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.

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.

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.

A charging station assembly capable of generating and delivering a conditioned airflow while charging a battery of a vehicle. The temperature and flow rate of this conditioned airflow may be controlled based on the ambient conditions and battery status. The conditioned airflow may be directed toward an outside heat exchanger of a refrigerant system of the vehicle to enhance capacity. The conditioned airflow may also be routed to a battery pack for direct cooling or heating through additional ventilation system. In hot ambient conditions, the charging station provides cool air to facilitate battery cooling. In cold ambient conditions, the charging station provides hot air to facilitate battery heating. This charging station assembly shifts the load from the vehicle refrigerant system to the charging system, thereby improving battery thermal management capability, while eliminating the need for an oversized refrigerant system.

A charging station assembly capable of generating and delivering a conditioned airflow while charging a battery of a vehicle. The temperature and flow rate of this conditioned airflow may be controlled based on the ambient conditions and battery status. The conditioned airflow may be directed toward an outside heat exchanger of a refrigerant system of the vehicle to enhance capacity. The conditioned airflow may also be routed to a battery pack for direct cooling or heating through additional ventilation system. In hot ambient conditions, the charging station provides cool air to facilitate battery cooling. In cold ambient conditions, the charging station provides hot air to facilitate battery heating. This charging station assembly shifts the load from the vehicle refrigerant system to the charging system, thereby improving battery thermal management capability, while eliminating the need for an oversized refrigerant system.

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.

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.

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.

A battery charging system includes a battery removably mounted on an electric power device using electric power, a charging device configured to charge the battery using renewable power which is electric power generated from renewable energy, and a server configured to communicate with the charging device. The charging device is configured to control charging of the battery accommodated in an accommodation unit on the basis of reception information received from the server. The server is configured to compare receivable power, which is the renewable power capable of being received by the charging device, with a threshold value and configured to transmit transmission information for causing the charging device to control the charging of the battery to the charging device on the basis of a result of comparing the receivable power with the threshold value.