Optimization of SI engine responses fueled with hydrogen‐enriched <scp>G30</scp> fuel: Experimental and statistical approach

Abstract Conventional gasoline engines face challenges in achieving high thermal efficiency and low emissions due to the inherent thermodynamic and environmental constraints of fossil fuels. Blending gasoline with higher alcohols such as butanol enhances combustion and reduces emissions, but partial substitution often results in suboptimal performance. Hydrogen, with its superior combustion characteristics and carbon‐free nature, offers a promising route to overcome these limitations. In this study, a hydrogen‐enriched G30 blend (70% gasoline + 30% butanol) was tested in a spark‐ignition engine to optimize performance and emission characteristics by varying fuel composition, injection timing, and engine speed. Response surface methodology (RSM) was applied to develop second‐order regression models for brake thermal efficiency (BTE), specific fuel consumption (SFC), and emissions (CO, UHC, NOₓ). The models demonstrated strong predictive accuracy with R 2 values of 0.9681 (SFC), 0.9643 (BTE), 0.9410 (CO), 0.9994 (UHC), and 0.9997 (NOₓ). Multi‐response optimization identified optimal conditions at hydrogen enrichment (+1.00), injection timing (−1.00), and engine speed (−1.00), achieving an SFC of 0.2613 kg/kWh, BTE of 30.28%, CO of 0.0191%, UHC of 27.70 ppm, and NOₓ of 84.50 ppm with an overall desirability of 83%. Experimental validation confirmed close agreement between predicted and observed results. The findings highlight that hydrogen enrichment enhances combustion efficiency and reduces incomplete combustion products, while the oxygenated nature of butanol aids in moderating NOₓ formation. Thus, hydrogen‐enriched G30 blends optimized via RSM present a viable pathway toward cleaner and more efficient spark‐ignition engine operation.