CN107092723B - Automatic calibration method for empirical parameters of double weber combustion rules - Google Patents

Automatic calibration method for empirical parameters of double weber combustion rules Download PDF

Info

Publication number
CN107092723B
CN107092723B CN201710176934.4A CN201710176934A CN107092723B CN 107092723 B CN107092723 B CN 107092723B CN 201710176934 A CN201710176934 A CN 201710176934A CN 107092723 B CN107092723 B CN 107092723B
Authority
CN
China
Prior art keywords
combustion
data
weber
separation point
double
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201710176934.4A
Other languages
Chinese (zh)
Other versions
CN107092723A (en
Inventor
王银燕
胡松
王贺春
杨传雷
袁帅
周鹏程
刘晓梅
吕游
杨鹏
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Harbin Engineering University
Original Assignee
Harbin Engineering University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Harbin Engineering University filed Critical Harbin Engineering University
Priority to CN201710176934.4A priority Critical patent/CN107092723B/en
Publication of CN107092723A publication Critical patent/CN107092723A/en
Application granted granted Critical
Publication of CN107092723B publication Critical patent/CN107092723B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/10—Numerical modelling

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Hardware Design (AREA)
  • Evolutionary Computation (AREA)
  • Geometry (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Combined Controls Of Internal Combustion Engines (AREA)

Abstract

The invention aims to provide an automatic calibration method for empirical parameters of a double weber combustion rule. The method comprises the steps of firstly obtaining a combustion phase separation point by adopting a combustion phase separation point determining method, dividing burned fraction test data into two parts and carrying out corresponding processing, respectively obtaining a preliminary Weber parameter estimation value by adopting algebraic analysis on the two parts of data, and then obtaining a final estimation value by adopting a least square algorithm. The invention combines an algebraic analysis method and a least square algorithm, complements the advantages and disadvantages of the algebraic analysis method and the least square algorithm, realizes the automatic calibration of the empirical parameters of the combustion rule of the double weber (Wiebe), has better convergence and stability and higher accuracy during the parameter calibration, and can quickly and accurately build a zero-dimensional combustion model based on the combustion rule of the double weber (Wiebe).

Description

Automatic calibration method for empirical parameters of double weber combustion rules
Technical Field
The invention relates to a method for acquiring a combustion rule of an internal combustion engine.
Background
In order to solve the increasingly serious environmental pollution problem, international emission regulations are increasingly strict, and harmful emissions of engines are limited, so that manufacturers are particularly important to control the emissions of the engines. The emission characteristic of the diesel engine is closely related to the combustion process in the cylinder, so that the realization of real-time control of the combustion process has important significance for the emission control of the engine. With the rapid development of computer technology, the computer simulation technology has vigorous vitality, a system model is abstracted through abstract simulation of a real system, and people carry out simulation test research on the model on a computer, so that the scientific research and production cost is reduced, the risk is reduced, and the scientific research efficiency is also improved. The reliability and accuracy of the system model directly determine the reliability and accuracy of the simulation result. In the field of internal combustion engines, a zero-dimensional combustion model based on a Weber (Wiebe) combustion rule is simple in form and small in modeling difficulty, and meanwhile, certain simulation accuracy is achieved within a certain working condition range. Based on the Weber Wiebe) combustion model, a plurality of researchers successfully predict the pressure and the temperature in a cylinder of a direct injection diesel engine, a non-direct injection diesel engine and a two-stroke diesel engine. Research shows that a single weber (Wiebe) combustion rule is only suitable for simulating a combustion process with one combustion phase or two slightly-mixed combustion phases, better simulation cannot be achieved for a combustion process with obviously two mixed combustion phases, and a double weber (Wiebe) combustion rule can better simulate a combustion process with two mixed combustion phases. Weber Wiebe) combustion rule empirical parameters directly influence the accuracy of a weber (Wiebe) combustion model, and there are documents which research how to calibrate the empirical parameters of the weber (Wiebe) combustion model, such as an algebraic analysis method and a least square algorithm, but the algebraic analysis method and the least square algorithm have advantages and disadvantages. The stability of the calibration parameter is good, an initial value does not need to be given, but the optimality of the calibration parameter cannot be guaranteed; the latter may guarantee local optimality of the calibration parameters, but convergence and calibration results depend on the given initial values. Therefore, the two methods are necessary to be considered to be combined, so that the advantages and the disadvantages of the two methods are complementary, and finally, the weber combustion rule empirical parameters are calibrated quickly and accurately. For the combustion process with obvious mixing of two combustion phases, how to automatically calibrate and obtain the double weber (Wiebe) combustion rule empirical parameters is very critical.
Disclosure of Invention
The invention aims to provide a double-Weber combustion rule empirical parameter automatic calibration method for accurately and automatically calibrating relevant parameters based on burned fraction test data.
The purpose of the invention is realized as follows:
the invention discloses a method for automatically calibrating empirical parameters of a double-Weber combustion rule, which is characterized by comprising the following steps of:
(1) performing combustion test on the diesel engine, collecting the burned fraction test data,
Figure GDA0002606996780000021
is the angle of crankshaft rotation, xbIs a sum of
Figure GDA0002606996780000022
Corresponding fraction burned, combustion fitting start angle
Figure GDA0002606996780000023
Taking a crank angle corresponding to 1% of burned fraction and a combustion fitting end point angle
Figure GDA0002606996780000024
Taking the crank angle corresponding to 99% of the burned fraction and extracting
Figure GDA0002606996780000025
Experimental data of (2) in (d)
Figure GDA0002606996780000026
(2) According to
Figure GDA0002606996780000027
Is calculated to obtain
Figure GDA0002606996780000028
And
Figure GDA0002606996780000029
preliminary estimate of (2)
Figure GDA00026069967800000210
And
Figure GDA00026069967800000211
wherein
Figure GDA00026069967800000212
Figure GDA00026069967800000213
The corresponding crank angle when the burned fraction is zero, if the burned fraction test data is always greater than zero, the corresponding crank angle of the data starting point is taken as
Figure GDA00026069967800000214
Linearize the simple Weber equation
Figure GDA00026069967800000215
Realize the test data sequence
Figure GDA00026069967800000216
Is linearized, the linearized data sequence is
Figure GDA00026069967800000217
(3) For data sequence
Figure GDA00026069967800000218
Deriving the combustion phase separation point p by combustion phase separation point determination, i.e. finding a point p such that it is before and after this point
Figure GDA00026069967800000219
And
Figure GDA00026069967800000220
comprehensive R for respectively carrying out linear fitting on data2The precision reaches the maximum;
(4) sequencing the fractional burn test data according to the separation point p
Figure GDA00026069967800000221
Divided into two parts, i.e.
Figure GDA00026069967800000222
And
Figure GDA00026069967800000223
wherein
Figure GDA00026069967800000224
x1b＝[xb(1),xb(2),…,xb(p)]，
Figure GDA00026069967800000225
x2b＝[xb(p+1),xb(p+2),…,xb(n)]；
Figure GDA00026069967800000226
α0＝xb(p) as an initial value of premixed combustion ratio, and for x1bAnd x2bAnd (3) carrying out normalization treatment:
Figure GDA00026069967800000227
Figure GDA00026069967800000228
order to
Figure GDA00026069967800000229
Figure GDA00026069967800000320
Respectively realize that
Figure GDA0002606996780000032
And
Figure GDA0002606996780000033
linearization, pair
Figure GDA0002606996780000034
And
Figure GDA0002606996780000035
respectively carrying out linear fitting on the two parts of data sequences to respectively obtain fitting slopes A1And A2From m10＝A1-1、m20＝A 21 gives m10And m20Wherein m10And m20Respectively setting a premixed combustion index initial value and a diffusion combustion index initial value; at alpha0、m10、
Figure GDA0002606996780000036
m20、
Figure GDA0002606996780000037
And
Figure GDA0002606996780000038
respectively as alpha, m1,
Figure GDA0002606996780000039
m2、
Figure GDA00026069967800000310
And
Figure GDA00026069967800000311
the initial iteration value of the method is fitted by adopting a nonlinear least square algorithm to obtain alpha, m1,
Figure GDA00026069967800000312
m2、
Figure GDA00026069967800000313
And
Figure GDA00026069967800000314
is estimated.
(5) And outputting a double weber equation parameter set, and automatically calibrating to obtain the empirical parameters of the double weber (Wiebe) combustion rule.
The present invention may further comprise:
1. the method for acquiring the combustion phase separation point p comprises the following steps:
suppose that the data separation point i separates the data sequence
Figure GDA00026069967800000315
Divided into two parts, the part before the ith data is
Figure GDA00026069967800000316
Sections following the ith dataIs divided into
Figure GDA00026069967800000317
To pair
Figure GDA00026069967800000318
And
Figure GDA00026069967800000319
respectively carrying out linear fitting, wherein the linear fitting precision of the two parts of data is R2 1And R2 2Comprehensive accuracy R2Is defined as R2(i)＝[R2 1×i+R2 2×(n-i)]N, where n is the total number of data, the data separation point i can be changed from 1 to n, and the comprehensive precision R can be respectively obtained in sequence2Then get the integrated precision R2The data separation point i at which the maximum value is reached is taken as the combustion phase separation point p.
The invention has the advantages that: the invention finally realizes a method for rapidly and accurately automatically calibrating to obtain the double-weber combustion rule empirical parameters by adopting an original double-weber (Wiebe) combustion rule empirical parameter automatic calibration method based on the weber (Wiebe) combustion rule and the burned fraction test data. The automatic calibration method for the combustion rule empirical parameters of the double weber (Wiebe) combustion rules determines the combustion phase separation point by adopting an original combustion phase separation method, combines an algebraic analysis method and a least square algorithm to complement the advantages and the disadvantages of the two methods, realizes the automatic calibration of the combustion rule empirical parameters of the double weber (Wiebe), has better convergence and stability and higher accuracy during parameter calibration, and provides great convenience for the researchers in the industry to calibrate the combustion rule empirical parameters of the double weber (Wiebe).
Drawings
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:
referring to FIG. 1, first, the ignition start point test value is used as the estimated value of the combustion start point
Figure GDA0002606996780000041
To be provided with
Figure GDA0002606996780000042
As duration of combustion
Figure GDA0002606996780000043
The estimated value of the fuel fraction test data is subjected to linear processing according to a Weber (Wiebe) equation; the method comprises the steps of firstly obtaining a combustion phase separation point by adopting a combustion phase separation point determining method provided by the invention for processed test data, secondly dividing the test data into two parts according to the combustion phase separation point, respectively carrying out corresponding processing on the two parts of data, then respectively obtaining a primary estimated value of combustion rule empirical parameters of the double weber (Wiebe) by adopting an algebraic analysis method for the two parts of data after processing, and finally obtaining a final estimated value of the combustion rule empirical parameters of the double weber (Wiebe) by adopting a nonlinear least square algorithm for calibration.
The method for automatically calibrating the combustion rule empirical parameters of double weber (Wiebe) comprises the following calculation processes:
the method comprises the following steps: introduction of measured fractional burn test data sequences
Figure GDA0002606996780000044
Wherein
Figure GDA0002606996780000045
Is the angle of crankshaft rotation, xbIs a sum of
Figure GDA0002606996780000046
Corresponding fraction burned, combustion fitting start angle
Figure GDA0002606996780000047
Taken to an as-burnt fraction x of slightly more than 0 (preferably 1%)bCorresponding crankshaft angle, combustion fitting end angle
Figure GDA0002606996780000048
Taking the burned fraction x to be slightly less than 1 (preferably 99%)bCorrespond toAnd crank angle of (2), and extracting
Figure GDA0002606996780000049
Experimental data of (2) in (d)
Figure GDA00026069967800000410
Step two: test data series based on fraction burned
Figure GDA00026069967800000411
First, it is calculated to obtain
Figure GDA00026069967800000412
And
Figure GDA00026069967800000413
preliminary estimate of (2)
Figure GDA00026069967800000414
And
Figure GDA00026069967800000415
wherein
Figure GDA00026069967800000416
Figure GDA00026069967800000417
The crank angle corresponding to zero burned fraction (for improving the applicability and stability of the method, if the burned fraction test data is always greater than zero, the crank angle corresponding to the data starting point is used as
Figure GDA00026069967800000418
). Linearize the simple Weber equation
Figure GDA00026069967800000419
Figure GDA00026069967800000420
Realize the test data sequence
Figure GDA00026069967800000421
Is linearized, the linearized data sequence is
Figure GDA00026069967800000422
Step three: for data sequence
Figure GDA00026069967800000423
And obtaining a combustion phase separation point p by adopting a combustion phase separation point determination method. Suppose that the data separation point i separates the data sequence
Figure GDA00026069967800000424
Divided into two parts, the part before the ith data is
Figure GDA00026069967800000425
The portion following the ith data is
Figure GDA00026069967800000426
To pair
Figure GDA00026069967800000427
And
Figure GDA00026069967800000428
respectively carrying out linear fitting, wherein the linear fitting precision of the two parts of data is R2 1And R2 2Comprehensive accuracy R2The definition is shown in the following formula, wherein n is the total number of data, the data separation point i can be changed from 1 to n, and the comprehensive precision R can be respectively obtained in turn2Then get the integrated precision R2The data separation point i at which the maximum value is reached is taken as the combustion phase separation point p.
R2(i)＝[R2 1×i+R2 2×(n-i)]/n
Step four: fractional burn test data series based on combustion phase separation point p
Figure GDA0002606996780000051
Divided into two parts, i.e.
Figure GDA0002606996780000052
And
Figure GDA0002606996780000053
wherein
Figure GDA0002606996780000054
x1b＝[xb(1),xb(2),…,xb(p)]，
Figure GDA0002606996780000055
x2b＝[xb(p+1),xb(p+2),…,xb(n)]。
Figure GDA0002606996780000056
Figure GDA0002606996780000057
α0＝xb(p) as an initial value of premixed combustion ratio, and for x1bAnd x2bAnd (3) carrying out normalization treatment:
Figure GDA0002606996780000058
order to
Figure GDA0002606996780000059
Figure GDA00026069967800000510
Respectively realize that
Figure GDA00026069967800000511
And
Figure GDA00026069967800000512
linearization, pair
Figure GDA00026069967800000513
And
Figure GDA00026069967800000514
respectively carrying out linear fitting on the two parts of data sequences to respectively obtain fitting slopes A1And A2From m10＝A1-1、m20＝A 21 gives m10And m20Wherein m10And m20Respectively setting a premixed combustion index initial value and a diffusion combustion index initial value; both a1 and a2 are preferably constant values of 4.605 (not limited to 4.605) corresponding to a fractional burn period of 0% to 99% as a combustion efficiency factor. At alpha0、m10、
Figure GDA00026069967800000515
m20、
Figure GDA00026069967800000523
And
Figure GDA00026069967800000517
respectively as alpha, m1,
Figure GDA00026069967800000518
m2、
Figure GDA00026069967800000524
And
Figure GDA00026069967800000525
the initial iteration value of the method is fitted by adopting a nonlinear least square algorithm to obtain alpha, m1,
Figure GDA00026069967800000521
m2、
Figure GDA00026069967800000526
And
Figure GDA00026069967800000527
is estimated.
Step five: and outputting the double weber equation parameter set.
So far, according to the measured test data, the empirical parameters of the combustion rule of the double weber (Wiebe) can be automatically calibrated.
The specific principle of the automatic calibration method for the combustion rule empirical parameters of the double weber (Wiebe) is as follows:
the simple weber equation is shown in equation (3).
Figure GDA0002606996780000061
In the formula, xbAs a percentage of fuel burned; m is a combustion quality index; a is a combustion efficiency factor;
Figure GDA0002606996780000062
-an instantaneous crank angle;
Figure GDA0002606996780000063
-duration of combustion;
Figure GDA0002606996780000064
-the start of combustion.
For the
Figure GDA0002606996780000065
From xbDetermining the corresponding crank angle when the crank angle is 0; for the
Figure GDA0002606996780000066
From xbThe crankshaft rotation angle period corresponding to 0-0.99 is determined.
Crank angle corresponding to 50% heat release
Figure GDA0002606996780000067
As the combustion center, corresponding to equation (3), is:
Figure GDA0002606996780000068
finishing to obtain:
Figure GDA0002606996780000069
converting formula (5) to:
Figure GDA00026069967800000610
from equation (6), m can be calculated by calculating the slopes of G and H.
Suppose the combustion fit starting point is xbsCorresponding to a crank angle of
Figure GDA00026069967800000611
Combustion fit endpoint of xbcCorresponding to a crank angle of
Figure GDA00026069967800000612
This can be derived from equation (3):
Figure GDA00026069967800000613
when the combustion duration is selected to be a crank angle period corresponding to 0-99% of the burned fraction,
Figure GDA00026069967800000614
as can be seen from equation (7), a will be different for different combustion durations and m. The present invention a is preferably 4.605.
Converting the single weber combustion rule of formula (3) into:
Figure GDA00026069967800000615
for a direct injection diesel engine, a premixed combustion mode exists more or less in the combustion process except for a diffusion combustion mode, and it is very critical to find a separation point of the premixed combustion mode and the diffusion combustion mode for the convenience of parameter calibration of a double weber equation. The software takes an original approach to determining the combustion mode split point and the validation algorithm is described below.
From the formula (8) it can be seen that m isThe size may reflect how fast the combustion process is. For the premixed combustion mode, the combustion speed is higher, so m is smaller; for the diffusion combustion mode, the combustion speed is slow, so m is large. The combustion mode separation point is the integrated R which finds a point so that the G and K data before and after the point are respectively subjected to line fitting2The accuracy reaches the maximum. Assume that a linear fit of R is applied to G and K before this point (the p-th data point)2Accuracy is R2 1G and K after this point are R with a linear fit2Accuracy is R2 2Define the general formula R2(p) precision is:
Figure GDA0002606996780000071
then, take R2And (p) is the maximum value, and the corresponding p is the combustion mode separation point to be found.
The fractional burn test data is divided into two parts according to the data split point p,
Figure GDA0002606996780000072
x1b＝xb(1:p)，
Figure GDA0002606996780000073
x2b＝xb(p+1:end)，
Figure GDA0002606996780000074
Figure GDA0002606996780000075
α0＝xb(p) and x1bAnd x2bAnd (3) processing:
Figure GDA0002606996780000076
respectively carrying out algebraic analysis on the processed two-dialing data to obtain m,
Figure GDA0002606996780000077
And
Figure GDA0002606996780000078
as an initial value of the iteration of the least-squares algorithm.
The least squares algorithm is commonly used for the nonlinear equation fitting problem, the theory of which is described below.
Given n pairs of independent and dependent variablesi,yi) The parameter set to be determined is β, the fitting equation chosen is p (x, β), and therefore the sum of the squares of the errors is:
Figure GDA0002606996780000079
the least squares algorithm is to obtain a set of β such that S (β) is minimal.
The preferred least squares algorithm of the present invention is the Levenberg-Marquardt algorithm. The algorithm calculation starts with an initial value that requires a parameter set β to be calibrated to be given. Thereafter, the newly estimated value β + is substituted at each iteration step β. To determine, equation p (x)iβ +) was estimated linearly:
p(xi,β+)＝p(xi,β)+Ji(11)
in the formula
Figure GDA00026069967800000710
Is a gradient with respect to β. When S (β) reaches the minimum, the gradient of the S (β) pair becomes 0. According to equation (11), the first order estimate of equation (10) is as follows:
Figure GDA0002606996780000081
expressed in vector form as:
S(β+)≈||y-f(β)-J||2(13)
equation (13) derives J and makes the derivative function zero, which yields:
(JTJ)＝JT[y-f(β)](14)
the Levenberg-Marquardt algorithm improves upon equation (14) to the following equation:
(JTJ+λI)＝JT[y-f(β)](15)
in the formula, I is an identity matrix, and λ is a damping coefficient, which is used to adjust the step length of each iteration. When lambda is zero, the formula (15) is reduced to the formula (14) which is a Gauss-Newton algorithm; when λ is large, equation (15) degenerates to the gradient descent algorithm.
For increasing the convergence rate of equation (15), J is used for equation (15)TJ instead of I, the final Levenberg-Marquardt algorithm is shown below:
(JTJ+λdiag(JTJ))＝JT[y-f(β)](16)
the initial value of the parameter to be calibrated needs to be given when the least square algorithm starts to calculate, the convergence and iterative computation time of the least square algorithm are strong in dependence on the initial value, the final result cannot guarantee global optimality, and only local optimality can be guaranteed, so that the key point is to give a reasonable initial value. The invention adopts an algebraic analysis method to calculate the weber empirical parameters according to the test data as the initial values of the least square algorithm, and then carries out further iterative calculation, thus not only ensuring the optimality of the calibration result, but also improving the convergence of the least square method to a great extent and reducing the iterative calculation time.

Claims (2)

1. The automatic calibration method of the empirical parameters of the double weber combustion rule is characterized by comprising the following steps:
(1) performing combustion test on the diesel engine, collecting the burned fraction test data,
Figure FDA0002457949290000011
is the angle of crankshaft rotation, xbIs a sum of
Figure FDA0002457949290000012
Corresponding fraction burned, combustion fitting start angle
Figure FDA0002457949290000013
Taking a crank angle corresponding to 1% of burned fraction and a combustion fitting end point angle
Figure FDA0002457949290000014
Taking the crank angle corresponding to 99% of the burned fraction and extracting
Figure FDA0002457949290000015
Experimental data of (2) in (d)
Figure FDA0002457949290000016
(2) According to
Figure FDA0002457949290000017
Is calculated to obtain
Figure FDA0002457949290000018
And
Figure FDA0002457949290000019
preliminary estimate of (2)
Figure FDA00024579492900000110
And
Figure FDA00024579492900000111
wherein
Figure FDA00024579492900000112
Figure FDA00024579492900000113
The corresponding crank angle when the burned fraction is zero, if the burned fraction test data is always greater than zero, the corresponding crank angle of the data starting point is taken as
Figure FDA00024579492900000114
Linearize the simple Weber equation
Figure FDA00024579492900000115
To realize the testData sequence
Figure FDA00024579492900000116
Is linearized, the linearized data sequence is
Figure FDA00024579492900000117
(3) For data sequence
Figure FDA00024579492900000118
Deriving the combustion phase separation point p by combustion phase separation point determination, i.e. finding a point p such that it is before and after this point
Figure FDA00024579492900000119
And
Figure FDA00024579492900000120
comprehensive precision R for respectively carrying out linear fitting on data2The maximum is reached;
(4) sequencing the fractional burn test data according to the separation point p
Figure FDA00024579492900000121
Divided into two parts, i.e.
Figure FDA00024579492900000122
And
Figure FDA00024579492900000123
wherein
Figure FDA00024579492900000124
x1b＝[xb(1),xb(2),…,xb(p)]，
Figure FDA00024579492900000125
x2b＝[xb(p+1),xb(p+2),…,xb(n)]；
Figure FDA00024579492900000126
Figure FDA00024579492900000127
α0＝xb(p) as an initial value of premixed combustion ratio, and for x1bAnd x2bAnd (3) carrying out normalization treatment:
Figure FDA00024579492900000128
Figure FDA00024579492900000129
order to
Figure FDA00024579492900000130
Figure FDA00024579492900000131
Respectively realize that
Figure FDA00024579492900000132
And
Figure FDA00024579492900000133
linearization, pair
Figure FDA0002457949290000021
And
Figure FDA0002457949290000022
respectively carrying out linear fitting on the two parts of data sequences to respectively obtain fitting slopes A1And A2From m10＝A1-1、m20＝A21 gives m10And m20Wherein m10And m20Respectively setting a premixed combustion index initial value and a diffusion combustion index initial value; at alpha0、m10、
Figure FDA0002457949290000023
m20、
Figure FDA0002457949290000024
And
Figure FDA0002457949290000025
respectively as alpha, m1,
Figure FDA0002457949290000026
m2、
Figure FDA0002457949290000027
And
Figure FDA0002457949290000028
the initial iteration value of the method is fitted by adopting a nonlinear least square algorithm to obtain alpha, m1,
Figure FDA0002457949290000029
m2、
Figure FDA00024579492900000210
And
Figure FDA00024579492900000211
the final estimate of (d);
(5) and outputting the double weber equation parameter set, and automatically calibrating to obtain the empirical parameters of the double weber Wieb combustion rule.
2. The method for automatically calibrating the empirical parameters of the dual weber combustion rule of claim 1, wherein: the method for acquiring the combustion phase separation point p comprises the following steps:
suppose that the data separation point i separates the data sequence
Figure FDA00024579492900000212
Divided into two parts, the part before the ith data is
Figure FDA00024579492900000213
The portion following the ith data is
Figure FDA00024579492900000214
To pair
Figure FDA00024579492900000215
And
Figure FDA00024579492900000216
respectively carrying out linear fitting, wherein the linear fitting precision of the two parts of data is R2 1And R2 2Comprehensive accuracy R2Is defined as R2(i)＝[R2 1×i+R2 2×(n-i)]N, where n is the total number of data, the data separation point i can be changed from 1 to n, and the comprehensive precision R can be respectively obtained in sequence2Then get the integrated precision R2The data separation point i at which the maximum value is reached is taken as the combustion phase separation point p.
CN201710176934.4A 2017-03-22 2017-03-22 Automatic calibration method for empirical parameters of double weber combustion rules Active CN107092723B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201710176934.4A CN107092723B (en) 2017-03-22 2017-03-22 Automatic calibration method for empirical parameters of double weber combustion rules

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201710176934.4A CN107092723B (en) 2017-03-22 2017-03-22 Automatic calibration method for empirical parameters of double weber combustion rules

Publications (2)

Publication Number Publication Date
CN107092723A CN107092723A (en) 2017-08-25
CN107092723B true CN107092723B (en) 2020-11-03

Family

ID=59646229

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201710176934.4A Active CN107092723B (en) 2017-03-22 2017-03-22 Automatic calibration method for empirical parameters of double weber combustion rules

Country Status (1)

Country Link
CN (1) CN107092723B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108918588B (en) * 2018-04-02 2021-06-01 广西玉柴机器股份有限公司 Method for simulating combustion state of high-pressure common-rail diesel engine

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2007248119A (en) * 2006-03-14 2007-09-27 Toyota Motor Corp Method for determining wiebe function parameter and device for presuming heat release rate of internal combustion engine
CN101809265A (en) * 2007-09-25 2010-08-18 丰田自动车株式会社 Control apparatus and control method for internal combustion engine
CN102518521A (en) * 2011-12-27 2012-06-27 大连理工大学 Torque estimation method for vehicle engine

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2007248119A (en) * 2006-03-14 2007-09-27 Toyota Motor Corp Method for determining wiebe function parameter and device for presuming heat release rate of internal combustion engine
CN101809265A (en) * 2007-09-25 2010-08-18 丰田自动车株式会社 Control apparatus and control method for internal combustion engine
CN102518521A (en) * 2011-12-27 2012-06-27 大连理工大学 Torque estimation method for vehicle engine

Also Published As

Publication number Publication date
CN107092723A (en) 2017-08-25

Similar Documents

Publication Publication Date Title
CN105209984B (en) For the method for the model for determining technological system output valve
JP2011106334A (en) Method of estimating heat release rate of engine using wiebe function model
Grill et al. Quasi-dimensional and empirical modeling of compression-ignition engine combustion and emissions
CN109282916B (en) Method and device for predicting highest surface temperature of piston of dual-fuel engine
US6256575B1 (en) Process for controlling an internal combustion engine
CN106908248A (en) The double regular empirical parameter automatic calibrating methods of weber burning of self-identifying list
CN107092723B (en) Automatic calibration method for empirical parameters of double weber combustion rules
CN113191071B (en) Method for virtually calibrating engine model and related device thereof
US20090204376A1 (en) Method for measuring a nonlinear dynamic real system
Sjerić New physically based sub-models for the cycle-simulation of spark-ignition engine
JP4042492B2 (en) Method and system for adapting engine control parameters
Stoeck et al. Application of the polynomial interpolation method for determining performance characteristics of a diesel engine
Al-Durra et al. A model-based methodology for real-time estimation of diesel engine cylinder pressure
Schilling et al. Model-based detection and isolation of faults due to ageing in the air and fuel paths of common-rail direct injection diesel engines equipped with a λ and a nitrogen oxides sensor
CN106960092B (en) Automatic calibration method for Weber combustion rule empirical parameters
Lian et al. Fast computation of combustion phasing and its influence on classifying random or deterministic patterns
CN108021739B (en) Method for analyzing influence degree of parameters of real-time simulation model of high-power military diesel engine
CN116258082A (en) Working medium thermodynamic property calculation method and system based on RBF neural network
JP2010513784A (en) Simulation method and apparatus for operation of an internal combustion engine
CN112883653B (en) Artificial intelligence-based modeling method for real-time engine model
US10612477B2 (en) Method for calculating a residual gas mass in a cylinder of an internal combustion engine and controller
US20220381196A1 (en) Method and system for calibrating a controller of an engine
Keuth et al. DoE and beyond: the evolution of the model based develop-ment approach how legal trends are changing methodology
US20190153969A1 (en) System and method for emissions determination and correction
Varsha et al. Global COR iDOE Methodology: An Efficient Way to Calibrate Medium & Heavy Commercial Vehicle Engine Emission and Fuel Consumption Calibration

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant