Computational optimization of fuel supply, syngas composition, and intake conditions for a syngas/diesel RCCI engine

Research output: Contribution to journalArticle


By utilizing the promising alternative fuel of syngas, and the syngas/diesel dual-fuel reactivity controlled compression ignition (RCCI) is a potential combustion strategy for internal combustion engines. However, the optimal operating parameters for syngas/diesel RCCI engines under wide operating conditions have not been investigated. In this study, the operating parameters include fuel supply, syngas composition, and intake conditions of a syngas/diesel RCCI engine were optimized under wide load by integrating the KIVA-3V code and the non-dominated sort genetic algorithm II (NSGA-II). The results indicated that nitrogen oxides (NOx) emissions can be controlled in considerably low levels, and the efficient combustion of the premixed syngas in the squish region can be realized with high premix ratio and early pilot injection of diesel. Equivalent indicated specific fuel consumption (EISFC) and ringing intensity (RI) are the major issues for the optimization at low and mid load, respectively. The double diesel injection strategy with the relatively late main injection timing is an effective way to both improve combustion efficiency at the low load and reduce RI at the mid load. For the double diesel injection, the ratio of pilot injection is controlled in a narrow range to provide sufficient high reactivity fuel in the piston bowl and to avoid the local high-temperature combustion region simultaneously. With the restrictions of EISFC and RI, the optimal H2 fraction in the syngas is 60–80%. Based on the optimal fuel supply and intake conditions, a syngas with 75% H2 and the diluent factor C of 0.8 is capable of realizing the high efficiency, moderate combustion, and low emissions for the RCCI engine at full load range.


  • Zhen Xu
  • Ming Jia
  • Yaopeng Li
  • Yachao Chang
  • Guangfu Xu
  • Leilei Xu
  • Xingcai Lu
External organisations
  • Dalian University of Technology
  • Shanghai Jiao Tong University
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Energy Engineering


  • Fuel supply, Genetic algorithm, Intake conditions, Reactivity controlled compression ignition (RCCI), Syngas composition, Syngas/diesel dual fuel
Original languageEnglish
Pages (from-to)120-134
Number of pages15
Publication statusPublished - 2018 Dec 15
Publication categoryResearch