Blending Octane Number of Ethanol on a Volume and Molar Basis in SI and HCCI Combustion Modes

2017-01-2256

10/08/2017

Features
Event
International Powertrains, Fuels & Lubricants Meeting
Authors Abstract
Content
The blending behavior of ethanol in five different hydrocarbon base fuels with octane numbers of approximately 70 and 84 was examined under Spark-Ignited (SI) and Homogeneous Charge Compression Ignited (HCCI) operating conditions. The Blending octane number (BON) was used to characterize the blending behavior on both a volume and molar basis. Previous studies have shown that the blending behavior of ethanol generally follows several well-established rules. In particular, non-linear blending effects are generally observed on a volume basis (i.e. BON > RON or MON of pure ethanol; 108 and 89, respectively), while linear blending effects are generally observed on a molar basis (i.e. BON = RON or MON of pure ethanol). This work firstly demonstrates that the non-linear volumetric blending effects traditionally observed under SI operating conditions are also observed under HCCI operating conditions. In keeping with previous studies, the degree of this non-linearity is shown to be a function of the base fuel composition and octane number. By contrast, the molar blending approach is shown to behave differently depending on the chosen combustion mode, with some non-linearity observed under HCCI operating conditions (i.e. BON ≠ RON or MON of pure ethanol). This suggests that the well-established blending rules for SI operating conditions may not always be relevant to other combustion modes that operate with globally lean or diluted air-fuel mixtures. This has implications for the design of future fuel specifications.
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DOI
https://doi.org/10.4271/2017-01-2256
Pages
15
Citation
Waqas, M., Morganti, K., Masurier, J., and Johansson, B., "Blending Octane Number of Ethanol on a Volume and Molar Basis in SI and HCCI Combustion Modes," SAE Technical Paper 2017-01-2256, 2017, https://doi.org/10.4271/2017-01-2256.
Additional Details
Publisher
Published
Oct 8, 2017
Product Code
2017-01-2256
Content Type
Technical Paper
Language
English