Comparative Analysis of Different Methodologies to Calculate Lambda (λ) Based on Extensive And systemic Experimentation on a Hydrogen Internal Combustion Engine

Author:

Azeem Naqash,Beatrice Carlo,Vassallo Alberto,Pesce Francesco,Davide Gessaroli,Guido Chiara,Rossi PhD Riccardo

Abstract

<div class="section abstract"><div class="htmlview paragraph">Hydrogen Internal Combustion Engines (H<sub>2</sub>-ICEs) are subject to increased attention thanks to their extremely low criteria pollutant emission and near-zero CO<sub>2</sub> tailpipe emissions. However, to further minimize exhaust emissions and increase the efficiency of a H<sub>2</sub>-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 (λ<sub>EMI</sub>), raw Universal Exhaust Gas Oxygen (λ<sub>R-UEGO</sub>), processed Universal Exhaust Gas Oxygen (λ<sub>P-UEGO</sub>) and speed-density (λ<sub>SD</sub>) outputs. The experimental data used to compare the four methodologies were acquired through detailed and systematic experimentation on a fully-instrumented single-cylinder H<sub>2</sub>-ICE. Results show that the λ<sub>P-UEGO</sub> is the closest one to the reference Spindt-Brettschneider analysis λ<sub>EMI</sub> and the most robust to ample variations in the nominal λ values. The sensor’s raw UEGO output λ<sub>R-UEGO</sub> is instead affected by the sensor calibration which is usually performed across a range of carbon-based fuels, a procedure that introduces a bias. The results can be used for the selection of the correct methodology to calculate λ in a H<sub>2</sub>-ICE and to choose optimal sensors for mobile applications.</div></div>

Publisher

SAE International

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