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Method for predicting gasoline octane value

A gasoline octane number and octane number technology, applied in chemical machine learning, chemical data mining, chemical statistics and other directions, can solve the lack of in-depth understanding and theoretical research on the octane number blending process, limited experimental methods, and models Problems such as insufficient prediction accuracy and scope of application

Active Publication Date: 2019-07-16
CHINA PETROLEUM & CHEM CORP +1
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  • Claims
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Problems solved by technology

[0003] At present, some research institutions at home and abroad have given a small amount of conjectures about the mathematical relationship between octane number and gasoline composition. However, these models are mostly derived from assumptions and inferences made by experimental laws, and lack in-depth understanding and theoretical research on the octane number blending process. , limited by the basis of the experimental method, the obtained model also has insufficient prediction accuracy and scope of application

Method used

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  • Method for predicting gasoline octane value
  • Method for predicting gasoline octane value
  • Method for predicting gasoline octane value

Examples

Experimental program
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Effect test

Embodiment 1

[0065] For the three parts of the combination, model 1A, model 2A, and model 3A are selected respectively, and the octane number of pure hydrocarbons is substituted, and the intermediate parameters are simplified to obtain the octane number prediction model expression 1A-2A-3A based on the detailed composition of gasoline:

[0066]

[0067] in, P represents the components considered to be involved in the correction of the conversion rate of active nuclei in Model 2, Among them, ρ i is the relative density of component i, M i is the relative molecular weight of component i. ON i is the octane number of each pure component, which is a known parameter, υ i is the volume fraction of component i, β i , a is the parameter that the model needs to regress, where, β i The initial value of can be obtained from the density and molecular weight of component i.

[0068] The model expression obtained by this combination is similar to the formula obtained by Exxon Company through...

Embodiment 2

[0071] For the three parts of the combination, model 1A, model 2B, and model 3A are selected respectively, and the octane number of pure hydrocarbons is substituted, intermediate parameters are simplified, and the octane number prediction model expression 1A-2B-3A based on the detailed composition of gasoline is obtained:

[0072]

[0073] Among them, I mix =∑ ij t ij no i no j , t ij It is the interaction parameter between component i and component j that needs to be considered in the correction of active nuclear conversion rate in model 2, and is obtained by model regression.

[0074] Also use the method in Example 1 to obtain parameter β i Initial value, use the data regression parameters, and verify the prediction effect of the expression. Such as Figure 4 As shown, the abscissa is the octane number actually measured by the sample, the ordinate is the octane number calculated by the model, "*" is the model parameter training set, "+" is the model parameter te...

Embodiment 3

[0076] For the three parts of the combination, model 1A, model 2A, and model 3B are selected respectively, and the octane number of pure hydrocarbons is substituted, intermediate parameters are simplified, and the octane number prediction model expression 1A-2A-3B based on the detailed composition of gasoline is obtained:

[0077]

[0078] Each parameter in the formula is identical with embodiment one.

[0079] Also use the method in Example 1 to obtain parameter β i Initial value, use the data regression parameters, and verify the prediction effect of the expression, such as Figure 5 As shown, the abscissa is the octane number actually measured by the sample, the ordinate is the octane number calculated by the model, "*" is the model parameter training set, "+" is the model parameter test set, and the results show that the standard deviation is 0.532 .

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Abstract

The embodiment of the invention provides a method for predicting a gasoline octane value, and belongs to the field of petroleum chemical engineering. The method comprises the steps that an active nucleus conversion rate is calculated according to ingredients in gasoline and an active nucleus conversion rate calculation model, and the gasoline octane value is calculated according to the active nucleus conversion rate and an octane value calculating model. A scheme provides the hypothesis that the active nucleus conversion rate in a system determines the octane value by means of researching a burning chemical model of hydrocarbon in an air cylinder to resolve a burning process, the octane value is calculated on the basis, and accordingly, the contribution or loss of the gasoline octane valuecaused by a non-linear blending effect in a blending process of the ingredients in the gasoline can be taken into consideration, and prediction of the gasoline octane value can be more precise.

Description

technical field [0001] The invention relates to the field of petrochemical industry, in particular to a method for predicting gasoline octane number. Background technique [0002] Gasoline is blended from various components. The inventors of the present application found in the process of realizing the present invention that no matter the blending components here refer to pure hydrocarbon compounds or certain component oils, the octane number in the blending process There will be obvious non-linear laws. It can be said that the gasoline octane number is not only related to the octane number of each blending component in gasoline, but also related to the blending characteristics of each component in the blending process. In recent years, in the process of upgrading oil products, more emphasis has been placed on the proportion of high-octane components added, while relatively ignoring the possible contribution or loss of gasoline octane due to nonlinear blending effects durin...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16C20/70
CPCG16C10/00G16C20/10
Inventor 王鑫磊耿晓棉周祥
Owner CHINA PETROLEUM & CHEM CORP
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