SI and RCCI Quasi-Dimensional Combustion Modeling of Ammonia-Fueled Engines with Fuel-NOx Formation

The increasing interest in carbon-free fuels has positioned ammonia as a promising energy carrier for Internal Combustion Engines (ICEs), particularly in hard-to-abate sectors such as Heavy-Duty (HD) transport and maritime applications. However, its low reactivity, narrow flammability limits, and intrinsic nitrogen content pose significant challenges for stable combustion and emissions control. This work presents a predictive Quasi-Dimensional (QD) combustion model applied to simulate ammonia-fueled engines operating under both Spark Ignition (SI) and Reactivity Controlled Compression Ignition (RCCI) modes. The proposed framework couples a turbulent premixed combustion sub-model with a diffusive combustion sub-model, including a dedicated fuel-NOx mechanism to capture nitrogen oxide formation pathways associated with fuel-bound nitrogen. The model accounts for key physical and chemical processes governing combustion, such as ignition delay, mixture stratification, and heat release dynamics, while maintaining computational efficiency suitable for parametric studies. The model is validated against experimental data from a Single-Cylinder Engine (SCE) over a wide range of operating conditions, including variations in equivalence ratio, spark timing, Ammonia Energy Fraction (AEF), and injection strategy. Results demonstrate good agreement in terms of in-cylinder pressure evolution, Apparent Heat Release Rate (AHRR), and NOx emissions, with peak-pressure errors below 4 bar and peak-pressure locations predicted within 2 crank angle degrees. Notably, the dedicated fuel-NOx sub-model substantially improves emission predictions, revealing that fuel-bound nitrogen is the dominant source of NOx in ammonia combustion. Overall, the proposed QD model represents a robust and efficient tool for the analysis and optimization of ammonia-fueled engines, supporting the development of low-carbon combustion strategies for future energy systems.