• Title of article

    An optimized chemical kinetic mechanism for HCCI combustion of PRFs using multi-zone model and genetic algorithm

  • Author/Authors

    Neshat، نويسنده , , Elaheh and Saray، نويسنده , , Rahim Khoshbakhti and Shafee، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2015
  • Pages
    12
  • From page
    172
  • To page
    183
  • Abstract
    Development of comprehensive chemical kinetic mechanisms is required for HCCI combustion and emissions prediction to be used in engine development. The main purpose of this study is development of a new chemical kinetic mechanism for primary reference fuels (PRFs) HCCI combustion, which can be applied to combustion models to predict in-cylinder pressure and exhaust CO and UHC emissions, accurately. Hence, a multi-zone model is developed for HCCI engine simulation. Two semi-detailed chemical kinetic mechanisms those are suitable for premixed combustion are used for n-heptane and iso-octane HCCI combustion simulation. The iso-octane mechanism contains 84 species and 484 reactions and the n-heptane mechanism contains 57 species and 296 reactions. A simple interaction between iso-octane and n-heptane is considered in new mechanism. The multi-zone model is validated using experimental data for pure n-heptane and iso-octane. A new mechanism is prepared by combination of these two mechanisms for n-heptane and iso-octane blended fuel, which includes 101 species and 594 reactions. New mechanism optimization is performed using genetic algorithm and multi-zone model. Mechanism contains low temperature heat release region, which decreases with increasing octane number. The results showed that the optimized chemical kinetic mechanism is capable of predicting engine-related combustion and performance parameters. Also after implementing the optimized mechanism, engine unburned HC and CO emissions predicted by the model are in good agreement with the corresponding experimental data.
  • Keywords
    HCCI combustion , Primary reference fuel , Multi-zone model , Chemical kinetic , genetic algorithm
  • Journal title
    Energy Conversion and Management
  • Serial Year
    2015
  • Journal title
    Energy Conversion and Management
  • Record number

    2339168