Impacts of enhanced physics-based estimation modeling for trapped air and EGR estimation in real-time control of hydrogen injection in a PFI internal combustion engine

Hydrogen PFI engines face abnormal combustion issues, especially during transient operation. The air-to-fuel ratio and trapped exhaust gas significantly affect combustion stability and NOx emissions, requiring continuous monitoring. Real-time estimation of the trapped gas composition and thermodynamic state is therefore crucial but challenging. This work introduces a real-time, physics-based Multi-Input-Multi-Output (MIMO) model for accurately estimating trapped air and exhaust gas mass at the intake valve closing (IVC) event. In detail, the estimation model makes use of dynamic in-cylinder and exhaust pressure measurements to accurately model mass flows and heat exchange equations with 0.5 CAD resolution. This allows an extremely high fidelity when modelling the physical properties of the various chemical species along the engine cycle. Moreover, the model calibration appears only in the form of two coefficients implemented on a lookup table for twelve different operating points, highlighting the small calibration effort. The physics-based model for the estimation of the amount of air and EGR was validated against 1-D numerical results for a hydrogen-fueled PFI engine prototype developed in GTPower environment. The validation process analyzes the model accuracy in multiple steady-state and transient profiles, in terms of in-cylinder trapped air, residuals and fuel. Results show the robustness and accuracy of the model, allowing proper AFR control especially when integrating a fuel-injection correcting controller. Preliminary analyses reported an average estimation error within single digit precision for both trapped air and residuals even in transient operation, proving how advanced numerical modeling can improve the reliability of H2 internal combustion engines.