Transient Emission Predictions With Quasi Stationary Models

Claes Ericson; Björn Westerberg; Rolf Egnell

doi:10.4271/2005-01-3852

2005-10-24

Transient Emission Predictions With Quasi Stationary Models 2005-01-3852

Heavy trucks contribute significantly to the overall air pollution, especially NOx and PM emissions. Models to predict the emissions from heavy trucks in real world on road conditions are therefore of great interest. Most such models are based on data achieved from stationary measurements, i.e. engine maps. This type of “quasi stationary” models could also be of interest in other applications where emission models of low complexity are desired, such as engine control and simulation and control of exhaust aftertreatment systems.

In this paper, results from quasi stationary calculations of fuel consumption, CO, HC, NOx and PM emissions are compared with time resolved measurements of the corresponding quantities. Measurement data from three Euro 3-class engines is used. The differences are discussed in terms of the conditions during transients and correction models for quasi stationary calculations are presented.

Simply using engine maps without transient correction is not sufficient. For the engines studied, accumulated errors of up to 60-70% are common before correction. Earlier work in this field has mainly been focused on statistical correction models of accumulated emissions. The transient correction model presented in this paper uses stepwise correction and has a physical interpretation. The delay introduced by the turbocharger during transients results in lower air flows and hence lower air-fuel ratios, than predicted from engine maps. A delay time and a corresponding transient air-fuel equivalence ratio (λ) is estimated in each time step and is used for compensation of the emissions.

Another important aspect of models for simulating real world emissions is generality, whether a common emission model can be used for all engines of a given emission classification. Differences between the engines in this study are discussed.

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Transient Emission Predictions With Quasi Stationary Models 2005-01-3852

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