Abstract
In this paper, a design process associated with new engine management system is implemented on a Honda CT110 motor bike running on hydrogen. Several ancillary instruments for measuring various engine operating parameters and emissions are fitted to appraise the performance of the motor bike. The engine‘s performance parameters as well as emission characteristics on hydrogen fuel are compared to gasoline fuel. Based on the extensive experimental emission data, an intelligent predictive neural networks model was developed for different emission characteristics of hydrogen powered motor bike internal combustion engine. The emission predictions were found to be ±5% to the experimental values. This work established knowledge of practical use of hydrogen as a fuel in a specific automotive application. With a large emphasis on control of emissions around the world, this modelling tool is seen as a means to quantitatively estimate emissions for two wheelers in the first instance. As an extension, this work forms a basis for predicting and establishing engine operating conditions, as inverse models, to ensure that the targeted emissions are not exceeded to meet EURO 3 regulations.
Keywords: Hydrogen motor bike, emission prediction, hydrogen internal combustion engine, artificial neural networks.