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    Distributed embedded controller implementation for self-learning controls
    2.
    发明授权
    Distributed embedded controller implementation for self-learning controls 有权

    公开(公告)号：US12145610B2

    公开(公告)日：2024-11-19

    申请号：US17695909

    申请日：2022-03-16

    Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

    Inventor： Ibrahim Haskara ,  Bharatkumar Hegde ,  Chen-Fang Chang

    IPC: B60W50/06 ,  B60W50/00 ,  G05B13/02

    Abstract: A distributed learning system of a vehicle includes: a control module configured to: control a plant of the vehicle using a policy; send signals to a learning module including information on an impact of the control on the plant; and selectively control the plant using exploratory control; and the learning module, where the learning module is separate from the control module and is configured to selectively update the policy based on (a) the signals from the control module, (b) state parameters resulting from the control of the plant using the policy, and (c) performance feedback determined based on the control of the plant using the policy and the selective control of the plant using exploratory control, where the control module is configured to receive the exploratory control from the learning module.

    ENERGY MANAGEMENT SYSTEM FOR AN ELECTRIC VEHICLE
    3.
    发明申请
    ENERGY MANAGEMENT SYSTEM FOR AN ELECTRIC VEHICLE 有权

    公开(公告)号：US20220332165A1

    公开(公告)日：2022-10-20

    申请号：US17224392

    申请日：2021-04-07

    Applicant: GM Global Technology Operations LLC

    Inventor： Ibrahim Haskara ,  Bharatkumar Hegde ,  Chen-Fang Chang

    IPC: B60H1/00 ,  B60W10/08

    Abstract: A computer for an energy management system of an electric vehicle includes a processor. The computer further includes a memory including instructions such that the processor is programmed to determine a value function V based on a plurality of actions U in a plurality of states S. The processor is further programmed to select an action associated with a highest reward value at a current state S. The action U is an HVAC subsystem variable. The state S is a traction power drawn from a rechargeable energy storage system (RESS) to operate a traction subsystem, a base power input drawn from the RESS to operate an HVAC subsystem, a nominal reference cabin heat input set-point determined by the local HVAC processor, an acceleration of the electric vehicle, a current vehicle speed, an average vehicle speed, and a calibrated average vehicle speed estimate.

    Two-stage turbocharger flow control
    7.
    发明授权
    Two-stage turbocharger flow control 有权
    两级涡轮增压器流量控制

    公开(公告)号：US09217362B2

    公开(公告)日：2015-12-22

    申请号：US14023947

    申请日：2013-09-11

    Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

    Inventor： Yue-Yun Wang ,  Ibrahim Haskara ,  Kevin Andrew Gady

    IPC: F02D23/00 ,  F02B37/013 ,  F02B37/16 ,  F02B37/18 ,  F02M37/18 ,  F02B37/00 ,  F02D41/00 ,  F02D41/18

    CPC classification number: F02B37/013 ,  F02B37/004 ,  F02B37/168 ,  F02B37/183 ,  F02D41/0007 ,  F02D41/18 ,  F02D2200/0406 ,  F02M37/18 ,  Y02T10/144

    Abstract: A method is disclosed for controlling a two-stage turbocharger system having low-pressure and high-pressure turbochargers in line, sequentially, with an engine. The turbochargers include a low-pressure (LP) turbine and an LP compressor, and a high-pressure (HP) turbine and an HP compressor. The LP compressor feeds the HP compressor, which feeds the engine intake. The engine exhaust feeds the HP turbine, which feeds the LP turbine. The method determines a total boost pressure, which provides combustion reactant for the engine. The method calculates an LP compressor power from the determined total boost pressure, and an LP turbine flow from the LP compressor power. The low-pressure turbocharger operates at the calculated LP turbine flow. The method calculates an HP compressor power from the determined total boost pressure, and an HP turbine flow from the HP compressor power. The high-pressure turbocharger operates at the calculated HP turbine flow.

    Abstract translation: 公开了一种用于根据发动机依次管理具有低压和高压涡轮增压器的两级涡轮增压器系统的方法。 涡轮增压器包括低压（LP）涡轮机和LP压缩机，以及高压（HP）涡轮机和HP压缩机。 LP压缩机为供应发动机进气口的HP压缩机供给。 发动机排气进给供给LP涡轮机的HP涡轮机。 该方法确定总增压压力，其为发动机提供燃烧反应物。 该方法根据所确定的总增压压力和来自LP压缩机功率的LP涡轮机流量来计算LP压缩机功率。 低压涡轮增压器以计算的LP涡轮机流量运行。 该方法根据确定的总增压压力和HP压缩机功率的HP涡轮机流量计算HP压缩机功率。 高压涡轮增压器以计算的HP涡轮流量运行。

    ARTIFICIAL INTELLIGENCE BASED SYSTEM AND METHOD FOR ENERGY CELL FAULT IDENTIFICATION
    8.
    发明申请
    ARTIFICIAL INTELLIGENCE BASED SYSTEM AND METHOD FOR ENERGY CELL FAULT IDENTIFICATION 有权

    公开(公告)号：US20240367539A1

    公开(公告)日：2024-11-07

    申请号：US18310794

    申请日：2023-05-02

    Applicant: GM Global Technology Operations LLC

    Inventor： Yue-Yun Wang ,  Ibrahim Haskara

    IPC: B60L53/62 ,  B60L58/10 ,  B60W50/12

    Abstract: A system for monitoring an electric power storage system includes: a processor electrically connected to multiple sensors, each of the sensors being configured to detect at least one parameter of the electric power storage system the processor being configured to acquire a set of direct measurement data of the set of power cells from the plurality of sensors, provide the set of direct measurement data to a physics model within the processor and generate a set of derived measurement data using the physics model, provide the derived measurement data and at least a portion of the direct measurement data to a machine learning model and generate a coordinate position corresponding to a fault condition of the set of power cells, compare the coordinate position to a fault map and identifying a probable fault cause based on the comparison, and alter an operation of the vehicle based on the comparison.

    Solar-load prediction for vehicular cabin thermal actuator control
    9.
    发明授权
    Solar-load prediction for vehicular cabin thermal actuator control 有权

    公开(公告)号：US12078500B2

    公开(公告)日：2024-09-03

    申请号：US17701782

    申请日：2022-03-23

    Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

    Inventor： Bharatkumar Hegde ,  Ibrahim Haskara ,  Shailendra Kaushik ,  Chen-Fang Chang

    IPC: G01C21/00 ,  B60W40/08 ,  G01C21/34

    CPC classification number: G01C21/3492 ,  B60W40/08 ,  G01C21/3461 ,  G01C21/3484 ,  B60W2040/0872

    Abstract: A solar loading-based system includes a memory, a disturbance prediction module, a cabin temperature estimation module and a thermal control module. The memory stores a cabin thermal load model of an interior cabin of a host vehicle and a solar load prediction model. The disturbance prediction module: receives signals indicative of states of cabin thermal actuators and comfort metrics; and predicts an effect of solar loading over a known portion of a predicted route including predicting cabin temperatures based on the solar load prediction model, the states of the cabin thermal actuators, and the comfort metrics. The cabin temperature estimation module, based on the cabin thermal load model, determines a first comfort metric based on the predicted cabin temperatures. The thermal control module controls cabin thermal actuators to adjust cabin states, including the first comfort metric, to respective target values based on the predicted effect of solar loading.

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