Modeling and Experimental Study on Spark-Ignition Engine Using Hydrogen–Methane–Blended Fuel

A combustion model of a hydrogen–methane–blended fuel for internal combustion engines is developed and validated. Mixed fuels include hydrogen–methane, octane–methanol, and octane–ethanol blends. To address the complex dependencies of laminar flame speed of hydrogen–methane–blended fuel on temperature, pressure, equivalence ratio, and exhaust gas recirculation (EGR) ratio, a machine learning–based model was constructed. Gaussian process interpolation and polynomial extrapolation were employed to create a comprehensive laminar flame speed map. Additionally, two flame-quenching models, wall quenching and turbulent flame stretching, were introduced to predict unburned hydrocarbons. NOx emissions were estimated using the extended Zel’dovich mechanism. The accuracy of these models was verified by comparing numerical simulations with experimental data from single-cylinder engine experiments. Results showed strong agreement for cylinder pressure, heat release rates, and emissions across various hydrogen ratios and engine operating conditions. Across all investigated cases, the model reproduced combustion duration (CA10–90) within ±2.2°CA, with an error ≤11%. Notably, the machine learning–based laminar flame speed model demonstrated high accuracy, even at elevated temperatures and pressures, without requiring additional parameter tuning for turbulence flame model. This study highlights the highly accurate modeling techniques for simulating the combustion of renewable hydrogen–methane blends. The results in this study will contribute to the development of more efficient, lower emission internal combustion engines, and support the transition to sustainable vehicle technology.