CN107203832B - Supercharged diesel engine optimal EGR performance evaluation method based on subjective and objective weighting-multi-objective grey decision-grey correlation analysis - Google Patents

Supercharged diesel engine optimal EGR performance evaluation method based on subjective and objective weighting-multi-objective grey decision-grey correlation analysis Download PDF

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CN107203832B
CN107203832B CN201710222568.1A CN201710222568A CN107203832B CN 107203832 B CN107203832 B CN 107203832B CN 201710222568 A CN201710222568 A CN 201710222568A CN 107203832 B CN107203832 B CN 107203832B
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王银燕
祖象欢
崔欣洁
王贺春
杨传雷
周鹏程
金鑫
李宗营
马正茂
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Abstract

The invention aims to provide a supercharged diesel engine optimal EGR performance evaluation method based on subjective and objective weighting-multi-target grey decision-grey correlation analysis, which comprises the following steps of: performing initial modeling on the EGR decision problem by adopting a multi-target grey situation decision method; carrying out subjective assignment on the NOx index weight eta according to different working conditions of the diesel engine; solving a comprehensive weight vector by adopting an objective comprehensive weighting method, and solving a comprehensive evaluation value by adopting a method based on objective comprehensive weighting-multi-target grey decision; solving the correlation coefficient between the original machine and the test scheme by adopting grey correlation; and comprehensively solving the final evaluation value by using the comprehensive evaluation value and the association coefficient. The method can realize the decision of the optimal scheme only by inputting the specific data with the evaluation scheme into the model, and is suitable for online real-time evaluation and comprehensive evaluation of the EGR performance of the supercharged diesel engine.

Description

Supercharged diesel engine optimal EGR performance evaluation method based on subjective and objective weighting-multi-objective grey decision-grey correlation analysis
Technical Field
The invention relates to a diesel engine EGR rate decision method.
Background
Exhaust Gas Recirculation (EGR) is a main measure for reducing NOx emission of a diesel engine at present, and the implementation process of the EGR mainly comprises the steps of introducing a part of exhaust gas in exhaust gas into an air inlet pipe, mixing the exhaust gas with fresh air, and then introducing the mixture into a cylinder to participate in combustion again. The key point of the EGR technology is to make enough exhaust gas flow back to an air inlet pipe, so that the problem of difficult EGR exhaust gas flow back caused by the fact that the supercharging pressure is higher than the exhaust pressure under the high working condition of a supercharged diesel engine is solved, and the optimal EGR rate is given according to different working conditions of the engine.
Different EGR rates have different effects on the combustion and emissions performance of a diesel engine, and therefore the dynamics, economy, and emissions performance of a diesel engine must be considered when determining the optimum EGR rate. The NOx in the exhaust gas is reduced as much as possible, and the emission of other pollutants such as particles is influenced as little as possible. At present, the commonly adopted method is as follows: and obtaining the operating parameters of the engine through a large number of tests, and determining the optimal EGR rate under the test working condition by carrying out subjective comprehensive analysis on the test results. Wherein different researchers have adopted different determination principles in the comprehensive analysis. If the learner adopts the principle that the particulate matter at the 13 working condition points does not exceed the original engine, the learner selects a high EGR rate at a low load and selects a low EGR rate at a high load by considering the comprehensive factors of the increase degree of the oil consumption, the improvement degree of the NOx and the like on the basis that the PM does not exceed the original engine. The method has a common defect that the result is greatly different due to differences in subjective judgment of different researchers because of lack of clear theoretical guidance.
The EGR performance evaluation and the decision of the optimal EGR rate under different working conditions belong to a typical multi-objective decision problem. Therefore, the decision to introduce a multi-objective grey decision to achieve the optimal EGR rate is considered. The multi-target grey decision is taken as an important branch in the grey system theory, has unique advantages in the decision problem of selecting the best scheme from a plurality of schemes, and is widely applied to the fields of aerospace, electronic power and the like due to the characteristics of low calculation complexity and high recognition effect. However, due to the subjectivity of the weights in the traditional decision model, more and more scholars are intensively studying the optimization of the weights. The entropy weight method is a representative method in weight optimization. In addition, grey correlation analysis is a branch of grey system theory, which is very active, and its basic idea is to determine whether the connection between different sequences is tight according to the curve geometry of the sequences. The method mainly comprises the steps of converting discrete behavior observed values of system factors into piecewise continuous reading broken lines through a linear interpolation method, and further constructing a model for measuring the association degree according to the geometric characteristics of the broken lines, wherein the model is widely applied to multiple fields at present.
In summary, how to adopt a clear theory to guide the determination of the optimal EGR rate becomes a key problem for the optimization of the EGR performance, there is no clear theoretical guidance in the current publications, and therefore, it is necessary to intensively study the problem.
Disclosure of Invention
The invention aims to provide a supercharged diesel engine optimal EGR performance evaluation method based on subjective and objective weighting-multi-objective grey decision-grey correlation analysis, which effectively solves the problem of supercharged diesel engine optimal EGR rate decision.
The purpose of the invention is realized as follows:
the invention relates to a supercharged diesel engine optimal EGR performance evaluation method based on subjective and objective weighting, multi-target grey decision-grey correlation analysis, which is characterized by comprising the following steps of:
(1) performing initial modeling on the EGR decision problem by adopting a multi-target grey situation decision method;
(2) carrying out subjective assignment on the NOx index weight eta according to different working conditions of the diesel engine;
(3) solving a comprehensive weight vector by adopting an objective comprehensive weighting method, and solving a comprehensive evaluation value by adopting a method based on objective comprehensive weighting-multi-target grey decision;
(4) solving the correlation coefficient between the original machine and the test scheme by adopting grey correlation;
(5) and comprehensively solving the final evaluation value by using the comprehensive evaluation value and the association coefficient.
The present invention may further comprise:
1. performing initial modeling on the EGR decision problem by adopting a multi-target grey situation decision method, selecting EGR performance parameters including fuel consumption and oil consumption, in-cylinder explosion pressure, NOX, CO and carbon smoke as decision indexes, and constructing an effect sample matrix
Figure BDA0001264215050000021
Figure BDA0001264215050000022
Wherein n represents an EGR performance parameter, m represents different EGR rates, unmRepresenting the corresponding data values for different parameters at different EGR rates.
2. Measuring fuel consumption, cylinder internal explosion pressure, NOX, CO and soot by using lower limit effect
Figure BDA0001264215050000031
Thereby solving for consistent measure of effect
Figure BDA0001264215050000032
Figure BDA0001264215050000033
3. Carrying out subjective assignment on the NOx index weight eta according to different working conditions of the diesel engine:
if the rotating speed n of the diesel engine is less than 250r/min and the load is less than 50%, the weight eta of NOX is 0.3; if the rotation speed of the diesel engine is more than or equal to 250r/min and less than 500r/min, and the load is more than or equal to 50% and less than 75%, the weight eta of NOX is 0.4; and if the rotating speed n of the diesel engine is more than or equal to 500r/min and the load is not less than 75%, the weight eta of the NOx is 0.5.
4. The comprehensive weight vector is obtained by adopting an objective comprehensive weighting method, and the comprehensive evaluation value is solved by adopting a method based on objective comprehensive weighting-multi-target grey decision, and the method specifically comprises the following steps:
(1) constructing an evaluation index matrix
Figure BDA0001264215050000034
Will be provided with
Figure BDA0001264215050000035
Eliminating data corresponding to NOX parameters under different EGR rates, and forming an evaluation index matrix by the residual parameters
Figure BDA0001264215050000036
Where i represents different EGR rates, j represents an EGR performance parameter,
Figure BDA0001264215050000038
data values representing the correspondence of the residual performance parameters at different EGR rates;
(2) evaluating index matrix obtained by entropy weight method
Figure BDA0001264215050000039
Entropy weight of each decision target in the setk(k＝1,2,3…j)；
(3) According to the formula (1-eta). alphakSolving for the target weight ηk(k ═ 1,2,3 … j), constitutes the final weight vector ηk'＝(η,ηk)；
(4) The final weight vector etak' Resubstitute the initial model to solve the comprehensive evaluation value R.
5. Solving the correlation coefficient of the original machine and the test scheme by adopting grey correlation, which specifically comprises the following steps: taking original data of EGR performance parameters as a master sequence, taking index parameter sequences corresponding to the EGR rates as subsequences, and solving the association degree r of the master and subsequencei。
6. Comprehensively solving the final estimated value R R by the comprehensive estimated value and the correlation coefficientiAnd giving out the best EGR scheme according to the quality sequence.
7. Effect sample matrix
Figure BDA0001264215050000041
And an evaluation index matrix
Figure BDA0001264215050000042
The evaluation satisfied the following conditions: i.e. imax＝mmax,jmax＝nmax-1。
The invention has the advantages that:
(1) the EGR performance is evaluated by adopting a decision-making method based on subjective and objective weighting-multiple target grey situation, the whole method is based on test data of different EGR schemes, objective accuracy and effectiveness are guaranteed, and benefit and disadvantage relations among the schemes are searched through data mining and analysis, so that a good and bad ranking is obtained, and the defect of lack of theoretical support commonly existing in the current best EGR rate decision is overcome.
(2) The method adopts a decision-making method based on subjective and objective weighting-multi-target grey situation to evaluate the EGR performance, is different from the existing various decision-making methods, fully considers the characteristics and requirements of the optimization of the EGR performance, and is used as a limiting condition to optimize a mathematical model, so that the decision-making result is more consistent with the actual EGR performance change condition.
(3) And solving the correlation coefficient of the original machine and the test scheme by adopting grey correlation, thereby ensuring that other performance parameters are close to the original machine as far as possible while effectively reducing the NOX, and ensuring that the comprehensive performance reaches the best. The method is consistent with basic criteria commonly adopted by the current best EGR rate, but the difference is that the method replaces subjective judgment with a specific mathematical model, and the accuracy is greatly improved.
(4) The method is easy to realize, can realize the decision of the optimal scheme only by inputting the specific data with the evaluation scheme into the model, and is suitable for online real-time evaluation and comprehensive evaluation of the EGR performance of the supercharged diesel engine.
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FIG. 1 is a flow chart of the present invention.
Detailed Description
The invention will now be described in more detail by way of example with reference to the accompanying drawings in which:
with reference to fig. 1, the present invention comprises the following steps:
(1) main operation parameters of the supercharged diesel engine under different working conditions and different EGR rates are obtained through tests.
(2) And performing initial modeling on the EGR decision problem by adopting a multi-target grey situation decision method.
(3) And carrying out subjective assignment on the NOx index weight eta according to different working conditions of the diesel engine.
(4) And solving the comprehensive weight vector by adopting an subjective and objective comprehensive weighting method.
(5) And solving the comprehensive evaluation value by adopting a method based on subjective and objective comprehensive weighting-multi-target grey decision.
(6) And solving the correlation coefficient of the original machine and the test scheme by adopting grey correlation.
(7) And comprehensively solving the final evaluation value by using the comprehensive evaluation value and the association coefficient.
Performing initial modeling on EGR decision problems by adopting a multi-target grey situation decision method, selecting EGR main performance parameters as decision indexes and constructing an effect sample matrix
Figure BDA0001264215050000051
And solve measure of consistent effect
Figure BDA0001264215050000052
Figure BDA0001264215050000053
Where n represents an EGR performance parameter and m represents a different EGR strategy.
And carrying out subjective assignment on the NOx index weight eta according to different working conditions of the diesel engine.
If the working condition is low, the NOX weighted value eta is 0.3; if the diesel engine is in a medium working condition, enabling the NOX weighted value eta to be 0.4; and if the diesel engine is in a high working condition, the weighted value eta of the NOx is made to be 0.5.
And solving a comprehensive weight vector by adopting an objective and subjective comprehensive weighting method, and solving a comprehensive evaluation value by adopting a method based on objective and subjective comprehensive weighting-multi-target grey decision. The method specifically comprises the following steps:
(1) constructing an evaluation index matrix
Figure BDA0001264215050000054
Will be provided with
Figure BDA0001264215050000055
Removing NOX parameters from the selected operation parameters, and forming an evaluation index matrix by the residual parameters
Figure BDA0001264215050000056
Figure BDA0001264215050000057
Where i represents different EGR scenarios and j represents an EGR performance parameter.
(2) Evaluating index matrix obtained by entropy weight method
Figure BDA0001264215050000058
Entropy weight of each decision target in the setk。
(3) According to the formula (1-eta). alphakSolving the target weight to form a final weight vector etak。
(4) The final weight vector etakAnd substituting the initial model again to solve the comprehensive evaluation value.
And solving the correlation coefficient of the original machine and the test scheme by adopting grey correlation. The method specifically comprises the following steps: taking the original machine data of each index as a mother sequence, taking the index parameter sequence corresponding to each EGR scheme as a subsequence, and solving the association degree r of the mother sequence and the subsequencei。
Comprehensively solving the final estimated value R R by the comprehensive estimated value and the correlation coefficientiAnd giving out the best EGR scheme according to the quality sequence.
Effect sample matrix
Figure BDA0001264215050000061
And an evaluation index matrix
Figure BDA0001264215050000062
The evaluation satisfied the following conditions: i.e. imax＝mmax,jmax＝nmax-1。
The method is characterized by comprising the following steps of selecting test data of a TBD234V12 type sequential supercharged diesel engine, and verifying:
1) test data of 5 different EGR rates under 9 working conditions of a TBD234V12 type sequential supercharged diesel engine are respectively selected, the main parameters are fuel consumption and oil consumption, in-cylinder explosion pressure, NOX, CO and soot, and the specific test data are shown in Table 1.
Figure BDA0001264215050000063
TABLE 1 part Condition Point test data
2) And performing initial modeling on the EGR decision problem by adopting a multi-target grey situation decision method. Taking the OP1 working condition as an example, the method specifically comprises the following steps:
2.1) firstly determining a decision target, which is respectively as follows: fuel consumption, cylinder internal explosion pressure, NOX, CO and soot. Constructing an effect sample matrix
Figure BDA0001264215050000064
Figure BDA0001264215050000071
Wherein the abscissa n in the matrix represents the fuel consumption rate, CO, NOX, soot and in-cylinder detonation pressure in that order. The ordinate m represents the different EGR rates.
2.2) determining the effectiveness measure of the decision target. Since the smaller the selected decision targets, the better, the lower limit effect measure is selected for the effect measure, so that a consistent effect measure matrix under k targets can be obtained:
Figure BDA0001264215050000072
and 2.3) carrying out subjective assignment on the NOx index weight eta according to different working conditions of the diesel engine.
The main purpose of EGR is to reduce NOX emission, and the control of EGR rate must be adjusted with the requirements of different operating conditions, emission characteristics, economy and dynamics of the engine, and the basic principle is: in idle, warm-up and low load, in order to ensure the stability and economy of the diesel engine, EGR circulation is not adopted generally. Secondly, the lower EGR rate is suitable for the acceleration working condition. And thirdly, the EGR rate should be correspondingly increased along with the increase of the load of the diesel engine.
Therefore, the temperature of the molten metal is controlled,the basic principle is considered to be converted into an initial condition and introduced into an optimization decision model, and the size of the NOx index weight eta reflects the importance degree of EGR under the current working condition. If the diesel engine is in a medium-low working condition, making NOX decision weight value eta30.3; if the diesel engine is in a medium-high working condition, let eta3＝0.5。
In conclusion, η is the low operating condition because the operating condition is the low operating condition3＝0.3。
3) And solving the comprehensive weight vector by adopting an subjective and objective comprehensive weighting method. The method mainly comprises the following steps:
3.1) mixing
Figure BDA0001264215050000073
Removing NOX parameters from the selected operation parameters, and forming an evaluation index matrix by the residual parameters
Figure BDA0001264215050000074
Figure BDA0001264215050000081
Where i represents different EGR scenarios and j represents an EGR performance parameter.
In particular, the effect sample matrix
Figure BDA0001264215050000082
And an evaluation index matrix
Figure BDA0001264215050000083
The evaluation satisfied the following conditions: i.e. imax＝mmax,jmax＝nmax-1
3.2) using the entropy weight method
Figure BDA0001264215050000084
The entropy weight alpha of each decision target is remainedk(k is 1,2,3, 4). The entropy weights of the indexes obtained by calculation are respectively as follows: 0.3179,0.2252,0.2213,0.2355.
3.3) according to the formula (1-. eta.)3)·αkTo obtainThe weight of each decision target finally constitutes a final weight vector etak(k is 1,2,3,4, 5). The final decision target weight vector after optimization is:
ηk＝[0.2226，0.1577，0.3，0.1549，0.1649]。
and 3.4) solving the comprehensive evaluation value by adopting a method based on subjective and objective comprehensive weighting-multi-target grey decision. According to the formula
Figure BDA0001264215050000085
Obtaining an optimized comprehensive evaluation value:
r1＝[0.8866，0.9011，0.8964，0.8575，0.7971]
4) and solving the correlation coefficient of the original machine and the test scheme by adopting grey correlation.
4.1) making the original machine data corresponding to each parameter as an original sequence, also called as a mother sequence:
X0(t)＝{x0(1),x0(2),…,x0(n)}
and (3) making the test data sequence corresponding to each scheme be a data sequence to be compared, also called a subsequence:
Xi(t)＝{xi(1),xi(2),…,xi(n)}
4.2) noting xii(k) Is a sequence X0(t) and Xi(t) correlation coefficient at time k:
Figure BDA0001264215050000086
wherein
Figure BDA0001264215050000087
And
Figure BDA0001264215050000088
respectively, that the two-level minimum difference is | x0(k)-xi(k) The two-level maximum difference and the two-level minimum difference of | are obtained; where 0.5 is the resolution factor, which is usually selected between 0 and 1.
4.3) calculating the sequence Xi(t) each timeAverage value of correlation coefficient, i.e. subsequence Xi(t) for the mother sequence X0Degree of association of (t):
Figure BDA0001264215050000091
in conclusion, the correlation coefficient between each EGR scheme and the original machine is obtained:
r2＝[0.1981,0.2090,0.2046,0.1953,0.1930]
5) and combining the evaluation value and the association coefficient to comprehensively solve the final evaluation value r which is r1 r 2.
r＝[0.1756，0.1884，0.1834，0.1674，0.1538]
6) And (4) sorting the advantages and the disadvantages of different EGR schemes according to an optimal decision principle, and obtaining the optimal EGR rate.
From 5) the results show that the evaluation value represents the quality degree of each scheme, and the final quality ranking is as follows: 4.6% > 8.6% > 1.4% > 10.4% > 11.6. The most estimated value is the optimal scheme, namely the optimal EGR rate under the current working condition is 4.6%, namely a smaller EGR rate is preferably adopted, which is consistent with the traditional optimal EGR rate selection principle.
Similarly, the final estimates for operating points OP2 and OP3 may be found:
OP2：
r＝[0.1838，0.1834，0.1801，0.1811，0.1618]
OP3：
r＝[0.1756，0.1766，0.1848，0.1797，0.1596]
from the results, the optimum EGR rates under operating conditions OP2 and OP3 were 0.8% and 8.7%, respectively. OP2 is low, and a smaller EGR rate is suitable; and OP3 belongs to the medium-high working condition, and the EGR rate is preferably increased, which is consistent with the conventional decision principle, and the effectiveness and feasibility of the method provided by the invention are also demonstrated.

Claims (1)

1. The supercharged diesel engine optimal EGR performance evaluation method based on subjective and objective weighting, multi-objective grey decision-grey correlation analysis is characterized by comprising the following steps of:
(1) performing initial modeling on the EGR decision problem by adopting a multi-target grey situation decision method;
(2) according to different working conditions of the diesel engine to NOXSubjective assignment is carried out on the index weight eta;
(3) solving a comprehensive weight vector by adopting an objective comprehensive weighting method, and solving a comprehensive evaluation value by adopting a method based on objective comprehensive weighting-multi-target grey decision;
(4) solving the correlation coefficient between the original machine and the test scheme by adopting grey correlation;
(5) comprehensively solving the final evaluation value by the comprehensive evaluation value and the association coefficient;
performing initial modeling on the EGR decision problem by adopting a multi-target grey situation decision method, and selecting EGR performance parameters including fuel consumption and oil consumption, in-cylinder explosion pressure and NOXCO and soot as decision indexes and constructing effect sample matrix
Figure FDA0002766960410000011
Figure FDA0002766960410000012
Wherein n represents an EGR performance parameter, m represents different EGR rates, unmData values representing the correspondence of different parameters at different EGR rates;
fuel consumption, cylinder detonation pressure, NOXLower limit effect measure for CO and soot
Figure FDA0002766960410000013
Thereby solving for consistent measure of effect
Figure FDA0002766960410000014
Figure FDA0002766960410000015
According to the difference of the diesel engineOperating condition to NOXAnd subjectively assigning the index weight eta:
if the rotating speed n of the diesel engine is less than 250r/min and the load is less than 50 percent, NO is determinedXThe weighted value eta is 0.3; if the rotation speed of the diesel engine is more than or equal to 250r/min and less than or equal to n and less than 500r/min and the load is more than or equal to 50% and less than 75%, NO is determinedXThe weighted value eta is 0.4; if the rotating speed n of the diesel engine is more than or equal to 500r/min and the load is not less than 75 percent, NO is addedXThe weighted value eta is 0.5;
the comprehensive weight vector is obtained by adopting an objective comprehensive weighting method, and the comprehensive evaluation value is solved by adopting a method based on objective comprehensive weighting-multi-target grey decision, and the method specifically comprises the following steps:
(1) constructing an evaluation index matrix
Figure FDA0002766960410000021
Will be provided with
Figure FDA0002766960410000022
NO at medium to different EGR ratesXEliminating data corresponding to the parameters, and forming an evaluation index matrix by the residual parameters
Figure FDA0002766960410000023
Figure FDA0002766960410000024
Where i represents different EGR rates, j represents an EGR performance parameter,
Figure FDA0002766960410000025
data values representing the correspondence of the residual performance parameters at different EGR rates;
(2) evaluating index matrix obtained by entropy weight method
Figure FDA0002766960410000026
Entropy weight of each decision target in the setk(k＝1,2,3…j)；
(3) According to the formula (1-eta). alphakSolving for objective weightsWeight ηk(k ═ 1,2,3 … j), constitutes the final weight vector ηk'＝(η,ηk)；
(4) Using the final weight vector ηk' and measure of consistent effects
Figure FDA0002766960410000027
Solving a comprehensive evaluation value R;
solving the correlation coefficient of the original machine and the test scheme by adopting grey correlation, which specifically comprises the following steps: taking the EGR performance parameter sequence of the original machine as a parent sequence, taking the performance parameter sequence corresponding to each EGR rate as a subsequence, and solving the association degree r of the parent sequence and the subsequencei；
Comprehensively solving the final estimated value R R by the comprehensive estimated value and the correlation coefficientiGiving an optimal EGR scheme according to the quality sequence;
effect sample matrix
Figure FDA0002766960410000028
And an evaluation index matrix
Figure FDA0002766960410000029
The evaluation satisfied the following conditions: i.e. imax＝mmax,jmax＝nmax-1。
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