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Measurements of the soot emissions and engine operating parameters from a diesel engine during transient operation were used to investigate the influence of transient operation on the soot emissions, as well as to validate a realtime mean value soot model (MVSM, [1]) for transient operation. To maximize the temporal resolution of the soot emission and engine parameter measurements (in particular EGR), fast instruments were used and their dynamic responses characterized and corrected. During tip-in transients, an increase in the soot emissions was observed due to a short term oxygen deficit compared to steady-state operation. No significant difference was seen between steady-state and transient operation for acceleration transients. When the MVSM was provided with inputs of sufficient temporal resolution, it was capable of reproducing the qualitative and, in part, quantitative soot emission trends.

Future engine emission legislation regulates soot from Diesel engines strictly and requires improvements in engine calibration, fast response sensor equipment and exhaust gas aftertreatment systems. The in-cylinder phenomena of soot formation and oxidation can be analysed using a pyrometer with optical access to the combustion chamber. The pyrometer collects the radiation of soot particles during diffusion combustion, and allows the calculation of soot temperature and a proportional value for the in-cylinder soot density (KL). A four-cylinder heavy-duty Diesel engine was equipped in all cylinders with prototype pyrometers and state of the art pressure transducers. The cylinder specific data was recorded crank angle-resolved for a set of steady-state and transient operating conditions, as well as exhaust gas recirculation (EGR) addition and over a wide range of soot emissions.

A new approach within the well-known trade-off in combustion process simulations between computational efforts (and thus the capability for engine operating map calculations) on the one hand, and accuracy of predictions on the other, has been developed and applied successfully to diesel combustion, in particular to energy release and pollutant formation. Using phenomenological models in combination with bio-inspired algorithms (for parameter identification), it is now possible to predict thermal, chemical and injection related engine characteristics over an entire operating map including different types of fuel (e.g. diesel, water-in-diesel emulsions and oxygenated diesel).