Multi-objective optimization of combustion, performance, and emission characteristics of diesel–MTBE–SiO2 fuel blends in a single-cylinder diesel engine using response surface methodology

The growing need for cleaner and more efficient diesel engine operation has increased interest in oxygenated fuel additives and nanoparticle-based fuel strategies. This study experimentally investigated the effects of methyl tert -butyl ether (MTBE) and silicon dioxide (SiO 2 ) addition on the combustion, performance, and emission characteristics of a single-cylinder compression-ignition diesel engine using response surface methodology (RSM). The experiments were conducted at 1800 rpm, considering engine load (8.24–24.72 Nm), MTBE ratio (5–15 vol%), and SiO 2 concentration (50–150 ppm) as input variables. A face-centered central composite design (CCD) comprising 18 experimental runs was employed, and second-order regression models were developed for the investigated responses. Model adequacy was assessed using analysis of variance (ANOVA) and related statistical criteria. The results showed that engine load was the dominant factor influencing the investigated responses, particularly the performance and emission characteristics. Increasing engine load increased indicated mean effective pressure (IMEP) and indicated thermal efficiency (ITE) while decreasing brake-specific fuel consumption (BSFC), but resulted in higher nitrogen oxides (NO x ) emissions. Moderate MTBE concentrations of approximately 9–11 vol% and SiO 2 concentrations of approximately 90–110 ppm were associated with favorable performance responses. Multi-objective optimization identified 24.72 Nm engine load, 7.84 vol% MTBE, and 150 ppm SiO 2 as the global optimum within the investigated experimental domain, with an overall desirability of 0.570. This condition represents a compromise among the conflicting combustion, performance, and emission objectives rather than the individually optimum condition for each response. Experimental validation under the optimized condition showed good agreement with the RSM predictions, with an average deviation of 4.71%. The findings indicate that MTBE–SiO 2 blending can provide a favorable balance among the investigated engine responses under the tested operating conditions; however, the results are limited to the specified engine, operating speed, and fuel composition ranges.