CN109698013A - A method of for predicting octane number - Google Patents
A method of for predicting octane number Download PDFInfo
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- CN109698013A CN109698013A CN201710996135.1A CN201710996135A CN109698013A CN 109698013 A CN109698013 A CN 109698013A CN 201710996135 A CN201710996135 A CN 201710996135A CN 109698013 A CN109698013 A CN 109698013A
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Abstract
The embodiment of the present invention provides a kind of method for predicting octane number, belongs to petrochemical industry.The described method includes: calculating active nucleus conversion ratio according to each component in the gasoline and active nucleus conversion ratio computation model；And according to the active nucleus conversion ratio and octane number computation model, calculate the octane number.Combustion chemistry model of the program by research hydro carbons in the cylinder, decomposition combustion process, propose the guess that active nucleus conversion ratio in system determines octane number size, and carry out calculated octane number based on this, so as to consider that non-linear blending effect may be contributed or be lost caused by octane number during each blending component blending in gasoline, so that the prediction of octane number is more accurate.
Description
Technical field
The present invention relates to petrochemical industries, more particularly to a kind of method for predicting octane number.
Background technique
No matter here gasoline is concocted by various ingredients, and present inventor has found in the implementation of the present invention,
Blending component refer to pure hydrocarbon compound or certain component oil, during blending octane number can all present significantly it is non-linear
Rule.It can be said that octane number is not only related with the octane number of blending component itself each in gasoline, also with it is each during blending
Component blending rating is related.In recent years, in oil product escalation process, it is more it is emphasised that antiknock component adding proportion,
And non-linear blending effect may be contributed or be lost caused by octane number during ignoring blending relatively.And it is based on
The octane value prediction model formed in detail aims to solve the problem that this problem, is recognized on a molecular scale octane number same
When, reach the target of octane number degree of precision prediction.And the core of this model foundation is then gasoline composition-octane number mathematical table
Up to the foundation of relationship.
At present both at home and abroad some research institutions give a small amount of octane number and gasoline composition mathematical relationship guess, however this
For a little models mostly from the hypothetic deduction that experiment law is made, shortcoming grinds the deep understanding and theory of octane number blending process
Study carefully, be limited to the basis of experimental method, gained model also has the deficiency in terms of precision of prediction and the scope of application.
Summary of the invention
The purpose of the embodiment of the present invention is that providing a kind of method for predicting octane number, gasoline octane can be improved
The precision of prediction of value.
To achieve the goals above, the embodiment of the present invention provides a kind of method for predicting octane number, this method
It include: that active nucleus conversion ratio is calculated according to each component in the gasoline and active nucleus conversion ratio computation model；And according to described
Active nucleus conversion ratio and octane number computation model, calculate the octane number.
Optionally, the octane number this it is being calculated according to the active nucleus conversion ratio and octane number computation model
Before, this method further include: according to the interaction relationship of each component in the gasoline and active Transforming rate calibration model, to described
Active nucleus conversion ratio is corrected.
On the other hand, the present invention provides a kind of machine readable storage medium, and finger is stored on the machine readable storage medium
It enables, which is used for so that the method that machine executes the above-mentioned prediction octane number of the application.
Octane number is the amount progress reference of normal heptane and isooctane, reaction gasoline antiknock shake ability index.This crime
Bright people's understanding: 1) octane number is a relative concept；2) octane number is incessantly related with gasoline composition, anti-also and in combustion process
Chemical correlation is answered, this is to cause the nonlinear reason of octane number during blending.The present invention provides a kind of gasoline composition with it is pungent
The method for building up of alkane value mathematical relationship expression formula: by research hydro carbons combustion chemistry model in the cylinder, decomposition combustion process,
It proposes active nucleus conversion ratio in system and determines the guess of octane number size, and carry out calculated octane number based on this, so as to
In view of blending component each in gasoline blending during non-linear blending effect may be contributed caused by octane number or
Loss, so that the prediction of octane number is more accurate.
The other feature and advantage of the embodiment of the present invention will the following detailed description will be given in the detailed implementation section.
Detailed description of the invention
Attached drawing is to further understand for providing to the embodiment of the present invention, and constitute part of specification, under
The specific embodiment in face is used to explain the present invention embodiment together, but does not constitute the limitation to the embodiment of the present invention.Attached
In figure:
Fig. 1 is the flow chart for the method for predicting octane number that one embodiment of the invention provides；
Fig. 2 be another embodiment of the present invention provides for predict octane number method flow chart；
Fig. 3 is that the method for predicting octane number provided according to first embodiment of the invention carries out octane number prediction
Effect picture；
Fig. 4 is that the method for predicting octane number provided according to second embodiment of the invention carries out octane number prediction
Effect picture；
Fig. 5 is that the method for predicting octane number provided according to third embodiment of the invention carries out octane number prediction
Effect picture；
Fig. 6 A and Fig. 6 B are pungent for the method progress for predicting octane number provided according to fourth embodiment of the invention
The effect picture of alkane value prediction；
Fig. 7 A and Fig. 7 B are pungent for the method progress for predicting octane number provided according to fifth embodiment of the invention
The effect picture of alkane value prediction；
Fig. 8 is that the method for predicting octane number provided according to sixth embodiment of the invention carries out octane number prediction
Effect picture；And
Fig. 9 is that the method for predicting octane number provided according to seventh embodiment of the invention carries out octane number prediction
Effect picture.
Specific embodiment
It is described in detail below in conjunction with specific embodiment of the attached drawing to the embodiment of the present invention.It should be understood that this
Locate described specific embodiment and be merely to illustrate and explain the present invention embodiment, is not intended to restrict the invention embodiment.
Fig. 1 is the flow chart for the method for predicting octane number that one embodiment of the invention provides.As shown in Figure 1,
One embodiment of the invention provides the method for predicting octane number, this method comprises: according to each component in the gasoline
And active nucleus conversion ratio computation model, calculate active nucleus conversion ratio；And according to the active nucleus conversion ratio and octane number meter
Model is calculated, the octane number is calculated.
Combustion chemistry model of the program by research hydro carbons in the cylinder, decomposition combustion process propose living in system
Property consideration convey rate determine the guess of octane number size, and carry out calculated octane number based on this, so as in view of each in gasoline
Non-linear blending effect may be contributed or be lost caused by octane number during blending component blending, so that gasoline is pungent
The prediction of alkane value is more accurate.The program simplifies combustion reaction process before gasoline low temperature flame by combustion mechanism, introduces
Active nucleus conversion ratio influence octane number it is assumed that octane number model foundation is divided into the calculating of active nucleus conversion ratio, active consideration convey
Three steps of incidence relation of the amendment of rate and octane number and active nucleus conversion ratio carry out each step modeling, and final group
Synthesize the octane number mechanism pattern number form formed based on detailed hydrocarbon.
Other than considering each component alone to the influence of active nucleus conversion ratio in system, in combustion between each component
Also it can interact, increase new active nucleus or inert core constructive ways, and then have an impact to active nucleus conversion ratio in system.
Fig. 2 be another embodiment of the present invention provides for predict octane number method flow chart.Preferably, as shown in Fig. 2,
Before calculating the octane number according to the active nucleus conversion ratio and octane number computation model and being somebody's turn to do, this method is also wrapped
It includes: according to the interaction relationship of each component in the gasoline and active Transforming rate calibration model, to the active nucleus conversion ratio
It is corrected.
Three models involved in above-mentioned technical proposal are introduced respectively below:
Model 1: active nucleus conversion ratio computation model
Specifically, the active nucleus conversion ratio computation model can be selected from it is one of following, with unit in counting system
The active nucleus conversion ratio Q that molar constituent generatesac:
Model 1A:
Wherein, QacIt is the active nucleus conversion ratio that unit molar constituent generates, [ni] indicate containing for the active nucleus that i component generates
Amount, niIt is i component molar score, υiIt is i volume components score, KiAt the end of being low temperature pre-flame reaction, pure component i generates activity
The conversion ratio of core, βiIt is the blending factor of i component,Wherein, ρiIt is the relative density of i component, MiIt is i group
The relative molecular weight divided.βiValue finally need to be returned by experimental data, but by simply derive it is found that its value with
The density of i component and the ratio of molecular weight are related, and the β it is found that isooctane and normal heptane is defined by octane numberiValue is 1, Ke Yiyou
This establishes reference function, obtains the β of each componentiInitial value.
Model 1B:
Wherein, niIt is the free radical molar fraction that i component generates in the low temperature pre-flame reaction stage, niIt is i component molar point
Number, θiIt is the reaction rate that low temperature pre-flame reaction stage i component generates free radical, qiIt is that i component free radical further generates activity
The reaction rate of core.The foundation basis of the model assumes that (i.e. free radical becomes active nucleus for the ratio of active nucleus and free radical
Ability) determine the size of octane number.
Model 1C:
Wherein, the meaning of each parameter is identical as the meaning of each parameter in above-mentioned model 1B in model 1C, the model be
The guess of component competitive oxidation, the model formed referring to adsorption mechanism are added on the basis of model 1B.
Model 2: active Transforming rate calibration model
Other than considering each component alone to the influence of active nucleus conversion ratio in system, in combustion between each component
Also it can interact, increase new active nucleus or inert core constructive ways, and then have an impact to active nucleus conversion ratio in system.
The functional relation of newly-increased active nucleus and composition can be obtained by the difference to mechanism it is assumed that establish steady-state equation.It gives herein
Two kinds of model forms of 2A, 2B, can calculate the number of active cores newly increased, are added into above-mentioned active nucleus conversion ratio and calculate mould
In type, to active nucleus conversion ratio QacComplete amendment.
The active Transforming rate calibration model can be selected from it is one of following, to active nucleus conversion ratio QacIt is modified:
Model 2A:
Model 2A is steady-state equation such as 2A ', wherein k from being derived by the steady-state equation that reaction mechanism A is establishedi、It is the reaction rate of reaction mechanism A, n respectivelyi、njIt is the molar fraction of i component and j component respectively,It is i group
Divide newly-increased active nucleus conversion ratio.
Reaction mechanism A
The model is when investigating the reaction of a certain component combustion, it is assumed that catalysis factor of other components as reaction, influencing should
The reaction mechanism mechanism of reaction of component.Wherein, A, B, C represent blending component, and [A] represents the active nucleus that component A is generated by the approach,
Represent a series of hydroxyl free radical that active nucleus is generated by branch's chain reactions.During this, active nucleus is once generated, will
Branch's chain reaction occurs rapidly and generates a large amount of hydroxyl free radicals, the rapid exothermic combustion of the latter generates pinking, and each blending component is such as
What generation active nucleus is that the rate determining step of low temperature pre-flame reaction is rapid, therefore active nucleus conversion ratio is the important indicator for influencing pinking.
Model 2B:
Model 2B is being derived by the steady-state equation that reaction mechanism B is established, and for example following 2B ' of steady-state equation is shown, tij
It is the interaction parameter of i component and j component, ni、njIt is the molar fraction of i component and j component respectively,It is that system is newly-increased
Active nucleus conversion ratio.
Reaction mechanism B
The model is thought to interact between two components when investigating the reaction of a certain component combustion, in system, promotion system
In active nucleus or inertia karyogenesis, influence gross activity core specific gravity.Wherein, A, B, C represent blending component, and [M] represents the approach
Newly generated active nucleus,Represent a series of hydroxyl free radical that active nucleus is generated by branch's chain reactions.
Model 3: octane number computation model
According to pinking principle analysis, it is believed that active nucleus conversion ratio and knock intensity are positively correlated.And according to octane number standard, it is quick-fried
It shakes intensity and octane number is negatively correlated, therefore active nucleus conversion ratio and octane number are negatively correlated.Accordingly it is proposed that various active is Nuclear transformation
The guess of the model of rate and octane relationship.The present invention provides four kinds of octane number computation models, and the octane number computation model is selected from
One of following four:
Model 3A (linear function): RON=aQac+b
Model 3B (reciprocal function): RON=a/Qac+b
Model 3C (quadratic function): RON=a (Qac+b)2+c
Model 3D (exponential function): RON=exp (aQac+b)
Wherein, RON is octane number, QacIt is active nucleus conversion ratio, a, b, c are corrected parameters.These ginsengs should be adjusted in modeling
Number guarantees octane number and the negatively correlated rule of active nucleus conversion ratio.
Above-mentioned three kinds of models are summarized as follows table:
Finally, the relationship of octane value prediction model can be the combination of this three parts model, combination are as follows:
Octane number=model 3 (model 1+ model 2)
In combination, model 1,2 is all optional part, can also be given no thought to.When only considering model 3 and using linear
When model 3A, finally obtained octane number model is exactly simplest linear model.When such prediction model is used for single group
The octane number of timesharing, the formula left side is the octane number of the pure component, uses ONiInstead of the υ on the rightiValue be 1, can disappear at this time
Fall most of unknown parameters in model, achievees the purpose that simplified model.In addition, in use model 2 to the active nucleus in model 1
When conversion ratio is corrected, newly-increased active nucleus can be added on the molecule of model 1, or enable:
It is newly-increased i component molar score by the amount conversion of newly-increased active nucleus, at this time:
ni=(1+Ii)niOr ni=(1+Imix/ni)ni
After doing the above processing, then revised i component molar score is substituted into and calculates active nucleus conversion ratio in model 1.
The present invention can be modeled respectively to above three model and the guess of multiple models, and utilizes above three model
Combination forms final octane value prediction model, is during which contemplated that according to pure hydrocarbon octane number data reduction Parameters in Mathematical Model, really
The theoretical explanation and initial value of each parameter in cover half type.Finally, using product oil data, to octane number Parameters in Forecasting Model into
Row correction, finally obtains completely based on the octane value prediction model formed in detail.
Three embodiments for establishing octane value prediction model mathematic(al) representation through the invention are given below.
Embodiment one
For three parts of combination, Selection Model 1A, model 2A, model 3A, substitute into pure hydrocarbon octane number respectively, simplify
Between parameter, obtain the octane value prediction model expression formula 1A-2A-3A formed in detail based on gasoline:
Wherein,P, which is represented, to be considered to participate in the 2 modified component of active nucleus conversion ratio of model,Wherein, ρiIt is the relative density of i component, MiIt is the relative molecular weight of i component.ONiFor each pure component
Octane number is known parameters, υiIt is i volume components score, βi, a be that model needs the parameter that returns, wherein βiInitial value can be by
The density and molecular weight of i component are sought.
The model expression combined in this way is similar to the formula that Exxon company is obtained by experiment, but logical
Crossing each parameter of formula that this method obtains all has practical significance, and gives key parameter βiInitial value obtain method: according to
Octane number test method it is found that normal heptane and isooctane βiBe 1, and density and molecular weight it is also known that, according to βiParameter meaning,
Interpolation obtains other component βiInitial value.
The 194 product oil samples and 67 component oil sample datas obtained using us are verified, the mathematic(al) representation pair
Octane number has preferable precision of prediction.As shown in figure 3, abscissa is the octane number of sample actual measurement, ordinate is to pass through mould
The octane number that type is calculated, " * " are model parameter training set, and "+" is model parameter test set, as the result is shown standard deviation
It is 0.513.
Embodiment two
For three parts of combination, Selection Model 1A, model 2B, model 3A, substitute into pure hydrocarbon octane number respectively, simplify
Between parameter, obtain the octane value prediction model expression formula 1A-2B-3A formed in detail based on gasoline:
Wherein, Imix=∑ij tijninj,tijTo need to consider to participate in 2 active nucleus conversion ratio of model
The interaction parameter of modified i component and j component, is returned to obtain by model.
Parameter beta is obtained also with the method in embodiment oneiInitial value using data regression parameter, and verifies the expression
The prediction effect of formula.As shown in figure 4, abscissa is the octane number of sample actual measurement, ordinate is to be calculated by model
Octane number, " * " be model parameter training set, "+" be model parameter test set, as the result is shown standard deviation be 0.488.
Embodiment three
For three parts of combination, Selection Model 1A, model 2A, model 3B, substitute into pure hydrocarbon octane number respectively, simplify
Between parameter, obtain the octane value prediction model expression formula 1A-2A-3B formed in detail based on gasoline:
Each parameter is the same as example 1 in formula.
Parameter beta is obtained also with the method in embodiment oneiInitial value using data regression parameter, and verifies the expression
The prediction effect of formula, as shown in figure 5, abscissa is the octane number of sample actual measurement, ordinate is to be calculated by model
Octane number, " * " be model parameter training set, "+" be model parameter test set, as the result is shown standard deviation be 0.532.
Example IV
Selection Model 1A and 3A can be distinguished, when for pure hydrocarbon, model 1A be can be expressed as:
Qac=Ki (1)
The left side of model 3A can use the pure hydrocarbon octane number ON of i componentiInstead of becoming:
ONi=aQac+b (2)
(1) formula is substituted into (2) formula, pure hydrocarbon octane number ON can be establishediWith KiRelationship:
Model 1A and (3) formula are substituted into again in model 3A, most of unknown parameters in the model that can disappear, reaches letter
Change the purpose of model, final octane number model are as follows:
Wherein, ONiFor each pure component octane number as known parameters, viIt is i volume components score, βiFor the tune of i component
The factor is closed, is the parameter that model needs to return.Lead to too small amount of composition to be trained model with octane number factual data, obtain
βiParameter, so that it may pass through its octane number of gasoline predicted composition.
Combination for model 1A and 3A can carry out following two embodiment to verify its validity.
Embodiment 1), model is verified using 194 product oil samples and 67 component oil sample datas, wherein 20
A data are used as training set, remaining data as verifying collection.After being returned using data to model parameter, model is to sample
Octane number has preferable precision of prediction.As shown in Figure 6A, abscissa is the octane number of sample actual measurement, and ordinate is to pass through mould
The octane number that type is calculated, " * " are model parameter training set, and "+" is model parameter test set, as the result is shown its standard deviation
Difference is 0.663.
Embodiment 2), model is used for the prediction of 6 groups of reformation component oils and 7 groups of catalytic cracking component oil, model parameter to be adopted
With above-described embodiment 1) in return obtained parameter, model has preferable precision of prediction to the octane number of sample.As shown in Figure 6B,
Abscissa is the octane number of sample actual measurement, and ordinate is the octane number being calculated by model, and " * " is model parameter
Training set, "+" are model parameter test set, its standard deviation is 0.371 as the result is shown.
Embodiment five
Selection Model 1C and 3A can be distinguished, the two is combined and passes through mathematical computations, simplifies intermediate parameters, obtains final
Octane number predicts expression model are as follows:
Wherein, niIt is the free radical molar fraction that i component generates in the low temperature pre-flame reaction stage, niIt is i component molar point
Number, θiIt is the reaction rate that low temperature pre-flame reaction stage i component generates free radical, ONiFor known to the octane number conduct of each pure component
Parameter.
Combination for model 1C and 3A can carry out following two embodiment to verify its validity.
Embodiment 1), model is verified using 194 product oil samples and 67 component oil sample datas, wherein 40
A data are used as training set, remaining data as verifying collection.After being returned using data to model parameter, model is to sample
Octane number has preferable precision of prediction.As shown in Figure 7 A, abscissa is the octane number of sample actual measurement, and ordinate is to pass through mould
The octane number that type is calculated, " * " are model parameter training set, and "+" is model parameter test set, as the result is shown its standard deviation
Difference is 0.649.
Embodiment 2), by the prediction of 70 catalytic cracking component oil of model Mr. Yu refinery, model parameter is using above-mentioned
Embodiment 1) in return obtained parameter, model has preferable precision of prediction to the octane number of sample.As shown in Figure 7 B, abscissa
For the octane number of sample actual measurement, ordinate is the octane number being calculated by model, and " * " is model parameter training set,
"+" is model parameter test set, its standard deviation is 0.412 as the result is shown.
Embodiment six
Selection Model 1B and 3A can be distinguished, the two is combined and passes through mathematical computations, simplifies intermediate parameters, obtains final
Octane number predicts expression model are as follows:
Wherein, ONiFor each pure component octane number as known parameters, niIt is i component molar score, θiBefore being low temperature flame
Stage of reaction i component generates the reaction rate of free radical, and the parameter returned is needed for model.Lead to too small amount of composition and octane number
Factual data is trained model, obtains θiParameter, so that it may pass through its octane number of gasoline predicted composition.
Verified using 194 product oil samples and 67 component oil sample datas, the mathematic(al) representation to octane number have compared with
Good precision of prediction.As shown in figure 8, abscissa is the octane number of sample actual measurement, ordinate is to be calculated by model
Octane number, " * " be model parameter training set, "+" be model parameter test set, as the result is shown standard deviation be 0.663.
Embodiment seven
Selection Model 1A and 3B can be distinguished, the two is combined and passes through mathematical computations, simplifies intermediate parameters, obtains final
Octane number predicts expression model are as follows:
Wherein, ONiFor each pure component octane number as known parameters, viIt is i volume components score, βiFor model needs
The parameter of recurrence.Lead to too small amount of composition to be trained model with octane number factual data, obtains parameter betaiValue, so that it may
Pass through its octane number of gasoline predicted composition.
Verified using 194 product oil samples and 67 component oil sample datas, the mathematic(al) representation to octane number have compared with
Good precision of prediction.As shown in figure 9, abscissa is the octane number of sample actual measurement, ordinate is to be calculated by model
Octane number, " * " be model parameter training set, "+" be model parameter test set, as the result is shown standard deviation be 0.681.
Correspondingly, the embodiment of the present invention also provides a kind of machine readable storage medium, deposited on the machine readable storage medium
Instruction is contained, which is used for so that the method that machine executes the above-mentioned prediction octane number of the application.
The optional embodiment of the embodiment of the present invention is described in detail in conjunction with attached drawing above, still, the embodiment of the present invention is simultaneously
The detail being not limited in above embodiment can be to of the invention real in the range of the technology design of the embodiment of the present invention
The technical solution for applying example carries out a variety of simple variants, these simple variants belong to the protection scope of the embodiment of the present invention.
It is further to note that specific technical features described in the above specific embodiments, in not lance
In the case where shield, it can be combined in any appropriate way.In order to avoid unnecessary repetition, the embodiment of the present invention pair
No further explanation will be given for various combinations of possible ways.
It will be appreciated by those skilled in the art that implementing the method for the above embodiments is that can pass through
Program is completed to instruct relevant hardware, which is stored in a storage medium, including some instructions are used so that single
Piece machine, chip or processor (processor) execute all or part of the steps of each embodiment the method for the application.And it is preceding
The storage medium stated includes: USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory
The various media that can store program code such as (RAM, Random Access Memory), magnetic or disk.
In addition, any combination can also be carried out between a variety of different embodiments of the embodiment of the present invention, as long as it is not
The thought of the embodiment of the present invention is violated, equally should be considered as disclosure of that of the embodiment of the present invention.
Claims (4)
1. a kind of method for predicting octane number, which is characterized in that this method comprises:
According to each component in the gasoline and active nucleus conversion ratio computation model, active nucleus conversion ratio is calculated；And
According to the active nucleus conversion ratio and octane number computation model, the octane number is calculated,
Wherein, the active nucleus conversion ratio computation model are as follows:
Model 1A:
Wherein, QacIt is the active nucleus conversion ratio that unit molar constituent generates, [ni] indicate i component generate active nucleus content, ni
It is i component molar score, υiIt is i volume components score, KiAt the end of being low temperature pre-flame reaction, pure component i generates turning for active nucleus
Rate, βiIt is the blending factor of i component；
The octane number computation model are as follows:
Model 3A:RON=aQac+b
Wherein, RON is octane number, QacIt is active nucleus conversion ratio, a, b, c are corrected parameters.
2. the method according to claim 1, wherein the model 1A and model 3A constitutes following octane number
Predict expression model:
Wherein, ONiFor each pure component octane number as known parameters, viIt is the molar fraction of i component, βiIt is needed back for model
The parameter returned.
3. the method according to claim 1, wherein
Wherein, βiIt is the blending factor of i component, ρiIt is the relative density of i component, MiIt is the relative molecular weight of component.
4. a kind of machine readable storage medium, it is stored with instruction on the machine readable storage medium, which is used for so that machine
Execute method described in any one of the application any of the above-described 1-3 claim.
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