Charging station
    51.
    外观设计

    公开(公告)号:USD1005937S1

    公开(公告)日:2023-11-28

    申请号:US29866728

    申请日:2022-09-26

    摘要: FIG. 1 is a rear perspective view of the charging station showing our new design;
    FIG. 2 is a front elevational view thereof;
    FIG. 3 is a front elevational view thereof;
    FIG. 4 is a rear elevational view thereof;
    FIG. 5 is a right-side elevational view thereof;
    FIG. 6 is a left-side elevational view thereof;
    FIG. 7 is a top plan view thereof; and,
    FIG. 8 is a bottom plan view thereof.
    The broken lines immediately adjacent the shaded areas represent the bounds of the claimed design while all other broken lines depict portions of the charging station that form no part of the claimed design; the broken lines form no part of the claimed design.

    AUTOMATIC PREDICTION OF VISITATIONS TO SPECIFIED POINTS OF INTEREST

    公开(公告)号:US20230341236A1

    公开(公告)日:2023-10-26

    申请号:US18346617

    申请日:2023-07-03

    IPC分类号: G01C21/36 H04W4/021 G06N5/022

    摘要: Techniques are described herein for predicting popularity metrics and/or visitation metrics that are used in the selection of a point of interest (POI) for placement of an electric vehicle charging station (EVCS). The techniques involve training a machine learning model based on information obtained about POIs at which EVCSs are already installed. The information used to train the machine learning model includes, for each existing installation location: (a) visitation data that describes visitation features, and (b) popularity metrics and/or visitation metrics that have been generated for the location. When the machine learning model has been trained, the trained machine learning model predicts popularity metrics and/or visitation metrics for a POI location at which no EVCS has been installed based on the visitation data of that POI.

    FLEET ELECTRIFICATION MANAGEMENT
    57.
    发明申请

    公开(公告)号:US20230045381A1

    公开(公告)日:2023-02-09

    申请号:US17932631

    申请日:2022-09-15

    摘要: Techniques are described herein for fleet electrification management. A method includes determining a composition of electric vehicles (EVs) to replace at least a portion of non-electric vehicles in a vehicle fleet while satisfying travel requirements of the vehicle fleet. The method includes estimating an energy demand of the composition of EVs. The method includes determining an electric vehicle supply equipment (EVSE) charging infrastructure to meet the estimated energy demand. The method includes providing one or more recommendations including at least one of: a fleet electrification recommendation for transitioning the vehicle fleet into the composition of EVs, or a charging infrastructure recommendation for implementing the EVSE charging infrastructure.

    AUTOMATIC PREDICTION OF VISITATIONS TO SPECIFIED POINTS OF INTEREST

    公开(公告)号:US20230040465A1

    公开(公告)日:2023-02-09

    申请号:US17880538

    申请日:2022-08-03

    IPC分类号: G01C21/36 H04W4/021

    摘要: Techniques are described herein for predicting popularity metrics and/or visitation metrics that are used in the selection of a point of interest (POI) for placement of an electric vehicle charging station (EVCS). The techniques involve training a machine learning model based on information obtained about POIs at which EVCSs are already installed. The information used to train the machine learning model includes, for each existing installation location: (a) visitation data that describes visitation features, and (b) popularity metrics and/or visitation metrics that have been generated for the location. When the machine learning model has been trained, the trained machine learning model predicts popularity metrics and/or visitation metrics for a POI location at which no EVCS has been installed based on the visitation data of that POI.

    FLEET ELECTRIFICATION MANAGEMENT
    59.
    发明申请

    公开(公告)号:US20230038368A1

    公开(公告)日:2023-02-09

    申请号:US17882481

    申请日:2022-08-05

    摘要: Techniques are described herein for fleet electrification management. A method includes determining a composition of electric vehicles (EVs) to replace at least a portion of non-electric vehicles in a vehicle fleet while satisfying travel requirements of the vehicle fleet. The method includes estimating an energy demand of the composition of EVs. The method includes determining an electric vehicle supply equipment (EVSE) charging infrastructure to meet the estimated energy demand. The method includes providing one or more recommendations including at least one of: a fleet electrification recommendation for transitioning the vehicle fleet into the composition of EVs, or a charging infrastructure recommendation for implementing the EVSE charging infrastructure.