Exploring the Future of Sustainable Fuels: Experimental and Predictive Insights on Engine Performance and Emissions Using Algae Biodiesel Blends

This study investigates the potential of biodiesel derived from Azolla algae as an alternative fuel for conventional diesel. The performance and emissions characteristics of various biodiesel blends were evaluated experimentally. The physicochemical properties of pure diesel (D100), and blends with Azolla biodiesel at 5% (BD5), 10% (BD10), 15% (BD15), 20% (BD20), and 100% (B100) were analyzed. It is observed that the amount of fuel consumed is higher at higher loads when fuel is blended with biodiesels. Hydrocarbon emissions were reduced with biodiesel blends at full load and the reduction is higher with increase in blend concentration. A significant difference of 85 ppm NO_x was observed between BD20 and D100 at full load. CO emissions decreased with higher biodiesel concentrations, with BD20 resulted less CO emissions than D100, making BD20 a more environmentally viable fuel. Artificial neural networks (ANN) were employed for predictive modeling, achieving approximately 95% accuracy. Pearson’s correlation coefficients (0.9770 to 1.000) and root mean square errors (0.01048 to 0.0804) for all the output parameters indicate the model’s high efficiency and accuracy, closely matching experimental values.