Precision coil alignment techniques for vehicle wireless power transfer

    公开(公告)号:US11021074B2

    公开(公告)日:2021-06-01

    申请号:US16011935

    申请日:2018-06-19

    摘要: In one embodiment, a device obtains sensor data indicative of three dimensional (3-D) orientations of primary and secondary wireless power transfer (WPT) charging coils. The secondary coil is mounted to a vehicle and the primary coil provides charge to the secondary coil during charging. The device detects misalignment between the primary and secondary WPT coils based on the sensor data. The device determines a coil alignment correction to offset the detected misalignment. The device sends control commands to one or more actuators to implement the coil alignment correction by moving one or more of the coils, either directly (e.g., via directly-coupled actuators) or indirectly (e.g., via the suspension of a vehicle).

    PRECISION COIL ALIGNMENT TECHNIQUES FOR VEHICLE WIRELESS POWER TRANSFER

    公开(公告)号:US20190381891A1

    公开(公告)日:2019-12-19

    申请号:US16011935

    申请日:2018-06-19

    IPC分类号: B60L11/18 H02J50/10 G06N99/00

    摘要: In one embodiment, a device obtains sensor data indicative of three dimensional (3-D) orientations of primary and secondary wireless power transfer (WPT) charging coils. The secondary coil is mounted to a vehicle and the primary coil provides charge to the secondary coil during charging. The device detects misalignment between the primary and secondary WPT coils based on the sensor data. The device determines a coil alignment correction to offset the detected misalignment. The device sends control commands to one or more actuators to implement the coil alignment correction by moving one or more of the coils, either directly (e.g., via directly-coupled actuators) or indirectly (e.g., via the suspension of a vehicle).

    COMMUNICATION SOLUTIONS FOR SELF-DRIVING CAR SERVICES

    公开(公告)号:US20180299895A1

    公开(公告)日:2018-10-18

    申请号:US15489857

    申请日:2017-04-18

    IPC分类号: G05D1/02 G06K7/10

    摘要: Presented herein are techniques for matching a user, e.g., a child, with an autonomous vehicle instructed to pick up the child. In an embodiment, a method includes receiving, at a server, information from an autonomous vehicle, receiving, at the server, information from a user device, receiving, at the server, information from a responsible party device, processing, by the server, the information from the autonomous vehicle, the information from the user device, and the information from the responsible party device, and based on the processing of the information from the autonomous vehicle, the information from the user device, and the information from the responsible party device, verifying, by the server, that the autonomous vehicle is matched with a user of the user device.

    Augmenting Wi-Fi localization with auxiliary sensor information
    5.
    发明授权
    Augmenting Wi-Fi localization with auxiliary sensor information 有权
    使用辅助传感器信息增强Wi-Fi本地化

    公开(公告)号:US09571980B1

    公开(公告)日:2017-02-14

    申请号:US14980316

    申请日:2015-12-28

    摘要: In one implementation, a method of maintaining continuous identity for mobile devices includes: obtaining a first address for a first device; and obtaining, from one or more auxiliary sensors, auxiliary sensor information related to the first device. The method also includes determining whether the auxiliary sensor information matches information associated with a second address, where the second address was previously associated with the first device. The method further includes linking the first address with the second address for the first device, in order to continue tracking the first device when the second address is no longer detected, in response to determining that the auxiliary sensor information matches information associated with the second address.

    摘要翻译: 在一个实现中,维护用于移动设备的连续身份的方法包括:获得第一设备的第一地址; 以及从一个或多个辅助传感器获得与所述第一设备相关的辅助传感器信息。 该方法还包括确定辅助传感器信息是否匹配与第二地址相关联的信息,其中第二地址先前与第一设备相关联。 该方法还包括:响应于确定辅助传感器信息匹配与第二地址相关联的信息,将第一地址与第一设备的第二地址相关联,以便当不再检测到第二地址时继续跟踪第一设备 。

    CORRELATING DEVICES AND CLIENTS ACROSS ADDRESSES

    公开(公告)号:US20230254687A1

    公开(公告)日:2023-08-10

    申请号:US18301937

    申请日:2023-04-17

    IPC分类号: H04W8/26 H04W8/02

    CPC分类号: H04W8/26 H04W8/02 H04W84/12

    摘要: Correlating devices and clients across addresses may be provided. A first address associated with a client device may be received. When the client device is not connected to a network, first location data associated with the first address may be obtained using a passive technique. A second address and second location data associated with the second address may then be obtained using an active technique. It may then be determined that the first location data and the second location data correlate. In response to determining that the first location data and the second location data correlate, it may be determined that the client device has changed from the first address to the second address.

    ORTHOGONAL FREQUENCY-DIVISION MULTIPLEXING EQUALIZATION USING DEEP NEURAL NETWORK

    公开(公告)号:US20210067397A1

    公开(公告)日:2021-03-04

    申请号:US16558942

    申请日:2019-09-03

    IPC分类号: H04L27/26 H04L27/01 G06N3/08

    摘要: Orthogonal frequency-division multiplexing (OFDM) equalization using a Deep Neural Network (DNN) may be provided. First, a signal in a packet structure may be received at an OFDM receiver from an OFDM transmitter. The signal may have distortion. Training constellation points, pilot constellation points, and data constellation points may be extracted from the signal based on the packet structure. Each data constellation point may correspond to a data subcarrier within a data symbol of the signal. Next, the training constellation points and the pilot constellation may be provided as input for the data symbol to a DNN. A coefficient for each data subcarrier within the data symbol that reverses the distortion may be received as output from the DNN. Then, the coefficient for each data subcarrier may be applied to the corresponding data constellation point to determine a per subcarrier constellation point prediction.