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Hydrogen Internal Combustion Engines (H2-ICEs) are subject to increased attention thanks to their extremely low criteria pollutant emission and near-zero CO2 tailpipe emissions. However, to further minimize exhaust emissions and increase the efficiency of a H2-ICE, it is important to carefully control the relative air-fuel ratio of operation, i.e. Lambda (λ), which will lead in turn to an optimal combustion process. The precise λ control mainly relies upon the methodology to calculate λ on board of the engine, where the availability of reliable sensors specifically-developed for hydrogen combustion is currently limited. In this article, a comparative analysis of different methodologies for the calculation of λ is performed, comparing four methodologies: exhaust gas analysis through a Spindt-Brettschneider approach (λEMI), raw Universal Exhaust Gas Oxygen (λR-UEGO), processed Universal Exhaust Gas Oxygen (λP-UEGO) and speed-density (λSD) outputs.

High cycle-to-cycle variations (CTCV) in a Hydrogen-Fueled Internal Combustion Engine (H2-ICE), especially in the lean-burn condition, not only lower the engine’s efficiency but also increase emissions and torque variations. High CTCV are mainly due to the variations in: mixture motion within the cylinder at the time of spark, amount of air and fuel fed to the cylinder, and mixing of the fresh mixture and residual gases within the cylinder during each cycle. In this article, multiple cycle-based methodologies were compared and analyzed specifically for H2-ICEs based on systematic experimentation. The experimental test campaign was performed on a Port Fuel Injection (PFI) H2-ICE designed by PUNCH Torino and data is processed with MATLAB. A MATLAB code is also proposed as a tool for comparing multiple methodologies for the analysis of CTCV specifically for H2-ICE.