Numerical Modeling of Hydrogen Combustion Using Preferential Species Diffusion, Detailed Chemistry and Adaptive Mesh Refinement in Internal Combustion Engines

Mitigating human-made climate change means cutting greenhouse gas (GHG) emissions, especially carbon dioxide (CO₂), which causes climate change. One approach to achieving this is to move to a carbon-free economy where carbon emissions are offset by carbon removal or sequestration. Transportation is a significant contributor to CO₂ emissions, so finding renewable alternatives to fossil fuels is crucial. Green hydrogen-fueled engines can reduce the carbon footprint of transportation and help achieve a carbon-free economy. However, hydrogen combustion is challenging in an internal combustion engine due to flame instabilities, pre-ignition, and backfire. Numerical modeling of hydrogen combustion is necessary to optimize engine performance and reduce emissions. In this work, a numerical methodology is proposed to model lean hydrogen combustion in a turbocharged port fuel injection (PFI) spark-ignition (SI) engine for automotive applications. The numerical method is based on 3D Computational Fluid Dynamics (CFD) simulations where Hydrogen injection is modeled using a mass flow boundary condition in the intake port, preferential species diffusion is used to model fuel-air mixing, and a 12 species, 37 reactions reduced chemical kinetics mechanism is used to model combustion with a detailed chemistry solver. Results shows good validation against measured multiple cycle cylinder pressure data for several operating conditions including varying load and equivalence ratios. The conventional methodology to simulate multiple engine cycles consecutively can be time consuming, hence, this paper evaluates the concurrent perturbation method which allows for simulating multiple cycles simultaneously in significantly less wall clock time.