Electric vehicle charging management system and method

1. A computer-implemented method for charging a battery of an electric vehicle with a low state of charge (SOC), the method being implemented via one or more processors, transceivers, servers, or sensors, any of which may be local or remote, the method comprising:

determining, via the one or more processors, the electric vehicle has a state of charge (SOC) below a predetermined threshold;

in response to determining that the SOC is below the predetermined threshold, determining, via the one or more processors, a plurality of homes capable of charging electric vehicles within a vicinity of a GPS location of the low SOC vehicle;

ranking, via the one or more processors, the plurality of homes based upon various factors;

determining, via the one or more processors, availability of the plurality of homes to charge the low SOC vehicle;

scheduling, via the one or more processors, a rendezvous time for the low SOC vehicle with a selected home of the plurality of homes, wherein the selected home is, from among homes of the plurality of homes both equipped to charge the low SOC vehicle and available to charge the low SOC vehicle, a home with the highest rank, and wherein the rendezvous time satisfies a home occupancy preference for the selected home, the home occupancy preference being one of the selected home being occupied or unoccupied;

generating, via the one or more processors, route information from a location of the low SOC vehicle to the selected home; and

causing, via the one or more processors, the route information to be transmitted to the low SOC vehicle.

2. The computer-implemented method of claim 1 , further comprising collecting and analyzing, by a mobile device associated with the low SOC vehicle, vehicle telematics data.

3. The computer-implemented method of claim 2 , wherein the vehicle telematics data includes one or more of: acceleration, braking, cornering, speed, direction, route, GPS location, and SOC of the low SOC vehicle.

4. The computer-implemented method of claim 1 , wherein the predetermined threshold is defined as a percentage of the SOC remaining after charging the electric vehicle.

5. The computer-implemented method of claim 1 , wherein the vicinity is defined as a determined distance that the electric vehicle is capable of driving, based upon the SOC remaining in the electric vehicle.

6. The computer-implemented method of claim 1 , wherein each of the homes capable of charging electric vehicles within the vicinity of the GPS location of the low SOC vehicle is ranked based upon (a) distance of the home to the low SOC vehicle; (b) charging equipment of the home; (c) neighborhood of the home; (d) ease of access to the home; and/or (e) whether the home is located along a route of the low SOC vehicle.

7. The computer-implemented method of claim 6 , wherein charging equipment data, type of neighborhood data, and ease of access to the home and/or to the charging equipment of the home data may be included in home telematics data broadcasted by each home via wireless communication or data transmission.

8. The computer-implemented method of claim 1 , the method comprising:

determining or evaluating, via the one or more processors, time constraints of the ranked homes to charge.

9. The computer-implemented method of claim 8 , wherein the time constraints and/or the availability of the homes is determined by collecting homeowner electronic calendar data broadcasted by each of the homes.

10. The computer-implemented method of claim 9 , wherein the homeowner electronic calendar data includes homeowner charging preference data and/or home occupancy data.

11. The computer-implemented method of claim 8 , the method further comprising:

eliminating one or more of the ranked homes based upon the determined or evaluated time constraints and/or availability; or wherein the various factors comprise the determined or evaluated time constraints and/or availability.

12. The computer-implemented method of claim 11 , the method comprising:

determining or evaluating, via the one or more processors, energy costs for each of a current set of ranked homes.

13. The computer-implemented method of claim 1 , the method comprising:

determining or evaluating, via the one or more processors, energy and charging supply and demand for an area through which the low SOC vehicle is traveling.

14. The computer-implemented method of claim 13 , the method comprising: initiating, by the one or more processors, a bidding process for a driver of the low SOC vehicle to bid on the homes in the vicinity.

15. The computer-implemented method of claim 1 , wherein the low SOC vehicle is autonomous, and the one or more processors determine a route for the low SOC vehicle, and automatically route the low SOC vehicle to the highest ranked home.

16. A computer system for recharging a battery of an electric vehicle with a low state of charge (SOC), the system comprising:

a network;

the electric vehicle operatively coupled to the network;

a plurality of potential charging locations operatively coupled to the network; and

a server operatively coupled to the network, the server comprising a controller configured to:

determine the electric vehicle has a state of charge (SOC) below a predetermined threshold;

in response to the determination that the SOC is below the predetermined threshold, determine a plurality of homes capable of charging electric vehicles within a vicinity of a GPS location of the low SOC vehicle;

rank the plurality of homes based upon various factors;

determine availability of the plurality of homes to charge the low SOC vehicle; and

schedule a rendezvous time for the low SOC vehicle with a selected home of the plurality of homes, wherein the selected home is, from among homes of the plurality of homes both capable of charging the low SOC vehicle and available to charge the low SOC vehicle, a home with the highest rank, and wherein the rendezvous time satisfies a home occupancy preference for the selected home, the home occupancy preference being one of the selected home being occupied or unoccupied.

17. The computer system of claim 16 , the controller being further configured to: collect and analyze, by a mobile device associated with the low SOC vehicle, vehicle telematics data.

18. The computer system of claim 16 , wherein the predetermined threshold is defined as a percentage of the SOC remaining after charging the electric vehicle.

19. The computer system of claim 16 , wherein the vicinity is defined as a determined distance that the electric vehicle is capable of driving, based upon the SOC remaining in the electric vehicle.

20. At least one non-transitory computer readable storage medium with instructions stored thereon, the instructions causing, in response to execution by at least one processor, the at least one processor to:

determine a low state of charge (SOC) vehicle, the low SOC vehicle having an SOC below a predetermined threshold;

in response to determining that the SOC is below the predetermined threshold, determine a plurality of homes capable of charging electric vehicles within a vicinity of a GPS location of the low SOC vehicle;

rank the plurality of homes based upon various factors;

determine availability of the plurality of homes to charge the low SOC vehicle;

schedule a rendezvous time for the low SOC vehicle with a selected home of the plurality of homes, wherein the selected home is, from among homes of the plurality of homes both equipped to charge the low SOC vehicle and available to charge the low SOC vehicle, a home with the highest rank, and wherein the rendezvous time satisfies a home occupancy preference for the selected home, the home occupancy preference being one of the selected home being occupied or unoccupied;

generate route information from a location of the low SOC vehicle to the selected home; and

cause the route information to be transmitted to the low SOC vehicle.