Optimization of performance and emission characteristics of a diesel engine fueled with MgCO3 nanoparticle doped second generation biodiesel from jojoba by using response surface methodology (RSM)

Abstract

As the availability of diesel fuel, derived from finite fossil resources, depletes and its combustion releases harmful emissions, the search for alternative fuels becomes increasingly critical. One of the most influential alternative fuels is biodiesel. In this study, the biodiesel was produced from jojoba, a second-generation plant that humans do not consume as food. Then, MgCO₃ nanoparticles were added to this biodiesel, and the performance and emission experiments were carried out in a single-cylinder diesel engine. The engine was tested at six different loads (0.5, 1, 1.5, 2, 2.5, and 3 kW) and with the addition of nanoparticles (50, 100 and 150 ppm). Finally, the experimental data were optimized using Response Surface Methodology (RSM). Engine loads and fuel compositions were determined as input parameters. Carbon dioxide (CO₂), nitrogen oxides (NO_x), hydrocarbons (HC), carbon monoxide (CO), brake thermal efficiency (BTE), and brake specific fuel consumption (BSFC) were determined as output parameters. RSM optimization seeks to find the optimal operating point that minimizes emissions and BSFC while maximizing BTE. In the RSM results, the R² value was calculated as a minimum of 95.95 % and a maximum of 99.42 %. The error rate in all parameters increased below 10 %. The highest error was in the HC value, which was 7.25 %. As a result of the optimization, the optimum value was reached under 74.20 ppm and 1.4 kW load. In these values, BTE, BSFC, NO_x, CO₂, HC, and CO values were calculated as 23.67 %, 376.27 g/kWh, 393.83 ppm, 4.28 %, 7.63 ppm, and 0.038 %, respectively.