Prediction of the PIONA and oxygenate composition of unconventional fuels with the Pseudo-Component Property Estimation (PCPE) method: Application to an Automotive Shredder Residues-derived gasoline.
2018
To check if an unconventional fuel can be burned in
an engine, monitoring the stability in terms of composition
is mandatory. When the composition of a
conventional fuel cannot be measured for practical reason,
it can be approximated using the API (American Petroleum
Institute) relations (Riazi-Daubert) linking the hydrocarbon
group fractions with well-chosen properties. These relations
cover only the paraffin (coupling iso and normal), naphthene
and aromatic (PNA) groups as they were developed for
conventional fuels presenting neglected amounts of olefins
and oxygenates. Olefins and oxygenates can be present in
unconventional fuels. This paper presents a methodology
applicable to any unconventional fuel to build a model to
estimate the n-paraffin, iso- paraffin, olefin, naphthene,
aromatic and oxygenate (PIONAOx) composition. The
current model was demonstrated for an automotive shredder
residues (ASR)-derived gasoline-like fuel (GLF). The model
was trained using real fractions measured with a comprehensive
two-dimensional gas chromatography coupled with
flame ionization detector (GC × GC-FID) technique. The
lowest cumulated absolute error comparing with the confidence
interval of the measured fractions was evaluated to be
12.4%. The model was tested for one fuel composition only,
therefore, the error of the calculated fractions will be investigated
with other fuels in future work.
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