首页    期刊浏览 2024年11月30日 星期六
登录注册

文章基本信息

  • 标题:Modeling and simulation of the thermodynamic cycle of the Diesel Engine using Neural Networks
  • 本地全文:下载
  • 作者:Ali Rida ; Hassan Moussa Nahim ; Rafic Younes
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2016
  • 卷号:49
  • 期号:3
  • 页码:221-226
  • DOI:10.1016/j.ifacol.2016.07.037
  • 语种:English
  • 出版社:Elsevier
  • 摘要:Abstract:In this paper, a unique single zone combustion model is proposed to predict Diesel engine’s performance, pressure, and temperature based on the conservation of mass and energy. In order to simulate all phases of combustion, the proposed model takes in consideration the dynamics of the intake and exhaust gas through the valves, the ignition delay, the instantaneous change in gas properties, the properties of the burned fuel, and the heat losses by the walls. Validation of this model has been realized by experimental data. Important issue has been recognized that the physical model takes too much time in calculation. For this purpose, a Feed-Forward Neural Network (FFNN) model is developed and validated experimentally to predict the pressure and temperature in the cylinder in nominal and faulty operations. Finally, the influence of some possible faults that may be produced on the diesel engine cycle during the operation has been analyzed.
  • 关键词:KeywordsDiesel EngineThermodynamic cycleArtificial Neural Network ModelingFaulty operation mode
国家哲学社会科学文献中心版权所有