Abstract

Effective abatement of harmful tail-pipe emissions from fossil fuel run engines is achieved through low-temperature combustion strategies; the reactivity controlled compression ignition (RCCI) mode of operation has been successful among such concepts. The present work deals with numerical work performed using ansys forte software with n-heptane as a high-reactivity fuel and hydrogen in different proportions as a low-reactivity fuel, respectively. With total energy fixed, the amount of hydrogen is varied from 0% to 80% fuel injection is regulated accordingly. Pertinent engine in-cylinder parameters with patterns are extracted, emphasizing the combustion phenomena of RCCI operation with the lowest possible emissions targeted, with the combined effects of hydrogen induction, start of injection, and split injections. The contours of fuel vapor and emission parameters are obtained to relate the performance with emissions. It is noted that with a split injection strategy at 50/50 and 75/25 split strategy and 45–50% energy share from hydrogen, the NOx, soot reductions, and thermal efficiency penalty are in the range of about 5.5%, 24%, and 7.5%, respectively, also, with 30% exhaust gas recirculation (EGR), about 95% NOx reduction but with higher soot values. A 75/25 split and advanced injection timing of 25 deg bTDC resulted in the RCCI mode of operation with reduced soot emissions, and the use of EGR has resulted in high levels of soot and poor fuel efficiency. Among the models of machine learning tested, random forest regressor emerged as the most suitable, with higher R2 values, indicating better predictive capability.

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