Adaptive classification of electric vehicle charging location using connected vehicle data

1 . A method for providing an electric vehicle charging recommendation, the method comprising:

obtaining, by a processor, information associated with a plurality of charging events for a vehicle, wherein the information comprises a plurality of vehicle geolocations associated with the plurality of charging events;

generating, by the processor, a plurality of charging geolocation clusters from the plurality of vehicle geolocations, wherein the plurality of charging geolocation clusters correspond to a plurality of charging station locations at which the vehicle has been charged;

determining, by the processor, a charging event occurrence frequency for each charging geolocation cluster based on the information, wherein the charging event occurrence frequency corresponds to a number of times the vehicle has been charged at the respective charging geolocation cluster;

classifying, by the processor, a first charging geolocation cluster from the plurality of charging geolocation clusters as a primary charging station location, and a plurality of second charging geolocation clusters from the plurality of charging geolocation clusters as routine charging station locations based on the charging event occurrence frequencies;

defining, by the processor, a virtual polygon connecting the primary charging station location and the routine charging station locations on a map of a geographical area;

determining, by the processor, the electric vehicle charging recommendation based on the virtual polygon;

transmitting, by the processor, the electric vehicle charging recommendation to a server; and

autonomously, based on the electric vehicle charging recommendation and the virtual polygon, operating the vehicle.

2 . The method of claim 1 , wherein the routine charging station locations have routine charging event occurrence frequencies greater than a predefined threshold.

3 . The method of claim 2 , wherein classifying the first charging geolocation cluster from the plurality of charging geolocation clusters as the primary charging station location comprises:

identifying a first routine charging station location from the routine charging station locations, wherein the first routine charging station has a maximum charging event occurrence frequency of the charging event occurrence frequencies for the routine charging station locations; and

classifying the first routine charging station location as the primary charging station location.

4 . The method of claim 1 , wherein the information further comprises a plurality of timestamps associated with the plurality of charging events.

5 . The method of claim 4 , further comprising:

assigning a weight to each charging event based on the timestamps; and

determining the charging event occurrence frequency based on the weights.

6 . The method of claim 1 , wherein generating the plurality of charging geolocation clusters from the plurality of vehicle geolocations comprises generating the plurality of charging geolocation clusters based on distances of the plurality of vehicle geolocations from each other.

7 . The method of claim 1 , wherein the plurality of charging events comprises at least one of: a vehicle key-on event, a vehicle key-off event, a vehicle charging start event, and a vehicle charging end event.

8 . The method of claim 7 , wherein the information further comprises a time duration between the vehicle charging start event and the vehicle charging end event.

9 . The method of claim 8 , wherein determining the electric vehicle charging recommendation based on the virtual polygon comprises determining the electric vehicle charging recommendation based on the virtual polygon and the time duration.

10 . The method of claim 1 , wherein the electric vehicle charging recommendation comprises at least one of a charging station infrastructure creation recommendation, and a charging station incentive recommendation.

11 . The method of claim 1 , further comprising classifying one or more third charging geolocation clusters from the plurality of charging geolocation clusters located within the virtual polygon as nearby charging station locations.

12 . The method of claim 11 , further comprising:

classifying one or more fourth charging geolocation clusters from the plurality of charging geolocation clusters located less than a predefined virtual distance from a virtual polygon edge as short trip charging station locations; and

classifying one or more fifth charging geolocation clusters from the plurality of charging geolocation clusters located more than the predefined virtual distance from the virtual polygon edge as long trip charging station locations.

13 . The method of claim 12 , wherein determining the electric vehicle charging recommendation based on the virtual polygon comprises determining the electric vehicle charging recommendation based on the virtual polygon, the short trip charging station locations, and the long trip charging station locations.

14 . A system for providing an electric vehicle charging recommendation, the system comprising:

a transceiver configured to receive information associated with a plurality of charging events for a vehicle, wherein the information comprises a plurality of vehicle geolocations associated with the plurality of charging events;

a processor communicatively coupled to the transceiver; and

a memory for storing executable instructions, the processor configured to execute the instructions to:

obtain the information from the transceiver;

generate a plurality of charging geolocation clusters from the plurality of vehicle geolocations, wherein the plurality of charging geolocation clusters correspond to a plurality of charging station locations at which the vehicle has been charged;

determine a charging event occurrence frequency for each charging geolocation cluster based on the information, wherein the charging event occurrence frequency corresponds to a number of times the vehicle has been charged at the respective charging geolocation cluster;

classify a first charging geolocation cluster from the plurality of charging geolocation clusters as a primary charging station location, and a plurality of second charging geolocation clusters from the plurality of charging geolocation clusters as routine charging station locations based on the charging event occurrence frequencies;

define a virtual polygon connecting the primary charging station location and the routine charging station locations on a map of a geographical area;

determine the electric vehicle charging recommendation based on the virtual polygon;

transmit the electric vehicle charging recommendation to a server; and

autonomously, based on the electric vehicle charging recommendation and the virtual polygon, operate the vehicle.

15 . The system of claim 14 , wherein the routine charging station locations have routine charging event occurrence frequencies greater than a predefined threshold.

16 . The system of claim 15 , wherein the processor is configured to classify the first charging geolocation cluster from the plurality of charging geolocation clusters as the primary charging station location by:

identifying a first routine charging station location from the routine charging station locations, wherein the first routine charging station location has a maximum charging event occurrence frequency of the charging event occurrence frequencies for the routine charging station locations; and

classifying the first routine charging station location as the primary charging station location.

17 . The system of claim 14 , wherein the processor is further configured to classify one or more third charging geolocation clusters from the plurality of charging geolocation clusters located within the virtual polygon as nearby charging station locations.

18 . The system of claim 17 , wherein the processor is further configured to:

classify one or more fourth charging geolocation clusters from the plurality of charging geolocation clusters located less than a predefined virtual distance from a virtual polygon edge as short trip charging station locations; and

classify one or more fifth charging geolocation clusters from the plurality of charging geolocation clusters located more than the predefined virtual distance from the virtual polygon edge as long trip charging station locations,

wherein the processor determines the electric vehicle charging recommendation based on the virtual polygon, the short trip charging station locations, and the long trip charging station locations.

19 . The system of claim 14 , wherein the electric vehicle charging recommendation comprises at least one of a charging station infrastructure creation recommendation, and a charging station incentive recommendation.

20 . A non-transitory computer-readable storage medium having instructions stored thereupon which, when executed by a processor, cause the processor to:

obtain information associated with a plurality of charging events for a vehicle, wherein the information comprises a plurality of vehicle geolocations associated with the plurality of charging events;

generate a plurality of charging geolocation clusters from the plurality of vehicle geolocations, wherein the plurality of charging geolocation clusters correspond to a plurality of charging station locations at which the vehicle has been charged;

determine a charging event occurrence frequency for each charging geolocation cluster based on the information, wherein the charging event occurrence frequency corresponds to a number of times the vehicle has been charged at the respective charging geolocation cluster;

classify a first charging geolocation cluster from the plurality of charging geolocation clusters as a primary charging station location, and a plurality of second charging geolocation clusters from the plurality of charging geolocation clusters as routine charging station locations based on the charging event occurrence frequencies;

define a virtual polygon connecting the primary charging station location and the routine charging station locations on a map of a geographical area;

determine an electric vehicle charging recommendation based on the virtual polygon;

transmit the electric vehicle charging recommendation to a server based on the virtual polygon; and

autonomously, based on the electric vehicle charging recommendation and the virtual polygon, operate the vehicle.