Optimization of ignition timing and compression ratio for enhanced performance, emission, and vibration control in a biogas–gasoline dual–fuel VCR SI engine

ABSTRACT The increasing demand for sustainable energy has accelerated the adoption of renewable fuels in spark-ignition engines. This study examines the performance, emissions, combustion, and vibration behaviour of a variable-compression-ratio spark-ignition engine fueled with food-waste-derived biogas–gasoline blends. Experiments were performed at 1800 rpm under wide-open-throttle conditions by varying the compression ratio (8–10), ignition timing (24–30° bTDC), and biogas fraction (0–20%). Response Surface Methodology (RSM) and Artificial Neural Network (ANN) models were employed for prediction and optimization. Moderate biogas enrichment enhanced combustion efficiency, reducing CO and HC emissions from 0.95% to 0.64% vol and from 125 to 85 ppm, respectively. Increasing the biogas fraction lowered NOx emissions by up to 40% through CO₂ dilution, whereas advanced ignition timing and higher compression ratios promoted NOx formation due to elevated in-cylinder temperatures. Vibration acceleration increased under highly advanced ignition settings owing to rapid pressure rise and stronger combustion-induced excitation. Optimization revealed an optimal combination of a compression ratio of 8.5, an ignition timing of 29.5° bTDC, and a biogas fraction of 7.5%, delivering a brake power of 5.70 kW, a brake thermal efficiency of 23.71%, and a brake-specific fuel consumption of 0.370 kg/kWh while maintaining low vibration levels. The results highlight that superior engine performance is achieved through a balanced compromise among energy conversion efficiency, emissions reduction, and vibration control, rather than by increasing the compression ratio or the biogas fraction alone. ANN predictions closely matched experimental measurements, with errors below 6.85%, confirming the robustness of the developed model.