Impact of Enhanced Physics-Based Estimation Modeling for Trapped Air and EGR in Real-Time Control of Hydrogen Injection in a PFI Internal Combustion Engine Università degli Studi di Firenze

Format:

Book

Conference/Event

Author/Creator:

Galli, Claudio, author.

Contributor:

Balduzzi, Francesco

Ferrara, Giovanni

Grilli, Niccolò

Romani, Luca

Vichi, Giovanni

Conference Name:

SETC2025: 29th Small Powertrains and Energy Systems Technology Conference (2025-11-10 : Florence, Italy)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2025

Summary:

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 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 GT-Power environment. The validation process analyzes the model accuracy in multiple steady-state and transient profiles, in terms of in-cylinder trapped air and residuals. 165 steady cases and two transient profiles of 1800 engine cycles each are studied. Results show the robustness and accuracy of the model, allowing proper AFR control especially when integrating a fuel-injection correcting controller. Indeed, value of normalized mean absolute percentage error around 2% and 5% are reported for air and EGR estimation. The model proves to be highly accurate even in fast-transient operation: however, further improvements will be carried out to reduce maximum errors observed

Notes:

Vendor supplied data

Publisher Number:

2025-32-0047

Access Restriction:

Restricted for use by site license