Researchers in the Transport Technologies Division of Saudi Aramco have used using computational fluid dynamics (CFD) and advanced machine learning (ML) techniques to co-optimize the piston bowl and the injector design of a gasoline compression ignition (GCI) engine.
The optimum ML design provided similar performance at mid-load but a 3.8% – 4.5% reduction in fuel consumption compared to the baseline cases at low- and high-load conditions. A paper on their work is published in the journal Fuel.
The study was performed at low- (6 bar), mid- (11 bar) and high-load (22 bar) indicated mean effective pressure (IMEP) conditions.
The team first validated the 3D CFD setup against experimental data, then simultaneously co-optimized bowl and injector. They considered 10 piston-related and 3 injector-related design parameters.
For each of the three load conditions, they generated 128 design of experiments (DoE) cases, and then analyzed the features and performance of the top three designs. To select the best DoE solution, they used weighted merit values to provide one best design across all load conditions. The simulated dataset was used for further optimization using ML techniques.
A flatter design with low center height, wide and shallow bowl, and the low lip was preferable in the low- and high-loads.
At the low-load partially premixed compression ignition (PPCI) mode, spray targeting the upper lip and divided into the bowl and squish zones for enhanced mixing is preferred.
At the high-load mixing-controlled diffusion combustion mode, where injection occurs near the top dead center (TDC) and diffusion burn is the dominant combustion mode, targeting the lower lip is favorable.
At the mid-load with a high premixed ratio, the combustion was close to homogeneous charge compression ignition (HCCI), and the piston bowl design had limited effect.
Larger number nozzles with smaller diameters were favorable at low-load to control partially premixed charge. At high-load, larger and fewer number nozzles are recommended.
Jaeheon Sim, Balaji Mohan, Jihad Badra (2022) “Co-optimization of piston bowl and injector for light-duty GCI engine using CFD and ML,” Fuel, Volume 329, doi: 10.1016/j.fuel.2022.125455
Posted on 08 August 2022 in Emissions, Engines, Fuel Efficiency, Fuels | Permalink | Comments (0)
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