2026-04-23T21:14:17Zhttps://uvadoc.uva.es/oai/request

oai:uvadoc.uva.es:10324/839712026-04-09T19:00:56Zcom_10324_1170com_10324_931com_10324_894col_10324_1367

Hydrogen’s role in mitigating emissions variability: A chemical kinetic-thermodynamic digital framework for cleaner combustion technologies Gabana Molina, Pedro Cova Bonillo, Alexis José Herreros, José Tsolakis, Athanasios Producción Científica The combustion process in spark-ignition (SI) engines inherently presents cycle-to-cycle variations (CCV), leading to engine instability and variability in emissions formation. This work develops a digital framework that integrates chemical kinetics and a two-zone thermodynamic diagnostic model to understand the role of hydrogen in mitigating CCV and its impact on emissions formation. The framework predicts the crank angle degree resolved evolution of CCV of CO, H2, NO, and N2O in the engine combustion chamber’s burned gas zone. The framework is calibrated with experimental results from an SI engine working with gasoline-hydrogen fuel mixtures under stoichiometric and lean combustion conditions. This investigation has revealed that the formation of nitrogen-based emissions, particularly NO, exhibits higher variability than CO and exhaust unburnt H2, with coefficients of variation ranging from 7% to 35%. The high NO variability is attributed to the rapid decrease in NO destruction rates (i.e., kinetic “freezing”) at different in-cylinder pressure and temperature conditions within each thermodynamic cycle. It is elucidated that N2O formation occurs predominantly during the expansion and exhaust strokes. New knowledge has been created to understand how the thermochemical properties of hydrogen reduce NO cycle-to-cycle variability. A synergistic effect is unveiled, hydrogen enrichment leads to an engine operational shift towards a more dilute state (i.e., increased residual gases), where hydrogen’s combustion-enhancing properties (e.g., high flame speed, low ignition energy) are crucial for stabilising combustion and thus reducing NO formation variability. Furthermore, the work proposes a new predictive statistical model capable of describing NO dispersion using only the resi- dual–gas fraction and the mean NO level, offering a practical tool for engine calibration and emissions control. Research findings can guide the development of emissions abatement technologies for combustion-based pow- ertrains operating with hydrogen under lean combustion conditions, where conventional catalysts are less effective and understanding gains are highly significant. The proposed digital framework offers an emissions variability predictive tool facilitating the stable operation of clean powertrain for future energy systems. 2026-04-09T09:24:02Z 2026-04-09T09:24:02Z 2026 info:eu-repo/semantics/article Energy Conversion and Management, 2026, vol. 357, p. 121431 0196-8904 https://uvadoc.uva.es/handle/10324/83971 10.1016/j.enconman.2026.121431 121431 Energy Conversion and Management 357 eng https://www.sciencedirect.com/science/article/pii/S0196890426004000 info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ © 2026 The Author(s) Atribución 4.0 Internacional Elsevier SI