SYSTEM AND METHOD OF PREDICTING USAGE OF A CHARGING STATION

• US 20150294329A1
• Filed: 04/11/2014
• Published: 10/15/2015
• Est. Priority Date: 04/11/2014
• Status: Abandoned Application

• Current Assignee: Nissan North America Incorporated (Nissan Motor Co., Ltd.)
• Original Assignee: Nissan North America Incorporated (Nissan Motor Co., Ltd.)
• Inventors: SAITO, Daisuke, MURAMATSU, Toshiro
• Application Number:
  US14/250,991
• Publication Number:
  US 20150294329A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60L 2210/30 AC to DC converters
• CPC Class Codes: B60L 2240/622 by satellite navigation
• CPC Class Codes: B60L 2240/72 Charging station selection relying on external data
• CPC Class Codes: B60L 2240/80 Time limits
• CPC Class Codes: B60L 2250/16 by display
• CPC Class Codes: B60L 2260/44 by parameter estimation
• CPC Class Codes: B60L 2260/50 by future state prediction
• CPC Class Codes: B60L 2260/52 drive range estimation, e.g. of estimation of available travel distance
• CPC Class Codes: B60L 2260/54 Energy consumption estimation
• CPC Class Codes: B60L 3/0046 relating to electric energy storage systems, e.g. batteries or capacitors
• CPC Class Codes: B60L 3/12 Recording operating variables ; Monitoring of operating variables
• CPC Class Codes: B60L 53/14 Conductive energy transfer
• CPC Class Codes: B60L 53/305 Communication interfaces
• CPC Class Codes: B60L 53/63 in response to network capacity
• CPC Class Codes: B60L 53/65 involving identification of vehicles or their battery types
• CPC Class Codes: B60L 58/12 responding to state of charge [SoC]
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0261 based on user location
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: H02J 2310/48 for electric vehicles [EV] or hybrid vehicles [HEV]
• CPC Class Codes: H02J 3/00 : Circuit arrangements for ac mains or ac distribution networks
• CPC Class Codes: H02J 3/003 : Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: Y02E 60/00 : Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y02T 10/70 : Energy storage systems for electromobility, e.g. batteries
• CPC Class Codes: Y02T 10/7072 : Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
• CPC Class Codes: Y02T 10/72 : Electric energy management in electromobility
• CPC Class Codes: Y02T 90/12 : Electric charging stations
• CPC Class Codes: Y02T 90/14 : Plug-in electric vehicles
• CPC Class Codes: Y02T 90/16 : Information or communication technologies improving the operation of electric vehicles
• CPC Class Codes: Y02T 90/167 : Systems integrating technologies related to power network operation and communication or information technologies for supporting the interoperability of electric or hybrid vehicles, i.e. smartgrids as interface for battery charging of electric vehicles [EV] or hybrid vehicles [HEV]
• CPC Class Codes: Y04S 10/126 : the energy generation units being or involving electric vehicles [EV] or hybrid vehicles [HEV], i.e. power aggregation of EV or HEV, vehicle to grid arrangements [V2G]
• CPC Class Codes: Y04S 30/14 : Details associated with the interoperability, e.g. vehicle recognition, authentication, identification or billing
• CPC Class Codes: Y04S 50/14 : Marketing, i.e. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards

Abstract

A system and method of predicting usage of a charging station includes collecting charging activity history of a plurality of charging stations. A charging station is determined associated with a requesting electric vehicle. A future demand for the charging station is predicted based on the collected charging activity history. A predicted usage value of the charging station is provided based on the predicted future demand for an estimated time of arrival of the requesting electric vehicle at the charging station.

Claims

1. A method of predicting usage of a charging station, comprising the steps of:

collecting charging activity history of a plurality of charging stations;

determining a charging station associated with a requesting electric vehicle;

predicting a future demand for the charging station based on the collected charging activity history; and

providing a predicted usage value of the charging station based on the predicted future demand for an estimated time of arrival of the requesting electric vehicle at the charging station.

2. The method of predicting usage of a charging station according to claim 1, wherein

the determining the charging station associated with the requesting electric vehicle step includes along a route of travel or proximal to a location of the requesting electric vehicle.

3. The method of predicting usage of a charging station according to claim 1, wherein

the charging activity history includes a location and charging start and end timestamps of the plurality of charging stations.

4. The method of predicting usage of a charging station according to claim 1, wherein

the charging activity history is probe data received from a plurality of electric vehicles.

5. The method of predicting usage of a charging station according to claim 1, wherein

the predicting and providing steps include a plurality of charging stations.

6. The method of predicting usage of a charging station according to claim 1, further comprising

providing a route to the requesting electric vehicle to a most appropriate charging station based on the predicted usage value and a state of charge of the requesting electric vehicle.

7. The method of predicting usage of a charging station according to claim 1, wherein

the predicted usage value is provided as an average waiting time at the charging station.

8. The method of predicting usage of a charging station according to claim 1, wherein

the predicted usage value is provided as a segmented waiting probability based on a percentage of chargers utilized at the charging station.

9. The method of predicting usage of a charging station according to claim 1, wherein

the predicted usage value is provided as an indication of congestion at the charging station.

10. The method of predicting usage of a charging station according to claim 9, wherein

the indication of congestion is color coded.

11. The method of predicting usage of a charging station according to claim 9, wherein

the indication of congestion is selected from the group consisting of vacant to indicate no waiting time, rarely occupied to indicate under approximately 10% vacant, slightly congested to indicate under approximately 30% vacant;

relatively crowded to indicate between approximately 30 to approximately 60% vacant and crowded to indicate over approximately 60% crowded.

12. The method of predicting usage of a charging station according to claim 1, wherein

the predicted usage value of the charging station is displayed within the requesting electric vehicle.

13. The method of predicting usage of a charging station according to claim 12, wherein

the predicted usage value of the charging station is displayed on a map showing a location of the charging station.

14. The method of predicting usage of a charging station according to claim 1, further comprising

determining a plurality of predicted usage values associated with a plurality of charging stations;

and

providing the plurality of predicted usage values of the plurality of charging stations to the requesting electric vehicle.

15. The method of predicting usage of a charging station according to claim 14, wherein

the plurality of predicted usage values associated with the plurality of charging stations are displayed within the requesting electric vehicle.

16. The method of predicting usage of a charging station according to claim 15, wherein

the plurality of predicted usage values associated with the plurality of charging stations are displayed on a map showing the locations of the plurality of charging stations.

17. The method of predicting usage of a charging station according to claim 1, wherein

the providing step includes sending data from a server directly to a telematics unit of the requesting electric vehicle.

18. The method of predicting usage of a charging station according to claim 1, wherein

the predicting future demand step includes determining a pattern of charging activity of one of the plurality of charging stations and applying the determined pattern to the requesting electric vehicle.

19. The method of predicting usage of a charging station according to claim 18, wherein

the pattern is based on a time period.

20. The method of predicting usage of a charging station according to claim 19, wherein

the time period is a predetermined time duration.

21. The method of predicting usage of a charging station according to claim 18, wherein

the pattern is based on a day of the week.

22. The method of predicting usage of a charging station according to claim 18, wherein

the pattern is based on a day of the year.

23. The method of predicting usage of a charging station according to claim 18, wherein

the pattern is based on a season of the year.

24. A system of predicting usage of a charging station, comprising:

a data center including

a data collector configured to collect charging activity history of a plurality of charging stations;

a determination unit configured to determine a charging station associated with a requesting electric vehicle and to predict a future demand for the charging station based on the collected charging activity history; and

a transmitting unit configured to transmit a predicted usage value of the charging station based on the predicted future demand for an estimated time of arrival of the requesting electric vehicle; and

a requesting electric vehicle including a communication unit configured to receive the usage value; and

a display configured to display the usage value.

25. The system of predicting usage of a charging station according to claim 24, wherein

the charging station includes at least one charger.

26. The system of predicting usage of a charging station according to claim 24, wherein

the display includes a map indicating a location of the charging station.

27. The system of predicting usage of a charging station according to claim 26, wherein

the predicted usage value of the charging station is indicated on the map.

28. The system of predicting usage of a charging station according to claim 27, wherein

the predicted usage value of the charging station provides a degree of congestion of the charging station.

29. The system of predicting usage of a charging station according to claim 28, wherein

the degree of congestion is color coded to represent the degree of congestion of the charging station.

30. The system of predicting usage of a charging station according to claim 28, wherein

the degree of congestion is indicated by a term to represent the degree of congestion of the charging station.