WO2017022010A1

WO2017022010A1 - Charging assistance method and charging assistance device for electric vehicle

Info

Publication number: WO2017022010A1
Application number: PCT/JP2015/071785
Authority: WO
Inventors: 誠秀中村
Original assignee: 日産自動車株式会社
Priority date: 2015-07-31
Filing date: 2015-07-31
Publication date: 2017-02-09
Also published as: JPWO2017022010A1; JP6531827B2

Abstract

Provided is an electric vehicle charging assistance method capable of providing beneficial information for predicting the congestion of a charging spot. On the basis of probe data, planned travel routes are estimated for each of a plurality of electric vehicles (30), and on the basis of the estimated planned travel route information, the positions of each of the plurality of electric vehicles (30) at an arbitrary point in time are estimated. On the basis of the estimated position information, a map of charging needs in an arbitrary information provision area is estimated, and when an electric vehicle (α) makes a request for the provision of information, the estimated charging needs map is presented on a display (31b) of the electric vehicle (α) that made the information provision request.

Description

Electric vehicle charging support method and charging support device

The present invention relates to a charging support method and a charging support device for an electric vehicle in a probe data utilization system that collects and processes probe data and outputs processed data according to a request.

2. Description of the Related Art Conventionally, there is known a charging support method that searches for charging spots that exist around the electric vehicle in response to a request from the electric vehicle and presents information on the charging spots that the electric vehicle can reach (for example, Patent Document 1).

JP 2012-251989

Here, the user of the electric vehicle feels stress when a waiting time longer than expected occurs between the time when the user reaches the charging spot and the time when charging is actually started. Therefore, there is a need to know how crowded the charging spot is when it reaches the charging spot.
However, the conventional charging support method only presents information on a charging spot that can be reached by the electric vehicle, and does not take into consideration any travel time to the charging spot. Therefore, when the electric vehicle actually reaches the charging spot, it is assumed that the charging spot is congested and the charging waiting time becomes longer than expected.

The present invention has been made paying attention to the above problem, and an object thereof is to provide a charging support method and a charging support device for an electric vehicle that can provide useful information for predicting the degree of congestion of charging spots. And

In order to achieve the above object, the present invention processes a database that stores probe data including position information and remaining charge information of an electric vehicle, and probe data read from the database, and processes it in response to a request from the electric vehicle. And a server for outputting completed data to the electric vehicle.
The server first estimates a planned travel route for each of the plurality of electric vehicles based on the probe data. Then, based on the estimated planned route information, the position of each of the plurality of electric vehicles at an arbitrary time is estimated. Furthermore, the distribution of charging needs in an arbitrary area is estimated based on the estimated position information.
Thereafter, when an information presentation request from the electric vehicle is generated, the estimated distribution of the charging needs is presented on the display of the electric vehicle that has made the information presentation request.

Therefore, in the present invention, when the information presentation request is output to the server when predicting the congestion of the charging spots to be used, the distribution of charging needs in an arbitrary area (such as an area around the charging spots to be used) can be obtained. I can know.
Here, it is conceivable that the higher the charging needs, the higher the likelihood of charging spots. That is, if the distribution of charging needs can be grasped, it is possible to predict at which point the charging spot is crowded, and it is possible to predict the degree of congestion of the charging spot when the user arrives at the charging spot that the user wants to use. .
As a result, it is possible to provide useful information for predicting the degree of congestion of the charging spot.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is an overall system diagram showing a probe data utilization system having a charging support device according to a first embodiment. It is an image figure of the point sequence data shown based on probe data. 4 is a flowchart illustrating a flow of charging support information presentation processing executed by the charging support device according to the first embodiment. In the charging assistance information presentation process of Example 1, it is explanatory drawing which shows the setting step of an information presentation area. In the charge assistance information presentation process of Example 1, it is explanatory drawing which shows the detection step of an electric vehicle. In the charging assistance information presentation process of Example 1, it is explanatory drawing which shows the scheduled driving | running route estimation step of an electric vehicle. In the charging assistance information presentation process of Example 1, it is explanatory drawing which shows the future position and remaining charge estimation step of an electric vehicle. FIG. 6 is an explanatory diagram illustrating a charging needs map creation step in the charging support information presentation process according to the first embodiment. FIG. 6 is an explanatory diagram illustrating an example of a charging need map presented in the charging support information presentation process according to the first embodiment.

Hereinafter, the form for implementing the charge assistance method and charge assistance apparatus of the electric vehicle of this invention is demonstrated based on Example 1 shown in drawing.

Example 1
First, the configuration of the charging support device for an electric vehicle according to the first embodiment will be described by dividing it into “a whole system configuration” and “a charging support information presentation processing configuration”.

[Entire system configuration]
FIG. 1 is an overall system diagram illustrating a probe data utilization system including the charging support apparatus according to the first embodiment. The overall system configuration of the embodiment will be described below with reference to FIG.

The probe data utilization system 1 according to the first embodiment includes a server 10 and a database 20 as shown in FIG.

The server 10 is a computer that performs everything from collecting probe data to processing the collected probe data and outputting the processed data. As illustrated in FIG. 1, the server 10 includes a probe data collection unit 11, a data processing unit 12, a processed data storage unit 13, and a communication unit 14.

The probe data collection unit 11 collects probe data of the electric vehicle 30 by receiving probe data transmitted from a large number of electric vehicles 30 and storing the received probe data in the database 20.
The electric vehicle 30 is a vehicle (an electric vehicle or a plug-in hybrid vehicle) that has a motor as a travel drive source and can be charged from the outside.

On the other hand, probe data includes an identification number (vehicle ID) assigned to each electric vehicle 30, position information obtained from GPS (Global Positioning System) mounted on each electric vehicle 30, charge remaining amount information, Here, at least point sequence data, trip data, and charge data are included. The point sequence data, trip data, and charge data are stored in the database 20 in association with the vehicle ID.

The point sequence data is data transmitted from each electric vehicle 30 at regular intervals (for example, 30 seconds) from ignition ON to ignition OFF, and includes data transmission time, data transmission position, travel distance, and remaining charge. Consist of quantity.
Here, the “data transmission position” is information (position information) indicating the position of the electric vehicle 30 when data is transmitted, and is indicated by latitude and longitude. The “travel distance” is the distance from the position where the previous data was transmitted to the position where the current data was transmitted. The “remaining charge amount” is the remaining battery charge when data is transmitted, and increases or decreases by repeatedly charging and running.
The “remaining charge amount” is the remaining charge information. Further, when “data transmission positions” shown on the map are connected in time series based on the point sequence data, the movement trajectory information as shown in FIG. 2 is obtained.

The trip data is data that is transmitted only once from each electric vehicle 30 between ignition ON and ignition OFF, and includes departure time, arrival time, departure position, arrival position, total travel distance, and total power consumption. .
Here, the “departure time” is the time when the ignition is turned on. “Arrival time” is the time when the ignition is turned off. The “departure position” is the position of the vehicle when the ignition is turned on. The “arrival position” is the position of the vehicle when the ignition is turned off. The “departure position” and “arrival position” are indicated by latitude and longitude. The “total travel distance” is the distance from the position where the ignition is turned on to the position where the ignition is turned off, and is the sum of the “travel distance” in the point sequence data. “Total power consumption” is the amount of power consumed from when the ignition is turned on to when the ignition is turned off.

The charge data is data transmitted every time the electric vehicle 30 performs external charging, and includes a charge position, a charge start time, a charge completion time, a charge power amount, and a charge type.
Here, the “charge position” is a position where external charging has been performed, and is indicated by latitude and longitude. “Charge type” is data indicating a charging method such as normal charging or rapid charging.

The data processing unit 12 reads the probe data stored in the database 20 and performs information processing such as charging support information presentation processing described later using the read probe data. Then, the processed data is output to the processed data storage unit 13.

The processed data storage unit 13 stores the data processed by the data processing unit 12 in the database 20 again.

The communication unit 14 is an external communication mechanism that performs communication with a specific electric vehicle 30 (α in FIG. 1). When the communication unit 14 receives the information presentation request transmitted from the electric vehicle α, the communication unit 14 reads necessary information from the processed data stored in the database 20 and is necessary for the electric vehicle α that has output the information presentation request. Information is sent.
In addition, the electric vehicle 30 has the control part 31a which can communicate with the communication part 14 of the server 10, and the display 31b which can display the information received by the control part 31a. That is, the information transmitted from the communication unit 14 to the electric vehicle 30 is presented on the display 31b.

The database 20 is a memory capable of transmitting / receiving data to / from the server 10. In this database 20, in addition to probe data obtained from a plurality of electric vehicles 30, map data, charging spot data including charging spot installation positions and charging type information, processed data, and the like are stored.

[Charging support information presentation processing configuration]
FIG. 3 is a flowchart illustrating the flow of the charging support information presentation process executed by the charging support apparatus according to the first embodiment. Hereinafter, the charging support information presentation processing configuration of the first embodiment will be described with reference to FIG.

In step S1, it is determined whether or not a request for charging needs information (charging needs information presentation request) has been transmitted from the electric vehicle α. If YES (information presentation request is present), the process proceeds to step S2. If NO (information presentation request is absent), step S1 is repeated.
Here, the charging need information presentation request is made by the user of the electric vehicle α operating the control unit 31a mounted on the electric vehicle α, for example, by tapping an icon displayed on the display 31b. Sent. Further, the charging need information presentation request is received by the communication unit 14.

In step S2, following the determination that there is an information presentation request in step S1, an “information presentation area” that is an area for presenting a charging need state is set, and the process proceeds to step S3.
Here, the “information presentation area” can be arbitrarily set. Here, as shown in FIG. 4A, any point selected by the user of the electric vehicle α (a point indicated by a circular icon in FIG. 4A). ) In the predetermined range. Note that the degree of the predetermined range (how far the “predetermined range” is set) is arbitrarily set. In addition, the selection point that serves as a reference when setting the “information presentation area” is transmitted from the electric vehicle α together with the charging needs information presentation request.

In step S3, following the setting of the information presentation area in step S2, the information presentation area set in step S2 (area surrounded by a broken line in FIG. 4B) and the peripheral area of the information presentation area (broken line in FIG. 4B) The electric vehicle 30 existing in the area surrounding the area surrounded by (indicated by a black circle in FIG. 4B) is detected, and the process proceeds to step S4.
Here, the presence of the electric vehicle 30 is detected based on position information from the GPS mounted on each electric vehicle 30. The extent of the peripheral area (how far is the “peripheral area”) is arbitrarily set.

In step S4, following detection of the electric vehicle 30 in step S3, one of the detected electric vehicles 30 is selected (referred to as 30A in FIG. 4C), and a route (scheduled travel) in which the electric vehicle 30A will travel in the future is selected. Route) (indicated by a thick black line in FIG. 4C), the process proceeds to step S5. That is, step S4 corresponds to a travel route estimation unit that estimates each planned travel route of the plurality of electric vehicles 30 based on the probe data.
Here, the estimated travel route is estimated based on the travel history of the electric vehicle 30A stored in the database 20 as probe data, the scheduler (destination information) of the electric vehicle 30A, and the like.

In step S5, following the estimation of the planned travel route in step S4, the position of the electric vehicle 30A that estimated the planned travel route in step S4 on the planned travel route at an arbitrary time (indicated by a double circle in FIG. 4D). ) And the remaining charge (SOC) at that time (indicated by numerals in FIG. 4D), and the process proceeds to step S6. That is, this step S5 corresponds to vehicle position estimation means for estimating the position of each of the plurality of electric vehicles 30 at an arbitrary point of time based on the estimated planned route information.
Here, the “arbitrary time point” is a time arbitrarily set such as “4 hours from now” or “8 pm”. The “arbitrary time” includes “current”. The “arbitrary time” may be set in advance or may be designated by the user of the electric vehicle α. When designated by the user of the electric vehicle α, the time information for setting the “arbitrary time” is transmitted from the electric vehicle α together with the charging needs information presentation request. Further, the “arbitrary time point” may be not only one arbitrary time point but also a plurality of time points.
The position of the electric vehicle 30A at an arbitrary time point is estimated based on the current location of the electric vehicle 30A, the planned travel route, the travel history, traffic information (congestion information), and the like. In addition, the remaining charge amount of the electric vehicle 30A at an arbitrary time point is estimated based on the current remaining charge amount of the electric vehicle 30A, the charge prediction estimated from the charge history, the average power consumption, the charge schedule, and the like.

In step S6, following the estimation of the position and remaining charge of the electric vehicle 30A at an arbitrary time in step S5, the electric motor detected to be present in the information presentation area set in step S2 and the peripheral area of the information presentation area. For all of the vehicles 30, it is determined whether or not the estimated travel route, the position at an arbitrary time, and the estimation of the remaining charge amount have been completed. If YES (estimation complete), the process proceeds to step S7. If NO (estimation incomplete), the process returns to step S4.

In step S7, following the determination that the estimation is completed in step S6, a charging needs map at an arbitrary time set in step S5 is created, and the process proceeds to step S8. That is, this step S7 corresponds to charging needs distribution estimation means for estimating the distribution of charging needs in an arbitrary area (information presentation area) based on the estimated position information of the electric vehicle 30.
Here, the “charging needs map” is information that displays on the map the distribution of charging needs at an arbitrary point in the information presentation area set in step S2. Here, the position of each electric vehicle 30 at the arbitrary point of time estimated in step S5 is indicated by a square icon on the map, and each square icon is colored with a color set according to the estimated remaining charge. Create a charging needs map.
That is, the remaining charge level is divided into a plurality of stages, and each stage is color-coded so as to gradually change from a warm color to a cold color from the smaller charge level to the larger charge level. As a result, as shown in an enlarged view in FIG. 4E, the icon indicating the position of a vehicle with a small remaining charge (for example, 40% or less) is colored with a warm color such as red (indicated by diagonal lines in FIG. 4E), An icon indicating the position of a vehicle having a large amount (for example, 70% or more) is colored in a cool color such as blue (shown in white in FIG. 4E). Furthermore, the icon indicating the position of a vehicle (for example, 40% to 70%) with a medium remaining charge is colored with an intermediate color such as green (indicated by dots in FIG. 4E). And about the many electric vehicles 30, by coloring the square icon which shows the position of the said electric vehicle 30 with the color according to charge remaining, as shown to FIG. The distribution of the remaining amount is displayed on the map in a rain cloud radar style.
At this time, it can be estimated that the charging needs increase as the density of the electric vehicle 30 increases. Moreover, it can be estimated that the electric vehicle 30 having a small remaining charge has a higher charging need. For this reason, displaying the distribution of the position of the electric vehicle 30 and the distribution of the remaining charge amount displays the distribution of charging needs on a map.

In step S8, following the creation of the charging needs map in step S7, the charging needs map created in step S7 is output to the electric vehicle α that transmitted the charging needs information presentation request, and is mounted on the electric vehicle α. Is displayed on the display 31b, and the process proceeds to step S9. That is, in step S8, when an information presentation request from the electric vehicle α is generated, the estimated charging needs distribution (charging needs map) is presented on the display 31b of the electric vehicle α that has made the charging needs information presentation request. It corresponds to the charging needs presentation means.
Thereby, the user of the electric vehicle α can grasp the distribution of charging needs at an arbitrary time point in the information presentation area.

In step S9, following the presentation of the charging needs map in step S8, was one charging spot selected by the user of the electric vehicle α from among the charging spots installed in the information presentation area indicated in the charging needs map? Judge whether or not. If YES (charging spot is selected), the process proceeds to step S10. If NO (charging spot is not selected), the process proceeds to the end.
Here, the charging spot is selected by, for example, displaying an icon indicating the position of the charging spot on the charging needs map and tapping one of the displayed charging spot icons (not shown here). The

In step S10, following the selection of the charging spot in step S9, the charging waiting time at an arbitrary time (the time set in step S5) at the charging spot selected in step S9 is calculated, and step S11 is performed. Proceed to
Here, the calculation of the charging waiting time is performed using statistical data of past usage history at the charging spot, a queue, and the like.

In step S11, following the calculation of the charging waiting time in step S10, an appropriate time (recommended departure time) for departure toward the charging spot selected in step S9 is set as the charging waiting time calculated in step S10. And the process proceeds to step S12.
Here, the “recommended departure time” is a departure time for arriving at a selected charging spot with a short charging waiting time. In order to calculate the “recommended departure time”, first, an addition time corresponding to the charging waiting time is set in advance. Then, an addition time corresponding to the charging waiting time is added to the travel time from the current point of the electric vehicle α to the arrival at the charging spot. Then, the “recommended departure time” is calculated by subtracting the corrected travel time from the recommended arrival time (a time zone in which the charging waiting time becomes shorter).

In step S12, following calculation of the recommended departure time in step S11, the electric vehicle α that has transmitted the charging needs information presentation request includes the charging waiting time calculated in step S10 and the recommended departure time calculated in step S11. Is displayed on the display 31b mounted on the electric vehicle α and proceeds to the end.
Thereby, the user of the electric vehicle α can grasp the charging waiting time at an arbitrary time point in the selected charging spot and the recommended departure time (recommended departure time) toward the charging spot.

Next, the operation will be described.
First, “basic requirements and problems of electric vehicle users” will be described, and subsequently, “charging support action” of the charging support device of the first embodiment will be described.

[Basic requirements and issues of electric vehicle users]
An electric vehicle such as an electric vehicle or a plug-in hybrid having a motor serving as a travel drive source requires external charging (external charging) for a battery that supplies electric power to the motor. Therefore, the user of the electric vehicle moves the vehicle to a charging spot set in various places as necessary, and charges the battery.

At this time, the electric vehicle user has a basic request to start charging immediately after arriving at the charging spot. In other words, when performing external charging, there is a demand for not spending time other than charging.
On the other hand, when presenting the charging spots installed around the current location of the host vehicle, a charging support device that presents full information on each charging spot and guides the empty charging spots can be considered. However, the fullness information in this case is information at the time when the charging spot is searched. For this reason, when the user of the electric vehicle moves to the guided charging spot, the full state changes, and a waiting time may occur.

On the other hand, even if a waiting time occurs before the start of charging, it is known that if the waiting time is less than expected, the electric vehicle user is less likely to feel stress. That is, if the difference between the assumed waiting time and the actual waiting time is small, the stress felt by the user of the electric vehicle is small.

On the other hand, a charging support apparatus that predicts a future full state using the usage history of each charging spot and presents this predicted full space information is conceivable. Thus, when the future full state is predicted, the degree of congestion of the charging spot can be predicted in consideration of the travel time of the electric vehicle. However, when the full state of the charging spot is predicted based on the usage history, the charging needs around the charging spot are not taken into consideration, and it is considered that the prediction of the full state greatly deviates.
That is, since the charge remaining amount of the electric vehicles other than the own vehicle is not grasped at all, the charging needs of each electric vehicle are completely unknown. Therefore, if there are many electric vehicles that are going to use the charging spot other than the own vehicle around the charging spot that the electric vehicle user wanted to use, the charging waiting time becomes longer than expected. Therefore, it is conceivable that the electric vehicle user feels a strong stress.

[Charging support function]
In the first embodiment, the electric vehicle user operates the control unit 31a mounted on the vehicle, and requests the communication unit 14 included in the server 10 of the probe data utilization system 1 to present charging needs information (hereinafter referred to as “charging needs”). Information request ”). Here, a charging needs information presentation request is transmitted by touching an icon displayed on the display 31b.

Then, when the communication unit 14 receives the charging needs information presentation request, in the flowchart shown in FIG. 3, the process proceeds from step S1 to step S2, and the data processing unit 12 included in the server 10 of the probe data utilization system 1 performs the information presentation area. Is set. Here, as shown in FIG. 4A, a predetermined range centered on an arbitrary position (position indicated by a circular icon in FIG. 4A) selected by the user of the electric vehicle α is set as an “information presentation area”.

Next, the process proceeds from step S3 to step S4, and as shown in FIG. 4B, the information presenting area and the electric vehicle 30 existing in the peripheral area of the information presenting area are detected. Then, as shown in FIG. 4C, the estimated traveling route of one arbitrarily selected electric vehicle 30A is estimated.

Further, the process proceeds to step S5, and as shown in FIG. 4D, the position of the selected electric vehicle 30A at an arbitrary time point and the remaining charge (SOC) at that time are estimated. As a result, it can be ascertained where the electric vehicle 30A is present at an arbitrary time (for example, 6 hours later) and how much charge is left at that time.

Then, for all the electric vehicles 30 existing in the information presentation area and the surrounding area of the information presentation area, the estimated travel route is estimated, and the position and the remaining charge amount are estimated at an arbitrary time point. When each estimation is completed in the vehicle 30, the process proceeds from step S6 to step S7, and the charging needs shown in FIG. 4F are obtained by color-coding the icon indicating the position of each electric vehicle 30 for each remaining charge (see FIG. 4E). A map is created. And it progresses to step S8 and a charging needs map is displayed on the display 31b which the electric vehicle (alpha) which performed the charging needs information presentation request | requirement has.

This charging needs map is information in which the position of an electric vehicle at an arbitrary time is color-coded according to the remaining charge and displayed on the map, and shows the distribution of charging needs at an arbitrary time. That is, the distribution of needs for the electric vehicle user's charging can be presented in a rain cloud radar style, and the user of the electric vehicle α can grasp the charging needs around the charging spot to be used.
Thereby, the prediction accuracy of the charging waiting time can be improved, the difference between the actual waiting time and the predicted waiting time can be reduced, and the stress felt by the electric vehicle user can be reduced.

Furthermore, the user of the electric vehicle α can predict a charging spot that is likely to be crowded due to an increase in charging needs at an arbitrary time based on the charging needs map. As a result, it is possible to reduce the waiting time for charging and reduce stress by changing the charging time or changing the charging spot to be used.

That is, in the first embodiment, the position and remaining charge of each electric vehicle 30 are detected, and the future position and remaining charge of the electric vehicle are predicted based on the detected position information and remaining charge information. And if the future position information and remaining charge information of each of the plurality of electric vehicles 30 can be predicted, it can be estimated in which area in the future the number of remaining vehicles will be small.

Here, the remaining charge amount has a strong correlation with the charging needs. That is, the smaller the remaining charge amount, the higher the need for external charging, and the charging needs increase. Thereby, if the distribution of the remaining charge amount can be grasped, the distribution of future charging needs can be grasped. Also, the density of electric vehicles has a correlation with charging needs. That is, if the density of electric vehicles is high, the number of electric vehicles that require external charging relatively increases, and as a result, charging needs increase. For this reason, if the distribution of the position of the electric vehicle can be grasped, the distribution of future charging needs can be grasped.
And in an area where charging needs are predicted to be high, it can be predicted that charging spots will be crowded and waiting time will be long. Here, regardless of the length of the waiting time, if the actual waiting time is as expected, the user of the electric vehicle is less likely to feel stress.

Therefore, by presenting a distribution of future charging needs, it is possible to improve the prediction accuracy of the charging waiting time and reduce the stress of the electric vehicle user. That is, the distribution information of future charging needs is useful information for predicting the future congestion of charging spots.
Furthermore, the electric vehicle user can reduce the charging waiting time based on the predicted distribution of the charging needs in the future, such as performing charging while avoiding the area where the charging needs are high or the time zone in which the charging needs are high. Judgment can also be made. Therefore, the distribution information of future charging needs becomes useful information when selecting a charging spot.
As a result, by presenting distribution information of charging needs, it is possible to provide information useful for predicting the degree of congestion of charging spots.

Further, in the first embodiment, after the charging needs map is provided, when a specific charging spot is selected by the user of the electric vehicle α, the process proceeds from step S9 to step S10 in the flowchart shown in FIG. A charging waiting time at an arbitrary time point is calculated at a charging spot selected using a method such as the above. And it progresses to step S11 and the recommended departure time according to the calculated charging waiting time is calculated.
Thereafter, the process proceeds to step S12, where the charging waiting time and the recommended departure time are presented on the display 31b of the electric vehicle α that has requested the charging needs information presentation.

Thereby, the user of the electric vehicle α can recognize the charging waiting time at the charging spot to be used and the departure time recommended for shortening the waiting time. As a result, the user of the electric vehicle α can take measures such as changing the charging spot to be used or changing the departure time, thereby reducing stress.

Further, in the first embodiment, the charging needs map is created based on the position information of the electric vehicle 30 at an arbitrary preset time and the remaining charge amount at that time. That is, the icon indicating the position of each electric vehicle 30 on the map is color-coded according to the remaining charge.

Thereby, compared with the charging needs map created only based on the position of each electric vehicle 30, that is, the density of the electric vehicles 30, the prediction accuracy of charging needs can be improved, and a more accurate charging needs map is created. be able to.

Next, the effect will be described.
In the charging support method and the charging support device for the electric vehicle according to the first embodiment, the effects listed below can be obtained.

(1) The database 20 that stores the probe data including the position information and the remaining charge information of the electric vehicle 30 and the probe data read from the database 20 are processed, and the processed data is processed in response to a request from the electric vehicle α. In the probe data utilization system 1 having the server 10 that outputs to the electric vehicle α,
The server 10
Based on the probe data, the estimated traveling route of each of the plurality of electric vehicles 30 is estimated,
Based on the estimated planned route information, the position of each of the plurality of electric vehicles 30 at an arbitrary time point is estimated,
Based on the estimated location information, estimate the charging needs distribution (charging needs map) in any area (information presentation area)
When the information presentation request from the electric vehicle α is generated, the estimated charging needs distribution (charging needs map) is presented on the display 31b of the electric vehicle α that has made the information presentation request.
Thereby, useful information can be provided to predict the degree of congestion of the charging spot.

(2) The server 10 estimates the remaining charge (SOC) of each of the plurality of electric vehicles 30 at an arbitrary time point based on the probe data,
Based on the estimated remaining charge information and the estimated position information of the electric vehicle 30, the distribution of charging needs (charging needs map) is estimated.
Thereby, rather than estimating the distribution of charging needs only from the position information of the electric vehicle 30, the prediction accuracy of the distribution of charging needs can be improved.

(3) Based on the estimated distribution of charging needs (charging needs map), the server 10 predicts charging waiting time at a specific charging spot designated by the user of the electric vehicle α that has made the information presentation request,
The predicted charging waiting time information is presented on the display 31b.
Thereby, the user of the electric vehicle α can grasp the charging waiting time at an arbitrary time point at the charging spot to be used, and can take measures to reduce the stress by reducing the charging waiting time.

(4) The database 20 that stores the probe data including the position information and the remaining charge information of the electric vehicle 30 and the probe data read from the database 20 are processed, and the processed data is processed in response to a request from the electric vehicle α. In the probe data utilization system 1 having the server 10 that outputs to the electric vehicle α,
The server 10
Travel route estimation means (step S4) for estimating a planned travel route of each of the plurality of electric vehicles 30 based on the probe data;
Vehicle position estimation means (step S5) for estimating the position of each of the plurality of electric vehicles at an arbitrary time point based on the estimated planned travel route information;
Charging needs distribution estimating means (step S7) for estimating the distribution of charging needs in an arbitrary area based on the estimated position information;
Charging needs presenting means (step S8) for presenting the estimated charging needs distribution on the display 31b of the electric vehicle α that has made the information presenting request when an information presenting request is generated from the electric vehicle α;
It was set as the structure provided with.
Thereby, useful information can be provided to predict the degree of congestion of the charging spot.

As mentioned above, although the charging assistance method and charging assistance apparatus of the electric vehicle of this invention were demonstrated based on Example 1, it is not restricted to this Example 1 about a concrete structure, Each claim of a claim Design changes and additions are allowed without departing from the spirit of the invention according to the paragraph.

In the first embodiment, a square icon indicating the position of the electric vehicle 30 existing in the information presentation area at an arbitrary time is color-coded according to the remaining charge, and a charging needs map is created by superimposing the color-coded icons on the map An example to do. However, charging needs have a correlation with the density of electric vehicles. Therefore, a square icon indicating the position of the electric vehicle 30 existing in the information presentation area at an arbitrary time may be displayed on the map so as to create a charging needs map.
In this case, it is not necessary to estimate the remaining amount of charge at any point in time for each electric vehicle 30, and the time required for creating the charging need map can be shortened.

In the first embodiment, an example in which the charging waiting time is calculated using a queue or the like is shown. However, the present invention is not limited to this. For example, the charging pattern of each electric vehicle 30 may be estimated based on the probe data, and the charging waiting time may be corrected using this charging pattern.

In the first embodiment, after the charging needs map is presented, when the user of the electric vehicle α selects a charging spot, the charging waiting time and the recommended departure time of the charging spot are calculated. Not limited to. For example, a charging spot to be used may be registered in advance, and a charging waiting time and a recommended departure time may be presented for the registered charging spot together with the presentation of the charging needs map.

Furthermore, when creating the charging needs map, corrections may be made as appropriate.
That is, for example, when there are a plurality of electric vehicles in a predetermined area and the remaining charge amount of each electric vehicle is small, the correction for coloring the icon with the color of the section with the smaller remaining charge amount is performed. May be.
In other words, if two electric vehicles are detected in a predetermined area and each of them is classified second from the one with the smallest remaining charge, the color divided when the remaining charge is the smallest, An icon indicating the position of each electric vehicle is colored. In addition, when there are a plurality of electric vehicles in a predetermined area and the remaining charge amount of each electric vehicle is large, the icon is colored with a color of a classification corresponding to the remaining charge amount. That is, if two electric vehicles are detected in a predetermined area and each of the electric vehicles is classified according to the color of the classification according to the remaining charge, if the second charge is determined from the one with the highest remaining charge. The icon indicating the position of is colored.

In addition, when there are a plurality of chargers installed in a predetermined area, an icon indicating an electric vehicle existing in the vicinity of the charger may be corrected by coloring with a color having a higher charge remaining amount. .

Further, when an icon indicating the position of the charging spot is displayed on the charging needs map, the icon may be displayed after the scale of the charging needs map becomes a predetermined value or less.

In the first embodiment, an example has been described in which the “information presentation area” is an area in a predetermined range centered on an arbitrary point designated by the user of the electric vehicle α, but is not limited thereto. For example, the “information presentation area” is an area of a predetermined range centered on the current location of the electric vehicle α that transmitted the charging needs information presentation request, or an area of a predetermined range centered on the destination of the electric vehicle α. Also good.

Further, in the first embodiment, the example in which the position information of the electric vehicle 30 is acquired based on the signal obtained from the GPS mounted on each electric vehicle 30 is shown. However, when it is difficult to receive the GPS signal, the gyro The vehicle position may be calculated based on a signal obtained using a sensor or a vehicle speed sensor.

Claims

A database that stores probe data including position information and remaining charge information of an electric vehicle, and a server that processes the probe data read from the database and outputs processed data to the electric vehicle in response to a request from the electric vehicle In a probe data utilization system having
The server
Based on the probe data, estimate the planned travel route of each of the plurality of electric vehicles,
Based on the estimated planned route information, the position of each of the plurality of electric vehicles at an arbitrary time point is estimated,
Based on the estimated location information, estimate the distribution of charging needs in any area,
A charging support method for an electric vehicle, wherein when an information presentation request is generated from an electric vehicle, the estimated distribution of charging needs is presented on a display of the electric vehicle that has made the information presentation request.
The charging support method for an electric vehicle according to claim 1,
The server estimates a remaining charge amount of each of the plurality of electric vehicles at an arbitrary time based on the probe data,
A charging support method for an electric vehicle characterized by estimating a distribution of the charging needs based on the estimated remaining charge information and the estimated position information of the electric vehicle.
In the charging support method for an electric vehicle according to claim 1 or 2,
Based on the estimated distribution of charging needs, the server predicts a charging waiting time at a specific charging spot designated by a user of the electric vehicle that has made the information presentation request,
The predicted charging wait time information is presented on the display. A charging support method for an electric vehicle, characterized in that:
A database that stores probe data including position information and remaining charge information of an electric vehicle, and a server that processes the probe data read from the database and outputs processed data to the electric vehicle in response to a request from the electric vehicle In a probe data utilization system having
The server
Based on the probe data, a travel route estimation unit that estimates a planned travel route of each of the plurality of electric vehicles;
Vehicle position estimation means for estimating the position of each of the plurality of electric vehicles at an arbitrary time point based on the estimated planned route information;
Charging needs distribution estimating means for estimating the distribution of charging needs in an arbitrary area based on the estimated position information;
Charging needs presenting means for presenting a distribution of estimated charging needs on a display of the electric vehicle that has made the information presentation request when an information presentation request from the electric vehicle is generated;
A charging support device for an electric vehicle, comprising: