Abstract Downsized gasoline engines equipped with a turbocharger (TC) and variable valve timing (VVT) can reach high levels of fuel efficiency. The determination of the optimum VVT position and spark timing using the conventional look-up tables, however, requires a significant calibration effort especially in vehicles capable of utilizing various gasoline-ethanol blends. Moreover, a factory calibration is necessary to be continuously updated or optimized to address component aging and environmental conditions. In this paper, an extremum seeking (ES) controller is designed to optimize and/or update VVT position and spark timing online at steady state conditions such as idle and cruise. In order to develop and tune the ES algorithm, a reduced-order model is developed to predict the effect of internal exhaust gas recirculation (iEGR) and combustion phasing (i.e. crank angle of 50% fuel burned), and the mean effective pressure (MEP) at various engine speeds and loads. The experimentally observed cycle-to-cycle variability is then emulated and statistical characteristics are superimposed in the deterministic model to predict the cycle-to-cycle combustion variation at different iEGR levels. The proposed model is then utilized to capture the effects of VVT and spark timing on combustion efficiency and predict the resulting net mean effective pressure (NMEP) and net specific fuel consumption (NSFC). An ES controller tuned based on this engine model demonstrates the convergence of both VVT and spark timing to the optimal values.
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