This study investigates the influence of fuel injection pressure and timing on the performance, combustion, and emission characteristics of a single-cylinder, 1500 rpm common rail direct injection (CRDI) diesel engine fueled with a diesel–biodiesel blend containing 20% palm kernel methyl ester and 80% diesel, enriched with hydrogen at a flow rate of 10 LPM (PKME20H10). The objective is to enhance engine efficiency and emission control through a green hydrogen–biodiesel strategy. Artificial Neural Network (ANN) models were developed to predict engine responses, and optimization was achieved using the hybrid NonDominated Sorting Genetic Algorithm II (NSGA-II) coupled with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Experimental and computational analyses revealed that the optimal combination of an injection timing of 25 before top dead center (BTDC) and an injection pressure of 512 bar achieved a brake thermal efficiency (BTE) of 30.1%, a brake specific fuel consumption (BSFC) of 0.123 kg/kWh, and substantial reductions in emissions. Carbon monoxide emissions decreased by 10%, unburnt hydrocarbon emissions decreased by 45%, and smoke opacity decreased by 17%. The study demonstrates that hydrogen enrichment in biodiesel improves combustion quality and engine sustainability, offering a viable pathway for low-carbon automotive energy systems.
P. Ajay Goud (Thu,) studied this question.