Development and Validation of a Knock Prediction Model for Methanol-Fuelled SI Engines

2013-01-1312

04/08/2013

Event
SAE 2013 World Congress & Exhibition
Authors Abstract
Content
Knock is one of the main factors limiting the efficiency of spark-ignition engines. The introduction of alternative fuels with elevated knock resistance could help to mitigate knock concerns. Alcohols are prime candidate fuels and a model that can accurately predict their autoignition behavior under varying engine operating conditions would be of great value to engine designers.
The current work aims to develop such a model for neat methanol. First, an autoignition delay time correlation is developed based on chemical kinetics calculations. Subsequently, this correlation is used in a knock integral model that is implemented in a two-zone engine code. The predictive performance of the resulting model is validated through comparison against experimental measurements on a CFR engine for a range of compression ratios, loads, ignition timings and equivalence ratios.
Compared to older correlations that were developed for gasoline, the current autoignition delay correlation captures the high temperature sensitivity of methanol autoignition kinetics. This results in a better prediction of the knock limited spark advance for variations in compression ratio and load. Also the deterioration of knock as a function of spark advance is well reproduced for these conditions.
The largest model inaccuracies appear when changing equivalence ratio. Knock tendency is consistently overpredicted for rich mixtures. This is probably due to the effect of evaporation cooling and wall heat transfer which are not well captured by the current model. Further model improvements should therefore focus on these thermal processes inside the cylinder.
Meta TagsDetails
DOI
https://doi.org/10.4271/2013-01-1312
Pages
17
Citation
Vancoillie, J., Sileghem, L., and Verhelst, S., "Development and Validation of a Knock Prediction Model for Methanol-Fuelled SI Engines," SAE Technical Paper 2013-01-1312, 2013, https://doi.org/10.4271/2013-01-1312.
Additional Details
Publisher
Published
Apr 8, 2013
Product Code
2013-01-1312
Content Type
Technical Paper
Language
English