric vehicle begins to drive, which is input on the information terminal 2. The location data may be an address or postal code indicating the reference position, a place name indicating a representative point of the reference position, or data indicating the latitude and longitude of the reference position.

[0042] The input data acquisition unit 132 may also function as a period data acquisition unit that acquires period data indicating the period from the first reference date to the second reference date. The period data is, for example, the period from the first reference date when user U starts using the electric vehicle to the second reference date when user U plans to end using the electric vehicle. In the example shown in Figure 2, this period is set to 6 years.

[0043] The mileage determination unit 133 determines the maximum mileage available to the electric vehicle for use by user U based on various data. For example, the mileage determination unit 133 determines the first maximum mileage at maximum charge of the electric vehicle on the first reference day by referring to performance data stored in the storage unit 12. Specifically, the mileage determination unit 133 refers to performance data corresponding to the performance corresponding to the battery state indicated by the reference processing data acquired by the reference data acquisition unit 131, and identifies the maximum mileage corresponding to the first reference day indicated by the performance data as the first maximum mileage.

[0044] For example, if the mileage identification unit 133 indicates that one year has passed since the electric vehicle was manufactured, it will refer to the performance data corresponding to the case where one year has passed since the electric vehicle was manufactured (for example, the performance data shown in Figure 4(b)). If the mileage identification unit 133 indicates that the cumulative mileage of the electric vehicle is 10,000 km, it may also refer to the performance data corresponding to a cumulative mileage of 10,000 km.

[0045] Furthermore, the mileage determination unit 133 determines the second maximum mileage at the time of maximum charge of the electric vehicle on the second reference day based on the elapsed time from the first reference day to the second reference day or the cumulative mileage during the period from the first reference day to the second reference day. The mileage determination unit 133 determines the second maximum mileage based, for example, on the period indicated by the period data. Specifically, the mileage determination unit 133 determines the second maximum mileage as the maximum mileage corresponding to the second reference day after the period indicated by the return data has elapsed from the first reference day, in the performance data used to determine the first maximum mileage.

[0046] If the performance data corresponding to the battery performance indicated by the processing reference data acquired by the reference data acquisition unit 131 is the data shown in Figure 4(a), the mileage identification unit 133 identifies the first maximum mileage as L1, since the maximum mileage available on the first reference day T1 is L1. Then, the mileage identification unit 133 identifies the second reference day T2, which is the period ΔT that has elapsed from the first reference day T1, and identifies the second maximum mileage as L2, since the maximum mileage available on the second reference day T2 is L2.

[0047] The mileage determination unit 133 may determine the first maximum mileage and the second maximum mileage by referring to performance data associated with the battery performance indicated by the processing reference data acquired by the reference data acquisition unit 131. For example, if the performance data corresponding to the battery performance indicated by the processing reference data acquired by the reference data acquisition unit 131 is the data shown in Figure 4(a), the mileage determination unit 133 determines that the first maximum mileage on the first reference day is L1, and determines that the second maximum mileage on the second reference day, after a period ΔT has elapsed from the first reference day, is L2.

[0048] On the other hand, if the performance data corresponding to the battery performance indicated by the processing reference data acquired by the reference data acquisition unit 131 is the data shown in Figure 4(b), the mileage determination unit 133 determines that the first maximum mileage on the first reference day is L1' and that the second maximum mileage on the second reference day is L2'. By operating in this manner, the mileage determination unit 133 takes into account the battery performance on the first reference day when determining the first and second maximum mileage, thereby improving the accuracy of the mileage determination unit 133 in determining the first and second maximum mileage.

[0049] Incidentally, battery performance varies depending on the environment in which the electric vehicle is used. Therefore, the mileage determination unit 133 may determine the first maximum mileage and the second maximum mileage starting from the reference position by referring to performance data associated with the temperature corresponding to the reference temperature at the reference position indicated by the position data. The mileage determination unit 133 may also determine the first maximum mileage and the second maximum mileage by calculating the first maximum mileage and the second maximum mileage by inputting the values ​​indicated by the performance data into a predetermined calculation formula. By operating in this manner, when the electric vehicle for which the information processing device 1 determines the first maximum mileage and the second maximum mileage is used in multiple regions with different climates, the difference between the first maximum mileage and the second maximum mileage determined by the mileage determination unit 133 and the actual distance the electric vehicle can travel can be reduced, regardless of the region.

[0050] Furthermore, the mileage determination unit 133 may determine the first and second maximum mileage for each of several time periods by referring to performance data corresponding to the average temperature for each period in the area where the electric vehicle is used. The mileage determination unit 133 determines the first and second maximum mileage for each month, for example, as shown in region R3 in Figure 2. The mileage determination unit 133 notifies the display processing unit 134 of the first and second maximum mileage in association with multiple time periods.

[0051] The display processing unit 134 displays a first distance image corresponding to the first maximum mileage identified by the mileage identification unit 133 and a second distance image corresponding to the second maximum mileage on a display device (e.g., information terminal 2) in an identifiable manner. The display processing unit 134 displays the first distance image and the second distance image on the display device, for example, associated with multiple time periods. In this case, the first distance image is, for example, image G1 shown in area R3 of Figure 2, and the second distance image is, for example, image G2 shown in area R3 of Figure 2. The display processing unit 134 may display only one of the first and second distance images selected by the user U on the information terminal 2.

[0052] The display processing unit 134 may overlay a first line image G4 showing the location of the first maximum travel distance from the reference location (e.g., "Yokohama") indicated by the position data acquired by the input data acquisition unit 132, a second line image G5 showing the location of the second maximum travel distance from the reference location, and an image showing the reference location onto the map image and display it on the information terminal 2, as shown in area R4 of Figure 2. By displaying such an image on the information terminal 2, the user U can more easily determine whether they can continue to use the electric vehicle for a desired purpose starting from the reference location after a predetermined number of years have passed since they started using the electric vehicle.

[0053] The display processing unit 134 may overlay an image showing the place name of the reference location onto the map image in a first manner, and may overlay at least one of the images showing the place name of the location corresponding to the first maximum travel distance or the place name of the location corresponding to the second maximum travel distance onto the map image in a second manner different from the first manner.

[0054] In the example shown in region R4 of Figure 2, the place name Yokohama, which is the reference location, is surrounded by a thick line frame, Atami, Sagamihara, Okegawa, Moriya, and Chonan, which correspond to the first maximum driving distance, are surrounded by a dashed line frame, and Odawara, Hachioji, Kawagoe, Kashiwa, and Ichihara, which correspond to the second maximum driving distance, are surrounded by a thin solid line frame. The display processing unit 134 may also display an image showing the place name that has been set in advance by the user U from among the multiple place names corresponding to the first and second maximum driving distances, starting from the reference location. By displaying the place names of the locations corresponding to the first maximum driving distance and the locations corresponding to the second maximum driving distance in this way, the user U can more easily understand the range in which the electric vehicle can travel.

[0055] The display processing unit 134 may set the color of the first distance image and the color of the place name corresponding to the first maximum distance traveled to the same color (first color), and the color of the second distance image and the color of the place name corresponding to the second maximum distance traveled to the same color (second color). By displaying the distance images and place names on the information terminal 2 in this way, the user U can more easily understand which points correspond to the first maximum distance traveled and which points correspond to the second maximum distance traveled.

[0056] The display processing unit 134 may display the first maximum mileage and the second maximum mileage, starting from the reference position, on the information terminal 2, which have been determined by the mileage determination unit 133 by referring to performance data associated with the temperature corresponding to the reference temperature at the reference position. The reference temperature is, for example, the annual average temperature, the annual maximum temperature, or the annual minimum temperature at the reference position. By having the display processing unit 134 display the first maximum mileage and the second maximum mileage, determined based on the temperature at the reference position, on the information terminal 2, users U in various regions can grasp the first maximum mileage and the second maximum mileage with high accuracy.

[0057] Furthermore, when the mileage identification unit 133 identifies a second maximum mileage corresponding to the period input by user U, the display processing unit 134 may change the second mileage image displayed on the information terminal 2 each time the input data acquisition unit 132 acquires new period data. By operating in this manner, user U can check the second mileage image while switching between planned periods of use for the electric vehicle, making it easier to decide on the planned period of use and to check the status of the electric vehicle if it is used for a longer period than planned.

[0058] [Display of maximum driving range by usage] Incidentally, the maximum driving range of an automobile varies depending on its intended use. For example, the maximum driving range for use on main roads with infrequent starts and stops is greater than the maximum driving range for use with frequent starts and stops. Therefore, the information processing device 1 may receive input from user U regarding the intended use of the electric vehicle and display a first maximum driving range and a second maximum driving range, which differ for each input intended use, on the information terminal 2.

[0059] The information processing device 1 uses effective coefficients associated with each application to determine the first and second maximum driving distances for each application. The storage unit 12 stores effective coefficients associated with each of the multiple applications of the electric vehicle, which represent coefficients that convert the driving distance in a standard application to the actual driving distance in each of the multiple applications. The effective coefficient is a value that represents the ratio of the energy efficiency in each application to the energy efficiency in the standard application. The standard application is, for example, an application with a low frequency of starting and stopping and relatively high energy efficiency.

[0060] Figure 5 shows an example of effective coefficients for different uses. The effective coefficient may be calculated based on the fuel efficiency (actual fuel efficiency) of a gasoline-powered vehicle, or based on the driving range of a fully charged electric vehicle. However, in the table shown in Figure 5, the relationship between use, fuel efficiency, and effective coefficient is shown. In the example shown in Figure 5, the effective coefficient for use in the general affairs department is the highest, while the effective coefficient for use in the delivery department, which involves frequent starting and stopping, is the lowest. The driving range of an electric vehicle may be calculated by first calculating the actual fuel efficiency of a gasoline vehicle, and then multiplying, dividing, adding, or subtracting the calculated actual fuel efficiency by a predetermined coefficient for converting between the actual fuel efficiency of a gasoline vehicle and the driving range of an electric vehicle.

[0061] The display processing unit 134 displays a screen on the information terminal 2 for selecting one application from multiple applications, and the input data acquisition unit 132 accepts the input or selection of an application by the user U. The mileage determination unit 133 calculates the first and second maximum mileage for the selected application by converting the first and second maximum mileage for the standard application using the effective coefficient corresponding to the selected application.

[0062] For example, if "commercial use" with an effective coefficient of 0.90 is selected as the application, and the first maximum mileage for the standard application is 150 km and the second maximum mileage is 130 km, the mileage determination unit 133 calculates the first maximum mileage for the "commercial use" as 150 × 0.90 = 135 km and the second maximum mileage as 130 × 0.90 = 117 km. The display processing unit 134 displays the first and second distance images corresponding to the first and second maximum mileage calculated in this way on the information terminal 2.

[0063] The display processing unit 134 may display the first distance image and the second distance image on the information terminal 2 along with information indicating the required mileage for the use selected by user U (for example, image G3 in Figure 2). The required mileage for the use selected by user U may be the distance entered by user U, or it may be the distance determined by the display processing unit 134 by referring to a table stored in the storage unit 12 that associates the use with the required mileage. With the information processing device 1 configured in this way, the first and second maximum mileage, which differ for each use of the electric vehicle by user U, are displayed on the information terminal 2, making it easier for user U to appropriately determine whether they will be able to continue using the electric vehicle for their own use several years from now.

[0064] Note that the maximum driving range also varies depending on the vehicle model. Therefore, the storage unit 12 may store multiple performance data associated with the electric vehicle model, and the display processing unit 134 may display a screen on the information terminal 2 for selecting one vehicle model from the multiple vehicle models, and on that screen, display the first distance image and the second distance image corresponding to the first and second maximum driving ranges corresponding to the selected vehicle model on the information terminal 2. In this case, the driving range identification unit 133 identifies the first and second maximum driving ranges by referring to the performance data corresponding to the selected vehicle model.

[0065] The display processing unit 134 may display a first distance image and a second distance image on the information terminal 2 that correspond to the combination of use and vehicle type selected by the user U. In this case, the mileage identification unit 133 calculates the first maximum mileage and the second maximum mileage for the standard use by referring to performance data corresponding to the vehicle type, and calculates the first distance image and the second distance image corresponding to the selected combination of use and vehicle type by converting the calculated first maximum mileage and the second maximum mileage using the effective coefficient of the selected use.

[0066] Figure 6 shows an example of a screen displaying the first and second distance images after the vehicle type and intended use have been selected by user U. Area R3 shows that the first maximum driving distance on the first reference date (present) when using an electric vehicle for commercial purposes is 135 km, and the second maximum driving distance six years later is 117 km. With the information processing device 1 configured in this way, user U can appropriately select a vehicle type that is suitable for their intended use.

[0067] [Processing flow of the information processing device 1 in the first embodiment] Figure 7 is a flowchart showing the processing flow in the information processing device 1. The flowchart shown in Figure 7 starts from the point when the application software for displaying the first distance image and the second distance image on the information terminal 2 is launched.

[0068] The display processing unit 134 displays a screen on the information terminal 2 that accepts the selection of a vehicle type, and the mileage determination unit 133 acquires the vehicle type via the input data acquisition unit 132 (S1). The mileage determination unit 133 determines whether or not performance data corresponding to the selected vehicle type is stored in the storage unit 12 (S2). If the mileage determination unit 133 determines that the performance data is not stored in the storage unit 12 (NO in S2), it displays error information on the information terminal 2 via the display processing unit 134 indicating that the maximum mileage cannot be displayed (S3).

[0069] If the mileage identification unit 133 determines that performance data is stored in the storage unit 12 (YES in S2), it acquires the usage via the input data acquisition unit 132 (S4). The mileage identification unit 133 identifies the effective coefficient corresponding to the usage (S5). Subsequently, the mileage identification unit 133 acquires the period between the first reference date and the second reference date via the input data acquisition unit 132 (S6). Based on the performance data, the mileage identification unit 133 identifies the first maximum mileage and the second maximum mileage corresponding to the acquired period. By converting the identified first and second maximum mileage based on the effective coefficient, the mileage identification unit 133 identifies the first and second maximum mileage corresponding to the vehicle type and usage selected by user U (S7).

[0070] Next, the display processing unit 134 acquires the reference position via the input data acquisition unit 132 (S8), and displays a first distance image indicating the position corresponding to the first maximum travel distance from the reference position and a second distance image corresponding to the second maximum travel distance on the information terminal 2 (S9). The information processing device 1 determines whether or not a termination operation has been performed on the information terminal 2 (S10), and repeats the processes from S1 to S9 until a termination operation is performed. The order in which the information processing device 1 acquires the vehicle type, purpose, period, and reference position is arbitrary, and these may be acquired simultaneously.

[0071] [Effects of the information processing device 1 in the first embodiment] As explained above, the mileage identification unit 133 identifies the first maximum mileage at maximum charge on the first reference day and the second maximum mileage at maximum charge on the second reference day by referring to the performance data stored in the storage unit 12. The display processing unit 134 then displays the first distance image corresponding to the first maximum mileage and the second distance image corresponding to the second maximum mileage on the information terminal 2 in an identifiable manner. With the information processing device 1 configured in this way, user U can easily understand the maximum mileage at the time of starting to use the electric vehicle and the maximum mileage several years later, so that they can easily decide whether or not to select this electric vehicle.

[0072] <Second Embodiment> The above explanation assumed that the vehicle type used by user U was predetermined or that user U selected the vehicle type. However, since there are many types of electric vehicles, it may be too time-consuming for user U to select each vehicle type from the many available and check the first and second maximum driving ranges. Therefore, the information processing device 1 may obtain the usage conditions for the electric vehicle from user U, select an electric vehicle that matches the obtained usage conditions, and present the selected electric vehicle to user U.

[0073] Figure 8 shows the configuration of the information processing device 1a according to the second embodiment. The information processing device 1a shown in Figure 8 differs from the information processing device 1 shown in Figure 3 in that it further includes a selection unit 135. In addition, the input data acquisition unit 132 in the information processing device 1a also functions as a usage condition acquisition unit.

[0074] The input data acquisition unit 132 acquires the usage conditions for an electric vehicle, including the required mileage, from user U who wishes to use an electric vehicle. The input data acquisition unit 132 notifies the selection unit 135 of the acquired usage conditions.

[0075] The mileage identification unit 133 identifies at least one of the first maximum mileage or second maximum mileage of multiple electric vehicles available to user U. The selection unit 135 compares the required mileage indicated by the usage conditions with at least one of the first maximum mileage or second maximum mileage corresponding to each of the multiple electric vehicles to select one or more electric vehicles available to user U from among the multiple electric vehicles.

[0076] If user U does not input a period for using the electric vehicle, the selection unit 135 compares the required mileage with the first maximum mileage and selects an electric vehicle whose first maximum mileage is greater than the required mileage. If user U does input a period for using the electric vehicle, the selection unit 135 compares the required mileage with the second maximum mileage on the second reference date corresponding to the input period and selects an electric vehicle whose second maximum mileage is greater than the required mileage. If user U does not input a period for using the electric vehicle, the selection unit 135 may select an electric vehicle whose second maximum mileage after a predetermined period (e.g., 5 years) is greater than the required mileage.

[0077] The display processing unit 134 displays information (e.g., vehicle number or vehicle model name) for identifying the electric vehicle selected by the selection unit 135 on the information terminal 2 as an electric vehicle recommended to user U. The display processing unit 134 may also display a first distance image and a second distance image on the information terminal 2 along with the information for identifying the electric vehicle.

[0078] Figure 9 shows an example of a screen for user U to input usage conditions. In Figure 9, area R5 is the area for user U to input the required mileage. Area R6 is the area for user U to input the intended use of the electric vehicle. Area R7 is the area for user U to input their base (i.e., reference location). After user U has entered the required mileage, intended use, and reference location, they press the "Search" button, at which point the selection unit 135 executes the selection process described above, and the display processing unit 134 displays the selection results.

[0079] Figure 10 shows an example of a screen displaying the selection results. The screen shown in Figure 10 contains the same content as the screen shown in Figure 2, but area R1 shows information for identifying the electric vehicle selected by the selection unit 135. Furthermore, if the selection unit 135 selects multiple electric vehicles, the display processing unit 134 displays an "Other Vehicles" button in area R1, and when user U presses the "Other Vehicles" button, it displays a first distance image and a second distance image corresponding to the other electric vehicles selected by the selection unit 135.

[0080] Furthermore, a "Research" button is displayed in area R1. When user U presses the "Research" button, the display processing unit 134 displays the screen shown in Figure 9 again. User U can then enter different conditions on the displayed screen and perform another search.

[0081] As described above, the information processing device 1a according to the second embodiment selects one or more electric vehicles that can be used by user U from among the multiple electric vehicles by comparing the required mileage indicated by the usage conditions with at least one of the first maximum mileage or second maximum mileage corresponding to each of the multiple electric vehicles. With the information processing device 1a configured in this way, user U can easily use the optimal electric vehicle without having to compare the first maximum mileage or second maximum mileage of many electric vehicles with the required mileage.

[0082] <Third Embodiment> [Deriving the conditions for using electric vehicles] In the above explanation, User U inputs the usage conditions for the electric vehicle. However, there may be discrepancies between the usage conditions for the electric vehicle assumed by User U and the usage conditions for the electric vehicle derived from the usage history of the vehicle managed by User U. If this discrepancy becomes large, there is a high risk that an electric vehicle that does not actually meet User U's usage conditions will be selected. Therefore, the information processing device 1b according to the third embodiment may derive the required mileage for User U and the mileage if the electric vehicle were to travel based on the usage history of the vehicle managed by User U, and present information based on the derived mileage to User U.

[0083] Figure 11 is a diagram illustrating the overview of the information processing system S in the third embodiment. The information processing system S further includes a managed vehicle V. The managed vehicle V is a vehicle managed by user U, and is, for example, a gasoline car, a PHEV (Plug-in Hybrid Electric Vehicle), or an electric vehicle. In this embodiment, the managed vehicle V will be described as a gasoline car. The managed vehicle V is equipped with a communication module for communicating with the information processing device 1b and a GPS (Global Positioning System) receiver for measuring the position of the managed vehicle V.

[0084] The information processing device 1b stores information about the vehicle. This information includes, for example, information made public by the vehicle manufacturer or an external organization other than the manufacturer, and includes at least performance values ​​(electricity consumption information indicating the electric vehicle's energy consumption, and information indicating the capacity of the battery installed in the electric vehicle). The performance values ​​are values ​​indicating the vehicle's performance as shown by catalog information (information such as the vehicle's performance and equipment as described in catalogs, etc.), and are, for example, information made public by the vehicle manufacturer or an external organization other than the manufacturer.

[0085] Furthermore, the information processing device 1b stores prediction parameters corresponding to the intended use of the electric vehicle for each intended use of the electric vehicle. The prediction parameters are parameters for predicting the energy consumption when the electric vehicle is driven for a predetermined purpose. The prediction parameters may also be parameters for predicting the fuel consumption when a gasoline vehicle is driven for a predetermined purpose. The prediction parameters are, for example, numerical values ​​represented by positive numbers less than or equal to 1.

[0086] The following describes the process by which the information processing system S presents information based on mileage to the user U. First, the information processing device 1b acquires mileage data from the managed vehicle V (Figure 11 (1)).

[0087] Driving data is GPS information received via a GPS receiver, which shows the location history of the managed vehicle V during a predetermined period. For example, it is data that associates location coordinates with the measurement time when those location coordinates were measured. The predetermined period is a set period, such as one week, one month, or one year.

[0088] If the managed vehicle V does not have a communication module and GPS receiver, the information processing device 1b may generate driving data based on regional information obtained from information managed in association with the managed vehicle V. Regional information includes, for example, data from a management ledger that manages the operation history of the managed vehicle V (e.g., history showing daily driving distance), maintenance data that records the state of the managed vehicle V when it is maintained (e.g., data that records the driving distance shown by the odometer at the time of maintenance), and interview data obtained by interviewing users of the managed vehicle V about their history of using the managed vehicle V (e.g., history showing the route traveled). The information processing device 1b generates driving data based, for example, one or a combination of data included in the regional information.

[0089] The information processing device 1b calculates the estimated energy consumption based on the energy consumption information of the candidate vehicle and the predicted parameters of the electric vehicle corresponding to the intended use of the managed vehicle V (Figure 11 (2)). The candidate vehicle is a candidate electric vehicle presented to the user U. The estimated energy consumption is the energy consumption expected if the candidate vehicle travels along the location history indicated by the driving data.

[0090] The information processing device 1b calculates a standard driving distance, which serves as the basis for the driving distance required for the candidate vehicle, based on the driving data (Figure 11 (3)). The standard driving distance is the standard driving distance, which serves as the basis for the driving distance required for the candidate vehicle.

[0091] The information processing device 1b calculates the maximum driving range at maximum charge based on the calculated estimated energy consumption and the capacity of the battery installed in the candidate vehicle (Figure 11 (4)). Then, the information processing device 1b displays information based on the driving standard distance and the driving range on the information terminal 2 (Figure 11 (5)).

[0092] In this way, the information processing system S can provide information indicating the performance required for user U's intended use of the electric vehicle, as well as information that closely reflects the performance when the user actually uses the electric vehicle. This allows user U to easily determine whether the presented candidate vehicles meet the performance requirements for their intended use of the electric vehicle. As a result, the information processing system S can reduce the risk of selecting an electric vehicle that does not meet the performance requirements for user U's intended use of the electric vehicle.

[0093] [Configuration of the information processing device 1b in the third embodiment] Figure 12 shows the configuration of the information processing device 1b according to the third embodiment. The information processing device 1b differs from the information processing device 1b shown in Figure 3 in that it further includes a driving data acquisition unit 136. In addition, the driving distance determination unit 133 also functions as a first calculation unit, a second calculation unit, and a third calculation unit.

[0094] The storage unit 12 stores information about the vehicle. This information includes, for example, performance values ​​of the electric vehicle (fuel efficiency information and battery capacity). The storage unit 12 may also store fuel efficiency information measured by a predetermined measurement method. Examples of predetermined measurement methods include the WLTC (Worldwide harmonized Light Vehicle Test Cycles) mode and the JC08 mode. The storage unit 12 also stores information about the managed vehicle V. This information includes, for example, information for the communication unit 11 to communicate with the managed vehicle V and the intended use of the managed vehicle V.

[0095] Furthermore, the memory unit 12 stores candidate vehicle information relating to candidate vehicles. Candidate vehicles are electric vehicles that are presented to the user as candidates. Candidate vehicles may include new cars or used cars. Candidate vehicle information includes, for example, the make and model year, battery capacity, the condition of the candidate vehicle (e.g., mileage, presence or absence of scratches, repair history, etc.), and the price of the candidate vehicle. Candidate vehicle information may also be processing standard data.

[0096] Furthermore, the memory unit 12 stores a parameter management database that manages prediction parameters. Figure 13 shows an example of the configuration of the parameter management database. As shown in Figure 13, the parameter management database stores the vehicle type, application, and prediction parameters in association.

[0097] The parameter management database may store predictive parameters corresponding to various types of information, not limited to the example shown in Figure 13. For example, the parameter management database may store predictive parameters corresponding to each predetermined measurement method.

[0098] Returning to Figure 12, the driving data acquisition unit 136 acquires driving data that shows the location history of the managed vehicle V during a predetermined period. The driving data acquisition unit 136 may acquire the driving data from the managed vehicle V, or it may acquire the driving data from an external device (not shown) that stores the driving data of the managed vehicle V.

[0099] The mileage determination unit 133 functions as a first calculation unit that calculates the estimated energy consumption expected when a candidate vehicle travels the route through the location history. The candidate vehicle may be a vehicle randomly selected from among multiple candidate vehicles, or it may be a vehicle among multiple candidate vehicles that meets predetermined conditions. The predetermined conditions may include, for example, that the candidate vehicle is of the same type as the managed vehicle V. Specifically, the mileage determination unit 133 calculates the estimated energy consumption expected when a candidate vehicle travels the route through the location history based on the energy consumption information of the candidate vehicle and the prediction parameters of the electric vehicle corresponding to the use of the managed vehicle V. The mileage determination unit 133 calculates the estimated energy consumption by executing the following steps from the first to the second step.

[0100] Firstly, the mileage identification unit 133 functions as an identification unit that identifies the purpose of the managed vehicle V based on the mileage data. For example, the purpose of the vehicle is defined by the assumed mileage ratio for each of several locations (e.g., urban areas, suburbs, highways, etc.) that are expected to be used when the vehicle is used for that purpose.

[0101] In this case, first, the mileage identification unit 133 calculates the mileage percentage that the managed vehicle V traveled to each of the multiple locations based on the travel data. Then, the mileage identification unit 133 identifies the use of the vehicle that corresponds to the estimated mileage percentage that is relatively close to the calculated mileage percentage (for example, the estimated mileage percentage that is closest to the calculated mileage percentage) from among the uses of the multiple vehicles. The mileage identification unit 133 is not limited to this, and may also identify the use of the vehicle that has a relatively large number of estimated mileage percentages that match the calculated mileage percentage (for example, the vehicle with the largest number of estimated mileage percentages that match the mileage percentage, or the vehicle with the largest number of estimated mileage percentages that fall within the range from the value indicated by the mileage percentage to a predetermined threshold). The mileage identification unit 133 may also identify the use of the managed vehicle V by acquiring information indicating the use specified by the user.

[0102] Secondly, the mileage determination unit 133 calculates the estimated energy consumption based on the energy consumption information of the candidate vehicle and the predicted parameters of the electric vehicle corresponding to the intended use of the identified management vehicle V. For example, the mileage determination unit 133 calculates the estimated energy consumption by multiplying the numerical value indicated by the energy consumption information of the candidate vehicle by the numerical value indicated by the predicted parameters stored in the parameter management database in association with the intended use of an electric vehicle equivalent to the intended use of the management vehicle V.

[0103] For example, if the storage unit 12 stores energy consumption information measured in WLTC mode corresponding to the candidate vehicle, the mileage determination unit 133 calculates the estimated energy consumption based on the energy consumption information measured in WLTC mode and the prediction parameters corresponding to WLTC mode. For example, if the storage unit 12 does not store energy consumption information measured in WLTC mode corresponding to the candidate vehicle, but stores energy consumption information measured in JC08 mode, the mileage determination unit 133 calculates the estimated energy consumption based on the energy consumption information measured in JC08 mode and the prediction parameters corresponding to JC08 mode.

[0104] Here, the assumed energy consumption varies depending on the type of electric vehicle. Therefore, the mileage determination unit 133 may further calculate the energy consumption rate based on prediction parameters corresponding to the type of electric vehicle.

[0105] Specifically, first, the driving data acquisition unit 136 acquires further information indicating the vehicle type of the managed vehicle V. For example, the driving data acquisition unit 136 refers to catalog information corresponding to the managed vehicle V and acquires information indicating the vehicle type of the managed vehicle V. The driving data acquisition unit 136 may also acquire information indicating the vehicle type of the managed vehicle V from the information terminal 2, vehicle registration data, vehicle management data managed by the user, etc.

[0106] The mileage determination unit 133 selects a candidate vehicle from among several candidate vehicles that is the same model as or similar to the managed vehicle V. The same model may include electric vehicles of the same make, while similar models may be defined as having similar vehicle height, width, length, body shape, etc. The mileage determination unit 133 then calculates the estimated energy consumption based on the energy consumption information of the selected candidate vehicle and the predicted parameters stored in the parameter management database, which are associated with the electric vehicle's use equivalent to that of the identified managed vehicle V. In this way, the information processing device 1b can improve the accuracy of calculating the estimated energy consumption.

[0107] The estimated electricity consumption differs depending on whether the air conditioner is used or not. Therefore, the mileage determination unit 133 may calculate the estimated electricity consumption corresponding to the use of the air conditioner and the use of the air conditioner. Specifically, the mileage determination unit 133 calculates the estimated electricity consumption when the air conditioner is used based on prediction parameters corresponding to the use of the air conditioner, and calculates the estimated electricity consumption when the air conditioner is not used based on prediction parameters corresponding to the non-use of the air conditioner.

[0108] The estimated electricity consumption may fluctuate from month to month. For example, since air conditioning is used in the summer and heating is used in the winter, the estimated electricity consumption may be worse than during periods when air conditioning or heating is not used (e.g., spring or autumn). Therefore, the mileage determination unit 133 may calculate the energy consumption rate based on different prediction parameters for each month. For example, the parameter management database stores prediction parameters associated with each month, and the mileage determination unit 133 calculates the estimated electricity consumption each month based on the prediction parameters stored in the parameter management database that are further associated with that month.

[0109] The mileage identification unit 133 functions as a second calculation unit that calculates a standard mileage that serves as the basis for the mileage required for the candidate vehicle. Specifically, the mileage identification unit 133 calculates a standard mileage that serves as the basis for the mileage required for the candidate vehicle based on the driving data. For example, the storage unit 12 stores standard mileage corresponding to each vehicle's intended use, and the mileage identification unit 133 calculates the standard mileage by identifying the standard mileage corresponding to the intended use of the managed vehicle V, which has been identified based on the driving data, from among the standard mileage stored in the storage unit 12.

[0110] The mileage identification unit 133 may calculate a statistical value of the mileage per predetermined period (e.g., one day) identified by the location history of the mileage data as the mileage reference distance. The statistical value may be, for example, the mean, mode, or median. The mileage identification unit 133 may also calculate the maximum value of the mileage per predetermined period identified by the location history of the mileage data as the mileage reference distance.

[0111] The mileage determination unit 133 functions as a third calculation unit that calculates the mileage available at maximum charge. Specifically, the mileage determination unit 133 calculates the mileage available at maximum charge based on the calculated estimated energy consumption and the battery capacity corresponding to the candidate vehicle. For example, the mileage determination unit 133 calculates the mileage available at maximum charge by multiplying the calculated estimated energy consumption by the battery capacity corresponding to the candidate vehicle.

[0112] The driving range of an electric vehicle varies depending on the degree of degradation of the battery installed in the electric vehicle. Therefore, the driving range determination unit 133 may calculate the driving range of a candidate vehicle at maximum charge based on the estimated energy consumption of the candidate vehicle and the degree of degradation of the battery installed in the candidate vehicle.

[0113] The degree of degradation of the battery installed in an electric vehicle is indicated, for example, by the battery performance shown in the processing reference data acquired by the reference data acquisition unit 131. Specifically, the mileage determination unit 133 calculates the mileage of the candidate vehicle at maximum charge based on the calculated estimated energy consumption of the candidate vehicle and the performance data associated with the battery performance shown in the processing reference data acquired by the reference data acquisition unit 131. In this way, the information processing device 1b can calculate the mileage according to the battery condition of the candidate vehicle.

[0114] The mileage determination unit 133 may calculate either the first maximum mileage or the second maximum mileage determined by referring to performance data as the mileage available when the candidate vehicle is fully charged, but it is preferable to calculate the second maximum mileage as the mileage available when the candidate vehicle is fully charged. By doing so, the information processing device 1b can reduce the occurrence of a situation where the mileage available later on falls below the standard mileage due to battery degradation while the user U is using the candidate vehicle.

[0115] The display processing unit 134 displays information on the information terminal 2 based on the driving standard distance and driving range calculated by the driving range identification unit 133. The display processing unit 134 may display the driving standard distance and driving range on the information terminal 2 in a manner that allows comparison, along with information about candidate vehicles, or it may display the difference between the driving standard distance and the driving range on the information terminal 2, or it may display information on the information terminal 2 indicating whether the candidate vehicle can travel the driving distance (driving standard distance) required by the user.

[0116] The display processing unit 134 may display on the information terminal 2 the remaining driving distance when the air conditioner is used and the remaining driving distance when the air conditioner is not used. The display processing unit 134 may also display on the information terminal 2 the remaining driving distance for each month. The display processing unit 134 may also display on the information terminal 2 the estimated energy consumption.

[0117] The display processing unit 134 may present to user U a candidate vehicle that meets user U's usage conditions from among multiple candidate vehicles. Specifically, first, the mileage determination unit 133 calculates the maximum mileage for each of the multiple candidate vehicles at maximum charge based on the fuel efficiency information of each candidate vehicle and the battery capacity corresponding to each candidate vehicle. Then, the display processing unit 134 displays as presented information the candidate vehicles whose mileage is equal to or greater than the mileage standard distance from among the multiple candidate vehicles. In this way, the information processing device 1b can present to user U a candidate vehicle that meets user U's usage conditions.

[0118] The display processing unit 134 may present to the information terminal 2 any candidate vehicles that meet additional conditions other than the candidate vehicle's drivable distance being equal to or greater than the drivable distance standard. For example, first, the drivable distance identification unit 133 calculates the expected fuel consumption that would be expected if the managed vehicle V traveled the location history indicated by the drivable data, based on the fuel consumption included in the catalog information of the managed vehicle V and the prediction parameters corresponding to the intended use of the managed vehicle V. The drivable distance identification unit 133 refers to the fuel consumption / electricity consumption conversion data and converts the calculated expected fuel consumption into the electric vehicle's conversion electricity consumption. The fuel consumption / electricity consumption conversion data is data in which the fuel consumption and electricity consumption are associated for each fuel consumption. Then, the drivable distance identification unit 133 presents to the information terminal 2 any candidate vehicles whose expected fuel consumption is equal to or greater than the conversion electricity consumption.

[0119] Furthermore, the mileage determination unit 133 calculates the battery capacity required to travel the standard distance based on the conversion energy consumption and the standard distance traveled, and presents to the information terminal 2 the candidate vehicles whose installed battery capacity is equal to or greater than the calculated battery capacity. In this way, the information processing device 1b can reduce the occurrence of situations in which it presents candidate vehicles whose remaining range is less than or equal to the standard distance traveled.

[0120] Before calculating the energy consumption of each candidate vehicle, the information processing device 1b may select candidate vehicles from among multiple electric vehicles that closely match the specifications of the managed vehicle V. The specifications of the managed vehicle V include, for example, body type (truck, van, passenger car, etc.), body color, maximum number of passengers, load capacity, vehicle height, etc. Specifically, the selection unit 135 selects electric vehicles from among multiple electric vehicles that meet at least some of the specifications of the managed vehicle as candidate vehicles. The selection unit 135, for example, refers to catalog information of the managed vehicle V and multiple electric vehicles and selects electric vehicles from among multiple electric vehicles in which the number of specifications matching those of the managed vehicle V is above a predetermined threshold as candidate vehicles. Subsequently, the mileage determination unit 133 calculates the mileage of the candidate vehicles selected by the selection unit 135. In this way, the information processing device 1b can present candidate vehicles from among candidate vehicles that closely match the specifications of the managed vehicle V.

[0121] The display processing unit 134 displays candidate vehicle information corresponding to the candidate vehicle stored in the storage unit 12 as presented information. In this way, the information processing device 1b can provide information to allow user U to consider whether or not to switch from the managed vehicle V to a candidate vehicle.

[0122] The display processing unit 134 may present information regarding the running costs of the managed vehicle V and the candidate vehicle to the user U as presented information. Specifically, the display processing unit 134 displays the comparison result of comparing the first running cost based on the energy consumed by the managed vehicle V with the second running cost based on the electricity consumed by the candidate vehicle as presented information on the information terminal 2.

[0123] The display processing unit 134 displays, for example, the difference between the gasoline cost of the managed vehicle V and the charging cost of the candidate vehicle over a predetermined period on the information terminal 2. In this way, the information processing device 1b can recognize how much the running costs will change if it switches from the managed vehicle V to the candidate vehicle.

[0124] The display processing unit 134 may present information regarding the CO2 emissions of the managed vehicle V and the candidate vehicle to the information terminal 2. Specifically, the display processing unit 134 displays the comparison result of the CO2 emissions generated by producing the energy consumed by the managed vehicle V and the CO2 emissions generated by producing the electricity consumed by the candidate vehicle as presented information.

[0125] For example, the memory unit 12 stores the amount of CO2 generated when producing 1 liter of gasoline and the amount of CO2 generated when producing 1 kWh of electricity. In this case, the display processing unit 134 displays on the information terminal 2 the comparison result between a first CO2 emission calculated based on the amount of gasoline consumed by the managed vehicle V over a predetermined period and the amount of CO2 corresponding to the gasoline stored in the memory unit 12, and a second CO2 emission calculated based on the amount of electricity consumed by the candidate vehicle over a predetermined period and the amount of CO2 corresponding to the electricity stored in the memory unit 12. In this way, the information processing device 1b can recognize how much environmental contribution can be made by switching from the managed vehicle V to the candidate vehicle.

[0126] Figure 14 shows an example of a screen that displays the information to be presented. The screen shown in Figure 14 displays information about one candidate vehicle. If there are multiple candidate vehicles to present to the user, information about each of the multiple candidate vehicles may be displayed.

[0127] In the upper left region R8 of Figure 14, candidate vehicle information corresponding to the candidate vehicle is displayed. In region R9 to the right of region R8, the electricity consumption and driving range depending on whether the air conditioner is ON or OFF are displayed. In the upper right region R10 of Figure 14, the running cost reduction amount and the amount of CO2 reduction amount when switching from managed vehicle V to candidate vehicle are displayed. In addition, in the lower region R11 of Figure 14, the monthly running costs of managed vehicle V and candidate vehicle are displayed. In this way, the information processing device 1b presents information on candidate vehicles and presents the results of comparing managed vehicle V and candidate vehicles, making it easy for user U to understand the benefits of switching from managed vehicle V to candidate vehicle.

[0128] [Processing flow of the information processing device 1b in the third embodiment] Figure 15 is a flowchart showing the processing flow in the information processing device 1b in the third embodiment. The flowchart shown in Figure 15 starts when the driving data acquisition unit 136 acquires driving data of the managed vehicle V (S21).

[0129] The mileage identification unit 133 identifies the use of the managed vehicle V based on the mileage data acquired by the mileage data acquisition unit 136 (S22). The mileage identification unit 133 calculates the estimated energy consumption based on the energy consumption information of the candidate vehicle and the predicted parameters corresponding to the use of an electric vehicle equivalent to the use of the identified managed vehicle V (S23).

[0130] The mileage determination unit 133 calculates a standard mileage based on the driving data, which serves as the required mileage for the candidate vehicle (S24). The mileage determination unit 133 calculates the maximum mileage at maximum charge based on the calculated estimated energy consumption and the battery capacity corresponding to the candidate vehicle (S25). The display processing unit 134 then displays information based on the standard mileage and mileage calculated by the mileage determination unit 133 on the information terminal 2 (S26).

[0131] [Effects of the information processing device 1b in the third embodiment] As explained above, the information processing device 1b calculates the estimated energy consumption based on the energy consumption information of the candidate vehicle and the predicted parameters of the electric vehicle corresponding to the intended use of the managed vehicle V. It then displays information on the information terminal 2 based on the calculated driving range calculated from the driving standard distance and the battery capacity of the candidate vehicle, and the driving standard distance calculated from the driving data. In this way, the information processing device 1b can provide information indicating the performance required for the electric vehicle's intended use by user U, and information that is close to the performance when the user actually uses the electric vehicle. As a result, user U can easily understand whether the presented candidate vehicle meets the performance requirements for the electric vehicle's intended use by user U. Consequently, the information processing device 1b can reduce the risk of selecting an electric vehicle that does not meet the performance requirements for the electric vehicle's intended use by user U.

[0132] Although the present invention has been described above using embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments, and various modifications and changes are possible within the scope of its gist. For example, all or part of the apparatus can be configured by functionally or physically distributing and integrating in any unit. Furthermore, new embodiments resulting from any combination of multiple embodiments are also included in the embodiments of the present invention. The effects of the new embodiments resulting from the combinations are combined with the effects of the original embodiments. [Explanation of symbols]

[0133] 1. Information Processing Device 2 Information terminals 11 Communications Department 12 Storage section 13 Control Unit 131 Reference Data Acquisition Unit 132 Input Data Acquisition Unit 133 Mileage Identification Section 134 Display Processing Unit 135 Selection Section 136 Driving data acquisition unit

Claims

1. An acquisition unit that acquires driving data showing the location history of a managed vehicle operated by a user over a predetermined period, A storage unit that stores the battery capacity of each electric vehicle, stores prediction parameters for predicting the fuel efficiency of each gasoline vehicle when it is driven for the purpose of a gasoline vehicle, and stores fuel-to-electricity conversion data that associates the fuel efficiency of the gasoline vehicle with the electric vehicle's energy consumption for each gasoline vehicle's energy consumption, A unit that identifies the use of the managed vehicle based on the aforementioned driving data or information indicating the use specified by the user, A first calculation unit calculates the expected fuel consumption when the managed vehicle travels the location history based on the fuel consumption included in the catalog information of the managed vehicle and the predicted parameters of the gasoline vehicle corresponding to the use of the managed vehicle identified by the identification unit, and converts the expected fuel consumption to the electricity consumption by referring to the fuel consumption-electricity conversion data. A second calculation unit calculates a standard driving distance, which serves as the driving distance required for a candidate electric vehicle, which is a candidate vehicle presented to the user, based on the aforementioned driving data. A third calculation unit calculates the driving range at maximum charge based on the estimated energy consumption converted by the first calculation unit and the battery capacity corresponding to the candidate vehicle, A display processing unit that displays information based on the aforementioned driving reference distance and the aforementioned driving range on a display device, An information processing device having

2. The memory unit further stores the prediction parameters defined for each type of gasoline vehicle, The first calculation unit further calculates the estimated energy consumption based on the prediction parameters corresponding to the vehicle type of the candidate vehicle. The information processing apparatus according to claim 1.

3. The memory unit further stores the energy consumption information of each electric vehicle, The second calculation unit calculates the maximum driving range of each of the multiple candidate vehicles at maximum charge based on the fuel consumption information of each of the multiple candidate vehicles and the battery capacity corresponding to each of the multiple candidate vehicles. The display processing unit displays, among the plurality of candidate vehicles, the candidate vehicle whose drivable distance is equal to or greater than the drivable standard distance, as the presented information. The information processing apparatus according to claim 1 or 2.

4. The third calculation unit further calculates the driving range of the candidate vehicle at maximum charge based on the degree of degradation of the battery installed in the candidate vehicle. The information processing apparatus according to any one of claims 1 to 3.

5. The storage unit further stores candidate vehicle information, including the status of the candidate vehicle and the price of the candidate vehicle. The display processing unit displays the candidate vehicle information corresponding to the candidate vehicle as the presented information. The information processing apparatus according to any one of claims 1 to 4.

6. The display processing unit displays the comparison result, obtained by comparing the running cost based on the energy consumed by the managed vehicle with the running cost based on the electricity consumed by the candidate vehicle, as previously displayed information. The information processing apparatus according to any one of claims 1 to 5.

7. The display processing unit displays the comparison result, obtained by comparing the CO2 generated in accordance with the energy consumed by the managed vehicle and the CO2 generated in accordance with the electricity consumed by the candidate vehicle, as the displayed information. The information processing apparatus according to any one of claims 1 to 6.

8. The system further includes a selection unit that selects, from among multiple electric vehicles, an electric vehicle that meets at least some of the specifications of the managed vehicle as the candidate vehicle. The information processing apparatus according to any one of claims 1 to 7.

9. A computer having a storage unit that stores the battery capacity of each electric vehicle, stores prediction parameters for predicting the fuel efficiency of each gasoline vehicle when it is driven for the purpose of a gasoline vehicle, and stores fuel-to-electricity conversion data that associates the fuel efficiency of the gasoline vehicle with the electric vehicle's energy consumption for each gasoline vehicle's energy consumption, executes the following: The steps include: acquiring driving data that shows the location history of the managed vehicle driven by the user during a predetermined period; A step of identifying the use of the managed vehicle based on the aforementioned driving data or information indicating the use specified by the user, The steps include: calculating the expected fuel consumption when the managed vehicle travels the location history, based on the fuel consumption included in the catalog information of the managed vehicle and the predicted parameters of the gasoline vehicle corresponding to the identified use of the managed vehicle; The steps include: converting the assumed fuel consumption to the electricity consumption by referring to the fuel consumption conversion data; Based on the aforementioned driving data, the steps include: calculating a standard driving distance that serves as the required driving distance for a candidate electric vehicle to be presented to the user; A step of calculating the driving range at maximum charge based on the converted estimated energy consumption and the battery capacity corresponding to the candidate vehicle, The steps include displaying information based on the aforementioned driving standard distance and the aforementioned driving range on a display device, An information processing method having

10. A computer having a storage unit that stores the battery capacity of each electric vehicle, predictive parameters for predicting the fuel consumption of each gasoline vehicle when it is driven for the purpose of a gasoline vehicle, and fuel-to-electricity conversion data that associates the fuel consumption of the gasoline vehicle with the electric vehicle's energy consumption for each gasoline vehicle's fuel consumption, Acquisition unit that acquires driving data showing the location history of managed vehicles operated by the user over a predetermined period. A specific unit identifies the use of the managed vehicle based on the aforementioned driving data or information indicating the use specified by the user. A first calculation unit calculates the expected fuel consumption when the managed vehicle travels the location history based on the fuel consumption included in the catalog information of the managed vehicle and the predicted parameters of the gasoline vehicle corresponding to the use of the managed vehicle identified by the identification unit, and converts the expected fuel consumption to the electricity consumption by referring to the fuel consumption-electricity conversion data. A second calculation unit calculates a standard driving distance, which serves as the required driving distance for a candidate electric vehicle presented to the user, based on the aforementioned driving data. A third calculation unit calculates the driving range at maximum charge based on the estimated energy consumption converted by the first calculation unit and the battery capacity corresponding to the candidate vehicle, and A display processing unit that causes a display device to display information based on the aforementioned driving reference distance and the aforementioned driving range. A program designed to function as such.

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