Development of an Oxy-Fuel Combustion System in a Compression-Ignition Engine for Ultra-Low Emissions Powerplants Using CFD and Evolutionary Algorithms

Abstract

This study uses an optimization approach for developing a combustion system in a compression–ignition engine that is able to operate under oxy-fuel conditions, and produces mainly CO2 and H2O as exhaust gases. This is achieved because the combustion concept uses pure oxygen as an oxidizer, instead of air, avoiding the presence of nitrogen. The O2 for the combustion system can be obtained by using a mixed ionic–electronic conducting membrane (MIEC), which separates the oxygen from the air onboard. The optimization method employed maximizes the energy conversion of the system, reducing pollutant emissions (CxHy, particulate matter, and carbon monoxides) to levels near zero. The methodology follows a novel approach that couples computational fluid dynamics (CFD) and particle swarm optimization (PSO) algorithms to optimize the complete combustion system in terms of engine performance and pollutant generation. The study involves the evaluation of several inputs that govern the combustion system design in order to fulfill the thermo-mechanical constraints. The parameters analyzed are the piston bowl geometry, fuel injector characteristics, air motion, and engine settings variables. Results evince the relevance of the optimization procedure, achieving very low levels of gaseous pollutants (CxHy and CO) in the optimum configuration. The emissions of CO were reduced by more than 10% while maintaining the maximum in-cylinder pressure within the limit imposed for the engine. However, indicated efficiency levels are compromised if they are compared with an equivalent condition operating under conventional diesel combustion.

Combustion Modeling Approach for the Optimization of a Temperature Controlled Reactivity Compression Ignition Engine Fueled with Iso-Octane

“…The grid size was selected after a preliminary mesh independence analysis based on the previous experience of the authors [5,6]. The domain has around 65,160 cells at TDC position [24,25]. The bottom image shows the automatic mesh generated to perform the optimization process in order to reduce the time required for each simulation.…”