New computational procedures are proposed for evaluating the exhaust brake specific mass emissions of each pollutant species in IC engines. The procedures start from the chemical reaction of fuel with combustion air and, basing on the measured exhaust raw emissions THC, CH4, NOx, CO, O2, CO2, calculate the volume fractions of the compounds in the exhaust gases, including those that are not usually measured, such as water, nitrogen and hydrogen. The method also takes the effects of various fuel and combustion air compositions into account, with particular reference to different natural gas blends as well as to the presence of water vapor, CO2, Ar and He in the combustion air. The molecular mass of the exhaust gases is then evaluated and the brake specific emissions can be obtained if the exhaust flow rate and the engine power output are measured. The methods stem from the extension of the different procedures that are used in the literature to evaluate α from measured raw volume emissions of IC engines running on conventional fuels. In the present study, a new algorithm is developed so as to generalize and refine all the mentioned α evaluation procedures, keeping conventional and alternative fuel compositions into account. First, the algorithm is applied to the evaluation of α in an automotive bi-fuel SI engine running on gasoline and CNG under a wide range of operating conditions. The α evaluation tests were carried out with a carefully controlled multipoint sequential injection system for both gasoline and CNG fueling. The results are compared to those obtained from the directly measured air and fuel mass flow rates as well as from more conventional UEGO sensor data. The algorithm is then applied to the evaluation of the brake specific mass emission of each pollutant species under gasoline and CNG engine operations for different steady-state working conditions. The sensitivity of results to the main engine working parameters, the influence of environmental conditions (in particular the effect of air humidity on NOx formation) and the experimental uncertainties are determined. The specific emissions calculated from the proposed algorithm are finally compared to those obtained by applying SAE and ISO recommended practices.
