Abstract
Hydrogen is a leading alternative fuel for eliminating the carbon emissions of internal combustion engines. Moreover, the use of hydrogen improves the combustion owing to its high flame speed. The hydrogen selective catalytic reduction is a promising solution for the reduction of nitric oxides (NO_x), which is the sole regulated gas species in hydrogen-fueled internal combustion engines. In the present study, hydrogen and NO_x emissions, the crucial species for the catalyst performance, were investigated using a heavy-duty, hydrogen spark-ignition engine. The ratio of H_2 to NO_x was above 100 at the excess air ratio (lambda) of 2.5 or higher. Three-dimensional, numerical simulation showed that the in-cylinder hydrogen distribution was dependent on the engine load and the lambda value. A regression analysis showed that the exhaust hydrogen quantity had a strong correlation with the seven parameters, namely engine speed, the gross indicated effective pressure (IMEPg), lambda, spark timing, total combustion duration, peak in-cylinder temperature, and peak pressure rise rate. Among these parameters, the IMEPg and the lambda value exhibited the highest weights in a neighborhood component analysis. The regression model with the seven features exhibited the highest R~2 value of 0.94 with the squared exponential Gaussian process regression. The proposed prediction model can contribute to not only reducing NO_x emission with aftertreatment, but also maximizing the thermal efficiency of hydrogen-fueled internal combustion engines.
NSTL
Elsevier