KR20210006768A - System for recommanding charging point of an electric vehicle - Google Patents

Abstract

The present invention relates to a system for recommending a charging station of an electric vehicle, comprising: an EV starting point recognition module which recognizes a starting point of the electric vehicle; a user EV POI recognition module which recognizes the places where a user of the electric vehicle visits frequently; a user EV trajectory recognition module which recognizes a road preferred by the user among the roads where the user moves from a starting point where the user visits frequently to a destination; a user CP POI recognition module which recognizes a charging station which is visited frequently by the user; a CP population recognition module which in real time recognizes the charged status of the charging station adjacent to a preferred road; a charging starting/ending charging volume recognition module which recognizes the charging volume when starting or ending the charging of the electric vehicle; and a control unit which is connected to be able to communicate with the electric vehicle and a mobile device possessed by the user of the electric vehicle, and to recommend to the user the charging station which can charge the electric vehicle for the charging volume needed for the electric vehicle to reach the destination. Therefore, user convenience is improved.

Description

Electric vehicle charging station recommendation system {SYSTEM FOR RECOMMANDING CHARGING POINT OF AN ELECTRIC VEHICLE}

The present invention relates to a system and method for recommending an electric vehicle charging station for recommending an optimal charging station for charging to a customer.

Interest in developing eco-friendly vehicles is increasing as the most effective alternative to achieving the carbon dioxide reduction target amount for each country in accordance with the strengthening of international regulations on greenhouse gas emissions. The construction of an electric vehicle charging infrastructure is urgently needed in line with the currently completed electric vehicle mass production schedule.

Unlike general internal combustion engine vehicles, electric vehicles are composed of batteries, electric motors, inverters, converters, and BMS (Battery Management System), and rechargeable secondary batteries are used for batteries.

The prerequisite for the spread of such electric vehicles is to construct the charging infrastructure, and countries around the world are in the process of deriving models for charging infrastructure configuration and service and conducting demonstration projects.

Meanwhile, electric vehicle (EV) charging station operators are disclosing the operating status of chargers (charging stations, CP: Charging Points) to attract customers.

Conventionally, a customer directly finds and charges a charging station that can be charged during his/her schedule by referring to information disclosed from the charging station operator.

In other words, if a customer (electric vehicle user) previously retrieves the charger operation status disclosed by the charging station operator and requests information on the charger usage status from the control system, the control system provides the necessary information back to the customer.

However, the existing charger usage status information service is a system in which a user can obtain necessary information only at the request of a customer. For this reason, there is a hassle of having to request information on the status of charger usage from the control system every time the customer is charging the electric vehicle.

The present invention was created to solve the conventional problem, and if the customer is initially registered as a member, an electric vehicle capable of recommending the optimal charging station to the customer at the appropriate time without the customer requesting a separate request to the control system An object thereof is to provide a charging station recommendation system and method.

In order to achieve the above object, the system for recommending an electric vehicle charging station according to the present invention includes: an EV departure point recognition module for recognizing a departure point of an electric vehicle; A user Eve PIO recognition module for recognizing where the electric vehicle user frequently goes; A user Eve trajectory recognition module for recognizing a preferred route among routes that the user frequently goes from a departure point to a destination; A user CPIO recognition module for recognizing a charging station that the user likes; A CP population recognition module that recognizes the charging state of the charging station adjacent to the preferred road in real time; A charging start/end charging amount recognition module for recognizing a charging amount when charging the electric vehicle starts and ends; And a control unit that is communicatively connected to an electric vehicle or a mobile device possessed by a user of the electric vehicle, and recommends a charging station capable of charging the electric vehicle to the user in order to charge an amount of charge required for the electric vehicle to go to the destination.

According to an example related to the present invention, the controller may recommend another charging station in which charging time is further shortened even when bypassing the charging station, taking into account a charging waiting time upon arrival at a charging station adjacent to the preferred road.

According to an example related to the present invention, a charging station adjacent to a path from the departure point to the destination has a plurality of chargers, and the control unit is configured to allow the user to arrive at the charging station compared to the charging completion time of each of the plurality of chargers. By calculating the time, it is possible to recommend a charger capable of charging in the order of a charging start time when arriving at the charging station.

According to an example related to the present invention, the user Eve PIO recognition module may recognize places that frequently go to each time zone.

According to an example related to the present invention, the user CPPI recognition module may search for a charger that can be used as a membership card of the favorite charging station.

According to an example related to the present invention, when the electric vehicle starts, it may further include a traffic condition recognition module in the EV Trejectory that recognizes the traffic condition on the preferred route and recommends a charging station in a section where there is no congestion. have.

According to an example related to the present invention, it further comprises a weather recognition module for recognizing whether it is snow or rain, and the control unit recommends charging the charging station to be recommended at the point of time immediately before snow or rain when the charging station to be recommended is outdoors Indoor charging stations can be recommended.

According to an example related to the present invention, the CP population recognition module may include a charging station adjacent to the user's preferred route as the user or customer uploads information when member authentication or charging starts to the charging station to the server of the control system. You can recognize the state of charge in real time.

According to an example related to the present invention, the user EVPIO recognition module may search for a charging station that can be charged when a registered customer arrives based on a charging service member card near the user's preferred charging station and the preferred charging station. have.

According to an example related to the present invention, the user's Eve trajectory recognition module may search for a charging station existing on a preferred route when moving from the origin to the destination.

According to an example related to the present invention, the user CPPI recognition module may recommend a charging station that can be charged according to the charging pattern of the user at the point of departure from the frequent destination.

According to an example related to the present invention, a charging time/period recognition module for recognizing the charging time and charging period of the user may be further included.

According to an example related to the present invention, the CP population recognition module determines the charging status of the charging station based on the time point at which the user is to be charged, and the number of chargers held for each charging station based on the location of the charging station. The density of each charging station can be estimated.

The effect of the electric vehicle charging station recommendation system according to the present invention will be described as follows.

First, as long as the customer (user) is registered as a member in the electric vehicle control center, the electric vehicle charging station recommendation system notifies the user at an appropriate time without requiring a separate search and request for the status of charger usage, etc., thereby improving user convenience. I can make it.

Second, the electric vehicle charging station recommendation system can track the traces of customers based on information coming into the electric vehicle control center.

Third, the electric vehicle charging station recommendation system is the location where the electric vehicle is parked (POI), the trektory (preferred path) that connects these places (POIs), the charging station that customers visit in this trektori, and the customer near the charging station. Charging stations that can be charged at the time of arrival, if the recommended charging station is outdoors, adjust the charging timing in consideration of the weather, and consider the traffic conditions and the amount of charging required to get to the destination. You can find and recommend it to your customers.

Fourth, the operating status of the charging station referred to by the user is based on the authentication/charging information of the member coming from the electric vehicle control center, and the density of the charging station can be predicted based on the density of the member's electric vehicle existing within the GPS radius of the charging station.

Fifth, the charger operation status information provided to the user by the electric vehicle charging station recommendation system of the present invention can be obtained more quickly than the charger operation status that can be checked by the user delaying 5 to 30 minutes through the Ministry of Environment.

1 is a conceptual diagram showing a module constituting an electric vehicle charging station recommendation system according to the present invention.
2 is a block diagram of a system for recommending an electric vehicle charging station of FIG. 1.
3 is a conceptual diagram showing an example of a semantic web as a method of implementing the electric vehicle charging station recommendation system in FIG. 1.
4 is a conceptual diagram showing a semantic web implementing the electric vehicle charging station recommendation system according to the present invention.
5 is a conceptual diagram illustrating a method of recognizing a state of a user's charging pattern by the electric vehicle charging station recommendation system according to the present invention.
FIG. 6 is a conceptual diagram illustrating a method of inferring a semantic situation for recommending a charging place/time to a user by the electric vehicle charging station recommendation system of the present invention using a probability-based state diagram.
FIG. 7 is a conceptual diagram showing a notification message for charging timing and charger recommendation transmitted to an electric vehicle dashboard of a user who uses car navigation.
FIG. 8 is a conceptual diagram showing a state in which a notification message for recommending charging timing and charging stations is transmitted to a user's phone using a car navigation system.
9 is a conceptual diagram for explaining in detail the configuration of the user Eve PIO recognition module and the user Eve trejectory recognition module of the present invention.
10 is a conceptual diagram illustrating a user CPIO recognition module of the present invention.
11 is a conceptual diagram for explaining the configuration of the charging start / end SoC and charging time / period recognition module of the present invention.
12 is a conceptual diagram illustrating an example of a method for recommending an electric vehicle charging station according to the present invention.
13 is a conceptual diagram illustrating a method of recommending an electric vehicle charging station according to an embodiment of the present invention.

Hereinafter, exemplary embodiments disclosed in the present specification will be described in detail with reference to the accompanying drawings, but identical or similar elements are denoted by the same reference numerals regardless of reference numerals, and redundant descriptions thereof will be omitted. The suffixes "module" and "unit" for components used in the following description are given or used interchangeably in consideration of only the ease of preparation of the specification, and do not have meanings or roles that are distinguished from each other by themselves. In addition, in describing the embodiments disclosed in the present specification, when it is determined that a detailed description of related known technologies may obscure the subject matter of the embodiments disclosed in the present specification, the detailed description thereof will be omitted. In addition, the accompanying drawings are for easy understanding of the embodiments disclosed in the present specification, and the technical idea disclosed in the present specification is not limited by the accompanying drawings, and all modifications included in the spirit and scope of the present invention It should be understood to include equivalents or substitutes.

Terms including ordinal numbers, such as first and second, may be used to describe various elements, but the elements are not limited by the terms. These terms are used only for the purpose of distinguishing one component from another component.

When a component is referred to as being "connected" or "connected" to another component, it is understood that it may be directly connected or connected to the other component, but other components may exist in the middle. Should be. On the other hand, when a component is referred to as being "directly connected" or "directly connected" to another component, it should be understood that there is no other component in the middle.

Singular expressions include plural expressions unless the context clearly indicates otherwise.

In the present application, terms such as "comprises" or "have" are intended to designate the presence of features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, but one or more other features. It is to be understood that the presence or addition of elements or numbers, steps, actions, components, parts, or combinations thereof, does not preclude in advance.

In the present invention, an electric vehicle is an eco-friendly vehicle, that is, an electric vehicle (EV), a hybrid electric vehicle (HEV), a plug-in hybrid vehicle (PHEV), and a fuel cell (FCEV) that drives a wheel using a power source of a battery. Electric Vehicle) can be understood as a concept. The core control device of the BMS (Battery Management System) can be installed inside the electric vehicle.

BMS manages the algorithm for predicting the distance available for driving, preventing full charging, preventing overcharging, and even charging between cells. It includes the function of battery replacement notification through failure management of battery cells or modules and battery life prediction.

The electric vehicle charging station recommendation system according to the present invention is a system that informs the customer of the charger usage status information, the electric vehicle charging location, and the charging time at an appropriate time even if the customer does not request the charger usage status information from the control system.

In the figure above, 1) information is the member information registered in the service company registered in the control system. If you register the above 1) information only once for the first time, you do not need to register additionally. This is because the initially registered member information is not only registered with the service company, but also registered as customer management information in the program in the control system.

Here, the control system is an electric vehicle control system.

The service companies may include, for example, ChargEV, Astrapic, Korea Charging (Happy Charger), the Ministry of Environment, and Korea Electric Power. Service providers are not limited thereto, and can be changed and updated.

The control system may include information on charging the electric vehicle at an appropriate time, for example, information on the status of use of a charger. The control system can recommend charging locations and charging times according to charging and driving patterns at an appropriate time to registered member customers.

To this end, the control system includes an electric vehicle charging station recommendation system that provides information on various electric vehicle charging for customer convenience.

The electric vehicle charging station recommendation system may be a frame work agency. The electric vehicle charging station recommendation system may be an artificial intelligence (AI) charging robot. The electric vehicle charging station recommendation system may be one of programs installed in the control system. It can also be referred to as an electric vehicle charging station recommendation system AI (artificial intelligence) charging infrastructure.

The electric vehicle charging station recommendation system is made to communicate in both directions with member customers (including mobile devices carried by customers). The electric vehicle charging station recommendation system may be configured to enable two-way communication with the electric vehicle used by the customer. The electric vehicle charging station recommendation system is configured to enable two-way communication with the control system. The electric vehicle charging station recommendation system is configured to enable bidirectional communication with the electric vehicle charging station 23 or the electric vehicle charger.

1 is a conceptual diagram showing a module constituting an electric vehicle charging station recommendation system according to the present invention. 2 is a block diagram of a system for recommending an electric vehicle charging station of FIG. 1.

The electric vehicle charging station recommendation system of the present invention recognizes a user EV POI recognition module 10, a user EV trajectory recognition module 11, and a user CP recognition POI. Module 12, charging start/end SoC and charging time/cycle recognition module 13, CP Population recognition module 14, EV start time recognition module 15, EV Trejectory ( EV Trajectory) includes a traffic condition recognition module 16 and a weather recognition module 17.

The electric vehicle charging station recommendation system (AI charging infrastructure) of the present invention analyzes data by the above-described module, and recommends an optimal charging station to a user at an appropriate time.

In the present specification, POI (Point of Interest) means a specific location in the real world or on a map or drawings that a specific person is interested in in a general sense, but in the present invention, "a place where an electric vehicle 19 (EV) is parked" Means.

The user EVPIO recognition module 10 is configured to analyze data using an Open API (Application Programming Interface). Open API is an open application program development environment.

User Eve P.O.I. Recognition module 10 is configured to recognize a place (parking place; POI) that a user frequently goes by time slot using an Open API. For example, a place where a user frequently goes may be a home, a stay, or a company (a place where the user regularly works). Stay means a place where the user stays for longer than a preset time.

The user Eve trajectory recognition module 11 is configured to recognize a preferred path 22 (TRAJECTORY) when moving from the first POI1 to the second POI2 using the Open API. For example, the term “trejectory” is a preferred route 22 among the roads (roads) that the user goes from home (POI1) to company (POI2).

The user CPPI recognition module 12 is configured to recognize a favorite charging station 23. CP (Charging Point) means a charging place or a charger. The user CPIO module is configured to search for a charger that can be used as a membership card of the charging station 23 that the user prefers in one cluster (CP Population) in which a plurality of chargers (CP) are gathered. For example, a happy charger card may be used as a membership card of a favorite charging station 23. The Happy Charger Card can be used to charge chargers (CPs) such as KEPCO, Ministry of Environment, and Gentel.

The charging time/end SoC (State of Charge; meaning the amount of charge) recognition module 131 is configured to recognize the SoC at the beginning of charging and the SoC at the end of charging.

In addition, the charging timing/cycle recognition module 132 is configured to recognize the charging timing and the charging period. The charging time/period recognition module 132 may receive and recognize a signal from the BMS of the electric vehicle 19.

The CP population recognition module 14 is configured to recognize the real-time charging status of the user's trajectory (preferred path 22) and the adjacent charging station 23. The CP population means the degree to which the charging stations (CP) are concentrated, that is, the density of the charging stations.

When the user authenticates the rotation and starts charging to the charger (CP), the information is uploaded to the server of the electric vehicle (19) control center (21), and the CP population recognition module (14) analyzes the logging data of the EV control center (21). It is possible to recognize a real-time charging state of the charging station 23.

The CP population recognition module 14 may recommend an optimal charger to a customer in consideration of the density of the member electric vehicle 19 within a radius close to the charging station 23 and GPS.

For example, by looking at the number of chargers in the charging station 23 adjacent to the user's trajectory as n (one cluster), it is possible to predict a charger (idle CP) that can be charged without waiting when the user arrives at the location.

For example, in the figure above, assuming that charging station 1 and charging station 2 are adjacent to each other and that charging station 3 is separated from charging stations 1 and 2, charging station 1 and charging station 2 can be grouped into a cluster. Charging station 1 has 2 chargers CP3 and CP4, and charging station 2 has 1 charger CP 1.

Charging station 3 is a separate cluster from charging station 1 and charging station 2, and has two chargers CP2 and CP5.

은 충전 중임을 표시하고, 속이 빈 빨간색 원형으로 표시된

은 충전 대기 중임을 표시한다.Marked with a solid red circle

Indicates charging, indicated by a hollow red circle.

Indicates waiting for charging.

The EV departure point recognition module is configured to recognize the departure point of the electric vehicle 19 through the following two methods.

First, the Eve E start time recognition module 15 may recognize through the user's mobile phone 20. For example, the starting point of the electric vehicle 19 may be recognized through a point in time when the user connects the electric vehicle 19 to Bluetooth using the mobile phone 20.

Second, the EV departure point recognition module 15 may predict the point of departure from the POI through learning (LEARNING).

The traffic condition recognition module 16 in the Eve Trejectory is configured to recognize the traffic condition in the road 22 preferred by the user. For example, it may be recommended to bypass the preferred route 22 when traffic is congested on the preferred route 22.

User CPIO recognition module 12, charging start/end SoC and charging time/cycle recognition module 132, CP population recognition module 14, EV departure time recognition module 15, and traffic conditions in the EV Trejectory Each of the recognition modules 16 may analyze logging data of the control system of the electric vehicle 19.

The weather recognition module 17 may analyze data using a web service. The weather recognition module 17 is configured to recognize snow or rain when the recommended charger is outdoors.

The electric vehicle charging station recommendation system may include a control unit 18. The control unit 18 includes the above-described user EVPIO recognition module 10, user EV trejectory recognition module 11, user CPPOI recognition module 12, charging start/end SoC and charging time/cycle recognition module It is connected to the CP population recognition module 14, the EV departure point recognition module 15, the traffic condition recognition module 16 and the weather recognition module 17 in the EV Trejectory. The control unit 18 is configured to recommend the optimal charging station to the customer at an appropriate time by using information recognized from the recognition modules such as the user Eve PIO recognition module 10.

When there is a snow or rain forecast from the weather recognition module 17, the control unit 18 may recommend charging the battery immediately before the snow or rain. In addition, the controller 18 may recommend the indoor charging station 23 when there is snow or rain forecast from the weather recognition module 17.

Each module of the electric vehicle 19 charger charging system configured as described above may perform the following functions.

The user EVPIO recognition module 10 may search for a charging station 23 that can be charged when a customer arrives based on the preferred charging station 23 and the service membership card held near the preferred charging station 23.

When moving from the customer's origin 27 (POI1) to the destination 28 (POI2), the user EV treasury recognition module 11 may search for a charging station 23 existing in the preferred route 22 (ROUTE). .

The user CPPOI recognition module 12 may recommend a charging station 23 that can be charged based on a customer's charging pattern at the point of departure from the POI.

The charging start/end SoC and the charging point/period recognition module 132 may recognize the charging panel of the customer and recommend the optimum charging station 23.

The CP population recognition module 14 can grasp the charging status of the charging station 23 based on the time when the customer will be charging.

The CP population recognition module 14 can estimate the density of each charging station 23 by location-based population.

The Eve departure recognition module may recognize the mildness of leaving the POI. The EV departure recognition module may estimate the departure time based on the moment when the electric vehicle 19 and the user's mobile phone 20, etc. are connected via Bluetooth or the customer's pattern (learning).

The traffic condition recognition module 16 in the EV Trejectory may recommend a charging station 23 in a section where there is no congestion in consideration of the traffic condition at the time when charging is required.

The weather recognition module 17 may recommend the indoor charging station 23 in order to reduce the hassle and inconvenience caused by charging with an umbrella or the like in the case of rain or snow.

The electric vehicle charging station recommendation system of the present invention can provide the following services.

An impact sensor may be installed at the charging port of the electric vehicle 19. The impact sensor may be configured to detect that the charging socket is inserted and coupled to the charging port.

The user EVPIO recognition module 10 detects that the charging station 23 is connected to the charging port of the electric vehicle 19 through an impact sensor, thereby recognizing the charging timing of the customer and accurately predicting the charging timing.

According to this configuration, the user Eve PIO recognition module 10 can accurately predict the charging timing even when self-charging at home using the impact sensor.

The user CPPI recognition module 12 may receive destination 28 information from the customer's navigation in the control system (or control center) of the electric vehicle 19.

Accordingly, the user CPIO recognition module 12 may recommend that the customer's electric vehicle 19 be further charged when the battery charge amount of the electric vehicle 19 is smaller than the charge amount required to reach the destination 28.

The CP population recognition module 14 may inform the customer of the usage status information of the charging station 23 when entering within a radius of 300m from the charging station 23 available with the customer's membership card.

At this time, the customer can check the usage status information of the charging station 23 and immediately make a charging reservation by pressing the charging reservation.

The electric vehicle charging station recommendation system of the present invention tracks the trajectory of a customer (member) based on information entering the EV control center 21 when a customer registers rotation information in the EV control center 21 (control system). can do.

According to the present invention, the electric vehicle charging station recommendation system includes a POI, a TRJECTORY that connects the POI, a charging station 23 (CP) that a customer visits within the trace, and a customer near the charging station 23 at the time of arrival. The chargers, when the recommended charger is outdoors, adjust the charging timing in consideration of the weather, and consider the traffic conditions and the SoC required to get to the destination (28). I can recommend it.

3 is a conceptual diagram showing an example of a semantic web as a method of implementing the electric vehicle charging station recommendation system in FIG. 1.

The present invention proposes a method of implementing an EV charging infrastructure electric vehicle charging station recommendation system with a Semantic Web.

In general, the semantic web refers to a link that connects the web and the web, but in this specification, the semantic web refers to a link that connects the POI and the POI instead of the web.

The electric vehicle charging station recommendation system may store the charging history as one piece of information through the main system of the phone 20 or the charging station 23 and annotate link information between the information.

According to the information link of the semantic web, it is easy for the controller 18 to comprehensively determine the information when recommending the charging station 23 by returning or moving the information recognized by each module to the previous one.

The electric vehicle charging station recommendation system includes user information registered in the customer management of the control center 21, destination 28 information at the current location through GPS and vehicle navigation, and the main system or GPS of the phone 20 and charging station 23. You can get charging location and charging information through.

For example, referring to FIG. 3, information such as ID: User 001, membership card: Ministry of Environment, vehicle type: Ioniq, and charging connector (CC): DC car demo can be obtained as user information.

When the user's electric vehicle (19) moves from the company (FROM) to the E-Mart Yangjae branch (TO), which is a charging location (CS, Chargine Station), the electric vehicle charging station recommendation system is charged through the main system of the phone (20) or the charging station (23). Information such as charging date and time: 3/8 (Fri) PM 6:20~50, SoC (charge amount) 30% at the start of charging, and SoC (charge amount) 60% at the end of charging can be obtained and stored.

In addition, when the user's electric vehicle (19) is charged at different times: 3/15 (Fri) PM 6:15~30 From the company to the E-Mart Yangjae store, SoC (charge amount) 30% when charging starts, SoC (charge amount) when charging ends In the case of charging at 60%, the electric vehicle charging station recommendation system may obtain and store charging information of the user through the main system of the phone 20 or the charging station 23 in the same manner.

In addition, when the user's electric vehicle (19) is charged: 3/8 (Fri) PM 6:20~50 PM from E-Mart Yangjae branch to the house and start charging SoC (charge) 30%, when charging ends SoC (charge) 60 In the case of charging in %, the electric vehicle charging station recommendation system may obtain and store charging information of the user through the main system of the phone 20 or the charging station 23 in the same manner.

After learning the above knowledge, the electric vehicle charging station recommendation system recommends a charging station 23 that can be directly charged on the way home when the customer's electric vehicle 19 leaves the company after 6 pm on Friday.

4 is a conceptual diagram showing a semantic web implementing the electric vehicle charging station recommendation system according to the present invention.

Referring to FIG. 4, the electric vehicle charging station recommendation system (EV charging infrastructure) may store charging information of member 1 among members of the Ministry of Environment, which is an EV charging service company, as follows. The electric car 19 of Member 1, a member of the Ministry of Environment, is a Hyundai electric car, and the car model is Ioniq 1. Member 1 moves from POI1 (FROM) to charging station 23 CP1. At this time, member 1 departs at 5:30 pm on the preferred route 22 (ROUTE 1). Member 1 departs at 6 pm after charging (charging 1) for 30 minutes at the charging station 23 CP1.

5 is a conceptual diagram illustrating a method of recognizing a state of a user's charging pattern by the electric vehicle charging station recommendation system according to the present invention.

The electric vehicle charging station recommendation system can recognize the customer's charging pattern.

The user EVPIO recognition module 10 may recognize where the user's electric vehicle 19 frequently goes. For example, the user Eve PIO recognition module 10 may recognize a company, home, SP1, or SP2 that customers frequently go to. Here, SP is an abbreviation of STAY POINT, and means a place where the electric vehicle 19 of a customer (user) stays for a predetermined time or longer. SP1 and SP2 refer to the first place and the second place where the customer stays longer than a preset time.

The user Eve trajectory recognition module 11 may recognize the preferred route 22 when the customer moves from one location POI1 to another location POI2.

For example, when a customer moves from home to SP1, from work to SP1, or from home to SP2, a preferred route 22 may be recognized.

The user CPPI recognition module 12 may recognize the charging station 23 CP1 or CP2 that the customer likes.

The charging start/end SoC recognition module 131 may recognize that the charging amount (startSoC) is less than 40% when the customer starts charging, and that the charging amount (endSoC) is less than 70% when charging ends.

In addition, the charging point/cycle recognition module can recognize that the customer performs charging on weekdays and evenings and periodically charging once every 3-4 days.

The CP population recognition module 14 may recognize a real-time charging state of a gun station adjacent to the road 22 that the user prefers.

When n chargers, for example, a first cluster in which CP1, CP3, and CP4 are gathered together, and another second cluster in which m chargers CP2 and CP5 are gathered, are separated from each other, the customer Upon arrival in the cluster or the second cluster, the CP population recognition module 14 may predict a charger that can be charged without waiting.

The EV departure point recognition module 15 may recognize the departure point of the electric vehicle 19 when a customer communicates with the electric vehicle 19 through Bluetooth through a mobile device and starts the vehicle.

For example, the Eve Departure Time Recognition Module 15 recognizes that the customer departs from the company at 7:00 pm on Monday, Tuesday and Friday, and leaves the company at 5:50 pm on Wednesday and Thursday. I can.

FIG. 6 is a conceptual diagram illustrating a method of inferring a semantic situation for recommending a charging place/time to a user by the electric vehicle charging station recommendation system of the present invention using a probability-based state diagram.

First (①), if a customer connects to the electric vehicle 19 via Bluetooth with a mobile device (eg, phone) at 7 pm on Tuesday, the probability of moving from the company to SP1 is 80% (0.8).

In the first step, the user Eve POI recognition module 10 may transmit a location (POI) that customers frequently go to to the user Eve trejectory recognition module 11.

The EV departure point recognition module 15 may transmit the user's EV trajectory recognition module 11 to the user EV trejectory recognition module 11 of the time when the customer's electric vehicle 19 departs.

In the second (②), the first information indicating that the probability of the customer moving from the company to SP1 is 50% (0.5) or more is transferred from the user Eve treasury recognition module 11 to the CP population recognition module 14. , Second information indicating that the possibility of charging by the preferred charging cycle is 70% (0.7) or more is transmitted from the user CPIO recognition module 12 to the CP population recognition module 14, and the customer's preferred charging station (CP Upon arrival at POI), third information indicating that the charging possibility is 70% (0.7) or more may be transmitted from the charging start/end SoC recognition module and the charging time/cycle recognition module 132 to the CP population recognition module 14.

When the first to third information is transmitted to the CP population recognition module 14, the CP population recognition module 14 recommends a charger with low POPULATION at a location adjacent to the customer's preferred road 22, and , The charger is recommended to arrive at the destination 28 in a minimum time.

7 is a conceptual diagram showing a state in which a notification message for charging timing and charger recommendation is transmitted to an electric vehicle dashboard of a user who uses car navigation. FIG. 8 is a conceptual diagram showing a notification message for recommending a charging timing and a charging station 23 that can be charged to a user's phone 20 using car navigation.

Referring to FIG. 7, the electric vehicle charging station recommendation system may transmit a charging timing and a charger recommendation notification message to a user who uses a car navigation system. The car navigation system can be embedded in the center fascia located between the driver's seat and the passenger's seat. A control panel unit 191 that performs navigation and audio (RADIO) functions may be disposed on the center fascia.

For example, "It's time to recharge! You have to wait 20 minutes or more for "E-Mart (Yangjae branch)", which you often go to," "Would you recommend it near the Gangnam Center Daycare"" is displayed on the dashboard of the user's electric vehicle (19). It can pop up.

Users can see the pop-up notification message and select "Yes" or "No".

Referring to FIG. 8, a notification message may be delivered to a mobile device (eg, phone 20) of a user who uses car navigation.

For example, a notification message "It is time to charge! Would you like to recommend a charging station 23 that can be charged immediately?" may pop up on the user's mobile device.

The user may request to recommend a charger by touching the pop-up notification message of the mobile device according to the pop-up notification message.

The configuration of each module included in the electric vehicle charging station recommendation system will be described in more detail.

9 is a conceptual diagram for explaining in detail the configuration of the user Eve PIO recognition module 10 and the user Eve trejectory recognition module 11 of the present invention.

The user Eve PIO recognition module 10 may recognize a place (POI) that a user frequently goes to using a Google API.

The user Eve trajectory recognition module 11 may recognize a preferred trajectory 22 during movement of a place where the user frequently goes by using the Google API.

The user EVE PIO recognition module 10 and the user EVE trejectory recognition module 11 may identify frequent places and preferred routes 22 by dividing weekdays/weekends (by day of the week) and time slots.

For example, the user Eve PIO recognition module 10 may recognize a house as a place where the user mainly stays at night (POI1 or POI2).

The user Eve PIO recognition module 10 may recognize the company as a place where the user mainly stays during the day (POI1 or POI2).

The user Eve PIO recognition module 10 may recognize the company as a place where the user mainly stays during the day (POI1 or POI2).

The user Eve PIO recognition module 10 may recognize SP1 (STAY POINT 1) or SP2 (STAY POINT 2) as a place where the user sometimes stays longer than a preset time even if the user does not stay periodically.

The user Eve PIO recognition module 10 may recognize SP1 (STAY POINT 1) as a place where the user frequently goes on weekdays. SP1 is located between POI1 and POI2. SP1 may be located in a trajectory 22 that the user prefers among the roads from POI1 to POI2.

The user Eve PIO recognition module 10 may recognize SP2 (STAY POINT 2) as a place where the user frequently goes on weekends. SP2 is not located between POI1 and POI2 and is not located within the radius of the circumference passing through POI1 and POI2. SP2 may be located on a path moving away from POI2. The SP2 may be located on a trajectory 22 that the user prefers while moving in a direction away from POI2.

10 is a conceptual diagram for explaining the user CPIO recognition module 12 of the present invention.

The user CPIO recognition module 12 may recognize a charging station (CP-POI1, CP-POI2, see the map on the right of FIG. 10) that the user likes.

The user CPPI recognition module 12 may recognize the user's unique number when a user of the electric vehicle 19 authenticates as a member at the charging station 23. The user CPPI recognition module 12 may recognize the service company of the membership card used by the user of the electric vehicle 19 for member authentication at the charging station 23. Examples of service companies include ChargEV, Estrepic, Korea Charging (Happy Charger), Ministry of Environment, and KEPCO.

Examples of service companies linked to Korea Charging and the Ministry of Environment include Jeju Electric Vehicle Service, Gentel, Power Cube, Daeyoung Chaebi, KT, Everon, and POSCO ICT.

The charging station 23 may transmit a logging of the user's charging information to the control center 21. Logging refers to recording and making a record of various information during operation in order to record and preserve the operating state of the system, investigate user behavior, and analyze system operation when operating the system.

The charging information may include a charging time, a charging amount of the battery of the electric vehicle 19 at the beginning of charging and the end of charging. For example, the charging time charged by the user may be 12:30 to 50 minutes in the afternoon. At the start of charging, the amount of charge may be 30%. At the end of charging, the amount of charging may be 60%.

11 is a conceptual diagram for explaining the configuration of the charging start / end SoC and charging time / period recognition module of the present invention.

The charging start/end SoC and charging point/period recognition module 13 may recognize and learn a charging amount (SoC) when a user starts charging and ends charging by day and place.

For example, in FIG. 11, the X-axis is the charging time, and the Y-axis is the charging amount. At the beginning of charging, the amount of charge may be 30% to 40%. At the end of charging, the amount of charge may be 50% to 60%.

12 is a conceptual diagram illustrating an example of a method of recommending an electric vehicle 19 charging station 23 according to the present invention.

The user Eve treasury recognition module 11 may perform bidirectional communication with the user's phone 20 to recognize the start and end times of the user's movement for each trajectory (preferred road 22). For example, among the roads frequently used by the user, the preferred road 22 may be a road from the company to SP1. The road 22 that the user prefers as the SP1 in the company is mainly available on weekdays.

The user CPPI recognition module 12 recognizes the charging station 25 frequently used by the user. Although the user CPIO recognition module 12 is not frequently used by the user, it can recognize the charging station 26 that can be charged by using a membership card held by the user.

The charging stations 25 frequently used by users may be located adjacent to each other in a cluster form. There may be three charging stations 25 gathered in one cluster. Two of the three charging stations 25 each have one charger. The other charging station 25 has three chargers, and the charging station 25 frequently used by the user may be located close to the company.

Although not frequently used by the user, the charging station 26 capable of charging using a rotating card held by the user may be located close to the SP1.

The EV departure point recognition module 15 connects the mobile device (phone 20) and the vehicle at 6 PM by Bluetooth, so that the EV departure point recognition module 15 can recognize that the user is boarding the vehicle. have.

In order to recognize the real-time charging status, the electric vehicle charging station recommendation system circles the usage status of the charger 24 on the user's navigation or dashboard when the electric vehicle 19 user authenticates a member at the charging station 23 or starts charging. ) Can be displayed. In the case of the charger 24 filled with a circle, the charging station 23 indicates that the electric vehicle 19 is being charged, and the charger 24 with an empty circle indicates that the charging station 23 is empty and can be charged without waiting. do.

Users can go home via SP1 from the company. Users can move from home to SP2 on weekends. The charging station 23 may be located in each of the house and SP2. The charging station 23 near the house is a charging station 26 that is not frequently used but can be charged using a user's membership card, and the charging station 23 near SP2 is a charging station 25 that is frequently used.

The electric vehicle charging station recommendation system may identify the charging station 23 that can be charged in the company-SP1-preferred path to home (TRAJECTORY) based on the user's driving pattern.

Electric vehicle 19 charging recommendation system In proportion to the number of chargers for each charging station, charging stations 23 capable of charging can be found in proportion to the estimated charging end time after starting charging for each preferred route of the user.

The electric vehicle charging station recommendation system can recommend the charging station 23 by normalizing the number of chargers in the dense charging stations 23 and calculating the time when the current user will arrive at the location compared to the charging completion time of each charger.

13 is a conceptual diagram illustrating a method of recommending an electric vehicle 19 charging station 23 according to an embodiment of the present invention.

First, it is possible to recognize that the user is boarding the electric vehicle 19. The EV departure point recognition module 15 may detect that the user's phone 20 is connected to the electric vehicle 19 through Bluetooth and recognize that the user has boarded the electric vehicle 19.

Second, the user sets the destination 28 (POI_ANON2) through the navigation or the phone 20. The user Eve PIO recognition module 10 may determine whether the destination 28 set by the user is a place where the user frequently goes.

Third, the amount of charge of the battery of the user's electric vehicle 19 at the user's departure point 27 (POI_home) may be 40%. The control unit 18 of the electric vehicle charging station recommendation system may calculate the amount of charge required to reach the destination 28.

The controller 18 may determine whether additional battery charging is required by comparing the amount of charge required to reach the destination 28 with the current amount of charge. If the amount of charge required to reach the destination 28 is larger than the current amount of charge, the controller 18 may calculate an additionally required charge amount.

Fourth, the user EV CP PIO recognition module of the electric vehicle charging station recommendation system can recognize that there is a charging station 23 having one charger in the “Tancheon No. 2 public parking lot” on the way of the user.

The charging start/end SoC recognition module 131 may recognize the charging start/end SoC when there is an electric vehicle 19 being charged at “Tancheon No. 2 public parking lot”.

The control unit 18 may compare the charging time of the electric vehicle 19 being charged at “Tancheon No. 2 public parking lot” and the user's arrival time at “Tancheon No. 2 public parking lot”. The control unit 18 first calculates the charging waiting time of the later user when the later user arrives at the “Tancheon No. 2 public parking lot” before the charging of the electric vehicle 19 being charged is completed.

Fifth, the controller 18 may recognize that there is a charger capable of charging without waiting in the charging station 23 of the “Asia Park Public Parking Lot” having three chargers on the way the user is going.

Seventh, the control unit 18 has to wait 15 minutes or more even if the user arrives at the “Tancheon No. 2 public parking lot” on the way to the user, so the charging station of the “Asia Park Public Parking Lot” with a charging station 23 that can be charged without waiting (23) can be recommended.

The electric vehicle charging station recommendation system may determine that it is a gain in time even if the user rotates a little.

Eighth, the control unit 18 may re-recommend the best route to the destination 28, including the charging station 23 and a stopover that can be charged without waiting according to the user's selection.

Therefore, according to the present invention, as long as the customer (user) is registered as a member in the electric vehicle control center, the electric vehicle charging station recommendation system notifies the user at an appropriate time, even if the customer does not separately search and request the charger usage status, etc. User convenience can be improved.

In addition, the electric vehicle charging station recommendation system can track the traces of customers based on information coming into the electric vehicle control center.

In addition, the electric vehicle charging station recommendation system is the location where the electric vehicle is parked (POI), the tresektori (preferred path) that connects these places (POIs), the charging stations that customers visit in this treasury, and the customers near the charging stations. Charging stations that can be charged at the time of arrival, if the recommended charging station is outdoors, adjust the charging timing in consideration of the weather, and consider the traffic conditions and the amount of charging required to get to the destination. You can find and recommend it to your customers.

In addition, the operating status of the charging station referred to by the user is based on the authentication/charging information of the member coming from the electric vehicle control center, and the density of the charging station can be predicted based on the density of the member's electric vehicle within the GPS radius of the charging station.

In addition, the charger operation status information provided to the user by the electric vehicle charging station recommendation system of the present invention can be obtained more quickly than the charger operation status that can be checked by the user delaying 5 to 30 minutes through the Ministry of Environment.

1: Electric vehicle charging station recommendation system
10: User Eve POH recognition module
11: User Eve trajectory recognition module
12: User CPPI recognition module
13: Charging start/end SoC and charging point/cycle recognition module
131: charging start/end SoC recognition module
132: charging point/cycle recognition module
14: CP population recognition module
15: Eve E departure point recognition module
16: Traffic situation awareness module in EV Trejectory
17: weather recognition module 18: control unit
19: electric vehicle 191: control panel part
20: phone 21: control center
22: preferred route 23: charging station
24: charger 25: frequently used charging station
26: non-jurisdiction charging station 27: departure point
28: destination

Claims (13)

An EV start time recognition module for recognizing a start time of the electric vehicle;
A user Eve PIO recognition module for recognizing where the electric vehicle user frequently goes;
A user Eve trajectory recognition module for recognizing a preferred route among routes that the user frequently goes from a departure point to a destination;
A user CPIO recognition module for recognizing a charging station that the user likes;
A CP population recognition module that recognizes the charging state of the charging station adjacent to the preferred road in real time;
A charging start/end charging amount recognition module for recognizing a charging amount when charging the electric vehicle starts and ends; And
Electric vehicle charging station recommendation including a control unit that is communicatively connected to an electric vehicle or a mobile device possessed by a user of the electric vehicle, and recommends a charging station capable of charging the electric vehicle to the user in order to charge the amount of charge required for the electric vehicle to go to the destination system. The method of claim 1,
The control unit,
An electric vehicle charging station recommendation system that recommends another charging station whose charging time is further shortened even when bypassing the charging station, taking into account the charging waiting time upon arrival at a charging station adjacent to the preferred road. The method of claim 1,
The charging station adjacent to the way from the origin to the destination has a plurality of chargers,
The control unit,
An electric vehicle charging station recommendation system that calculates a time for the user to arrive at the charging station compared to the charging completion time of each of the plurality of chargers, and recommends a charger capable of charging in the order of a charging start time when arriving at the charging station. The method of claim 1,
The user Eve POH recognition module is an electric vehicle charging station recommendation system for recognizing frequent places for each time zone. The method of claim 1,
The user CPPOI recognition module is an electric vehicle charging station recommendation system that searches for a charger that can be used as a membership card of the favorite charging station. The method of claim 1,
The electric vehicle charging station recommendation system further comprises a traffic situation recognition module in the EV Trejectory for recognizing the traffic situation on the preferred road when the electric vehicle departs and recommending a charging station in a section where there is no congestion. The method of claim 1,
The electric vehicle charging station further includes a weather recognition module for recognizing whether it is snow or rain, and the control unit recommends charging the charging station to be recommended at the point of time just before it rains or snows when the charging station to be recommended is outdoors. Recommendation system. The method of claim 1,
The CP population recognition module,
An electric vehicle charging station recommendation system that recognizes in real time a charging state of a charging station adjacent to a road preferred by the user as the user or customer uploads information at the time of membership authentication or charging start to the charging station to the server of the control system. The method of claim 1,
The user EVPIO recognition module is an electric vehicle charging station recommendation system that searches for a charging station that can be charged when a registered customer arrives based on a charging service member card near the user's preferred charging station and the preferred charging station. The method of claim 1,
The user EV tresoktori recognition module is an electric vehicle charging station recommendation system for searching for a charging station existing on a preferred route when moving from the starting point to the destination. The method of claim 1,
The electric vehicle charging station recommendation system for recommending a charging station that can be charged according to the user's charging pattern at a time when the user CPPOI recognition module leaves the frequently-going place. The method of claim 1,
Electric vehicle charging station recommendation system further comprising a charging time / cycle recognition module for recognizing the charging time and the charging cycle of the user. The method of claim 1,
The CP population recognition module identifies the charging status of the charging station based on the time when the user will charge, and recommends an electric vehicle charging station that estimates the density of each charging station according to the number of chargers held by the charging station based on the location of the charging station. system.

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