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Soft Computing Model for Prediction of EGR Effects on Particle Sizing at CR Diesel Engine Exhaust
Technical Paper
2007-24-0104
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Use of EGR (Exhaust Gas Recirculation) and after-treatment devices allows diesel engines to comply with actual emission regulations. In order to satisfy future emission standards it will be necessary a careful analysis of peculiarities and limits of the current systems for pollution control and of their possible influence on production of other harmful substances. Engine control maps determine optimal EGR considering a trade-off between NOx and smoke emissions. However, actual control strategies do not consider, in the definition of optimal EGR, its effect on particle number density, which has a great importance for the optimal functioning of after-treatment systems. In this paper a soft computing model that gives real time information on the characteristic of exhaust particles, is proposed. The model, by using a neural network approach, is able to provide information on the effect of EGR on particulate mass concentration and particle size distribution. The proposed model can be employed for advanced real time engine controls which, acting on the amount of recirculated exhaust gas, can lead to a reduction of exhaust emission optimizing at the same the particulate size distribution. The experiments have been carried out at the exhaust of a Common Rail 1.9 l, 16 v Diesel engine for different engine operating conditions. Particle number size distributions in the range 7 nm-10 μm have been measured.
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Authors
- Ferdinando Tagliatatela Scafati - Automotive Product Group - Advanced System Applications STMicroelectronics, Via R. De Feo, 1 - 80022 Arzano (NA), Italy
- Nicola Cesario - Automotive Product Group - Advanced System Applications STMicroelectronics, Via R. De Feo, 1 - 80022 Arzano (NA), Italy
- Mario Lavorgna - Automotive Product Group - Advanced System Applications STMicroelectronics, Via R. De Feo, 1 - 80022 Arzano (NA), Italy
- Simona S. Merola - Istituto Motori - CNR, Via G. Marconi, 8 - 80125 Napoli (Italy)
- Bianca M. Vaglieco - Istituto Motori - CNR, Via G. Marconi, 8 - 80125 Napoli (Italy)
Topic
Citation
Scafati, F., Cesario, N., Lavorgna, M., Merola, S. et al., "Soft Computing Model for Prediction of EGR Effects on Particle Sizing at CR Diesel Engine Exhaust," SAE Technical Paper 2007-24-0104, 2007, https://doi.org/10.4271/2007-24-0104.Also In
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