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Volumn , Issue , 2011, Pages

Neural network based models for virtual NOx sensing of compression ignition engines

Author keywords

[No Author keywords available]

Indexed keywords

IGNITION; NETWORK ARCHITECTURE; NEURAL NETWORKS; NITROGEN OXIDES;

EID: 85072506488     PISSN: 01487191     EISSN: 26883627     Source Type: Journal    
DOI: 10.4271/2011-24-0157     Document Type: Conference Paper
Times cited : (12)

References (22)
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    • (1999) SAE Technical Paper 1999-01-1532
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  • 3
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    • Virtual Sensing: A Neural Network-based Intelligent Performance and Emissions Prediction System for On-Board Diagnostics and Engine Control
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    • Atkinson, C. M., Long, T. W., Hanzevack, E. L., "Virtual Sensing: A Neural Network-based Intelligent Performance and Emissions Prediction System for On-Board Diagnostics and Engine Control," SAE Technical Paper 980516, 1998, doi: 10.4271/980516.
    • (1998) SAE Technical Paper 980516
    • Atkinson, C.M.1    Long, T.W.2    Hanzevack, E.L.3
  • 4
    • 85072410932 scopus 로고    scopus 로고
    • Modelling Diesel Engine Combustion and NOx Formation for Model Based Control and Simulation of Engine and Exhaust Aftertreatment Systems
    • doi: 10.4271/2006-01-0687
    • Ericson, C., Westerberg, B., Andersson, M., Egnell, R., "Modelling Diesel Engine Combustion and NOx Formation for Model Based Control and Simulation of Engine and Exhaust Aftertreatment Systems," SAE Technical Paper 2006-01-0687, 2006, doi: 10.4271/2006-01-0687.
    • (2006) SAE Technical Paper 2006-01-0687
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  • 5
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    • The Impact of Exhaust Gas Recirculation on Performance and Emissions of a Heavy-Duty Diesel Engine
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    • Jacobs, T., Assanis, D., and Filipi, Z., "The Impact of Exhaust Gas Recirculation on Performance and Emissions of a Heavy-Duty Diesel Engine," SAE Technical Paper 2003-01-1068, 2003, doi: 10.4271/2003-01-1068.
    • (2003) SAE Technical Paper 2003-01-1068
    • Jacobs, T.1    Assanis, D.2    Filipi, Z.3
  • 6
    • 85072424296 scopus 로고    scopus 로고
    • Diesel Emission Control in Review
    • doi: 10.4271/2006-01-0030
    • Johnson, T. V., "Diesel Emission Control in Review," SAE Technical Paper 2006-01-0030, 2006, doi: 10.4271/2006-01-0030.
    • (2006) SAE Technical Paper 2006-01-0030
    • Johnson, T.V.1
  • 7
    • 85072500727 scopus 로고    scopus 로고
    • Development of Recurrent Neural Networks for Virtual Sensing of NOx Emissions in Internal Combustion Engines
    • doi: 10.4271/2009-24-0110
    • Arsie, I., Pianese, C., Sorrentino, M., "Development of Recurrent Neural Networks for Virtual Sensing of NOx Emissions in Internal Combustion Engines," SAE Int. J. Fuels Lubr. 2 (2): 354-361, 2009, doi: 10.4271/2009-24-0110.
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  • 9
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    • A Mean Value Model of the Exhaust System with SCR for an Automotive Diesel Engine
    • doi: 10.4271/2009-24-0131
    • Covassin, F., Preziuso, M., De Cesare, M., Serra, G., "A Mean Value Model of the Exhaust System with SCR for an Automotive Diesel Engine," SAE Technical Paper 2009-24-0131, 2009, doi: 10.4271/2009-24-0131.
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  • 11
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    • doi: 10.4271/2005-01-0045
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    • Nareid, H.1    Grimes, M.2    Verdejo, J.3
  • 13
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    • Virtual Sensor Design of Particulate and Nitric Oxide Emissions in a di Diesel Engine
    • doi: 10.4271/2005-24-063
    • Alberer, D., del Re, L., Winkler, S., Langthaler, P., "Virtual Sensor Design of Particulate and Nitric Oxide Emissions in a DI Diesel Engine," SAE Technical Paper 2005-24-063, 2005, doi: 10.4271/2005-24-063.
    • (2005) SAE Technical Paper 2005-24-063
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  • 14
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    • Information Based Selection of Neural Networks Training Data for S.I. Engine Mapping
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  • 22
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.