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    Exhaust Pressure Estimation and Its Application to Detection and Isolation of Turbocharger System Faults for Internal Combustion Engines

    Source: Journal of Dynamic Systems, Measurement, and Control:;2012:;volume( 134 ):;issue: 002::page 21002
    Author:
    Yue-Yun Wang
    ,
    Ibrahim Haskara
    DOI: 10.1115/1.4005045
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Engine exhaust backpressure is a critical parameter in the calculation of the volumetric efficiency and exhaust gas recirculation flow of an internal combustion engine. The backpressure also needs to be controlled to a presetting limit under high speed and load engine operating conditions to avoid damaging a turbocharger. In this paper, a method is developed to estimate exhaust pressure for internal combustion engines equipped with variable geometry turbochargers. The method uses a model-based approach that applies a coordinate transformation to generate a turbine map for the estimation of exhaust pressure. This estimation can substitute for an expensive pressure sensor, thus saving significant cost for production vehicles. On the other hand, for internal combustion engines that have already installed exhaust pressure sensors, this estimation can be used to generate residual signals for model-based diagnostics. Cumulative sum algorithms are applied to residuals based on multiple sensor fusion, and with the help of signal processing, the algorithms are able to detect and isolate critical failure modes of a turbocharger system.
    keyword(s): Pressure , Exhaust systems , Engines , Sensors , Turbines AND Pressure sensors ,
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      Exhaust Pressure Estimation and Its Application to Detection and Isolation of Turbocharger System Faults for Internal Combustion Engines

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    http://yetl.yabesh.ir/yetl1/handle/yetl/148503
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    • Journal of Dynamic Systems, Measurement, and Control

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    contributor authorYue-Yun Wang
    contributor authorIbrahim Haskara
    date accessioned2017-05-09T00:49:12Z
    date available2017-05-09T00:49:12Z
    date copyrightMarch, 2012
    date issued2012
    identifier issn0022-0434
    identifier otherJDSMAA-26582#021002_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/148503
    description abstractEngine exhaust backpressure is a critical parameter in the calculation of the volumetric efficiency and exhaust gas recirculation flow of an internal combustion engine. The backpressure also needs to be controlled to a presetting limit under high speed and load engine operating conditions to avoid damaging a turbocharger. In this paper, a method is developed to estimate exhaust pressure for internal combustion engines equipped with variable geometry turbochargers. The method uses a model-based approach that applies a coordinate transformation to generate a turbine map for the estimation of exhaust pressure. This estimation can substitute for an expensive pressure sensor, thus saving significant cost for production vehicles. On the other hand, for internal combustion engines that have already installed exhaust pressure sensors, this estimation can be used to generate residual signals for model-based diagnostics. Cumulative sum algorithms are applied to residuals based on multiple sensor fusion, and with the help of signal processing, the algorithms are able to detect and isolate critical failure modes of a turbocharger system.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleExhaust Pressure Estimation and Its Application to Detection and Isolation of Turbocharger System Faults for Internal Combustion Engines
    typeJournal Paper
    journal volume134
    journal issue2
    journal titleJournal of Dynamic Systems, Measurement, and Control
    identifier doi10.1115/1.4005045
    journal fristpage21002
    identifier eissn1528-9028
    keywordsPressure
    keywordsExhaust systems
    keywordsEngines
    keywordsSensors
    keywordsTurbines AND Pressure sensors
    treeJournal of Dynamic Systems, Measurement, and Control:;2012:;volume( 134 ):;issue: 002
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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