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    SYSTEM AND METHOD FOR ENERGY EFFICIENT PROGNOSTICS
    1.
    发明公开
    SYSTEM AND METHOD FOR ENERGY EFFICIENT PROGNOSTICS 审中-公开

    公开(公告)号：US20230288930A1

    公开(公告)日：2023-09-14

    申请号：US18317270

    申请日：2023-05-15

    Applicant: GM Cruise Holdings LLC

    Inventor： Michael Frank Schmidt ,  Chase Brian Kaufman ,  Samuel Harrison Glidden ,  Erik Birk Nielsen ,  Jason Lee

    IPC: G05D1/00 ,  G06F17/18 ,  G07C5/08 ,  G07C5/00 ,  G05D1/02

    CPC classification number: G05D1/0088 ,  G06F17/18 ,  G07C5/0808 ,  G07C5/006 ,  G05D1/0291

    Abstract: Described herein is a server computing system that controls an autonomous vehicle to perform an operation to at least one of measure or isolate an effect of a variable on an actual power consumption by the autonomous vehicle. Data indicative of the actual power consumption, which is generated based on the operation, and data indicative of a projected power consumption, which is accumulated based on prior execution of the operation by a same or different autonomous vehicle, is received by the server computing system to determine whether an energy efficiency of the autonomous vehicle is degraded. The operation may be performed to identify a degraded vehicle system or component of the autonomous vehicle or to identify an autonomous vehicle in a fleet of autonomous vehicles for which further analysis is desirable. An output is generated by the server computing system that is indicative of the energy efficiency prognostics.

    PREDICTIVE MAINTENANCE AND DIAGNOSTICS USING MODULAR CONDITION MONITORING
    2.
    发明申请
    PREDICTIVE MAINTENANCE AND DIAGNOSTICS USING MODULAR CONDITION MONITORING 有权

    公开(公告)号：US20210390803A1

    公开(公告)日：2021-12-16

    申请号：US17463486

    申请日：2021-08-31

    Applicant: GM Cruise Holdings LLC

    Inventor： Michael Frank Schmidt ,  Samuel Harrison Glidden ,  Erik Birk Nielsen ,  Chase Brian Kaufman

    IPC: G07C5/08 ,  G07C5/00

    Abstract: Predictive maintenance and diagnostics for an electronic module of an autonomous vehicle using modular condition monitoring is described herein. A computing system receives a signal from a data logger which monitors a condition of the electronic module of the autonomous vehicle, wherein the signal is indicative of damage accumulation information thereof. The computing system identifies a type of the electronic module and a damage accumulation threshold for the type of the electronic module to generate a predicted maintenance schedule for the electronic module of the autonomous vehicle. The damage accumulation information can be stored in a data store to define the damage accumulation threshold for the type of the electronic module.

    PREDICTIVE MAINTENANCE AND DIAGNOSTICS USING MODULAR CONDITION MONITORING
    5.
    发明申请
    PREDICTIVE MAINTENANCE AND DIAGNOSTICS USING MODULAR CONDITION MONITORING 审中-公开

    公开(公告)号：US20200184747A1

    公开(公告)日：2020-06-11

    申请号：US16215249

    申请日：2018-12-10

    Applicant: GM Cruise Holdings LLC

    Inventor： Michael Frank Schmidt ,  Samuel Harrison Glidden ,  Erik Birk Nielsen ,  Chase Brian Kaufman

    IPC: G07C5/08 ,  G07C5/00

    Abstract: Predictive maintenance and diagnostics for an electronic module of an autonomous vehicle using modular condition monitoring is described herein. A computing system receives a signal from a data logger which monitors a condition of the electronic module of the autonomous vehicle, wherein the signal is indicative of damage accumulation information thereof. The computing system identifies a type of the electronic module and a damage accumulation threshold for the type of the electronic module to generate a predicted maintenance schedule for the electronic module of the autonomous vehicle. The damage accumulation information can be stored in a data store to define the damage accumulation threshold for the type of the electronic module.

    SYSTEM AND METHOD TO DYNAMICALLY SUPPRESS NOISE AT ELECTRIC VEHICLE CHARGING SITES
    8.
    发明公开
    SYSTEM AND METHOD TO DYNAMICALLY SUPPRESS NOISE AT ELECTRIC VEHICLE CHARGING SITES 审中-公开

    公开(公告)号：US20230166621A1

    公开(公告)日：2023-06-01

    申请号：US17539129

    申请日：2021-11-30

    Applicant: GM Cruise Holdings LLC

    Inventor： Jeffrey Brandon ,  Darren Hau ,  Samuel Harrison Glidden ,  Michael Frank Schmidt

    IPC: B60L53/62 ,  B60L53/30 ,  B60L58/24

    CPC classification number: B60L53/62 ,  B60L53/30 ,  B60L58/24 ,  B60L2270/147

    Abstract: Systems and methods for dynamically suppressing noise at electric vehicle charging sites. In particular, systems and methods are provided for measuring the ambient noise at a charging site and adjusting electric vehicle chargers to reduce noise pollution. In some examples, electric vehicle charger cooling fans potentially generate a high level of noise, and the power output of a charger can be decreased to decrease the heat generated by the chargers, thereby reducing the need for fans. In various examples, reduction of noise pollution can be especially important in specified geographies (e.g., residential neighborhoods) and/or during selected timeframes (e.g., overnight). In various examples, the system interfaces with a central computer service (e.g., a dispatch service) to intelligently route autonomous vehicles to charging sites based on noise levels at various available charging sites.

    System and method for energy efficient prognostics
    10.
    发明授权
    System and method for energy efficient prognostics 有权

    公开(公告)号：US11294373B2

    公开(公告)日：2022-04-05

    申请号：US16371008

    申请日：2019-03-31

    Applicant: GM Cruise Holdings LLC

    Inventor： Michael Frank Schmidt ,  Chase Brian Kaufman ,  Samuel Harrison Glidden ,  Erik Birk Nielsen ,  Jason Lee

    IPC: G05D1/00 ,  G06F17/18 ,  G07C5/08 ,  G07C5/00 ,  G05D1/02

    Abstract: Described herein is a server computing system that controls an autonomous vehicle to perform an operation to at least one of measure or isolate an effect of a variable on an actual power consumption by the autonomous vehicle. Data indicative of the actual power consumption, which is generated based on the operation, and data indicative of a projected power consumption, which is accumulated based on prior execution of the operation by a same or different autonomous vehicle, is received by the server computing system to determine whether an energy efficiency of the autonomous vehicle is degraded. The operation may be performed to identify a degraded vehicle system or component of the autonomous vehicle or to identify an autonomous vehicle in a fleet of autonomous vehicles for which further analysis is desirable. An output is generated by the server computing system that is indicative of the energy efficiency prognostics.

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