System and method for presenting electric vehicle charging options

Abstract

A system and method for presenting electric vehicle charging options that include determining a current geo-location of an electric vehicle. The system and method also include determining a current state of charge of a battery of the electric vehicle. The system and method additionally include analyzing at least one travel routine of an operator of the electric vehicle to determine at least one prospective travel path of the electric vehicle. The system and method further include analyzing the current geo-location of the electric vehicle, the current state of charge of the battery of the electric vehicle, and the at least one prospective travel path of the electric vehicle to predict a prospective state of charge of the battery of the electric vehicle.

1 . A computer-implemented method for presenting electric vehicle charging options, comprising:
 determining a current geo-location of an electric vehicle;   determining a current state of charge of a battery of the electric vehicle;   analyzing at least one travel routine of an operator of the electric vehicle to determine at least one prospective travel path of the electric vehicle; and   analyzing the current geo-location of the electric vehicle, the current state of charge of the battery of the electric vehicle, and the at least one prospective travel path of the electric vehicle to predict a prospective state of charge of the battery of the electric vehicle, wherein at least one charging station that is reachable by the electric vehicle based on the prospective state of charge and the prospective travel path is presented on a charging station map user interface.   
     
     
         2 . The computer-implemented method of  claim 1 , wherein determining the current state of charge further includes determining a remaining distance that the electric vehicle is capable of traveling based on analyzing the current state of charge of the electric vehicle, an average speed of the electric vehicle, and at least one road type that is located within a vicinity of the current geo-location of the electric vehicle. 
     
     
         3 . The computer-implemented method of  claim 1 , wherein analyzing the at least one travel routine of the operator includes accessing a location log that includes a log of locations at which the electric vehicle is driven, parked, or charged. 
     
     
         4 . The computer-implemented method of  claim 3 , wherein analyzing the at least one travel routine of the operator includes analyzing the location log in comparison to point of interest data to determine at least one point of interest location that is routinely traveled to by the electric vehicle. 
     
     
         5 . The computer-implemented method of  claim 3 , wherein analyzing the at least one travel routine of the operator includes analyzing the at least one travel routine through a neural network to provide computer machine based deep learning techniques to determine whether a particular trip of the electric vehicle is a routine trip or a non-routine trip. 
     
     
         6 . The computer-implemented method of  claim 1 , wherein a road type of at least one prospective travel path of the electric vehicle and an average speed of the electric vehicle is analyzed to predict the prospective state of charge of the battery of the electric vehicle. 
     
     
         7 . The computer-implemented method of  claim 1 , further including presenting the at least one charging station with an estimated cost to charge the electric vehicle based on the prospective state of charge of the battery of the electric vehicle. 
     
     
         8 . The computer-implemented method of  claim 1 , further including presenting a queue wait time and an incentive that is associated with the at least one charging station. 
     
     
         9 . The computer-implemented method of  claim 1 , further including determining a current geo-location of at least one additional electric vehicle that is capable of charging the electric vehicle and presenting the charging station map user interface to pin point the current geo-location of the additional electric vehicle. 
     
     
         10 . A system for presenting electric vehicle charging options, comprising:
 a memory storing instructions when executed by a processor cause the processor to:   determine a current geo-location of an electric vehicle;   determine a current state of charge of a battery of the electric vehicle;   analyze at least one travel routine of an operator of the electric vehicle to determine at least one prospective travel path of the electric vehicle; and   analyze the current geo-location of the electric vehicle, the current state of charge of the battery of the electric vehicle, and the at least one prospective travel path of the electric vehicle to predict a prospective state of charge of the battery of the electric vehicle, wherein at least one charging station that is reachable by the electric vehicle based on the prospective state of charge and the prospective travel path is presented on a charging station map user interface.   
     
     
         11 . The system of  claim 10 , wherein determining the current state of charge further includes determining a remaining distance that the electric vehicle is capable of traveling based on analyzing the current state of charge of the electric vehicle, an average speed of the electric vehicle, and at least one road type that is located within a vicinity of the current geo-location of the electric vehicle. 
     
     
         12 . The system of  claim 10 , wherein analyzing the at least one travel routine of the operator includes accessing a location log that includes a log of locations at which the electric vehicle is driven, parked, or charged. 
     
     
         13 . The system of  claim 12 , wherein analyzing the at least one travel routine of the operator includes analyzing the location log in comparison to point of interest data to determine at least one point of interest location that is routinely traveled to by the electric vehicle. 
     
     
         14 . The system of  claim 12 , wherein analyzing the at least one travel routine of the operator includes analyzing the at least one travel routine through a neural network to provide computer machine based deep learning techniques to determine whether a particular trip of the electric vehicle is a routine trip or a non-routine trip. 
     
     
         15 . The system of  claim 10 , wherein a road type of at least one prospective travel path of the electric vehicle and an average speed of the electric vehicle is analyzed to predict the prospective state of charge of the battery of the electric vehicle. 
     
     
         16 . The system of  claim 10 , further including presenting the at least one charging station with an estimated cost to charge the electric vehicle based on the prospective state of charge of the battery of the electric vehicle. 
     
     
         17 . The system of  claim 10 , further including presenting a queue wait time and an incentive that is associated with the at least one charging station. 
     
     
         18 . The system of  claim 10 , further including determining a current geo-location of at least one additional electric vehicle that is capable of charging the electric vehicle and presenting the charging station map user interface to pin point the current geo-location of the additional electric vehicle. 
     
     
         19 . A non-transitory computer readable storage medium storing instructions that when executed by a computer, which includes a processor perform a method, the method comprising:
 determining a current geo-location of an electric vehicle;   determining a current state of charge of a battery of the electric vehicle;   analyzing at least one travel routine of an operator of the electric vehicle to determine at least one prospective travel path of the electric vehicle; and   analyzing the current geo-location of the electric vehicle, the current state of charge of the battery of the electric vehicle, and the at least one prospective travel path of the electric vehicle to predict a prospective state of charge of the battery of the electric vehicle, wherein at least one charging station that is reachable by the electric vehicle based on the prospective state of charge and the prospective travel path is presented on a charging station map user interface.   
     
     
         20 . The non-transitory computer readable storage medium of  claim 19 , wherein a road type of at least one prospective travel path of the electric vehicle and an average speed of the electric vehicle is analyzed to predict the prospective state of charge of the battery of the electric vehicle.