Modeling and optimization of dual-fuel natural gas-DME combustion in an HCCI engine: a 3E analysis using NSGA-II

This study investigates, models, and optimizes the dual combustion of dimethyl ether (DME) and natural gas (NG) fuels in an HCCI engine. Recognized for high efficiency and low emissions, HCCI engines play a vital role in reducing environmental impact. DME and NG were selected for their eco-friendly properties and potential to enhance engine performance. Key performance variables engine speed, compression ratio, equivalence ratio, initial temperature, initial pressure, and NG molar percentage in the DME-NG mixture were analyzed and used as inputs for an accurate zero-dimensional computational model. These variables were optimized using the non-dominated sorting genetic algorithm II (NSGA-II) for multi-objective optimization and the genetic algorithm (GA) for single-objective optimization. The study minimized exergy efficiency, total emissions (HC, CO, CO₂), and work exergy cost. Multi-objective optimization yielded an optimal scenario with a 451.48 K initial temperature, 1501.3 rpm engine speed, 1 bar initial pressure, 0.13 NG molar percentage, 12.75 compression ratio, and 0.3 equivalence ratio, achieving a reverse exergy efficiency of 130.49 (1/η_ex), total emissions of 2.373e−04 kg, and a work exergy cost of 0.2715e−04 $ per engine cycle. Another scenario at 350 K, 1434.4 rpm, 1.19 bar, 0.333 NG molar percentage, 24.38 compression ratio, and 2.23 equivalence ratio resulted in a reverse exergy efficiency of 2.267, emissions of 0.0044 kg, and a work exergy cost of 6.1483e−04 $. Single-objective optimization revealed a reverse exergy efficiency of 2.2290, emissions of 3.6403e−24 kg, and a work exergy cost of 1.8578e−09 $. These findings highlight the critical role of optimal parameters in balancing environmental, economic, and exergy objectives for enhanced engine performance.