Bálint Szabó

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Publications - 2

Experimental Validation and Optimization of a Hydrogen–Gasoline Dual-Fuel Combustion Model in a Spark Ignition Engine with a Moderate Hydrogen Ratio

Publication Name: Energies

Publication Date: 2025-07-01

Volume: 18

Issue: 13

Page Range: Unknown

Description:

Hydrogen–gasoline dual-fuel spark ignition (SI) engines represent a promising transitional solution toward cleaner combustion and reduced carbon emissions. In a previous study, a predictive engine model was developed to simulate the performance and combustion characteristics of such systems; however, its accuracy was constrained by the use of estimated combustion parameters. This study presents an experimental validation based on high-resolution in-cylinder pressure measurements performed on a naturally aspirated SI engine operating with a 20% hydrogen energy share. The objectives are twofold: (1) to refine the combustion model using empirically derived combustion metrics, and (2) to evaluate the feasibility of moderate hydrogen enrichment in a stock engine configuration. To facilitate a more accurate understanding of how key combustion parameters evolve under different operating conditions, Vibe function was fitted to the ensemble-averaged heat release rate curves computed from 100 consecutive engine cycles at each static full-load operating point. This approach enabled the extraction of stable and representative metrics, including the mass fraction burned at 50% (MFB50) and combustion duration, which were then used to recalibrate the predictive combustion model. In addition, cycle-to-cycle variation and combustion duration were also investigated in the dual-fuel mode. The combustion duration exhibited a consistent and substantial reduction across all of the examined operating points when compared to pure gasoline operation. Furthermore, the cycle-to-cycle variation difference remained statistically insignificant, indicating that the introduction of 20% hydrogen did not adversely affect combustion stability. In addition to improving model accuracy, this work investigates the occurrence of abnormal combustion phenomena—including backfiring, auto-ignition, and knock—under enriched conditions. The results confirm that 20% hydrogen blends can be safely utilized in standard engine architectures, yielding faster combustion and reduced burn durations. The validated model offers a reliable foundation for further dual-fuel optimization and supports the broader integration of hydrogen into conventional internal combustion platforms.

Open Access: Yes

DOI: 10.3390/en18133501

Prediction of Efficiency, Performance, and Emissions Based on a Validated Simulation Model in Hydrogen–Gasoline Dual-Fuel Internal Combustion Engines

Publication Name: Energies

Publication Date: 2024-11-01

Volume: 17

Issue: 22

Page Range: Unknown

Description:

This study explores the performance and emissions characteristics of a dual-fuel internal combustion engine operating on a blend of hydrogen and gasoline. This research began with a baseline simulation of a conventional gasoline engine, which was subsequently validated through experimental testing on an AVL testbed. The simulation results closely matched the testbed data, confirming the accuracy of the model, with deviations within 5%. Building on this validated model, a hydrogen–gasoline dual-fuel engine simulation was developed. The predictive simulation revealed an approximately 5% increase in overall engine efficiency at the optimal operating point, primarily due to hydrogen’s combustion properties. Additionally, the injected gasoline mass and CO2 emissions were reduced by around 30% across the RPM range. However, the introduction of hydrogen also resulted in a slight reduction (~10%) in torque, attributed to the lower volumetric efficiency caused by hydrogen displacing intake air. While CO emissions were significantly reduced, NOx emissions nearly doubled due to the higher combustion temperatures associated with hydrogen. This research demonstrates the potential of hydrogen–gasoline dual-fuel systems in reducing carbon emissions, while highlighting the need for further optimization to balance performance with environmental impact.

Open Access: Yes

DOI: 10.3390/en17225680