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Fuel reforming during a Negative Valve Overlap (NVO) period is an effective approach to control Low Temperature Gasoline Combustion (LTGC) ignition. Previous work has shown through experiments that primary reference fuels reform easily and produce several species that drastically affect ignition characteristics. However, our previous research has been unable to accurately predict measured reformate composition at the end of the NVO period using simple single-zone models. In this work, we use a stochastic reactor model (SRM) closed cycle engine simulation to predict reformate composition accounting for in-cylinder temperature and mixture stratification. The SRM model is less computationally intensive than CFD simulations while still allowing the use of large chemical mechanisms to predict intermediate species formation rates.

While spark-ignition (SI) engine technology is aggressively moving towards challenging (dilute and boosted) combustion regimes, advanced ignition technologies generating non-equilibrium types of plasma are being considered by the automotive industry as a potential replacement for the conventional spark-plug technology. However, there are currently no models that can describe the low-temperature plasma (LTP) ignition process in computational fluid dynamics (CFD) codes that are typically used in the multi-dimensional engine modeling community. A key question for the engine modelers that are trying to describe the non-equilibrium ignition physics concerns the plasma characteristics. A key challenge is also represented by the plasma formation timescale (nanoseconds) that can hardly be resolved within a full engine cycle simulation.