The present research employs an experimental–computational study for investigating the performance, combustion and emission characteristics of a single-cylinder compression ignition engine fuelled with conventional diesel and Mahua biodiesel–diesel blends doped with TiO₂–CeO₂ hybrid nanoparticles. A comprehensive engine test campaign was conducted at a variety of loads, and critical parameters such as brake thermal efficiency (BTE), brake specific fuel consumption (BSFC), and exhaust emissions (Carbon Monoxide (CO), Hydrocarbon (HC), Oxides of nitrogen (NOₓ), smoke, and Carbon di-oxide (CO₂) were carefully analysed over the entire engine operating range. They also examined the combustion of gasoline in the engine. Compared to the normal diesel, Mahua biodiesel blended with nanoparticles revealed a significant enhancement in brake thermal efficiency of 6–8% for the blends. There was also up to a 7% reduction in brake-specific fuel consumption at higher loads. Emission reductions were substantial, with CO, HC, and smoke opacity reduced by 25–30%, 20–25%, and 35–40%, respectively. The cylinders, being hotter, did however lead to a moderate increase in NOₓ emissions (by 8–12%) because they accelerated oxidation processes. In addition to the experimental study, we developed machine learning-based predictive models to predict engine outputs. The XGBoost model performed better than others. R² values obtained through Leave-One-Out Cross-Validation (LOOCV) were very high: 0.993 for BTE, 0.996 for BSFC and > 0.97 for all emission parameters. Both RMSE and MAE were very low for the model. The analysis of residuals and sensitivity demonstrated strong generalisability and a consistent effect of physical traits. The elaborate experimental and machine learning framework demonstrated the potential of Titanium Dioxide Nanoparticles (TiO₂)–Cerium Oxide Nanoparticles (CeO₂) nanoparticle-enhanced Mahua biodiesel towards a viable alternative fuel that may enable a cleaner and more efficient operation of compression ignition engines.
Janaki et al. (Thu,) studied this question.