基于汽油分子组成的辛烷值模型开发

Development of Octane Model Based on Molecular Composition of Gasoline

建立了一种基于Ghosh RON模型的改进了分子组成的预测汽油辛烷值的模型,能够通过调合组分分子组成和调合比例预测调合汽油产品的研究法辛烷值。该改进模型以汽油馏分的488种烃分子及含氧化合物为基础,并综合考虑了总芳烃与总烷烃、总烯烃、总环烷烃、含氧化合物4类组分之间的相互作用对辛烷值的影响。采用改进模型对直馏石脑油、重整生成油、催化汽油等炼油厂多种汽油调合组分(实测研究法辛烷值为45~108)进行预测,预测结果的标准误差为0.21。针对调合过程,预测6种不同辛烷值的调合汽油产品,改进模型预测结果的标准误差为0.69。改进模型不受调合组分数量、种类及性质的限制,对不同来源的汽油调合组分及调合汽油产品均有较好的预测精度。

A molecular composition based gasoline octane number prediction model was proposed,which can predict not only the octane number of diverse blending gasoline components but also blended gasoline products by the use of blending the molecular composition and blending ratio of the components.The proposed model was based on 488 hydrocarbon molecules and oxygenates of the gasoline.The effect of interactions on octane number in detail was taken into account,which are among the total aromatics and the total alkanes,total olefins,total naphthenes,oxygenates four components.The improved model was used to predict various gasoline blending components with measured research octane number from 45 to 108 in refineries such as straight run naphtha,reformed oil and FCC gasoline,and the standard error of model prediction result was 0.21.For the gasoline blending process,six different measured research octane number blended gasoline products are predicted,and the standard error of model prediction result is 0.69.The prediction results demonstrate that the proposed model is independent on the quantity,type or property of the blended components,and has robust prediction accuracy for both different gasoline blending components and blended gasoline products.