Exploring the Exhaust Emission and Efficiency of Algal Biodiesel Powered Compression Ignition Engine: Application of Box–Behnken and Desirability Based Multi-Objective Response Surface Methodology

Sustainable Development Goals were established by the United Nations General Assembly to ensure that everyone has access clean, affordable, and sustainable energy. Third-generation biodiesel derived from algae sources can be a feasible option in tackling climate change caused fossil fuels as it no impact on human food supply chain. In this paper, combustion emission characteristics of Azolla Pinnata oil biodiesel-diesel blends are investigated. The multi-objective response surface methodology (MORSM) with Box–Behnken design is employed decrease number trials conserve finite resources terms labor, time, cost. MORSM was used study investigate interaction, model prediction, optimization operating parameters biodiesel-powered diesel engines obtain best performance least emission. For engine output prognostic developed. Engine optimized using desirability technique, efficiency lowest criteria. results show Theil’s uncertainty for model’s predictive capability (Theil’s U2) between 0.0449 0.1804. Nash–Sutcliffe validated excellent 0.965 0.9988, whilst mean absolute percentage deviation less than 4.4%. conditions achieved 81.2% load, 17.5 compression ratio, 10% blending ratio. proposed MORSM-based technique’s dependability robustness validate experimental methods.