US-12624956-B2 - Charging station recommendation device and method therefor

US12624956B2US 12624956 B2US12624956 B2US 12624956B2US-12624956-B2

Abstract

A charging station recommendation device and a method therefor include a data collection device that collects real-time information of at least one charging station and real-time information of at least one vehicle associated with the at least one charging station, a data processing device that generates charging information including a congestion of the at least one charging station, based on the real-time information of the at least one charging station and the real-time information of the at least one vehicle, a data storage storing the charging information of the at least one charging station, and a data application device that recommends an optimal charging station among the at least one charging station to a host vehicle, based on the charging information of the at least one charging station, which is stored in the data storage.

Inventors

Won Seok YANG
Joon Sung KWON

Assignees

HYUNDAI MOTOR COMPANY
KIA CORPORATION

Dates

Publication Date: 20260512
Application Date: 20221006
Priority Date: 20220218

Claims (18)

1 . A charging station recommendation apparatus, comprising: a data collection device configured to collect real-time information of at least one charging station and real-time information of at least one vehicle associated with the at least one charging station; a data processing device configured to generate charging information including a congestion of the at least one charging station, based on the collected real-time information of the at least one charging station and the collected real-time information of the at least one vehicle; a data storage configured for storing the generated charging information of the at least one charging station; and a data application device configured to recommend an optimal charging station among the at least one charging station to a host vehicle, based on the generated charging information of the at least one charging station, the generated charging information being stored in the data storage, wherein the data application device is configured to allocate a predetermined value to each of the at least one charging station selected for each predetermined time period among a plurality of charging stations, based on at least one of a charging station preference of a driver, a charger type preference of the driver, a distance to a final destination, or a distance to a stop, and to recommend the optimal charging station, in accordance with the allocated predetermined value and real-time information of at least one vehicle associated with the at least one charging station, and wherein the congestion information and the vehicle information include at least one of an average daily time taken for charging, an estimated charging time, a charging start time, or a charging end time, and wherein the data application device is further configured to calculate a weight for each of the charging stations in real time, by considering an estimated available charging time of the at least one charging station, an estimated arrival time of the host vehicle, a required charging time, a congestion level of the charging station, a driver's preference, and a state of the host vehicle, based on the real-time information of the at least one vehicle and the real-time information of the at least one charging station, and to recommend the optimal charging station to the host vehicle in real time based on the calculated weight.
2 . The charging station recommendation apparatus of claim 1 , wherein the data application device is configured to determine a difference between an estimated charging end time of the at least one vehicle and an estimated arrival time when the host vehicle arrives at the optimal charging station, when the at least one vehicle is a vehicle which is being charged in the optimal charging station, and the optimal charging station is recommended when the difference is less than a predetermined time period.
3 . The charging station recommendation apparatus of claim 1 , wherein the data application device is configured to determine a difference between an estimated charging end time of the at least one vehicle, the estimated charging end time including an estimated arrival time when the at least one vehicle arrives at the optimal charging station, when the at least one vehicle is a vehicle which is traveling to the optimal charging station, and the optimal charging station is recommended when the difference is less than a predetermined time period.
4 . The charging station recommendation apparatus of claim 1 , wherein the data processing device is configured to generate a database for the congestion, based on an average time taken for charging in the at least one charging station.
5 . The charging station recommendation apparatus of claim 4 , wherein the data processing device is configured to update the database for each predetermined time period, based on the collected real-time information of the at least one charging station and the collected real-time information of the at least one vehicle, and wherein the data storage is configured to store the generated charging information including the updated database.
6 . The charging station recommendation apparatus of claim 1 , wherein the data application device is configured to recommend the optimal charging station, when it is determined that it is impossible for the host vehicle to arrive at at least one of a destination of the host vehicle or a stop of the host vehicle, based on a state of charge, a distance to empty, a location of the host vehicle, or a distance to the destination or the stop, after the at least one of the destination or the stop is set, and wherein the data of the host vehicle includes at least one of position information of the host vehicle, a current state of charge (SOC) value of the host vehicle, or a distance to empty (DTE) of the host vehicle.
7 . The charging station recommendation apparatus of claim 1 , wherein the at least one charging station includes a charging station selected for each predetermined time period among the plurality of charging stations, the charging station in which an estimated arrival time when the host vehicle arrives at each of the charging stations is less than, or less than or equal to, a threshold time.
8 . The charging station recommendation apparatus of claim 1 , wherein the collected real-time information of the at least one charging station includes at least one of state information of a charger in the at least one charging station, a type of the charger, position information of the at least one charging station, or information related to convenient facilities around the at least one charging station.
9 . The charging station recommendation apparatus of claim 8 , wherein the state information of the charger includes at least one of whether the charger is charged, whether it is possible to use the charger, or whether the charger fails, and wherein the type of the charger includes at least one of an ultrafast type, a fast type, or a slow type.
10 . A charging station recommendation method, comprising: collecting, by a data collection device, real-time information of at least one charging station and real-time information of at least one vehicle associated with the at least one charging station; generating, by a data processing device, charging information including a congestion of the at least one charging station, based on the collected real-time information of the at least one charging station and the collected real-time information of the at least one vehicle; storing, by a data storage, the generated charging information of the at least one charging station; and recommending, by a data application device, an optimal charging station among the at least one charging station to a host vehicle, based on the generated charging information of the at least one charging station, the generated charging information being stored in the data storage, wherein the recommending of the optimal charging station among the at least one charging station to the host vehicle includes: allocating, by the data application device, a predetermined value to each of the at least one charging station selected for each predetermined time period among a plurality of charging stations, based on at least one of a charging station preference of a driver, a charger type preference of the driver, a distance to a final destination, or a distance to a stop, and real-time information of at least one vehicle associated with the at least one charging station, wherein the congestion information and the vehicle information include at least one of an average daily time taken for charging, an estimated charging time, a charging start time, or a charging end time, calculating, by the data application device, a weight for each of the charging stations in real time, by considering an estimated available charging time of the at least one charging station, an estimated arrival time of the host vehicle, a required charging time, a congestion level of the charging station, a driver's preference, and a state of the host vehicle, based on the real-time information of the at least one vehicle and the real-time information of the at least one charging station; and recommending, by the data application device, the optimal charging station, to the host vehicle in real time based on the calculated weight.
11 . The charging station recommendation method of claim 10 , wherein the recommending of the optimal charging station among the at least one charging station to the host vehicle includes: determining, by the data application device, a difference between an estimated charging end time of the at least one vehicle and an estimated arrival time when the host vehicle arrives at the optimal charging station; and recommending, by the data application device, the optimal charging station when the difference is less than a predetermined time period, when the at least one vehicle is a vehicle which is being charged in the optimal charging station.
12 . The charging station recommendation method of claim 10 , wherein the recommending of the optimal charging station among the at least one charging station to the host vehicle includes: determining, by the data application device, a difference between an estimated charging end time of the at least one vehicle, the estimated charging end time including an estimated arrival time when the at least one vehicle arrives at the optimal charging station, and an estimated arrival time when the host vehicle arrives at the optimal charging station; and recommending, by the data application device, the optimal charging station when the difference is less than the predetermined time period, when the at least one vehicle is a vehicle which is traveling to the optimal charging station.
13 . The charging station recommendation method of claim 10 , wherein the generating of the charging information including the congestion of the at least one charging station includes: generating, by the data processing device, a database for the congestion, based on an average time taken for charging in the at least one charging station.
14 . The charging station recommendation method of claim 13 , wherein the generating of the charging information including the congestion of the at least one charging station includes: updating, by the data processing device, the database for each predetermined time period, based on the collected real-time information of the at least one charging station and the collected real-time information of the at least one vehicle, and wherein the storing of the generated charging information of the at least one charging station includes: storing, by the data storage, the generated charging information including the updated database.
15 . The charging station recommendation method of claim 10 , wherein the recommending of the optimal charging station among the at least one charging station to the host vehicle includes: recommending, by the data application device, the optimal charging station, when it is determined that it is impossible for the host vehicle to arrive at at least one of a destination of the host vehicle or a stop of the host vehicle, based on data of the host vehicle or the at least one of the destination or the stop, after the at least one of the destination or the stop is set, and wherein the data of the host vehicle includes at least one of position information of the host vehicle, a current state of charge (SOC) value of the host vehicle, or a distance to empty (DTE) of the host vehicle.
16 . The charging station recommendation method of claim 10 , wherein the at least one charging station includes a charging station selected for each predetermined time period among the plurality of charging stations, the charging station in which an estimated arrival time when the host vehicle arrives at each of the charging stations is less than, or less than or equal to, a threshold time.
17 . The charging station recommendation method of claim 10 , wherein the collected real-time information of the at least one charging station includes at least one of state information of a charger in the at least one charging station, a type of the charger, position information of the at least one charging station, or information related to convenient facilities around the at least one charging station.
18 . The charging station recommendation method of claim 17 , wherein the state information of the charger includes at least one of whether the charger is charged, whether it is possible to use the charger, or whether the charger fails, and wherein the type of the charger includes at least one of an ultrafast type, a fast type, or a slow type.

Description

CROSS-REFERENCE TO RELATED APPLICATION The present application claims priority to Korean Patent Application No. 10-2022-0021688, filed on Feb. 18, 2022, the entire contents of which is incorporated herein for all purposes by this reference. BACKGROUND OF THE PRESENT DISCLOSURE Field of the Present Disclosure The present disclosure relates to a charging station recommendation device and a method therefor, and more particularly, relates to technologies of recommending a charging station using real-time information of the charging station. Description of Related Art Recently, interest in electric vehicle and hybrid vehicle has been increased to reduce carbon emissions. In general, an electric vehicle (EV) refers to a vehicle which utilizes its battery and motor without using petroleum-based fuels and an engine. Such an electric vehicle may operate using electrical energy charged in its battery as the battery loaded into the electric vehicle is charged by a general charging system in the parked state. When it is necessary to charge the battery when the electric vehicle operates, a driver of the electric vehicle should visit a charging station to charge the battery. However, unlike a general vehicle which utilizes oil as fuel, it takes a relatively long time for the electric vehicle to charge the battery. Thus, while many electric vehicles are being charged or are waiting for charging in a specific charging station, an electric vehicle which visits the charging station may wait for a long time to charge its battery or it may be difficult for the electric vehicle to be charged as much as it wants. The information included in this Background of the present disclosure is only for enhancement of understanding of the general background of the present disclosure and may not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art. BRIEF SUMMARY Various aspects of the present disclosure are directed to providing a charging station recommendation device configured for more accurately providing prediction information related to a charging station, when searching for an optimal charging station and guiding a driver to the optimal charging station using real-time charging station information and vehicle information and a method therefor. Another aspect of the present disclosure provides a charging station recommendation device configured for controlling a congestion of a charging station using real-time charging station information and vehicle information and a method therefor. The technical problems to be solved by the present disclosure are not limited to the aforementioned problems, and any other technical problems not mentioned herein will be clearly understood from the following description by those skilled in the art to which the present disclosure pertains. According to an aspect of the present disclosure, a charging station recommendation device may include a data collection device that collects real-time information of at least one charging station and real-time information of at least one vehicle associated with the at least one charging station, a data processing device that generates charging information including a congestion of the at least one charging station, based on the collected real-time information of the at least one charging station and the collected real-time information of the at least one vehicle, a data storage configured for storing the generated charging information of the at least one charging station, and a data application device that recommends an optimal charging station among the at least one charging station to a host vehicle, based on the generated charging information of the at least one charging station, the generated charging information being stored in the data storage. In an exemplary embodiment of the present disclosure, the data application device may determine a difference between an estimated charging end time of the at least one vehicle and an estimated arrival time when the host vehicle arrives at the optimal charging station and may recommend the optimal charging station when the difference is less than the predetermined time period, when the at least one vehicle is a vehicle which is being charged in the optimal charging station. In an exemplary embodiment of the present disclosure, the data application device may determine a difference between an estimated charging end time of the at least one vehicle, the estimated charging end time including an estimated arrival time when the at least one vehicle arrives at the optimal charging station, and an estimated arrival time when the host vehicle arrives at the optimal charging station and may recommend the optimal charging station when the difference is less than the predetermined time period, when the at least one vehicle is a vehicle which is traveling to the optimal charging station. In an exemplary embodiment of the present disclosure, th