JP2016218647A - Congestion state presentation device, congestion state presentation system, and congestion state presentation method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a congestion state presentation device, a congestion state presentation system, and a congestion state presentation method with which it is possible to predict the congestion state of a charge spot with greater accuracy.SOLUTION: A server 12 acquires the current position information, travel route information, and battery charge rate information of a plurality of electric vehicles 10, and specifies an electric vehicle 10 that is predicted to be traveling near the charge spot 13 in the future as a proximity object vehicle on the basis of the travel route information. The server also calculates, on the basis of each of the information, the anticipated charge rate of a battery when the proximity object vehicle approaches the charge spot, and predicts the congestion state of the charge sport 13 on the basis of the calculated anticipated charge rate when the electric vehicle 10 approaches the charge spot 13. Then, the server presents information about the predicted congestion state to the electric vehicle 10.SELECTED DRAWING: Figure 2

Description

  The present invention relates to a congestion status presentation device, a congestion status presentation system, and a congestion status presentation method for predicting the congestion status of a charging spot and presenting it to an occupant of each electric vehicle.

  When charging a battery mounted on an electric vehicle at a charging spot (sometimes referred to as a “charging station” or “charging station”), the waiting time becomes longer if the charging spot is crowded. There is an annoying problem.

  In Patent Document 1, a search is made for a charging spot that is within the reach of the vehicle's remaining battery level at that time, and another electric vehicle that exists around the searched charging spot is searched. Providing information that can be charged in a short waiting time to the occupant of the own vehicle by predicting the congestion situation when the vehicle reaches a certain charging spot and notifying the occupant of the own vehicle of this information It is disclosed.

JP 2011-13893 A

  However, since the conventional example disclosed in Patent Document 1 predicts the congestion state of the charging spot based on the charging rate at that time, it does not accurately predict the congestion state. That is, the driver usually determines whether or not to charge based on the charging rate at the time of reaching the charging spot. Therefore, in the conventional method of determining whether or not charging is necessary using the charging rate when the charging spot has not been reached and predicting the congestion status based on the determination result, the congestion status of the charging spot is accurately determined. It cannot be said that it is predicting.

  The present invention has been made to solve such a conventional problem, and the object of the present invention is to provide a congestion status presentation device and a congestion status that can more accurately predict the congestion status of a charging spot. To provide a presentation system and a congestion situation presentation method.

  In order to achieve the above object, a congestion status presentation device according to the present invention acquires current position information, travel route information, and battery charge rate information of a plurality of electric vehicles, and based on the travel route information of each electric vehicle. Thus, the electric vehicle that is expected to travel in the vicinity of the charging spot is specified as the approach target vehicle. In addition, based on each acquired information, an expected charging rate of the battery when the approaching target vehicle approaches the charging spot is calculated, and one electric vehicle approaches the charging spot based on the expected charging rate of the approaching target vehicle. The congestion status of the charging spot is predicted. Furthermore, information on the predicted congestion situation is presented to one electric vehicle.

  The congestion status presentation system according to the present invention is a congestion status presentation system including each vehicle-side device mounted on a plurality of electric vehicles and a server that presents the congestion status of the charging spot to the vehicle-side device. A vehicle side communication unit that communicates with the server, a current position detection unit that detects current position information of the electric vehicle, a travel route acquisition unit that acquires travel route information by an occupant, and a charging rate of a battery mounted on the electric vehicle And a charging rate detection unit for detecting. Further, the server identifies an electric vehicle that is expected to travel in the vicinity of the charging spot in the future as the approach target vehicle based on the travel route information transmitted from the vehicle side device, and each information transmitted from the vehicle side device. Based on the above, the expected charging rate of the battery when each approaching target vehicle approaches the charging spot is calculated. Based on the expected charging rate of each approach target vehicle calculated by the expected charging rate calculation unit, the congestion state of the charging spot when one electric vehicle approaches the charging spot is predicted. Furthermore, the information on the congestion status predicted by the congestion status prediction unit is transmitted to the vehicle side device of one electric vehicle by the server side communication unit.

  The congestion status presentation method according to the present invention acquires current position information, travel route information, and battery charge rate information of a plurality of electric vehicles, and in the vicinity of a charging spot in the future based on the travel route information of each electric vehicle. An electric vehicle that is expected to travel is identified as an approach target vehicle. Further, based on each information acquired by the information acquisition unit, the expected charging rate of the battery when the approaching target vehicle approaches the charging spot is calculated, and the expected charging of the approaching target vehicle calculated by the expected charging rate calculation unit Based on the rate, the congestion state of the charging spot when one electric vehicle approaches the charging spot is predicted. Information on the predicted congestion situation is presented to one electric vehicle.

  According to the present invention, since the congestion state of the charging spot is predicted based on the expected charging rate when each electric vehicle approaches the charging spot, the congestion state of the charging spot can be predicted more accurately. Become.

It is a network connection figure of the congestion condition presentation system which concerns on embodiment of this invention. It is a block diagram which shows the structure of the congestion condition presentation system which concerns on 1st Embodiment of this invention. It is explanatory drawing which shows the road area which concerns on embodiment of this invention and divided the charging spot and the surrounding road. It is a map which concerns on 1st Embodiment of this invention and shows the relationship between an estimated charging rate and a score. It is a flowchart which shows the process sequence by the vehicle side apparatus of the congestion condition presentation system which concerns on 1st Embodiment of this invention. It is the 1st partial view of the flowchart which shows the process sequence by the server of the congestion condition presentation system which concerns on 1st Embodiment of this invention. It is the 2nd division of the flowchart which shows the process sequence by the server of the congestion condition presentation system which concerns on 1st Embodiment of this invention. It is a map which concerns on the 1st modification of 1st Embodiment of this invention, and shows the relationship between the distance to a destination, and a score. It is a map which concerns on the 2nd modification of 1st Embodiment of this invention, and shows the relationship between the ratio of the distance from the charge spot to the destination which occupies for all the strokes, and a score. It is a block diagram which shows the structure of the congestion condition presentation system which concerns on 2nd Embodiment of this invention. It is the 1st partial view of the flowchart which shows the process sequence by the server of the congestion condition presentation system which concerns on 2nd Embodiment of this invention. It is the 2nd partial view of the flowchart which shows the process sequence by the server of the congestion condition presentation system which concerns on 2nd Embodiment of this invention. It is a map which concerns on 2nd Embodiment of this invention and shows the relationship between a predicted remaining cruising distance and a score.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
[Description of First Embodiment]
FIG. 1 is a network connection diagram showing a schematic configuration of a congestion status presentation system and its peripheral devices according to an embodiment of the present invention. As shown in FIG. 1, the congestion situation presentation system 100 includes a plurality of electric vehicles 10 and a server 12 (congestion situation presentation device) connected to each electric vehicle 10 via a network. The server 12 is connected to a plurality of charging spots 13 via a network. The server 12 predicts the congestion status of each charging spot 13 based on the current position information, travel route information, battery charging rate information, and position information of each charging spot 13 of each electric vehicle 10, and the electric vehicle 10. Notify Although FIG. 1 shows three charging spots 13 and three electric vehicles 10, the present invention is not limited to this.

  FIG. 2 is a block diagram showing a detailed configuration of the congestion status presentation system 100 according to the first embodiment. As shown in FIG. 2, the congestion status presentation system 100 includes a vehicle-side device 11 mounted on the electric vehicle 10 and a server 12 connected to each vehicle-side device 11 via a network. The server 12 is connected to the charging spot 13 via the network. In FIG. 2, only one vehicle side device 11 and one charging spot 13 are shown.

  The vehicle side device 11 includes a communication unit 21 (vehicle side communication unit), a GPS 22 (current position detection unit), a navigation device 23 (travel route acquisition unit), and a charging rate detection unit 24 that communicate with the server 12. And a display unit 25 and a power consumption calculation unit 26.

  The GPS 22 detects the current position of the electric vehicle 10 on which the vehicle side device 11 is mounted. The navigation device 23 sets a travel route on which the electric vehicle 10 is expected to travel in the future according to a destination set by an occupant input operation or the like.

  The charging rate detection unit 24 detects the charging rate of the battery of the electric vehicle 10 (the ratio of the charging power amount at that time to the total charging power amount of the battery). The display unit 25 has a function of displaying various types of information, and particularly displays information related to the congestion status of each charging spot 13 as will be described later.

  The power consumption calculation unit 26 calculates a travel distance per unit electric energy of the electric vehicle 10 (this is referred to as “electricity cost”). Since the power consumption varies depending on the environment during traveling, for example, the power consumption is calculated from the travel distance of the last several hours and the amount of power consumed.

  Note that the communication unit 21, the charge rate detection unit 24, and the power consumption calculation unit 26 can be configured as an integrated computer including a central processing unit (CPU) and storage means such as a RAM, a ROM, and a hard disk, for example. .

  On the other hand, the server 12 includes a communication unit 31 (information acquisition unit, information presentation unit, server side communication unit) that communicates with each vehicle-side device 11 and each charging spot 13 via a network, and an expected charging rate calculation unit. 32, a vehicle identification unit 33, a closest distance calculation unit 34, a drop-in probability calculation unit 35, a congestion state prediction unit 36, and a storage unit 37. The communication unit 31 has a function as an information acquisition unit that acquires current position information, travel route information, and battery charge rate information of the plurality of electric vehicles 10. Each component of the server 12 can be configured as an integrated computer including a central processing unit (CPU) and storage means such as a RAM, a ROM, and a hard disk.

  The expected charging rate calculation unit 32 includes the position information of each charging spot 13, the current position information of a certain electric vehicle (one electric vehicle; this is indicated by 10A (see FIG. 1)), and the charging rate of the electric vehicle 10A. Based on the above, the charging rate when the electric vehicle 10A approaches each charging spot 13 is predicted. Hereinafter, the predicted charging rate is referred to as “expected charging rate”.

  The vehicle specifying unit 33 acquires travel route information of each vehicle-side device 11 from the plurality of vehicle-side devices 11 with which communication has been executed, and travels in the vicinity of each charging spot 13 in the future based on the travel route information. The electric vehicle 10 is specified. For example, when a range with a radius of 5 km is set from each charging spot 13 and the travel route is included in this range, it is determined that the electric vehicle 10 may be charged at the charging spot 13. Then, the electric vehicle 10 is set as an “approach target vehicle”. The travel route information is data set by the navigation device 23 of the vehicle side device 11 and is received by the communication unit 31.

  The closest approach distance calculating unit 34 is a distance (maximum distance) between the two when the electric vehicle 10 specified by the vehicle specifying unit 33 is closest to a certain charging spot (this is 13A (see FIG. 1)). (Approach distance) is calculated. This will be described below with reference to the explanatory diagram shown in FIG.

  FIG. 3 is an explanatory diagram schematically showing the charging spot 13A and a road around the charging spot 13A. The road around the charging spot 13A is set in advance as a road section divided by two intersections. Specifically, as shown in FIG. 3, road sections d1 to d15 are set. This information is stored in the storage unit 37. Further, the midpoint of each road section d1 to d15 is set as a representative point of the road section. For example, the representative point of the road section d8 is α. The distance from the representative point of each road section d1 to d15 to the charging spot 13A is the distance between the road section and the charging spot 13A. For example, the distance between the road section d8 and the charging spot 13A is the distance β shown in FIG. When the traveling route of the electric vehicle 10A is, for example, the route indicated by the symbol Y1 in FIG. 3, the charging spot 13A is closest when passing through the road section d10. Therefore, the closest approach distance is the distance β1 from the midpoint of the road section d10 to the charging spot 13A.

  2 for the charging spot 13A, the “charging rate” when each electric vehicle 10 is closest to the charging spot 13A (in the first modification described later, “from the charging spot 13A to the destination The distance from the charging spot 13A to the destination in the entire process, and the “remaining cruising distance” in the second embodiment). The probability of charging by stopping at the spot 13A is obtained. Specifically, as shown in FIG. 4, a score map for determining a score between 1 and 10 with respect to the charging rate is set in advance, and this score map is stored in the storage unit 37.

  When the expected charge rate is calculated by the expected charge rate calculation unit 32, a score is obtained with reference to the score map shown in FIG. 4 based on the expected charge rate. This score map is set such that the lower the expected charging rate, the higher the score. And based on this score, the possibility that each electric vehicle 10 stops at the charging spot 13A is calculated. For example, when the score of the electric vehicle 10A is “7”, the probability that the electric vehicle 10A stops at the charging spot 13A and charges is set to 70%.

  The congestion status prediction unit 36 predicts the congestion status of each charging spot 13 for each time zone based on the probability that each electric vehicle 10 calculated by the drop-in probability calculation unit 35 stops at each charging spot 13. Specifically, an arbitrary time zone (for example, every 10 minutes) is set, and based on the number of electric vehicles 10 that may stop at a certain charging spot 13A and the probability of stopping, the congestion state of this charging spot 13A Predict. And the information of a congestion condition is transmitted to the vehicle side apparatus 11 from the communication part 31, and is shown to the passenger | crew of the electric vehicle 10. FIG. That is, the communication unit 31 has a function as an information presenting unit that presents information on the predicted congestion state to the passenger of the electric vehicle 10.

  The storage unit 37 includes various information such as position information of each charging spot 13, current position information of each electric vehicle 10 that changes from time to time, power consumption information of each electric vehicle 10, a map indicating a relationship between a charging rate and a score. The information is memorized.

  Next, the operation of the congestion status presentation system 100 according to the present embodiment configured as described above will be described with reference to the flowcharts shown in FIGS. 5, 6, and 7.

  FIG. 5 is a flowchart showing a processing procedure of the vehicle side device 11. First, in step S <b> 1, the GPS 22 provided in the vehicle side device 11 acquires current position information of the electric vehicle 10. In step S2, the navigation device 23 acquires travel route information from the current position of the electric vehicle 10 to the destination based on the destination information input by the occupant.

  In step S <b> 3, the charging rate detection unit 24 detects the charging rate of the battery mounted on the electric vehicle 10. In step S <b> 4, the power consumption calculation unit 26 calculates the power consumption for the last week of the electric vehicle 10.

  In step S <b> 5, the communication unit 21 transmits the above-described current position information, travel route information, current charging rate information, and power consumption information to the server 12. That is, the server 12 (congestion status presentation device) can acquire current position information, travel route information, charging rate information, and electricity cost information of a plurality of electric vehicles.

  After that, in step S6, the information reception from the server 12 is awaited. In step S7, various information (details will be described later) transmitted from the server 12 are displayed on the display unit 25.

  Next, the processing procedure of the server 12 will be described with reference to FIGS. First, in step S11, when there is a data transmission request from a certain electric vehicle 10 (hereinafter referred to as “own vehicle”), the server 12 determines whether or not the travel route is based on the travel route information of the own vehicle. Alternatively, the charging spot 13 existing in a place close to the travel route is recognized. For example, the charging spot 13 existing within 5 km from the travel route is recognized. When the number of recognized charging spots 13 is N, each charging spot 13 is set to a charging spot n (where n = 1 to N).

  In step S12, the server 12 sets n = 1. In step S <b> 13, the server 12 acquires road segment data in the vicinity of the charging spot n. Specifically, as shown in FIG. 3, with respect to the charging spot 13A, data such as road sections d1 to d15, and distances from the road sections d1 to d15 to the charging spot 13A (for example, as shown in FIG. 3). Get the distance β).

  In step S <b> 14, the server 12 acquires information transmitted from each electric vehicle 10. That is, since various types of information are transmitted from each vehicle-side device 11 by the processing of each vehicle-side device 11 shown in FIG. 5, the server 12 stores these information, that is, current position information, travel route information, current The charging rate information and the power consumption information are received by the communication unit 31, and the information is acquired.

  In step S15, the electric vehicle 10 that travels around the charging spot n (for example, within a radius of 5 km) within 24 hours is listed. The listed electric vehicle 10 is an approach target vehicle for the charging spot n.

  In step S16, when the number of approach target vehicles is M, the server 12 sets each approach target vehicle to the approach target vehicle m (where m = 1 to M). In step S17, m = 1.

  In step S18, the road section where the approach target vehicle m is closest to the charging spot n and the distance are calculated. Specifically, assuming that the charging spot 13A shown in FIG. 3 is the charging spot n, the road section d10 is the closest road section when the traveling route of the approaching target vehicle m is the path indicated by the symbol Y1. Therefore, the distance β1 from the charging spot n to the road section d10 is calculated.

  In step S19, the travel distance until the approach target vehicle m is closest to the charging spot n and the time are calculated.

In step S20, the charging rate when the approaching target vehicle m is closest to the charging spot n is predicted based on the current charging rate of the approaching target vehicle m and the power consumption. This is the expected charging rate. When the current charging rate of the approaching vehicle m is y, the distance from the current position to the closest point of the charging spot n is x, the most recent power consumption is z, and the electric energy during full charging is w, the expected charging rate y 'Can be obtained by the following equation (1).
y ′ = y−x / z / w (1)

  In step S21, it is determined whether or not the expected charging rate obtained by the equation (1) is a negative value. If it is a negative value (YES in step S21), it is determined that this approach target vehicle m does not stop at the charging spot n, and the process proceeds to step S26 in FIG.

  On the other hand, when the expected charging rate is not a negative value (NO in step S21), in step S22 in FIG. 7, the server 12 scores the approaching vehicle m based on the expected charging rate calculated in the process of step S20. Ring. Specifically, referring to the score map shown in FIG. 4, for example, when the expected charging rate is 20%, the score is determined as “9”.

  In step S23, the server 12 recognizes another charging spot 13 existing within a range of a predetermined distance from the charging spot n (for example, a range within a radius of 5 km) as a “peripheral charging spot”. Here, as an example, it is assumed that the total number of charging spots n and peripheral charging spots is K (that is, (K−1) peripheral charging spots).

  In step S24, the server 12 determines the rank k (where k = 1 to 1) according to the distance when the approach target vehicle m is closest to the charging spot n and (K-1) surrounding charging spots. K) is set. And the order | rank k about the charging spot n is calculated | required. For example, among the K charging spots, k = 1 when the distance between the charging spot n and the approaching vehicle m is the shortest, and k = 2 when the distance is the second shortest. It becomes.

Then, the correction coefficient P is calculated based on the following equation (2).
P = 1−k / (K + 1) (2)

  Specifically, when K = 5 and k = 1, P = 0.83. When K = 5 and k = 5, P = 0.17. Therefore, based on the travel route of the approach target vehicle m, the probability that the approach target vehicle m stops at the charging spot existing around the travel route is corrected by the correction coefficient P described above.

  That is, an occupant of an electric vehicle should not go to the charging spot 13 located away from the travel route, but should go to the charging spot 13 on the travel route or as close to the travel route as possible. . Therefore, according to the above equation (2), the correction coefficient P is set to be large for charging spots that are located closer to the traveling route of the electric vehicle, and conversely, charging spots 13 that are located far from the traveling route of the host vehicle. Is set to a small correction coefficient P.

  In step S25, the probability that the approach target vehicle m stops at the charging spot n is calculated. In this process, the drop probability is calculated by multiplying the score calculated in step S22 by the correction coefficient P calculated in step S25. As a result, the probability that the approach target vehicle m stops at the charging spot n in a predetermined time zone is obtained.

  In step S26, the server 12 determines whether m = M. If m = M is not satisfied (NO in step S26), m is incremented in step S30, and the process returns to step S18. By this process, the probability of stopping at the charging spot n is obtained for every time zone for all approaching vehicles with respect to the charging spot n.

  If m = M (YES in step S26), in step S27, the server 12 calculates the degree of congestion for each time zone of the charging spot n. That is, the congestion degree in this time zone is calculated based on the drop-in probability obtained for all approaching target vehicles. For example, if there are 10 approaching vehicles at the charging spot n in a certain time zone, of which 4 vehicles have a 50% drop probability and 6 vehicles have a 80% drop probability, 4 * 0. Since 5 + 6 * 0.8 = 6.8, and about 6 to 7 electric vehicles are expected to be charged at the charging spot n, the degree of congestion corresponding to this number can be set.

  Next, in step S28, it is determined whether n = N. If n = N is not satisfied (NO in step S28), in step S31, the server 12 increments n and returns to the process of step S13. By doing so, the degree of congestion for each time zone is calculated for each charging spot 13 existing in the vicinity of the travel route of the host vehicle.

  In step S29, the server 12 transmits the degree of congestion of each charging spot 13 for each time zone from the communication unit 31 to the vehicle-side device 11 of the host vehicle. Thereafter, this process is terminated. The above processing is executed at a predetermined time interval such as an interval of 10 minutes.

  In the vehicle-side device 11 of the own vehicle, information on the degree of congestion of each charging spot 13 is displayed on the display unit 25 and presented to the occupant. Thus, the occupant of the own vehicle can recognize the congestion state of each charging spot 13 existing on the traveling route of the own vehicle or in the vicinity of the traveling route.

  Thus, in the server 12 (congestion status presentation device) according to the first embodiment, based on the current position information, travel route information, and battery charge rate information of each electric vehicle 10 transmitted from the vehicle side device 11. The expected charging rate when each electric vehicle 10 approaches each charging spot 13 is calculated. Then, based on the expected charging rate, the degree of congestion of each charging spot 13 is obtained and presented to the passenger of the electric vehicle 10.

  That is, instead of the current charging rate of each electric vehicle 10, the charging rate when each electric vehicle 10 actually approaches each charging spot 13 is predicted, and the degree of congestion of each charging spot 13 using this predicted charging rate. Seeking. Accordingly, it is possible to obtain a congestion degree that matches the actual situation as compared with the conventional method, and it is possible to predict the congestion state of each charging spot 13 more accurately.

  In addition, since it is determined that the smaller the expected charging rate obtained by the expected charging rate calculation unit 32 is, the more likely it is to stop at the charging spot 13, it is possible to more accurately predict the congestion situation. Furthermore, since the electric vehicle 10 that is expected to reach zero in the expected charging rate when approaching the charging spot 13 is excluded from the candidates as not being charged at the charging spot 13, unnecessary calculations can be avoided. .

  Furthermore, when a certain electric vehicle 10A passes near a certain charging spot 13A, another charging spot existing within a predetermined distance from the travel route of this electric vehicle 10A is set as a peripheral charging spot, and the electric vehicle 10A Calculates the distance when the closest charging spot to the surrounding charging spot. Then, the rank k is set in ascending order of the distance, and the correction coefficient P is calculated based on the rank k. That is, the higher the rank k is, the higher the correction coefficient P is set, and the correction coefficient P is used to calculate the probability that the electric vehicle 10A will stop at the charging spot 13A. Therefore, it is possible to obtain the drop-in probability according to the action that the occupant of the electric vehicle 10A will take, and it is possible to predict the congestion situation with higher accuracy.

  In addition, in the charging spot congestion state presentation system 100 according to the first embodiment, it is possible to notify the occupant of the congestion state of each charging spot 13 existing in the vicinity of the travel route on which the electric vehicle 10 will travel in the future. The ten passengers can recognize the charging spot 13 with less congestion, and can charge the battery at the charging spot 13 with less waiting time.

[Description of First Modification of First Embodiment]
Next, a first modification of the above-described first embodiment will be described. In the first embodiment, the probability of stopping at the charging spot 13 is calculated based on the charging rate when each electric vehicle 10 is closest to the charging spot 13. In the first modification, the drop probability to each charging spot 13 is calculated based on the distance from the charging spot 13 to the destination of the electric vehicle 10 instead of the charging rate. Specifically, as shown in FIG. 8, a score map indicating the relationship between the distance from the charging spot 13 to the destination and the score is set and stored in the storage unit 37. Then, using this score map, scoring is performed for the approach target vehicle of each charging spot 13. That is, the process shown in step S22 of FIG. 7 is scored using the score map shown in FIG. The distance from the charging spot 13 to the destination can be acquired from the travel route information of each electric vehicle 10.

  In the score map shown in FIG. 8, the score is set higher as the distance from the charging spot 13 to the destination is shorter. This is set based on the psychology that the occupant of the electric vehicle 10 wants to charge in consideration of the return path as he approaches the destination. Then, on the basis of the score determined using the score map of FIG. 8, the same processing as that in the flowcharts of FIGS. The congestion state of the charging spot 13 can be recognized.

  For this reason, as in the first embodiment, the occupant of the electric vehicle 10 can easily recognize the charging spot 13 with less congestion, and can charge the battery with the charging spot 13 with less waiting time. it can. In addition, you may make it calculate the drop-in probability of each charging spot 13 using both the score map shown in FIG. 3 and the score map shown in FIG.

[Description of Second Modification of First Embodiment]
Next, a second modification of the above-described first embodiment will be described. In the second modified example, the drop-in probability for each charging spot 13 is calculated according to the ratio of the distance from the charging spot 13 to the destination in all processes on the travel route. Specifically, as shown in FIG. 9, a score map indicating the relationship between the ratio of the distance from the charging spot 13 to the destination in all the steps of the travel route and the score is set and stored in the storage unit 37. To do. Then, using this score map, scoring is performed on the approach target vehicle of each charging spot 13. That is, the process shown in step S22 of FIG. 7 is scored using the score map shown in FIG. In addition, the ratio of the distance from the charging spot 13 to the destination in all the steps of the travel route can be obtained from the travel route information of each electric vehicle 10.

  In the score map shown in FIG. 9, the score is set higher as the ratio is smaller. This is set based on the psychology that the occupant of the electric vehicle 10 wants to charge in consideration of the return trip as the ratio of the travel distance to the destination decreases. Then, based on the score determined using the score map of FIG. 9, charging similar to that on the travel route of the electric vehicle 10 or close to the travel route is performed by executing the same processing as in FIG. 6 and FIG. 7 described above. The congestion state of the spot 13 can be recognized.

  For this reason, as in the first embodiment, the charging spot 13 with less congestion can be easily recognized, and the battery can be charged with the charging spot 13 with less waiting time. In addition, you may make it calculate the drop-in probability of each charging spot 13 using both the score map shown in FIG. 3 and the score map shown in FIG.

[Description of Second Embodiment]
Next, a second embodiment of the present invention will be described. In the first embodiment described above, the probability of stopping at each charging spot 13 is calculated based on the expected charging rate when each electric vehicle 10 approaches the charging spot 13, and the degree of congestion of each charging spot 13 is obtained. On the other hand, in 2nd Embodiment, when each electric vehicle 10 approaches the charging spot 13, the remaining cruising distance is calculated | required and the drop-in probability to each charging spot 13 is calculated based on the calculated remaining cruising distance. . The remaining cruising distance indicates a distance that can be traveled according to the amount of charge power of the battery at that time.

  Hereinafter, the second embodiment will be described in detail. The overall network connection diagram is the same as that in FIG. FIG. 10 is a block diagram showing a detailed configuration of the congestion status presentation system 200 according to the second embodiment. As shown in FIG. 10, the congestion status presentation system 200 includes a vehicle-side device 11 mounted on the electric vehicle 10 and a server 12a (congestion status presentation device). The server 12a is connected to the charging spot 13 via a network. In FIG. 10, only one vehicle side device 11 and one charging spot 13 are shown.

  Since the vehicle-side device 11 is the same as the vehicle-side device 11 shown in FIG.

  The server 12a is different from the server 12 shown in FIG. 2 in that a remaining cruising distance calculation unit 38 is provided. The other constituent elements are the same as those shown in FIG.

  The remaining cruising distance calculation unit 38 calculates the expected charging rate calculated by the expected charging rate calculation unit 32, that is, the expected charging rate when the electric vehicle 10 is closest to a certain charging spot 13 </ b> A, and the nearest electric vehicle 10. The remaining cruising distance is calculated based on the electricity cost.

  Next, a processing procedure of the congestion status presentation system 200 according to the second embodiment will be described with reference to FIGS. 11 and 12. Note that the processing procedure of the vehicle-side device 11 is the same as the flowchart of FIG.

  11 and 12 are different from the flowcharts of FIGS. 6 and 7 only in the processes of steps S20, S21, and S22. Therefore, in FIG. 10 and FIG. 11, steps S20, S21, and S22 are shown as S20a, S21a, and S22a, respectively, and these processes will be described.

In the first embodiment, the expected charging rate is calculated using the above-described equation (1), and the approaching vehicle is scored using the expected charging rate. In contrast, in the second embodiment, an expected remaining cruising distance that is an expected value of the remaining cruising distance when the approaching target vehicle m approaches the charging spot n is calculated using the following equation (3).
u ′ = u−x (3)

  In the equation (3), u ′ is the expected remaining cruising distance, u is the current remaining cruising distance, and x is the distance from the current position of the approaching target vehicle m to the closest charging spot n. The expected remaining cruising distance can be calculated from the expected charging rate and the electricity cost, and the remaining cruising distance can be calculated from the current charging rate and the electricity cost.

  Then, in step S20a shown in FIG. 11, the expected remaining cruising distance at the closest point is calculated from the charging rate of the approach target vehicle m and the electricity cost. In step S21a, it is determined whether the expected remaining cruising distance is a negative value. If it is not a negative value, the approach target vehicle m is scored based on the predicted remaining cruising distance in step S22a of FIG.

  In this process, the score map shown in FIG. 13 is used. FIG. 13 is a score map showing the relationship between the predicted remaining cruising distance and the score. When the expected remaining cruising distance is obtained, the score is obtained with reference to the score map shown in FIG. 13 based on the predicted remaining cruising distance. This score map is set such that the shorter the expected remaining cruising distance, the higher the score. That is, it is based on the possibility that the electric vehicle 10 is likely to stop at the charging spot 13 when the remaining cruising distance is shortened. And based on the score calculated | required from this score map, the possibility that each electric vehicle 10 will stop at the charging spot 13A is calculated. The processing procedure after step S23 in FIG. 12 is the same as that in FIG.

  Thus, in the server 12a (congestion status presentation device) according to the second embodiment, the current position information, travel route information, battery charge rate information, and power consumption of each electric vehicle 10 transmitted from the vehicle side device 11 are obtained. Based on the information, an expected remaining cruising distance when each electric vehicle 10 approaches each charging spot 13 is calculated. Based on the estimated remaining cruising distance, the degree of congestion of each charging spot 13 is obtained and presented to the passenger of the electric vehicle 10.

  That is, instead of the current remaining cruising distance of each electric vehicle 10, the remaining cruising distance when each electric vehicle 10 actually approaches each charging spot 13 is predicted, and each charging spot 13 is used by using this predicted remaining cruising distance. Seeking the degree of congestion. Accordingly, it is possible to obtain a congestion degree that matches the actual situation as compared with the conventional method, and it is possible to predict the congestion state of each charging spot 13 more accurately.

  In addition, the degree of congestion of each charging spot 13 is estimated by using an intuitively easy-to-understand index called the remaining cruising distance of each approaching target vehicle, so that it is possible to predict the congestion situation more suited to the actual situation. A high congestion situation can be predicted.

  Furthermore, in the charging spot congestion state presentation system 200 according to the second embodiment, the passenger can be informed of the congestion state of each charging spot 13 existing in the vicinity of the travel route on which the electric vehicle 10 will travel in the future. The ten passengers can recognize the charging spot 13 with less congestion, and can charge the battery at the charging spot 13 with less waiting time.

  As described above, the congestion status presentation device, the congestion status presentation system, and the congestion status presentation method of the present invention have been described based on the illustrated embodiment. However, the present invention is not limited to this, and the configuration of each unit is the same. It can be replaced with an arbitrary configuration having the above function.

DESCRIPTION OF SYMBOLS 10 Electric vehicle 11 Vehicle side apparatus 12, 12a Server 13 Charging spot 21 Communication part 22 GPS
DESCRIPTION OF SYMBOLS 23 Navigation apparatus 24 Charge rate detection part 25 Display part 26 Electricity cost calculation part 31 Communication part 32 Expected charge rate calculation part 33 Vehicle specific part 34 Closest distance calculation part 35 Stopping probability calculation part 36 Congestion condition prediction part 37 Storage part 38 Remaining continuation Distance calculation unit 100, 200 Congestion status presentation system d1 to d15 ... road section

Claims (8)

A congestion status presentation device that presents the congestion status of a charging spot to a single electric vehicle,
An information acquisition unit that acquires current position information, travel route information, and battery charge rate information of a plurality of electric vehicles;
Based on the travel route information of each electric vehicle, a vehicle identifying unit that identifies an electric vehicle that is expected to travel near the charging spot in the future as an approach target vehicle;
Based on each information acquired by the information acquisition unit, an expected charging rate calculation unit that calculates an expected charging rate of a battery when the approach target vehicle approaches the charging spot;
A congestion state prediction unit for predicting a congestion state of the charging spot when the one electric vehicle approaches the charging spot based on the predicted charging rate of the approaching vehicle calculated by the expected charging rate calculation unit; ,
An information presentation unit for presenting information on the predicted congestion status to the one electric vehicle;
A congestion status presentation device characterized by comprising: The congestion situation prediction unit predicts the congestion situation by determining that the vehicle to be approached is likely to be charged at the charging spot as the expected charge rate calculated by the expected charge rate calculation unit is smaller. The congestion status presentation device according to claim 1, wherein: When the expected charge rate calculated by the expected charge rate calculation unit reaches zero for the approach target vehicle, the congestion state prediction unit determines that the approach target vehicle is not charged at the charge spot, The congestion status presentation apparatus according to claim 1, wherein the congestion status is predicted. A closest distance calculation unit for calculating a distance from the charging spot to the approaching target vehicle when the approaching target vehicle is closest to the charging spot;
The congestion situation prediction unit predicts the congestion situation for the approach target vehicle by determining that the shorter the distance calculated by the closest approach distance calculation unit, the higher the possibility of charging at the charging spot. The congestion status presentation device according to any one of claims 1 to 3. The congestion status prediction unit recognizes a destination of the approach target vehicle from the travel route information of the approach target vehicle acquired by the information acquisition unit, and from the charging spot to the destination of the approach target vehicle 5. The congestion state is predicted by determining that the approach target vehicle is more likely to be charged at the charging spot as the distance is shorter. 6. Congestion status presentation device. The information acquisition unit acquires the power consumption of the electric vehicle, and
The remaining cruising distance for calculating the remaining cruising distance when the approaching target vehicle approaches the charging spot based on the expected charging rate when the approaching target vehicle approaches the charging spot and the power consumption of the approaching target vehicle An arithmetic unit,
The congestion state prediction unit predicts a congestion state of the charging spot when the one electric vehicle approaches the charging spot based on the remaining cruising distance calculated by the remaining cruising distance calculation unit. The congestion status presentation device according to any one of claims 1 to 5. Each vehicle-side device mounted on a plurality of electric vehicles, and a server connected to each of the vehicle-side devices via a network and presenting the congestion status of the charging spot to the vehicle-side device of one electric vehicle A situation presentation system,
The vehicle side device
A vehicle-side communication unit that communicates with the server;
A current position detector for detecting current position information of the electric vehicle;
A travel route acquisition unit for acquiring travel route information by a passenger;
A charge rate detector for detecting a charge rate of a battery mounted on the electric vehicle;
The server
A server-side communication unit that communicates with each vehicle-side device;
Based on the travel route information transmitted from the vehicle-side device, a vehicle identifying unit that identifies an electric vehicle that is expected to travel near the charging spot in the future as an approach target vehicle;
Based on each information transmitted from the vehicle-side device, an expected charging rate calculation unit that calculates an expected charging rate of the battery when each approach target vehicle approaches the charging spot;
Based on the expected charging rate of each approach target vehicle calculated by the expected charging rate calculation unit, the congestion status prediction unit predicts the congestion status of the charging spot when the one electric vehicle approaches the charging spot. And comprising
Transmitting information on the congestion status predicted by the congestion status prediction unit to the vehicle side device of the one electric vehicle by the server side communication unit;
Congestion status presentation system. A congestion status presentation method for presenting the congestion status of a charging spot to one electric vehicle,
Obtaining current position information, travel route information, and battery charge rate information of a plurality of electric vehicles;
Identifying an electric vehicle that is expected to travel in the vicinity of the charging spot in the future as an approach target vehicle based on the travel route information of each electric vehicle;
A step of calculating an expected charging rate of the battery when the approaching target vehicle approaches the charging spot based on each acquired information;
A step of predicting the congestion state of the charging spot when the one electric vehicle approaches the charging spot based on the calculated expected charging rate of the approaching vehicle;
Presenting the predicted congestion status information to the one electric vehicle;
A congestion status presentation method characterized by comprising:

Images