Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)

Legacy Department

Automotive Engineering

Committee Member

Dr. Robert Prucka, Committee Chair

Committee Member

Dr. Zoran Filipi, Co-Chair

Committee Member

Dr. Pierluigi Pisu

Committee Member

Dr. Hussein Dourra


With more restrictive engine emissions regulations and higher energy prices, the modern engine is equipped with an increasing number of actuators to meet the fuel economy, drivability and emissions requirements. Although map-based engine control and calibration routines are state of the art, they become burdensome when the number of control degrees of freedom increases significantly. The increased system complexity motivates the use of model-based methods to minimize product development time and ensure calibration flexibility when the engine is altered during the design process. Model-based control has the potential to significantly reduce the labor, time and expense of engine calibration, as compared to state-of-the-art experimentally based methods. In this research, physics-based models designed for real-time SI engine combustion phasing prediction and control are proposed. To realize real-time implementation of this system several models are derived; (1) a physics based internal residual gas mass prediction model, (2) a real-time cylinder pressure calculation model, (3) a two-step physics based turbulence intensity model, (4) a flame kernel development prediction model, and (5) a spark selection algorithm are subsequently developed. The complete physical models based combustion phasing prediction and control system are implemented into a rapid prototype ECU to realize real-time engine tests. Steady-state and transient engine test results show that the proposed system can accurately predict key variables and control the SI engine combustion phasing in real-time. The root-mean-square-error (RMSE) of the combustion phasing control over a wide range of operating conditions is 2-3 crank angle degrees.



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