Provided is a bootstrap method for registering a charging station (CS), which was in an offline state, to an electric vehicle charging station management system (CSMS) and operating same. The bootstrap method comprises the steps of: storing at least partial bootstrap information in a CS so as to configure bootstrap information; connecting the CS to a CSMS by setting a security channel between the CS and the CSMS for maintaining registration information about the CS; and registering the CS to the CSMS.

Embodiments described herein relate to predicting the utilization of electric vehicle (EV) charge points. Methods may include: receiving an indication of a plurality of candidate locations for EV charge points; determining static map features of the plurality of candidate locations; inputting the plurality of candidate locations and static map features into a machine learning model, where the machine learning model is trained on existing EV charge point locations, existing EV charge point static map features, and existing EV charge point utilization; determining, based on the machine learning model, a predicted utilization of an EV charge point at the plurality of candidate locations; and generating a representation of a map including the plurality of candidate locations, where candidate locations of the plurality of candidate locations are visually distinguished based on a respective predicted utilization of an EV charge point at the candidate locations.

A system comprises a computer having a processor and a memory, the memory storing instructions executable by the processor to receive, from a charge-requesting vehicle, a charge request, determine a suggested provider pool for fulfilling the charge request, the suggested provider pool including multiple suggested charge-providing vehicles, send suggested provider data to the charge-requesting vehicle, the suggested provider data identifying the multiple suggested charge-providing vehicles, receive, from the charge-requesting vehicle, a provider selection identifying one of the multiple suggested charge-providing vehicles as a selected charge-providing vehicle, identify transfer parameters for a battery charge transfer from the selected charge-providing vehicle to the charge-requesting vehicle; and send a transfer initiation message to instruct the selected charge-providing vehicle to initiate the battery charge transfer according to the transfer parameters.

Embodiments described herein relate to predicting the utilization of electric vehicle (EV) charge points. Methods may include: receiving an indication of a plurality of candidate locations for EV charge points; determining static map features of the plurality of candidate locations; inputting the plurality of candidate locations and static map features into a machine learning model, where the machine learning model is trained on existing EV charge point locations, existing EV charge point static map features, and existing EV charge point utilization; determining, based on the machine learning model, a predicted utilization of an EV charge point at the plurality of candidate locations; and generating a representation of a map including the plurality of candidate locations, where candidate locations of the plurality of candidate locations are visually distinguished based on a respective predicted utilization of an EV charge point at the candidate locations.

A remote computer server communicates with a fleet of electric vehicles, and gathers telemetry data from the fleet of electric vehicles. An intelligent EVSE unit and/or a DC fast charging unit communicates with the remote server, and charges an electric vehicle based at least in part on the telemetry data from the fleet of electric vehicles. The remote computer server can generate charging instructions based at least in part on the telemetry data gathered from the fleet of electric vehicles. The intelligent EVSE unit and/or the DC fast charging unit receive the charging instructions, and charge the electric vehicle based at least in part on the charging instructions, the telemetry data, and/or an existent electrical load associated with an electrical panel of a house or a building.

There is provided a cart. An electric motor generates a travel driving force based on a control signal from an external control unit configured to perform control related a travel path of the cart. A battery supplies power to the electric motor. An engine drives a power generator which is configured to be capable of charging the battery. A determination unit determines whether the engine is to be operated, based on a predetermined condition.

An information processing apparatus includes an acquirer that acquires first information indicating a remaining charge of a first battery that is detachably mounted in an electric vehicle and supplies electric power for traveling of the electric vehicle and second information regarding a destination of the electric vehicle, a travel route predictor that predicts a travel route of the electric vehicle based on the second information acquired by the acquirer, and a determiner that refers to map information indicating, on a map, positions of a plurality of charging stations at which a second battery to be rented to a user is charged and determines a charging station at which the second battery is rented as a replacement for the first battery mounted in the electric vehicle based on the travel route predicted by the travel route predictor.

The present disclosure relates to a wired/wireless integrated power reception system provided in a vehicle, the wireless/wireless integrated power reception system including: a wired power reception apparatus configured to receive power from a transformer in a wired power receiving mode; a relay unit, which upon detecting reception of wireless power from a wireless power transmission pad, is configured to switch to a wireless power receiving mode; and a wireless power reception pad configured to receive power by magnetic coupling in the wireless power receiving mode.

A robot apparatus for establishing a charging connection between a charging device and an energy storage unit of a motor vehicle, having a movement unit, by which the robot apparatus is movable in relation to the charging device and the motor vehicle, having a receptacle device, by which a charging element of the charging device can be received, can be coupled to a coupling element of the energy storage unit and subsequently released, and having a detection unit, by which a position of the coupling element on the motor vehicle is ascertainable, wherein the robot apparatus is connectable by a support device to the motor vehicle, whereby a force is transmittable from the robot apparatus to the motor vehicle.

When a process of returning a vehicle is performed, a fee setting device identifies a zone where the vehicle is returned, and calculates the identified zone's zone SOC. The fee setting device determines whether a discount for leveling is applicable. The fee setting device compares a zone SOC of a zone where a user rented a vehicle and a zone SOC of a zone where the user returned the vehicle. When the zone SOC of the zone where the user rented the vehicle is larger than the zone SOC of the zone where the user returned the vehicle, the discount for leveling is applied.