CN109472062A - A kind of variable cycle engine self-adaptive component grade simulation model construction method - Google Patents
A kind of variable cycle engine self-adaptive component grade simulation model construction method Download PDFInfo
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Abstract
The invention discloses a kind of variable cycle engine self-adaptive component grade simulation model construction methods, on the basis of the non-linear components grade dynamic general model of the above state of variable cycle engine slow train, it proposes to use adaptive extended kalman filtering device, after estimating the immesurable performance characteristic parameter of variable cycle engine gas path component, the performance plots such as flow and the efficiency of gas path component are automatically updated using the characteristic parameter estimated, gas path component characterisitic parameter adjusted is used for the calculating of component aerothermo-parameters, establish the variable cycle engine self-adaptive component grade simulation model of the above state of slow train.Model mismatch caused by the present invention degrades to engine individual difference and performance has stronger adaptability, significantly improve the above state nonlinear individual model accuracy of variable cycle engine slow train, it reduces and manually adjusts engine air passage characteristics of components using experience, make the huge workload of Model Matching bring, the control and health control theory to variable cycle engine provide model basis.
Description
Technical field
The present invention relates to aeroengine modeling and emulation field more particularly to a kind of variable cycle engine self-adaptive components
Grade simulation model construction method.
Background technique
Variable cycle engine can change the heating power of engine because it is with adjustable geometry component under different flying conditions
Circulation, obtains optimal flying quality, double outer basic structures for containing variable cycle engines as shown in Figure 1, its mainly by two kinds of allusion quotations
The operating mode of type.
Single to contain mode: close pattern selector valve turns forward and backward adjustable culvert channel injector (Variable Area down
Bypass Injector, VABI) area, the air mass flow almost all for flowing through leading portion fan flows through core driving fan
And high-pressure compressor, only allow sub-fraction flow by the cooling jet pipe of by-pass air duct, engine specific thrust is maximum at this time, with
Meet aircraft take off, climb or when supersonic flight to thrust the needs of.
Double culvert modes: mode selector valve is opened, forward and backward adjustable culvert channel injector area, forefan air mass flow are tuned up
Increase, flows through air mass flow a part of CDFS (Core Drive Fan Stage, core driving fan grade) from CDFS duct
Main outer culvert is flowed into, another part flows into compressor, and engine bypass ratio is maximum at this time, oil consumption rate can be reduced, to be suitable for Asia
Sonic flight.
Variable cycle engine working environment is severe and increasingly complex compared to conventional engine structure, to its safety with
And reliability requirement is all very high, the research for variable cycle engine adaptive model modeling technique is an important topic.Become
Cycle engine adaptive model can reflect that the factors such as performance degeneration are to hair in the individual difference between engine and validity period
The influence of motivation performance is the basis realized engine self-adaptive adjustment control, guarantee engine work.It is recycled with time-varying
Engine control is also required to accurate engine mockup as precondition, for the engine control based on model with health control
System and diagnostic system for, it is contemplated that between engine there is individual difference, real engine part location tolerance and make
It is not able to satisfy online with the influence of factors such as degrade of the performance in the phase if corresponding airborne model is not subject to adjustment appropriate
Under the required precision of performance seeking control or fault diagnosis, designed control and diagnostic system performance occur in various degree
Drop, is unable to reach the working condition of design.The operating mode that there is variable cycle engine adjustable geometry component engine can be changed,
Engine structure is increasingly complex, and working condition is badly changeable, and to variable cycle engine model, more stringent requirements are proposed, so building
Accurate variable cycle engine adaptive model is found with important theory significance and engineering practical value.
Currently, there are two types of the mainstream simulation models of variable cycle engine: non-linear components grade model and linear model.Start
Machine linear model is to carry out local linearization to model on the basis of engine non-linear components grade model, establishes state change
Model and stable state basic point model are measured, realizes the estimation of component performance parameter and adaptive using linear kalman filter.Linearly
Model calculation amount is smaller, to low in resources consumption, but this method is inevitably introduced when linearizing to nonlinear model
Two modelings error, and linear model is lower for the fitting precision of engine dynamic process.Engine non-linear components grade mould
Type modeling method mainly has rotor dynamics method and volume dynamics method.Relative to engine linear model, non-linear components grade
Model will not introduce two modelings error, tracking accuracy with higher for the dynamic process of engine, can accurate mould
The different operating conditions of variable cycle engine in quasi- envelope curve.With the development of filtering estimation technique, some non-linear Kalman filtering devices
It may be directly applied to nonlinear system, realize accurate state estimation.The present invention is by variable cycle engine non-linear
Part grade universal model proposes a kind of variable cycle engine self-adaptation nonlinear component in conjunction with adaptive extended kalman filtering device
Grade simulation model, degrading to gas path component performance has real-time estimation ability, while model following precision with higher.
Summary of the invention
The technical problem to be solved by the present invention is to be directed to the defect of background technique, higher individual can be had by providing one kind
Model accuracy, and caused model mismatch is degraded with stronger adaptability to engine individual difference and performance, it significantly improves
The above state individual model accuracy of variable cycle engine slow train reduces and manually adjusts engine air passage characteristics of components using experience,
Make a kind of variable cycle engine self-adaptive component grade simulation model construction method of the huge workload of Model Matching bring.
The present invention uses following technical scheme to solve above-mentioned technical problem:
Step A), establish the non-linear components grade dynamic general model of the above state of variable cycle engine slow train；
Step B), adaptive extended kalman filtering device is designed, estimates variable cycle engine fan, CDFS, compressor, height
Press the immesurable performance characteristic parameters of gas path components such as turbine, low-pressure turbine；
Step C), the performance plots such as flow and the efficiency of gas path component are automatically updated using the performance characteristic parameter estimated,
Gas path component characterisitic parameter adjusted is used for the calculating of component aerothermo-parameters, establishes the adaptive of the above state of slow train
Simulation model.
As a kind of further optimization of variable cycle engine self-adaptive component grade simulation model construction method of the present invention
Scheme, step A) specific step is as follows:
Step A1), it is built according to each component aerothermodynamics characteristic of variable cycle engine, design point parameter and firing test data
The mathematical model of each component of variable cycle engine of the vertical above state of slow train, according to flow continuous, static balance, power-balance and
The principles such as rotor dynamics establish the co-operation equation between each component, are finally asked using Nonlinear-Equations Numerical Solution method iteration
Solution obtains the parameter of each working sections of engine, and the variable cycle engine non-linear components grade for establishing the above state of slow train is dynamic
State universal model；
Step A2), according to engineering reality, selection needs the sensor of engine mockup working sections to be used to measure ginseng
Number.
As a kind of further optimization of variable cycle engine self-adaptive component grade simulation model construction method of the present invention
Scheme, step B) specific step is as follows:
Step B1), model is calculated into resulting each section temperature pressure sensor data and is normalized；
Step B2), variable cycle engine fan, CDFS, compressor, height are estimated using adaptive extended kalman filtering device
The immesurable performance characteristic parameters of gas path components such as turbine, low-pressure turbine are pressed, the tool of the performance difference of model and engine is obtained
Body numerical value；
As a kind of further optimization of variable cycle engine self-adaptive component grade simulation model construction method of the present invention
Scheme, step is B.2) specific step is as follows:
Step B2.1), initialize the posterior estimate of performance characteristic parameter vector, posterior variance matrix and for adaptive
The sliding window (length M) of calculating.
Step B2.2), the property at this moment is generated according to the performance characteristic parameter Posterior estimator and posterior variance of last moment
Can characteristic parameter, call non-linear components grade dynamic general model solution Jacobian matrix, and to each performance characteristic parameter into
The row time updates, the prior estimate and prior variance of calculated performance characteristic parameter.
Step B2.3), according to the prior estimate of performance characteristic parameter and prior variance, call non-linear components grade dynamic general
Model simultaneously carries out measurement update to Kalman filter, obtains kalman gain matrix according to Jacobian matrix and prior variance.
Measurement residuals weighted sum between the prior estimate of performance characteristic parameter and engine and model can obtain the performance characteristic at this moment
The Posterior estimator of parameter can calculate posterior variance matrix according to Kalman filtering gain, Jacobian matrix and prior variance.
Step B2.4), extended Kalman filter adaptive polo placement, when performance mutation occurs, using Generalized Likelihood Ratio
The approximate mutation value for calculating performance characteristic parameter and covariance matrix, to performance characteristic on the basis of Kalman filtered results
Parameter is modified, and improves response speed of the extended Kalman filter when performance is mutated.
Step B2.5), the later moment repeats step B2.2) to step B2.4) complete performance characteristic parameter recursion
Estimation.
As a kind of further optimization of variable cycle engine self-adaptive component grade simulation model construction method of the present invention
Scheme, step C) specific step is as follows:
Step C1), by the resulting gas circuit performance characteristic parameter comprising coefficients such as efficiency, flows, it is input to engine portion
In the corresponding component of part grade model, flow, the efficiency characteristic figure of gas path component are updated.Under same equivalent revolving speed, keep each
The pressure ratio coordinate values of rotor part performance plot curve are constant, by efficiency in performance plot, flow numerical value along change in coordinate axis direction into
Row scaling amendment.
For fan, CDFS, compressor part, in pressure ratio-flow diagram, characteristic curve zooms in and out along the x-axis direction, scaling
Ratio is the flow performance characteristic parameter of corresponding fan, CDFS, compressor；In efficiency-flow diagram, characteristic curve is along x first
Axis direction zooms in and out, and zoom ratio is the flow performance characteristic parameter of corresponding fan, CDFS, compressor, and then curve is along y
Axis direction zooms in and out, and zoom ratio is the efficiency performance characteristic parameter of corresponding fan, CDFS, compressor.
For high and low pressure turbine part, in efficiency-flow diagram, characteristic curve zooms in and out along the x-axis direction first, scaling
Ratio is the flow performance characteristic parameter of corresponding high and low pressure turbine, and then characteristic curve zooms in and out along the y-axis direction, scaling
Ratio is the efficiency performance characteristic parameter of corresponding high and low pressure turbine；In flow-pressure ratio figure, characteristic curve carries out along the y-axis direction
Scaling, zoom ratio are the flow performance characteristic parameter of corresponding high and low pressure turbine.
Step C2), gas path component characterisitic parameter adjusted is used for the calculating of component aerothermo-parameters, carries out component
The calculating of performance plot each cross section parameter of non-linear components grade model adjusted, establishes the variable cycle engine of the above state of slow train
Self-adaptive component grade simulation model.
The invention adopts the above technical scheme compared with prior art, has following technical effect that
(1) a kind of variable cycle engine self-adaptive component grade simulation model construction method proposed by the present invention, use are non-thread
Property component-level universal model construction self-adapting simulation model will not be because of model compared to traditional adaptive line model
Linearization procedure and introduce two modelings error, it is high to the output tracking accuracy of real engine dynamic process, can satisfy change
The demand of model accuracy in cycle engine envelope curve；
(2) a kind of variable cycle engine self-adaptive component grade simulation model construction method proposed by the present invention, to engine
Model mismatch caused by individual difference and performance are degraded has stronger adaptability, and when performance mutation occurs, response is very fast, energy
Significantly improve the above state nonlinear component stage motor individual model accuracy of slow train；
(3) the variable cycle engine self-adaptive component grade simulation model that the present invention designs is reduced manual currently with experience
Engine air passage characteristics of components is adjusted, makes the huge workload of Model Matching bring, while variable cycle engine gas circuit can be obtained
The situation of change of component capabilities feature provides performance reference frame for variable cycle engine condition maintenarnce.
Detailed description of the invention
Fig. 1 is double outer culvert variable cycle engine structure charts；
Fig. 2 is variable cycle engine self-adaptive component grade simulation model schematic diagram；
Fig. 3 adaptive extended kalman filtering device calculation flow chart；
Fig. 4 is the gas circuit performance estimation and change circulation hair for the design point Imitating Capability of Compressor variation that mode is singly contained on ground
The tracking effect figure of motivation self-adaptive component grade simulation model, and the amendment of compressor part normalization performance plot；
The gas circuit performance estimation and variable cycle engine that Fig. 5 is the double culvert mode Imitating low-pressure turbine performance changes in ground are certainly
Adapt to the amendment of the tracking effect figure and low-pressure turbine component normalization performance plot of component-level simulation model；
Fig. 6 is variable cycle engine model and variable cycle engine self-adaptive component in the double culvert mode dynamic processes in ground
Grade simulation model main chamber fuel oil variation；
Fig. 7 is the gas circuit of variable cycle engine self-adaptive component grade simulation model in the double culvert mode dynamic processes in ground
The tracking effect figure of energy estimated result and model output；
Fig. 8 is that high-altitude is singly contained in mode dynamic process in envelope curve, and variable cycle engine model and variable cycle engine are adaptive
Component-level simulation model main chamber fuel oil is answered to change；
Fig. 9 is that high-altitude is singly contained in dynamic process in envelope curve, the gas circuit of variable cycle engine self-adaptive component grade simulation model
The tracking effect figure of performance estimation results and model output；
Specific embodiment
Thinking of the invention is for multivariable Control of the advanced aero engine based on model and prediction health control
Demand is extended and designs and develops to existing aero-engine simulation model, establishes the above state self-adaption component-level of slow train
Simulation model can be reduced model error caused by engine individual difference and performance degeneration, guarantee the essence of engine body Model
Degree has high confidence.
A specific embodiment of the invention is constructed with the double outer variable cycle engine self-adaptive component grade simulation models of containing of certain type
For, Fig. 1 is variable cycle engine self-adaptive component grade simulation model schematic diagram, and the foundation of the simulation model includes following step
It is rapid:
Step A), establish the non-linear components grade dynamic general model of the above state of variable cycle engine slow train；
Step B), adaptive extended kalman filtering device is designed, estimates variable cycle engine fan, CDFS, compressor, height
Press the immesurable performance characteristic parameters of gas path components such as turbine, low-pressure turbine；
Step C), the performance plots such as flow and the efficiency of gas path component are automatically updated using the performance characteristic parameter estimated,
Gas path component characterisitic parameter adjusted is used for the calculating of component aerothermo-parameters, establishes the adaptive of the above state of slow train
Simulation model.
Wherein step A) detailed step it is as follows:
Step A1), the above shape of slow train is established according to variable cycle engine characteristics of components, design point parameter and firing test data
The mathematical model of each component of the variable cycle engine of state, the h type engine h main component include air intake duct, fan, CDFS, calm the anger
Machine, combustion chamber, high-pressure turbine, low-pressure turbine, by-pass air duct, mixing chamber and jet pipe etc., continuous, static balance, function further according to flow
The principles such as rate balance and rotor dynamics establish the co-operation equation between each component, finally use Nonlinear-Equations Numerical Solution
Method iterative solution, obtains the parameter of each working sections of engine.The component characteristic models comparative maturity in the industry, is not added herein in detail
It states.Engine components grade universal model is the averaging model obtained according to characteristics of components and firing test data etc., cannot be more accurate
Reflect the output of homotype Different Individual engine, while with the increase of engine active time, the performance of gas path component also can
Different degrees of degeneration occurs, therefore, it is poor to characterize engine individual performance to introduce engine air passage component capabilities characteristic parameter
Different or use time bring performance is degraded, and gas path component performance characteristic parameter chooses the efficiency factor SE of rotary partiWith
Discharge coefficient SWi, it is defined as follows
In formula: ηi,wiFor the actual efficiency and flow of component, andFor the ideal value of component efficiencies and flow.This hair
The engine of bright use-case altogether there are five rotary part, therefore gas path component performance characteristic parameter be selected as fan, CDFS, compressor and
The efficiency and discharge coefficient of high and low pressure turbine, are defined as totally by ten
H=[SE1,SW1,SE2,SW2,SE3,SW3,SE4,SW4,SE5,SW5]T。
Step A2), the above state self-adaption component-level simulation model of bicycle and motorcycle is started in consideration is joined using engine measuring
The residual error between model output is counted to realize the amendment of engine, therefore needs Rational choice engine mockup output parameter.
The selected engine mockup sensor includes: rotation speed of the fan NL, CDFS and rotating speed of gas compressor NH, fan outlet total temperature T21,
Fan outlet stagnation pressure P21, CDFS export total temperature T24, the outlet CDFS stagnation pressure P24, blower outlet total temperature T3, and blower outlet is total
P3 is pressed, high-pressure turbine exports total temperature T43, and high-pressure turbine exports stagnation pressure P43, low-pressure turbine exit total temperature T6, low-pressure turbine exit
Stagnation pressure P5.
Step B) detailed step it is as follows:
Step B1), different measurement parameters have different physical significances, and the mutual order of magnitude differs greatly, this will band
The problem of calculating and data for carrying out matrix store.Therefore output parameter is done into normalized.
Parameter normalization process is as follows:
In formula, subscript indicates variable cycle engine design point parameter containing d.
Step B2), it is assumed that variable cycle engine component-level nonlinear mathematical model is as follows:
K is time parameter, ω in formulakAnd νkThe respectively independent system noise of system and measurement noise, and meet ωk~N
(0,Q2), vk~N (0, R2), Q, R are respectively the covariance matrix of noise, choose Q=0.0003 × I12×12, R=0.0015 ×
I12×12。xkRepresent the quantity of state of system, ukFor the input quantity of system, ykFor the sensor measuring value of system, I is unit matrix.
The performance characteristic parameter of gas path component is filtered estimation usually as a part of engine condition amount, and each variables choice is
xk=[PNL,PNH,hT]T, uk=[PWf PA8 PA224 PA163]T,
Y=[PNL,PNH,PT21,PP21,PT24,PP24,PT3,PP3, PP43,PT43,PT6,PP5]T。zkFor flight condition parameter
Vector includes flying height H, Mach number Ma and inlet temperature T1 etc..Wherein, WfFor main chamber fuel flow, A8For jet pipe
Throatpiston product, A224、A163Respectively forward and backward adjustable culvert channel injector area.
Step is B.2.1), the posterior estimate of init state amountPosterior variance matrix P0|0Be used for adaptometer
The sliding window (length M) of calculation.
Step is B.2.2), the property at this moment is generated according to the performance characteristic parameter Posterior estimator and posterior variance of last moment
Energy characteristic parameter, calls non-linear components grade dynamic general model solution Jacobian matrix simultaneously to carry out to each performance characteristic parameter
Time updates, the prior estimate and prior variance of calculated performance characteristic parameter, calculation formula are as follows:
In formula, Jacobian matrix
Step B2.3), according to the prior estimate of performance characteristic parameter and prior variance, call non-linear components grade dynamic general
Model simultaneously carries out measurement update to Kalman filter, obtains kalman gain matrix according to Jacobian matrix and prior variance.
Measurement residuals weighted sum between the prior estimate of performance characteristic parameter and engine and model can obtain the performance characteristic at this moment
The Posterior estimator of parameter can calculate posterior variance matrix according to Kalman filtering gain, Jacobian matrix and prior variance.
Calculation formula are as follows:
In formula, Jacobian matrix
Step B2.4), the time index that τ is sliding window is defined, karr is extended using the method for Generalized Likelihood Ratio
Graceful filter adaptive polo placement.When performance mutation occurs, the approximate mutation of performance characteristic parameter and covariance matrix is calculated
Value, is modified performance characteristic parameter on the basis of Kalman filtered results, improves Kalman filter and is mutated in performance
When response speed, calculating process is as follows:
For the newest element (τ=k) in sliding window, the formula of calculating are as follows:
For the stored parameter of sliding window (k-M < τ≤k), the formula of calculating is updated are as follows:
Wherein, H, F, J, d are the intermediate variable calculated.
Calculate log-likelihood ratio lk|τ, the formula of calculating are as follows:
It finds outWith For lk|ττ corresponding value when obtaining maximum value, and lk|τMaximum value be expressed as
IfThen performance mutates, and carries out adaptive correction to performance characteristic parameter, η is the critical valve of setting
Value.Calculation formula is as follows:
IfThen performance does not mutate, calculates as follows:
The chi square distribution for obeying n dimension of critical threshold η, calculates as follows:
Wherein, PFFor misinformation probability, H0Indicate that performance does not occur by the end of current time is mutated, and p (l=L | H0) indicate
H0Under the conditions of lk|τObedience chi square distribution probability density, L is integration variable.
Step B2.5), the later moment repeats step B2.2) to step B2.4) complete performance characteristic parameter recursion
Estimation.
Step C) detailed step it is as follows:
By the efficiency of each rotor part, discharge coefficient in resulting performance characteristic parameter, it is input to engine components grade mould
In the corresponding component of type, the performance plots such as flow and the efficiency of gas path component are updated.
Using the efficiency of each rotor part, discharge coefficient in the performance characteristic parameter estimated as each gas path component performance plot
The zoom factor of middle efficiency, flow number zooms in and out amendment to the characteristics of components figure of original universal model.Specific calculating process
It is as follows:
In formula, SE 'i,SWi' it is the efficiency of each rotor part, discharge coefficient, η ' in the performance characteristic parameter estimatedi,
w′iFor the efficiency adjusted and flow of component.Under same equivalent revolving speed, the pressure of each rotor part performance plot curve is kept
It is more constant than coordinate values, efficiency, flow coordinate values in performance plot are zoomed in and out into amendment along change in coordinate axis direction.
For fan, CDFS, compressor part, in pressure ratio-flow diagram, characteristic curve zooms in and out along the x-axis direction, scaling
Ratio is the flow performance characteristic parameter SW of corresponding fan, CDFS, compressor1′,SW2', SW3′；It is first in efficiency-flow diagram
First characteristic curve zooms in and out along the x-axis direction, and zoom ratio is the flow performance feature ginseng of corresponding fan, CDFS, compressor
Number SW1′,SW2', SW3', then curve zooms in and out along the y-axis direction, and zoom ratio is corresponding fan, CDFS, compressor
Efficiency performance characteristic parameter SE '1,SE′2,SE′3。
For high and low pressure turbine part, in efficiency-flow diagram, characteristic curve zooms in and out along the x-axis direction first, scaling
Ratio is the flow performance characteristic parameter SW of corresponding high and low pressure turbine4′,SW5', then characteristic curve contracts along the y-axis direction
It puts, zoom ratio is the efficiency performance characteristic parameter SE ' of corresponding high and low pressure turbine4,SE′5.In flow-pressure ratio figure, characteristic is bent
Line zooms in and out along the y-axis direction, and zoom ratio is the flow performance characteristic parameter SW of corresponding high and low pressure turbine4′,SW5′。
Gas path component characterisitic parameter adjusted is used for the calculating of component aerothermo-parameters, carries out characteristics of components figure tune
The self-adaptive component grade simulation model of the above state of slow train is established in the calculating of non-linear components grade model after whole.
In order to verify a kind of variable cycle engine self-adaptive component grade simulation model construction method designed by the present invention
Validity has carried out following Digital Simulation under MATLAB environment.
I.e. mode H=0m, Ma=0, PW are singly contained in ground at variable cycle engine design pointf=1.000, PA8=1.000,
PA224=1.000, PA163=1.000, sliding window length is M=5, PFValue is 10-5And η=45.08.Fig. 4 (a), (b),
(c) simulation is given in 12.5s when compressor efficiency decline 2%, flow decline 1%, variable cycle engine self-adaptive component
The output parameter tracking result of grade simulation model and the estimated result of characteristics of components corrected parameter (as space is limited, only give height
The tracking result of rotational speed of lower pressure turbine rotor), variable cycle engine self-adaptive component grade simulation model can be good at starting in tracking
The output of machine body Model.Fig. 4 (d) (e) gives under this performance change, the amendment signal of compressor part characterisitic parameter
Figure is (with SE '3=0.98, SW '3For=0.99).Under same equivalent revolving speed, each rotor part performance plot curve is kept
Pressure ratio coordinate values are constant, and efficiency, flow number in performance plot are zoomed in and out amendment along change in coordinate axis direction.In the effect of component
In rate-flow diagram, it is 0.99 that x-axis direction, which scales ratio, and it is 0.98 that y-axis direction, which scales ratio,.In pressure ratio-flow diagram of component
In, performance plot curve carries out the scaling variation in x-axis direction, and scaling ratio is 0.99.
In the double culvert mode H=0m, Ma=0, PW in variable cycle engine groundf=0.652, PA8=1.033, PA224=
0.667, PA163=2.941, sliding window length is M=5, PFValue is 10-5And η=45.08, simulation low pressure in 12.5s
Turbine performance variation (efficiency decline 2%, flow rise 1%) when, variable cycle engine self-adaptive component grade simulation model it is defeated
The estimated result of parameter tracking result and characteristics of components corrected parameter such as Fig. 5 (a) out, (b), (c) shown, variable cycle engine is certainly
Adapting to component-level simulation model can be good at tracking the output of engine body Model.Fig. 5 (d) (e) gives in this property
Under capable of changing, the amendment schematic diagram of compressor part characterisitic parameter is (with SE '3=0.98, SW '3For=1.01).Same
Under equivalent revolving speed, keep the pressure ratio coordinate values of each rotor part performance plot curve constant, by efficiency, flow number in performance plot
Amendment is zoomed in and out along change in coordinate axis direction.In efficiency-flow diagram of component, it is 1.01 that x-axis direction, which scales ratio, y-axis direction
Scaling ratio is 0.98.In flow-pressure ratio figure of component, performance plot curve carries out the scaling variation on y-axis direction, pantograph ratio
Value is 1.01.
In order to verify variable cycle engine self-adaptive component grade simulation model to the tracking accuracy of engine dynamic process,
The double culvert states (H=0m, Ma=0) in ground do such as figure engine mockup and variable cycle engine self-adaptive component grade simulation model
W shown in 6fChange procedure, while the compressor efficiency decline 2% in 2.5s is simulated, HP&LP Rotor revolving speed and component are special
Property corrected parameter simulation result such as Fig. 7 (a)-(c) shown in, sliding window length be M=5, PFValue is 10-5And η=
45.08.Simulation result shows that in simulating the dynamic process, variable cycle engine self-adaptive component grade simulation model can be very
The output of engine mockup in good tracking, model worst error are no more than 0.2%.In order to verify different operating point in envelope curve
Model following precision, in high dummy status (H=11km, Ma=1.5) to engine mockup and variable cycle engine self-adaptive component
Grade simulation model is W as shown in Figure 8fChange procedure, while simulating identical performance change situation, HP&LP Rotor revolving speed and
Shown in the simulation result of characteristics of components corrected parameter such as Fig. 9 (a)-(c).Simulation result shows in simulating the dynamic process, becomes
Cycle engine self-adaptive component grade simulation model can be good at tracking the output of engine mockup, and model worst error is not
More than 0.2%.It can be seen that in the dynamic process of different flight state, variable cycle engine self-adaptive component grade simulation model
Characteristics of components parameter can accurately be estimated, the output of model precision with higher is made.
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, several improvement can also be made without departing from the principle of the present invention, these improvement also should be regarded as of the invention
Protection scope.
Claims (5)
1. a kind of variable cycle engine self-adaptive component grade simulation model construction method, which comprises the following steps:
Step A), establish the non-linear components grade dynamic general model of the above state of variable cycle engine slow train；
Step B), adaptive extended kalman filtering device is designed, estimates variable cycle engine fan, CDFS, compressor, high pressure whirlpool
The immesurable performance characteristic parameter of the gas path components such as wheel, low-pressure turbine；
Step C), the performance plots such as flow and the efficiency of gas path component are automatically updated using the performance characteristic parameter estimated, will be adjusted
Gas path component performance characteristic parameter after whole is calculated for component aerothermo-parameters, establishes the adaptive imitative of the above state of slow train
True mode.
2. a kind of change as described in claim 1 recycles motivation self-adaptive component grade simulation model construction method, which is characterized in that
The step A) specific step is as follows:
Step A1), it is established according to each component aerothermodynamics characteristic of variable cycle engine, design point parameter and firing test data slow
The mathematical model of each component of variable cycle engine of the above state of vehicle, continuous, static balance, power-balance and rotor according to flow
The principles such as dynamics establish the co-operation equation between each component, are finally iteratively solved using Nonlinear-Equations Numerical Solution method,
The parameter for obtaining each working sections of variable cycle engine, establishes the variable cycle engine non-linear components grade of the above state of slow train
Dynamic general model；
Step A2), according to engineering reality, selection can develop the sensor measurement parameters of each working sections of engine used.
3. a kind of variable cycle engine self-adaptive component grade simulation model construction method as described in claim 1, feature exist
In the step B), specific step is as follows:
Step B1), model is calculated into resulting each section temperature pressure sensor data and is normalized；
Step B2), variable cycle engine fan, CDFS, compressor, high pressure whirlpool are estimated using adaptive extended kalman filtering device
The immesurable performance characteristic parameter of the gas path components such as wheel, low-pressure turbine obtains the specific number of the performance difference of model and engine
Value.
4. a kind of variable cycle engine self-adaptive component grade simulation model construction method as claimed in claim 3, feature exist
The detailed step of immesurable gas circuit performance characteristic parameter is calculated using adaptive extended kalman filtering device in step B2)
It is as follows:
Step B2.1), it initializes the posterior estimate of performance characteristic parameter vector, posterior variance matrix and is used for adaptometer
The sliding window of calculation；
Step B2.2), the performance at current time is generated according to the performance characteristic parameter Posterior estimator and posterior variance of last moment
Characteristic parameter, call non-linear components grade dynamic general model solution Jacobian matrix, and to each performance characteristic parameter carry out when
Between update, the prior estimate and prior variance of calculated performance characteristic parameter；
Step B2.3), according to the prior estimate of performance characteristic parameter and prior variance, call non-linear components grade dynamic general model
And measurement update is carried out to Kalman filter, kalman gain matrix is obtained according to Jacobian matrix and prior variance；Performance
Measurement residuals weighted sum between characteristic parameter prior estimate and engine/model can obtain the performance characteristic parameter at current time
Posterior estimator, according to Kalman filtering gain, Jacobian matrix and prior variance calculate posterior variance matrix；
Step B2.4), extended Kalman filter adaptive polo placement is calculated when performance mutation occurs using Generalized Likelihood Ratio
The approximate mutation value of performance characteristic parameter and covariance matrix out, to performance characteristic on the basis of Extended Kalman filter result
Parameter is modified, and improves response speed of the extended Kalman filter when performance is mutated；
Step B2.5), the later moment repeats step B2.2) to step B2.4) complete performance characteristic parameter recurrence estimation.
5. a kind of variable cycle engine self-adaptive component grade simulation model construction method as claimed in claim 3, feature exist
In step C), specific step is as follows:
Step C1), by the resulting gas path component performance characteristic parameter comprising coefficients such as efficiency, flows, it is input to engine portion
In the corresponding component of part grade universal model, flow, the efficiency characteristic figure of gas path component are updated；Under same equivalent revolving speed, protect
The pressure ratio coordinate values for holding gas circuit rotary part performance plot curve are constant, by efficiency in performance plot, flow numerical value along reference axis
Direction zooms in and out amendment；
For fan, CDFS, compressor part, in pressure ratio-flow diagram, characteristic curve zooms in and out along the x-axis direction, zoom ratio
For corresponding fan, CDFS, compressor flow performance characteristic parameter；In efficiency-flow diagram, characteristic curve is along x-axis side first
To zooming in and out, zoom ratio is the flow performance characteristic parameter of corresponding fan, CDFS, compressor, and then curve is along y-axis side
To zooming in and out, zoom ratio is the efficiency performance characteristic parameter of corresponding fan, CDFS, compressor；
For high and low pressure turbine part, in efficiency-flow diagram, characteristic curve zooms in and out along the x-axis direction first, zoom ratio
For the flow performance characteristic parameter of corresponding high and low pressure turbine, then characteristic curve zooms in and out along the y-axis direction, zoom ratio
For the efficiency performance characteristic parameter of corresponding high and low pressure turbine；In flow-pressure ratio figure, characteristic curve contracts along the y-axis direction
It puts, zoom ratio is the flow performance characteristic parameter of corresponding high and low pressure turbine；
Step C2), gas path component characterisitic parameter adjusted is used for the calculating of component aerothermo-parameters, carries out characteristics of components
Scheme the calculating of each cross section parameter of non-linear components grade model adjusted, the variable cycle engine for establishing the above state of slow train is adaptive
Answer component-level simulation model.
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