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CFD-Guided Combustion System Optimization of a Gasoline Range Fuel in a Heavy-Duty Compression Ignition Engine Using Automatic Piston Geometry Generation and a Supercomputer
- Yuanjiang Pei - Aramco Research Center - Detroit ,
- Pinaki Pal - Argonne National Laboratory ,
- Yu Zhang - Aramco Research Center - Detroit ,
- Michael Traver - Aramco Research Center - Detroit ,
- David Cleary - Aramco Research Center - Detroit ,
- Carsten Futterer - Friendship Systems ,
- Mattia Brenner - Friendship Systems ,
- Daniel Probst - Convergent Science Inc. ,
- Sibendu Som - Argonne National Laboratory
ISSN: 2641-9637, e-ISSN: 2641-9645
Published January 15, 2019 by SAE International in United States
Citation: Pei, Y., Pal, P., Zhang, Y., Traver, M. et al., "CFD-Guided Combustion System Optimization of a Gasoline Range Fuel in a Heavy-Duty Compression Ignition Engine Using Automatic Piston Geometry Generation and a Supercomputer," SAE Int. J. Adv. & Curr. Prac. in Mobility 1(1):166-179, 2019, https://doi.org/10.4271/2019-01-0001.
A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty diesel engine running with a gasoline fuel that has a research octane number (RON) of 80. The goal was to optimize the gasoline compression ignition (GCI) combustion recipe (piston bowl geometry, injector spray pattern, in-cylinder swirl motion, and thermal boundary conditions) for improved fuel efficiency while maintaining engine-out NOx within a 1-1.5 g/kW-hr window. The numerical model was developed using the multi-dimensional CFD software CONVERGE. A two-stage design of experiments (DoE) approach was employed with the first stage focusing on the piston bowl shape optimization and the second addressing refinement of the combustion recipe. For optimizing the piston bowl geometry, a software tool, CAESES, was utilized to automatically perturb key bowl design parameters. This led to the generation of 256 combustion chamber designs evaluated at several engine operating conditions. The second DoE campaign was conducted to optimize injector spray patterns, fuel injection strategies and in-cylinder swirl motion for the best performing piston bowl designs from the first DoE campaign. This comprehensive optimization study was performed on a supercomputer, Mira, to accelerate the development of an optimized fuel-efficiency focused design. Compared to the production combustion system in the baseline engine, the new combustion recipe from this study showed significantly improved closed-cycle fuel efficiency across key engine operating points while meeting the engine-out NOx targets. Optimized piston bowl designs and injector spray patterns were predicted to provide enhanced in-cylinder air utilization and more rapid mixing-controlled combustion, thereby leading to a fuel efficiency improvement. In addition, shifting the engine thermal boundary conditions toward leaner operation was also key to the improved fuel efficiency.