| CPC B60L 53/65 (2019.02) [B60L 53/62 (2019.02); B60L 53/665 (2019.02); B60L 53/67 (2019.02); B60L 53/68 (2019.02); B60L 2240/80 (2013.01); B60L 2260/46 (2013.01)] | 20 Claims |
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1. A big data based central control charging system, comprising:
an electric vehicle charging unit which charges an electric vehicle using a plurality of charging modules; and
a central controller which collects state-of-charge (SOC) data by performing communication with the electric vehicle, by means of the electric vehicle charging unit,
wherein the central controller converts SOC data received from the electric vehicle, by means of the electric vehicle charging unit, into big data, extracts a feature item for each electric vehicle model and a data value of the feature item by analyzing and learning the big data of the SOC data, builds or updates a vehicle model identification model for identifying the electric vehicle model based on the extracted feature item and the feature item data value, selects SOC data of the same vehicle model, among the big data of the SOC data, compares the selected SOC data for each electric vehicle to extract different identification items, and stores charging and payment information for each electric vehicle in the database by matching an identification data value of one of the identification items,
wherein
the central controller applies a vehicle model specific variance of a target current to SoC for charging-control,
the value of the target current in a first SoC period is lower than the value of the target current in a second SoC period and the value of the target current in a third SoC period,
the first SoC period is from a beginning point to a first predetermined point in an entire SoC period,
the second SoC period is from the first predetermined point to a second predetermined point in the entire SoC period,
the third SoC period is from the second predetermined point to an end point in the entire SoC period,
the vehicle model specific variance of the target current is defined for each vehicle model by analyzing and learning the big data of the SOC data, and
the feature item includes a maximum current limit, a maximum voltage limit, a maximum power limit, a scale value, an identifier (ID) arrangement method, a bulk SoC, a full SoC, a variance of the target current to the SoC, a variance of the target current according to a temperature, a variance of the target current according to a state of health (SoH), and a message transmission speed for the electric vehicle.
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