Numerical modeling of lean hydrogen spark-ignition engines: On the role of intrinsic instabilities

Hydrogen-fueled internal combustion engines (H 2 -ICEs) hold strong potential as a pathway toward CO 2 -neutral propulsion. To reduce emissions, H 2 -ICEs are usually operated under fuel-lean conditions, where the flames are prone to thermo-diffusive instabilities (TDIs). These TDIs govern both local and global flame propagation, but their impact on full-scale engine combustion remains an open question. In this study, high-fidelity three-dimensional large-eddy simulations (LES) are performed at multiple mesh resolutions, with the finest grid sufficiently resolved to directly characterize flame front dynamics relevant to engine-scale combustion. The simulations reveal cellular and finger-like flame structures characteristic of TDIs throughout the entire combustion process. Analysis of the local thermo-chemical state demonstrates that differential diffusion induces pronounced mixture stratification and elevates reaction rates, resulting in super-adiabatic temperatures that strongly correlate with flame curvature. Building on these findings, the performance of the baseline artificially thickened flame (ATF) model and a recently developed thermo-diffusive (TD)-aware extension is assessed. Unlike the state-of-the-art ATF model, which suffers from grid dependence and underestimates the experimental pressure trace, the TD-aware formulation captures experimental trends more accurately and provides consistent, grid-independent integrated heat-release (IHR) traces. For the operating condition considered here, the results show that TD effects represent sub-grid-scale contributions that need to be accounted for to obtain consistent predictions of global combustion behavior under the investigated lean H 2 -ICE conditions. • LES captured cellular and finger-like thermo-diffusive flame structures. • Coarser grids suppressed fine-scale instabilities resolved at high resolution. • Local mixture stratification enhanced reactivity and caused super-adiabatic states. • ATF model showed grid bias from missing thermo-diffusive instability treatment. • Thermo-diffusive-aware ATF model reduced grid bias and improved predictive accuracy.