Multivariable optimization of spark ignition engine performance and emissions using tamanu based biofuel blends under variable operating conditions

This work reports a systematic engineering investigation into the coupled effects of tamanu-based biofuel blend fraction (TPBB), engine speed, and compression ratio on the performance and exhaust emissions of a spark-ignition engine, employing a response surface methodology–Face Centered Central Composite Design (RSM–FCCD) framework. The Tamanu Oil Fraction was varied from 2% to 10% (v/v) while maintaining constant levels of oxygenated additives, and experiments were conducted across an engine speed range of 4000–9000 rpm at compression ratios of 9.5, 10, and 11. Key engine responses including power, specific fuel consumption, thermal efficiency (TE), and emissions of CO, HC, and NOx were experimentally measured and statistically modeled. The results demonstrate that engine speed and Tamanu Blend dominate performance behavior, whereas compression ratio critically governs TE and NOx formation through nonlinear interaction effects. The developed quadratic models exhibit strong predictive accuracy, with coefficients of determination (R² = 0.9390–0.9943) and statistically insignificant lack-of-fit, confirming model robustness. Experimental–predicted agreement further validates the reliability of the proposed framework. The main contribution of this study lies in delivering a statistically validated multivariable optimization strategy for tamanu-based fuel application, providing actionable engineering insight into balancing performance and emission trade-offs. The findings support the practical integration of renewable biofuels into SI engine systems and offer a scalable methodology applicable to broader engine optimization problems.