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Particulate and regulated gaseous emissions were characterized in a feasibility study for a 1994 Ford Taurus Flexible Fuel Vehicle (FFV) operating on five fuels. The five fuels included Federal Reformulated Gasoline (RFG); 85% fuel grade methanol and 15% gasoline (M85); 85% denatured ethanol and 15% gasoline (E85d); liquefied petroleum gas (LPG) meeting HD-5 specifications; and industry average compressed natural gas (CNG). The vehicle was operated fuel-rich to simulate a vehicle operating condition leading to increased production of particulate matter. This simulation was accomplished by using a universal exhaust gas oxygen sensor (UEGO) in connection with an external controller. Appropriate aftermarket conversion kits involving closed-loop control and adaptive learning capabilities allowed operation on the gaseous fuels. Particulate emissions were characterized by total mass and particle size.

Oil consumption has been identified as a contributor to diesel particulate exhaust emissions. The strict requirements for reduced diesel exhaust particulates in 1991 and in 1994 call for a much greater understanding of the level of oil consumption during transient as well as steady-state operations. A system has been assembled to continuously measure diesel engine oil consumption through on-line detection using sulfur as a tracer. The system requires a sulfur-free fuel, a high-sulfur diesel engine oil, an exhaust sampling system, and a sensitive detector. A series of engine tests were conducted using the sulfur-trace oil consumption measurement system. Variations in oil consumption at steady state and during transient operations have been measured. Quantitative measurement of oil consumption rates were confirmed by two separate calibration checks.

A theoretical model for predicting cetane number of primary reference fuels from parameters measurable by proton nuclear magnetic resonance is presented. This modeling technique is expanded to include secondary reference fuels, pure hydrocarbons, and commercial-type fuels. An evaluation of the ignition process indicated that not only hydrogen type distribution measurable by proton NMR, but also relative hydrogen population is important in predicting cetane number. Two mathematical models are developed. One predicts cetane number of saturate fuels and the second predicts cetane number of fuels containing aromatic components. The aromatic fuel model is tested using the ASTM Diesel Check Fuels and shown to predict within the standard error of the model.