http://www.cnr.it/ontology/cnr/individuo/prodotto/ID284644
A knock model for 1D simulations accounting for cyclic dispersion phenomena (Articolo in rivista)
- Type
- Label
- A knock model for 1D simulations accounting for cyclic dispersion phenomena (Articolo in rivista) (literal)
- Anno
- 2014-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.4271/2014-01-2554 (literal)
- Alternative label
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- F.Bozza, V.De Bellis, D.Siano (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
- SAE PAPER N. 2014-01-2554 (literal)
- Rivista
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
- Note
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- F.Bozza - Università di Napoli
V.De Bellis - Università di Napoli (literal)
- Titolo
- A knock model for 1D simulations accounting for cyclic dispersion phenomena (literal)
- Abstract
- Control of knock phenomenon is becoming more and more
important in modern SI engine, due to the tendency to develop
high boosted turbocharged engines (downsizing). To this aim,
improved modeling and experimental techniques are required
to precisely define the maximum allowable spark advance.
On the experimental side, the knock limit is identified based on
some indices derived by the analysis of the in-cylinder
pressure traces or of the cylinder block vibrations. The
threshold levels of the knock indices are usually defined
following an heuristic approach.
On the modeling side, in the 1D codes, the knock is usually
described by simple correlation of the auto-ignition time of the
unburned gas zone within the cylinders. In addition, the latter
methodology commonly refers to ensemble-averaged pressure
cycles and, for this reason, does not take into account the
cycle-by-cycle variations.
In this work, an experimental activity is carried out to
characterize the effects of cyclic dispersion on knock
phenomena for different engine speeds, at full load operations
and referring to a spark advance of borderline knock. In each
case, a train of 200 consecutive in-cylinder pressure traces is
processed and the knocking cycles are identified through a
standard FFT analysis, compared to an auto-regressive (AR)
technique. The latter, proved to be more sensitive, is utilized to
define the percentage of knocking cycles occurring in each
operating condition, through the assignment of a proper
threshold level.
Then, a 1D model is set up to reproduce the above
experimental pressure traces in terms of average IMEP and
cycle-by-cycle variation. A kinetic sub-model is used to
compute the heat released in the end-gas zone to be related to
the knock occurrence. A new knock index is defined for each
simulated cycle and its distribution is compared with the AR
model outcomes. The above comparison proves a substantial
congruence between the AR model-based knock detection
methodology and the numerical one. (literal)
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