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    Intelligent Mass Air Flow (MAF) Prediction System with Neural Network
    2.
    发明申请
    Intelligent Mass Air Flow (MAF) Prediction System with Neural Network 有权

    公开(公告)号：US20220349358A1

    公开(公告)日：2022-11-03

    申请号：US17245484

    申请日：2021-04-30

    申请人： International Engine Intellectual Property Company, LLC

    发明人： Askin Minaz ,  Ravi Rayala ,  Jungme Park ,  Rahul Rajampeta Rahul Rajampeta ,  Manoj Vemuri ,  Sriram Jayachandran Raguraman

    IPC分类号： F02D41/18 ,  G06N3/08 ,  G06K9/62

    摘要： The Method and Apparatus of Predicting MAF Sensor Information includes training multiple candidate Artificial Neural Network (ANN) architectures using training data, and then selecting an ANN architecture from the candidates using an automated ANN architecture selection algorithm and testing data. An intelligent engine intake MAF prediction or estimation system using the selected ANN architecture then provides an engine intake Mass Air Flow (MAF) output variable, which is used along with the output of a hot-wire type engine intake MAF sensor. The system is deployed into the engine controller. The training and testing sets of data include input variables from engine sensors and/or actuators that relate to engine intake MAF, and may be acquired by testing a target engine. Selecting the optimal ANN architecture may be based on Root Mean Squared Error (RMSE) analysis using the automated ANN architecture algorithm and the training set of data.

    MOTOR VEHICLE WITH INTERNAL COMBUSTION ENGINE
    3.
    发明申请
    MOTOR VEHICLE WITH INTERNAL COMBUSTION ENGINE 有权

    公开(公告)号：US20210213929A1

    公开(公告)日：2021-07-15

    申请号：US17216483

    申请日：2021-03-29

    申请人： International Engine Intellectual Property Company, LLC

    发明人： Lee Tran ,  Askin Minaz ,  Ravi Rayala ,  Suttisak Pardungkiattisak

    IPC分类号： B60W10/06 ,  B60W30/188 ,  G06Q30/06 ,  H04W4/40 ,  G06Q30/00

    摘要： A motor vehicle including a chassis, drive wheels connected to the chassis, steered wheels connected to the chassis, and an internal combustion engine. The internal combustion engine connected to the chassis. The internal combustion engine connected to the drive wheels. The internal combustion engine has a first predetermined range of operational capability. The engine being suitably designed for operating across the first predetermined range of operational capability throughout the life of the engine. The internal combustion engine has a second predetermined range of operational capability. The second range of operational capability is greater than the first range of operational capability. The internal combustion engine operates at the second range of operational capability for a predetermined time period when an additional fee is paid. When the predetermined time period ends, the internal combustion engine returns to the first predetermined range of operational capability.

    System and method for estimating engine exhaust nitrogen oxide sensor instability
    4.
    发明授权
    System and method for estimating engine exhaust nitrogen oxide sensor instability 有权

    公开(公告)号：US10690078B2

    公开(公告)日：2020-06-23

    申请号：US15962650

    申请日：2018-04-25

    申请人： International Engine Intellectual Property Company, LLC

    发明人： Askin Minaz ,  Robert Manoni

    IPC分类号： F02D41/14 ,  F01N3/20

    摘要： A system and method is provided for estimating engine exhaust nitrogen oxide sensor signal instability in transient conditions, for example when rapid changes occur in driver demanded torque, and for eliminating fluctuations in EONOx sensor signal status, in order to have more robust on-board diagnostics monitoring and exhaust nitrogen oxide control. The system and method predicts EONOx sensor signal instability by comparing a calculated pedal based driver demand torque delta to calculated instability thresholds and instability threshold hysteresis margins, and generates instability flags. The system and method further validates any predicted EONOx sensor signal instability by observation. Upon validation of the predicted EONOx sensor signal instability, the system and method latches the EONOx sensor signal status to a stable value.

    Method and Arrangement for Predicting Engine Out Nitrogen Oxides (EONOx) using a Neural Network
    5.
    发明申请
    Method and Arrangement for Predicting Engine Out Nitrogen Oxides (EONOx) using a Neural Network 有权

    公开(公告)号：US20220351022A1

    公开(公告)日：2022-11-03

    申请号：US17245626

    申请日：2021-04-30

    申请人： International Engine Intellectual Property Company, LLC

    发明人： Askin Minaz

    IPC分类号： G06N3/04 ,  G06N3/08

    摘要： The Method and Arrangement for Predicting Engine Out Nitrogen Oxides (EONOx) includes training multiple candidate Artificial Neural Network (ANN) architectures using training data, and then selecting an ANN architecture from the candidates using an automated ANN architecture selection algorithm and testing data. An intelligent EONOx prediction or estimation system using the selected ANN architecture then provides an EONOx output variable, which is used along with the output of an EONOx sensor. The system is deployed into the engine controller. The training and testing sets of data include input variables from engine sensors and/or actuators that relate to EONOx, and may be acquired by testing a target engine. Selecting the optimal ANN architecture may be based on Root Mean Squared Error (RMSE) analysis using the automated ANN architecture algorithm and the training set of data.

    System and Method for Estimating Engine Exhaust Nitrogen Oxide Sensor Instability
    8.
    发明申请
    System and Method for Estimating Engine Exhaust Nitrogen Oxide Sensor Instability 审中-公开

    公开(公告)号：US20190331044A1

    公开(公告)日：2019-10-31

    申请号：US15962650

    申请日：2018-04-25

    申请人： International Engine Intellectual Property Company, LLC

    发明人： Askin Minaz ,  Robert Manoni

    IPC分类号： F02D41/14 ,  F01N3/20

    摘要： A system and method is provided for estimating engine exhaust nitrogen oxide sensor signal instability in transient conditions, for example when rapid changes occur in driver demanded torque, and for eliminating fluctuations in EONOx sensor signal status, in order to have more robust on-board diagnostics monitoring and exhaust nitrogen oxide control. The system and method predicts EONOx sensor signal instability by comparing a calculated pedal based driver demand torque delta to calculated instability thresholds and instability threshold hysteresis margins, and generates instability flags. The system and method further validates any predicted EONOx sensor signal instability by observation. Upon validation of the predicted EONOx sensor signal instability, the system and method latches the EONOx sensor signal status to a stable value.