Six Stroke Engine Optimization For Mid To High Loads Using Genetic Algorithm

The development of new internal combustion (IC) engine technologies is essential as the automotive industry moves towards hybrid powertrains. Six-stroke (6S) gasoline compression ignition (GCI) engine is one such promising technology. It has the potential to improve performance and reduce emissions by introducing an additional power stroke (PS2) after the first power stroke (PS1). The aim of this study was to determine the optimal injection parameters for 6S GCI operation with one injection event in each power stroke. Parameters included the start of first (SOI1) and second injection (SOI2), and the fuel split ratio (SR) between PS1 and PS2. The study focused on mid (12, 15 bar) to high (18, 21 bar) engine loads, relevant for hybrid powertrains. Genetic algorithm technique was employed to optimize thermal efficiency while adhering to constraints on soot, NOx, maximum pressure rise rate (MPRR), and peak cylinder pressure (PCP). For 12 bar load, delaying the SOI1 timing to -4 CA ATDC led to PS1 misfire and kinetically-mixing controlled (K-MCM) combustion in PS2, minimizing overall heat loss thus giving the highest efficiency. SR of 60% was found to be optimal, constrained by MPRR. At 15 bar, there was close competition between PS2 kinetically-mixing controlled mode (K-MCM) ignition only and a combined PS1 KCM + PS2 MCM combustion mode. For higher loads of 18 and 21 bar, both power strokes needed ignition to meet the constraints, with KCM in PS1 and MCM in PS2 proving to be the most effective strategy. As the load increased from 15 to 21 bar, the SR had to be reduced to comply with MPRR constraints. The SOI2 timing was adjusted to balance thermal efficiency with NOx and MPRR limits.