Modeling of combustion phasing of a reactivity-controlled compression ignition engine for control applications

Reactivity-controlled compression ignition (RCCI) is a promising combustion strategy to achieve near-zero NOx and soot emissions and diesel-like efficiencies. Model-based control of RCCI combustion phasing requires a computationally efficient combustion model that encompasses factors such as injection timings, fuel blend composition, and reactivity. In this work, physics-based models are developed to predict the onset of auto-ignition in RCCI and to estimate the burn duration based on an approximation of the spontaneous ignition front speed. A mean value control-oriented model of RCCI is then developed by combining the auto-ignition model, the burn duration model, and a Wiebe function to predict combustion phasing. The control-oriented model is parameterized and validated using simulation data from an experimentally validated, detailed computational fluid dynamics combustion model developed using the KIVA-3V code. The validation results show that the control-oriented model can predict the start of combustion, burn duration, and crank angle of 50% burnt fuel with an average error of less than 2 crank angle degrees. Thus, the control-oriented model demonstrates sufficient accuracy in predicting RCCI combustion phasing for control applications. The control-oriented model is an integral part of designing a model-based controller, which in the case of RCCI is of paramount importance due to various attributes concerning combustion, particularly for transient engine operation.

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