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A dual-fuel approach to control combustion in HCCI engine is investigated in this work. This approach involves controlling the combustion heat release rate by adjusting fuel reactivity according to the conditions inside the cylinder. Experiments were performed on a single-cylinder research engine fueled with different ratios of primary reference fuels and operated at different speed and load conditions, and results from these experiments showed a clear potential for the approach to expand the HCCI engine operation window. Such potential is further demonstrated dynamically using an optimized stochastic reactor model integrated within a MATLAB code that simulates HCCI multi-cycle operation and closed-loop control of fuel ratio. The model, which utilizes a reduced PRF mechanism, was optimized using a multi-objective genetic algorithm and then compared to a wide range of engine data.

A multi-objective optimization scheme based on stochastic global search is developed and used to examine the performance of an HCCI model containing a reduced chemical kinetic mechanism, and to study interrelations among different model responses. A stochastic reactor model of an HCCI engine is used in this study, and dedicated HCCI engine experiments are performed to provide reference for the optimization. The results revealed conflicting trends among objectives normally used in mechanism optimization, such as ignition delay and engine cylinder pressure history, indicating that a single best combination of optimization variables for these objectives did not exist. This implies that optimizing chemical mechanisms to maintain universal predictivity across such conflicting responses will only yield a predictivity tradeoff. It also implies that careful selection of optimization objectives increases the likelihood of better predictivity for these objectives.