Performance prediction of HCCI engines with oxygenated fuels using artificial neural networks

Applied Energy

Volumn 138, Issue , 2015, Pages 460-473

  Rezaei, Javad ^a   Shahbakhti, Mahdi ^b   Bahri, Bahram ^c   Aziz, Azhar Abdul ^d  

^a IRAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Iran)

^b Michigan Technological University   (United States)

^c ISLAMIC AZAD UNIVERSITY   (Iran)

^d UNIVERSITI TEKNOLOGI MALAYSIA   (Malaysia)

Author keywords

Engine performance; HCCI; Neural network; Oxygenated fuel

Indexed keywords

CARBON MONOXIDE; ENGINE CYLINDERS; ETHANOL; ETHANOL FUELS; FORECASTING; FUELS; IGNITION; NEURAL NETWORKS; NITROGEN OXIDES; RADIAL BASIS FUNCTION NETWORKS;

ENGINE PERFORMANCE; EXPERIMENTAL DATA ANALYSIS; HCCI; HOMOGENEOUS CHARGE COMPRESSION IGNITION; INDICATED MEAN EFFECTIVE PRESSURE; OXYGENATED FUEL; PERFORMANCE AND EMISSIONS; RADIAL BASIS FUNCTION(RBF);

ENGINES;

ALCOHOL; ALTERNATIVE FUEL; ARTIFICIAL NEURAL NETWORK; ENGINE; EXHAUST EMISSION; FUEL CONSUMPTION; PERFORMANCE ASSESSMENT; PREDICTION;

EID: 84909991989     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2014.10.088     Document Type: Article

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