Combustion system optimization for the integration of e-fuels (Oxymethylene Ether) in compression ignition engines

• CFD-guided optimization of an engine combustion system using Oxymethylene Ether. Obtention a configuration adapted to OME properties. Optimized maximized efficiency and decreased NOx for the low-sooting fuel. A neural network model was trained from obtained data sensitivity analysis. In this study, numerical methodology chamber in compression ignited engines as fuel is presented. The objective obtain dedicated that fueled with alternative improving reducing emissions NO x . This article proposes integration between algorithm CFD codes evaluate behavior fuelled low sooting OME. Based on diesel validated against experimental data, further implemented evaluating performance engine. particle swarm (PSO) modified based Novelty Search concepts used algorithm. Several tools are coupled order create each case where all routine automates entire process. result optimized provides increase (about 2.2%) reduction (35.7%) comparison baseline conventional addition, neuronal results simulations performed during process, studying influence parameter efficiency. From analysis it concluded EGR rate injection pressure affects range variability 63% 38% respectively.