The cold start hydrocarbon emission from the increasing population of two
wheelers in countries like India is one of the research issues to be
addressed. This work describes the prediction of cold start hydrocarbon
emissions from air cooled spark ignition engines through fuzzy logic
technique. Hydrocarbon emissions were experimentally measured from test
engines of different cubic capacity, at different lubricating oil temperature
and at different idling speeds with and without secondary air supply in
exhaust. The experimental data were used as input for modeling average
hydrocarbon emissions for 180 seconds counted from cold start and warm start
of gasoline bike engines. In fuzzy logic simulation, member functions were
assigned for input variables (cubic capacity and idling rpm) and output
variables (average hydrocarbon emission for first 180 seconds at cold start
and warm start). The knowledge based rules were adopted from the analyzed
experimental data and separate simulations were carried out for predicting
hydrocarbon emissions from engines equipped with and without secondary air
supply. The simulation yielded the average hydrocarbon emissions of air
cooled gasoline engine for a set of given input data with accuracy over 90%.