Title of article :
Multi-Objective Optimization of a RCCI Engine Fueled with Diesel Fuel and Natural Gas Enriched with Hydrogen
Author/Authors :
Mabadi Rahimi, Hadi Department of Mechanical Engineering - Islamic Azad UniversityAyatollah Amoli Branch, Amol, Iran , Jazayeri, Ali Department of Mechanical Engineering - K. N. Toosi University of Technology, Tehran, Iran , Ebrahimi, Mojtaba Department of Mechanical Engineering - Islamic Azad University Ayatollah Amoli Branch, Amol, Iran
Abstract :
The present study seeks to conduct the optimization of a heavy-duty diesel engine
under RCCI combustion fueled with diesel fuel and natural gas enriched with hydrogen. Since
NOx emission is one of the most important concerns of using hydrogen as a sole fuel or an
additive to hydrocarbon fuels in an internal combustion engine like RCCI engine, thus, the
main goals of this study are to overcome the NOx challenge, enhance the RCCI combustion
characteristics, and reduce the fuel consumption when the conventional hydrocarbon fuels are
substituted with hydrogen. In order to conduct the optimization process, an artificial neural
network coupled with the design of the experiment concept was employed to identify the RCCI
combustion mathematical model and provide the required population for two optimization
algorithms, namely genetic algorithm, and particle swarm optimization algorithm. The results
from the optimization process show that by advancing the diesel fuel injection along with the
appropriate amount of exhaust gas recirculation and nitrogen as diluents, the level of EURO
VI for NOx can be met. However, the losses in the RCCI engine output power is less than 5%
meanwhile the gross indicated efficiency is over 50% and the reduction in hydrocarbon fuels
consumption is about 40%.
Keywords :
RCCI combustion , Heavy-duty diesel engine , Hydrogen , Artificial neural network , optimization
Journal title :
Gas Processing Journal