Control-Oriented Statistical Model of In-Cylinder Pressure, Combustion Phasing, and Torque for Compression-Ignition Engines Operating with Low Cetane Fuels

<div class="section abstract"><div class="htmlview paragraph">Sustainable aviation fuels are becoming more widely available for current and future engine powered propulsion systems. However, the diversity of ignition behavior in these fuels poses a challenge to achieving robust, efficient operation. Specifically, low cetane fuels with poor ignitability exhibit highly variable torque production unless fuel is injected earlier during compression. The tradeoff is that earlier injection may cause dangerously high in-cylinder pressure rise rates. Novel models that can simulate these competing behaviors are needed so that appropriate strategies may be developed for controlling combustion at low cetane fueling conditions. This work builds upon a previously developed model that simulates asymmetric combustion phasing (CA50) distributions as a function of fuel cetane, fuel injection timing, and electrical power supplied to an in-cylinder thermal ignition assist device. An extension of the model is presented in which the phasing output is used to reconstruct in-cylinder pressure traces, by which indicated mean effective pressure (IMEP) can then be simulated. Additionally, a functional form is parametrized for modeling maximum in-cylinder pressure rise rate (MPRR). The model’s parameters are regressed using a total 121,237 engine cycles of experimental data from a commercial CI engine operating with four fuel blends with cetane number ranging from 25 to 48. Relative to the data, the model simulates mean CA50 within a root mean square error (RMSE) of approximately 3 CAD over a range of 64 CAD, mean IMEP within an RMSE of 0.85 bar over a range of 5.8 bar, and mean MPRR within an RMSE of 6.1 bar/CAD over a range of 88 bar/CAD. Along with the mean-value trends, it accurately emulates the variability of all three combustion metrics. Ultimately, this work marks the first time a low-order, control-oriented model simulates statistical distributions of CA50, IMEP, and MPRR.</div></div>