Response Surface Methodology-Based Multi-Objective Optimization for Biofuel-Powered Engine Response Map Development under the Steady-State Operating Conditions

<div>The twin challenges of the automotive industry namely petroleum dependence and environmental pollution paved way for the development of an environmentally friendly and feasible substitute for diesel, possessing power characteristics equivalent to those of a diesel engine. Biofuel has potential as a renewable energy source, offering a more sustainable alternative to traditional fossil fuels. However, it does come with some challenges, such as varying quality and combustion properties. To enhance its performance, engines can be fine-tuned by adjusting fuel injection parameters, such as timing, pressure, and duration. Accordingly, this research article focuses on optimizing the fuel injection parameters for a CRDi engine powered by D+LPO (20% lemon peel oil and 80% diesel) biofuel, with the goal of improving both performance and emission characteristics. The experimental design matrix was generated using Design Expert-13 software, employing the I-optimal technique. Utilizing response surface methodology, a higher-order regression relationship is formulated for engine output performance and emissions response. The engine response matrix is developed with higher-order fit model (R<sup>2</sup>) for the entire operating speed and torque operations under various fuel injection operating points. The results obtained as, for better BTE, D+LPO maintained a higher quantity of pilot mass than diesel, which is identified as 22–26% for D+LPO and 10–16% for diesel. The combustion quality of D+LPO was increased with homogeneity of the air–fuel mixture, which was improved by the advanced pilot injection. At lower speeds higher injection pressure and at higher speeds lower injection pressure is identified for diesel than D+LPO.</div>