Proposal and Validation of 3D-CFD Framework for Ultra-Lean Hydrogen Combustion in ICEs Universita di Modena e Reggio Emilia

Format:

Book

Conference/Event

Author/Creator:

Sfriso, Stefano, author.

Contributor:

Berni, Fabio

Breda, Sebastiano

Brequigny, Pierre

Fontanesi, Stefano

Foucher, F. (Fabrice)

Ramalho Leite, Caio

Conference Name:

WCX SAE World Congress Experience (2024-04-16 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2024

Summary:

In recent months, the increasing debate within the European Union to review the ban on internal combustion engines has led to the pursuit of environmentally neutral solutions for ICEs, as an attempt to promote greater economic and social sustainability. Interest in internal combustion engines remains strong to uphold the principle of technological neutrality. In this perspective, the present paper proposes a numerical methodology for 3D-CFD in-cylinder simulations of hydrogen-fueled internal combustion engines. The combustion modelling relies on G-equation formulation, along with Damköhler and Verhelst turbulent and laminar flame speeds, respectively. Numerical simulations are validated with in-cylinder pressure traces and images of chemiluminescent hydrogen flames captured through the piston of a single-cylinder optical spark-ignition engine. To mitigate the uncertainties related to the modeling of mixture stratification and injection, hydrogen is port-injected and continuously supplied into the intake pipe to ensure mixture homogeneity. Therefore, the main challenge in this study is represented by an accurate characterization of the combustion propagation, which is the key element in the validation of the computational framework. In this regard, a remarkable alignment between simulations and experiments is achieved in terms of pressure traces and flame imaging, evidencing the model's capabilities. The validation is carried out at different equivalence ratios, demonstrating the reliability of the numerical framework to consistently reproduce results without the need for case-by-case adjustments

Notes:

Vendor supplied data

Publisher Number:

2024-01-2685

Access Restriction:

Restricted for use by site license