Autoignition model optimized based on simple artificial brain

Ken Naitoh, Tairo Ise*


研究成果: Conference article査読


A well-known auto-ignition model for gasoline, which was proposed by Halstead et al, is automatically optimized on computers by using a simple artificial brain including genetic algorithm as learning theory and an intuition model. Arbitrary constants inside the mathematical equations of highly-nonlinear chemical reaction processes can be fitted by using the experimental time-evolutions of several components. Thus, ignition delay, the interval from compression start to ignition occurrence, can be accurately calculated for different types of fuel, production regions, and engine test benches. The intuition model clarifies whether the arbitrary constants are optimized or not. The present approach will be important for building up several types of virtual engines, which are based on zero-dimensional thermodynamic models, ensemble-averaged flow simulators, and large eddy simulation (LES).

ジャーナルSAE Technical Papers
出版ステータスPublished - 2003 1月 1
イベントPowertrain and Fluid Systems Conference and Exhibition - Pittsburgh, PA, United States
継続期間: 2003 10月 272003 10月 30

ASJC Scopus subject areas

  • 自動車工学
  • 安全性、リスク、信頼性、品質管理
  • 汚染
  • 産業および生産工学


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