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A simplified combustion and emission formation model for diesel engines has been developed in a project where the long term objective is to predict emissions during transient operation. The intended application implies that the final model must be both computationally inexpensive and comprehensive so that it can be used for optimization of engine control variables when coupled to full-engine simulation software. As starting point, the proposed model uses diesel spray correlations established in combustion vessels regarding spray penetration, dispersion, gas entrainment, ignition and flame lift-off. It has been found that with minor adaption, these correlations are valid also for combustion in an engine. By assuming a fully mixing controlled combustion after ignition and by use of simplified emission models, the correlations have been found useful for predicting trends in engine-out emission with low computational cost.

A clear trend in engine development is that the engines are becoming more and more complex both regarding components and component-systems as well as controlling them. These complex engines have great potential to minimize emissions but they also have a great number of combinations of setting. Systematic testing to find these optimum settings is getting more and more challenging. A possible remedy is to roughly optimize these settings offline with predictive models and then only perform the fine tuning in the engine test bed. To be able to do so, two things are needed; firstly a engine model that will predict how the different setting affect engine performance and secondly how the engine performance affects the emissions. A new approach for predicting soot emissions has previously been presented [1] where the frame of the model was a multizone approach developed for NO formation prediction.

A clear trend in engine development is that the engines are becoming more and more complex both regarding components and component-systems as well as controlling them. These complex engines have great potential to minimize emissions but they also have a great number of combinations of setting. Systematic testing to find these optimum settings is getting more and more challenging. A possible remedy is to roughly optimize these settings offline with predictive models and then only perform the fine tuning in the engine test bed. To be able to do so, two things are needed; firstly a engine model that will predict how the different setting affect engine performance and secondly how the engine performance affects the emissions. This article shows a new approach for predicting soot emissions. The frame of the model is a multizone approach developed for NO formation prediction.

PM-emissions during a load transient have been measured regarding particle mass, exhaust transparency and particle number concentrations in different size ranges. The load transient was from low to medium load at constant speed and was performed with a single cylinder research engine. Mass measurements were conducted with a Tapered Element Oscillating Microbalance. Exhaust transparency was measured with an Opacimeter. Particle Number Concentrations were measured with two different Condensation Particle Counters, CPCs, where one of them was equipped with a Particle Size Selector, PSS, in order to distinguish accumulation mode particles from nucleation mode. An Engine Exhaust Particle Sizer, EEPS, was also used in parallel with the CPCs and provided a full size distribution. For dilution, a rotating disc diluter and a two stage ejector diluter was used. In total two stages of hot dilution and one unheated.