Optimum NOx abatement in diesel exhaust using inferential feedforward reductant control
✍ Scribed by H.C. Krijnsen; J.C.M. van Leeuwen; R. Bakker; C.M. van den Bleek; H.P.A. Calis
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 165 KB
- Volume
- 80
- Category
- Article
- ISSN
- 0016-2361
No coin nor oath required. For personal study only.
✦ Synopsis
To adequately control the reductant ¯ow for the selective catalytic reduction of NO x in diesel exhaust gas a tool is required that is capable of accurately and quickly predicting the engine's ¯uctuating NO x emissions based on its time-dependent operating variables, and that is also capable of predicting the optimum reductant/NO x ratio for NO x abatement. Measurements were carried out on a semi-stationary diesel engine. Four algorithms for non-linear modelling are evaluated. The models resulting from the algorithms gave very accurate NO x predictions with a short computation time. Together with the small errors this makes the models very promising tools for on-line automotive NO x emission control. The optimum reductant/NO x ratio (to get the lowest combined NO x 1 reductant emission of the exhaust treating system) was best predicted by a neural network.