Server, vehicle and charging information providing method
阅读说明:本技术 服务器、车辆及充电信息提供方法 (Server, vehicle and charging information providing method ) 是由 今井功 于 2019-07-08 设计创作,主要内容包括:本发明提供一种服务器、车辆及充电信息提供方法。服务器(5)对于多台车辆(1~4)的各个,计算设置于该车辆的可到达范围内的充电器的台数,所计算出的台数越多则将该车辆的台数换算为越少。服务器(5)通过对于至少一个充电器的各个合计能够到达该充电器的车辆的换算台数,来计算具有使用该充电器进行外部充电的可能性的车辆的实效性台数。服务器(5)基于实效台数来计算表示至少一个充电器的各个的潜在的外部充电的需要的指标,并向车辆(2)提供。(The invention provides a server, a vehicle and a charging information providing method. The server (5) calculates the number of chargers provided in the reachable range of each of the plurality of vehicles (1-4), and converts the number of the vehicles into a smaller number as the calculated number increases. The server (5) calculates the effective number of vehicles that can be externally charged using at least one charger by summing up the number of vehicles that can reach the charger. The server (5) calculates an index indicating the need for potential external charging of each of the at least one charger based on the number of effective stations, and provides the index to the vehicle (2).)
1. A server that provides charging information for external charging to a plurality of vehicles each equipped with a power storage device, the server comprising:
a communication device configured to be capable of communicating with the plurality of vehicles; and
an arithmetic unit for generating the charging information,
the arithmetic device, when providing the charging information to a target vehicle of the plurality of vehicles,
acquiring an reachable range of the subject vehicle determined by electric power stored in the electric storage device of the subject vehicle and a current location of the subject vehicle, and extracting at least one charger set within the acquired reachable range,
calculating the number of chargers provided in the reachable range of the vehicle for each of the plurality of vehicles, and converting the number of the vehicles into a smaller number as the calculated number of chargers increases,
calculating the number of effective vehicles, which is the number of effective vehicles that may be externally charged by the charger, by summing up the number of vehicles that can reach the charger for each of the at least one charger,
an index representing a need for potential external charging of each of the at least one charger is calculated based on the number of effective stations, and provided to the subject vehicle.
2. The server of claim 1, wherein,
a database is also provided for storing actual usage of the at least one charger,
the arithmetic device calculates the index based on the number of effective stations and the actual use case.
3. The server according to claim 2, wherein,
the actual usage includes a proportional usage rate of a usage period of each of the at least one charger with respect to a period divided according to a predetermined condition,
the arithmetic device calculates the index based on a value weighted by a first coefficient for the number of effective devices and a value weighted by a second coefficient for the usage rate.
4. The server according to claim 3, wherein,
among the usage rates, there is a standard range representing a range of the usage rates assumed in accordance with the number of effective stations,
the arithmetic device obtains the standard range according to the number of effective devices, and when the usage rate is higher than the maximum value of the standard range, the arithmetic device increases the weighting of the usage rate by the second coefficient as compared with a case where the usage rate is within the standard range.
5. The server according to claim 3, wherein,
among the usage rates, there is a standard range representing a range of the usage rates assumed in accordance with the number of effective stations,
the arithmetic device obtains the standard range from the number of effective devices, and when the usage rate is lower than the minimum value of the standard range, the arithmetic device increases the weight of the number of effective devices by the first coefficient as compared with a case where the usage rate is within the standard range.
6. The server according to claim 3, wherein,
when a period during which the data of the usage rate is acquired is shorter than a predetermined period, the arithmetic device increases the weight of the effective number of stations by the first coefficient, as compared with a case in which the period is longer than the predetermined period.
7. The server according to claim 3, wherein,
the arithmetic device increases the weighting of the usage rate by the second coefficient when the number of effective devices is less than a predetermined number of effective devices, as compared with when the number of effective devices is greater than the predetermined number of effective devices.
8. A vehicle that receives, from a server, provision of charging information for external charging, comprising:
an electrical storage device; and
a communication device configured to be capable of communicating with the server,
transmitting information indicating the electric power stored in the power storage device and the current location of the vehicle to the server,
the server acquires an reachable range of the vehicle determined by the electric power and the current location, and extracts at least one charger set within the acquired reachable range,
for each of the plurality of vehicles, calculating the number of chargers provided in the reachable range of the vehicle, and converting the number of the vehicles into a smaller number as the calculated number of chargers increases,
calculating the number of effective vehicles, which is the number of effective vehicles that may be externally charged by the charger, by summing up the number of vehicles that can reach the charger for each of the at least one charger,
calculating an index representing a need for potential external charging of each of the at least one charger based on the number of effective stations, and transmitting the index to the vehicle,
the vehicle further includes a notification device configured to notify a user of the vehicle of the index.
9. The vehicle according to claim 8,
the notification device includes a display device that displays each of the at least one charger by an icon corresponding to a size of the index.
10. A charging information providing method for providing charging information for external charging to a plurality of vehicles each having a power storage device mounted thereon, comprising the steps of:
acquiring an reachable range of a target vehicle determined by electric power stored in the power storage device of the target vehicle and a current location of the target vehicle when the charging information is provided to the target vehicle among the plurality of vehicles, and extracting at least one charger provided within the acquired reachable range;
calculating the number of chargers provided in the reachable range of the vehicle for each of the plurality of vehicles, and converting the number of the vehicles into a smaller number as the calculated number of chargers increases;
calculating an effective number of vehicles that may be externally charged by the charger by summing up the converted number of vehicles that can reach the charger for each of the at least one charger; and
an index representing a need for potential external charging of each of the at least one charger is calculated based on the number of effective stations, and provided to the subject vehicle.
Technical Field
The present invention relates to a server, a vehicle, and a charging information providing method, and more particularly, to a server that provides charging information for external charging to a plurality of vehicles, a vehicle that receives the provision of the charging information from the server, and a charging information providing method.
Background
In recent years, vehicles configured to be externally chargeable (specifically, electric vehicles, plug-in hybrid vehicles, and the like) have been spreading. The external charging means charging the vehicle-mounted power storage device with electric power supplied from the outside of the vehicle.
Generally, refueling of gasoline or the like is completed in a short time of about several minutes, while external charging requires a long time (typically several tens of minutes to several hours). Therefore, when external charging is required using a charger (also referred to as a charging stand or a charging station) at a destination, when the charger is being used by another vehicle, the user cannot start external charging of the vehicle until external charging of the other vehicle is completed.
In the case where the user cannot know whether or not the charger is usable (whether or not the charger is idle) without going to the charger, there is a possibility that another vehicle is in use although the charger is reached. In this case, the user needs to wait until the external charging of another vehicle is completed. Alternatively, in view of the user's schedule, there is a possibility that it is not possible to wait until the external charging of another vehicle is completed and it is necessary to search for another charger.
In order to improve the convenience of the user, it is desirable that the user can grasp which charger is selected to start external charging quickly even without going to the charger. Therefore, a charger disclosed in, for example, japanese patent application laid-open No. 2011-024335 provides a reference value of the charging wait time to the user.
Disclosure of Invention
From japanese patent application laid-open publication No. 2011-024335, the following is assumed: in a certain charger, one vehicle (electric vehicle) is in charge, and other vehicles are waiting for charging. In this case, the charging wait time is transmitted from the charger to the vehicle of the user in order for the user to determine whether or not to use the charger. The charging wait time includes a charging time (remaining charging time) of a vehicle that is already being charged and a charging time (predetermined charging time) of a vehicle that is waiting for charging (see, for example, paragraphs [0025] to [0027] of japanese patent application laid-open No. 2011-024335).
The existence of another vehicle that is waiting for charging when calculating the charging wait time is also considered in japanese patent laid-open No. 2011-024335. The vehicle waiting for charging indicates a vehicle that has performed an operation for scheduling external charging to the charger, and indicates an intention of external charging.
However, when a wider range such as a range of several kilometers to several tens of kilometers around the charger is considered, there may be other vehicles that are not currently waiting for charging (that is, although the intention of external charging is not shown), but are likely to be externally charged. The existence of such a vehicle (potential need for external charging) may be considered to be competitive with the vehicle of the user in selecting the charger, but is not considered in japanese patent application laid-open No. 2011-024335.
The present invention has been made to solve the above-described problems, and an object of the present invention is to provide appropriate information for a user to determine which charger is preferable to select when the user externally charges his or her vehicle.
(1) According to a server of an aspect of the present invention, charging information for external charging is provided to a plurality of vehicles each having a power storage device mounted thereon. The server is provided with: a communication device configured to be capable of communicating with a plurality of vehicles; and an arithmetic unit that generates charging information. When charging information is provided to a target vehicle among the plurality of vehicles, the arithmetic device acquires an reachable range of the target vehicle specified by electric power stored in the power storage device of the target vehicle and a current location of the target vehicle, and extracts at least one charger provided in the acquired reachable range. The computing device calculates the number of chargers provided in the reachable range of each of the plurality of vehicles, and converts the number of the vehicles into a smaller number as the calculated number of chargers increases. The computing device calculates the number of effective vehicles, which is the number of effective vehicles that can be externally charged by the charger, by summing up the number of vehicles that can reach the charger after conversion for each of the at least one charger. The arithmetic device calculates an index indicating a need for potential external charging of each of the at least one charger based on the number of effective devices, and provides the index to the subject vehicle.
In the configuration of (1) described above, the number of effective vehicles, which is the number of effective vehicles that may be externally charged using a charger installed in the range of the target vehicle (the vehicle of a certain user), is calculated. Then, an index indicating a potential need for external charging of the charger is calculated based on the number of effective devices. In this way, by taking into account the potential need for external charging, the degree of congestion of the charger and the charging wait time can be estimated with higher accuracy. Therefore, according to the configuration of (1), appropriate information for the user to determine which charger is preferable to select can be provided.
(2) The server is also provided with a database storing the actual use of at least one charger. The arithmetic device calculates an index based on the number of effective devices and the actual usage.
According to the configuration of the above (2), the index indicating the potential need for external charging is calculated based on the actual usage of the charger in addition to the number of effective batteries. By using the actual usage of the charger (for example, the actual usage on the same day of the week, the actual usage on the same time zone, or the like), the degree of congestion of the charger and the charging wait time can be estimated more accurately.
(3) The actual usage includes a ratio utilization rate of a usage period of each of the at least one charger with respect to a period divided according to a predetermined condition. The arithmetic device calculates an index based on a value weighted by the number of effective devices by the first coefficient and a value weighted by the usage rate by the second coefficient.
(4) The usage rate includes a standard range representing a range of usage rates assumed according to the number of effective stations. The arithmetic device obtains a standard range from the number of effective devices, and when the usage rate is higher than the maximum value of the standard range, the arithmetic device increases the weight of the usage rate by the second coefficient as compared with the case where the usage rate is within the standard range. (5) The usage rate includes a standard range representing a range of usage rates assumed according to the number of effective stations. The arithmetic device obtains a standard range from the number of effective devices, and when the usage rate is lower than the minimum value of the standard range, the arithmetic device increases the weight of the number of effective devices by the first coefficient as compared with the case where the usage rate is within the standard range.
As described later in detail, in the case where the usage rate of the charger is greater than the maximum value of the standard range, in other words, in the case where the usage rate is significantly higher than the usage rate that is generally assumed from the number of effective units, there is a possibility that a plurality of vehicles (unregistered vehicles) that do not perform communication with the server exist around the charger, and the charger is frequently used by these unregistered vehicles. According to the configurations of (3) and (4) described above, in such a case, in order to place more importance on the usage rate than the number of effective stations, the weighting of the usage rate by the second coefficient is made larger than in the case where the usage rate is within the standard range. Thus, the index is calculated mainly based on the usage rate, and the influence of the past actual usage can be reflected to a greater extent by the index. As a result, the calculation accuracy of the index is improved, and the degree of congestion of the charger and the charging wait time can be estimated more accurately.
Conversely, when the usage rate of the charger is smaller than the minimum value of the standard range, in other words, when the usage rate is significantly lower than the usage rate that is normally assumed from the number of effective units, the usage rate of the charger may become too low for the reason that the charger is installed recently, for example, and the usage rate is not sufficiently recognized by the user. According to the configurations of (3) and (5) described above, in such a case, in order to place more importance on the number of effective stations than the usage rate, the weighting of the number of effective stations by the first coefficient is made larger than in a case where the usage rate is within the standard range. Therefore, the index is calculated mainly based on the number of effective units, and the influence of the number of effective units can be reflected to a greater extent by the index. As a result, the calculation accuracy of the index is improved, and the degree of congestion of the charger and the charging wait time can be estimated more accurately.
(6) When the period for acquiring the data of the usage rate is shorter than a predetermined period, the arithmetic device increases the weight of the number of effective devices by the first coefficient as compared with the case where the period is longer than the predetermined period. (7) When the number of effective devices is less than the predetermined number, the arithmetic device increases the weight of the usage rate by the second coefficient, as compared with the case where the number of effective devices is greater than the predetermined number.
According to the configurations of (6) and (7) described above, when the acquisition period of the usage rate is shorter than the predetermined period, it is considered that there is a possibility that the data amount of the usage rate is insufficient, and the weighting of the number of effective stations by the first coefficient is increased. Conversely, when the number of effective devices is less than the predetermined amount, the data amount of the number of effective devices is considered to be insufficient, and the weighting of the usage rate by the second coefficient is increased. In this way, the parameter having a larger data size and higher reliability among the usage rate and the number of effective chargers greatly affects the index, and therefore, the calculation accuracy of the index is improved. Therefore, the degree of congestion of the charger and the charging wait time can be estimated more accurately.
(8) According to the vehicle of the other aspect of the invention, the provision of the charging information for the external charging is accepted from the server. The vehicle includes a power storage device and a communication device configured to be able to communicate with a server. The vehicle transmits information indicating the electric power stored in the power storage device and the current location of the vehicle to the server. The server acquires an reachable range of the vehicle determined by the electric power and the current location, and extracts at least one charger set within the acquired reachable range. The server calculates the number of chargers provided in the reachable range of each of the plurality of vehicles, and converts the number of the vehicles into a smaller number as the calculated number of chargers increases. The server calculates the number of effective vehicles, which is the number of effective vehicles that may be externally charged using at least one charger, by summing up the number of vehicles that can reach the charger. The server calculates an index indicating a need for potential external charging of each of the at least one charger based on the number of effective stations, and transmits the index to the vehicle. The vehicle further includes a notification device configured to notify a user of the vehicle of the indicator.
According to the configuration of (8) above, the user of the vehicle can grasp the magnitude of the index calculated in the same manner as the configuration of (1) above by the notification device. Thus, the user can select a desired charger based on the size of the index.
(9) The notification device includes a display device that displays each of the at least one charger by an icon corresponding to the size of the index.
According to the configuration of (9), the size of the index is visualized by displaying a colored icon corresponding to the size of the index, for example. This makes it easier for the user to grasp the size of the index.
(10) According to another aspect of the present invention, a charging information providing method is a method for providing charging information for external charging to a plurality of vehicles each having a power storage device mounted thereon. The charging information providing method includes first to fourth steps. The first step is a step of acquiring, when providing charging information to a target vehicle among the plurality of vehicles, an reachable range of the target vehicle specified by electric power stored in a power storage device of the target vehicle and a current location of the target vehicle, and extracting at least one charger provided in the acquired reachable range. The second step is a step of calculating the number of chargers provided in the reachable range of each of the plurality of vehicles, and converting the number of vehicles into a smaller number as the number of calculated chargers increases. The third step is a step of calculating the number of effective vehicles, which is the number of effective vehicles that can be externally charged by the charger, by summing up the number of vehicles that can reach the charger for each of the at least one charger. The fourth step is a step of calculating an index indicating a need for potential external charging of each of the at least one charger based on the number of effective devices, and providing the index to the subject vehicle.
According to the method (10), as in the configuration (1) or (8), appropriate information for the user to determine which charger is preferable to select can be provided.
The above and other objects, features, aspects and advantages of the present invention will become apparent from the following detailed description of the present invention when taken in conjunction with the accompanying drawings.
Drawings
Fig. 1 is a diagram schematically showing the overall configuration of a charging information providing system according to embodiment 1.
Fig. 2 is a diagram showing the configuration of the charging information providing system in more detail.
Fig. 3 is a diagram showing an example of a case where the charging information providing system is used.
Fig. 4 is a diagram showing an example of actual usage information of the charger.
Fig. 5 is a diagram for explaining the usage rate of the charger.
Fig. 6 is a diagram for explaining the number of effective devices in each charger.
Fig. 7 is a diagram for explaining a method of calculating the congestion index of the charger.
Fig. 8 is a flowchart showing a process of assisting selection of a charger in embodiment 1.
Fig. 9A is a first diagram for explaining a method of displaying a congestion index on a display of a navigation device.
Fig. 9B is a second diagram for explaining a method of displaying the congestion index on the display of the navigation device.
Fig. 10 is a flowchart showing a process of assisting selection of a charger in
Fig. 11 is a diagram for qualitatively explaining a relationship between the number of effective chargers and the usage rate of the chargers.
Fig. 12 is a flowchart showing a process for assisting selection of a charger in modification 1 of
Fig. 13 is a flowchart showing a process for assisting selection of a charger in
Detailed Description
In the embodiment described below, "charging information" indicating which charger is selected to be ideal is provided to each of the plurality of vehicles. A system for providing the charging information is referred to as a "charging information providing system", and the configuration thereof will be described in detail below with reference to the drawings. In the drawings, the same or corresponding portions are denoted by the same reference numerals, and description thereof will not be repeated.
[ embodiment 1]
< construction of charging information providing System >
Fig. 1 is a diagram schematically showing the overall configuration of a charging information providing system according to embodiment 1. The charging information providing system 9 includes a plurality of vehicles 1 to 4 and a
In order to prevent the explanation from becoming complicated, the example of the configuration in which 4 vehicles 1 to 4 are included in the charging information providing system 9 is explained, but actually, many more vehicles (for example, several thousands to several hundred thousands) may be included in the charging information providing system 9. In addition, more than 6 chargers may be provided.
The vehicle 1 and the
Further, the charger a and the
Fig. 2 is a diagram showing the configuration of the charging information providing system 9 in more detail. The
Vehicle 1 includes an ECU (Electronic Control Unit) 100, a
The
The
The
More specifically, the
The
The ECU100 includes a CPU (Central Processing Unit), a memory, an input/output port, and a timer, all of which are not shown. The ECU100 controls each device in the vehicle 1 so that the vehicle 1 is in a desired state based on detection values of various sensors (not shown) and a program stored in a memory.
The
The
The
The
The
< calculation of usage >
Fig. 3 is a diagram showing an example of a case where the charging information providing system 9 is used. In embodiment 1, it is assumed that the chargers a to F are arranged at six places as shown in fig. 3, and 4 vehicles 1 to 4 are traveling. In the charging information providing system, in order to assist the selection of the charger by the user, an index indicating a potential need (potential congestion degree) for plug-in charging by the chargers a to F is provided as the charging information to the respective vehicles 1 to 4. For the sake of simplicity of the following description, the processing executed by the
The
Fig. 4 is a diagram showing an example of actual use information of the charger a. As shown in fig. 4, the actual usage information includes information indicating that the usage time (unit: point) of the charger a is measured for each time period. The time period is, for example, set to four hours in six equal parts per day (24 hours). In addition, the day on which the usage time is measured is divided into a day of the week, and the day is also divided into a weekday, a holiday, or a holiday.
As can be read from the example shown in fig. 4, for example, the first day of a certain month is wednesday, and the use time of the charger a in the period from late night to early morning (0 time to 4 times) of the day is 20 minutes. It can be read that friday on the third day is a holiday, and the use time of charger a in the period from noon to evening (12 to 16) on that day is 200 minutes.
Such information on the use time is continuously acquired and accumulated in the actual
Fig. 5 is a diagram for explaining the usage rate of charger a. Referring to fig. 5, the use time shown in fig. 4 is divided by a working day and a holiday or a holiday, for example, and further, by a time period. And, the usage rate (unit:%) of the charger a for each time period is calculated by averaging the measurement results of the usage time (unit: minutes) for each division. In the example shown in fig. 5, for example, it is calculated that the usage rate of the charger a in the time period from late night to early morning (0 time to 4 time) on a weekday is 5% and is very low, but the usage rate of the charger a in the time period from midday to late afternoon (12 time to 16 time) on a holiday or holiday is 68% and is very high.
The calculation result of the usage rate of the charger a is also stored in the
Although fig. 4 and 5 illustrate an example in which the attribute distinction between the time zone and the measurement day is used for calculating the usage rate, the usage rate may be calculated by dividing the usage time by another parameter that can affect the usage rate. For example, weather such as sunny, cloudy, and rainy weather may be acquired from a weather information database, not shown, and the usage rates of the chargers may be calculated for each weather. In addition, the usage rates of the chargers may be calculated separately for each outside air temperature. Alternatively, any of the parameters of the time zone, the attributes of the measured day, the weather, and the outside air temperature may be combined.
< calculation of number of effective stations >
In addition to the actual use of the chargers a to F, the present embodiment also considers the traveling conditions of the vehicles 1 to 4. Specifically, the number of chargers provided in a vehicle reachable range (referred to as an "reachable range") is first calculated for each of the vehicles 1 to 4, and the larger the number of calculated chargers is, the smaller the number of vehicles is. The number of converted units is hereinafter referred to as "the number of converted units n".
Fig. 6 is a diagram for explaining the converted number n of vehicles 1 to 4. In fig. 6, the reach of the vehicle 1 is represented by a circular region R1. The circular region R1 is a circular region having a radius of the distance the vehicle 1 can travel, with the current location of the vehicle 1 as the center.
More specifically,
In the example shown in fig. 6, the charger a is located inside the circular region R1, but the remaining chargers B to F are located outside the circular region R1. In this case, vehicle 1 cannot reach chargers B to F but only charger a. This means that, when considering from the perspective of the charger a, the plug-in charging of the vehicle 1 is always performed using the charger a, although it is not known at what point in time. In the present embodiment, the converted number n of vehicles 1 is defined by the reciprocal of the number of chargers that the vehicle 1 can reach, and is calculated as n 1/1 1.00.
Next, with respect to the
Similarly, with respect to the
Next, for each charger A, B, C, E, the "effective number N" of vehicles, which is the effective number of vehicles that may be plug-in charged using that charger, is calculated from the converted number N of vehicles 1 to 4.
In the example shown in fig. 6, two
Likewise, the only vehicle that can reach charger B is
Then, an index indicating a potential need for the plug-in charging by the chargers a to F is calculated by a function including the number N of effective chargers and the usage rate U of the chargers in the current time slot as parameters. This index is referred to as "congestion index" and is denoted by I. The function for calculating the congestion index I is referred to as an "evaluation function" and is denoted by f. The congestion index I is expressed by the following equation (1) using an evaluation function f having the number of effective stations N and the usage U as parameters.
I=f(N,U)…(1)
The evaluation function f may take various forms as a concrete one. In embodiment 1, as a simplest example, the evaluation function f is defined by the product of the number of effective devices N and the usage rate U (see the following expression (2)).
I=N×U…(2)
Fig. 7 is a diagram for explaining a method of calculating the congestion index I of the chargers a to F. Referring to fig. 7, as described above, the effective number N of chargers a is 1.25. On the other hand, in the case of the time period from 8 hours to 12 hours of the current working day, the usage U of the charger a is 35% from the usage list shown in fig. 5. Therefore, the congestion index I of the charger a at present is calculated to be 1.25 × 35% ≈ 0.44.
The number of effective chargers B is 0.25. The usage rate U of charger B in the time period from 8 hours to 12 hours on the working day is 40% (not shown). In this case, the congestion index I of charger B is calculated to be 0.25 × 40% — 0.10. The same applies to the calculation method of the congestion index I of the other chargers C to F, and detailed description will not be repeated.
As the number N of effective chargers a increases, the number of vehicles that can be plug-in charged using the chargers a increases. However, if the number of vehicles that can be plug-in charged using charger a is large, plug-in charging is not necessarily performed actually. Depending on the time zone, there may be a case where the need for plug-in charging is small even if the number of vehicles is large, and conversely, there may be a case where the need for plug-in charging is large even if the number of vehicles is small. Therefore, the past actual usage (usage rate U) of the charger a in the current time period is also considered. Since the high usage rate U means that the demand of the charger a is large in the same period of time in the past, there is a high possibility that the demand of the charger a is also large at the present time.
As described above, according to the present embodiment, the congestion index I of the charger a is calculated by considering both the effective number N and the usage rate U. The higher the congestion index I, the greater the potential need for plug-in charging using the charger, the higher the likelihood that the charger is congested, although it is not actually certain whether it is being used. Therefore, when a user has a plurality of chargers installed in the range of the vehicle, the possibility of avoiding congestion or shortening the waiting time is increased by selecting a charger having a low congestion index I as much as possible. In this way, the
< selection assistance processing flow >
In the following flowchart, a configuration in which the
Fig. 8 is a flowchart showing a process of assisting selection of a charger in embodiment 1. In the flowcharts of fig. 8 and fig. 10 described later, a series of processes executed by the vehicle 2 (the ECU100 of the vehicle 2) is shown on the left side in the drawing, and a series of processes executed by the server 5 (the
Although not shown, the
Referring to fig. 8, at S11, vehicle 1 desires plug-in charging and
In S21, the
In S22, the
In S23, the
In S24, the
In S25, the
In S26, the
At S27, the
In S12, when the ECU100 of the
Fig. 9A and 9B are diagrams for explaining a method of displaying the congestion index I on the
As an example, as shown in fig. 9A, the congestion index I of the charger is divided into five stages according to predetermined values I1 to I4. The icons are displayed in red when the congestion index I is I4 or more, in orange when the congestion index I is I3 or more and less than I4, in yellow when the congestion index I is I2 or more and less than I3, in green when the congestion index I is I1 or more and less than I2, and in blue when the congestion index I is (0 or more) less than I1. In this way, by visualizing the congestion index I with the color of the icon of the charger, the user can more easily select a charger with a low congestion index I (a charger with a low congestion degree).
Although an example of color division of icons by the congestion index I (absolute value) is described in fig. 9A, the method of color division is not particularly limited. For example, the icons may be color-divided according to the relative value of the congestion index I.
To explain in more detail, in the flowchart of fig. 8, a description is given of a case where the chargers that are the calculation targets of the congestion index I are chargers A, B, C, E located at four positions within the reach of the
Specific examples are given for explanation. The
For example, as shown in fig. 9B, the icon may be displayed in red when the relative congestion index P is 90% or more (and 100% or less), in orange when the relative congestion index P is 70% or more and less than 90%, in yellow when the relative congestion index P is 50% or more and less than 70%, in green when the relative congestion index P is 30% or more and less than 50%, and in blue when the relative congestion index P is (0% or more) less than 30%.
The user of
As described above, in embodiment 1, the number of effective vehicles N is calculated, which indicates the number of effective vehicles that are located within a range that can reach a certain charger and that can be plug-in charged by the charger. Then, a congestion index I (═ N × U) as an index indicating the magnitude of the potential need for plug-in charging by the charger is calculated based on the number N of effective chargers and the past actual usage of the charger. By using the congestion index I, the user can appropriately select a charger with a low probability of congestion. Thus, according to embodiment 1, it is possible to provide appropriate information for the user to determine which charger is preferable to select.
In the present embodiment, the description has been given of the mode in which both the number N of effective stations and the usage rate U are used in the calculation of the congestion index I, but the usage rate U is not necessarily used. The large number of effective vehicles N that can reach a certain charger means that the number of vehicles that can be plug-in charged using the charger is large, and therefore the charger is highly likely to be crowded. That is, the possibility of congestion of the charger can be estimated only from the effective number N. Therefore, the congestion index I may be set to the actual number N of chargers without considering the past actual use of a certain charger.
Note that the chargers extracted by the
In embodiment 1, the description has been given of the case where any of the vehicles 1 to 4 is an electric vehicle, but the vehicles 1 to 4 may be plug-in hybrid vehicles. In the plug-in hybrid vehicle, since refueling is possible even when the travelable distance is reduced, the need for plug-in charging is considered to be relatively small compared to the electric vehicle. Therefore, the
[ embodiment 2]
In embodiment 1, an example in which the congestion index I is defined by the product of the number N of effective chargers and the usage rate U is described (see the above equation (2)). However, this is merely an example of the evaluation function f for calculating the congestion index I of the charger a, and the form of the evaluation function f is not particularly limited. In
In
I=αN+βU…(3)
The coefficient α of the number of effective devices N and the coefficient β of the usage rate U in the equation (3) are determined by an optimization algorithm so as to optimally match data (a large number of combinations of the congestion index I, the number of effective devices N, and the usage rate U, so-called big data) actually acquired when a large number of vehicles are plug-in charged. As described below, the coefficients α and β can be determined by machine learning using a gradient method.
Consider a case where a certain vehicle (referred to herein as "vehicle V") is plug-in charged by a certain charger (referred to as "charger CHG"). In this case, the
Similarly, when plug-in charging is performed for a vehicle other than vehicle V, by taking the values of the number of effective stations N, the usage rate U, and the congestion index I into formula (3), another equation is obtained in which the coefficients α and β are unknowns. By doing so, the same equation as the number of times there is a chance of plug-in charging can be obtained.
The combination of the two coefficients α, β is calculated by the gradient method in such a way as to best fit the multiple equations thus obtained. More specifically, the mean square error J of equation (3) is calculated by machine learning (α N + β U-I)2Is the combination of the smallest coefficients alpha, beta. By using the calculated coefficients α and β, the congestion index I can be calculated from the number N of effective vehicles and the usage rate U when plug-in charging of the vehicle is newly performed.
Fig. 10 is a flowchart showing a process for assisting selection of a charger in
Referring to fig. 10, the flowchart differs from the flowchart in embodiment 1 (see fig. 8) in that the process of S36 is included instead of the process of S26. In S36, the
As described above, in
[ modification 1 of embodiment 2]
In
Fig. 11 is a diagram for quantitatively explaining a relationship between the effective number N of chargers and the usage rate U of the chargers. In fig. 11, the horizontal axis represents the number N of effective chargers, and the vertical axis represents the usage rate U of the chargers.
There is a correspondence between the number N of actual chargers at present and the usage rate U of actual chargers in the past. To describe in more detail, generally, the larger the number N of effective chargers, the larger the number of vehicles to be plug-in charged by using the chargers in the near future. This trend is considered to be the same in the past. Therefore, the usage rate U of the charger is higher as the number N of effective chargers is larger. As an example of such an example, fig. 11 shows an example in which the usage rate U linearly increases as the number of effective devices N increases (see a straight line L1).
Generally, if the number of effective stations N is determined, the usage rate U is also included in a certain range including the straight line L1. This range is referred to as a "standard range" of the usage rate U. In fig. 11, a straight line indicating the maximum value of the standard range is denoted by L2, and a straight line indicating the minimum value of the standard range is denoted by L3.
Hereinafter, a case where the effective number N of chargers (referred to as chargers X) is N0 in a certain time period (referred to as time period T) will be described. As shown in fig. 11, the standard range of the usage rate U when the number of effective devices N is N0 is a range between the minimum value Umin and the maximum value Umax.
The usage rate U of the charger X in the time period T stored in the
Next, the usage rate U of the charger X in the time period T is assumed to be Ua. Ua is higher than the maximum value Umax of the standard range. That is, the usage rate U of the charger X in the time period T is significantly higher than the usage rate normally assumed from the number N of effective stations. In this case, in the past actual use situation of the charger X, there is a possibility that a plurality of unregistered vehicles exist around the charger X in the time period T or a plurality of vehicles exist around the charger X due to some activity or the like, and the charger X is frequently used by these vehicles.
In view of the above, in the case where the usage rate of the charger in a certain period of time is larger than the maximum value of the standard range calculated from the number of effective chargers, the congestion index I is calculated from a calculation formula different from the case where the usage rate of the charger is within the standard range in order to consider the presence of unregistered vehicles and the like. Specifically, when the usage rate of the charger is within the standard range, the coefficients α and β (see the above equation (3)) are used for calculating the congestion index I, whereas when the usage rate of the charger is larger than the maximum value of the standard range, the other coefficients γ and δ are used as shown in the following equation (4).
I=γN+δU…(4)
The coefficients γ and δ in the equation (4) can be determined by machine learning using a gradient method on a large amount of data acquired when the usage rate of the charger is higher than the maximum value of the standard range, similarly to the coefficients α and β.
When equation (3) is compared with equation (4), the size of coefficient δ relative to coefficient γ (δ/γ) is larger than the size of coefficient β relative to coefficient α (β/α). This means that, when the usage rate of the charger is higher than the maximum value of the standard range, the 2 nd term (δ U) of the expression (4) is relatively more emphasized than the 1 st term (γ N) of the expression (4), in other words, the usage rate U is weighted more than the actual number of stations N.
In contrast, the case where the usage rate U of the charger X in the period T is Uc lower than the minimum value Umin of the standard range is explained. In this case, the usage rate U of the charger X in the time period T is significantly lower than the usage rate normally assumed by the number of effective stations N. This is likely, for example, because the charger X was set recently, and the presence of the charger X after the setting was not sufficiently recognized or the like, and the usage rate U becomes too low in the past actual use case of the charger X. In this case, the congestion index I is also calculated from a calculation formula using another coefficient ∈ or ζ (see the following formula (5)).
I=εN+ζU…(5)
Here, the size of the coefficient ∈ relative to the coefficient ζ (═ ∈/ζ) is larger than the size of the coefficient α relative to the coefficient β (═ α/β). This means that when the usage rate of the charger is smaller than the minimum value of the standard range, the term 1 (∈ N) of the expression (5) is relatively more important than the term 2(ζ U) of the expression (5), in other words, the term means that the number of effective devices N is weighted more than the weight of the usage rate U.
In fig. 11, an example in which the usage rate U linearly increases as the number of effective devices N increases is described. However, the function indicating the manner of increase of the usage rate U is not particularly limited as long as the usage rate U monotonically increases as the number of effective stations N increases.
Fig. 12 is a flowchart showing a process for assisting selection of a charger in modification 1 of
Since the processes of S41 to S45 are the same as those of S31 to S35 in
At S46, the
In S471, the
In contrast, when usage rate U is outside the standard range (no in S471),
On the other hand, when the usage U is smaller than the minimum value Umin of the standard range (no in S472), the
When any one of the processes of S473 to S475 is finished, the
As described above, in modification 1 of
In addition, in the example shown in fig. 12, an example in which three cases are divided according to the magnitude relationship between the usage rate U of the charger and the standard range is explained. However, the division may be performed only whether the usage rate U of the charger is within the standard range or higher than the maximum value Umax of the standard range. Further, the division may be performed only as to whether the usage rate U of the charger is within the standard range or lower than the minimum value Umin of the standard range.
(
As described above, the coefficients α and β are calculated by applying an optimization algorithm such as machine learning using a gradient method to a large amount of data (big data). Generally, in order to ensure the accuracy of machine learning, a sufficient amount of data needs to be prepared. Therefore, if the amount of data relating to the actual usage (usage rate U) of the charger is insufficient, the accuracy of calculating the coefficients α and β may be low.
In addition, even when one or more vehicles are present within the range of a certain charger, whether or not plug-in charging using the charger is actually performed is probabilistic. If the number of vehicles (effective number N) existing within the reach of the charger is very large, the congestion index I appropriately reflects the potential need for plug-in charging using the charger. However, if the number N of effective chargers is too small, the influence of the variation becomes large, and even if the congestion index I is calculated, the congestion index I may not be reliable. As described above, in
Fig. 13 is a flowchart showing a process for assisting selection of a charger in
In S561, the
When the data amount of the usage rate U is sufficient and the number of effective stations N is equal to or greater than the reference number of stations Nc (yes in S561), the
When the data amount of the usage rate U is sufficient but the number of effective stations N is smaller than the reference number of stations Nc (no in S562), the
I=α’N+βU…(6)
The coefficient α 'of the effective number N in expression (6) is smaller than the coefficient α in expression (3) by a predetermined value (α' < α). In this way, expression (6) is an expression obtained by correcting expression (3) so that the weight of the effective number N becomes smaller.
When the data amount of the usage rate U is insufficient and the number of effective stations N is equal to or greater than the reference number of stations Nc (no in S563), the
I=αN+β’U…(7)
The coefficient β 'of the usage rate U in the equation (7) is smaller than the coefficient β in the equation (3) by a predetermined value (β' < β). In this way, in S566, the congestion index I of the charger is calculated from equation (7) obtained by correcting equation (3) so that the weight of the usage rate U becomes smaller.
If the data amount of the usage rate U of a certain charger is insufficient and the number of effective stations N is smaller than the reference number of stations Nc (no in S563), the
As described above, in
However, it is not essential to consider both the data amount of the usage rate U of the charger and the number N of effective chargers. The following processing may also be performed: instead of the example shown in fig. 13, only whether or not the data amount of the usage rate U of the charger is sufficient is determined, and the weight of the usage rate U is different depending on the determination result. Further, the following processing may be performed: only the magnitude relation between the effective number N of chargers and the reference number Nc is determined, and the weight of the effective number N is made different according to the determination result.
The configuration for charging the
While the embodiments of the present invention have been described, it should be understood that the embodiments disclosed herein are illustrative and not restrictive in all respects. The scope of the present invention is indicated by the scope of the claims, and is intended to include all modifications within the meaning and range equivalent to the scope of the claims.
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