Estimating the minimum ignition energy of spark-ignited fuel/air mixtures: preliminary steps towards a novel modelling approach

In spark-ignition (SI) engines, the achievement of a fast combustion with low cycle-to-cycle variation is highly dependent on the successful initiation of a flame kernel from the spark plug. Its growth can be sped up by increasing the electrical energy supply, but at the cost of higher plug wear, whereas too little energy may result in an ignition failure. Therefore, knowledge of the minimum ignition energy (MIE) of a fuel/air mixture is of key importance to guarantee a proper combustion process at minimal cost. To model the MIE several approaches have been proposed in literature, primarily derived from the experiments conducted by Lewis and Von Elbe and their resulting theory of quenching distances. However, these approaches appear in conflict with more recent experimental outcomes, and the impact of the ignition device is neglected. This work proposes a novel approach for modelling the MIE, which is based on a flame kernel expansion model recently proposed in another paper. In this approach, the proposed model, which has general validity, is specialized to the particular case of the estimation of the MIE, supplied via an electrical breakdown. A model advancement is also included that consists in the quantification, albeit at a preliminary level, of the impact of different gap distances and spark plug quenching effects on the flame kernel development. The results are validated against literature models and experimental data for two fuels, propane and hydrogen, and multiple equivalence ratios. In contrast with the noticeable MIE overestimation of literature models, for propane the proposed approach leads to better results compared to the experiments. Instead, for hydrogen a tendency towards a MIE underestimation is observed, especially for lean mixtures. The model is also tested for SI-engine-relevant conditions, showing satisfactory overall trends. The key source of error seems related to the very complex kernel-electrode interaction, the modelling of which will be improved in future developments.