Abstract: A method for identifying prospective purchasers of battery electric vehicles (BEVs) may include defining a predetermined time frame associated with vehicle ownership, receiving a first dataset including a first subset of drivers are drivers who have owned or leased any first internal combustion engine (ICE) vehicle followed by any second ICE vehicle within the predetermined time frame, a second subset of drivers are drivers who have owned or leased any first ICE vehicle followed by any second BEV within the predetermined time frame, and a third subset of drivers are drivers who have not changed vehicles within the predetermined time frame, receiving a second dataset including a set of drivers who own or lease any first ICE vehicle which is in a same vehicle class as a target BEV, and identifying a target set of prospective purchasers of BEVs.

Abstract: A system and method for home identification is provided. The system selects a set of locations corresponding to a set of calendar dates from user's location history. Each location is associated with a dwell time period which is greater than a first threshold time-period. The system creates a location table by including the set of locations against the set of calendar dates and selects a first location from the location table based on whether a total number of day-wise occurrences of the first location in the location table is above a threshold number in a week period. The system determines a first count of weeks for which the total number of day-wise occurrences of the first location is above the threshold number and determines the first location as a user's home location based on whether the determined first count of weeks is above a threshold number of weeks.

Abstract: According to one aspect, a charging station or a system for adjustment of electric vehicle (EV) charging timing, power, or location in coordination with the electrical grid (V1G) or vehicle to grid bidirectional power flow (V2G) selection may include a memory, a processor, and a charge controller or controller. The memory may receive a profile associated with an electric vehicle (EV). The profile may be indicative of a V1G/V2G charging schedule preference for the EV. The processor may determine a presence of the EV and the charge controller may control charging of a battery of the EV by selecting V1G or V2G based on the profile and in accordance with the V1G/V2G charging schedule preference.

Abstract: A system and method for home identification is provided. The system selects a set of locations corresponding to a set of calendar dates from user's location history. Each location is associated with a dwell time period which is greater than a first threshold time-period. The system creates a location table by including the set of locations against the set of calendar dates and selects a first location from the location table based on whether a total number of day-wise occurrences of the first location in the location table is above a threshold number in a week period. The system determines a first count of weeks for which the total number of day-wise occurrences of the first location is above the threshold number and determines the first location as a user's home location based on whether the determined first count of weeks is above a threshold number of weeks.

Abstract: According to one aspect, a charging station or a system for adjustment of electric vehicle (EV) charging timing, power, or location in coordination with the electrical grid (V1G) or vehicle to grid bidirectional power flow (V2G) selection may include a memory, a processor, and a charge controller or controller. The memory may receive a profile associated with an electric vehicle (EV). The profile may be indicative of a V1G/V2G charging schedule preference for the EV. The processor may determine a presence of the EV and the charge controller may control charging of a battery of the EV by selecting V1G or V2G based on the profile and in accordance with the V1G/V2G charging schedule preference.

Abstract: A method for identifying prospective purchasers of battery electric vehicles (BEVs) may include defining a predetermined time frame associated with vehicle ownership, receiving a first dataset including a first subset of drivers are drivers who have owned or leased any first internal combustion engine (ICE) vehicle followed by any second ICE vehicle within the predetermined time frame, a second subset of drivers are drivers who have owned or leased any first ICE vehicle followed by any second BEV within the predetermined time frame, and a third subset of drivers are drivers who have not changed vehicles within the predetermined time frame, receiving a second dataset including a set of drivers who own or lease any first ICE vehicle which is in a same vehicle class as a target BEV, and identifying a target set of prospective purchasers of BEVs.

Abstract: A failure determination apparatus includes an electricity storage, a state sensor, a data accumulator, and a controller. The state sensor is to detect a state of the electricity storage as data. The data accumulator is to accumulate the data acquired by the state sensor as accumulated data. The controller is to determine, based on the accumulated data, whether a failure occurs in at least one of the electricity storage and the state sensor.

Abstract: A failure determination apparatus includes an electricity storage, a state sensor, a data accumulator, and a controller. The state sensor is to detect a state of the electricity storage as data. The data accumulator is to accumulate the data acquired by the state sensor as accumulated data. The controller is to determine, based on the accumulated data, whether a failure occurs in at least one of the electricity storage and the state sensor.